Patent Application
20220074941
The instant application contains a Sequence Listing which has been submitted electronically in ASCII format and is hereby incorporated by reference in its entirety. Said ASCII copy, created Apr. 22, 2021 is named 2003080-1845_SL.txt and is 5,493 bytes in size.
Throughout this application numerous public documents including issued and pending patent applications, publications, and the like are identified. These documents in their entireties are hereby incorporated by reference into this application to help define the state of the art as known to persons skilled therein.
There is a great need to understand the molecular aberrations that maintain the malignant phenotype of cancer cells. Such an understanding would enable more selective targeting of tumor-promoting molecules and aid in the development of more effective and less toxic anti-cancer treatments. Most cancers arise from multiple molecular lesions, and likely the resulting redundancy limits the activity of specific inhibitors of signaling molecules. While combined inhibition of active pathways promises a better clinical outcome, comprehensive identification of oncogenic pathways is currently beyond reach.
Application of genomics technologies, including large-scale genome sequencing, has led to the identification of many gene mutations in various cancers, emphasizing the complexity of this disease (Ley et al., 2008; Parsons et al., 2008). However, whereas these genetic analyses are useful in providing information on the genetic make-up of tumors, they intrinsically lack the ability to elucidate the functional complexity of signaling networks aberrantly activated as a consequence of the genetic defect(s). Development of complementary proteomic methodologies to identify molecular lesions intrinsic to tumors in a patient- and disease stage-specific manner must thus follow.
Most proteomic strategies are limited to measuring protein expression in a particular tumor, permitting the identification of new proteins associated with pathological states, but are unable to provide information on the functional significance of such findings (Hanash & Taguchi, 2010). Some functional information can be obtained using antibodies directed at specific proteins or post-translational modifications and by activity-based protein profiling using small molecules directed to the active site of certain enzymes (Kolch & Pitt, 2010; Nomura et al., 2010; Brehme et al., 2009; Ashman & Villar, 2009). Whereas these methods have proven useful to query a specific pathway or post-translational modification, they are not as well suited to capture more global information regarding the malignant state (Hanash & Taguchi, 2010). Moreover, current proteomic methodologies are costly and time consuming. For instance, proteomic assays often require expensive SILAC labeling or two-dimensional gel separation of samples.
Accordingly, there exists a need to develop simpler, more cost effective proteomic methodologies that capture important information regarding the malignant state. As it is recognized that the molecular chaperone protein heat shock protein (Hsp90) maintains many oncoproteins in a pseudo-stable state (Zuehlke & Johnson, 2010; Workman et al., 2007), Hsp90 may be an important protein in the development of new proteomic methods.
In support of this hypothesis, heat shock protein (Hsp90), a chaperone protein that functions to properly fold numerous proteins to their active conformation, is recognized to play important roles in maintaining the transformed phenotype (Zuehlke & Johnson, 2010; Workman et al., 2007). Hsp90 and its associated co-chaperones assist in the correct conformational folding of cellular proteins, collectively referred to as “client proteins”, many of which are effectors of signal transduction pathways controlling cell growth, differentiation, the DNA damage response, and cell survival. Tumor cell addiction to deregulated proteins (i.e. through mutations, aberrant expression, improper cellular translocation etc) can thus become critically dependent on Hsp90 (Workman et al., 2007). While Hsp90 is expressed in most cell types and tissues, work by Kamal et al demonstrated an important distinction between normal and cancer cell Hsp90 (Kamal et al, 2003). Specifically, they showed that tumors are characterized by a multi-chaperone complexed Hsp90 with high affinity for certain Hsp90 inhibitors, while normal tissues harbor a latent, uncomplexed Hsp90 with low affinity for these inhibitors.
Many of the client proteins of Hsp90 also play a prominent role in disease onset and progression in several pathologies, including cancer. (Whitesell and Lindquist, Nat Rev Cancer 2005, 5, 761; Workman et al., Ann NY Acad Sci 2007, 1113, 202; Luo et al., Mol Neurodegener 2010, 5, 24.) As a result there is also significant interest in the application of Hsp90 inhibitors in the treatment of cancer. (Taldone et al., Opin Pharmacol 2008, 8, 370; Janin, Drug Discov Today 2010, 15, 342.)
Based on the body of evidence set forth above, we hypothesize that proteomic approaches that can identify key oncoproteins associated with Hsp90 can provide global insights into the biology of individual tumor and can have widespread application towards the development of new cancer therapies. Accordingly, the present disclosure provides tools and methods for identifying oncoproteins that associate with Hsp90. Moreover, the present disclosure provides methods for identifying treatment regimens for cancer patient.
The present disclosure relates to the discovery that small molecules able to target tumor-enriched Hsp90 complexes (e.g., Hsp90 inhibitors) can be used to affinity-capture Hsp90-dependent oncogenic client proteins. The subsequent identification combined with bioinformatic analysis enables the creation of a detailed molecular map of transformation-specific lesions. This map can guide the development of combination therapies that are optimally effective for a specific patient. Such a molecular map has certain advantages over the more common genetic signature approach because most anti-cancer agents are small molecules that target proteins and not genes, and many small molecules targeting specific molecular alterations are currently in pharmaceutical development.
Accordingly, the present disclosure relates to Hsp90 inhibitor-based chemical biology/proteomics approach that is integrated with bioinformatic analyses to discover oncogenic proteins and pathways. We show that the method can provide a tumor-by-tumor global overview of the Hsp90-dependent proteome in malignant cells which comprises many key signaling networks and is considered to represent a significant fraction of the functional malignant proteome.
The disclosure provides small-molecule probes that can affinity-capture Hsp90-dependent oncogenic client proteins. Additionally, the disclosure provides methods of harnessing the ability of the molecular probes to affinity-capture Hsp90-dependent oncogenic client proteins to design a proteomic approach that, when combined with bioinformatic pathway analysis, identifies dysregulated signaling networks and key oncoproteins in different types of cancer.
In one aspect, the disclosure provides small-molecule probes derived from Hsp90 inhibitors based on purine and purine-like (e.g., PU-H71, MPC-3100, Debio 0932), isooxazole (e.g., NVP-AUY922) and indazol-4-one (e.g., SNX-2112) chemical classes (see
In another aspect, the disclosure provides methods of identifying specific oncoproteins associated with Hsp90 that are implicated in the development and progression of a cancer. Such methods involve contacting a sample containing cancer cells from a subject suffering from cancer with an inhibitor of Hsp90, and detecting the oncoproteins that are bound to the inhibitor of Hsp90. In particular embodiments, the inhibitor of Hsp90 is linked to a solid support, such as a bead. In these embodiments, oncoproteins that are harbored by the Hsp90 protein bound to the solid support can be eluted in a buffer and submitted to standard SDS-PAGE, and the eluted proteins can be separated and analyzed by traditional means. In some embodiments of the method the detection of oncoproteins comprises the use of mass spectroscopy. Advantageously, the methods of the disclosure do not require expensive SILAC labeling or two-dimensional separation of samples.
In certain embodiments of the invention the analysis of the pathway components comprises use of a bioinformatics computer program, for example, to define components of a network of such components.
The methods of the disclosure can be used to determining oncoproteins associated with various types of cancer, including but not limited to a breast cancer, a lung cancer including a small cell lung cancer and a non-small cell lung cancer, a cervical cancer, a colon cancer, a choriocarcinoma, a bladder cancer, a cervical cancer, a basal cell carcinomachoriocarcinoma, a colon cancer, a colorectal cancer, an endometrial cancer esophageal cancer, a gastric cancer, a head and neck cancer, a acute lymphocytic cancer (ACL), a myelogenous leukemia including an acute myeloid leukemia (AML) and a chronic myeloid chronic myeloid leukemia (CML), a multiple myeloma, a T-cell leukemia lymphoma, a liver cancer, lymphomas including Hodgkin's disease, lymphocytic lymphomas neuroblastomas follicular lymphoma and a diffuse large B-cell lymphoma, an oral cancer, an ovarian cancer, a pancreatic cancer, a prostate cancer, a rectal cancer, sarcomas, skin cancers such as melanoma, a testicular cancer, a thyroid cancer, a renal cancer, myeloproliferative disorders, gastrointestinal cancers including gastrointestinal stromal tumors, an esophageal cancer, a stomach cancer, a gallbladder cancer, an anal cancer, brain tumors including gliomas, lymphomas including a follicular lymphoma and a diffuse large B-cell lymphoma. Additionally, the disclosure provides proteomic methods to identify dysregulated signaling networks associated with a particular cancer. In addition, the approach can be used to identify new oncoproteins and mechanisms.
In another aspect, the methods of the disclosure can be used to provide a rational basis for designing personalized therapy for cancer patients. A personalized therapeutic approach for cancer is based on the premise that individual cancer patients will have different factors that contribute to the development and progression of the disease. For instance, different oncogenic proteins and/or cancer-implicated pathways can be responsible for the onset and subsequent progression of the disease, even when considering patients with identical types at cancer and at identical stages of progression, as determined by currently available methods. Moreover, the oncoproteins and cancer-implicated pathways are often altered in an individual cancer patient as the disease progresses. Accordingly, a cancer treatment regimen should ideally be targeted to treat patients on an individualized basis. Therapeutic regimens determined from using such an individualized approach will allow for enhanced anti-tumor activity with less toxicity and with less chemotherapy or radiation.
Hence, in one aspect, the disclosure provides methods of identifying therapeutic regimens for cancer patients on an individualized basis. Such methods involve contacting a sample containing cancer cells from a subject suffering from cancer with an inhibitor of Hsp90, detecting the oncoproteins that are bound to the inhibitor of Hsp90, and selecting a cancer therapy that targets at least one of the oncoproteins bound to the inhibitor of Hsp90. In certain aspects, a combination of drugs can be selected following identification of oncoproteins bound to the Hsp90. The methods of the disclosure can be used to identify a treatment regimen for a variety of different cancers, including, but not limited to a breast cancer, a lung cancer, a brain cancer, a cervical cancer, a colon cancer, a choriocarcinoma, a bladder cancer, a cervical cancer, a choriocarcinoma, a colon cancer, an endometrial cancer an esophageal cancer, a gastric cancer, a head and neck cancer, an acute lymphocytic cancer (ACL), a myelogenous leukemia, a multiple myeloma, a T-cell leukemia lymphoma, a liver cancer, lymphomas including Hodgkin's disease and lymphocytic lymphomas neuroblastomas, an oral cancer, an ovarian cancer, a pancreatic cancer, a prostate cancer, a rectal cancer, sarcomas, a skin cancer, a testicular cancer, a thyroid cancer and a renal cancer.
In another aspect, the methods involve contacting a sample containing cancer cells from a subject suffering from cancer with an inhibitor of Hsp90, detecting the oncoproteins that are bound to the inhibitor of Hsp90, determining the protein network(s) associated with these oncoproteins and selecting a cancer therapy that targets at least one of the molecules from the networks of the oncoproteins bound to the inhibitor of Hsp90.
In certain aspects, a combination of drugs can be selected following identification of oncoproteins bound to the Hsp90. In other aspects, a combination of drugs can be selected following identification of networks associated with the oncoproteins bound to the Hsp90. The methods of the disclosure can be used to identify a treatment regimen for a variety of different cancers, including, but not limited to a breast cancer, a lung cancer, a brain cancer, a cervical cancer, a colon cancer, a choriocarcinoma, a bladder cancer, a cervical cancer, a choriocarcinoma, a colon cancer, an endometrial cancer an esophageal cancer, a gastric cancer, a head and neck cancer, an acute lymphocytic cancer (ACL), a myelogenous leukemia, a multiple myeloma, a T-cell leukemia lymphoma, a liver cancer, lymphomas including Hodgkin's disease and lymphocytic lymphomas neuroblastomas, an oral cancer, an ovarian cancer, a pancreatic cancer, a prostate cancer, a rectal cancer, sarcomas, a skin cancer, a testicular cancer, a thyroid cancer and a renal cancer.
In one embodiment of the present invention, after a personalized treatment regimen for a cancer patient is identified using the methods described above, the selected drugs or combination of drugs is administered to the patient. After a sufficient amount of time taking the selected drug or drug combination, another sample can be taken from the patient and the an assay of the present can be run again to determine if the oncogenic profile of the patient changed. If necessary, the dosage of the drug(s) can be changed or a new treatment regimen can be identified. Accordingly, the disclosure provides methods of monitoring the progress of a cancer patient over time and changing the treatment regimen as needed.
In another aspect, the methods of the disclosure can be used to provide a rational basis for designing personalized combinatorial therapy for cancer patients built around the Hsp90 inhibitors. Such therapeutic regimens may allow for enhanced anti-tumor activity with less toxicity and with less chemotherapy. Targeting Hsp90 and a complementary tumor-driving pathway may provide a better anti-tumor strategy since several lines of data suggest that the completeness with which an oncogcnic target is inhibited could be critical for therapeutic activity, while at the same time limiting the ability of the tumor to adapt and evolve drug resistance.
Accordingly this invention provides a method for selecting an inhibitor of a cancer-implicated pathway, or of a component of a cancer-implicated pathway, for coadministration with an inhibitor of Hsp90, to a subject suffering from a cancer which comprises the following steps:
In connection with the invention a cancer-implicated pathway is a pathway involved in metabolism, genetic information processing, environmental information processing, cellular processes, or organismal systems including any pathway listed in Table 1.
In the practice of this invention the cancer-implicated pathway or the component of the cancer-implicated pathway is involved with a cancer selected from the group consisting of colorectal cancer, pancreatic cancer, thyroid cancer, a leukemia including acute myeloid leukemia and chronic myeloid leukemia, basal cell carcinoma, melanoma, renal cell carcinoma, bladder cancer, prostate cancer, a lung cancer including small cell lung cancer and non-small cell lung cancer, breast cancer, neuroblastoma, myeloproliferative disorders, gastrointestinal cancers including gastrointestinal stromal tumors, esophageal cancer, stomach cancer, liver cancer, gallbladder cancer, anal cancer, brain tumors including gliomas, lymphomas including follicular lymphoma and diffuse large B-cell lymphoma, and gynecologic cancers including ovarian, cervical, and endometrial cancers. For example the component of the cancer-implicated pathway and/or the pathway may be any component identified in
In a preferred embodiment involving personalized medicine in step (a) the subject is the same subject to whom the inhibitor of the cancer-implicated pathway or the component of the cancer-implicated pathway is to be administered although the invention in step (a) also contemplates the subject is a cancer reference subject.
In the practice of this invention in step (a) the sample comprises any tumor tissue or any biological fluid, for example, blood.
Suitable samples for use in the invention include, but are not limited to, disrupted cancer cells, lysed cancer cells, and sonicated cancer cells.
In connection with the practice of the invention the inhibitor of Hsp90 to be administered to the subject may be the same as or different from the (a) inhibitor of Hsp90 used, or (b) the inhibitor of Hsp90, the analog, homolog or derivative of the inhibitor of Hsp90 used, in step (a).
In one embodiment, wherein the inhibitor of Hsp90 to be administered to the subject is PU-H71 or an analog, homolog or derivative of PU-H71 having the biological activity of PU-H71.
In another embodiment PU-H71 is the inhibitor of Hsp90 used, or is the inhibitor of Hsp90, the analog, homolog or derivative of which is used, in step (a). Alternatively, the inhibitor of Hsp90 may be selected from the group consisting of the compounds shown in
In one embodiment in step (a) the inhibitor of Hsp90 or the analog, homolog or derivative of the inhibitor of Hsp90 is preferred immobilized on a solid support, such as a bead.
In certain embodiments in step (b) the detection of pathway components comprises the use of mass spectroscopy, and in step (c) the analysis of the pathway components comprises use of a bioinformatics computer program.
In one example of the invention the cancer is a lymphoma, and in step (c) the pathway component identified is Syk. In another example, the cancer is a chronic myelogenous leukemia (CML) and in step (c) the pathway or the pathway component identified is a pathway or component shown in any of the Networks shown in
In the practice of this method the inhibitor of Hsp90 may be PU-H71 or an analog, homolog or derivative of PU-H71 although PU-H71 is currently a preferred inhibitor. In the practice of the invention, however the inhibitor of Hsp90 may be selected from the group consisting of the compounds shown in
In one desirable embodiment of the invention in (a) binding of the inhibitor of Hsp90 or the analog, homolog, or derivative of such Hsp90 inhibitor traps Hsp90 in a cancer pathway components-bound state.
This invention further provides a kit for carrying out the method which comprises an inhibitor of Hsp90 immobilized on a solid support such as a bead. Typically, such a kit will further comprise control beads, buffer solution, and instructions for use. This invention further provides an inhibitor of Hsp90 immobilized on a solid support wherein the inhibitor is useful in the method described herein. One example is where the inhibitor is PU-H71. In another aspect this invention provides a compound having the structure:
Still further the invention provides a method for selecting an inhibitor of a cancer-implicated pathway or a component of a cancer-implicated pathway which comprises identifying the cancer-implicated pathway or one or more components of such pathway according to the method described and then selecting an inhibitor of such pathway or such component. In addition, the invention provides a method of treating a subject comprising selecting an inhibitor according to the method described and administering the inhibitor to the subject alone or in addition to administering the inhibitor of the pathway component. More typically said administering will be effected repeatedly. Still further the methods described for identifying pathway components or selecting inhibitors may be performed at least twice for the same subject. In yet another embodiment this invention provides a method for monitoring the efficacy of treatment of a cancer with an Hsp90 inhibitor which comprises measuring changes in a biomarker which is a component of a pathway implicated in such cancer. For example, the biomarker used may be a component identified by the method described herein. In addition, this invention provides a method for monitoring the efficacy of a treatment of a cancer with both an Hsp90 inhibitor and a second inhibitor of a component of the pathway implicated in such cancer which Hsp90 inhibits which comprises monitoring changes in a biomarker which is a component of such pathway. For example, the biomarker used may be the component of the pathway being inhibited by the second inhibitor. Finally, this invention provides a method for identifying a new target for therapy of a cancer which comprises identifying a component of a pathway implicated in such cancer by the method described herein, wherein the component so identified has not previously been implicated in such cancer.
A primer that amplifies an intergenic region was used as negative control. Results are expressed as percentage of the input for the specific antibody (STAT5 or Hsp90) over the respective IgG control. (g) The transcript abundance of CCND2 and AfYC was measured by QPCR in K562 cells exposed to 1 μM of PU-H71. Results are expressed as fold change compared to baseline (time 0 h) and were normalized to RPL13A. HPRT was used as negative control. Experiments were carried out in biological quintuplicates with experimental duplicates. Data are presented as means±SEM. (h) Proposed mechanism for and Hsp90-facilitated increased STAT5 signaling in CML. Hsp90 binds to and influences the conformation of STAT5 and maintains STAT5 in an active conformation directly within STATS-containing transcriptional complexes.
Gene expression, cell cycle and cellular assembly Individual proteins are displayed as nodes, utilizing gray to represent that the protein was identified in this study. Proteins identified by IPA only are represented as white nodes. Different shapes are used to represent the functional class of the gene product. Proteins are depicted in networks as two circles when the entity is part of a complex; as a single circle when only one unit is present; a triangle pointing up or down to describe a phosphatase or a kinase, respectively; by a horizontal oval to describe a transcription factor; and by circle to depict “other” functions. The edges describe the nature of the relationship between the nodes: an edge with arrow-head means that protein A acts on protein B, whereas an edge without an arrow-head represents binding only between two proteins. Direct interactions appear in the network diagram as a solid line, whereas indirect interactions as a dashed line. In some cases a relationship may exist as a circular arrow or line originating from one molecule and pointing back at that same molecule. Such relationships are termed “self-referential” and arise from the ability of a molecule to act upon itself.
Quantitative analysis of synergy between mTOR and Hsp90 inhibitors: To determine the drug interaction between pp242 (mTOR inhibitor) and PU-H71 (Hsp90 inhibitor), the combination index (CI) isobologram method of Chou-Talalay was used as previously described. This method, based on the median-effect principle of the law of mass action, quantifies synergism or antagonism for two or more drug combinations, regardless of the mechanisms of each drug, by computerized simulation. Based on algorithms, the computer software displays median-effect plots, combination index plots and normalized isobolograms (where non constant ratio combinations of 2 drugs are used). PU-H71 (0.5, 0.25, 0.125, 0.0625, 0.03125, 0.0125 μM) and pp242 (0.5, 0.125, 0.03125, 0.0008, 0.002, 0.001 μM) were used as single agents in the concentrations mentioned or combined in a non constant ratio (PU-H71:pp242; 1:1, 1:2, 1:4, 1:7.8, 1:15.6, 1:12.5). The Fa (fraction killed cells) was calculated using the formulae Fa=1−Fu; Fu is the fraction of unaffected cells and was used for a dose effect analysis using the computer software (CompuSyn, Paramus, N.J., USA).
9-(2-Bromoethyl)-8-(6-(dimethylamino)benzo[d][1,3]dioxol-5-ylthio)-9H-purin-6-amine (2a). 1a (29 mg, 0.0878 mmol), Cs2CO3 (42.9 mg, 0.1317 mmol), 1,2-dibromoethane (82.5 mg, 37.8 μL, 0.439 mmol) in DMF (0.6 mL) was stirred for 1.5 h at rt. Then additional Cs2CO3 (14 mg, 0.043 mmol) was added and the mixture stirred for an additional 20 min. The mixture was dried under reduced pressure and the residue purified by preparatory TLC (CH2Cb:MeOH:AcOH, 15:1:0.5) to give 2a (24 mg, 63%). 1H NMR (500 MHz, CDCh/MeOH-d4) 8 8.24 (s, 1H), 6.81 (s, 1H), 6.68 (s, 1H), 5.96 (s, 2H), 4.62 (t, J=6.9 Hz, 2H), 3.68 (t, J=6.9 Hz, 2H), 2.70 (s, 6H); MS (ESI) m/z 437.2/439.1 [M+H]+.
tert-Butyl (6-((2-(6-amino-8-((6-(dimethylamino)benzo[1,3]dioxol-5-yl)thio)-9H-purin-9-yl)ethyl)amino)hexyl)carbamate (3a). 2a (0.185 g, 0.423 mmol) and text-butyl 6-aminohexylcarbamate (0.915 g, 4.23 mmol) in DMF (7 mL) was stirred at rt for 24 h. The reaction mixture was concentrated and the residue chromatographed [CHCl3:MeOH:MeOH—NH3 (7N), 100:7:3] to give 0.206 g (85%) of 3a; MS (ESI) m/z 573.3 [M+H]+.
(4a). 3a (0.258 g, 0.45 mmol) was dissolved in 15 mL of CH2Cl2:TFA (4:1) and the solution was stirred at rt for 45 min. Solvent was removed under reduced pressure and the residue dried under high vacuum overnight. This was dissolved in DMF (12 mL) and added to 25 mL of Affi-Gel 10 beads (prewashed, 3×50 mL DMF) in a solid phase peptide synthesis vessel. 225 μL of N,N-diisopropylethylamine and several crystals of DMAP were added and this was shaken at rt for 2.5 h. Then 2-methoxyethylamine (0.085 g, 97 μl, 1.13 mmol) was added and shaking was continued for 30 minutes. Then the solvent was removed and the beads washed for 10 minutes each time with CH2Cl2:Et3N (9:1, 4×50 mL), DMF (3×50 mL), Felts buffer (3×50 mL) and i-PrOH (3×50 mL). The beads 4a were stored in i-PrOH (beads: i-PrOH (1:2), v/v) at −80° C.
9-(3-Bromopropyl)-8-(6-(dimethylamino)benzo[d][1,3]dioxol-5-ylthio)-9H-purin-6-amine (2b). 1a (60 mg, 0.1818 mmol), Cs2CO3 (88.8 mg, 0.2727 mmol), 1,3-dibromopropane (184 mg, 93 μL, 0.909 mmol) in DMF (2 mL) was stirred for 40 min. at rt. The mixture was dried under reduced pressure and the residue purified by preparatory TLC (CH2Cl2:MeOH:AcOH, 15:1:0.5) to give 2b (60 mg, 73%). 1H NMR (500 MHz, CDCl3) δ 8.26 (s, 1H), 6.84 (br s, 2H), 6.77 (s, 1H), 6.50 (s, 1H), 5.92 (s, 2H), 4.35 (t, J=7.0 Hz, 2H), 3.37 (t, J=6.6 Hz, 2H), 2.68 (s, 6H), 2.34 (m, 2H); MS (ESI) m/z 451.1/453.1 [M+H]+.
tert-Butyl (6-((3-(6-amino-8-((6-(dimethylamino)benzo[d][1,3]dioxol-5-yl)thio)-9H-purin-9-yl)propyl)amino)hexyl)carbamate (3b). 2b (0.190 g, 0.423 mmol) and tert-butyl 6-aminohexylcarbamate (0.915 g, 4.23 mmol) in DMF (7 mL) was stirred at rt for 24 h. The reaction mixture was concentrated and the residue chromatographed [CHCl3:MeOH:MeOH—NH3 (7N), 100:7:3] to give 0.218 g (88%) of 3b; MS (ESI) m/z 587.3 [M+H]+.
(4b). 3b (0.264 g, 0.45 mmol) was dissolved in 15 mL of CH2Cl2:TFA (4:1) and the solution was stirred at rt for 45 min. Solvent was removed under reduced pressure and the residue dried under high vacuum overnight. This was dissolved in DMF (12 mL) and added to 25 mL of Affi-Gel 10 beads (prewashed, 3×50 mL DMF) in a solid phase peptide synthesis vessel. 225 μL of N,N-diisopropylethylamine and several crystals of DMAP were added and this was shaken at rt for 2.5 h. Then 2-methoxyethylamine (0.085 g, 97 μl, 1.13 mmol) was added and shaking was continued for 30 minutes. Then the solvent was removed and the beads washed for 10 minutes each time with CH2Cl2:Et3N (9:1, 4×50 mL), DMF (3×50 mL), Felts buffer (3×50 mL) and i-PrOH (3×50 mL). The beads 4b were stored in i-PrOH (beads: i-PrOH (1:2), v/v) at −80° C.
1-(2-Bromoethyl)-2-((6-(dimethylamino)benzo[d][1,3]dioxol-5-yl)thio)-1H-imidazo[4,5-c]pyridin-4-amine (5a). 1b (252 mg, 0.764 mmol), Cs2CO3 (373 mg, 1.15 mmol), 1,2-dibromoethane (718 mg, 329 μL, 3.82 mmol) in DMF (2 mL) was stirred for 1.5 h at rt. Then additional Cs2CO3 (124 mg, 0.38 mmol) was added and the mixture stirred for an additional 20 min. The mixture was dried under reduced pressure and the residue purified by preparatory TLC (CH2Cl2:MeOH, 10:1) to give 5a (211 mg, 63%); MS (ESI) m/z 436.0/438.0 [M+H]+.
tert-Butyl (6-((2-(4-amino-2-((6-(dimethylamino)benzo[d][1,3]dioxol-5-yl)thio)-1H-imidazo[4,5-c]pyridin-1-yl)ethyl)amino)hexyl)carbamate (6a). 5a (0.184 g, 0.423 mmol) and tert-butyl 6-aminohexylcarbamate (0.915 g, 4.23 mmol) in DMF (7 mL) was stirred at rt for 24 h. The reaction mixture was concentrated and the residue chromatographed [CHCl3:MeOH:MeOH—NH3 (7N), 100:7:3] to give 0.109 g (45%) of 6a; MS (ESI) m/z 572.3 [M+H]+.
