Patent Grant
10900086
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 on Dec. 8, 2016, is named 48289-528001WO1 ST25.txt and is 328,192 bytes in size.
Prostate cancer, also known as carcinoma of the prostate, is the development of cancer in the prostate, a gland in the male reproductive system. Prostate cancer cells may also metastasize from the prostate to other parts of the body, e.g., the bones and/or lymph nodes. Prior to the invention described herein, studies within human prostate cancer cohorts were challenging due to the complexity in characterizing genomic changes in epithelium separately from the surrounding microenvironment (i.e., stroma) and the lack of statistical tools to assess and quantify cross-talk across the epithelial and stromal compartments. As such, there is a pressing need to identify more effective diagnostic, prognostic, and treatment methods for prostate cancer.
The invention is based upon the identification of a gene expression signature (i.e., a “bone homing signature”) that predicts the likelihood that prostate cancer will metastasize, e.g., to bone. In some aspects, the invention relates to methods, arrays and kits for diagnosing and monitoring prostate cancer and cancer metastases.
Provided is a method of determining whether prostate cancer in a subject, e.g., a human subject, will metastasize, e.g., to bone, comprising obtaining a test sample from a subject having or at risk of developing prostate cancer; determining the expression level of at least one prostate cancer-associated gene in the test sample; comparing the expression level of the prostate cancer-associated gene in the test sample with the expression level of the prostate cancer-associated gene in a reference sample; and determining that the prostate cancer in the subject will metastasize if the expression level of the prostate cancer-associated gene in the test sample is differentially expressed as compared to the level of the prostate cancer-associated gene in the reference sample.
Alternatively, the expression level of the prostate cancer-associated gene in the test sample is compared with a threshold expression level of the prostate cancer-associated gene (e.g., a “cut-off level”). The method involves determining whether prostate cancer in the subject will metastasize, e.g., to the bone, if the expression level of the prostate cancer-associated gene in the test sample is differentially expressed as compared to the threshold expression level of the prostate cancer-associated gene. In some cases, the threshold expression level of each gene is determined and compared individually. Alternatively, the threshold expression level is a combined score computed from the expression of each gene in the “bone homing signature.”
In another case, the expression level of the prostate cancer-associated gene in the test sample is compared with an expression level of a housekeeping gene within the test sample. The method involves determining whether prostate cancer in the subject will metastasize, e.g., to the bone, if the expression level of the prostate cancer-associated gene in the test sample is differentially expressed as compared to the expression level of the housekeeping gene. A suitable housekeeping genes includes glyceraldehyde 3-phosphate dehydrogenase (GAPDH). In some cases, the expression level of a housekeeping gene is utilized for normalization purposes.
The expression level of the prostate cancer-associated gene in the test sample is differentially expressed as compared to the level of the prostate cancer-associated gene in the reference sample, the threshold expression level, or the expression level of a housekeeping gene. For example, the expression level of the prostate cancer-associated gene in the test sample is upregulated (i.e., increased) by at least 2 fold, at least 3 fold, at least 4 fold, at least 5 fold, at least 6 fold, at least 7 fold, at least 8 fold, at least 9 fold, at least 10 fold, at least 15 fold, at least 20 fold, at least 25 fold, at least 30 fold, at least 35 fold, at least 40 fold, at least 45 fold, at least 50 fold, at least 60 fold, at least 70 fold, at least 80 fold, at least 90 fold, at least 100 fold, at least 125 fold, at least 150 fold, at least 175 fold, at least 200 fold, at least 250 fold, at least 300 fold, at least 350 fold, at least 400 fold, at least 500 fold, at least 600 fold, at least 700 fold or at least 800 fold as compared to the level of the prostate cancer-associated gene in the reference sample, the threshold expression level, or the expression level of a housekeeping gene.
Alternatively, the expression level of the prostate cancer-associated gene in the test sample is downregulated (i.e., decreased) by at least 2 fold, at least 3 fold, at least 4 fold, at least 5 fold, at least 6 fold, at least 7 fold, at least 8 fold, at least 9 fold, at least 10 fold, at least 15 fold, at least 20 fold, at least 25 fold, at least 30 fold, at least 35 fold, at least 40 fold, at least 45 fold, at least 50 fold, at least 60 fold, at least 70 fold, at least 80 fold, at least 90 fold, at least 100 fold, at least 125 fold, at least 150 fold, at least 175 fold, at least 200 fold, at least 250 fold, at least 300 fold, at least 350 fold, at least 400 fold, at least 500 fold, at least 600 fold, at least 700 fold or at least 800 fold as compared to the level of the prostate cancer-associated gene in the reference sample, the threshold expression level, or the expression level of a housekeeping gene.
For example, the prostate cancer-associated gene comprises adipocyte enhancer-binding protein 1 (AEBP1), anthrax toxin receptor 1 (ANTXR1), biglycan (BGN), complement component 1, q subcomponent, A chain (C1QA), complement component 1, q subcomponent, B chain (C1QB), complement component 1, q subcomponent, C chain (C1QC), complement component 1, R subcomponent (C1R), complement component 1, s subcomponent (C1S), cadherin 11 (CDH11), collagen type I (COL1A1), collagen type III alpha 1 chain (COL3A1), fibulin 5 (FBLN5), Fc Fragment of IgG Receptor IIb (receptor for CD32; FCGR2B), major histocompatibility complex, class II, DR Beta 1 (HLA-DRB1), lumican (LUM), monooxygenase, DBH-like 1 (MOXD1), proline/arginine-rich end leucine-rich repeat protein (PRELP), ribonuclease 1 (RNASE1), secreted frizzled related protein 2 (SFRP2), secreted frizzled related protein 4 (SFRP4), sulfatase 1 (SULF1), thrombospondin 2 (THBS2), Thy-1 cell surface antigen (THY1), or Thymosin Beta 4, X-Linked (TMSB4X); and it is determined that the prostate cancer in the subject will metastasize if the expression level of the prostate cancer-associated gene in the test sample is higher than the level of the prostate cancer-associated gene in the reference sample.
In another example, the prostate cancer-associated gene comprises activated leukocyte cell adhesion molecule (ALCAM), lumican (LUM), collagen type I alpha 1 chain (COL1A1), biglycan (BGN), complement component 1, q subcomponent, C chain (C1QC), complement component 1, s subcomponent (C1S), complement component 1, q subcomponent, B chain (C1QB), histocompatibility leukocyte antigen-DRB3 (HLA-DRB3), adipocyte enhancer-binding protein 1 (AEBP1), secreted frizzled related protein 4 (SFRP4), fibulin 5 (FBLN5), Fc fragment of IgG, low affinity IIC, receptor for CD32 (FCGR2C), complement component 1, q subcomponent, A chain (C1QA), secreted frizzled related protein 2 (SFRP2), sulfatase 1 (SULF1), thrombospondin 2 (THBS2), monooxygenase, DBH-like 1 (MOXD1), serpin peptidase inhibitor, Glade G (C1 inhibitor), member 1 (SERPING1), proline/arginine-rich end leucine-rich repeat protein (PRELP), cluster of differentiation 52 (CD52), latent transforming growth factor beta binding protein 2 (LTBP2), integrin, alpha 11 (ITGA11), or tensin 3 (TNS3); and it is determined that the prostate cancer in the subject will metastasize if the expression level of the prostate cancer-associated gene in the test sample is higher than the level of the prostate cancer-associated gene in the reference sample.
In some cases, the prostate cancer-associated gene comprises protein tyrosine phosphatase-like A domain containing 1 (PTPLAD1) or myelin and lymphocyte protein, T-cell differentiation protein 2 (MAL2); and it is determined that the prostate cancer in the subject will metastasize if the expression level of the prostate cancer-associated gene in the test sample is higher than the level of the prostate cancer-associated gene in the reference sample.
Alternatively, the prostate cancer-associated gene comprises chromosome 12 open reading frame 51 (C12orf51), transmembrane protein 205 (TMEM205), heat shock 70 kDa protein 9 (HSPA9), claudin 8 (CLDN8); and it is determined that the prostate cancer in the subject will metastasize if the expression level of the prostate cancer-associated gene in the test sample is higher than the level of the prostate cancer-associated gene in the reference sample.
Alternatively, the genes described herein are associated with an immune response. For example, an immune response gene panel includes C1S, C1QA, C1QB, C1QC, SERPING1, FCGR2C, CD52, and HLA-DRB3.
In another example, the genes described herein are associated with the extracellular matrix. For example, the extracellular matrix gene panel includes SFRP2, SULF1, COL1A1, ITGA11, Biglycan, LTBP3, Fibulin-5, Biglycan proteoglycan and Lumacin.
In some examples, the genes include a bone-related subset of genes. For example, the bone-related subset of genes includes PRELP, LTBP2, FBLN5, ITGA11, COL1A1, ALCAM, SFRP2, TNS3, SULF1, BGN, and THBS2.