(7a). 6a (0.257 g, 0.45 mmol) was dissolved in 15 mL of CH2Cl2:TFA (4:1) and the solution was stirred at rt for 45 min. Solvent was removed under reduced pressure and the residue dried under high vacuum overnight. This was dissolved in DMF (12 mL) and added to 25 mL of Affi-Gel 10 beads (prewashed, 3×50 mL DMF) in a solid phase peptide synthesis vessel. 225 μL of N,N-diisopropylethylamine and several crystals of DMAP were added and this was shaken at rt for 2.5 h. Then 2-methoxyethylamine (0.085 g, 97 μl, 1.13 mmol) was added and shaking was continued for 30 minutes. Then the solvent was removed and the beads washed for 10 minutes each time with CH2Cl2:Et3N (9:1, 4×50 mL), DMF (3×50 mL), Felts buffer (3×50 mL) and i-PrOH (3×50 mL). The beads 7a were stored in i-PrOH (beads: i-PrOH (1:2), v/v) at −80° C.
The beads 7b were prepared in a similar manner as described above for 7a.
(8a). 2a (3.8 mg, 0.0086 mmol) and EZ-Link® Amine-PEO3-Biotin (5.4 mg, 0.0129 mmol) in DMF (0.2 mL) was stirred at rt for 24 h. The reaction mixture was concentrated and the residue chromatographed [CHCl3:MeOH—NH3 (7N), 10:1] to give 2.3 mg (35%) of 8a. MS (ESI): m/z 775.2 [M+H]+.
(9a). 5a (3.7 mg, 0.0086 mmol) and EZ-Link® Amine-PEO3-Biotin (5.4 mg, 0.0129 mmol) in DMF (0.2 mL) was stirred at rt for 24 h. The reaction mixture was concentrated and the residue chromatographed [CHCl3:MeOH—NH3 (7N), 10:1] to give 1.8 mg (27%) of 9a. MS (ESI): m/z 774.2 [M+H]+.
Biotinylated compounds 8b and 9b were prepared in a similar manner from 2b and 5b, respectively.
2-(3-(6-Amino-8-(6-(dimethylamino)benzo[d][1,3]dioxol-5-ylthio)-9H-purin-9-yl)propyl)isoindoline-1,3-dione. 1a (0.720 g, 2.18 mmol), Cs2CO3 (0.851 g, 2.62 mmol), 2-(3-bromopropyl)isoindoline-1,3-dione (2.05 g, 7.64 mmol) in DMF (15 mL) was stirred for 2 h at rt. The mixture was dried under reduced pressure and the residue purified by column chromatography (CH2Cl2:MeOH:AcOH, 15:1:0.5) to give 0.72 g (63%) of the titled compound. 1H NMR (500 MHz, CDCl3/MeOH-d4): δ 8.16 (s, 1H), 7.85-7.87 (m, 2H), 7.74-7.75 (m, 2H), 6.87 (s, 1H), 6.71 (s, 1H), 5.88 (s, 2H), 4.37 (t, J=6.4 Hz, 2H), 3.73 (t, J=6.1 Hz, 2H), 2.69 (s, 6H), 2.37-2.42 (m, 2H); HRMS (ESI) m/z [M+H]+ calcd. for C25H24N7O4S, 518.1610; found 518.1601.
9-(3-Aminopropyl)-8-(6-(dimethylamino)benzo[d][1,3]dioxol-5-ylthio)-9H-purin-6-amine (10b). 2-(3-(6-Amino-8-(6-(dimethylamino)benzo[d][1,3]dioxol-5-ylthio)-9H-purin-9-yl)propyl)isoindoline-1,3-dione (0.72 g, 1.38 mmol), hydrazine hydrate (2.86 g, 2.78 mL, 20.75 mmol), in CH2Cl2:MeOH (4 mL:28 mL) was stirred for 2 h at rt. The mixture was dried under reduced pressure and the residue purified by column chromatography (CH2Cl2:MeOH—NH3(7N), 20:1) to give 430 mg (80%) of 10b. 1H NMR (500 MHz, CDCl3): δ 8.33 (s, 1H), 6.77 (s, 1H), 6.49 (s, 1H), 5.91 (s, 2H), 5.85 (br s, 2H), 4.30 (t, J=6.9 Hz, 2H), 2.69 (s, 6H), 2.65 (t, J=6.5 Hz, 2H), 1.89-1.95 (m, 2H); 13C NMR (125 MHz, CDCl3): δ 154.5, 153.1, 151.7, 148.1, 147.2, 146.4, 144.8, 120.2, 120.1, 109.3, 109.2, 101.7, 45.3, 45.2, 40.9, 38.6, 33.3; HRMS (ESI) m/z [M+H]+ calcd. for C17H22N7O2S, 388.1556; found 388.1544.
(12b). 10b (13.6 mg, 0.0352 mmol), EZ-Link® NHS-LC-LC-Biotin (22.0 mg, 0.0387 mmol) and DIEA (9.1 mg, 12.3 μL, 0.0704 mmol) in DMF (0.5 mL) was stirred at rt for 1 h. The reaction mixture was concentrated under reduced pressure and the resulting residue was purified by preparatory TLC (CH2Cl2:MeOH—NH3 (7N), 10:1) to give 22.7 mg (77%) of 12b. MS (ESI): m/z 840.2 [M+H]+.
(14b). 10b (14.5 mg, 0.0374 mmol), EZ-Link® NHS-PEG4-Biotin (24.2 mg, 0.0411 mmol) and DIEA (9.7 mg, 13 μL, 0.0704 mmol) in DMF (0.5 mL) was stirred at rt for 1 h. The reaction mixture was concentrated under reduced pressure and the resulting residue was purified by preparatory TLC (CH2Cl2:MeOH—NH3 (7N), 10:1) to give 24.1 mg (75%) of 14b. MS (ESI): m/z 861.3 [M+H]′.
Biotinylated compounds 12a, 13a, 13b, 14a, 15a and 15b were prepared in a similar manner as described for 12b and 14b.
8-((6-Bromobenzo[d][1,3]dioxol-5-yl)thio)-9-(2-(piperidin-4-yl)ethyl)-9H-purin-6-amine (18). 16 (300 mg, 0.819 mmol), Cs2CO3 (534 mg, 1.64 mmol), 17 (718 mg, 2.45 mmol) in DMF (10 mL) was stirred for 1.5 h at rt. The reaction mixture was filtered and dried under reduced pressure and chromatographed (CH2Cl2:MeOH, 10:1) to give a mixture of Boc-protected N9/N3 isomers. 20 mL of TFA:CH2Cl2 (1:1) was added at rt and stirred for 6 h. The reaction mixture was dried under reduced pressure and purified by preparatory HPLC to give 18 (87 mg, 22%); MS (ESI) m/z 477.0 [M+H]+.
6-Amino-1-(4-(2-(6-amino-8-((6-bromobenzo[d][1,3]dioxol-5-yl)thio)-9H-purin-9-yl)ethyl)piperidin-1-yl)hexan-1-one (19). To a mixture of 18 (150 mg, 0.314 mmol) in CH2Cl2 (5 ml) was added 6-(Boc-amino)caproic acid (145 mg, 0.628 mmol), EDCI (120 mg, 0.628 mmol) and DMAP (1.9 mg, 0.0157 mmol). The reaction mixture was stirred at rt for 2 h then concentrated under reduced pressure and the residue purified by preparatory TLC [CH2Cl2:MeOH—NH3 (7N), 15:1] to give 161 mg (74%) of 19; MS (ESI) in/z 690.1 [M+H]+.
(20). 19 (0.264 g, 0.45 mmol) was dissolved in 15 mL of CH2Cl2:TFA (4:1) and the solution was stirred at rt for 45 min. Solvent was removed under reduced pressure and the residue dried under high vacuum overnight. This was dissolved in DMF (12 mL) and added to 25 mL of Affi-Gel 10 beads (prewashed, 3×50 mL DMF) in a solid phase peptide synthesis vessel. 225 μL of N,N-diisopropylethylamine and several crystals of DMAP were added and this was shaken at rt for 2.5 h. Then 2-methoxyethylamine (0.085 g, 97 μl, 1.13 mmol) was added and shaking was continued for 30 minutes. Then the solvent was removed and the beads washed for 10 minutes each time with CH2Cl2:Et3N (9:1, 4×50 mL), DMF (3×50 mL), Felts buffer (3×50 mL) and i-PrOH (3×50 mL). The beads 20 were stored in i-PrOH (beads: i-PrOH (1:2), v/v) at −80° C.
(21). 18 (13.9 mg, 0.0292 mmol), EZ-Link® NHS-LC-LC-Biotin (18.2 mg, 0.0321 mmol) and DIEA (7.5 mg, 10.2 μL, 0.0584 mmol) in DMF (0.5 mL) was heated at 35° C. for 6 h. The reaction mixture was concentrated under reduced pressure and the resulting residue was purified by preparatory TLC (CH2Cl2:MeOH—NH3 (7N), 10:1) to give 7.0 mg (26%) of 21. MS (ESI): m/z 929.3 [M+H]′.
(22). 18 (13.9 mg, 0.0292 mmol), EZ-Link® NHS-PEG4-Biotin (18.9 mg, 0.0321 mmol) and DIEA (7.5 mg, 10.2 μL, 0.0584 mmol) in DMF (0.5 mL) was heated at 35° C. for 6 h. The reaction mixture was concentrated under reduced pressure and the resulting residue was purified by preparatory TLC (CH2Cl2:MeOH—NH3 (7N), 10:1) to give 8.4 mg (30%) of 22; MS (ESI): m/z 950.2 [M+H]+.
(24). 23 (16.3 mg, 0.0352 mmol), EZ-Link® NHS-LC-LC-Biotin (22.0 mg, 0.0387 mmol) and DIEA (9.1 mg, 12.3 μL, 0.0704 mmol) in DMF (0.5 mL) was stirred at rt for 1 h. The reaction mixture was concentrated under reduced pressure and the resulting residue was purified by preparatory TLC (CH2Cl2:MeOH, 10:1) to give 26.5 mg (82%) of 24; MS (ESI): m/z 916.4 [M+H]+.
(25). 23 (17.3 mg, 0.0374 mmol), EZ-Link® NHS-PEG4-Biotin (24.2 mg, 0.0411 mmol) and DIEA (9.7 mg, 13 μL, 0.0704 mmol) in DMF (0.5 mL) was stirred at rt for 1 h. The reaction mixture was concentrated under reduced pressure and the resulting residue was purified by preparatory TLC (CH2Cl2:MeOH, 10:1) to give 30.1 mg (78%) of 25; MS (ESI): m/z 937.3 [M+H]+.
The present disclosure provides methods of identifying cancer-implicated pathways and specific components of cancer-implicated pathways (e.g., oncoproteins) associated with Hsp90 that are implicated in the development and progression of a cancer. Such methods involve contacting a sample containing cancer cells from a subject suffering from cancer with an inhibitor of Hsp90, and detecting the components of the cancer-implicated pathway that are bound to the inhibitor of Hsp90.
As used herein, certain terms have the meanings set forth after each such term as follows:
“Cancer-Implicated Pathway” means any molecular pathway, a variation in which is involved in the transformation of a cell from a normal to a cancer phenotype. Cancer-implicated pathways may include pathways involved in metabolism, genetic information processing, environmental information processing, cellular processes, and organismal systems. A list of many such pathways is set forth in Table 1 and more detailed information may be found about such pathways online in the KEGG PATHWAY database; and the National Cancer Institute's Nature Pathway Interaction Database. See also the websites of Cell Signaling Technology, Beverly, Mass.; BioCarta, San Diego, Calif.; and Invitrogen/Life Technologies Corporation, Clarsbad, Calif. In addition,
“Component of a Cancer-Implicated Pathway” means a molecular entity located in a Cancer-Implicated Pathway which can be targeted in order to effect inhibition of the pathway and a change in a cancer phenotype which is associated with the pathway and which has resulted from activity in the pathway. Examples of such components include components listed in
“Inhibitor of a Component of a Cancer-Implicated Pathway” means a compound (other than an inhibitor of Hsp90) which interacts with a Cancer-Implicated Pathway or a Component of a Cancer-Implicated Pathway so as to effect inhibition of the pathway and a change in a cancer phenotype which has resulted from activity in the pathway. Examples of inhibitors of specific Components are widely known. Merely by way of example, the following U.S. patents and U.S. patent application publications describe examples of inhibitors of pathway components as listed follows:
Still further a few examples of inhibitors of protein kinases are shown in
“Inhibitor of Hsp90” means a compound which interacts with, and inhibits the activity of, the chaperone, heat shock protein 90 (Hsp90). The structures of several known Hsp90 inhibitors, including PU-H71, are shown in
The attachment of small molecules to a solid support is a very useful method to probe their target and the target's interacting partners. Indeed, geldanamycin attached to solid support enabled for the identification of Hsp90 as its target. Perhaps the most crucial aspects in designing such chemical probes are determining the appropriate site for attachment of the small molecule ligand, and designing an appropriate linker between the molecule and the solid support. Our strategy to design Hsp90 chemical probes entails several steps. First, in order to validate the optimal linker length and its site of attachment to the Hsp90 ligand, the linker-modified ligand was docked onto an appropriate X-ray crystal structure of Hsp90α. Second, the linker-modified ligand was evaluated in a fluorescent polarization (FP) assay that measures competitive binding to Hsp90 derived from a cancer cell extract. This assay uses Cy3b-labeled geldanamycin as the FP-optimized Hsp90 ligand (Du et al., 2007). These steps are important to ensure that the solid-support immobilized molecules maintain a strong affinity for Hsp90. Finally, the linker-modified small molecule was attached to the solid support, and its interaction with Hsp90 was validated by incubation with an Hsp90-containing cell extract.
When a probe is needed to identify Hsp90 in complex with its onco-client proteins, further important requirements are (1.) that the probe retains selectivity for the “oncogenic Hsp90 species” and (2.) that upon binding to Hsp90, the probe locks Hsp90 in a client-protein bound conformation. The concept of “oncogenic Hsp90” is further defined in this application as well as in
When a probe is needed to identify Hsp90 in complex with its onco-client proteins by mass spectrometry techniques, further important requirements are (1.) that the probe isolates sufficient protein material and (2.) that the signal to ratio as defined by the amount of Hsp90 onco-clients and unspecifically resin-bound proteins, respectively, be sufficiently large as to be identifiable by mass spectrometry. This application provides examples of the production of such probes.
We chose Affi-Gel® 10 (BioRad) for ligand attachment. These agarose beads have an N-hydroxysuccinimide ester at the end of a 10C spacer arm, and in consequence, each linker was designed to contain a distal amine functionality. The site of linker attachment to PU-H71 was aided by the co-crystal structure of it bound to the N-terminal domain of human Hsp90a (PDB ID: 2FWZ). This structure shows that the purine's N9 amine makes no direct contact with the protein and is directed towards solvent (
We also designed a biotinylated derivative of PU-H71. One advantage of the biotinylated agent over the solid supported agents is that they can be used to probe binding directly in cells or in vivo systems. The ligand-Hsp90 complexes can then be captured on biotin-binding avidin or streptavidin containing beads. Typically this process reduces the unspecific binding associated with chemical precipitation from cellular extracts. Alternatively, for in vivo experiments, the presence of active sites (in this case Hsp90), can be detected in specific tissues (i.e. tumor mass in cancer) by the use of a labeled-streptavidin conjugate (i.e. FITC-streptavidin). Biotinylated PU-H71 (7) was obtained by reaction of 2 with biotinyl-3,6,9-trioxaundecanediamine (EZ-Link® Amine-PEO3-Biotin) (
From the available co-crystal structure of NVP-AUY922 with Hsp90a (PDB 2VCI,
Although a co-crystal structure of SNX-2112 with Hsp90 is not publicly available, that of a related tetrahydro-4H-carbazol-4-one (27) bound to Hsp90a (PDB ID: 3D0B,
Synthesis of PU-H71 beads (6) is shown in
Synthesis of NVP-AUY922 beads (11) from aldehyde 8 (Brough et al., 2008) is shown in
Synthesis of SNX-2112 beads (21) is shown in
Several methods were employed to measure the progress of the reactions for the synthesis of the final probes. UV monitoring of the liquid was used by measuring a decrease in λmax for each compound. In general, it was observed that that there was no further decrease in the λmax after 1.5 h, indicating completion of the reaction. TLC was employed as a crude measure of the progress of the reaction whereas LC-MS monitoring of the liquid was used to confirm complete reaction. While on TLC the spot would not disappear since excess compound was used (1.2 eq.), a clear decrease in intensity indicated progress of the reaction.
The synthesis and full characterization of the Hsp90 inhibitors PU-H71 (He et al., 2006) and NVP-AUY922 (Brough et al., 2008) have been reported elsewhere. SNX-2112 had previously been mentioned in the patent literature (Serenex et al., 2008, WO-2008130879A2; Serenex et al., 2008, US-20080269193A1), and only recently has it been fully characterized and its synthesis adequately described (Huang et al., 2009). At the time this research project began specific details on its synthesis were lacking. Additionally, we had difficulty reproducing the amination of 16 with trans-4-aminocyclohexanol under conditions reported for similar compounds [Pd(OAc)2, DPPF, NaOtBu, toluene, 120° C., microwave]. In our hands, only trace amounts of product were detected at best. Changing catalyst to PdCl2, Pd(PPh3)4 or Pd2(dba)3 or solvent to DMF or 1,2-dimethoxyethane (DME) or base to K3PO4 did not result in any improvement. Therefore, we modified this step and were able to couple 16 to trans-4-aminocyclohexanol tetrahydropyranyl ether (24) under Buchwald conditions (Old et al., 1998) using Pd2(dba)3 and DavePhos in DME to give nitrile 25 (28%) along with amide 26 (17%) for a combined yield of 45% (
Next, we investigated whether the synthesized beads retained interaction with Hsp90 in cancer cells. Agarose beads covalently attached to either of PU-H71, NVP-AUY922, SNX-2112 or 2-methoxyethylamine (PU-, NVP-, SNX-, control-beads, respectively), were incubated with K562 chronic myeloid leukemia (CML) or MDA-MB-468 breast cancer cell extracts. As seen in
Further, to probe the ability of these chemical tools to isolate genuine Hsp90 client proteins in tumor cells, we incubated PU-H71 attached to solid support (6) with cancer cell extracts. We were able to demonstrate dose-dependent isolation of Hsp90/c-Kit and Hsp90/IGF-IR complexes in MDA-MB-468 cells (
Similar experiments were possible with PU-H71-biotin (7) (
It is important to note that previous attempts to isolate Hsp90/client protein complexes using a solid-support immobilized GM were of little success (Tsaytler et al., 2009). In that case, the proteins bound to Hsp90 were washed away during the preparative steps. To prevent the loss of Hsp90-interacting proteins, the authors had to subject the cancer cell extracts to crosslinking with DSP, a homobifunctional amino-reactive DTT-reversible cross-linker, suggesting that unlike PU-H71, GM is unable to stabilize Hsp90/client protein interactions. We observed a similar profile when using beads with GM directly covalently attached to the Affi-Gel® 10 resin. Crystallographic and biochemical investigations suggest that GM preferentially interacts with Hsp90 in an apo, open-conformation, that is unfavorable for certain client protein binding (Roe et al., 1999; Stebbins et al., 1997; Nishiya et al., 2009) providing a potential explanation for the limited ability of GM-beads to capture Hsp90/client protein complexes. It is currently unknown what Hsp90 conformations are preferred by the other Hsp90 chemotypes, but with the NVP- and SNX-beads also available, as reported here, similar evaluations are now possible, leading to a better understanding of the interaction of these agents with Hsp90, and of the biological significance of these interactions.
In another application of the chemical tools designed here, we show that PU-H71-biotin (7) can also be used to specifically detect Hsp90 when expressed on the cell surface (
In summary, we have prepared useful chemical tools based on three different Hsp90 inhibitors, each of a different chemotype. These were prepared either by attachment onto solid support, such as PU-H71 (purine), NVP-AUY922 (isoxazole) and SNX-2112 (indazol-4-one)-beads, or by biotinylation (PU-H71-biotin). The utility of these probes was demonstrated by their ability to efficiently isolate Hsp90 and, in the case of PU-H71 beads (6), isolate Hsp90 onco-protein containing complexes from cancer cell extracts. Available co-crystal structures and SAR were utilized in their design, and docking to the appropriate X-ray crystal structure of Hsp90a used to validate the site of attachment of the linker. These are important chemical tools in efforts towards better understanding Hsp90 biology and towards designing Hsp90 inhibitors with most favorable clinical profile.
The disclosure provides methods of identifying components of cancer-implicated pathway (e.g., oncoproteins) using the Hsp90 probes described above. In one embodiment of the invention the cancer-implicated pathway is a pathway involved in metabolism, genetic information processing, environmental information processing, cellular processes, or organismal systems. For example, the cancer-implicated pathway may be a pathway listed in Table 1.
More particularly, the cancer-implicated pathway or the component of the cancer-implicated pathway is involved with a cancer such as a cancer selected from the group consisting of a colorectal cancer, a pancreatic cancer, a thyroid cancer, a leukemia including an acute myeloid leukemia and a chronic myeloid leukemia, a basal cell carcinoma, a melanoma, a renal cell carcinoma, a bladder cancer, a prostate cancer, a lung cancer including a small cell lung cancer and a non-small cell lung cancer, a breast cancer, a neuroblastoma, myeloproliferative disorders, gastrointestinal cancers including gastrointestinal stromal tumors, an esophageal cancer, a stomach cancer, a liver cancer, a gallbladder cancer, an anal cancer, brain tumors including gliomas, lymphomas including a follicular lymphoma and a diffuse large B-cell lymphoma, and gynecologic cancers including ovarian, cervical, and endometrial cancers.
The following subsections describe use of the Hsp90 probes of the present disclosure to determine properties of Hsp90 in cancer cells and to identify oncoproteins and cancer-implicated pathways.
To investigate the interaction of small molecule Hsp90 inhibitors with tumor Hsp90 complexes, we made use of agarose beads covalently attached to either geldanamycin (GM) or PU-H71 (GM- and PU-beads, respectively) (
First we evaluated the binding of these agents to Hsp90 in a breast cancer and in chronic myeloid leukemia (CML) cell lysates. Four consecutive immunoprecipitation (IP) steps with H9010, but not with a non-specific IgG, efficiently depleted Hsp90 from these extracts (
To exclude the possibility that changes in Hsp90 configuration in cell lysates make it unavailable for binding to immobilized PU-H71 but not to the antibody, we analyzed binding of radiolabeled 131I-PU-H71 to Hsp90 in intact cancer cells (
Collectively, these data suggest that certain Hsp90 inhibitors, such as PU-H71, preferentially bind to a subset of Hsp90 species that is more abundant in cancer cells than in normal cells (
To explore the biochemical functions associated with these Hsp90 species, we performed immunoprecipitations (IPs) and chemical precipitations (CPs) with antibody- and Hsp90-inhibitor beads, respectively, and we analysed the ability of Hsp90 bound in these contexts to co-precipitate with a chosen subset of known clients. K562 CML cells were first investigated because this cell line co-expresses the aberrant Bcr-Abl protein, a constitutively active kinase, and its normal counterpart c-Abl. These two Abl species are clearly separable by molecular weight and thus easily distinguishable by Western blot (
In contrast, PU-bound Hsp90 preferentially isolated the Bcr-Abl protein (
To further differentiate between the PU-H71- and antibody-associated Hsp90 fractions, we performed sequential depletion experiments and evaluated the co-chaperone constituency of the two species (Zuehlke & Johnson, 2010). The fraction of Hsp90 containing the Hsp90/Bcr-Abl complexes bound several co-chaperones, including Hsp70, Hsp40, HOP and HIP (
These findings suggest the existence of distinct pools of Hsp90 preferentially bound to either Bcr-Abl or Abl in CML cells (
We next evaluated whether other inhibitors that interact with the N-terminal regulatory pocket of Hsp90 in a manner similar to PU-H71, including the synthetic inhibitors SNX-2112 and NVP-AUY922, and the natural product GM (Janin, 2010), could selectively isolate similar Hsp90 species (
To determine whether selectivity towards onco-proteins was not restricted to Bcr-Abl, we tested several additional well-defined Hsp90 client proteins in other tumor cell lines (
The data presented above suggest that PU-H71, which specifically interacts with Hsp90 (
Protein cargo isolated from cell lysate with PU-beads or control-beads was subjected to proteomic analysis by nano liquid chromatography coupled to tandem mass spectrometry (nano LC-MS/MS). Initial protein identification was performed using the Mascot search engine, and was further evaluated using Scaffold Proteome Software (Tables 5a-d). Among the PU-bead-interacting proteins, Bcr-Abl was identified (see Bcr and Abl1, Table 5a and
Ingenuity Pathway Analysis (IPA) was then used to build biological networks from the identified proteins (
In addition to signaling proteins, we identified proteins that regulate carbohydrate and lipid metabolism, protein synthesis, gene expression, and cellular assembly and organization. These findings are in accord with the postulated broad roles of Hsp90 in maintaining cellular homeostasis and in being an important mediator of cell transformation (Zuehlke & Johnson, 2010; Workman et al., 2007; Dezwaan & Freeman, 2008; McClellan et al., 2007).