In another example, the prostate cancer-associated gene comprises ALCAM, LUM, COL1A1, BGN, C1QC, C1S, C1QB, HLA-DRB3, AEBP1, SFRP4, FBLN5, FCGR2C, C1QA, SFRP2, SULF1, THBS2, MOXD1, SERPING1, PRELP, CD52, LTBP2, ITGA11, TNS3, C12orf51, TMEM205, HSPA9, CLDN8, PTPLAD1, and MAL2; and it is determined that the prostate cancer in the subject will metastasize if the expression level of ALCAM, LUM, COL1A1, BGN, C1QC, C1S, C1QB, HLA-DRB3, AEBP1, SFRP4, FBLN5, FCGR2C, C1QA, SFRP2, SULF1, THBS2, MOXD1, SERPING1, PRELP, CD52, LTBP2, ITGA11, TNS3 in the test sample is higher than the level of the prostate cancer-associated gene in the reference sample, and if the expression level of C12orf51, TMEM205, HSPA9, CLDN8, PTPLAD1, and MAL2 in the test sample is higher than the level of the prostate cancer-associated gene in the reference sample.
In some aspects, the number of predictive prostate cancer-associated genes comprises 29 genes, i.e., 29 of the genes described herein. In other aspects, the number of predictive genes is at least 1 gene; e.g., at least 2 genes, at least 3 genes, at least 4 genes, at least 5 genes, at least 6 genes, at least 7 genes, at least 8 genes, at least 9 genes, at least 10 genes, at least 11 genes, at least 12 genes, at least 13 genes, at least 14 genes, at least 15 genes, at least 16 genes, at least 17 genes, at least 18 genes, at least 19 genes, at least 20 genes, at least 21 genes, at least 22 genes, at least 23 genes, at least 24 genes, at least 25 genes, at least 26 genes, at least 27 genes, or at least 28 genes of the genes described herein.
For example, the expression level of the prostate cancer-associated gene is detected via an Affymetrix Gene Array hybridization chip for transcriptome analysis. Alternatively, a real time reverse transcriptase polymerase chain reaction (real time RT-PCR) assay may be used to validate the genes in other tissues. In another aspect, the expression level of the prostate cancer-associate gene is detected via next-generation sequencing, ribonucleic acid sequencing (RNA-seq), immunohistochemistry, or immunofluorescence.
In one aspect, the subject is identified as having Gleason 6 grade prostate cancer or Gleason 8 or higher grade prostate cancer with the methods described herein. For example, the subject is identified as having Gleason grade 9 prostate cancer, or Gleason grade 10 prostate cancer. In some cases, the subject is identified as having Gleason grade 7 prostate cancer.
In some cases, the test sample is obtained from prostate stromal (benign, high grade PIN (hgPIN), or tumor) tissue, prostate gland (benign, hgPIN, or tumor) tissue from patients having undergone radical prostatectomy or from patients who have not had radical prostatectomy. Preferably, the sample comprises ribonucleic acid (RNA) or deoxyribonucleic acid (DNA). Suitable reference samples were obtained from healthy normal control prostate stromal tissue, benign prostate stromal tissue from patients having undergone cystoprostatectomy and were confirmed not to have prostate cancer. Other suitable types of samples include a plasma sample and a blood sample.
In one aspect, the subject has relapsed with prostate cancer or is at risk of relapsing with prostate cancer. Identifying a relapsed subject who is likely to develop prostate cancer metasteses will enable timely prevention/treatment strategies.
Optionally, the subject has undergone a radical prostatectomy. In other cases, the methods further comprise performing a radical prostatectomy on the subject after determining whether the prostate cancer will metastasize, e.g., to bone. In another example, the subject is treated with a chemotherapeutic agent, radiation therapy, cryotherapy, or hormone therapy after determining whether the prostate cancer will metastasize. Exemplary chemotherapeutic agents include doceaxel, cabazitaxel, mitoxantrone, estramustine, doxorubicin, etoposide and paclitaxel.
In some cases, the corresponding polypeptide level of the prostate-cancer associated gene in the test sample is compared with the polypeptide level of the prostate cancer-associated gene in the reference sample, a threshold polypeptide level, or a housekeeping gene polypeptide level. It is determined that the prostate cancer in the subject will metastasize if the corresponding polypeptide level of the prostate cancer-associated gene in the test sample is higher than the polypeptide level of the prostate cancer-associated gene in the reference sample, a threshold polypeptide level, or a housekeeping gene polypeptide level.
The methods described herein involve monitoring whether prostate cancer in a subject will metastasize, e.g., to bone, over time. For example, the methods described herein are repeated over time, wherein an alteration in the level of the prostate cancer-associated gene over time indicates a corresponding alteration in the aggressiveness of the prostate cancer. Preferably, in this case, a radical prostatectomy is not performed so the cancer may be evaluated over time.
In some cases, the subject is treated if it is determined that the subject has prostate cancer that is likely to metastasize. For example, an inhibitor of the prostate cancer gene with a higher level of expression compared to the level of the prostate cancer-associated gene in the reference sample is administered to the subject, thereby treating the prostate cancer. Exemplary inhibitors include a small molecule inhibitor, RNA interference (RNAi), an antibody, or any combination thereof. Alternatively, the methods further comprise administering an agonist of the prostate cancer gene with a lower level of expression compared to the level of the prostate cancer-associated gene in the reference sample, thereby treating the prostate cancer.
Also provided are compositions comprising a prostate cancer-associated gene, wherein the prostate cancer-associated gene comprises ALCAM, LUM, COL1A1, BGN, C1QC, C1S, C1QB, HLA-DRB3, AEBP1, SFRP4, FBLN5, FCGR2C, C1QA, SFRP2, SULF1, THBS2, MOXD1, SERPING1, PRELP, CD52, LTBP2, ITGA11, TNS3, C12orf51, TMEM205, HSPA9, CLDN8, PTPLAD1, or MAL2 synthesized complementary deoxyribonucleic acid (cDNA).
Alternatively, the genes described herein are associated with an immune response. For example, an immune response gene panel includes C1S, C1QA, C1QB, C1QC, SERPING1, FCGR2C, CD52, and/or HLA-DRB3 synthesized complementary deoxyribonucleic acid (cDNA).
In another example, the genes described herein are associated with an extracellular matrix. For example, an extracellular matrix gene panel includes SFRP2, SULF1, COL1A1, ITGA11, Biglycan, LTBP3, Fibulin-5, Biglycan proteoglycan and/or Lumacin synthesized complementary deoxyribonucleic acid (cDNA).
In some examples, the genes include a bone-related subset of genes. For example the bone-related subset of genes includes PRELP, LTBP2, FBLN5, ITGA11, COL1A1, ALCAM, SFRP2, TNS3, SULF1, BGN, and/or THBS2 synthesized complementary deoxyribonucleic acid (cDNA).
Additional compositions include a composition comprising a prostate cancer-associated gene, wherein the prostate cancer-associated gene comprises AEBP1, ANTXR1, BGN, C1QA, C1QB, C1QC, C1R, C1S, CDH11, COL1A1, COL3A1, FBLN5, FCGR2B, HLA-DRB1, LUM, MOXD1, PRELP, RNASE1, SFRP2, SFRP4, SULF1, THBS2, THY1, or TMSB4X synthesized complementary deoxyribonucleic acid (cDNA).
Preferably, the prostate cancer-associated gene is immobilized on a solid support. In one aspect, the prostate cancer-associated gene is linked to a detectable label. Suitable detectable labels include a fluorescent label, a luminescent label, a chemiluminescent label, a radiolabel, a SYBR Green label, or a Cy3-label.
Also provided are kits comprising a package with a prostate cancer-associated gene, wherein the prostate cancer-associated gene comprises ALCAM, LUM, COL1A1, BGN, C1QC, C1S, C1QB, HLA-DRB3, AEBP1, SFRP4, FBLN5, FCGR2C, C1QA, SFRP2, SULF1, THBS2, MOXD1, SERPING1, PRELP, CD52, LTBP2, ITGA11, TNS3, C12orf51, TMEM205, HSPA9, CLDN8, PTPLAD1, or MAL2 and instructions for use thereof in the evaluation of prostate cancer progression and metastasis.
Provided is a kit comprising a package with a prostate cancer-associated gene, wherein the prostate cancer-associated gene comprises AEBP1, ANTXR1, BGN, C1QA, C1QB, C1QC, C1R, C1S, CDH11, COL1A1, COL3A1, FBLN5, FCGR2B, HLA-DRB1, LUM, MOXD1, PRELP, RNASE1, SFRP2, SFRP4, SULF1, THBS2, THY1, or TMSB4X and instructions for use thereof in the evaluation of prostate cancer progression and metastasis.
As described herein, a 24-gene signature reflecting bone remodeling and immune-related pathways was upregulated in high compared to low Gleason score cases and comprises a “bone homing signature” (Table 24).
As described in detail below, a 29-gene signature was defined herein (7 epithelial and 22 stromal genes), which distinguishes Gleason 6 from Gleason 8, which comprise a “bone homing signature” (Table 1).
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Unless specifically stated or obvious from context, as used herein, the term “about” is understood as within a range of normal tolerance in the art, for example within 2 standard deviations of the mean. “About” can be understood as within 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, 0.5%, 0.1%, 0.05%, or 0.01% of the stated value. Unless otherwise clear from context, all numerical values provided herein are modified by the term “about.”
The term “antineoplastic agent” is used herein to refer to agents that have the functional property of inhibiting a development or progression of a neoplasm in a human, e.g., a prostate cancer. Inhibition of metastasis is frequently a property of antineoplastic agents.
By “agent” is meant any small compound, antibody, nucleic acid molecule, or polypeptide, or fragments thereof.
By “alteration” is meant a change (increase or decrease) in the expression levels or activity of a gene or polypeptide as detected by standard art-known methods such as those described herein. As used herein, an alteration includes at least a 1% change in expression levels, e.g., at least a 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 100% change in expression levels. For example, an alteration includes at least a 5%-10% change in expression levels, preferably a 25% change, more preferably a 40% change, and most preferably a 50% or greater change in expression levels.
By “ameliorate” is meant decrease, suppress, attenuate, diminish, arrest, or stabilize the development or progression of a disease.
The term “antibody” (Ab) as used herein includes monoclonal antibodies, polyclonal antibodies, multispecific antibodies (e.g., bispecific antibodies), and antibody fragments, so long as they exhibit the desired biological activity. The term “immunoglobulin” (Ig) is used interchangeably with “antibody” herein.
By “binding to” a molecule is meant having a physicochemical affinity for that molecule. By “control” or “reference” is meant a standard of comparison. As used herein, “changed as compared to a control” sample or subject is understood as having a level that is statistically different than a sample from a normal, untreated, or control sample. Control samples include, for example, cells in culture, one or more laboratory test animals, or one or more human subjects. Methods to select and test control samples are within the ability of those in the art. An analyte can be a naturally occurring substance that is characteristically expressed or produced by the cell or organism (e.g., an antibody, a protein) or a substance produced by a reporter construct (e.g, β-galactosidase or luciferase). Depending on the method used for detection, the amount and measurement of the change can vary. Determination of statistical significance is within the ability of those skilled in the art, e.g., the number of standard deviations from the mean that constitute a positive result.
“Cystoprostatectomy” (CP) refers to a surgical procedure wherein the bladder and prostate are simultaneously removed.
“Detect” refers to identifying the presence, absence, or amount of the agent (e.g., a nucleic acid molecule, for example deoxyribonucleic acid (DNA) or ribonucleic acid (RNA)) to be detected.
By “detectable label” is meant a composition that when linked (e.g., joined—directly or indirectly) to a molecule of interest renders the latter detectable, via, for example, spectroscopic, photochemical, biochemical, immunochemical, or chemical means. Direct labeling can occur through bonds or interactions that link the label to the molecule, and indirect labeling can occur through the use of a linker or bridging moiety which is either directly or indirectly labeled. Bridging moieties may amplify a detectable signal. For example, useful labels may include radioactive isotopes, magnetic beads, metallic beads, colloidal particles, fluorescent labeling compounds, electron-dense reagents, enzymes (for example, as commonly used in an enzyme-linked immunosorbent assay (ELISA)), biotin, digoxigenin, or haptens. When the fluorescently labeled molecule is exposed to light of the proper wave length, its presence can then be detected due to fluorescence. Among the most commonly used fluorescent labeling compounds are fluorescein isothiocyanate, rhodamine, phycoerythrin, phycocyanin, allophycocyanin, p-phthaldehyde and fluorescamine. The molecule can also be detectably labeled using fluorescence emitting metals such as 152 Eu, or others of the lanthanide series. These metals can be attached to the molecule using such metal chelating groups as diethylenetriaminepentacetic acid (DTPA) or ethylenediaminetetraacetic acid (EDTA). The molecule also can be detectably labeled by coupling it to a chemiluminescent compound. The presence of the chemiluminescent-tagged molecule is then determined by detecting the presence of luminescence that arises during the course of chemical reaction. Examples of particularly useful chemiluminescent labeling compounds are luminol, isoluminol, theromatic acridinium ester, imidazole, acridinium salt and oxalate ester.
A “detection step” may use any of a variety of known methods to detect the presence of nucleic acid. The types of detection methods in which probes can be used include Western blots, Southern blots, dot or slot blots, and Northern blots.
As used herein, the term “diagnosing” refers to classifying pathology or a symptom, determining a severity of the pathology (e.g., grade or stage), monitoring pathology progression, forecasting an outcome of pathology, and/or determining prospects of recovery.
By the terms “effective amount” and “therapeutically effective amount” of a formulation or formulation component is meant a sufficient amount of the formulation or component, alone or in a combination, to provide the desired effect. For example, by “an effective amount” is meant an amount of a compound, alone or in a combination, required to ameliorate the symptoms of a disease, e.g., prostate cancer, relative to an untreated patient. The effective amount of active compound(s) used to practice the present invention for therapeutic treatment of a disease varies depending upon the manner of administration, the age, body weight, and general health of the subject. Ultimately, the attending physician or veterinarian will decide the appropriate amount and dosage regimen. Such amount is referred to as an “effective” amount.
The term “expression profile” is used broadly to include a genomic expression profile. Profiles may be generated by any convenient means for determining a level of a nucleic acid sequence, e.g., quantitative hybridization of microRNA, labeled microRNA, amplified microRNA, complementary/synthetic DNA (cDNA), etc., quantitative polymerase chain reaction (PCR), and ELISA for quantitation, and allow the analysis of differential gene expression between two samples. A subject or patient tumor sample is assayed. Samples are collected by any convenient method, as known in the art. According to some embodiments, the term “expression profile” means measuring the relative abundance of the nucleic acid sequences in the measured samples.
By “FDR” is meant False Discovery Rate. When performing multiple statistical tests, for example, in comparing the signal of two groups in multiple data features, there is an increasingly high probability of obtaining false positive results, by random differences between the groups that can reach levels that would otherwise be considered statistically significant. In some cases, in order to limit the proportion of such false discoveries, statistical significance is defined only for data features in which the differences reached a p-value (by two-sided t-test) below a threshold, which is dependent on the number of tests performed and the distribution of p-values obtained in these tests.
By “fragment” is meant a portion of a polypeptide or nucleic acid molecule. This portion contains, preferably, at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, or 90% of the entire length of the reference nucleic acid molecule or polypeptide. For example, a fragment may contain 10, 20, 30, 40, 50, 60, 70, 80, 90, or 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 nucleotides or amino acids. However, the invention also comprises polypeptides and nucleic acid fragments, so long as they exhibit the desired biological activity of the full length polypeptides and nucleic acid, respectively. A nucleic acid fragment of almost any length is employed. For example, illustrative polynucleotide segments with total lengths of about 10,000, about 5000, about 3000, about 2,000, about 1,000, about 500, about 200, about 100, about 50 base pairs in length (including all intermediate lengths) are included in many implementations of this invention. Similarly, a polypeptide fragment of almost any length is employed. For example, illustrative polypeptide segments with total lengths of about 10,000, about 5,000, about 3,000, about 2,000, about 1,000, about 5,000, about 1,000, about 500, about 200, about 100, or about 50 amino acids in length (including all intermediate lengths) are included in many implementations of this invention.
A “Gleason score” or “Gleason grade” evaluates the prognosis of men with prostate cancer using samples from a prostate biopsy. Prostate cancer cells in biopsy samples are given a Gleason grade. The grade describes the aggressiveness of the cancer, and its likelihood to grow and spread outside the prostate. The system describes a score between 2 and 10, with 2 being the least aggressive and being 10 the most aggressive. When cancer cells are seen under the microscope, they have different patterns, depending on how quickly they're likely to grow. The pattern is given a grade from 1 to 5, based on how much the arrangement of cancer cells mimics normal prostate cells from glands. This is called the Gleason grade. If a grade is given, it will usually be 3 or higher, as grades 1 and 2 are not cancerous. To be counted, a pattern (grade) needs to occupy more than 5% of the biopsy specimen. The scoring system requires biopsy material (core biopsy or operative specimens) in order to be accurate (cytological preparations cannot be used).
“Hybridization” means hydrogen bonding, which may be Watson-Crick, Hoogsteen or reversed Hoogsteen hydrogen bonding, between complementary nucleobases. For example, adenine and thymine are complementary nucleobases that pair through the formation of hydrogen bonds.
By “hybridize” is meant pair to form a double-stranded molecule between complementary polynucleotide sequences (e.g., a gene described herein), or portions thereof, under various conditions of stringency. (See, e.g., Wahl, G. M. and S. L. Berger (1987) Methods Enzymol. 152:399; Kimmel, A. R. (1987) Methods Enzymol. 152:507).
The terms “isolated,” “purified,” or “biologically pure” refer to material that is free to varying degrees from components which normally accompany it as found in its native state. “Isolate” denotes a degree of separation from original source or surroundings. “Purify” denotes a degree of separation that is higher than isolation.
A “purified” or “biologically pure” gene or protein is sufficiently free of other materials such that any impurities do not materially affect the biological properties of the gene or protein or cause other adverse consequences. That is, a nucleic acid or peptide of this invention is purified if it is substantially free of cellular material, viral material, or culture medium when produced by recombinant DNA techniques, or chemical precursors or other chemicals when chemically synthesized. Purity and homogeneity are typically determined using analytical chemistry techniques, for example, polyacrylamide gel electrophoresis or high performance liquid chromatography. The term “purified” can denote that a nucleic acid or protein gives rise to essentially one band in an electrophoretic gel. For a protein that can be subjected to modifications, for example, phosphorylation or glycosylation, different modifications may give rise to different isolated proteins, which can be separately purified.
Similarly, by “substantially pure” is meant a nucleotide or polypeptide that has been separated from the components that naturally accompany it. Typically, the nucleotides and polypeptides are substantially pure when they are at least 60%, 70%, 80%, 90%, 95%, or even 99%, by weight, free from the proteins and naturally-occurring organic molecules with they are naturally associated.