Following identification by MS, a number of key proteins were further validated by chemical precipitation and Western blot, in both K562 cells and in primary CML blasts (
The top scoring networks enriched on the PU-beads were those used by Bcr-Abl to propagate aberrant signaling in CML: the PI3K/mTOR-, MAPK- and NFκB-mediated signaling pathways (Network 1, 22 focus molecules, score=38 and Network 2, 22 focus molecules, score=36, Table 5f). Connectivity maps were created for these networks to investigate the relationship between component proteins (
Activation of the PI3K/mTOR-pathway has emerged as one of the essential signaling mechanisms in Bcr-Abl leukemogenesis (Ren, 2005). Of particular interest within this pathway is the mammalian target of rapamycin (mTOR), which is constitutively activated in Bcr-Abl-transformed cells, leading to dysregulated translation and contributing to leukemogenesis. A recent study provided evidence that both the mTORC1 and mTORC2 complexes are activated in Bcr-Abl cells and play key roles in mRNA translation of gene products that mediate mitogenic responses, as well as in cell growth and survival (Carayol et al., 2010). mTOR and key activators of mTOR, such as RICTOR, RAPTOR, Sin 1 (MAPKAP1), class 3 PI3Ks PIK3C3, also called hVps34, and PIK3R4 (VSP15) (Nobukuni et al., 2007), were identified in the PU-Hsp90 pull-downs (Tables 5a, 5d;
Activation of nuclear factor-κB (NF-κB) is required for Bcr-Abl transformation of primary bone marrow cells and for Bcr-Abl-transformed hematopoietic cells to form tumors in nude mice (McCubrey et al., 2008). PU-isolated proteins enriched on this pathway include NF-κB as well as activators of NF-kB such as IKBKAP, that binds NF-kappa-B-inducing kinase (NIK) and IKKs through separate domains and assembles them into an active kinase complex, and TBK-1 (TANK-binding kinase 1) and TAB1 (TAK1-binding protein 1), both positive regulators of the I-kappaB kinase/NF-kappaB cascade (Häcker & Karin, 2006) (Tables 5a, 5d). Recently, Bcr-Abl-induced activation of the NF-κB cascade in myeloid leukemia cells was demonstrated to be largely mediated by tyrosine-phosphorylated PKD2 (or PRKD2) (Mihailovic et al., 2004) which we identify here to be a PU-H71/Hsp90 interactor (Tables 5a, 5d;
Key effectors of the MAPK pathway, another important pathway activated in CML (Ren, 2005; McCubrey et al., 2008), such as Raf-1, A-Raf, ERK, p90RSK, vav and several MAPKs were also included the PU-Hsp90-bound pool (Tables 5a, 5d;
The STAT-pathway is also activated in CML and confers cytokine independence and protection against apoptosis (McCubrey et al., 2008) and was enriched by PU-H71 chemical precipitation (Network 8, 20 focus molecules, score=14, Table 5f,
Retention and homing of progenitor blood cells to the marrow microenvironment are regulated by receptors and agonists of survival and proliferation. Bcr-Abl induces adhesion independence resulting in aberrant release of hematopoietic stem cells from the bone marrow, and leading to activation of adhesion receptor signaling pathways in the absence of ligand binding. The focal adhesion pathway was well represented in PU-H71 pulldowns (Network 12, 16 focus molecules, score=13, Table 5f,
Other important transforming pathways in CML, those driven by MYC (Sawyers, 1993) (Network 7, 15 focus molecules, score=22,
In summary, PU-H71 enriches a broad cross-section of proteins that participate in signaling pathways vital to the malignant phenotype in CML (
We demonstrate that the presence of these proteins in the PU-bead pull-downs is functionally significant and suggests a role for Hsp90 in broadly supporting the malignant signalosome in CML cells.
To demonstrate that the networks identified by PU-beads are important for transformation in K562, we next showed that inhibitors of key nodal proteins from individual networks (
Next we demonstrated that PU-beads identified Hsp90 interactors with yet no assigned role in CML, also contribute to the transformed phenotype. The histone-arginine methyltransferase CARM1, a transcriptional co-activator of many genes (Bedford & Clarke, 2009), was validated in the PU-bead pull-downs from CML cell lines and primary CML cells (
To demonstrate that the presence of proteins in the PU-pulldowns is due to their participation in aberrantly activated signaling and not merely their abundant expression, we compared PU-bead pulldowns from K562 and Mia-PaCa-2, a pancreatic cancer cell line (Table 5a). While both cells express high levels of STAT5 protein (
The mTOR pathway was identified by the PU-beads in both K562 and Mia-PaCa-2 cells (
PU-bead pull-downs contain several proteins, including Bcr-Abl (Ren, 2005), CAMKIIγ (Si & Collins, 2008), FAK (Salgia et al., 1995), vav-1 (Katzav, 2007) and PRKD2 (Mihailovic et al., 2004) that are constitutively activated in CML leukemogenesis. These are classical Hsp90-regulated clients that depend on Hsp90 for their stability because their steady-state levels decrease upon Hsp90 inhibition (
To investigate this hypothesis further we focused on STAT5, which is constitutively phosphorylated in CML (de Groot et al., 1999). The overall level of p-STAT5 is determined by the balance of phosphorylation and dephosphorylation events. Thus, the high levels of p-STAT5 in K562 cells may reflect either an increase in upstream kinase activity or a decrease in protein tyrosine phosphatase (PTPase) activity. A direct interaction between Hsp90 and p-STAT5 could also modulate the cellular levels of p-STAT5.
To dissect the relative contribution of these potential mechanisms, we first investigated the effect of PU-H71 on the main kinases and PTPases that regulate STAT5 phosphorylation in K562 cells. Bcr-Abl directly activates STAT5 without the need for JAK phosphorylation (de Groot et al., 1999). Concordantly, STAT5-phosphorylation rapidly decreased in the presence of the Bcr-Abl inhibitor Gleevec (
Thus reduction of p-STAT5 phosphorylation by PU-H71 in the 0 to 90 min interval (
We therefore examined whether the rapid decrease in p-STAT5 levels in the presence of PU-H71 may be accounted for by an increase in PTPase activity. The expression and activity of SHP2, the major cytosolic STAT5 phosphatase (Xu & Qu, 2008), were also not altered within this time interval (
Thus no effect on STAT5 in the interval 0-90 min can likely be attributed to a change in kinase or phosphatase activity towards STAT5. As an alternative mechanism, and because the majority of p-STAT5 but not STAT5 is Hsp90 bound in CML cells (
The activation/inactivation cycle of STATs entails their transition between different dimer conformations. Phosphorylation of STATs occurs in an anti-parallel dimer conformation that upon phosphorylation triggers a parallel dimer conformation. Dephosphorylation of STATs on the other hand require extensive spatial reorientation, in that the tyrosine phosphorylated STAT dimers must shift from parallel to anti-parallel configuration to expose the phosphotyrosine as a better target for phosphatases (Lim & Cao, 2006). We find that STAT5 is more susceptible to trypsin cleavage when bound to Hsp90 (
To investigate this possibility we used a pulse-chase strategy in which orthovanadate (Na3VO4), a non-specific PTPase inhibitor, was added to cells to block the dephosphorylation of STAT5. The residual level of p-STAT5 was then determined at several later time points (
Hsp90 Maintains STAT5 in an Active Conformation Directly within STAT5-Containing Transcriptional Complexes
In addition to STAT5 phosphorylation and dimerization, the biological activity of STAT5 requires its nuclear translocation and direct binding to its various target genes (de Groot et al., 1999; Lim & Cao, 2006). We wondered therefore, whether Hsp90 might also facilitate the transcriptional activation of STAT5 genes, and thus participate in promoter-associated STAT5 transcription complexes. Using an ELISA-based assay, we found that STAT5 (
Collectively, these data show that STAT5 activity is positively regulated by Hsp90 in CML cells (
More broadly, the data suggest that it is the PU-H71-Hsp90 fraction of cellular Hsp90 that is most closely involved in supporting oncogenic protein functions in tumor cells, and PU-H71-Hsp90 proteomics can be used to identify a broad cross-section of the protein pathways required to maintain the malignant phenotype in specific tumor cells (
It is now appreciated that many proteins that are required to maintain tumor cell survival may not present mutations in their coding sequence, and yet identifying these proteins is of extreme importance to understand how individual tumors work. Genome wide mutational studies may not identify these oncoproteins since mutations are not required for many genes to support tumor cell survival (e.g. IRF4 in multiple myeloma and BCL6 in B-cell lymphomas) (Cerchietti et al., 2009). Highly complex, expensive and large-scale methods such as RNAi screens have been the major means for identifying the complement of oncogenic proteins in various tumors (Horn et al., 2010). We present herein a rapid and simple chemical-proteomics method for surveying tumor oncoproteins regardless of whether they are mutated (
While this method presents a unique approach to identify the oncoproteins that maintain the malignant phenotype of tumor cells, one needs to be aware that, similarly to other chemical or antibody-based proteomics techniques, it also has potential limitations (Rix & Superti-Furga, 2009). For example, “sticky” or abundant proteins may also bind in a nondiscriminatory fashion to proteins isolated by the PU-H71 beads. Such proteins were catalogued by several investigators (Trinkle-Mulcahy et al., 2008), and we have used these lists to eliminate them from the pull-downs with the clear understanding that some of these proteins may actually be genuine Hsp90 clients. Second, while we have presented several lines of evidence that PU-H71 is specific for Hsp90 (
In spite of the potential limitations described in the preceeding paragraph, we have, using this method, performed the first global evaluation of Hsp90-facilitated aberrant signaling pathways in CML. The Hsp90 interactome identified by PU-H71 affinity purification significantly overlaps with the well-characterized CML signalosome (
Since single agent therapy is not likely to be curative in cancer, it is necessary to design rational combinatorial therapy approaches. Proteomic identification of oncogenic Hsp90-scaffolded signaling networks may identify additional oncoproteins that could be further targeted using specific small molecule inhibitors. Indeed, inhibitors of mTOR and CAMKII, which are identified by our method to contribute to the transformation of K562 CML cells and be key nodal proteins on individual networks (
When applied to less well-characterized tumor types, PU-H71 chemical proteomics might provide less obvious and more impactful candidate targets for combinatorial therapy. We exemplify this concept in the MDA-MB-468 triple-negative breast cancer cells, the MiaPaCa2 pancreatic cancer cells and the OCI-LY1 diffuse large B-cell lymphoma cells.
In the triple negative breast cancer cell line MDA-MB-468 major signaling networks identified by the method were the PI3K/AKT, IGF-IR, NRF2-mediated oxidative stress response, MYC, PKA and the IL-6 signaling pathways (
S. cerevisiae)
Drosophila)-like
Phosphatidylinositol 3 kinases (PI3K) are a family of lipid kinases whose inositol lipid products play a central role in signal transduction pathways of cytokines, growth factors and other extracellular matrix proteins. PI3Ks are divided into three classes: Class 1, 11 and III with Class I being the best studied one. It is a heterodimer consisting of a catalytic and regulatory subunit. These are most commonly found to be p110 and p85. Phosphorylation of phosphoinositide(4,5)bisphosphate (PIP2) by Class I PI3K generates PtdIns(3,4,5)P3. The different PI3ks are involved in a variety of signaling pathways. This is mediated through their interaction with molecules like the receptor tyrosine kinases (RTKs), the adapter molecules GAB1-GRB2, and the kinase JAK. These converge to activate PDK1 which then phosphorylates AKT. AKT follows two distinct paths: 1) Inhibitory role—for example, AKT inhibits apoptosis by phosphorylating the Bad component of the Bad/Bcl-XL complex, allowing for cell survival. 2) Activating role—AKT activates IKK leading to NF-κB activation and cell survival. By its inhibitory as well as activating role, AKT is involved in numerous cellular processes like energy storage, cell cycle progression, protein synthesis and angiogenesis.
This pathway is composed of, but not restricted to 1-phosphatidyl-D-myo-inositol 4,5-bisphosphate, 14-3-3, 14-3-3-Cdkn1b, Akt, BAD, BCL2, BCL2L1, CCND1, CDC37, CDKN1A, CDKN1B, citrulline, CTNNB1, EIF4E, EIF4EBP1, ERK1/2, FKHR, GAB1/2, GDF15, Glycogen synthase, GRB2, Gsk3, Ikb, IkB-NfkB, IKK (complex), ILK, Integrin, JAK, L-arginine, LIMS1, MAP2K1/2, MAP3K5, MAP3K8, MAPK81P1, MCL1, MDM2, MTOR, NANOG, NFkB (complex), nitric oxide, NOS3, P110, p70 S6k, PDPK1, phosphatidylinositol-3,4,5-triphosphate, PI3K p85, PP2A, PTEN, PTGS2, RAF1, Ras, RHEB, SFN, SHC1 (includes EG:20416), SHIP, Sos, THEM4, TP53 (includes EG:22059), TSC1, Tsc1-Tsc2, TSC2, YWHAE
Insulin-like growth factor-1 (IGF-1) is a peptide hormone under control of the growth hormone. IGF-1 promotes cell proliferation, growth and survival. Six specific binding proteins, IGFBP 1-6, allow for a more nuanced control of IGF activity. The IGF-1 receptor (IGF-1R) is a transmembrane tyrosine kinase protein. IGF-1-induced receptor activation results in autophosphorylation followed by an enhanced capability to activate downstream pathways. Activated IGF-1R phosphorylates SHC and IRS-1. SHC along with adapter molecules GRB2 and SOS forms a signaling complex that activates the Ras/Raf/MEK/ERK pathway. ERK translocation to the nucleus results in the activation of transcriptional regulators ELK-1, c-Jun and c-Fos which induce genes that promote cell growth and differentiation. IRS-1 activates pathways for cell survival via the PI3K/PDK1/AKT/BAD pathway. IRS-1 also activates pathways for cell growth via the PI3K/PDK1/p70RSK pathway. IGF-1 also signals via the JAK/STAT pathway by inducing tyrosine phosphorylation of JAK-1, JAK-2 and STAT-3. SOCS proteins are able to inhibit the JAKs thereby inhibiting this pathway. The adapter protein GRB10 interacts with IGF-IR. GRB10 also binds the E3 ubiquitin ligase NEDD4 and promotes ligand stimulated ubiquitination, internalization, and degradation of the IGF-IR as a means of long-term attenuation of signaling.
This pathway is composed of, but not restricted to 1-phosphatidyl-D-myo-inositol 4,5-bisphosphatc, 14-3-3, 14-3-3-Bad, Akt, atypical protein kinase C, BAD, CASP9 (includes EG:100140945), Ck2, ELK1, ERK1/2, FKHR, FOS, GRB10, GRB2, IGF1, Igfl-Igfbp, IGF1R, Igfbp, IRS1/2, JAK1/2, JUN, MAP2K1/2, MAPK8, NEDD4, p70 S6k, PDPK1, phosphatidylinositol-3,4,5-triphosphate, PI3K (complex), Pka, PTK2 (includes EG:14083), PTPN11, PXN, RAF1, Ras, RASA1, SHC1 (includes EG:20416), SOCS, SOCS3, Sos, SRF, STAT3, Stat3-Stat3
Oxidative stress is caused by an imbalance between the production of reactive oxygen and the detoxification of reactive intermediates. Reactive intermediates such as peroxides and free radicals can be very damaging to many parts of cells such as proteins, lipids and DNA. Severe oxidative stress can trigger apoptosis and necrosis. Oxidative stress is involved in many diseases such as atherosclerosis, Parkinson's disease and Alzheimer's disease. Oxidative stress has also been linked to aging. The cellular defense response to oxidative stress includes induction of detoxifying enzymes and antioxidant enzymes. Nuclear factor-erythroid 2-related factor 2 (Nrf2) binds to the antioxidant response elements (ARE) within the promoter of these enzymes and activates their transcription. Inactive Nrf2 is retained in the cytoplasm by association with an actin-binding protein Keap1. Upon exposure of cells to oxidative stress, Nrf2 is phosphorylated in response to the protein kinase C, phosphatidylinositol 3-kinase and MAP kinase pathways. After phosphorylation, Nrf2 translocates to the nucleus, binds AREs and transactivates detoxifying enzymes and antioxidant enzymes, such as glutathione S-transferase, cytochrome P450, NAD(P)H quinone oxidoreductase, heme oxygenase and superoxide dismutase.
This pathway is composed of, but not restricted to ABCC1, ABCC2, ABCC4 (includes EG:10257), Actin, Actin-Nrf2, Afar, AKRIA1, AKT1, AOX1, ATF4, BACH1, CAT, Cbp/p300, CBR1, CCT7, CDC34, CLPP, CUL3 (includes EG:26554), Cul3-Rocl, Cypla/2a/3a/4a/2c, EIF2AK3, ENC1, EPHX1, ERK1/2, ERP29, FKBP5, FM01 (includes EG:14261), FOS, FOSL1, FTH1 (includes EG:14319), FTL, GCLC, GCLM, GPX2, GSK3B, GSR, GST, HERPUD1, HMOX1, Hsp22/Hsp40/Hsp90, JINK1/2, Jnkk, JUN/JUNB/JUND, KEAP1, Keap1-Nrf2, MAF, MAP2K1/2, MAP2K5, MAP3K1, MAP3K5, MAP3K7 (includes EG:172842), MAPK14, MAPK7, MKK3/6, musculoaponeurotic fibrosarcoma oncogene, NFE2L2, NQO, PI3K (complex), Pkc(s), PMF1, PPIB, PRDX1, Psm, PTPLAD1, RAF1, Ras, RBX1, reactive oxygen species, SCARB1, SLC35A2, Sod, SQSTM1, STIP1, TXN (includes EG:116484), TXNRD1, UBB, UBE2E3, UBE2K, USP14, VCP
Protein kinase A (PKA) regulates processes as diverse as growth, development, memory, and metabolism. It exists as a tetrameric complex of two catalytic subunits (PKA-C) and a regulatory (PKA-R) subunit dimer. Type-II PKA is anchored to specific locations within the cell by AKAPs. Extracellular stimuli such as neurotransmitters, hormones, inflammatory stimuli, stress, epinephrine and norepinephrine activate G-proteins through receptors such as GPCRs and ADR-α/β. These receptors along with others such as CRHR, GcgR and DCC are responsible for cAMP accumulation which leads to activation of PKA. The conversion of ATP to cAMP is mediated by the 9 transmembrane AC enzymes and one soluble AC. The transmembrane AC are regulated by heterotrimeric G-proteins, Gαs, Gαq and Gαi. Gαs and Gαq activate while Gαi inhibits AC. Gβ and Gγ subunits act synergistically with Gαs and Gαq to activate ACII, IV and VII. However the β and γ subunits along with Gαi inhibit the activity of ACI, V and VI.
G-proteins indirectly influence cAMP signaling by activating PLC, which generates DAG and IP3. DAG in turn activates PKC. IP3 modulates proteins upstream to cAMP signaling with the release of Ca2+ from the ER through IP3R. Ca2+ is also released by CaCn and CNG. Ca2+ release activates Calmodulin, CamKKs and CamKs, which take part in cAMP modulation by activating ACI. Gal3 activates MEKK1 and RhoA via two independent pathways which induce phosphorylation and degradation of IκBα and activation of PKA. High levels of cAMP under stress conditions like hypoxia, ischemia and heat shock also directly activate PKA. TGF-β activates PKA independent of cAMP through phosphorylation of SMAD proteins. PKA phosphorylates Phospholamban which regulates the activity of SERCA2 leading to myocardial contraction, whereas phosphorylation of TnnI mediates relaxation. PKA also activates KDELR to promote protein retrieval thereby maintaining steady state of the cell. Increase in concentration of Ca2+ followed by PKA activation enhances eNOS activity which is essential for cardiovascular homeostasis. Activated PKA represses ERK activation by inhibition of Raf1. PKA inhibits the interaction of 14-3-3 proteins with BAD and NFAT to promote cell survival. PKA phosphorylates endothelial MLCK leading to decreased basal MLC phosphorylation. It also phosphorylates filamin, adducin, paxillin and FAK and is involved in the disappearance of stress fibers and F-actin accumulation in membrane ruffles. PKA also controls phosphatase activity by phosphorylation of a specific PPtase1 inhibitor, DARPP32. Other substrates of PKA include histone H1, histone H2B and CREB.
This pathway is composed of, but not restricted to 1-phosphatidyl-D-myo-inositol 4,5-bisphosphate, 14-3-3, ADCY, ADCY1/5/6, ADCY2/4/7, ADCY9, Adducin, AKAP, APC, ATFL (includes EG:100040260), ATP, BAD, BRAF, Ca2+, Calcineurin protein(s), Calmodulin, CaMK_II, CHUK, Cng Channel, Creb, CREBBP, CREM, CTNNB1, cyclic AMP, DCC, diacylglycerol, ELK1, ERK1/2, Filamin, Focal adhesion kinase, G protein alphai, G protein beta gamma, G-protein beta, G-protein gamma, GLI3, glycogen, glycogen phosphorylase, Glycogen synthase, GNA13, GNAQ, GNAS, GRK1/7, Gsk3, Hedgehog, Histone H1, Histone h3, Ikb, IkB-NfkB, inositol triphosphate, ITPR, KDELR, LIPE, MAP2K1/2, MAP3K1, Mlc, myosin-light-chain kinase, Myosin2, Nfat (family), NFkB (complex), NGFR, NOS3, NTN1, Patched, Pde, Phk, Pka, Pka catalytic subunit, PKAr, Pkc(s), PLC, PLN, PP1 protein complex group, PPP1R1B, PTPase, PXN, RAF1, Rap1, RHO, RHOA, Rock, Ryr, SMAD3, Smad3-Smad4, SMAD4, SMO, TCF/LEF, Tgf beta, Tgf beta receptor, TGFBR1, TGFBR2, TH, Tni, VASP
The central role of IL-6 in inflammation makes it an important target for the management of inflammation associated with cancer. IL-6 responses are transmitted through Glycoprotein 130 (GP130), which serves as the universal signal-transducing receptor subunit for all IL-6-related cytokines. IL-6-type cytokines utilize tyrosine kinases of the Janus Kinase (JAK) family and signal transducers and activators of transcription (STAT) family as major mediators of signal transduction. Upon receptor stimulation by IL-6, the JAK family of kinases associated with GP130 are activated, resulting in the phosphorylation of GP130. Several phosphotyrosine residues of GP130 serve as docking sites for STAT factors mainly STAT3 and STAT1. Subsequently, STATs are phosphorylated, form dimers and translocate to the nucleus, where they regulate transcription of target genes. In addition to the JAK/STAT pathway of signal transduction, IL-6 also activates the extracellular signal-regulated kinases (ERK1/2) of the mitogen activated protein kinase (MAPK) pathway. The upstream activators of ERK1/2 include RAS and the src homology-2 containing proteins GRB2 and SHC. The SHC protein is activated by JAK2 and thus serves as a link between the IL-6 activated JAK/STAT and RAS-MAPK pathways. The phosphorylation of MAPKs in response to IL-6 activated RAS results in the activation of nuclear factor IL-6 (NF-IL6), which in turn stimulates the transcription of the IL-6 gene. The transcription of the IL-6 gene is also stimulated by tumor necrosis factor (TNF) and Interleukin-1 (IL-1) via the activation of nuclear factor kappa B (NFκB).
Based on the findings by the method described here in MDA-MB-468 cells, combination of an inhibitor of components of these identified pathways, such as those targeting but not limited to AKT, mTOR, PI3K, 1GF1R, IKK, Bcl2, PKA complex, phosphodiesterases are proposed to be efficacious when used in combination with an Hsp90 inhibitor.
Example of AKT inhibitors are PF-04691502, Triciribine phosphate (NSC-280594), A-674563, CCT128930, AT7867, PHT-427, GSK690693, MK-2206
Example of PI3K inhibitors are 2-(1H-indazol-4-yl)-6-(4-methanesulfonylpiperazin-1-ylmethyl)-4-morpholin-4-ylthieno(3,2-d)pyrimidine, BKM120, NVP-BEZ235, PX-866, SF 1126, XL147.
Example of mTOR inhibitors are deforolimus, everolimus, NVP-BEZ235, OSI-027, tacrolimus, temsirolimus, Ku-0063794, WYE-354, PP242, OSI-027, GSK2126458, WAY-600, WYE-125132
Examples of Bcl2 inhibitors are ABT-737, Obatoclax (GX15-070), ABT-263, TW-37
Examples of IGF1R inhibitors are NVP-ADW742, BMS-754807, AVE1642, BIIB022, cixutumumab, ganitumab, IGF1, OSI-906
Examples of JAK inhibitors are Tofacitinib citrate (CP-690550), AT9283, AG-490, INCB018424 (Ruxolitinib), AZD1480, LY2784544, NVP-BSK805, TG101209, TG-101348
Examples of IkK inhibitors are SC-514, PF 184
Examples of inhibitors of phosphodiesterases are aminophylline, anagrelide, arofylline, caffeine, cilomilast, dipyridamole, dyphylline, L 869298, L-826,141, milrinone, nitroglycerin, pentoxifylline, roflumilast, rolipram, tetomilast, theophylline, tolbutamide, amrinone, anagrelide, arofylline, caffeine, cilomilast, L 869298, L-826,141, milrinone, pentoxifylline, roflumilast, rolipram, tetomilast
In the Diffuse large B-cell lymphoma (DLBCL) cell line OCI-LY1, major signaling networks identified by the method were the B cell receptor, PKCteta, PI3K/AKT, CD40, CD28 and the ERK/MAPK signaling, pathways (
S. cerevisiae)
Drosophila)
Signals propagated through the B cell antigen receptor (BCR) are crucial to the development, survival and activation of B lymphocytes. These signals also play a central role in the removal of potentially self-reactive B lymphocytes. The BCR is composed of surface-bound antigen recognizing membrane antibody and associated Ig-α and Ig-β heterodimers which are capable of signal transduction via cytosolic motifs called immunoreceptor tyrosine based activation motifs (ITAM). The recognition of polyvalent antigens by the B cell antigen receptor (BCR) initiates a series of interlinked signaling events that culminate in cellular responses. The engagement of the BCR induces the phosphorylation of tyrosine residues in the ITAM. The phosphorylation of ITAM is mediated by SYK kinase and the SRC family of kinases which include LYN, FYN and BLK. These kinases which are reciprocally activated by phosphorylated ITAMs in turn trigger a cascade of interlinked signaling pathways. Activation of the BCR leads to the stimulation of nuclear factor kappa B (NFκB). Central to BCR signaling via NF-kB is the complex formed by the Bruton's tyrosine kinase (BTK), the adaptor B-cell linker (BLNK) and phospholipase C gamma 2 (PLCγ2). Tyrosine phosphorylated adaptor proteins act as bridges between BCR associated tyrosine kinases and downstream effector molecules. BLNK is phosphorylated on BCR activation and serves to couple the tyrosine kinase SYK to the activation of PLCγ2. The complete stimulation of PLCγ2 is facilitated by BTK. Stimulated PLCγ2 triggers the DAG and Ca2+ mediated activation of Protein kinase (PKC) which in turn activates IkB kinase (IKK) and thereafter NFκB. In addition to the activation of NFκB, BLNK also interacts with other proteins like VAV and GRB2 resulting in the activation of the mitogen activated protein kinase (MAPK) pathway. This results in the transactivation of several factors like c-JUN, activation of transcription factor (ATF) and ELK6. Another adaptor protein, B cell adaptor for phosphoinositide 3-kinase (PI3K), termed BCAP once activated by SYK, goes on to trigger a PI3K/AKT signaling pathway. This pathway inhibits Glycogen synthase kinase 3 (GSK3), resulting in the nuclear accumulation of transcription factors like nuclear factor of activated T cells (NFAT) and enhancement of protein synthesis. Activation of PI3K/AKT pathway also leads to the inhibition of apoptosis in B cells. This pathway highlights the important components of B cell receptor antigen signaling.