By “isolated nucleic acid” is meant a nucleic acid that is free of the genes which flank it in the naturally-occurring genome of the organism from which the nucleic acid is derived. The term covers, for example (a) a DNA which is part of a naturally occurring genomic DNA molecule, but is not flanked by both of the nucleic acid sequences that flank that part of the molecule in the genome of the organism in which it naturally occurs; (b) a nucleic acid incorporated into a vector or into the genomic DNA of a prokaryote or eukaryote in a manner, such that the resulting molecule is not identical to any naturally occurring vector or genomic DNA; (c) a separate molecule such as a synthetic cDNA, a genomic fragment, a fragment produced by polymerase chain reaction (PCR), or a restriction fragment; and (d) a recombinant nucleotide sequence that is part of a hybrid gene, i.e., a gene encoding a fusion protein. Isolated nucleic acid molecules according to the present invention further include molecules produced synthetically, as well as any nucleic acids that have been altered chemically and/or that have modified backbones. For example, the isolated nucleic acid is a purified cDNA or RNA polynucleotide. Isolated nucleic acid molecules also include messenger ribonucleic acid (mRNA) molecules.
By an “isolated polypeptide” is meant a polypeptide of the invention that has been separated from components that naturally accompany it. Typically, the polypeptide is isolated when it is at least 60%, by weight, free from the proteins and naturally-occurring organic molecules with which it is naturally associated. Preferably, the preparation is at least 75%, more preferably at least 90%, and most preferably at least 99%, by weight, a polypeptide of the invention. An isolated polypeptide of the invention may be obtained, for example, by extraction from a natural source, by expression of a recombinant nucleic acid encoding such a polypeptide; or by chemically synthesizing the protein. Purity can be measured by any appropriate method, for example, column chromatography, polyacrylamide gel electrophoresis, or by HPLC analysis.
The term “immobilized” or “attached” refers to a probe (e.g., nucleic acid or protein) and a solid support in which the binding between the probe and the solid support is sufficient to be stable under conditions of binding, washing, analysis, and removal. The binding may be covalent or non-covalent. Covalent bonds may be formed directly between the probe and the solid support or may be formed by a cross linker or by inclusion of a specific reactive group on either the solid support or the probe or both molecules. Non-covalent binding may be one or more of electrostatic, hydrophilic, and hydrophobic interactions. Included in non-covalent binding is the covalent attachment of a molecule to the support and the non-covalent binding of a biotinylated probe to the molecule Immobilization may also involve a combination of covalent and non-covalent interactions.
“Laser capture microdissection” or “LCM” is a method for isolating specific cells from microscopic regions of tissues, cells or organisms. LCM is a method to procure subpopulations of tissue cells under direct microscopic visualization. LCM technology can harvest the cells of interest directly or it can isolate specific cells by cutting away unwanted cells to give histologically pure enriched cell populations.
By “marker” is meant any protein or polynucleotide having an alteration in expression level or activity that is associated with a disease or disorder, e.g., prostate cancer.
By “modulate” is meant alter (increase or decrease). Such alterations are detected by standard art-known methods such as those described herein.
The term, “normal amount” refers to a normal amount of a complex in an individual known not to be diagnosed with prostate cancer. The amount of the molecule can be measured in a test sample and compared to the “normal control level,” utilizing techniques such as reference limits, discrimination limits, or risk defining thresholds to define cutoff points and abnormal values (e.g., for prostate cancer). The “normal control level” means the level of one or more proteins (or nucleic acids) or combined protein indices (or combined nucleic acid indices) typically found in a subject known not to be suffering from prostate cancer. Such normal control levels and cutoff points may vary based on whether a molecule is used alone or in a formula combining other proteins into an index. Alternatively, the normal control level can be a database of protein patterns from previously tested subjects who did not convert to prostate cancer over a clinically relevant time horizon.
The level that is determined may be the same as a control level or a cut off level or a threshold level, or may be increased or decreased relative to a control level or a cut off level or a threshold level. In some aspects, the control subject is a matched control of the same species, gender, ethnicity, age group, smoking status, body mass index (BMI), current therapeutic regimen status, medical history, or a combination thereof, but differs from the subject being diagnosed in that the control does not suffer from the disease in question or is not at risk for the disease.
Relative to a control level, the level that is determined may be an increased level. As used herein, the term “increased” with respect to level (e.g., expression level, biological activity level, etc.) refers to any % increase above a control level. The increased level may be at least or about a 1% increase, at least or about a 5% increase, at least or about a 10% increase, at least or about a 15% increase, at least or about a 20% increase, at least or about a 25% increase, at least or about a 30% increase, at least or about a 35% increase, at least or about a 40% increase, at least or about a 45% increase, at least or about a 50% increase, at least or about a 55% increase, at least or about a 60% increase, at least or about a 65% increase, at least or about a 70% increase, at least or about a 75% increase, at least or about a 80% increase, at least or about a 85% increase, at least or about a 90% increase, or at least or about a 95% increase, relative to a control level.
Relative to a control level, the level that is determined may be a decreased level. As used herein, the term “decreased” with respect to level (e.g., expression level, biological activity level, etc.) refers to any % decrease below a control level. The decreased level may be at least or about a 1% decrease, at least or about a 5% decrease, at least or about a 10% decrease, at least or about a 15% decrease, at least or about a 20% decrease, at least or about a 25% decrease, at least or about a 30% decrease, at least or about a 35% decrease, at least or about a 40% decrease, at least or about a 45% decrease, at least or about a 50% decrease, at least or about a 55% decrease, at least or about a 60% decrease, at least or about a 65% decrease, at least or about a 70% decrease, at least or about a 75% decrease, at least or about a 80% decrease, at least or about a 85% decrease, at least or about a 90% decrease, or at least or about a 95% decrease, relative to a control level.
Nucleic acid molecules useful in the methods of the invention include any nucleic acid molecule that encodes a polypeptide of the invention or a fragment thereof. Such nucleic acid molecules need not be 100% identical with an endogenous nucleic acid sequence, but will typically exhibit substantial identity. Polynucleotides having “substantial identity” to an endogenous sequence are typically capable of hybridizing with at least one strand of a double-stranded nucleic acid molecule.
For example, stringent salt concentration will ordinarily be less than about 750 mM NaCl and 75 mM trisodium citrate, preferably less than about 500 mM NaCl and 50 mM trisodium citrate, and more preferably less than about 250 mM NaCl and 25 mM trisodium citrate. Low stringency hybridization can be obtained in the absence of organic solvent, e.g., formamide, while high stringency hybridization can be obtained in the presence of at least about 35% formamide, and more preferably at least about 50% formamide Stringent temperature conditions will ordinarily include temperatures of at least about 30° C., more preferably of at least about 37° C., and most preferably of at least about 42° C. Varying additional parameters, such as hybridization time, the concentration of detergent, e.g., sodium dodecyl sulfate (SDS), and the inclusion or exclusion of carrier DNA, are well known to those skilled in the art. Various levels of stringency are accomplished by combining these various conditions as needed. In a preferred embodiment, hybridization will occur at 30° C. in 750 mM NaCl, 75 mM trisodium citrate, and 1% SDS. In a more preferred embodiment, hybridization will occur at 37° C. in 500 mM NaCl, 50 mM trisodium citrate, 1% SDS, 35% formamide, and 100 μg/ml denatured salmon sperm DNA (ssDNA). In a most preferred embodiment, hybridization will occur at 42° C. in 250 mM NaCl, 25 mM trisodium citrate, 1% SDS, 50% formamide, and 200 μg/ml ssDNA. Useful variations on these conditions will be readily apparent to those skilled in the art.
For most applications, washing steps that follow hybridization will also vary in stringency. Wash stringency conditions can be defined by salt concentration and by temperature. As above, wash stringency can be increased by decreasing salt concentration or by increasing temperature. For example, stringent salt concentration for the wash steps will preferably be less than about 30 mM NaCl and 3 mM trisodium citrate, and most preferably less than about 15 mM NaCl and 1.5 mM trisodium citrate. Stringent temperature conditions for the wash steps will ordinarily include a temperature of at least about 25° C., more preferably of at least about 42° C., and even more preferably of at least about 68° C. In a preferred embodiment, wash steps will occur at 25° C. in 30 mM NaCl, 3 mM trisodium citrate, and 0.1% SDS. In a more preferred embodiment, wash steps will occur at 42 C in 15 mM NaCl, 1.5 mM trisodium citrate, and 0.1% SDS. In a more preferred embodiment, wash steps will occur at 68° C. in 15 mM NaCl, 1.5 mM trisodium citrate, and 0.1% SDS. Additional variations on these conditions will be readily apparent to those skilled in the art. Hybridization techniques are well known to those skilled in the art and are described, for example, in Benton and Davis (Science 196:180, 1977); Grunstein and Hogness (Proc. Natl. Acad. Sci., USA 72:3961, 1975); Ausubel et al. (Current Protocols in Molecular Biology, Wiley Interscience, New York, 2001); Berger and Kimmel (Guide to Molecular Cloning Techniques, 1987, Academic Press, New York); and Sambrook et al., Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Laboratory Press, New York.
By “neoplasia” is meant a disease or disorder characterized by excess proliferation or reduced apoptosis. Illustrative neoplasms for which the invention can be used include, but are not limited to pancreatic cancer, leukemias (e.g., acute leukemia, acute lymphocytic leukemia, acute myelocytic leukemia, acute myeloblastic leukemia, acute promyelocytic leukemia, acute myelomonocytic leukemia, acute monocytic leukemia, acute erythroleukemia, chronic leukemia, chronic myelocytic leukemia, chronic lymphocytic leukemia), polycythemia vera, lymphoma (Hodgkin's disease, non-Hodgkin's disease), Waldenstrom's macroglobulinemia, heavy chain disease, and solid tumors such as sarcomas and carcinomas (e.g., fibrosarcoma, myxosarcoma, liposarcoma, chondrosarcoma, osteogenic sarcoma, chordoma, angiosarcoma, endotheliosarcoma, lymphangiosarcoma, lymphangioendotheliosarcoma, synovioma, mesothelioma, Ewing's tumor, leiomyosarcoma, rhabdomyosarcoma, colon carcinoma, breast cancer, ovarian cancer, prostate cancer, squamous cell carcinoma, basal cell carcinoma, adenocarcinoma, sweat gland carcinoma, sebaceous gland carcinoma, papillary carcinoma, papillary adenocarcinomas, cystadenocarcinoma, medullary carcinoma, bronchogenic carcinoma, renal cell carcinoma, hepatoma, nile duct carcinoma, choriocarcinoma, seminoma, embryonal carcinoma, Wilm's tumor, cervical cancer, uterine cancer, testicular cancer, lung carcinoma, small cell lung carcinoma, bladder carcinoma, epithelial carcinoma, glioma, glioblastoma multiforme, astrocytoma, medulloblastoma, craniopharyngioma, ependymoma, pinealoma, hemangioblastoma, acoustic neuroma, oligodenroglioma, schwannoma, meningioma, melanoma, neuroblastoma, and retinoblastoma).
As used herein, “obtaining” as in “obtaining an agent” includes synthesizing, purchasing, or otherwise acquiring the agent.
By “Ontology Enrichment Analysis,” is meant as a technique for interpreting sets of genes making use of the Gene Ontology (GO) system of classification, in which genes are assigned to a set of predefined bins depending on their functional characteristics. Researchers performing high-throughput experiments that yield sets of genes often want to retrieve a functional profile of that gene set, in order to better understand the underlying biological processes. This can be done by comparing the input gene set each of the bins (terms) in the GO, and a statistical test can be performed for each bin to see if it is enriched for the input genes. The output of the analysis is typically a ranked list of GO terms, each associated with a p-value.
Unless specifically stated or obvious from context, as used herein, the term “or” is understood to be inclusive. Unless specifically stated or obvious from context, as used herein, the terms “a”, “an”, and “the” are understood to be singular or plural.
The phrase “pharmaceutically acceptable carrier” is art recognized and includes a pharmaceutically acceptable material, composition or vehicle, suitable for administering compounds of the present invention to mammals. The carriers include liquid or solid filler, diluent, excipient, solvent or encapsulating material, involved in carrying or transporting the subject agent from one organ, or portion of the body, to another organ, or portion of the body. Each carrier must be “acceptable” in the sense of being compatible with the other ingredients of the formulation and not injurious to the patient. Some examples of materials which can serve as pharmaceutically acceptable carriers include: sugars, such as lactose, glucose and sucrose; starches, such as corn starch and potato starch; cellulose, and its derivatives, such as sodium carboxymethyl cellulose, ethyl cellulose and cellulose acetate; powdered tragacanth; malt; gelatin; talc; excipients, such as cocoa butter and suppository waxes; oils, such as peanut oil, cottonseed oil, safflower oil, sesame oil, olive oil, corn oil and soybean oil; glycols, such as propylene glycol; polyols, such as glycerin, sorbitol, mannitol and polyethylene glycol; esters, such as ethyl oleate and ethyl laurate; agar; buffering agents, such as magnesium hydroxide and aluminum hydroxide; alginic acid; pyrogen-free water; isotonic saline; Ringer's solution; ethyl alcohol; phosphate buffer solutions; and other non-toxic compatible substances employed in pharmaceutical formulations.
By “protein” or “polypeptide” or “peptide” is meant any chain of more than two natural or unnatural amino acids, regardless of post-translational modification (e.g., glycosylation or phosphorylation), constituting all or part of a naturally-occurring or non-naturally occurring polypeptide or peptide, as is described herein.
By “PIN” is meant a prostatic intraepithelial neoplasia. PIN is a condition in which some prostate cells have begun to look and behave abnormally.
The terms “preventing” and “prevention” refer to the administration of an agent or composition to a clinically asymptomatic individual who is at risk of developing, susceptible, or predisposed to a particular adverse condition, disorder, or disease, and thus relates to the prevention of the occurrence of symptoms and/or their underlying cause.
The term “prognosis,” “staging,” and “determination of aggressiveness” are defined herein as the prediction of the degree of severity of the neoplasia, e.g., prostate cancer, and of its evolution as well as the prospect of recovery as anticipated from usual course of the disease. Once the aggressiveness (e.g. the Gleason score) has been determined, appropriate methods of treatments are chosen.
“Radical prostatectomy” (RP) refers to an operation to remove (completely or partially) the prostate gland and some of the tissue surrounding it to treat prostate cancer or benign prostatic hyperplasia.
Ranges can be expressed herein as from “about” one particular value, and/or to “about” another particular value. When such a range is expressed, another aspect includes from the one particular value and/or to the other particular value. Similarly, when values are expressed as approximations, by use of the antecedent “about,” it is understood that the particular value forms another aspect. It is further understood that the endpoints of each of the ranges are significant both in relation to the other endpoint, and independently of the other endpoint. It is also understood that there are a number of values disclosed herein, and that each value is also herein disclosed as “about” that particular value in addition to the value itself. It is also understood that throughout the application, data are provided in a number of different formats and that this data represent endpoints and starting points and ranges for any combination of the data points. For example, if a particular data point “10” and a particular data point “15” are disclosed, it is understood that greater than, greater than or equal to, less than, less than or equal to, and equal to 10 and 15 are considered disclosed as well as between 10 and 15. It is also understood that each unit between two particular units are also disclosed. For example, if 10 and 15 are disclosed, then 11, 12, 13, and 14 are also disclosed.
Ranges provided herein are understood to be shorthand for all of the values within the range. For example, a range of 1 to 50 is understood to include any number, combination of numbers, or sub-range from the group consisting 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, or 50 as well as all intervening decimal values between the aforementioned integers such as, for example, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, and 1.9. With respect to sub-ranges, “nested sub-ranges” that extend from either end point of the range are specifically contemplated. For example, a nested sub-range of an exemplary range of 1 to 50 may comprise 1 to 10, 1 to 20, 1 to 30, and 1 to 40 in one direction, or 50 to 40, 50 to 30, 50 to 20, and 50 to 10 in the other direction.
By “reduces” is meant a negative alteration of at least 10%, 25%, 50%, 75%, or 100%.
A “reference sequence” is a defined sequence used as a basis for sequence comparison or a gene expression comparison. A reference sequence may be a subset of or the entirety of a specified sequence; for example, a segment of a full-length cDNA or gene sequence, or the complete cDNA or gene sequence. For polypeptides, the length of the reference polypeptide sequence will generally be at least about 16 amino acids, preferably at least about 20 amino acids, more preferably at least about 25 amino acids, and even more preferably about 35 amino acids, about 50 amino acids, or about 100 amino acids. For nucleic acids, the length of the reference nucleic acid sequence will generally be at least about 40 nucleotides, preferably at least about 60 nucleotides, more preferably at least about 75 nucleotides, and even more preferably about 100 nucleotides or about 300 or about 500 nucleotides or any integer thereabout or there between.
The term “sample” as used herein refers to a biological sample obtained for the purpose of evaluation in vitro. Exemplary tissue samples for the methods described herein include tissue samples from prostate tumors or the surrounding microenvironment (i.e., the stroma). With regard to the methods disclosed herein, the sample or patient sample preferably may comprise any body fluid or tissue. In some embodiments, the bodily fluid includes, but is not limited to, blood, plasma, serum, lymph, breast milk, saliva, mucous, semen, vaginal secretions, cellular extracts, inflammatory fluids, cerebrospinal fluid, feces, vitreous humor, or urine obtained from the subject. In some aspects, the sample is a composite panel of at least two of a blood sample, a plasma sample, a serum sample, and a urine sample. In exemplary aspects, the sample comprises blood or a fraction thereof (e.g., plasma, serum, fraction obtained via leukopheresis). Preferred samples are whole blood, serum, plasma, or urine. A sample can also be a partially purified fraction of a tissue or bodily fluid.
A reference sample can be a “normal” sample, from a donor not having the disease or condition fluid, or from a normal tissue in a subject having the disease or condition. A reference sample can also be from an untreated donor or cell culture not treated with an active agent (e.g., no treatment or administration of vehicle only). A reference sample can also be taken at a “zero time point” prior to contacting the cell or subject with the agent or therapeutic intervention to be tested or at the start of a prospective study.