This pathway is composed of, but not restricted to 1-phosphatidyl-D-myo-inositol 4,5-bisphosphate, ABL1, Akt, ATF2, BAD, BCL10, Bcl10-Card10-Malt1, BCL2A1, BCL2L1, BCL6, BLNK, BTK, Calmodulin, CaMKII, CARD10, CD19, CD22, CD79A, CD79B, Creb, CSK, DAPP1, EGR1, ELK1, ERK1/2, ETS1, Fcgr2, GAB1/2, GRB2, Gsk3, Ikb, IkB-NfkB, IKK (complex), JINK1/2, Jnkk, JUN, LYN, MALT1, MAP2K1/2, MAP3K, MKK3/4/6, MTOR, NFAT (complex), NFkB (complex), P38 MAPK, p70 S6k, PAG1, phosphatidylinositol-3,4,5-triphosphate, PI3K (complex), PIK3AP1, PKC(β,θ), PLCG2, POU2F2, Pp2b, PTEN, PTPN11, PTPN6, PTPRC, Rac/Cdc42, RAFT, Ras, SHC1 (includes EG:20416), SHIP, Sos, SYK, VAV
An effective immune response depends on the ability of specialized leukocytes to identify foreign molecules and respond by differentiation into mature effector cells. A cell surface antigen recognition apparatus and a complex intracellular receptor-coupled signal transducing machinery mediate this tightly regulated process which operates at high fidelity to discriminate self antigens from non-self antigens. Activation of T cells requires sustained physical interaction of the TCR with an MHC-presented peptide antigen that results in a temporal and spatial reorganization of multiple cellular elements at the T-Cell-APC contact region, a specialized region referred to as the immunological synapse or supramolecular activation cluster. Recent studies have identified PKCθ, a member of the Ca-independent PKC family, as an essential component of the T-Cell supramolecular activation cluster that mediates several crucial functions in TCR signaling leading to cell activation, differentiation, and survival through IL-2 gene induction. High levels of PKCθ are expressed in skeletal muscle and lymphoid tissues, predominantly in the thymus and lymph nodes, with lower levels in spleen. T cells constitute the primary location for PKCθ expression. Among T cells, CD4+/CD8+ single positive peripheral blood T cells and CD4+/CD8+ double positive thymocytes are found to express high levels of PKCθ. On the surface of T cells, TCR/CD3 engagement induces activation of Src, Syk, ZAP70 and Tec-family PTKs leading to stimulation and membrane recruitment of PLCγ1, PI3K and Vav. A Vav mediated pathway, which depends on Rac and actin cytoskeleton reorganization as well as on PI3K, is responsible for the selective recruitment of PKCθ to the supramolecular activation cluster. PLCγ1-generated DAG also plays a role in the initial recruitment of PKCθ. The transcription factors NF-κB and AP-1 are the primary physiological targets of PKCθ. Efficient activation of these transcription factors by PKCθ requires integration of TCR and CD28 co-stimulatory signals. CD28 with its CD80/CD86 (B7-1/B7-2) ligands on APCs is required for the recruitment of PKCθ specifically to the supramolecular activation cluster. The transcriptional element which serves as a target for TCR/CD28 costimulation is CD28RE in the IL-2 promoter. CD28RE is a combinatorial binding site for NF-κB and AP-1. Recent studies suggest that regulation of TCR coupling to NF-κB by PKCθ is affected through a variety of distinct mechanisms. PKCθ may directly associate with and regulate the IKK complex; PKCθ may regulate the IKK complex indirectly though CaMKII; It may act upstream of a newly described pathway involving BCL10 and MALT1, which together regulate NF-κB and IκB via the IKK complex. PKCθ has been found to promote Activation-induced T cell death (AICD), an important process that limits the expansion of activated antigen-specific T cells and ensures termination of an immune response once the specific pathogen has been cleared. Enzymatically active PKCθ selectively synergizes with calcineurin to activate a caspase 8-mediated Fas/FasL-dependent AICD. CD28 co-stimulation plays an essential role in TCR-mediated IL-2 production, and in its absence the T cell enters a stable state of unresponsiveness termed anergy. PKCθ-mediated CREB phosphorylation and its subsequent binding to a cAMP-response element in the IL-2 promoter negatively regulates IL-2 transcription thereby driving the responding T cells into an anergic state. The selective expression of PKCθ in T-Cells and its essential role in mature T cell activation establish it as an attractive drug target for immunosuppression in transplantation and autoimmune diseases.
This pathway is composed of, but not restricted to Ap1, BCL10, Bcl10-Card11-Malt1, Calcineurin protein(s), CaMKII, CARD11, CD28, CD3, CD3-TCR, CD4, CD80 (includes EG:12519), CD86, diacylglycerol, ERK1/2, FOS, FYN, GRAP2, GRB2, Ikb, IkB-NfkB, Ikk (family), IL2, inositol triphosphate, JUN, LAT, LCK, LCP2, MALT1, MAP2K4, MAP3K, MAPK8, MHC Class II (complex), Nfat (family), NFkB (complex), phorbol myristate acetate, PI3K (complex), PLC gamma, POU2F1, PRKCQ, Rac, Ras, Sos, TCR, VAV, voltage-gated calcium channel, ZAP70
CD40 is a member of the tumor necrosis factor superfamily of cell surface receptors that transmits survival signals to B cells. Upon ligand binding, canonical signaling evoked by cell-surface CD40 follows a multistep cascade requiring cytoplasmic adaptors (called TNF-receptor-associated factors [TRAFs], which are recruited by CD40 in the lipid rafts) and the IKK complex. Through NF-κB activation, the CD40 signalosome activates transcription of multiple genes involved in B-cell growth and survival. Because the CD40 signalosome is active in aggressive lymphoma and contributes to tumor growth, immunotherapeutic strategies directed against CD40 are being designed and currently tested in clinical trials [Bayes 2007 and Fanale 2007).
CD40-mediated signal transduction induces the transcription of a large number of genes implicated in host defense against pathogens. This is accomplished by the activation of multiple pathways including NF-κB, MAPK and STAT3 which regulate gene expression through activation of c-Jun, ATF2 and Rel transcription factors. Receptor clustering of CD40L is mediated by an association of the ligand with p53, a translocation of ASM to the plasma membrane, activation of ASM, and formation of ceramide. Ceramide serves to cluster CD40L and several TRAF proteins (including TRAF1, TRAF2, TRAF3, TRAF5, and TRAF6) with CD40. TRAF2, TRAF3 and TRAF6 bind to CD40 directly. TRAF1 does not directly bind CD40 but is recruited to membrane micro domains through heterodimerization with TRAF2. Analogous to the recruitment of TRAF1, TRAF5 is also indirectly recruited to CD40 in a TRAF3-dependent manner. Act1 links TRAF proteins to TAK1/IKK to activate NF-κB/I-κB, and MKK complex to activate JNK, p38 MAPK and ERK1/2. NIK also plays a leading role in activating IKK. Act1-dependent CD40-mediated NF-κB activation protects cells from CD40L-induced apoptosis. On stimulation with CD40L or other inflammatory mediators, I-κB proteins are phosphorylated by IKK and NF-κB is activated through the Act1-TAK1 pathway. Phosphorylated I-κB is then rapidly ubiquitinated and degraded. The liberated NF-κB translocates to the nucleus and activates transcription. A20, which is induced by TNF inhibits NF-κB activation as well as TNF-mediated apoptosis. TRAF3 initiates signaling pathways that lead to the activation of p38 and JNK but inhibits Act1-dependent CD40-mediated NF-κB activation and initiates CD40L-induced apoptosis. TRAF2 is required for activation of SAPK pathways and also plays a role in CD40-mediated surface upregulation, IgM secretion in B-Cells and up-regulation of ICAM1. CD40 ligation by CD40L stimulates MCP1 and IL-8 production in primary cultures of human proximal tubule cells, and this occurs primarily via recruitment of TRAF6 and activation of the ERK1/2, SAPK/JNK and p38 MAPK pathways. Activation of SAPK/JNK and p38 MAPK pathways is mediated via TRAF6 whereas ERK1/2 activity is potentially mediated via other TRAF members. However, stimulation of all three MAPK pathways is required for MCP1 and IL-8 production. Other pathways activated by CD40 stimulation include the JAK3-STAT3 and PI3K-Akt pathways, which contribute to the anti-apoptotic properties conferred by CD40L to B-Cells. CD40 directly binds to JAK3 and mediates STAT3 activation followed by up-regulation of ICAM1, CD23, and LT-α.
This pathway is composed of, but not restricted to Act1, Ap1, ATF1 (includes EG:100040260), CD40, CD40LG, ERK1/2, FCER2, I kappa b kinase, ICAM1, Ikb, IkB-NfkB, JAK3, Jnk, LTA, MAP3K14, MAP3K7 (includes EG:172842), MAPKAPK2, Mek, NFkB (complex), P38 MAPK, PI3K (complex), STAT3, Stat3-Stat3, TANK, TNFAIP3, TRAF1, TRAF2, TRAF3, TRAF5, TRAF6
CD28 is a co-receptor for the TCR/CD3 and is a major positive co-stimulatory molecule. Upon ligation with CD80 and CD86, CTLA4 provides a negative co-stimulatory signal for the termination of activation. Further binding of CD28 to Class-I regulatory PI3K recruits PI3K to the membrane, resulting in generation of PIP3 and recruitment of proteins that contain a pleckstrin-homology domain to the plasma membrane, such as PIK3C3. PI3K is required for activation of Akt, which in turn regulates many downstream targets that to promote cell survival. In addition to NFAT, NF-κB has a crucial role in the regulation of transcription of the IL-2 promoter and anti-apoptotic factors. For this, PLC-γ utilizes PIP2 as a substrate to generate IP3 and DAG. IP3 elicits release of Ca2+ via IP3R, and DAG activates PKC-θ. Under the influence of RLK, PLC-γ, and Ca2+; PKC-θ regulates the phosphorylation state of IKK complex through direct as well as indirect interactions. Moreover, activation of CARMA1 phosphorylates BCL10 and dimerizes MALT1, an event that is sufficient for the activation of IKKs. The two CD28-responsive elements in the IL-2 promoter have NF-κB binding sites. NF-κB dimers are normally retained in cytoplasm by binding to inhibitory I-κBs. Phosphorylation of I-κBs initiates its ubiquitination and degradation, thereby freeing NF-κB to translocate to the nucleus. Likewise, translocation of NFAT to the nucleus as a result of calmodulin-calcineurin interaction effectively promotes IL-2 expression. Activation of Vav1 by TCR-CD28-PI3K signaling connects CD28 with the activation of Rac and CDC42, and this enhances TCR-CD3-CD28 mediated cytoskeletal re-organization. Rac regulates actin polymerization to drive lamellipodial protrusion and membrane ruffling, whereas CDC42 generates polarity and induces formation of filopodia and microspikes. CDC42 and Rac GTPases function sequentially to activate downstream effectors like WASP and PAK1 to induce activation of ARPs resulting in cytoskeletal rearrangements. CD28 impinges on the Rac/PAK1-mediated IL-2 transcription through subsequent activation of MEKK1, MKKs and JNKs. JNKs phosphorylate and activate c-Jun and c-Fos, which is essential for transcription of IL-2. Signaling through CD28 promotes cytokine IL-2 mRNA production and entry into the cell cycle, T-cell survival, T-Helper cell differentiation and Immunoglobulin isotype switching.
This pathway is composed of, but not restricted to 1,4,5-IP3, 1-phosphatidyl-D-myo-inositol 4,5-bisphosphate, Akt, Ap1, Arp2/3, BCL10, Ca2+, Calcineurin protein(s), Calmodulin, CARD11, CD28, CD3, CD3-TCR, CD4, CD80 (includes EG:12519), CD86, CDC42, CSK, CTLA4, diacylglycerol, FOS, FYN, GRAP2, GRB2, Ikb, IkB-NfkB, IKK (complex), IL2, ITK, ITPR, Jnk, JUN, LAT, LCK, LCP2, MALT1, MAP2K1/2, MAP3K1, MHC Class II (complex), Nfat (family), NFkB (complex), PAK1, PDPK1, phosphatidylinositol-3,4,5-triphosphate, PI3K (complex), PLCG1, PRKCQ, PTPRC, RAC1, SHP, SYK, TCR, VAV1, WAS, ZAP70
The ERK (extracellular-regulated kinase)/MAPK (mitogen activated protein kinase) pathway is a key pathway that transduces cellular information on meiosis/mitosis, growth, differentiation and carcinogenesis within a cell. Membrane bound receptor tyrosine kinases (RTK), which are often growth factor receptors, are the starting point for this pathway. Binding of ligand to RTK activates the intrinsic tyrosine kinase activity of RTK. Adaptor molecules like growth factor receptor bound protein 2 (GRB2), son of sevenless (SOS) and Shc form a signaling complex on tyrosine phosphorylated RTK and activate Ras. Activated Ras initiates a kinase cascade, beginning with Raf (a MAPK kinase kinase) which activates and phosphorylates MEK (a MAPK kinase); MEK activates and phosphorylates ERK (a MAPK). ERK in the cytoplasm can phosphorylate a variety of targets which include cytoskeleton proteins, ion channels/receptors and translation regulators. ERK is also translocated across into the nucleus where it induces gene transcription by interacting with transcriptional regulators like ELK-1, STAT-1 and -3, ETS and MYC. ERK activation of p90RSK in the cytoplasm leads to its nuclear translocation where it indirectly induces gene transcription through interaction with transcriptional regulators, CREB, c-Fos and SRF. RTK activation of Ras and Raf sometimes takes alternate pathways. For example, integrins activate ERK via a FAK mediated pathway. ERK can also be activated by a CAS-CRK-Rap1 mediated activation of B-Raf and a PLCγ-PKC-Ras-Raf activation of ERK.
This pathway is be composed of, but not restricted to 1,4,5-IP3, 1-phosphatidyl-D-myo-inositol 4,5-bisphosphate, 14-3-3(β,γ,θ,η,ζ), 14-3-3(η,θ,ζ), ARAF, ATF1 (includes EG:100040260), BAD, BCAR1, BRAF, c-Myc/N-Myc, cAMP-Gef, CAS-Crk-DOCK 180, Cpla2, Creb, CRK/CRKL, cyclic AMP, diacylglycerol, DOCK1, DUSP2, EIF4E, EIF4EBP1, ELK1, ERK1/2, Erk1/2 dimer, ESR1, ETS, FOS, FYN, GRB2, Histone h3, Hsp27, Integrin, KSR1, LAMTOR3, MAP2K1/2, MAPKAPK5, MKP1/2/3/4, MNK1/2, MOS, MSK1/2, NFATC1, Pak, PI3K (complex), Pka, PKC (α,β,γ,δ,ε,ι), PLC gamma, PP1/PP2A, PPARG, PTK2 (includes EG:14083), PTK2B (includes EG:19229), PXN, Rac, RAFT, Rap1, RAPGEF1, Ras, RPS6KA1 (includes EG:20111), SHC1 (includes EG:20416), Sos, SRC, SRF, Stat1/3, Talin, VRK2
Based on the findings by the method described here in the DLBCL OCI-LY1, combination of an inhibitor of components of these pathways, such as those targeting but not limited to SYK, BTK, mTOR, PI3K, Ikk, CD40, MEK, Raf, JAK, the MHC complex components, CD80, CD3 are proposed to be efficacious when used in combination with an Hsp90 inhibitor.
Examples of BTK inhibitors are PCI-32765
Examples of SYK inhibitors are R-406, 8406, R935788 (Fostamatinib disodium)
Examples of CD40 inhibitors are SGN-40 (anti-huCD40 mAb)
Examples of inhibitors of the CD28 pathway are abatacept, belatacept, blinatumomab, muromonab-CD3, visilizumab.
Example of inhibitors of major histocompatibility complex, class II are apolizumab
Example of PI3K inhibitors are 2-(1H-indazol-4-yl)-6-(4-methanesulfonylpiperazin-1-ylmethyl)-4-morpholin-4-ylthieno(3,2-d)pyrimidine, BKM120, NVP-BEZ235, PX-866, SF 1126, XL147.
Example of mTOR inhibitors are deforolimus, everolimus, NVP-BEZ235, OSI-027, tacrolimus, temsirolimus, Ku-0063794, WYE-354, PP242, OSI-027, GSK2126458, WAY-600, WYE-125132
Examples of JAK inhibitors are Tofacitinib citrate (CP-690550), AT9283, AG-490, INCB018424 (Ruxolitinib), AZD1480, LY2784544, NVP-BSK805, TG101209, TG-101348
Examples of 1kK inhibitors are SC-514, PF 184
Example of inhibitors of Raf are sorafenib, vemurafenib, GDC-0879, PLX-4720, PLX4032 (Vemurafenib), NVP-BHG712, SB590885, AZ628, ZM 336372
Example of inhibitors of SRC are AZM-475271, dasatinib, saracatinib
In the MiaPaCa2 pancreatic cancer cell line major signaling networks identified by the method were the PI3K/AKT, KIEL cell cycle-G2/M DNA damage checkpoint regulation, ERK/MAPK and the PKA signaling pathways (
Interactions between the several network component proteins are exemplified in
Pancreatic adenocarcinoma continues to be one of the most lethal cancers, representing the fourth leading cause of cancer deaths in the United States. More than 80% of patients present with advanced disease at diagnosis and therefore, are not candidates for potentially curative surgical resection. Gemcitabine-based chemotherapy remains the main treatment of locally advanced or metastatic pancreatic adenocarcinoma since a pivotal Phase III trial in 1997. Although treatment with gemcitabine does achieve significant symptom control in patients with advanced pancreatic cancer, its response rates still remain low and is associated with a median survival of approximately 6 months. These results reflect the inadequacy of existing treatment strategies for this tumor type, and a concerted effort is required to develop new and more effective therapies for patients with a pancreatic cancer.
A current review of Pub Med. literature, clinical trial database (clinicaltrials.gov), American Society of Clinical Oncology (ASCO) and American Association of Cancer Research (AACR) websites, concluded that the molecular pathogenesis of a pancreatic cancer involves multiple pathways and defined mutations, suggesting this complexity as a major reason for failure of targeted therapy in this disease. Faced with a complex mechanism of activating oncogenic pathways that regulate cellular proliferation, survival and metastasis, therapies that target a single activating molecule cannot thus, overpower the multitude of aberrant cellular processes, and may be of limited therapeutic benefit in advanced disease.
Based on the findings by the method described here in MiaPaCa2 cells, combination of an inhibitor of components of these identified pathways, such as those targeting but not limited to AKT, mTOR, PI3K, JAK, STAT3, IKK, Bcl2, PKA complex, phosphodiesterases, ERK, Raf, JNK are proposed to be efficacious when used in combination with an Hsp90 inhibitor.
Example of AKT inhibitors are PF-04691502, Triciribine phosphate (NSC-280594), A-674563, CCT128930, AT7867, PHT-427, GSK690693, MK-2206 dihydrochloride
Example of PI3K inhibitors are 2-(1H-indazol-4-yl)-6-(4-methanesulfonylpiperazin-1-ylmethyl)-4-morpholin-4-ylthieno(3,2-d)pyrimidine, BKM120, NVP-BEZ235, PX-866, SF 1126, XL147.
Example of mTOR inhibitors are deforolimus, everolimus, NVP-BEZ235, OSI-027, tacrolimus, temsirolimus, Ku-0063794, WYE-354, PP242, OSI-027, GSK2126458, WAY-600, WYE-125132
Examples of Bcl2 inhibitors are ABT-737, Obatoclax (GX15-070), ABT-263, TW-37
Examples of JAK inhibitors are Tofacitinib citrate (CP-690550), AT9283, AG-490, INCB018424 (Ruxolitinib), AZD1480, LY2784544, NVP-BSK805, TG101209, TG-101348
Examples of IkK inhibitors are SC-514, PF 184
Examples of inhibitors of phosphodiesterases are aminophylline, anagrelide, arofylline, caffeine, cilomilast, dipyridamole, dyphylline, L 869298, L-826,141, milrinonc, nitroglycerin, pentoxifylline, roflumilast, rolipram, tetomilast, theophylline, tolbutamide, amrinone, anagrelide, arofylline, caffeine, cilomilast, L 869298, L-826,141, milrinone, pentoxifylline, roflumilast, rolipram, tetomilast
Indeed, inhibitors of mTOR, which is identified by our method to potentially contribute to the transformation of MiaPaCa2 cells (
Quantitative analysis of synergy between mTOR and Hsp90 inhibitors: To determine the drug interaction between pp242 (mTOR inhibitor) and PU-H71 (Hsp90 inhibitor), the combination index (CI) isobologram method of Chou-Talalay was used as previously described. This method, based on the median-effect principle of the law of mass action, quantifies synergism or antagonism for two or more drug combinations, regardless of the mechanisms of each drug, by computerized simulation. Based on algorithms, the computer software displays median-effect plots, combination index plots and normalized isobolograms (where non constant ratio combinations of 2 drugs are used). PU-H71 (0.5, 0.25, 0.125, 0.0625, 0.03125, 0.0125 μM) and pp242 (0.5, 0.125, 0.03125, 0.0008, 0.002, 0.001 μM) were used as single agents in the concentrations mentioned or combined in a non constant ratio (PU-H71:pp242; 1:1, 1:2, 1:4, 1:7.8, 1:15.6, 1:12.5). The Fa (fraction killed cells) was calculated using the formulae Fa=1-Fu; Fu is the fraction of unaffected cells and was used for a dose effect analysis using the computer software (CompuSyn, Paramus, N.J., USA).
In a similar fashion, inhibitors of the PI3K-AKT-mTOR pathway which is identified by our method to contribute to the transformation of MDA-MB-468 cells, are more efficacious in the MDA-MB-468 breast cancer cells when combined with the Hsp90 inhibitor.
G2/M checkpoint is the second checkpoint within the cell cycle. This checkpoint prevents cells with damaged DNA from entering the M phase, while also pausing so that DNA repair can occur. This regulation is important to maintain genomic stability and prevent cells from undergoing malignant transformation. Ataxia telangiectasia mutated (ATM) and ataxia telangiectasia mutated and rad3 related (ATR) are key kinases that respond to DNA damage. ATR responds to UV damage, while ATM responds to DNA double-strand breaks (DSB). ATM and ATR activate kinases Chk1 and Chk2 which in turn inhibit Cdc25, the phosphatase that normally activates Cdc2. Cdc2, a cyclin-dependent kinase, is a key molecule that is required for entry into M phase. It requires binding to cyclin B1 for its activity. The tumor suppressor gene p53 is an important molecule in G2/M checkpoint regulation. ATM, ATR and Chk2 contribute to the activation of p53. Further, p19Arf functions mechanistically to prevent MDM2's neutralization of p53. Mdm4 is a transcriptional inhibitor of p53. DNA damage-induced phosphorylation of Mdm4 activates p53 by targeting Mdm4 for degradation. Well known p53 target genes like Gadd45 and p21 are involved in inhibiting Cdc2. Another p53 target gene, 14-3-3σ, binds to the Cdc2-cyclin B complex rendering it inactive. Repression of the cyclin B1 gene by p53 also contributes to blocking entry into mitosis. In this way, numerous checks are enforced before a cell is allowed to enter the M phase.
This pathway is composed of, but not limited to 14-3-3, 14-3-3 (β,ε,ζ), 14-3-3-Cdc25, ATM, ATM/ATR, BRCA1, Cdc2-CyclinB, Cdc2-CyclinB-Sfn, Cdc25B/C, CDK1, CDK7, CDKN1A, CDKN2A, Cdkn2a-Mdm2, CHEK1, CHEK2, CKS1B, CKS2, Cyclin B, EP300, Ep300/Pcaf, GADD45A, KAT2B, MDM2, Mdm2-Tp53-Mdm4, MDM4, PKMYT1, PLK1, PRKDC, RPRM, RPS6KA1 (includes EG:20111), Scf, SFN, Top2, TP53 (includes EG:22059), WEE1
Based on the findings by the method described here, combination of an inhibitor of components of this pathway, such as those targeting CDK1, CDK7, CHEK1, PLK1 and TOP2A(B) are proposed to be efficacious when used in combination with an Hsp90 inhibitor.
Examples of inhibitors are AQ4N, becatecarin, BN 80927, CPI-0004Na, daunorubicin, dexrazoxane, doxorubicin, elsamitrucin, epirubicin, etoposide, gatifloxacin, gemifloxacin, mitoxantrone, nalidixic acid, nemorubicin, norfloxacin, novobiocin, pixantrone, tafluposide, TAS-103, tirapazamine, valrubicin, XK469, BI2536
PU-beads also identify proteins of the DNA damage, replication and repair, homologous recombination and cellular response to ionizing radiation as Hsp90-regulated pathways in select CML, pancreatic cancer and breast cancer cells. PU-H71 synergized with agents that act on these pathways.
Specifically, among the Hsp90-regulated pathways identified in the K562 CML cells, MDA-MB-468 breast cancer cells and the Mia-PaCa-2 pancreatic cancer cells are several involved in DNA damage, replication and repair response and/or homologous recombination (Tables 3, 5a-5f). Hsp90 inhibition may synergize or be additive with agents that act on DNA damage and/or homologous recombination (i.e. potentiate DNA damage sustained post treatment with IR/chemotherapy or other agents, such as PARP inhibitors that act on the proteins that are important for the repair of double-strand DNA breaks by the error-free homologous recombinational repair pathway). Indeed, we found that PU-H71 radiosensitized the Mia-PaCa-2 human pancreatic cancer cells. We also found PU-H71 to synergize with the PARP inhibitor olaparib in the MDA-MB-468 and HCC1937 breast cancer cells (
Identification of Hsp90 clients required for tumor cell survival may also serve as tumor-specific biomarkers for selection of patients likely to benefit from Hsp90 therapy and for pharmacodynamic monitoring of Hsp90 inhibitor efficacy during clinical trials (i.e. clients in
This work substantiates and significantly extends the work of Kamal et al, providing a more sophisticated understanding of the original model in which Hsp90 in tumors is described as present entirely in multi-chaperone complexes, whereas Hsp90 from normal tissues exists in a latent, uncomplexed state (Kamal et al., 2003). We propose that Hsp90 forms biochemically distinct complexes in cancer cells (
In sum, our work uses chemical tools to provide new insights into the heterogeneity of tumor associated Hsp90 and harnesses the biochemical features of a particular Hsp90 inhibitor to identify tumor-specific biological pathways and proteins (
The CML cell lines K562, Kasumi-4, MEG-01 and KU182, triple-negative breast cancer cell line MDA-MB-468, HER2+ breast cancer cell line SKBr3, melanoma cell line SK-Mel-28, prostate cancer cell lines LNCaP and DU145, pancreatic cancer cell line Mia-PaCa-2, colon fibroblast, CCCD18Co cell lines were obtained from the American Type Culture Collection. The CML cell line KCL-22 was obtained from the Japanese Collection of Research Bioresources. The NIH-3T3 fibroblast cells were transfected as previously described (An et al., 2000). Cells were cultured in DMEM/F12 (MDA-MB-468, SKBr3 and Mia-PaCa-2), RPMI (K562, SK-Mel-28, LNCaP, DU145 and NIH-3T3) or MEM (CCD18Co) supplemented with 10% FBS, 1% L-glutamine, 1% penicillin and streptomycin. Kasumi-4 cells were maintained in IMDM supplemented with 20% FBS, 10 ng/ml Granulocyte macrophage colony-stimulating factor (GM-CSF) and 1×Pen/Strep. PBL (human peripheral blood leukocytes) and cord blood were obtained from patient blood purchased from the New York Blood Center. Thirty five ml of the cell suspension was layered over 15 ml of Ficoll-Paque plus (GE Healthcare). Samples were centrifuged at 2,000 rpm for 40 min at 4° C., and the leukocyte interface was collected. Cells were plated in RPMI medium with 10% FBS and used as indicated. Primary human blast crisis CML and AML cells were obtained with informed consent. The manipulation and analysis of specimens was approved by the University of Rochester, Weill Cornell Medical College and University of Pennsylvania Institutional Review Boards. Mononuclear cells were isolated using Ficoll-Plaque (Pharmacia Biotech, Piscataway, N.Y.) density gradient separation. Cells were cryopreserved in freezing medium consisting of Iscove's modified Dulbecco medium (IMDM), 40% fetal bovine serum (FBS), and 10% dimethylsulfoxide (DMSO) or in CryoStor™ CS-10 (Biolife). When cultured, cells were kept in a humidified atmosphere of 5% CO2 at 37° C.