A “solid support” describes a strip, a polymer, a bead, or a nanoparticle. The strip may be a nucleic acid-probe (or protein) coated porous or non-porous solid support strip comprising linking a nucleic acid probe to a carrier to prepare a conjugate and immobilizing the conjugate on a porous solid support. Well-known supports or carriers include glass, polystyrene, polypropylene, polyethylene, dextran, nylon, amylases, natural and modified celluloses, polyacrylamides, gabbros, and magnetite. The nature of the carrier can be either soluble to some extent or insoluble for the purposes of the present invention. The support material may have virtually any possible structural configuration so long as the coupled molecule is capable of binding to a binding agent (e.g., an antibody or nucleic acid molecule). Thus, the support configuration may be spherical, as in a bead, or cylindrical, as in the inside surface of a test tube, or the external surface of a rod. Alternatively, the surface may be flat such as a sheet, or test strip, etc. For example, the supports include polystyrene beads. Those skilled in the art will know many other suitable carriers for binding antibody or antigen, or will be able to ascertain the same by use of routine experimentation. In other aspects, the solid support comprises a polymer, to which an agent is chemically bound, immobilized, dispersed, or associated. A polymer support may be a network of polymers, and may be prepared in bead form (e.g., by suspension polymerization). The location of active sites introduced into a polymer support depends on the type of polymer support. For example, in a swollen-gel-bead polymer support the active sites are distributed uniformly throughout the beads, whereas in a macroporous-bead polymer support they are predominantly on the internal surfaces of the macropores. The solid support, e.g., a device contains a binding agent alone or together with a binding agent for at least one, two, three or more other molecules.
By “specifically binds” is meant a compound or antibody that recognizes and binds a polypeptide of the invention, but which does not substantially recognize and bind other molecules in a sample, for example, a biological sample, which naturally includes a polypeptide of the invention.
A “specific binding agent” describes agents having greater than 10-fold, preferably greater than 100-fold, and most preferably, greater than 1000-fold affinity for the target molecule as compared to another molecule. As the skilled artisan will appreciate the term specific is used to indicate that other biomolecules present in the sample do not significantly bind to the binding agent specific for the target molecule. Preferably, the level of binding to a biomolecule other than the target molecule results in a binding affinity which is at most only 10% or less, only 5% or less only 2% or less or only 1% or less of the affinity to the target molecule, respectively. A preferred specific binding agent will fulfill both the above minimum criteria for affinity as well as for specificity. For example, an antibody has a binding affinity in the low micromolar (10−6), nanomolar (10−7-10−9), with high affinity antibodies in the low nanomolar (10−9) or pico molar (10−12) range for its specific target molecule.
By “substantially identical” is meant a polypeptide or nucleic acid molecule exhibiting at least 50% identity to a reference amino acid sequence (for example, any one of the amino acid sequences described herein) or nucleic acid sequence (for example, any one of the nucleic acid sequences described herein). Preferably, such a sequence is at least 60%, more preferably 80% or 85%, and more preferably 90%, 95% or even 99% identical at the amino acid level or nucleic acid to the sequence used for comparison.
Sequence identity is typically measured using sequence analysis software (for example, Sequence Analysis Software Package of the Genetics Computer Group, University of Wisconsin Biotechnology Center, 1710 University Avenue, Madison, Wis. 53705, BLAST, BESTFIT, GAP, or PILEUP/PRETTYBOX programs). Such software matches identical or similar sequences by assigning degrees of homology to various substitutions, deletions, and/or other modifications. Conservative substitutions typically include substitutions within the following groups: glycine, alanine; valine, isoleucine, leucine; aspartic acid, glutamic acid, asparagine, glutamine; serine, threonine; lysine, arginine; and phenylalanine, tyrosine. In an exemplary approach to determining the degree of identity, a BLAST program may be used, with a probability score between e−3 and e−100 indicating a closely related sequence.
The term “subject” as used herein includes all members of the animal kingdom prone to suffering from the indicated disorder. In some aspects, the subject is a mammal, and in some aspects, the subject is a human. The methods are also applicable to companion animals such as dogs and cats as well as livestock such as cows, horses, sheep, goats, pigs, and other domesticated and wild animals.
A subject “suffering from or suspected of suffering from” a specific disease, condition, or syndrome has a sufficient number of risk factors or presents with a sufficient number or combination of signs or symptoms of the disease, condition, or syndrome such that a competent individual would diagnose or suspect that the subject was suffering from the disease, condition, or syndrome. Methods for identification of subjects suffering from or suspected of suffering from conditions associated with cancer (e.g., prostate cancer) is within the ability of those in the art. Subjects suffering from, and suspected of suffering from, a specific disease, condition, or syndrome are not necessarily two distinct groups.
As used herein, “susceptible to” or “prone to” or “predisposed to” or “at risk of developing” a specific disease or condition refers to an individual who based on genetic, environmental, health, and/or other risk factors is more likely to develop a disease or condition than the general population. An increase in likelihood of developing a disease may be an increase of about 10%, 20%, 50%, 100%, 150%, 200%, or more.
“Primer set” means a set of oligonucleotides that may be used, for example, for PCR. A primer set would consist of at least 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 30, 40, 50, 60, 80, 100, 200, 250, 300, 400, 500, 600, or more primers.
The terms “treating” and “treatment” as used herein refer to the administration of an agent or formulation to a clinically symptomatic individual afflicted with an adverse condition, disorder, or disease, so as to effect a reduction in severity and/or frequency of symptoms, eliminate the symptoms and/or their underlying cause, and/or facilitate improvement or remediation of damage. It will be appreciated that, although not precluded, treating a disorder or condition does not require that the disorder, condition or symptoms associated therewith be completely eliminated.
In some cases, a composition of the invention is administered orally or systemically. Other modes of administration include rectal, topical, intraocular, buccal, intravaginal, intracisternal, intracerebroventricular, intratracheal, nasal, transdermal, within/on implants, or parenteral routes. The term “parenteral” includes subcutaneous, intrathecal, intravenous, intramuscular, intraperitoneal, or infusion. Intravenous or intramuscular routes are not particularly suitable for long-term therapy and prophylaxis. They could, however, be preferred in emergency situations. Compositions comprising a composition of the invention can be added to a physiological fluid, such as blood. Oral administration can be preferred for prophylactic treatment because of the convenience to the patient as well as the dosing schedule. Parenteral modalities (subcutaneous or intravenous) may be preferable for more acute illness, or for therapy in patients that are unable to tolerate enteral administration due to gastrointestinal intolerance, ileus, or other concomitants of critical illness. Inhaled therapy may be most appropriate for pulmonary vascular diseases (e.g., pulmonary hypertension).
Pharmaceutical compositions may be assembled into kits or pharmaceutical systems for use in arresting cell cycle in rapidly dividing cells, e.g., cancer cells. Kits or pharmaceutical systems according to this aspect of the invention comprise a carrier means, such as a box, carton, tube, having in close confinement therein one or more container means, such as vials, tubes, ampoules, bottles, syringes, or bags. The kits or pharmaceutical systems of the invention may also comprise associated instructions for using the kit.
Any compositions or methods provided herein can be combined with one or more of any of the other compositions and methods provided herein.
Any compositions or methods provided herein can be combined with one or more of any of the other compositions and methods provided herein.
The transitional term “comprising,” which is synonymous with “including,” “containing,” or “characterized by,” is inclusive or open-ended and does not exclude additional, unrecited elements or method steps. By contrast, the transitional phrase “consisting of” excludes any element, step, or ingredient not specified in the claim. The transitional phrase “consisting essentially of” limits the scope of a claim to the specified materials or steps “and those that do not materially affect the basic and novel characteristic(s)” of the claimed invention.
Other features and advantages of the invention will be apparent from the following description of the preferred embodiments thereof, and from the claims. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, suitable methods and materials are described below. All published foreign patents and patent applications cited herein are incorporated herein by reference. Genbank and NCBI submissions indicated by accession number cited herein are incorporated herein by reference. All other published references, documents, manuscripts and scientific literature cited herein are incorporated herein by reference. In the case of conflict, the present specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and not intended to be limiting.
Category 1 (top) epithelial amino acid metabolism
Category 2 epithelial: secretory pathway
Category 3 epithelial: RNA synthesis
Category 4 epithelial: RNA, protein and lipid synthesis
Category 5 epithelial: miscellaneous
Category 1 (top) stromal: muscle development and localization
Category 2 stromal immune regulation, angiogenesis and cell proliferation
Category 3 stromal: signal transduction, cell migration and angiogenesis
Category 4 stromal: TGF beta, signal transduction and bone remodeling
Category 5 stromal: miscellaneous
In prostate cancer, approximately 80% of metastatic sites are found in the bone. The invention is based, at least in part, upon the identification of a gene expression signature (i.e., a “bone homing signature”) that predicts the likelihood that prostate cancer will metastasize, e.g., to bone. In some aspects, the invention relates to methods, arrays and kits for diagnosing and monitoring prostate cancer and cancer metastases.
The present invention relates to the pathological progression of prostate cancer to metastatic sites. For example, as described in detail below, the surrounding tumor microenvironment, i.e., the stroma, is modified to appear more bone-like, which is an indication that prostate tumor cells have or will metastizie to metastatic sites, e.g., to bone. That is, when the tumor microenvironment looks like bone and contains structures that act and behave like bone, the likelihood that prostate cancer cells will metastasize to the bone is high.
Stromal cells are connective tissue cells of any organ, e.g., in the uterine mucosa (endometrium), prostate, bone marrow, and the ovary. Stromal cells are cells that support the function of the parenchymal cells of that organ. Fibroblasts and pericytes are among the most common types of stromal cells. As described in detail below, the stroma is involved in human prostate cancer initiation and in a progressive evolution towards a microenvironment similar to that of bone, the prototypic destination of end-stage prostate cancer. As described herein, molecular manipulation of the surrounding tumor microenvironment by the tumor influences prostate cancer initiation, maintenance, and metastatic progression.