Cells were lysed by collecting them in Felts Buffer (HEPES 20 mM, KCl 50 mM, MgCl2 5 mM, NP40 0.01%, freshly prepared Na2MoO4 20 mM, pH 7.2-7.3) with added 1 μg/μL of protease inhibitors (leupeptin and aprotinin), followed by three successive freeze (in dry ice) and thaw steps. Total protein concentration was determined using the BCA kit (Pierce) according to the manufacturer's instructions.
The Hsp90 antibody (H9010) or normal IgG (Santa Cruz Biotechnology) was added at a volume of 10 μL to the indicated amount of cell lysate together with 40 μL of protein G agarose beads (Upstate), and the mixture incubated at 4° C. overnight. The beads were washed five times with Felts lysis buffer and separated by SDS-PAGE, followed by a standard western blotting procedure.
Hsp90 inhibitors beads or Control beads, containing an Hsp90 inactive chemical (ethanolamine) conjugated to agarose beads, were washed three times in lysis buffer. Unless otherwise indicated, the bead conjugates (80 μL) were then incubated at 4° C. with the indicated amounts of cell lysates (120-500 μg), and the volume was adjusted to 200 μL with lysis buffer. Following incubation, bead conjugates were washed 5 times with the lysis buffer and proteins in the pull-down analyzed by Western blot. For depletion studies, 2-4 successive chemical precipitations were performed, followed by immunoprecipitation steps, where indicated.
Additional methods are also described herein at pages 173-183.
Table 5. (a-d) List of proteins isolated in the PU-beads pull-downs and identified as indicated in Supplementary Materials and Methods. (e) Dataset of mapped proteins used for analysis in the Ingenuity Pathway. (f) Protein regulatory networks generated by bioinformatic pathways analysis through the use of the Ingenuity Pathways Analysis (IPA) software. Proteins listed in Table 5e were analyzed by IPA.
elegans)
pombe)
Drosophila)
The Hsp90 inhibitors, the solid-support immobilized and the fluorescein-labeled derivatives were synthesized as previously reported (Taldone et al., 2011, Synthesis and Evaluation of Small . . . ; Taldone et al., 2011, Synthesis and Evaluation of Fluorescent . . . ; He et al., 2006). We purchased Gleevec from LC Laboratories, AS703026 from Selleck, KN-93 from Tocris, and PP242, BMS-345541 and sodium vanadate from Sigma. All compounds were used as DMSO stocks.
Cells were either treated with PU-H71 or DMSO (vehicle) for 24 h and lysed in 50 mM Tris, pH 7.4, 150 mM NaCl and 1% NP40 lysis buffer supplemented with leupeptin (Sigma Aldrich) and aprotinin (Sigma Aldrich). Protein concentrations were determined using BCA kit (Pierce) according to the manufacturer's instructions. Protein lysates (15-200 μg) were electrophoretically resolved by SDS/PAGE, transferred to nitrocellulose membrane and probed with the following primary antibodies against: Hsp90 (1:2000, SMC-107A/B; StressMarq), Bcr-Abl (1:75, 554148; BD Pharmingen), PI3K (1:1000, 06-195; Upstate), mTOR (1:200, Sc-1549; Santa Cruz), p-mTOR (1:1000, 2971; Cell Signaling), STAT3 (1:1000, 9132; Cell Signaling), p-STAT3 (1:2000, 9145; Cell Signaling), STAT5 (1:500, Sc-835; Santa Cruz), p-STAT5 (1:1000, 9351; Cell Signaling), RICTOR (1:2000, NB100-611; Novus Biologicals), RAPTOR (1:1000, 2280; Cell Signaling), P90RSK (1:1000, 9347; Cell Signaling), Raf-1 (1:300, Sc-133; Santa Cruz), CARM1 (1:1000, 09-818; Millipore), CRKL (1:200, Sc-319; Santa Cruz), GRB2 (1:1000, 3972; Cell Signaling), FAK (1:1000, Sc-1688; Santa Cruz), BTK (1:1000, 3533; Cell Signaling), A-Raf (1:1000, 4432; Cell Signaling), PRKD2 (1:200, sc-100415, Santa Cruz), HCK (1:500, 06-833; Milipore), p-HCK (1:500, ab52203; Abeam) and β-actin (1:2000, A1978; Sigma). The membranes were then incubated with a 1:3000 dilution of a corresponding horseradish peroxidase conjugated secondary antibody. Detection was performed using the ECL-Enhanced Chemiluminescence Detection System (Amersham Biosciences) according to manufacturer's instructions.
Gels were scanned in Adobe Photoshop 7.0.1 and quantitative densitometric analysis was performed using Un-Scan-It 5.1 software (Silk Scientific).
Lysates prepared as mentioned above were first pre-cleaned by incubation with control beads overnight at 4° C. Pre-cleaned K562 cell extract (1,000 pig) in 200 μl Felts lysis buffer was incubated with PU-H71 or control-beads (80 μl) for 24 h at 4° C. Beads were washed with lysis buffer, proteins eluted by boiling in 2% SDS, separated on a denaturing gel and Coomassie stained according to manufacturer's procedure (Biorad). Gel-resolved proteins from pull-downs were digested with trypsin, as described (Winkler et al., 2002). In-gel tryptic digests were subjected to a micro-clean-up procedure (Erdjument-Bromage et al., 1998) on 2 μL bed-volume of Poros 50 R2 (Applied Biosystems—‘AB’) reversed-phase beads, packed in an Eppendorf gel-loading tip, and the eluant diluted with 0.1% formic acid (FA). Analyses of the batch purified pools were done using a QSTAR-Elite hybrid quadrupole time-of-flight mass spectrometer (QTof MS) (AB/MDS Sciex), equipped with a nano spray ion source. Peptide mixtures (in 20 μL) are loaded onto a trapping guard column (0.3×5-mm PepMap C18 100 cartridge from LC Packings) using an Eksigent nano MDLC system (Eksigent Technologies, Inc) at a flow rate of 20 μL/min. After washing, the flow was reversed through the guard column and the peptides eluted with a 5-45% MeCN gradient (in 0.1% FA) over 85 min at a flow rate of 200 nL/min, onto and over a 75-micron×15-cm fused silica capillary PepMap C18 column (LC Packings); the eluant is directed to a 75-micron (with 10-micron orifice) fused silica nano-electrospray needle (New Objective). Electrospray ionization (ESI) needle voltage was set at about 1800 V. The mass analyzer is operated in automatic, data-dependent MS/MS acquisition mode, with the threshold set to 10 counts per second of doubly or triply charged precursor ions selected for fragmentation scans. Survey scans of 0.25 sec are recorded from 400 to 1800 amu; up to 3 MS/MS scans are then collected sequentially for the selected precursor ions, recording from 100 to 1800 amu. The collision energy is automatically adjusted in accordance with the m/z value of the precursor ions selected for MS/MS. Selected precursor ions are excluded from repeated selection for 60 sec after the end of the corresponding fragmentation duty cycle. Initial protein identifications from LC-MS/MS data was done using the Mascot search engine (Matrix Science, version 2.2.04; www.matrixscience.com) and the NCBI (National Library of Medicine, NIH—human taxonomy containing, 223,695 protein sequences) and IPI (International Protein Index, EBI, Hinxton, UK—human taxonomy, containing 83,947 protein sequences) databases. One missed tryptic cleavage site was allowed, precursor ion mass tolerance=0.4 Da fragment ion mass tolerance=0.4 Da, protein modifications were allowed for Met-oxide, Cys-acrylamide and N-terminal acetylation. MudPit scoring was typically applied with ‘require bold red’ activated, and using significance threshold score p<0.05. Unique peptide counts (or ‘spectral counts’) and percent sequence coverages for all identified proteins were exported to Scaffold Proteome Software (version 2_06_01, www.proteomesoftware.com) for further bioinformatic analysis (Table 5a). Using output from Mascot, Scaffold validates, organizes, and interprets mass spectrometry data, allowing more easily to manage large amounts of data, to compare samples, and to search for protein modifications. Findings were validated in a second MS system, the Waters Xevo QTof MS instrument (Table 5d). Potential unspecific interactors were identified and removed from further analyses as indicated (Trinkle-Mulcahy et al., 2008).
Proteins were analyzed further by bioinformatic pathways analysis (Ingenuity Pathway Analysis 8.7 [IPA]; Ingenuity Systems, Mountain View, Calif., www.ingenuity.com) (Munday et al., 2010; Andersen et al., 2010). IPA constructs hypothetical protein interaction clusters based on a regularly updated “Ingenuity Pathways Knowledge Base”. The Ingenuity Pathways Knowledge Base is a very large curated database consisting of millions of individual relationships between proteins, culled from the biological literature. These relationships involve direct protein interactions including physical binding interactions, enzyme substrate relationships, and cis-trans relationships in translational control. The networks are displayed graphically as nodes (individual proteins) and edges (the biological relationships between the nodes). Lines that connect two molecules represent relationships. Thus any two molecules that bind, act upon one another, or that are involved with each other in any other manner would be considered to possess a relationship between them. Each relationship between molecules is created using scientific information contained in the Ingenuity Knowledge Base. Relationships are shown as lines or arrows between molecules. Arrows indicate the directionality of the relationship, such that an arrow from molecule A to B would indicate that molecule A acts upon B. Direct interactions appear in the network diagram as a solid line, whereas indirect interactions as a dashed line. In some cases a relationship may exist as a circular arrow or line originating from one molecule and pointing back at that same molecule. Such relationships are termed “self-referential” and arise from the ability of a molecule to act upon itself. In practice, the dataset containing the UniProtKB identifiers of differentially expressed proteins is uploaded into IPA. IPA then builds hypothetical networks from these proteins and other proteins from the database that are needed fill out a protein cluster. Network generation is optimized for inclusion of as many proteins from the inputted expression profile as possible, and aims for highly connected networks. Proteins are depicted in networks as two circles when the entity is part of a complex; as a single circle when only one unit is present; a triangle pointing up or down to describe a phosphatase or a kinase, respectively; by a horizontal oval to describe a transcription factor; and by circle to depict “other” functions. IPA computes a score for each possible network according to the fit of that network to the inputted proteins. The score is calculated as the negative base-10 logarithm of the p-value that indicates the likelihood of the inputted proteins in a given network being found together due to random chance. Therefore, scores of 2 or higher have at least a 99% confidence of not being generated by random chance alone. All the networks presented here were assigned a score of 10 or higher (Table 51).
Saturation studies were performed with 131I-PU-H71 and cells (K562, MDA-MB-468, SKBr3, LNCaP, DU-145, MRC-5 and PBL). Briefly, triplicate samples of cells were mixed with increasing amount of 131I-PU-H71 either with or without 1 μM unlabeled PU-H71. The solutions were shaken in an orbital shaker and after 1 hr the cells were isolated and washed with ice cold Tris-buffered saline using a Brandel cell harvester. All the isolated cell samples were counted and the specific uptake of 131I-PU-H71 determined. These data were plotted against the concentration of 131I-PU-H71 to give a saturation binding curve. For the quantification of PU-bound Hsp90, 9.2×107 K562 cells, 6.55×107 KCL-22 cells, 2.55×107 KU182 cells and 7.8×107 MEG-01 cells were lysed to result in 6382, 3225, 1349 and 3414 μg of total protein, respectively. To calculate the percentage of Hsp90, cellular Hsp90 expression was quantified by using standard curves created of recombinant Hsp90 purified from HeLa cells (Stressgen #ADI-SPP-770).
K562 cells were treated with Na3VO4 (1 mM) with or without PU-H71 (5 μM), as indicated. Cells were collected at indicated times and lysed in 50 mM Tris pH 7.4, 150 mM NaCl and 1% NP-40 lysis buffer, and were then subjected to western blotting procedure.
K562 cells were treated for 30 min with vehicle or PU-H71 (50 μM). Cells were collected and lysed in 50 mM Tris pH 7.4, 150 mM NaCl, 1% NP-40 lysis buffer. STAT5 protein was immunoprecipitated from 500 μg of total protein lysate with an anti-STAT5 antibody (Santa Cruz, sc-835). Protein precipitates bound to protein G agarose beads were washed with trypsin buffer (50 mM Tris pH 8.0, 20 mM CaCl2) and 33 ng of trypsin has been added to each sample. The samples were incubated at 37° C. and aliquots were collected at the indicated time points. Protein aliquots were subjected to SDS-PAGE and blotted for STAT5.
The DNA-binding capacity of STAT5a and STAT5b was assayed by an ELISA-based assay (TransAM, Active Motif, Carlsbad, Calif.) following the manufacturer instructions. Briefly, 5×106 K562 cells were treated with PU-H71 1 and 10 μM or control for 24 h. Ten micrograms of cell lysates were added to wells containing pre-adsorbed STAT consensus oligonucleotides (5′-TTCCCGGAA-3′). For control treated cells the assay was performed in the absence or presence of 20 μmol of competitor oligonucleotides that contains either a wild-type or mutated STAT consensus binding site. Interferon-treated HeLa cells (5 μg per well) were used as positive controls for the assay. After incubation and washing, rabbit polyclonal anti-STAT5a or anti-STAT5b antibodies (1:1000, Active Motif) was added to each well, followed by HPR-anti-rabbit secondary antibody (1:1000, Active Motif). After HRP substrate addition, absorbance was read at 450 nm with a reference wavelength of 655 nm (Synergy4, Biotek, Winooski, Vt.). In this assay the absorbance is directly proportional to the quantity of DNA-bound transcription factor present in the sample. Experiments were carried out in four replicates. Results were expressed as arbitrary units (AU) from the mean absorbance values with SEM.
Q-ChIP was made as previously described with modifications (Cerchietti et al., 2009). Briefly, 108 K562 cells were fixed with 1% formaldehyde, lysed and sonicated (Branson sonicator, Branson). STAT5 N20 (Santa Cruz) and Hsp90 (Zymed) antibodies were added to the pre-cleared sample and incubated overnight at 4° C. Then, protein-A or G beads were added, and the sample was eluted from the beads followed by de-crosslinking. The DNA was purified using PCR purification columns (Qiagen). Quantification of the ChIP products was performed by quantitative PCR (Applied Biosystems 7900HT) using Fast SYBR Green (Applied Biosystems). Target genes containing STAT binding site were detected with the following primers: CCND2 (5-GTTGTTCTGGTCCCTTTAATCG (SEQ ID NO:1) and 5-ACCTCGCATACCCAGAGA(SEQ ID NO:2)), MYC (5-ATGCGTTGCTGGGTTATTTT(SEQ ID NO:3) and 5-CAGAGCGTGGGATGTTAGTG(SEQ ID NO:4)) and for the intergenic control region (5-CCACCTGAGTCTGCAATGAG (SEQ ID NO:5) and 5-CAGTCTCCAGCCTTTGTTCC(SEQ ID NO:6)).
RNA was extracted from PU-H71-treated and control K562 cells using RNeasy Plus kit (Qiagen) following the manufacturer instructions. cDNA was synthesized using High Capacity RNA-to-cDNA kit (Applied Biosystems). We amplified specific genes with the following primers: MYC (5-AGAAGAGCATCTTCCGCATC (SEQ ID NO:7) and 5-CCTTTAAACAGTGCCCAAGC(SEQ ID NO:8)), CCND2 (5-TGAGCTGCTGGCTAAGATCA (SEQ ID NO:9) and 5-ACGGTACTGCTGCAGGCTAT (SEQ ID NO:10)), BCL-XL (5-CTTTTGTGGAACTCTATGGGAACA (SEQ ID NO:11) and 5-CAGCGGTTGAAGCGTTCCT (SEQ ID NO:12)), MCLI (5-AGACCTTACGACGGGTTGG (SEQ ID NO:13) and 5-ACATTCCTGATGCCACCTTC (SEQ ID NO:14)), CCND1 (5-CCTGTCCTACTACCGCCTCA (SEQ ID NO:15) and 5-GGCTTCGATCTGCTCCTG (SEQ ID NO:16)), HPRT (5-CGTCTTGCTCGAGATGTGATG (SEQ ID NO:17) and 5-GCACACAGAGGGCTACAATGTG (SEQ ID NO:18)), GAPDH (5-CGACCACTTTGTCAAGCTCA (SEQ ID NO:19) and 5-CCCTGTTGCTGTAGCCAAAT(SEQ ID NO:20)), RPLI3A (5-TGAGTGAAAGGGAGCCAGAAG (SEQ ID NO:21) and 5-CAGATGCCCCACTCACAAGA(SEQ ID NO:22)). Transcript abundance was detected using the Fast SYBR Green conditions (initial step of 20 sec at 95° C. followed by 40 cycles of 1 sec at 95° C. and 20 sec at 60° C.). The CT value of the housekeeping gene (RPLI3A) was subtracted from the correspondent genes of interest (CT). The standard deviation of the difference was calculated from the standard deviation of the CT values (replicates). Then, the CT values of the PU-H71-treated cells were expressed relative to their respective control-treated cells using the CT method. The fold expression for each gene in cells treated with the drug relative to control treated cells is determined by the expression: 2-MCT. Results were represented as fold expression with the standard error of the mean for replicates.
Transfections were carried out by electroporation (Amaxa) and the Nucleofector Solution V (Amaxa), according to manufacturer's instructions. Hsp70 knockdown studies were performed using siRNAs designed as previously reported (Powers et al., 2008) against the open reading frame of Hsp70 (HSPAIA; accession number NM_005345). Negative control cells were transfected with inverted control siRNA sequence (Hsp70C; Dharmacon RNA technologies). The active sequences against Hsp70 used for the study are Hsp70A (5′-GGACGAGUUUGAGCACAAG-3′ (SEQ ID NO:23)) and Hsp70B (5′-CCAAGCAGACGCAGAUCUU-3′ (SEQ ID NO:24)).
Sequence for the control is Hsp70C (5′-GGACGAGUUGUAGCACAAG-3 (SEQ ID NO:25)). Three million 5 cells in 2 mL media (RPMI supplemented with 1% L-glutamine, 1% penicillin and streptomycin) were transfected with 0.5 μM siRNA according to the manufacturer's instructions. Transfected cells were maintained in 6-well plates and at 84 h, lysed followed by standard Western blot procedures.
For most assays, kinase-tagged T7 phage strains were grown in parallel in 24-well blocks in an E. coli host derived from the BL21 strain. E. coli were grown to log-phase and infected with T7 phage from a frozen stock (multiplicity of infection=0.4) and incubated with shaking at 32° C. until lysis (90-150 min). The lysates were centrifuged (6,000×g) and filtered (0.2 tm) to remove cell debris. The remaining kinases were produced in HEK-293 cells and subsequently tagged with DNA for qPCR detection. Streptavidin-coated magnetic beads were treated with biotinylated small molecule ligands for 30 minutes at room temperature to generate affinity resins for kinase assays. The liganded beads were blocked with excess biotin and washed with blocking buffer (SeaBlock (Pierce), 1% BSA, 0.05% Tween 20, 1 mM DTT) to remove unbound ligand and to reduce non-specific phage binding.
Binding reactions were assembled by combining kinases, liganded affinity beads, and test compounds in Ix binding buffer (20% SeaBlock, 0.17×PBS, 0.05% Tween 20, 6 mM DTT). Test compounds were prepared as 40× stocks in 100% DMSO and directly diluted into the assay. All reactions were performed in polypropylene 384-well plates in a final volume of 0.04 ml. The assay plates were incubated at room temperature with shaking for 1 hour and the affinity beads were washed with wash buffer (Ix PBS, 0.05 Tween 20). The beads were then re-suspended in elution buffer (Ix PBS, 0.05% Tween 20, 0.5 μm non-biotinylated affinity ligand) and incubated at room temperature with shaking for 30 minutes. The kinase concentration in the eluates was measured by qPCR. KINOMEscan's selectivity score (S) is a quantitative measure of compound selectivity. It is calculated by dividing the number of kinases that bind to the compound by the total number of distinct kinases tested, excluding mutant variants. TREEspot™ is a proprietary data visualization software tool developed by KINOMEscan (Fabian et al., 2005). Kinases found to bind are marked with red circles, where larger circles indicate higher-affinity binding. The kinase dendrogram was adapted and is reproduced with permission from Science and Cell Signaling Technology, Inc.
Lentiviral constructs of shRNA knock-down of CARMI were purchased from the TRC lentiviral shRNA libraries of Openbiosystem: pLK0.1-shCARMl-KD1 (catalog No: RHS3979-9576107) and pLK0.1-shCARM1-KD2 (catalog No: RHS3979-9576108). The control shRNA (shRNA scramble) was Addgene plasmid 1864. GFP was cloned in to replace puromycin as the selection marker. Lentiviruses were produced by transient transfection of 293T as in the previously described protocol (Moffat et al., 2006). Viral supernatant was collected, filtered through a 0.45-μm filter and concentrated. K562 cells were infected with high-titer lentiviral concentrated suspensions, in the presence of 8 μg/ml polybrene (Aldrich). Transduced K562 cells were sorted for green fluorescence (GFP) after 72 hours transfection.
RNA Extraction and Quantitative Real-Time PCR (qRT-PCR)
For qRT-PCR, total RNA was isolated from 106 cells using the RNeasy mini kit (QIAGEN, Germany), and then subjected to reverse-transcription with random hexamers (SuperScript III kit, Invitrogen). Real-time PCR reactions were performed using an ABI 7500 sequence detection system. The PCR products were detected using either Sybr green I chemistry or TaqMan methodology (PE Applied Biosystems, Norwalk, Conn.). Details for real-time PCR assays were described elsewhere (Zhao et al., 2009). The primer sequences for CARMI qPCR
Viability assessment in K562 cells untransfected or transfected with CARMI shRNA or scramble was performed using Trypan Blue. This chromophore is negatively charged and does not interact with the cell unless the membrane is damaged. Therefore, all the cells that exclude the dye are viable. Apoptosis analysis was assessed using fluorescence microscopy by mixing 2 μL of acridine orange (100 μg/mL), 2 μL of ethidium bromide (100 μg/mL), and 20 μL of the cell suspension. A minimum of 200 cells was counted in at least five random fields. Live apoptotic cells were differentiated from dead apoptotic, necrotic, and normal cells by examining the changes in cellular morphology on the basis of distinctive nuclear and cytoplasmic fluorescence. Viable cells display intact plasma membrane (green color), whereas dead cells display damaged plasma membrane (orange color). An appearance of ultrastructural changes, including shrinkage, heterochromatin condensation, and nuclear degranulation, are more consistent with apoptosis and disrupted cytoplasmic membrane with necrosis. The percentage of apoptotic cells (apoptotic index) was calculated as: % Apoptotic cells=(total number of cells with apoptotic nuclei/total number of cells counted)×100. For the proliferation assay, 5×103 K562 cells were plated on a 96-well solid black plate (Corning). The assay was performed according to the manufacturer's indications (CellTiter-Glo Luminescent Cell Viability Assay, Promega). All experiments were repeated three times. Where indicated, growth inhibition studies were performed using the Alamar blue assay. This reagent offers a rapid objective measure of cell viability in cell culture, and it uses the indicator dye resazurin to measure the metabolic capacity of cells, an indicator of cell viability. Briefly, exponentially growing cells were plated in microtiter plates (Corning #3603) and incubated for the indicated times at 37° C. Drugs were added in triplicates at the indicated concentrations, and the plate was incubated for 72 h. Resazurin (55 μM) was added, and the plate read 6 h later using the Analyst GT (Fluorescence intensity mode, excitation 530 nm, emission 580 nm, with 560 nm dichroic mirror). Results were analyzed using the Softmax Pro and the GraphPad Prism softwares. The percentage cell growth inhibition was calculated by comparing fluorescence readings obtained from treated versus control cells. The IC50 was calculated as the drug concentration that inhibits cell growth by 50%.
Quantitative Analysis of Synergy Between mTOR and Hsp90 Inhibitors
To determine the drug interaction between pp242 (mTOR inhibitor) and PU-H71 (Hsp90 inhibitor), the combination index (CI) isobologram method of Chou-Talalay was used as previously described (Chou, 2006; Chou & Talalay, 1984). This method, based on the median-effect principle of the law of mass action, quantifies synergism or antagonism for two or more drug combinations, regardless of the mechanisms of each drug, by computerized simulation. Based on algorithms, the computer software displays median-effect plots, combination index plots and normalized isobolograms (where non constant ratio combinations of 2 drugs are used). PU-H71 (0.5, 0.25, 0.125, 0.0625, 0.03125, 0.0125 μM) and pp242 (0.5, 0.125, 0.03125, 0.0008, 0.002, 0.001 μM) were used as single agents in the concentrations mentioned or combined in a non constant ratio (PU-H71:pp242; 1:1, 1:2, 1:4, 1:7.8, 1:15.6, 1:12.5). The Fa (fraction killed cells) was calculated using the formulae Fa=1-Fu; Fu is the fraction of unaffected cells and was used for a dose effect analysis using the computer software (CompuSyn, Paramus, N.J., USA).
CD34 isolation—CD34+ cell isolation was performed using CD34 MicroBead Kit and the automated magnetic cell sorter autoMACS according to the manufacturer's instructions (Miltenyi Biotech, Auburn, Calif.). Viability assay—CML cells lines were plated in 48-well plates at the density of 5×105 cells/ml, and treated with indicated doses of PU-H71. Cells were collected every 24 h, stained with Annexin V-V450 (BD Biosciences) and 7-AAD (Invitrogen) in Annexin V buffer (10 mM HEPES/NaOH, 0.14 M NaCl, 2.5 mM CaCl2). Cell viability was analyzed by flow cytometry (BD Biosciences). For patient samples, primary CML cells were plated in 48-well plates at 2×106 cells/ml, and treated with indicated doses of PU-H71 for up to 96 h. Cells were stained with CD34-APC, CD38-PE-CY7 and CD45-APC-H7 antibodies (BD Biosciences) in FACS buffer (PBS, 0.05% FBS) at 4° C. for 30 min prior to Annexin V/7-AAD staining. PU-H71 binding assay—CML cells lines were plated in 48-well plates at the density of 5×105 cells/ml, and treated with 1 μM PU-H71-FITC. At 4 h post treatment, cells were washed twice with FACS buffer. To measure PU-H71-FITC binding in live cells, cells were stained with 7-AAD in FACS buffer at room temperature for 10 min, and analyzed by flow cytometry (BD Biosciences). Alternatively, cells were fixed with fixation buffer (BD Biosciences) at 4° C. for 30 min, permeabilized in Perm Buffer III (BD Biosciences) on ice for 30 min, and then analyzed by flow cytometry. At 96 h post PU-H71-FITC treatment, cells were stained with Annexin V-V450 (BD Biosciences) and 7-AAD in Annexin V buffer, and subjected to flow cytometry to measure viability. To evaluate the binding of PU-H71-FITC to leukemia patient samples, primary CML cells were plated in 48-well plates at 2×106 cells/ml, and treated with 1 μM PU-H71-FITC. At 24 h post treatment, cells were washed twice, and stained with CD34-APC, CD38-PE-CY7 and CD45-APC-H7 antibodies in FACS buffer at 4° C. for 30 min prior to 7-AAD staining. At 96 h post treatment, cells were stained with CD34-APC, CD38-PE-CY7 and CD45-APC-H7 antibodies followed by Annexin V-V450 and 7-AAD staining to measure cell viability. For competition test, CML cell lines at the density of 5×105 cells/ml or primary CML samples at the density of 2×106 cells/ml were treated with 1 μM unconjugated PU-H71 for 4 h followed by treatment of 1 μM PU-H71-FITC for 1 h. Cells were collected, washed twice, stained for 7-AAD in FACS buffer, and analyzed by flow cytometry. Hsp90 staining—Cells were fixed with fixation buffer (BD Biosciences) at 4° C. for 30 min, and permeabilized in Perm Buffer III (BD Biosciences) on ice for 30 min. Cells were stained with anti-Hsp90 phycoerythrin conjugate (PE) (F-8 clone, Santa Cruz Biotechnologies; CA) for 60 minutes. Cells were washed and then analyzed by flow cytometry. Normal mouse IgG2a-PE was used as isotype control.
Unless otherwise indicated, data were analyzed by unpaired 2-tailed t tests as implemented in GraphPad Prism (version 4; GraphPad Software). A P value of less than 0.05 was considered significant. Unless otherwise noted, data are presented as the mean±SD or mean±SEM of duplicate or triplicate replicates. Error bars represent the SD or SEM of the mean. If a single panel is presented, data are representative of 2 or 3 individual experiments.
Heat shock protein 90 (Hsp90) is an abundant molecular chaperone, the substrate proteins of which are involved in cell survival, proliferation and angiogenesis. Hsp90 is expressed constitutively and can also be induced by cellular stress, such as heat shock. Because it can chaperone substrate proteins necessary to maintain a malignant phenotype, Hsp90 is an attractive therapeutic target in cancer. In fact, inhibition of Hsp90 results in degradation of many of its substrate proteins. PUH71, an inhibitor of Hsp90, selectively inhibits the oncogenic Hsp90 complex involved in chaperoning onco-proteins and has potent anti-tumor activity diffuse large B cell lymphomas (DLBCLs). By immobilizing PUH71 on a solid support, Hsp90 complexes can be precipitated and analyzed to identify substrate onco-proteins of Hsp90, revealing known and novel therapeutic targets. Preliminary data using this method identified many components of the B cell receptor (BCR) pathway as substrate proteins of Hsp90 in DLBCL. BCR pathway activation has been implicated in lymphomagenesis and survival of DLBCLs. In addition to this, many components of the COP9 signalosome (CSN) were identified as substrates of Hsp90 in DLBCL. The CSN has been implicated in oncogenesis and activation of NF-κB, a survival mechanism of DLBCL. Based on these findings, we hypothesize that combined inhibition of Hsp90 and BCR pathway components and/or the CSN will synergize in killing DLBCL. Therefore, our specific aims are:
Immobilized PU-H71 will be used to pull down Hsp90 complexes in DLBCL cell lines to detect interactions between Hsp90 and BCR pathway components. DLBCL cell lines treated with increasing doses of PU-H71 will be analyzed for degradation of BCR pathway components DLBCL cell lines will be treated with inhibitors of BCR pathway components alone and in combination with PU-H71 and assessed for viability. Effective combination treatments will be investigated in DLBCL xenograft mouse models.
CPs and treatment with PU-H71 will validate the CSN as a substrate of Hsp90 in DLBCL cell lines. The CSN will be genetically ablated alone and in combination with PU-H71 in DLBCL cell lines to demonstrate DLBCL dependence on the CSN for survival. Mouse xenograft models will be treated with CSN inhibition, alone and in combination with PU-H71, to show effect on tumor growth and animal survival.
Immunoprecipitations (IPs) of the CSN will be used to demonstrate CSN-CBM interaction. Genetic ablation of the CSN will be used to demonstrate degradation of Bcl10 and ablation of NF-κB activity in DLBCL cell lines.
DLBCL is the most common form of non-Hodgkin's lymphoma. In order to improve diagnosis and treatment of DLBCL, many studies have attempted to classify this molecularly heterogeneous disease. One gene expression profiling study divided DLBCL into two major subtypes (Alizadeh et al., 2000). Germinal center (GC) B cell like (GCB) DLBCL can be characterized by the expression of genes important for germinal center differentiation including BCL6 and CD10, whereas activated B cell like (ABC) DLBCL can be distinguished by a gene expression profile resembling that of activated peripheral blood B cells. The NF-κB pathway is more active and often mutated in ABC DLBCL. Another classification effort using gene expression profiling identified three major classes of DLBCL. OxPhos DLBCL shows significant enrichment of genes involved in oxidative phosphorylation, mitochondrial function, and the electron transport chain. BCR/proliferation DLBCL can be characterized by an increased expression of genes involved in cell-cycle regulation. Host response (HR) DLBCL is identified based on increased expression of multiple components of the T-cell receptor (TCR) and other genes involved in T cell activation (Monti et al., 2005).
These prospective classifications were made using patient samples and have not been the final answer for diagnosis or treatment of patients. Because patient samples are comprised of heterogeneous populations of cells and tumor microenvironment plays a role in the disease, (de Jong and Enblad, 2008), DLBCL cell lines do not classify as well as patient samples. However, well-characterized cell lines can be used as models of the different subtypes of DLBCL in which to investigate the molecular mechanisms behind the disease.
Standard chemotherapy regimens such as the combination of cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) cure about 40% of DLBCL patients, with 5-year overall survival rates for GCB and ABC patients of 60% and 30%, respectively (Wright et al., 2003). The addition of rituximab immunotherapy to this treatment schedule (R-CHOP) increases survival of DLBCL patients by 10 to 15% (Coiffier et al., 2002). However, 40% of DLBCL patients do not respond to R-CHOP, and the side effects of this combination chemoimmunotherapy are not well tolerated, emphasizing the need for identifying novel targets and treatments for this disease.
Classification of patient tumors has advanced the understanding of the molecular mechanisms underlying DLBCL to a degree. Until these details are better understood, treatments cannot be individually tailored. Preclinical studies of treatments with new drugs alone and in combination treatments and the investigation of new targets in DLBCL will provide new insight on the molecular mechanisms behind the disease.
Hsp90 is an emerging therapeutic target for cancer. The chaperone protein is expressed constitutively, but can also be induced upon cellular stress, such as heat shock. Hsp90 maintains the stability of a wide variety of substrate proteins involved in cellular processes such as survival, proliferation and angiogenesis (Neckers, 2007). Substrate proteins of Hsp90 include oncoproteins such as NPM-ALK in anaplastic large cell lymphoma, and BCR-ACL in chronic myelogenous leukemia (Bonvini et al., 2002; Gone et al., 2002). Because Hsp90 maintains the stability of oncogenic substrate proteins necessary for disease maintenance, it is an attractive therapeutic target. In fact, inhibition of Hsp90 results in degradation of many of its substrate proteins (Bonvini et al., 2002; Caldas-Lopes et al., 2009; Chiosis et al., 2001; Neckers, 2007; Nimmanapalli et al., 2001). As a result, many inhibitors of Hsp90 have been developed for the clinic (Taldone et al., 2008).
A novel purine scaffold Hsp90 inhibitor, PU-H71, has been shown to have potent anti-tumor effects with an improved pharmacodynamic profile and less toxicity than other Hsp90 inhibitors (Caldas-Lopes et al., 2009; Cerchietti et al., 2010a; Chiosis and Neckers, 2006). Studies from our laboratory have shown that PU-H71 potently kills DLBCL cell lines, xenografts and ex vivo patient samples, in part, through degradation of BCL-6, a transcriptional repressor involved in DLCBL proliferation and survival (Cerchietti et al., 2010a).
A unique property of PU-H71 is its high affinity for tumor related-Hsp90, which explains why the drug been shown to accumulate preferentially in tumors (Caldas-Lopes et al., 2009; Cerchietti et al., 2010a). This property of PU-H71 makes it a useful tool in identifying novel targets for cancer therapy. By immobilizing PU-H71 on a solid support, a chemical precipitation (CP) of tumor-specific Hsp90 complexes can be obtained, and the substrate proteins of Hsp90 can be identified using a proteomics approach. Preliminary experiments using this method in DLBCL cell lines have revealed at least two potential targets that are stabilized by Hsp90 in DLBCL cells: the BCR pathway and the COP9 signalosome (CSN).
Identifying rational combination treatments for cancer is essential because single agent therapy is not curative (Table 6). Monotherapy is not effective in cancer because of tumor cell heterogeneity. Although tumors grow from a single cell, their genetic instability produces a heterogeneous population of daughter cells that are often selected for enhanced survival capacity in the form of resistance to apoptosis, reduced dependence on normal growth factors, and higher proliferative capacity (Hanahan and Weinberg, 2000). Because tumors are comprised of heterogeneous populations of cells, a single drug will kill not all cells in a given tumor, and surviving cells cause tumor relapse. Tumor heterogeneity provides an increased number of potential drug targets and therefore, the need for combining treatments.
aOne agent is curative, but a higher cure rate results with two or more.
bOne agent cures state 1 African Burkitt, but two or more are better.
indicates data missing or illegible when filed
Exposure to chemotherapeutics can give rise to resistant populations of tumor cells that can survive in the presence of drug. Avoiding this therapeutic resistance is another important rationale for combination treatments.
Combinations of drugs with non-overlapping side effects can result in additive or synergistic anti-tumor effect at lower doses of each drug, thus lowering side effects. Therefore, the possible favorable outcomes for synergism or potentiation include i) increasing the efficacy of the therapeutic effect, ii) decreasing the dosage but increasing or maintaining the same efficacy to avoid toxicity, iii) minimizing the development of drug resistance, iv) providing selective synergism against a target (or efficacy synergism) versus host. Drug combinations have been widely used to treat complex diseases such as cancer and infectious diseases for these therapeutic benefits.
Because inhibition of Hsp90 kills malignant cells and results in degradation of many of its substrate proteins, identification of tumor-Hsp90 substrate proteins may reveal additional therapeutic targets. In this study, we aim to investigate the BCR pathway and the CSN, substrates of Hsp90, in DLBCL survival as potential targets for combination therapy with Hsp90 inhibition. We predict that combined inhibition of Hsp90 and its substrate proteins will synergize in killing DLBCL, providing increased patient response with decreased toxicity.
The transcriptional repressor BCL6, a signature of GCB DLBCL gene expression, is the most commonly involved oncogene in DLBCL. BCL6 forms a transcriptional repressive complex to negatively regulate expression of genes involved in DNA damage response and plasma cell differentiation of GC B cells. BCL6 is required for B cells to undergo immunoglobulin affinity maturation (Ye et al., 1997), and somatic hypermutation in germinal centers. Aberrant constitutive expression of BCL6 (Ye et al., 1993), may lead to DLBCL as shown in animal models. A peptidomimetic inhibitor of BCL6, RIBPI, selectively kills BCL-6-dependent DLBCL cells (Cerchietti et al., 2010a; Cerchietti et al., 2009b) and is under development for the clinic.
CPs using PU-H71 beads reveal that BCL6 is a substrate protein of Hsp90 in DLBCL cell lines, and treatment with PU-H71 induces degradation of BCL6 (Cerchietti et al., 2009a) (
The BCR is a large transmembrane receptor whose ligand-mediated activation leads to an extensive downstream signaling cascade in B cells (outlined in
Signals from the BCR signalosome are transduced to extracellular signal-related kinase (ERK) family proteins through Ras and to the mitogen activated protein kinase (MAPK) family through Rac/cdc43. Activation of PLCγ causes increases in cellular calcium (Ca2+), resulting in activation of Ca2+-calmodulin kinase (CamK) and NFAT. Significantly, increased cellular Ca2+ activates PKC-β, which phosphorylates Carma1 (CARD11), an adaptor protein that forms a complex with BCL10 and MALT1. This CBM complex activates IκB kinase (IKK), resulting in phosphorylation of IκB, which sequesters NF-κB subunits in the cytosol. Phosphorylated IκB is ubiquitinylated, causing its degradation and localization of NF-κB subunits to the nucleus. Many other downstream effectors in this complex pathway (p38 MAPK, ERK1/2, CaMK) translocate to the nucleus to affect changes in transcription of genes involved in cell survival, proliferation, growth, and differentiation (NF-κB, NFAT). Syk also activates phosphatidylinositol 3-kinase (PI3K), resulting in increased cellular PIP3. This second messenger activates the acutely transforming retrovirus (Akt)/mammalian target of rapamycin (mTOR) pathway which promotes cell growth and survival (Dal Porto et al., 2004).
BCR signaling is necessary for survival and maturation of B cells (Lam et al., 1997), particularly survival signaling through NF-κB. In fact, constitutive NF-κB signaling is a hallmark of ABC DLBCL (Davis et al., 2001). Moreover, mutations in the BCR and its effectors contribute to the enhanced activity of NF-κB in DLBCL, specifically ABC DLBCL.
It has been shown that mutations in the ITAMs of the CD79a/CD79b heterodimer associated with hyperresponsive BCR activation and decreased receptor internalization in DLBCL (Davis et al., 2010). CD79 ITAM mutations also block negative regulation by Lyn kinase. Lyn phosphorylates immunoreceptor tyrosine-based inactivation motifs (ITIMs) on CD22 and the Fc γ-receptor, membrane receptors that communicate with the BCR. After docking on these phosphorylated ITIMs, SHP1 dephosphorylates CD79 ITAMs causing downmodulation of BCR signaling. Lyn also phosphorylates Syk at a negative regulatory site, decreasing its activity (Chan et al., 1997). Taken together, mutations in CD79 ITAMs, found in both ABC and GCB DLBCL, result in decreased Lyn kinase activity and increased signaling through the BCR.
Certain mutations in the BCR pathway components directly enhance NF-κB activity. Somatic mutations in the CARD11 adaptor protein result in constitutive activation of IKK causing enhanced NF-κB activity even in the absence of BCR engagement (Lenz et al., 2008). A20, a ubiquitin-editing enzyme, terminates NF-κB signaling by removing ubiquitin chains from IKK. Inactivating mutations in A20 remove this brake from NF-κB signaling in ABC DLBCL (Compagno et al., 2009).
This constitutive BCR activity in ABC DLBCL has been referred to as “chronic active BCR signaling” to distinguish it from “tonic BCR signaling.” Tonic BCR signaling maintains mature B cells and does not require CARD11 because mice deficient in CBM components have normal numbers of B cells (Thome, 2004). Chronic active BCR signaling, however, requires the CBM complex and is distinguished by prominent BCR clustering, a characteristic of antigen-stimulated B cells and not resting B cells. In fact, knockdown of CARD11, MALT1, and BCL10 is preferentially toxic for ABC as compared to GCB DLBCL cell lines (Ngo et al., 2006). Chronic active BCR signaling is associated mostly with ABC DLBCL, however CARD11 and CD79 ITAM mutations do occur in GCB DLBCL (Davis et al., 2010; Lenz et al., 2008), suggesting that BCR signaling is a potential target across subtypes of DLBCL.
Because it promotes cell growth, proliferation and survival, BCR signaling is an obvious target in cancer. Mutations in the BCR pathway in DLBCL (described above) highlight its relevance as a target in the disease. In fact, many components of the BCR have been targeted in DLBCL, and some of these treatments have already translated to patients.
Overexpression of protein tyrosine phosphatase (PTP) receptor-type 0 truncated (PTPROt), a negative regulator of Syk, inhibits proliferation and induces apoptosis in DLBCL, identifying Syk as a target in DLBCL (Chen et al., 2006). Inhibition of Syk by small molecule fostamatinib disodium (R406) blocks proliferation and induces apoptosis in DLBCL cell lines (Chen et al., 2008). This orally available compound has also shown significant clinical activity with good tolerance in DLBCL patients (Friedberg et al., 2010).
An RNA interference screen revealed Btk as a potential target in DLBCL. Short hairpin RNAs (shRNAs) targeting Btk are highly toxic for DLBCL cell lines, specifically ABC DLBCL. A small molecule irreversible inhibitor of Btk, PCI-32765 (Honigberg et al., 2010), potently kills DLBCL cell lines, specifically ABC DLBCL (Davis et al., 2010). The compound is in clinical trials and has shown efficacy in B cell malignancies with good tolerability (Fowler et al., 2010).
Constitutive activity of NF-κB makes it a rational target in DLBCL. NF-κB can be targeted through different approaches Inhibition of IKK blocks phosphorylation of IκB, preventing release and nuclear translocation of NF-κB subunits. MLX105, a selective IKK inhibitor, potently kills ABC DLBCL cell lines (Lam et al., 2005). NEDD8-activating enzyme (NAE) regulates the CRL1βTRCP ubiquitination of phosphorylated IκB, resulting in its degradation and the release of NF-κB subunits. Inhibition of NAE by small molecules such as MLN4924 induces apoptosis in ABC DLBCL and shows strong tumor burden regression in DLBCL and patient xenograft models. MLN4924 shows more potency in ABC DLBCL, which is expected because of the higher dependence on constitutive NF-κB activity for survival in this subtype (Milhollen et al., 2010). Because it activates IKK, inhibiting PKC-β is another approach to block NF-κB activity. Specific PKC-β inhibitors, such as Ly379196, kill both ABC and GCB DLBCL cell lines, albeit at high doses (Su et al., 2002).
These approaches to targeting NF-κB activity are promising therapies for DLBCL. Inhibition of IKK and NAE is most potent in ABC DLBCL, but less potent effect was also seen in GCB DLBCL. These studies suggest that combining NF-κB activity with other targeted therapies may produce a more robust effect across DLBCL subtypes.
The PI3K/Akt/mTOR pathway is deregulated in many human diseases and is constitutively activated in DLBCL (Gupta et al., 2009). Because malignant cells exploit this pathway to promote cell growth and survival, small molecule inhibitors of the pathway have been heavily researched. Rapamycin (sirolimus), a macrolide antibiotic that targets mTOR, is an FDA approved oral immunosuppressant (Yap et al., 2008). Everolimus, an orally available rapamycin analog, has also been approved as a transplant immunosuppressant (Hudes et al., 2007). These compounds have antitumor activity in DLBCL cell lines and patient samples (Gupta 2009), but their effect is mostly antiproliferative and only narrowly cytotoxic. To achieve cytotoxicity, rapamycin and everolimus have been evaluated in combination with many other therapeutic agents (Ackler et al., 2008; Yap et al., 2008). Phase II clinical studies of everolimus in DLBCL have been moderately successful with an ORR of 35% (Reeder C, 2007). Everolimus has also been shown to sensitize DLBCL cell lines to other cytotoxic agents (Wanner et al., 2006). These findings clearly demonstrate the therapeutic potential of mTOR inhibition in DLBCL, especially in combination therapies.
Inhibition of Aid is also a promising cancer therapy and can be targeted in many ways. Lipid based inhibitors block the PIP3-binding PH domain of Akt to prevent its translocation to the membrane. One such drug, perifosine, has shown antitumor activity both in vitro and in vivo.
Overall, the compound has shown only partial responses, prompting combination with other targeted therapies (Yap et al., 2008). Small molecule inhibitors of Akt, such as GSK690693, cause growth inhibition and apoptosis in lymphomas and leukemias, specifically ALL (Levy et al., 2009), and may be effective in killing DLBCL as a monotherapy or in combination with other targeted therapies.
The MAPK pathway is another interesting target in cancer therapeutics. The oncogene MCT-1 is highly expressed in DLBCL patient samples and is regulated by ERK Inhibition of ERK causes apoptosis in DLBCL xenograft models (Dai et al., 2009). Small molecule inhibitors of ERK and MEK have been developed and demonstrate excellent safety profiles and tumor suppressive activity in the clinic. The response to these drugs, however, has not been robust with four partial patient responses observed and stable disease reported in 22% of patients (Friday and Adjei, 2008) Inhibition of MEK alone may be insufficient to cause cytotoxicity because the upstream regulators of the MAPK pathway, namely Ras and Raf, are most frequently mutated in cancer and may regulate other kinases that maintain cell survival despite MEK inhibition. In the face of these pitfalls, MEK inhibitors such as AZD6244 have entered the clinic. The partial response to MEK inhibition suggests that combinations of these inhibitors with other targeted therapies may reveal a more robust patient response (Friday and Adjei, 2008).
The CSN was first discovered in Aradopsis in 1996 as a negative regulator of photomorphogenesis (Chamovitz et al., 1996). The complex is highly conserved from yeast to human and is comprised of eight subunits, CSN1-CSN8, numbered in size from largest to smallest (Deng et al., 2000). Most of the CSN subunits are more stable as part of the eight subunit holocomplex, but some smaller complexes, such as the mini-CSN, containing CSN4-7, have been reported (Oron et al., 2002; Tomoda et al., 2002). CSN5, first identified as Junactivation-domain-binding protein (Jab1), functions independently of the holo-CSN, and has been shown to interact with many cellular signaling mediators (Kato and Yoneda-Kato, 2009). The molecular constitution and functionality of these complexes are not yet clearly understood.
CSN5 and CSN6 each contain an MPR1-PAD1-N-terminal (MPN) domain, but only CSN5 contains a JAB1 MPN domain metalloenzyme motif (JAMM/MPN+ motif). The other six subunits contain a proteasome-COP9 signalosome-initiation factor 3 domain (PCI (or PINT)) (Hofmann and Bucher, 1998). Though the exact function of these domains is not yet fully understood, they bear an extremely similar homology to the lid complex of the proteasome and the eIF3 complex (Hofmann and Bucher, 1998), suggesting that the function of the CSN relates to protein synthesis and degradation.
The best characterized function of the CSN is the regulation of protein stability. The CSN regulates protein degradation by deneddylation of cullins. Cullins are protein scaffolds at the center of the ubiquitin E3 ligase. They also serve as docking sites for ubiquitin E2 conjugating enzymes and protein substrates targeted for degradation. The cullin-RING-E3 ligases (CRLs) are the largest family of ubiquitin ligases. Post-translational modification of the cullin subunit of a CRL by conjugation of Nedd8 is required for CRL activity (Chiba and Tanaka, 2004; Ohh et al., 2002). The CSN5 JAMM motif catalyzes removal of Nedd8 from CRLs; this deneddylation reaction requires an intact CSN holocomplex (Cope et al., 2002; Sharon et al., 2009). Although cullin deneddylation inactivates CRLs, the CSN is required for CRL activation (Schwechheimer and Deng, 2001), and may prevent CRL components from self-destruction by autoubiquitinylation (Peth et al., 2007).
The CSN has many other biological functions, including apoptosis and cell proliferation. Knockout of CSN components 2, 3, 5, and 8 in mice causes early embryonic death due to massive apoptosis with CSN5 knockout exhibiting the most severe phenotype (Lykke-Andersen et al., 2003; Menon et al., 2007; Tomoda et al., 2004; Yan et al., 2003). These functions may be related to the complex's role in protein stability and degradation because the phenotypes in these knockout animals parallel the phenotype of NAE knockout mice (Tateishi et al., 2001) and knockout mice of various cullins (Dealy et al., 1999; Li et al., 2002; Wang et al., 1999).
Ablation of CSN5 in thymocytes results in apoptosis as a result of increased expression of proapoptotic BCL2-associated X protein (Bax) and decreased expression of anti-apoptotic Bcl-xL protein (Panattoni et al., 2008). The interaction of CSN5 with the cyclin-dependent kinase (CDK) inhibitor p27 suggests its role in cell proliferation (Tomoda et al., 1999). CSN5 knockout thymocytes display G2 arrest (Panattoni et al., 2008), while CSN8 plays a role in T cell entry to the cell cycle from quiescence (Menon et al., 2007).
The involvement of the CSN in such cellular functions as apoptosis, proliferation and cell cycle regulation suggest that it may play a role in cancer. In fact, overexpression of CSN5 is observed in a variety of tumors (Table 7), and knockdown of CSN5 inhibits the proliferation of tumor cells (Fukumoto et al., 2006). CSN5 is also involved in myc-mediated transcriptional activation of genes involved in cell proliferation, invasion and angiogenesis (Adler et al., 2006). CSN2 and CSN3 are identified as putative tumor suppressors due to their ability to overcome senescence (Leal et al., 2008), and inhibit the proliferation of mouse fibroblasts (Yoneda-Kato et al., 2005), respectively.
indicator
with poor clinical outcome
(101)
carcinoma (53)
carcinoma (102)
squamous cell carcinoma (87)
squamous cell carcinoma (
)
and poor prognosis
(105)
with
but not disease-free survival
)
(91)
(131)
)
indicates data missing or illegible when filed
Knockdown of CSN5 in xenograft models significantly decreases tumor growth (Supriatno et al., 2005). Derivatives of the natural product curcumin inhibit the growth of pancreatic cancer cells by inhibition of CSN5 (Li et al., 2009). Taken together, these findings indicate that the CSN is a good therapeutic target in cancer.
The CSN regulates NF-κB activity differently in different cellular contexts. In TNFα-stimulated synviocytes of rheumatoid arthritis patients, knockdown of CSN5 abrogates TNFR1-ligation dependent IκBα degradation and NF-κB activation (Wang et al., 2006). Ablation of CSN subunits in TNFα-stimulated endothelial cells, however, results in stabilization of IκBα and sustained nuclear translocation of NF-κB (Schweitzer and Naumann, 2010).