As described in detail below, a 29-gene signature was defined herein (7 epithelial and 22 stromal genes), which distinguishes Gleason 6 from Gleason 8, which comprise the “bone homing signature” (Table 1).
In another case, the “bone homing signature” is described in Table 24, which provides a 24 gene signature that distinguishes low grade from high grade Gleason score.
Prostate Cancer
After skin cancer, prostate cancer is the most common cancer in American men, and is the second leading cause of cancer death in American men (only behind lung cancer). As of year 2015, 220,800 new cases were diagnosed, and about 27,540 deaths were due to prostate cancer. About 1 man in 7 will be diagnosed with prostate cancer during his lifetime, and about 1 man in 38 will die of prostate cancer. Rates of prostate cancer vary widely across the world. Prostate cancer is least common among Asian men and most common among black men, with figures for white men in between.
Prostate cancer develops primarily in men over fifty. Although the disease is typically diagnosed during the later years of men, its impact is still significant in that the average life span of a man who dies from prostate cancer is reduced by 9-10 years. The disease is slowly fatal once the tumor spreads outside the prostate. Thus, early detection and accurate staging are of great importance for the accurate choice of therapy, and should improve the success rate of treatments and reduce the mortality rate associated with prostate cancer. Patients diagnosed with a locally confined tumor can be cured by radical prostatectomy or by radiation therapy. No curative treatment is currently available for patients with distantly spread disease. More than 80% of men will develop prostate cancer by the age of 80. However, in the majority of cases, it will be slow-growing and harmless. In such men, diagnosing prostate cancer is over-diagnosis, the needless identification of a technically aberrant condition that will never harm the patient, and treatment in such men exposes them to all of the adverse effects, with no possibility of extending their lives.
In vivo pre-clinical models have shown that while progression from normal prostatic epithelium to invasive cancer is driven by molecular alterations, tumor cells and cells in the cancer microenvironment co-exist, are co-dependent and co-evolve. In addition, stromal cells may acquire the ability to mimic other cell types, e.g., bone cells. Whereas benign epithelium in prostates with and without tumor is similar in gene expression space, stroma away from the tumor is very different from that in cystoprostatectomies.
Prostate Cancer Treatment
Treatment of prostate cancer varies depending on individual situations; however, some treatment options include expectant management or active surveillance, surgery, radiation therapy, cryosurgery (cryotherapy), hormone therapy, chemotherapy, vaccine treatment or bone-directed treatment. The treatments are generally used one at a time, although they may be combined in certain situations.
Active surveillance monitors the cancer closely with regular prostate-specific antigen (PSA) blood tests, digital rectal exams, and ultrasounds. Often, the tests are performed about every 3-6 months. Men with slow-growing cancers often opt for active surveillance because it is not yet known whether treating the cancer with surgery or radiation will increase the patient's life expectancy.
Surgery is often a commonly elected treatment for prostate cancer if the cancer is thought not to have spread outside the glands. The main type of surgery for prostate cancer treatment is called radical prostatectomy. Often, the surgeon removes the entire prostate (or part of it) plus some of the tissue around it, including the seminal vesicles. The surgery may be done by open surgery or through laparoscopic surgery (through small incisions).
Radiation therapy may be used in prostate cancer as the first treatment for low-grade cancer that is sequestered to the prostate gland. Additionally, radiation therapy can be used in a patient as part of the first treatment for cancers that have spread outside of the prostate gland and into adjacent tissues. Radiation therapy is an option in situations in which the cancer recurs or was not completely removed, or in advanced-stage cancer. The therapy may be used to reduce the size of the tumor and to provide relief from symptoms for the patient.
Cryosurgery is a method used to treat early-stage prostate cancer (or if the cancer has recurred after other treatments). This approach involves freezing the cancer by passing cold gasses through hollow probes which are inserted into the prostate. The cold gases create ice balls that destroy the prostate.
The goal of hormone therapy is to reduce the level of male hormones, androgens testosterone and dihydrotestoterone (DHT), and to stop them from affecting prostate cancer cells, by either shrinking prostate cancer cells, or decreasing prostate cancer cell growth rate. Hormone therapy alone often does not cure prostate cancer. Situations in which hormone therapy may be used include: if the cancer has spread enough such that surgery and radiation are not viable options, if the cancer remains or recurs with other treatments, in combination with radiation as an initial treatment, or before radiation to try to shrink the cancer and make the radiation treatment more effective.
Chemotherapy may be used to treat prostate cancer in situations in which the cancer has spread outside the prostate gland. Exemplary chemo drugs include doceaxel, cabazitaxel, mitoxantrone, estramustine, doxorubicin, etoposide and paclitaxel. Alternatively, a vaccine (e.g., sipuleucel-T) may be used to treat advanced prostate cancer that is no longer responding to other treatments. If the cancer has spread outside the prostate, preventing the spread of the cancer to the bones is a major goal of treatment. Bisphosphonates can help relieve pain that has spread to the bones.
In one embodiment, the active compounds are administered in combination therapy, i.e., combined with other agents, e.g., therapeutic agents, that are useful for treating pathological conditions or disorders, such as various forms of cancer, autoimmune disorders and inflammatory diseases. The term “in combination” in this context means that the agents are given substantially contemporaneously, either simultaneously or sequentially. If given sequentially, at the onset of administration of the second compound, the first of the two compounds is preferably still detectable at effective concentrations at the site of treatment.
Prostatic Intraepithelial Neoplasia
PIN (prostatic intraepithelial neoplasia) is a condition in which some prostate cells have begun to look and behave abnormally. The abnormal cells are located in two areas: the lining of tiny sacs known as acini, which give the prostate its sponge-like composition and produce fluid that is added to sperm to create semen; and the lining of the ducts that carry this fluid to the main ejaculatory duct that reaches the penis. When PIN develops, the epithelial cells lining the acini and ducts become abnormal, but the lining itself remains intact. In contrast, when prostate cancer develops, the epithelial lining is ruptured and the malignant cells penetrate into the tissue of the prostate gland itself. To further complicate matters, a related condition known as proliferative inflammatory atrophy (PIA) may also develop in the same area of the prostate, and may also increase cancer risk.
In high-grade PIN, the degree of cellular abnormality is more pronounced than in low-grade PIN. Several pieces of evidence also indicate that high-grade PIN is more likely to lead to the development of prostate cancer. First, high-grade PIN tends to arise in the peripheral zone of the prostate, which is where most cases of prostate cancer develop. Second, an autopsy study has shown that 82% of prostate specimens with cancer also had areas of high-grade PIN, while only 43% of those without prostate cancer had areas of high-grade PIN. Third, most studies that have compared outcomes have found that men with high-grade PIN have an increased risk of being diagnosed with prostate cancer during a follow-up biopsy, when compared with men whose initial biopsies revealed low-grade PIN or normal tissue.
High-grade PIN is characterized by cells that share many genetic and molecular similarities with cancer cells. In high-grade PIN, the cell nucleus, which contains genetic material, is often enlarged, and particular components of the nucleus become abnormal, all of which may contribute to increasingly atypical behavior that can push the cells further down the path to malignancy. Over time, the abnormal cells may begin to proliferate excessively while becoming resistant to the programmed cell death that normally makes room for new cells by eliminating old ones. Malignant tumors grow partly because abnormal cells proliferate more than normal, but also because these cells somehow resist apoptosis. The result may be the out-of-control cell growth characteristic of cancer. High-grade PIN does not always progress to full-fledged invasive prostate cancer.
Prostate Cancer Diagnosis
Prostate cancer is diagnosed by biopsy—the removal of small pieces of the prostate for microscopic examination. Medical imaging may then be done to determine if the cancer has spread to other parts of the body. However, prior to a biopsy, less invasive testing can be conducted. There are also several other tests that can be used to gather more information about the prostate and the urinary tract. For example, a digital rectal examination (DRE) may allow a doctor to detect prostate abnormalities. Also, cystoscopy shows the urinary tract from inside the bladder, using a thin, flexible camera tube inserted down the urethra. Transrectal ultrasonography creates a picture of the prostate using sound waves from a probe in the rectum.
Gleason Score
A “Gleason score” or “Gleason grade” evaluates the prognosis of men with prostate cancer using samples from a prostate biopsy. Prostate cancer cells in biopsy samples are given a Gleason grade. The grade describes the aggressiveness of the cancer, and its likelihood to grow and spread outside the prostate. The system describes a score between 2 and 10, with 2 being the least aggressive and being 10 the most aggressive. When cancer cells are seen under the microscope, they have different patterns, depending on how quickly they're likely to grow. The pattern is given a grade from 1 to 5, based on how much the arrangement of cancer cells mimics normal prostate cells from glands. This is called the Gleason grade. If a grade is given, it will usually be 3 or higher, as grades 1 and 2 are not cancerous. To be counted, a pattern (grade) needs to occupy more than 5% of the biopsy specimen. The scoring system requires biopsy material (core biopsy or operative specimens) in order to be accurate (cytological preparations cannot be used).