Studies of the CSN in T cells demonstrate its critical role in T cell development and survival. Thymocytes from CSN5 null mice display cell cycle arrest and increased apoptosis. Importantly, these cells show accumulation of IκBα, reduced nuclear NF-κB accumulation, and decreased expression of anti-apoptotic NF-κB target genes (Panattoni et al., 2008), suggesting that CSN5 regulates T-cell activation. In fact, the CSN interacts with the CBM complex in activated T cells. T-cell activation stimulates interaction of the CSN with MALT1 and CARD11 and with BCL10 through MALT1. CSN2 and CSN5 stabilize the CBM by deubiquitinylating BCL10. Knockdown of either subunit causes rapid degradation of Bcl10 and also blocks IKK activation in TCR-stimulated T cells, suggesting that CSN may regulate NF-κB activity through this mechanism (Welteke et al., 2009).
The exact function of the CSN in NF-κB regulation is not well defined, and may differ depending on cell type. The involvement of the CSN in NF-κB regulation, particularly in T cells and through the stabilization of the CBM, suggests that it may play a role in DLBCL pathology.
CPs were performed in OCI-Ly1 and OCI-Ly7 DLBCL cell lines. Cells were lysed, and cytosolic and nuclear lysates were extracted. Lysates were incubated with either control or agarose beads coated with PUH71 overnight, then washed to remove non-specifically bound proteins. Tightly binding proteins were eluted by boiling in SDS/PAGE loading buffer, separated by SDS/PAGE and visualized by colloidal blue staining Gel lanes were cut into segments and analyzed by mass spectroscopy by our collaborators. Proteins that were highly represented (determined by number of peptides) in PUH71 pulldowns but not control pulldowns are candidate DLBCL-related Hsp90 substrate proteins. After excluding common protein contaminants and the agarose proteome, we obtained 80% overlapping putative client proteins (N=˜200) in both cell lines represented by multiple peptides. One of the pathways highly represented among PU-H71 Hsp90 clients in these experiments is the BCR pathway (23 proteins out of 200, shown in grey in
Our preliminary data identified many components of the BCR pathway as substrate proteins of Hsp90 in DLBCL. The BCR pathway has been implicated in oncogenesis and DLBCL survival. We hypothesize that combined inhibition of Hsp90 and components of the BCR pathway will synergize in killing DLBCL.
DLBCL cell lines will be maintained in culture. GCB DLBCL cell lines will include OCI-Ly1, OCI-Ly7, and Toledo. ABC DLBCL cell lines will include OCI-Ly3, OCI-Ly10, HBL-1, TMD8. Cell lines OCI-Ly1, OCT-Ly7, and OCT-Ly10 will be maintained in 90% Iscove's modified medium containing 10% FBS and supplemented with penicillin and streptomycin. Cell lines Toledo, OCI-Ly3, and HBL-1 will be grown in 90% RPMI and 10% FBS supplemented with penicillin and streptomycin, L-glutamine, and HEPES. The TMD8 cell line will be grown in medium containing 90% mem-alpha and 10% FBS supplemented with penicillin and streptomycin.
Components of the BCR pathway were identified as substrate proteins of Hsp90 in a preliminary experiment of a proteomics analysis of PU-H71 CPs in two DLBCL cell lines. To verify that the components of the BCR pathway are stabilized by Hsp90, CPs will be performed using DLBCL cell lines and analyzed by western blot using commercially available antibodies to BCR pathway components, including CD79a, CD79b, Syk, Btk, PLCγ2, AKT, mTOR, CAMKII, p38 MAPK, p40 ERK1/2, p65, Bcl-XL, Bcl6. CPs will be performed with increasing salt concentrations to show the affinity of Hsp90 for these substrate proteins. Because some proteins are expressed at low levels, nuclear/cytosolic separation of cell lysates will be performed to enrich for Hsp90 substrate proteins that are not readily detected using whole cell lysate.
Hsp90 stabilization of BCR pathway components will also be demonstrated by treatment of DLBCL cell lines with increasing doses of PU-H71. Levels of the substrate proteins listed above will be determined by western blot. Substrate proteins are expected to be degraded by exposure to PU-H71 in a dose-dependent and time-dependent manner.
Viability of DLBCL cell lines will be assessed following treatment with PU-H71 or inhibitors of BCR pathway components (Syk, Btk, PLCγ2, AKT, mTOR, p38 MAPK, p40 ERK1/2, NF-κB). Inhibitors of BCR pathway components will be selected and prioritized based on reported data in DLBCL and use in clinical trials. For example, the Melnick lab has MTAs in place to use PCI-32765 and MLN4924 (described above). Cells will be plated in 96-well plates at concentrations sufficient to keep untreated cells in exponential growth for the duration of drug treatment. Drugs will be administered in 6 different concentrations in triplicate wells for 48 hours. Cell viability will be measured with a fluorometric resazurin reduction method (CellTiter-Blue, Promega).
Fluorescence (560excitation/590emission) will be measured using the Synergy4 microplate reader in the Melnick lab (BioTek). Viability of treated cells will be normalized to appropriate vehicle controls, for example, water, in the case of PU-H71. Dose-effect curves and calculation of the drug concentration that inhibits the growth of the cell line by 50% compared to control (GI50) will be performed using CompuSyn software (Biosoft). Although many of these findings may be confirmatory of published data, instituting effective methods with these inhibitors and determining their dose-responses in our cell lines will be necessary for later combination treatment experiments demonstrating the effect of combined inhibition of Hsp90 and the BCR pathway.
Once individual dose-response curves and G150s for BCR pathway inhibitors have been established, DLBCL cells will be treated with both PU-H71 and single inhibitors of the BCR pathway to demonstrate the effect of the combination on cell killing. Experiments will be performed in 96-well plates using the conditions described above. Cells will be treated with 6 different concentrations of combination of drugs in constant ratio in triplicate with the highest dose being twice the GI50 of each drug as measured in individual dose-response experiments. Drugs will be administered in different sequences in order to determine the most effective treatment schedule: PU-H71 followed by drug X after 24 hours, drug X followed by PU-H71 after 24 hours, and PU-H71 with drug X. Viability will be determined after 48 hours using the assays mentioned above. Isobologram analysis of cell viability will be performed using Compusyn software.
Combination treatments in DLBCL cell lines proposed above will guide experiments in xenograft models in terms of dose and schedule. The drug schedules that exhibit the best cell killing effect will be translated to xenograft models. DLBCL cell lines will be injected subcutaneously into SCID mice, using two cell lines expected to respond to drug and one cell line expected not to respond as a negative control. Tumor growth will be monitored every other day until palpable (about 75-100 mm3). Animals (n=20) will be randomly divided into the following groups: control, PU-H71, BCR pathway inhibitor (drug X), and PU-H71+drug X with five animals per group. To measure drug effect on tumor growth, tumor volume will be measured with Xenogen IVIS system every other day after drug administration. After ten days, all animals will be sacrificed, and tumors will be assayed for apoptosis by TUNEL. To assess drug effect on survival, a second cohort of animals as specified above will be treated and sacrificed when tumors reach 1000 mm3 in size. Tumors will be analyzed biochemically to demonstrate that the drugs hit their targets, by ELISA for NF-κB activity or phosphorlyation of downstream targets, for example. We will perform toxicity studies established in the Melnick lab (Cerchietti et al., 2009a) in treated mice including physical examination, macro and microscopic tissue examination, serum chemistries and CBCs.
If the fluorescence assay used to detect cell viability is incompatible with some cell lines (due to acidity of media, for example) an ATP-based luminescent method (CellTiter-Glo, Promega) will be used. Also, because some drugs may not kill cells in 48 hours, higher drug doses and longer drug incubations will be performed if necessary to determine optimal drug treatments. It is possible inhibition of some BCR pathway components will not demonstrate an improved effect in killing DLBCL when combined with inhibition of Hsp90, but based on preliminary data shown above, we believe that some combinations will be more effective than either drug alone.
Our preliminary data has identified subunits of the CSN as substrate proteins of Hsp90 in DLBCL. The CSN has been implicated in cancer and may play a role in DLBCL survival. We hypothesize that DLBCL requires the CSN for survival and that combined inhibition of Hsp90 and the CSN will synergize in killing DLBCL.
Expression of CSN subunits in DLBCL cell lines (described above) will be verified. DLBCL cell lines will be lysed for protein harvest and analyzed by SDS-PAGE and western blotting using commercially available antibodies to the CSN subunits and actin as a loading control.
The CSN was identified as a substrate protein of Hsp90 in a preliminary proteomics analysis of PU-H71 CPs in two DLBCL cell lines. To verify that Hsp90 stabilizes the CSN, CPs will be performed as described above using DLBCL cell lines and analyzed by western blot. Hsp90 stabilization of the CSN will also be demonstrated by treatment of DLBCL cell lines with increasing PU-H71 concentration. Protein levels of CSN subunits will be determined by western blot. CSN subunits are expected to be degraded upon exposure to PU-H71 in a dose-dependent and time-dependent manner.
DLBCL cells lines will be infected with lentiviral pLKO.1 vectors containing short hairpin (sh)RNAs targeting CSN2 or CSN5 and selected by puromycin resistance. These vectors are commercially available through the RNAi Consortium. These subunits will be used because knockdown of one CSN subunit can affect expression of other CSN subunits (Menon et al., 2007; Schweitzer et al., 2007; Schweitzer and Naumann, 2010), and knockdown of CSN2 ablates formation of the CSN holocomplex. CSN5 knockdown will be used because this subunit contains the enzymatic domain of the CSN. A pool of 3 to 5 shRNAs will be tested against each target to obtain the sequence with optimal knockdown of the target protein. Empty vector and scrambled shRNAs will be used as controls. Because we predict that knockdown of CSN subunits will kill DLBCL cells, and we aim to measure cell viability, tetracycline (tet) inducible constructs will be used. This method may also allow us to establish conditions for dose-dependent knockdown of CSN subunits using a titration of shRNA induction. Knockdown efficiency will be assessed by western blot following infection and tet induction. Cells will be assessed for viability using the methods described in Aim 1 following infection. We predict that knockdown the CSN will kill DLBCLs, and ABC DLBCLs are expected to depend on the CSN for survival more than GCB DLBCLs because of the CSN's role in stabilizing the CBM complex.
Following CSN monotherapy experiments in DLBCL, induction of CSN knockdown will be combined with PU-H71 treatment in DLBCL cell lines. shRNA constructs that demonstrate effective dose dependent CSN knock down in 48 hours (as evaluated in earlier experiments) will be used in order to perform 48 hour cell viability experiments. Control shRNAs as described above will be used. Control cells and cells infected with tet-inducible shRNA constructs targeting CSN subunits will be treated with different doses of tet and PU-H71 in constant ratio in triplicate. Drugs will be administered in different sequences in order to determine the most effective treatment schedule: PU-H71 followed by tet, tet followed by PU-H71, and PU-H71 with tet. Cell viability will be measured as described in Aim 1. Combined inhibition of the CSN and Hsp90 is expected to synergize in killing DLBCL, specifically ABC DLBCL.
Combined inhibition of the CSN and Hsp90 in DLBCL cell lines proposed above will guide experiments in xenograft models. The most effective combination of PU-H71 and CSN knockdown from in vitro experiments will be used in xenograft experiments. Control and inducible-knockout-CSN DLBCL cells will be used for xenograft, using two cell lines expected to respond to treatment and one cell line expected not to respond to treatment as a negative control. Animals will be treated with vehicle, PU-H71, or tet, using the dose and schedule of the most effective combination of PU-H71 and tet as determined by in vitro experiments. Tumor growth, animal survival and toxicity will be assayed as described in Aim 1.
Accomplishing dose-dependent knockdown of the CSN by titration of tetracycline induction may prove difficult. If this occurs, in order to demonstrate proof of principle, shRNAs with different knockdown efficiencies will be used to simulate increasing inhibition of the CSN as a monotherapy and in combination with different doses of PU-H71.
Since the CSN has been shown to interact with the CBM complex and activate IKK in stimulated T-cells, we hypothesize that the CSN interacts with the CBM, stabilizes Bcl10, and activates NF-κB in DLBCL.
DLBCL cell lysates will be incubated with an antibody to CSN1 that effectively precipitates the whole CSN complex (da Silva Correia et al., 2007; Wei and Deng, 1998). Precipitated CSN1 complexes will be separated by SDS-PAGE and analyzed for interaction with CBM components by western blot using commercially available antibodies to the different components of the CBM: CARD11, BCL10, and MALT1. Based on reported experiments in T cells, we expect the CSN to interact preferentially with CARD11 and MALT1 in ABC DLBCL cell lines as opposed to GCB DLBCL cell lines because of the chronic active BCR signaling in ABC DLBCL.
Because the CSN, specifically CSN5, has been shown to regulate Bcl10 stability and degradation in activated T-cells, we hypothesize that the CSN stabilizes Bcl10 in DLBCL. DLBCL cells lines will be infected with short hairpin (sh)RNAs targeting CSN subunits as described above. Cells will be treated with tet to induce CSN subunit knockdown and Bcl10 protein levels in infected and induced cells will be quantified by western blot. We expect Bcl10 levels to be degraded with CSN subunit knockdown in a dose-dependent and time-dependent manner. To demonstrate that reduction in Bcl10 protein is not a result of cell death, cell viability will be measured by counting viable cells with Trypan blue before cell lysis. CSN subunit knockdown will be combined with proteasome inhibition to demonstrate that Bcl10 degradation is a specific effect of CSN ablation.
Knockdown of CSN2 or CSN5 is expected to abrogate NF-κB activity in DLBCL cell lines. Using DLBCL cell lines infected with control shRNAs or shRNAs to CSN2 or CSN5, control and infected cells will be assayed for NF-κB activity in several ways. First, lysates will be analyzed by western blot to determine levels of IκBα protein. Second, nuclear translocation of the NF-κB subunits p65 and c-Rel will be measured by western blot of nuclear and cytosolic fractions of lysed cells or by plate-based EMSA of nuclei from control and infected cells. Finally, NF-κB target gene expression of these cells will be evaluated at the transcript and protein level by quantitative PCR of cDNA prepared by reverse transcriptase PCR (RT-PCR) and western blot, respectively.
Because the CSN was shown to interact with the CBM in TCR-stimulated T cells, we predict that the CSN interacts with the CBM in DLBCL, especially in ABC DLBCL because this subtype exhibits chronic active BCR signaling. If CSN-CBM interaction is not apparent in DLBCL, then cells will be stimulated with IgM in order to activate the BCR pathway and stimulate formation of the CBM. To determine the kinetics of the CSN interaction with the CBM, cellular IPs as described above will be performed over a time course from the point of IgM stimulation. To correlate CSN-CBM interaction with the kinetics of CBM formation, BCL10 IP will be performed to demonstrate BCL10-CARD11 interaction over the same time course.
The development of PU-H71 as a new therapy for DLBCL is promising, but combination treatments are likely to be more potent and less toxic. PU-H71 can also be used as a tool to identify substrate proteins of Hsp90. In experiments using this method, the BCR pathway and the CSN were identified as substrates of Hsp90 in DLBCL.
The BCR plays a role in DLBCL oncogenesis and survival, and efforts to target components of this pathway have been successful. We predict that combining PU-H71 and inhibition of BCR pathway components will be a more potent and less toxic treatment approach. Identified synergistic combinations in cells and xenograft models will be evaluated for translation to clinical trials, and ultimately advance patient treatment toward rationally designed targeted therapy and away from chemotherapy.
The CSN has been implicated in cancer and NF-κB activation, indicating that it may be a good target in DLBCL. We hypothesize that the CSN stabilizes the CBM complex, promoting NF-κB activation and DLBCL survival. Therefore, we predict that combined inhibition of Hsp90 and the CSN will synergize in killing DLBCL. These studies will act as proof of principle that new therapeutic targets can be identified using the proteomics approach described in this proposal.
Future studies will identify compounds that target the CSN, and ultimately bring CSN inhibitors to the clinic as an innovative therapy for DLBCL. Determining downstream effects of CSN inhibition, such as CBM stabilization and NF-κB activation may reveal new opportunities for additional combinatorial drug regimens of three drugs. Future studies will evaluate combinatorial regimens of three drugs inhibiting Hsp90, the CSN and its downstream targets together.
The most effective drug combinations with PU-H71 found in this study will be performed using other Hsp90 inhibitors in clinical development such as 17-DMAG to demonstrate the broad clinical applicability of identified effective drug combinations.
DLBCL, the most common form of non-Hodgkins lymphoma, is an aggressive disease that remains without cure. The studies proposed herein will advance the understanding of the molecular mechanisms behind DLBCL and improve patient therapy.
Here, we report on the design and synthesis of molecules based on purine, purine-like isoxazole and indazol-4-one chemical classes attached to Affi-Gel® 10 beads (
1H and 13C NMR spectra were recorded on a Bruker 500 MHz instrument. Chemical shifts were reported in δ values in ppm downfield from TMS as the internal standard. 1H data were reported as follows: chemical shift, multiplicity (s=singlet, d=doublet, t=triplet, q=quartet, br=broad, m=multiplet), coupling constant (Hz), integration. 13C chemical shifts were reported in δ values in ppm downfield from TMS as the internal standard. Low resolution mass spectra were obtained on a Waters Acquity Ultra Performance LC with electrospray ionization and SQ detector. High-performance liquid chromatography analyses were performed on a Waters Autopurification system with PDA, MicroMass ZQ and ELSD detector and a reversed phase column (Waters X-Bridge C18, 4.6×150 mm, 5 μm) using a gradient of (a) H2O+0.1% TFA and (b) CH3CN+0.1% TFA, 5 to 95% b over 10 minutes at 1.2 mL/min. Column chromatography was performed using 230-400 mesh silica gel (EMD). All reactions were performed under argon protection. Affi-Gel® 10 beads were purchased from Bio-Rad (Hercules, Calif.). EZ-Link® Amine-PEO3-Biotin was purchased from Pierce (Rockford, Ill.). PU-H71 (He et al., 2006) and NVP-AUY922 (Brough et al., 2008) were synthesized according to previously published methods. GM was purchased from Aldrich.
1 (He et al., 2006) (0.500 g, 1.21 mmol) was dissolved in DMF (15 mL). Cs2CO3 (0.434 g, 1.33 mmol) and 1,3-dibromopropane (1.22 g, 0.617 mL, 6.05 mmol) were added and the mixture was stirred at rt for 45 minutes. Then additional Cs2CO3 (0.079 g, 0.242 mmol) was added and the mixture was stirred for 45 minutes. Solvent was removed under reduced pressure and the resulting residue was chromatographed (CH2Cl2:MeOH:AcOH, 120:1:0.5 to 80:1:0.5) to give 0.226 g (35%) of 2 as a white solid. 1H NMR (CDCl3/MeOH-d4) δ 8.24 (s, 1H), 7.38 (s, 1H), 7.03 (s, 1H), 6.05 (s, 2H), 4.37 (t, J=7.1 Hz, 2H), 3.45 (t, J=6.6 Hz, 2H), 2.41 (m, 2H); MS (ESI): m/z 534.0/536.0 [M+H]+.
1,6-diaminohexane (10 g, 0.086 mol) and Et3N (13.05 g, 18.13 mL, 0.129 mol) were suspended in CH2Cl2 (300 mL). A solution of di-tert-butyl dicarbonate (9.39 g, 0.043 mol) in CH2Cl2 (100 mL) was added dropwise over 90 minutes at rt and stirring continued for 18 h. The reaction mixture was added to a separatory funnel and washed with water (100 mL), brine (100 mL), dried over Na2SO4 and concentrated under reduced pressure. The resulting residue was chromatographed [CH2Cl2:MeOH-NH3 (7N), 70:1 to 20:1] to give 7.1 g (76%) of 3. 1H NMR (CDCl3) δ 4.50 (br s, 1H), 3.11 (br s, 2H), 2.68 (t, J=6.6 Hz, 2H), 1.44 (s, 13H), 1.33 (s, 4H); MS (ESI): m/z 217.2 [M+H]+.
2 (0.226 g, 0.423 mmol) and 3 (0.915 g, 4.23 mmol) in DMF (7 mL) was stirred at rt for 24 h. The reaction mixture was concentrated and the residue chromatographed [CHCl3:MeOH:MeOH-NH3 (7N), 100:7:3] to give 0.255 g (90%) of 4. 1H NMR (CDCl3) δ 8.32 (s, 1H), 7.31 (s, 1H), 6.89 (s, 1H), 5.99 (s, 2H), 5.55 (br s, 2H), 4.57 (br s, 1H), 4.30 (t, J=7.0 Hz, 2H), 3.10 (m, 2H), 2.58 (t, J=6.7 Hz, 2H), 2.52 (t, J=7.2 Hz, 2H), 1.99 (m, 2H), 1.44 (s, 13H), 1.30 (s, 4H); 13C NMR (125 MHz, CDCl3) δ 156.0, 154.7, 153.0, 151.6, 149.2, 149.0, 146.3, 127.9, 120.1, 119.2, 112.4, 102.3, 91.3, 79.0, 49.8, 46.5, 41.8, 40.5, 31.4, 29.98, 29.95, 28.4, 27.0, 26.7; HRMS (ESI) m/z [M+H]+ calcd. for C26H37IN7O4S, 670.1673; found 670.1670; HPLC: tR=7.02 min.
4 (0.310 g, 0.463 mmol) was dissolved in 15 mL of CH2Cl2:TFA (4:1) and the solution was stirred at rt for 45 min. Solvent was removed under reduced pressure and the residue chromatographed [CH2Cl2:MeOH-NH3 (7N), 20:1 to 10:1] to give 0.37 g of a white solid. This was dissolved in water (45 mL) and solid Na2CO3 added until pH-12. This was extracted with CH2Cl2 (4×50 mL) and the combined organic layers were washed with water (50 mL), dried over Na2SO4, filtered and concentrated under reduced pressure to give 0.200 g (76%) of 5. 1H NMR (CDCl3) δ 8.33 (s, 1H), 7.31 (s, 1H), 6.89 (s, 1H), 5.99 (s, 2H), 5.52 (br s, 2H), 4.30 (t, J=6.3 Hz, 2H), 2.68 (t, J=7.0 Hz, 2H), 2.59 (t, J=6.3 Hz, 2H), 2.53 (t, J=7.1 Hz, 2H), 1.99 (m, 2H), 1.44 (s, 4H), 1.28 (s, 4H); 13C NMR (125 MHz, CDCl3/MeOH-d4) δ 154.5, 152.6, 151.5, 150.0, 149.6, 147.7, 125.9, 119.7, 119.6, 113.9, 102.8, 94.2, 49.7, 46.2, 41.61, 41.59, 32.9, 29.7, 29.5, 27.3, 26.9; HRMS (ESI) m/z [M+H]+ calcd. for C21H29IN7O2S, 570.1148; found 570.1124; HPLC: tR=5.68 min.
4 (0.301 g, 0.45 mmol) was dissolved in 15 mL of CH2Cl2:TFA (4:1) and the solution was stirred at rt for 45 min. Solvent was removed under reduced pressure and the residue dried under high vacuum overnight. This was dissolved in DMF (12 mL) and added to 25 mL of Affi-Gel 10 beads (prewashed, 3×50 mL DMF) in a solid phase peptide synthesis vessel. 225 μL of N,N-diisopropylethylamine and several crystals of DMAP were added and this was shaken at rt for 2.5 h. Then 2-methoxyethylamine (0.085 g, 97 μl, 1.13 mmol) was added and shaking was continued for 30 minutes. Then the solvent was removed and the beads washed for 10 minutes each time with CH2Cl2:Et3N (9:1, 4×50 mL), DMF (3×50 mL), Felts buffer (3×50 mL) and i-PrOH (3×50 mL). The beads 6 were stored in i-PrOH (beads: i-PrOH (1:2), v/v) at −80° C.
2 (4.2 mg, 0.0086 mmol) and EZ-Link® Amine-PEO3-Biotin (5.4 mg, 0.0129 mmol) in DMF (0.2 mL) was stirred at rt for 24 h. The reaction mixture was concentrated and the residue chromatographed [CHCl3:MeOH-NH3 (7N), 5:1] to give 1.1 mg (16%) of 7. 1H NMR (CDCl3) δ 8.30 (s, 1H), 8.10 (s, 1H), 7.31 (s, 1H), 6.87 (s, 1H), 6.73 (br s, 1H), 6.36 (br s, 1H), 6.16 (br s, 2H), 6.00 (s, 2H), 4.52 (m, 1H), 4.28-4.37 (m, 3H), 3.58-3.77 (m, 10H), 3.55 (m, 2H), 3.43 (m, 2H), 3.16 (m, 1H), 2.92 (m, 1H), 2.80 (m, 2H), 2.72 (m, 1H), 2.66 (m, 2H), 2.17 (t, J=7.0 Hz, 2H), 2.04 (m, 2H), 1.35-1.80 (m, 6H); MS (ESI): m/z 872.2 [M+H]+.
AcOH (0.26 g, 0.25 mL, 4.35 mmol) was added to a mixture of 8 (Brough et al., 2008) (0.5 g, 0.87 mmol), 3 (0.56 g, 2.61 mmol), NaCNBH3 (0.11 g, 1.74 mmol), CH2Cl2 (21 mL) and 3 Å molecular sieves (3 g). The reaction mixture was stirred for 1 h at rt. It was then concentrated under reduced pressure and chromatographed [CH2Cl2:MeOH-NH3 (7N), 100:1 to 60:1] to give 0.50 g (75%) of 9. 1H NMR (CDCl3) δ 7.19-7.40 (m, 12H), 7.12-7.15 (m, 2H), 7.08 (s, 1H), 6.45 (s, 1H), 4.97 (s, 2H), 4.81 (s, 2H), 3.75 (s, 2H), 3.22 (m, 2H), 3.10 (m, 3H), 2.60 (t, J=7.1 Hz, 2H), 1.41-1.52 (m, 13H), 1.28-1.35 (m, 4H), 1.21 (t, J=7.2 Hz, 3H), 1.04 (d, J=6.9 Hz, 6H); MS (ESI): m/z 775.3 [M+H]+.
To a solution of 9 (0.5 g, 0.646 mmol) in CH2Cl2 (20 mL) was added a solution of BCl3 (1.8 mL, 1.87 mmol, 1.0 M in CH2Cl2) and this was stirred at rt for 10 h. Saturated NaHCO3 was added and CH2Cl2 was evaporated under reduced pressure. The water was carefully decanted and the remaining yellow precipitate was washed a few times with EtOAc and CH2Cl2 to give 0.248 g (78%) of 10. 1H NMR (CDCl3/MeOH-d4) δ 7.32 (d, J=8.1 Hz, 2H), 7.24 (d, J=8.1 Hz, 2H), 6.94 (s, 1H), 6.25 (s, 1H), 3.74, (s, 2H), 3.41 (q, J=7.3 Hz, 2H), 3.08 (m, 1H), 2.65 (t, J=7.1 Hz, 2H), 2.60 (t, J=7.1 Hz, 2H), 1.40-1.56 (m, 4H), 1.28-1.35 (m, 4H), 1.21 (t, J=7.3 Hz, 3H), 1.01 (d, J=6.9 Hz, 6H); 13C NMR (125 MHz, CDCl3/MeOH-d4) δ 168.4, 161.6, 158.4, 157.6, 155.2, 139.0, 130.5, 129.5, 128.71, 128.69, 127.6, 116.0, 105.9, 103.6, 53.7, 49.2, 41.8, 35.0, 32.7, 29.8, 27.6, 27.2, 26.4, 22.8, 14.5; HRMS (ESI) m/z [M+H]′ calcd. for C28H39N4O4, 495.2971; found 495.2986; HPLC: tR=6.57 min.
10 (46.4 mg, 0.094 mmol) was dissolved in DMF (2 mL) and added to 5 mL of Affi-Gel 10 beads (prewashed, 3×8 mL DMF) in a solid phase peptide synthesis vessel. 45 μl of N,N-diisopropylethylamine and several crystals of DMAP were added and this was shaken at rt for 2.5 h. Then 2-methoxyethylamine (17.7 mg, 21 μl, 0.235 mmol) was added and shaking was continued for 30 minutes. Then the solvent was removed and the beads washed for 10 minutes each time with CH2Cl2 (3×8 mL), DMF (3×8 mL), Felts buffer (3×8 mL) and i-PrOH (3×8 mL). The beads 11 were stored in i-PrOH (beads: i-PrOH, (1:2), v/v) at −80° C.
10.00 g (71.4 mmol) of dimedone (13), 13.8 g (74.2 mmol) of tosyl hydrazide (12) and p-toluene sulfonic acid (0.140 g, 0.736 mmol) were suspended in toluene (600 mL) and this was refluxed with stirring for 1.5 h. While still hot, the reaction mixture was filtered and the solid was washed with toluene (4×100 mL), ice-cold ethyl acetate (2×200 mL) and hexane (2×200 mL) and dried to give 19.58 g (89%) of 14 as a solid. TLC (100% EtOAc) Rf=0.23; 1H NMR (DMSO-d6) δ 9.76 (s, 1H), 8.65 (br s, 1H), 7.69 (d, J=8.2 Hz, 2H), 7.41 (d, J=8.1 Hz, 2H), 5.05 (s, 1H), 2.39 (s, 3H), 2.07 (s, 2H), 1.92 (s, 2H), 0.90 (s, 6H); MS (ESI): m/z 309.0 [M+H]+.
To 5.0 g (16.2 mmol) of 14 in THF (90 mL) and Et3N (30 mL) was added trifluoroacetic anhydride (3.4 g, 2.25 mL, 16.2 mmol) in one portion. The resulting red solution was heated at 55° C. for 3 h. After cooling to rt, methanol (8 mL) and 1M NaOH (8 mL) were added and the solution was stirred for 3 h at rt. The reaction mixture was diluted with 25 mL of saturated NH4Cl, poured into a separatory funnel and extracted with EtOAc (3×50 mL). The combined organic layers were washed with brine (3×50 mL), dried over Na2SO4 and concentrated under reduced pressure to give a red oily residue which was chromatographed (hexane:EtOAc, 80:20 to 60:40) to give 2.08 g (55%) of 15 as an orange solid. TLC (hexane:EtOAc, 6:4) Rf=0.37; 1H NMR (CDCl3) δ 2.80 (s, 2H), 2.46 (s, 2H), 1.16 (s, 6H); MS (ESI): m/z 231.0 [M−H]−.
To a mixture of 15 (0.100 g, 0.43 mmol) and NaH (15.5 mg, 0.65 mmol) in DMF (8 mL) was added 2-bromo-4-fluorobenzonitrile (86 mg, 0.43 mmol) and heated at 90° C. for 5 h. The reaction mixture was concentrated under reduced pressure and the residue chromatographed (hexane:EtOAc, 10:1 to 10:2) to give 0.162 g (91%) of 16 as a white solid. 1H NMR (CDCl3) δ 7.97 (d, J=2.1 Hz, 1H), 7.85 (d, J=8.4 Hz, 1H), 7.63 (dd, J=8.4, 2.1 Hz, 1H), 2.89 (s, 2H), 2.51 (s, 2H), 1.16 (s, 6H); MS (ESI): m/z 410.0/412.0 [M−H]−.
A mixture of 16 (0.200 g, 0.485 mmol), NaOtBu (93.3 mg, 0.9704 mmol), Pd2(dba)3 (88.8 mg, 0.097 mmol) and DavePhos (38 mg, 0.097 mmol) in 1,2-dimethoxyethane (15 mL) was degassed and flushed with argon several times. trans-1,4-Diaminocyclohexane (0.166 g, 1.456 mmol) was added and the flask was again degassed and flushed with argon before heating the reaction mixture at 50° C. overnight. The reaction mixture was concentrated under reduced pressure and the residue purified by preparatory TLC (CH2Cl2:MeOH-NH3 (7N), 10:1) to give 52.5 mg (24%) of 17. Additionally, 38.5 mg (17%) of amide 18 was isolated for a total yield of 41%. 1H NMR (CDCl3) δ 7.51 (d, J=8.3 Hz, 1H), 6.81 (d, J=1.8 Hz, 1H), 6.70 (dd, J=8.3, 1.8 Hz, 1H), 4.64 (d, J=7.6 Hz, 1H), 3.38 (m, 1H), 2.84 (s, 2H), 2.81 (m, 1H), 2.49 (s, 2H), 2.15 (d, J=11.2 Hz, 2H), 1.99 (d, J=11.0 Hz, 2H), 1.25-1.37 (m, 4H), 1.14 (s, 6H); MS (ESI): m/z 446.3 [M+H]+.
A solution of 17 (80 mg, 0.18 mmol) in DMSO (147 μl), EtOH (590 μl), 5N NaOH (75 μl) and H2O2 (88 μl) was stirred at rt for 3 h. The reaction mixture was concentrated under reduced pressure and the residue purified by preparatory TLC [CH2Cl2:MeOH-NH3 (7N), 10:1] to give 64.3 mg (78%) of 18. 1H NMR (CDCl3) δ 8.06 (d, J=7.5 Hz, 1H), 7.49 (d, J=8.4 Hz, 1H), 6.74 (d, J=1.9 Hz, 1H), 6.62 (dd, J=8.4, 2.0 Hz, 1H), 5.60 (br s, 2H), 3.29 (m, 1H), 2.85 (s, 2H), 2.77 (m, 1H), 2.49 (s, 2H), 2.13 (d, J=11.9 Hz, 2H), 1.95 (d, J=11.8 Hz, 2H), 1.20-1.42 (m, 4H), 1.14 (s, 6H); MS (ESI): m/z 464.4 [M+H]+; HPLC: tR=7.05 min.
To a mixture of 18 (30 mg, 0.0647 mmol) in CH2Cl2 (1 ml) was added 6-(Boc-amino)caproic acid (29.9 mg, 0.1294 mmol), EDCI (24.8 mg, 0.1294 mmol) and DMAP (0.8 mg, 0.00647 mmol). The reaction mixture was stirred at rt for 2 h then concentrated under reduced pressure and the residue purified by preparatory TLC [hexane:CH2Cl2:EtOAc:MeOH-NH3 (7N), 2:2:1:0.5] to give 40 mg (91%) of 19. 1H NMR (CDCl3/MeOH-d4) δ 7.63 (d, J=8.4 Hz, 1H), 6.75 (d, J=1.7 Hz, 1H), 6.61 (dd, J=8.4, 2.0 Hz, 1H), 3.75 (m, 1H), 3.31 (m, 1H), 3.06 (t, J=7.0 Hz, 2H), 2.88 (s, 2H), 2.50 (s, 2H), 2.15 (m, 4H), 2.03 (d, J=11.5 Hz, 2H), 1.62 (m, 2H), 1.25-1.50 (m, 17H), 1.14 (s, 6H); 13C NMR (125 MHz, CDCl3/MeOH-d4) δ 191.5, 174.1, 172.3, 157.2, 151.5, 150.3, 141.5, 140.6 (q, J=39.4 Hz), 130.8, 120.7 (q, J=268.0 Hz), 116.2, 114.2, 109.5, 107.3, 79.5, 52.5, 50.7, 48.0, 40.4, 37.3, 36.4, 36.0, 31.6, 31.3, 29.6, 28.5, 28.3, 25.7, 25.4; HRMS (ESI) m/z [M+Na]+ calcd. for C34H47F3N6O5Na, 699.3458; found 699.3472; HPLC: tR=9.10 min.
19 (33 mg, 0.049 mmol) was dissolved in 1 mL of CH2Cl2:TFA (4:1) and the solution was stirred at rt for 45 min. Solvent was removed under reduced pressure and the residue purified by preparatory TLC [CH2Cl2:MeOH-NH3 (7N), 6:1] to give 24 mg (86%) of 20. 1H NMR (CDCl3/MeOH-d4) δ 7.69 (d, J=8.4 Hz, 1H), 6.78 (d, J=1.9 Hz, 1H), 6.64 (dd, J=8.4, 1.9 Hz, 1H), 3.74 (m, 1H), 3.36 (m, 1H), 2.92 (t, J=7.5 Hz, 2H), 2.91 (s, 2H), 2.51 (s, 2H), 2.23 (t, J=7.3 Hz, 2H), 2.18 (d, J=10.2 Hz, 2H), 2.00 (d, J=9.1 Hz, 2H), 1.61-1.75 (m, 4H), 1.34-1.50 (m, 6H), 1.15 (s, 6H); 13C NMR (125 MHz, MeOH-d4) δ 191.2, 173.6, 172.2, 151.8, 149.7, 141.2, 139.6 (q, J=39.5 Hz), 130.3, 120.5 (q, J=267.5 Hz), 115.5, 114.1, 109.0, 106.8, 51.6, 50.0, 47.8, 39.0, 36.3, 35.2, 35.1, 31.0, 30.5, 26.8, 26.7, 25.4, 24.8; HRMS (ESI) m/z [M+H]+ calcd. for C29H40F3N6O3, 577.3114; found 577.3126; HPLC: tR=7.23 min.
19 (67 mg, 0.0992 mmol) was dissolved in 3.5 mL of CH2Cl2:TFA (4:1) and the solution was stirred at rt for 20 min. Solvent was removed under reduced pressure and the residue dried under high vacuum for two hours. This was dissolved in DMF (2 mL) and added to 5 mL of Affi-Gel 10 beads (prewashed, 3×8 mL DMF) in a solid phase peptide synthesis vessel. 45 μl of N,N-diisopropylethylamine and several crystals of DMAP were added and this was shaken at rt for 2.5 h. Then 2-methoxyethylamine (18.6 mg, 22 μl, 0.248 mmol) was added and shaking was continued for 30 minutes. Then the solvent was removed and the beads washed for 10 minutes each time with CH2Cl2 (3×8 mL), DMF (3×8 mL) and i-PrOH (3×8 mL). The beads 21 were stored in i-PrOH (beads: i-PrOH, (1:2), v/v) at −80° C.
To a solution of trans-4-aminocyclohexanol hydrochloride (2.0 g, 13.2 mmol) in dioxane:water (26:6.5 mL) was added Et3N (1.08 g, 1.49 mL, 10.7 mmol) and this was stirred for 10 min. Then Fmoc-OSu (3.00 g, 8.91 mmol) was added over five minutes and the resulting suspension was stirred at rt for 2 h. The reaction mixture was concentrated to −5 mL, then some CH2Cl2 was added. This was filtered and the solid was washed with H2O (4×40 mL) then dried to give 2.85 g (95%) of 22 as a white solid. Additional 0.100 g (3%) of 22 was obtained by extracting the filtrate with CH2Cl2 (2×100 mL), drying over Na2SO4, filtering and removing solvent for a combined yield of 98%. TLC (hexane:EtOAc, 20:80) Rf=0.42; 1H NMR (CDCl3) δ 7.77 (d, J=7.5 Hz, 2H), 7.58 (d, J=7.4 Hz, 2H), 7.40 (t, J=7.4 Hz, 2H), 7.31 (t, J=7.4 Hz, 2H), 4.54 (br s, 1H), 4.40 (d, J=5.6 Hz, 2H), 4.21 (t, J=5.6 Hz, 1H), 3.61 (m, 1H), 3.48 (m, 1H), 1.9-2.1 (m, 4H), 1.32-1.48 (m, 2H), 1.15-1.29 (m, 2H); MS (ESI): m/z 338.0 [M+H]′.
1.03 g (3.05 mmol) of 22 and 0.998 g (1.08 mL, 11.86 mmol) of 3,4-dihydro-2H-pyran (DHP) was suspended in dioxane (10 mL). Pyridinium p-toluenesulfonate (0.153 g, 0.61 mmol) was added and the suspension stirred at rt. After 1 hr additional DHP (1.08 mL, 11.86 mmol) and dioxane (10 mL) were added and stirring continued. After 9 h additional DHP (1.08 mL, 11.86 mmol) was added and stirring continued overnight. The resulting solution was concentrated and the residue chromatographed (hexane:EtOAc, 75:25 to 65:35) to give 1.28 g (100%) of 23 as a white solid. TLC (hexane:EtOAc, 70:30) Rf=0.26; 1H NMR (CDCl3) δ 7.77 (d, J=7.5 Hz, 2H), 7.58 (d, J=7.5 Hz, 2H), 7.40 (t, J=7.4 Hz, 2H), 7.31 (dt, J=7.5, 1.1 Hz, 2H), 4.70 (m, 1H), 4.56 (m, 1H), 4.40 (d, J=6.0 Hz, 2H), 4.21 (t, J=6.1 Hz, 1H), 3.90 (m, 1H), 3.58 (m, 1H), 3.45-3.53 (m, 2H), 1.10-2.09 (m, 14H); MS (ESI): m/z 422.3 [M+H]+.
1.28 g (3.0 mmol) of 23 was dissolved in CH2Cl2 (20 mL) and piperidine (2 mL) was added and the solution stirred at rt for 5 h. Solvent was removed and the residue was purified by chromatography [CH2Cl2:MeOH-NH3 (7N), 80:1 to 30:1] to give 0.574 g (96%) of 24 as an oily residue which slowly crystallized. 1H NMR (CDCl3) δ 4.70 (m, 1H), 3.91 (m, 1H), 3.58 (m, 1H), 3.49 (m, 1H), 2.69 (m, 1H), 1.07-2.05 (m, 14H); MS (ESI): m/z 200.2 [M+H]+.
A mixture of 16 (0.270 g, 0.655 mmol), NaOtBu (0.126 g, 1.31 mmol), Pd2(dba)3 (0.120 g, 0.131 mmol) and DavePhos (0.051 g, 0.131 mmol) in 1,2-dimethoxyethane (20 mL) was degassed and flushed with argon several times. 24 (0.390 g, 1.97 mmol) was added and the flask was again degassed and flushed with argon before heating the reaction mixture at 60° C. for 3.5 h. The reaction mixture was concentrated under reduced pressure and the residue purified by preparatory TLC [hexane:CH2Cl2:EtOAc:MeOH-NH3 (7N), 7:6:3:1.5] to give 97.9 mg (28%) of 25. Additionally, 60.5 mg (17%) of amide 26 was isolated for a total yield of 45%. 1H NMR (CDCl3) δ 7.52 (d, J=8.3 Hz, 1H), 6.80 (d, J=1.7 Hz, 1H), 6.72 (dd, J=8.3, 1.8 Hz, 1H), 4.72 (m, 1H), 4.67 (d, J=7.6 Hz, 1H), 3.91 (m, 1H), 3.68 (m, 1H), 3.50 (m, 1H), 3.40 (m, 1H), 2.84 (s, 2H), 2.49 (s, 2H), 2.06-2.21 (m, 4H), 1.30-1.90 (m, 10H), 1.14 (s, 6H); MS (ESI): m/z 529.4 [M−H]−.
A solution of 25 (120 mg, 0.2264 mmol) in DMSO (220 μl), EtOH (885 μl), 5N NaOH (112 μl) and H2O2 (132 μl) was stirred at rt for 4 h. Then 30 mL of brine was added and this was extracted with EtOAc (5×15 mL), dried over Na2SO4, filtered and concentrated under reduced pressure. The residue was purified by preparatory TLC [hexane:CH2Cl2:EtOAc:MeOH-NH3 (7N), 7:6:3:1.5] to give 102 mg (82%) of 26. 1H NMR (CDCl3) δ 8.13 (d, J=7.4 Hz, 1H), 7.50 (d, J=8.4 Hz, 1H), 6.74 (d, J=1.9 Hz, 1H), 6.63 (dd, J=8.4, 2.0 Hz, 1H), 5.68 (br s, 2H), 4.72 (m, 1H), 3.91 (m, 1H), 3.70 (m, 1H), 3.50 (m, 1H), 3.34 (m, 1H), 2.85 (s, 2H), 2.49 (s, 2H), 2.05-2.19 (m, 4H), 1.33-1.88 (m, 10H), 1.14 (s, 6H); MS (ESI): m/z 547.4 [M−H]−.
26 (140 mg, 0.255 mmol) and pyridinium p-toluenesulfonate (6.4 mg, 0.0255 mmol) in EtOH (4.5 mL) was heated at 65° C. for 17 h. The reaction mixture was concentrated under reduced pressure and the residue purified by preparatory TLC [hexane:CH2Cl2:EtOAc:MeOH-NH3 (7N), 2:2:1:0.5] to give 101 mg (85%) of SNX-2112. 1H NMR (CDCl3) δ 8.10 (d, J=7.4 Hz, 1H), 7.52 (d, J=8.4 Hz, 1H), 6.75 (d, J=1.3 Hz, 1H), 6.60 (dd, J=8.4, 1.6 Hz, 1H), 5.97 (br s, 2H), 3.73 (m, 1H), 3.35 (m, 1H), 2.85 (s, 2H), 2.48 (s, 2H), 2.14 (d, J=11.8 Hz, 2H), 2.04 (d, J=11.1 Hz, 2H), 1.33-1.52 (m, 4H), 1.13 (s, 6H); 13C NMR (125 MHz, CDCl3/MeOH-d4) δ 191.0, 171.9, 151.0, 150.0, 141.3, 140.3 (q, J=39.6 Hz), 130.4, 120.3 (q, J=270.2 Hz), 115.9, 113.7, 109.2, 107.1, 69.1, 52.1, 50.2, 40.1, 37.0, 35.6, 33.1, 30.2, 28.0; MS (ESI): m/z 463.3 [M−H]−, 465.3 [M+H]+; HPLC: tR=7.97 min.
DMF (8.5 mL) was added to 20 mL of Affi-Gel 10 beads (prewashed, 3×40 mL DMF) in a solid phase peptide synthesis vessel. 2-Methoxyethylamine (113 mg, 129 μL, 1.5 mmol) and several crystals of DMAP were added and this was shaken at rt for 2.5 h. Then the solvent was removed and the beads washed for 10 minutes each time with CH2Cl2 (4×35 mL), DMF (3×35 mL), Felts buffer (2×35 mL) and i-PrOH (4×35 mL). The beads were stored in i-PrOH (beads: i-PrOH (1:2), v/v) at −80° C.
For the competition studies, fluorescence polarization (FP) assays were performed as previously reported (Du et al., 2007). Briefly, FP measurements were performed on an Analyst GT instrument (Molecular Devices, Sunnyvale, Calif.). Measurements were taken in black 96-well microtiter plates (Corning #3650) where both the excitation and the emission occurred from the top of the wells. A stock of 10 μM GM-cy3B was prepared in DMSO and diluted with Felts buffer (20 mM Hepes (K), pH 7.3, 50 mM KCl, 2 mM DTT, 5 mM MgCl2, 20 mM Na2MoO4, and 0.01% NP40 with 0.1 mg/mL BGG). To each 96-well were added 6 nM fluorescent GM (GM-cy3B), 3 ng SKBr3 lysate (total protein), and tested inhibitor (initial stock in DMSO) in a final volume of 100 μL HFB buffer. Drugs were added in triplicate wells. For each assay, background wells (buffer only), tracer controls (free, fluorescent GM only) and bound GM controls (fluorescent GM in the presence of SKBr3 lysate) were included on each assay plate. GM was used as positive control. The assay plate was incubated on a shaker at 4° C. for 24 h and the FP values in mP were measured. The fraction of tracer bound to Hsp90 was correlated to the mP value and plotted against values of competitor concentrations. The inhibitor concentration at which 50% of bound GM was displaced was obtained by fitting the data. All experimental data were analyzed using SOFTmax Pro 4.3.1 and plotted using Prism 4.0 (Graphpad Software Inc., San Diego, Calif.).
The leukemia cell lines K562 and MV4-11 and the breast cancer cell line MDA-MB-468 were obtained from the American Type Culture Collection. Cells were cultured in RPMI (K562), in Iscove's modified Dulbecco's media (MV4-11) or in DME/F12 (MDA-MB-468) supplemented with 10% FBS, 1% L-glutamine, 1% penicillin and streptomycin, and maintained in a humidified atmosphere of 5% CO2 at 37° C. Cells were lysed by collecting them in Felts buffer (HEPES 20 mM, KCl 50 mM, MgCl2 5 mM, NP40 0.01%, freshly prepared Na2MoO4 20 mM, pH 7.2-7.3) with added 10 μg/μL of protease inhibitors (leupeptin and aprotinin), followed by three successive freeze (in dry ice) and thaw steps. Total protein concentration was determined using the BCA kit (Pierce) according to the manufacturer's instructions.
Hsp90 inhibitor beads or control beads containing an Hsp90 inactive chemical (2-methoxyethylamine) conjugated to agarose beads were washed three times in lysis buffer. The bead conjugates (80 μL or as indicated) were then incubated overnight at 4° C. with cell lysates (250 μg), and the volume was adjusted to 200-300 μL with lysis buffer. Following incubation, bead conjugates were washed 5 times with the lysis buffer and analyzed by Western blot, as indicated below.
For treatment with PU-H71, cells were grown to 60-70% confluence and treated with inhibitor (5 μM) for 24 h. Protein lysates were prepared in 50 mM Tris pH 7.4, 150 mM NaCl and 1% NP-40 lysis buffer.
For Western blotting, protein lysates (10-50 μg) were electrophoretically resolved by SDS/PAGE, transferred to nitrocellulose membrane and probed with a primary antibody against Hsp90 (1:2000, SMC-107A/B, StressMarq), anti-IGF-IR (1:1000, 3027, Cell Signaling) and anti-c-Kit (1:200, 612318, BD Transduction Laboratories). The membranes were then incubated with a 1:3000 dilution of a corresponding horseradish peroxidase conjugated secondary antibody. Detection was performed using the ECL-Enhanced Chemiluminescence Detection System (Amersham Biosciences) according to manufacturer's instructions.
To detect the binding of PU-H71 to cell surface Hsp90, MV4-11 cells at 500,000 cells/ml were incubated with the indicated concentrations of PU-H71-biotin or D-biotin as control for 2 h at 37° C. followed by staining of phycoerythrin (PE) conjugated streptavidin (SA) (BD Biosciences) in FACS buffer (PBS+0.5% FBS) at 4° C. for 30 min. Cells were then analyzed using the BD-LSRII flow cytometer. Mean fluorescence intensity (MFI) was used to calculate the binding of PU-H71-biotin to cells and values were normalized to the MFI of untreated cells stained with SA-PE.
Molecular docking computations were carried out on a HP workstation xw8200 with the Ubuntu 8.10 operating system using Glide 5.0 (Schrodinger). The coordinates for the Hsp90a complexes with bound inhibitor PU-H71 (PDB ID: 2FWZ), NVP-AUY922 (PDB ID: 2VCI) and 27 (PDB ID: 3D0B) were downloaded from the RCSB Protein Data Bank. For docking experiments, compounds PU-H71, NVP-AUY922, 5, 10, 20 and 27 were constructed using the fragment dictionary of Maestro 8.5 and geometry-optimized using the Optimized Potentials for Liquid Simulations-All Atom (OPLS-AA) force field (Jorgensen et al., 1996) with the steepest descent followed by truncated Newton conjugate gradient protocol as implemented in Macromodel 9.6, and were further subjected to ligand preparation using default parameters of LigPrep 2.2 utility provided by Schrödinger LLC. Each protein was optimized for subsequent grid generation and docking using the Protein Preparation Wizard provided by Schrödinger LLC. Using this tool, hydrogen atoms were added to the proteins, bond orders were assigned, water molecules of crystallization not deemed to be important for ligand binding were removed, and the entire protein was minimized. Partial atomic charges for the protein were assigned according to the OPLS-2005 force field. Next, grids were prepared using the Receptor Grid Generation tool in Glide. With the respective bound inhibitor in place, the centroid of the workspace ligand was chosen to define the grid box. The option to dock ligands similar in size to the workspace ligand was selected for determining grid sizing.
Next, the extra precision (XP) Glide docking method was used to flexibly dock compounds PU-H71 and 5 (to 2FWZ), NVP-AUY922 and 10 (to 2VCI), and 20 and 27 (to 3D0B) into their respective binding site. Although details on the methodology used by Glide are described elsewhere (Patel et al., 2008; Friesner et al., 2004; Halgren et al., 2004), a short description about parameters used is provided below. The default setting of scale factor for van der Waals radii was applied to those atoms with absolute partial charges less than or equal to 0.15 (scale factor of 0.8) and 0.25 (scale factor of 1.0) electrons for ligand and protein, respectively. No constraints were defined for the docking runs. Upon completion of each docking calculation, at most 100 poses per ligand were allowed to generate. The top-scored docking pose based on the Glide scoring function (Eldridge et al., 1997) was used for our analysis. In order to validate the XP Glide docking procedure the crystallographic bound inhibitor (PU-H71 or NVP-AUY922 or 27) was extracted from the binding site and re-docked into its respective binding site. There was excellent agreement between the localization of the inhibitor upon docking and the crystal structure as evident from the 0.098 Å (2FWZ), 0.313 Å (2VC1) and 0.149 Å (3D0B) root mean square deviations. Thus, the present study suggests the high docking reliability of Glide in reproducing the experimentally observed binding mode for Hsp90 inhibitors and the parameter set for the Glide docking reasonably reproduces the X-ray structure.
The inventions described herein were made, at least in part, with support from Grant No. ROI CA 155226 from the National Cancer Institute, Department of Health and Human Services; and the U.S. Government has rights in any such subject invention.
| Number | Date | Country | |
|---|---|---|---|
| 61480198 | Apr 2011 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 16713111 | Dec 2019 | US |
| Child | 17006359 | US | |
| Parent | 14113779 | Jun 2014 | US |
| Child | 16713111 | US |