The “Gleason Grade” is a commonly used prostate cancer grading system. There may be more than one grade of cancer in the biopsy sample. An overall Gleason score adds together two Gleason grades. The first (primary grade) is the most common grade in all the samples, and has to be greater than 50% of the total pattern observed). The second (secondary grade) is the highest grade of what's left, and has to be less than 50%, but at least 5% of the pattern of the total pattern observed). When these two grades are added together, the total is called the Gleason score. The higher the Gleason score, the more aggressive the cancer, and the more likely it is to spread. The Gleason system is based exclusively on the architectural pattern of the glands of the prostate tumor. It evaluates how effectively the cells of any particular cancer are able to structure themselves into glands resembling those of normal prostate. The ability of a tumor to mimic normal gland architecture is called its differentiation, and a tumor whose structure is nearly normal (well differentiated) will probably have a biological behavior relatively close to normal (e.g., not very aggressively malignant).
A Gleason grading from very well differentiated (grade 1) to very poorly differentiated (grade 5) is usually done for the most part by viewing the low magnification microscopic image of the cancer. There are important additional details which require higher magnification, and an ability to accurately grade any tumor is achieved only through much training and experience in pathology.
Gleason Grades 1 and 2: These two grades closely resemble normal prostate. These grades seldom occur in the general population confer a prognostic benefit which is only slightly better than grade 3. The glands are round to oval shaped and proportionally large (as compared to a Gleason pattern of 3), and are approximately equal in size and shape to one another. Both of these grades are composed by mass; in grade 2 they are more loosely aggregated, and some glands wander (invade) into the surrounding muscle (stroma).
Gleason Grade 3: This is the most common grade and is also considered well differentiated (like grades 1 and 2). This is because all three grades have a normal “gland unit” like that of a normal prostate; that is, every cell is part of a circular row which forms the lining of a central space (the lumen). The lumen contains prostatic secretion like normal prostate, and each gland unit is surrounded by prostate muscle which keeps the gland units apart. In contrast to grade 2, wandering of glands (invading) into the stroma (muscle) is very prominent and is the main defining feature. The cells are dark rather than pale and the glands often have more variable shapes, and are often long and/or angular. The glands are usually small/micro-glandular in comparison to Gleason 1 or 2 grades.
Gleason Grade 4: This is a fairly common grade and is often (but not always) associated with a poor patient prognosis. Grade 4 is associated with a loss of architecture. For the first time, disruption and loss of the normal gland unit is observed. In fact, grade 4 is identified almost entirely by loss of the ability to form individual, separate gland units, each with its separate lumen (secretory space). Much experience is required for this diagnosis.
Gleason Grade 5: Gleason grade 5 is an important grade because it usually predicts another significant step towards poor prognosis. Grade 5 is less common than grade 4, and it is seldom seen in men whose prostate cancer is diagnosed early in its development. This grade shows a variety of patterns, all of which demonstrate no evidence of any attempt to form gland units. This grade is often called undifferentiated, because its features are not significantly distinguishing to make it look any different from undifferentiated cancers which occur in other organs.
When a pathologist looks at prostate cancer specimens under the microscope and gives them a Gleason grade, an attempt to identify two architectural patterns and assign a Gleason grade to each one is made. There may be a primary or most common pattern and then a secondary or second most common pattern and then a secondary or second most common pattern which the pathologist will seek to describe for each specimen; alternatively there may often be only a single pure grade.
The combined Gleason sums or scores may be determined as follows:
2 (1+1): The lowest possible Gleason score is 2, where both the primary and secondary patterns have a Gleason grade of 1.
5 (2+3): The primary pattern has a Gleason grade of 2 and the secondary pattern has grade 3.
6 (3+3): a pure Gleason pattern. The lowest Gleason score of a cancer is found on a prostate biopsy is a 6. All of the cancer cells found in the biopsy look likely to grow slowly. These cancers may be called well-differentiated or low-grade and are less aggressive.
(7) 3+4: Most of the cancer cells found in the biopsy look likely to grow slowly. There are some cancer cells that look more likely to grow at a more moderate rate.
(7) 4+3: Most of the cancer cells found in the biopsy look likely to grow at a moderate rate; there are some cancer cells that look likely to grow slowly.
(8) 4+4—All of the cancer cells found in the biopsy look likely to grow at a moderately quick rate; these cancers tend to be aggressive.
(9) 4+5—Most of the cancer cells found in the biopsy look likely to grow at a moderately quick rate, and there are some cancer cells that are likely to grow more quickly.
(9) 5+4—Most of the cancer cells found in the biopsy look likely to grow quickly.
(10) 5+5—All of the cancer cells found in the biopsy look likely to grow quickly.
Tumors with Gleason scores of 8-10 tend to be advanced neoplasms that are unlikely to be cured. Although prostate cancers may become more aggressive over time, most often, the Gleason score remains stable for several years.
Gene Expression Profiling
Gene expression profiling (GEP) in the tumor-adjacent stroma is strongly associated with Gleason grade. In general, methods of gene expression profiling can be divided into two large groups: methods based on hybridization analysis of polynucleotides, and methods based on sequencing of polynucleotides. Methods known in the art for the quantification of mRNA expression in a sample include northern blotting and in situ hybridization, RNAse protection assays, and reverse transcription polymerase chain reaction (RT-PCR). Alternatively, antibodies are employed that recognize specific duplexes, including DNA duplexes, RNA duplexes, and DNA-RNA hybrid duplexes or DNA-protein duplexes. Representative methods for sequencing-based gene expression analysis include Serial Analysis of Gene Expression (SAGE), and gene expression analysis by massively parallel signature sequencing (MPSS). For example, RT-PCR is used to compare mRNA levels in different sample populations, in normal and tumor tissues, with or without drug treatment, to characterize patterns of gene expression, to discriminate between closely related mRNAs, and/or to analyze RNA structure.
In some cases, a first step in gene expression profiling by RT-PCR is the reverse transcription of the RNA template into cDNA, followed by amplification in a PCR reaction. For example, extracted RNA is reverse-transcribed using a GeneAmp RNA PCR kit (Perkin Elmer, Calif., USA), following the manufacturer's instructions. The cDNA is then used as template in a subsequent PCR amplification and quantitative analysis using, for example, a TaqMan® (Life Technologies, Inc., Grand Island, N.Y.) assay.
Microarrays
Differential gene expression can also be identified, or confirmed using a microarray technique. In these methods, polynucleotide sequences of interest (including cDNAs and oligonucleotides) are plated, or arrayed, on a microchip substrate. The arrayed sequences are then hybridized with specific DNA probes from cells or tissues of interest. Just as in the RT-PCR method, the source of mRNA typically is total RNA isolated from human tumors or tumor cell lines and corresponding normal tissues or cell lines. Thus, RNA is isolated from a variety of primary tumors or tumor cell lines. If the source of mRNA is a primary tumor, mRNA is extracted from frozen or archived tissue samples.
In the microarray technique, PCR-amplified inserts of cDNA clones are applied to a substrate in a dense array. The microarrayed genes, immobilized on the microchip, are suitable for hybridization under stringent conditions.
In some cases, fluorescently labeled cDNA probes are generated through incorporation of fluorescent nucleotides by reverse transcription of RNA extracted from tissues of interest (e.g., prostate tissue). Labeled cDNA probes applied to the chip hybridize with specificity to loci of DNA on the array. After washing to remove non-specifically bound probes, the chip is scanned by confocal laser microscopy or by another detection method, such as a charge-coupled device (CCD) camera. Quantification of hybridization of each arrayed element allows for assessment of corresponding mRNA abundance.
In some configurations, dual color fluorescence is used. With dual color fluorescence, separately labeled cDNA probes generated from two sources of RNA are hybridized pairwise to the array. The relative abundance of the transcripts from the two sources corresponding to each specified gene is thus determined simultaneously. In various configurations, the miniaturized scale of the hybridization can afford a convenient and rapid evaluation of the expression pattern for large numbers of genes. In various configurations, such methods can have sensitivity required to detect rare transcripts, which are expressed at fewer than 1000, fewer than 100, or fewer than 10 copies per cell. In various configurations, such methods can detect at least approximately two-fold differences in expression levels (Schena et al., Proc. Natl. Acad. Sci. USA 93(2): 106-149 (1996)). In various configurations, microarray analysis is performed by commercially available equipment, following manufacturer's protocols, such as by using the Affymetrix GenChip technology, or Incyte's microarray technology.
RNA-Seq
RNA sequencing (RNA-seq), also called whole transcriptome shotgun sequencing (WTSS), uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample at a given moment in time.
RNA-Seq is used to analyze the continually changing cellular transcriptome. See, e.g., Wang et al., 2009 Nat Rev Genet, 10(1): 57-63, incorporated herein by reference. Specifically, RNA-Seq facilitates the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/SNPs and changes in gene expression. In addition to mRNA transcripts, RNA-Seq can look at different populations of RNA to include total RNA, small RNA, such as miRNA, tRNA, and ribosomal profiling. RNA-Seq can also be used to determine exon/intron boundaries and verify or amend previously annotated 5′ and 3′ gene boundaries.
Prior to RNA-Seq, gene expression studies were done with hybridization-based microarrays. Issues with microarrays include cross-hybridization artifacts, poor quantification of lowly and highly expressed genes, and needing to know the sequence of interest. Because of these technical issues, transcriptomics transitioned to sequencing-based methods. These progressed from Sanger sequencing of Expressed Sequence Tag libraries, to chemical tag-based methods (e.g., serial analysis of gene expression), and finally to the current technology, NGS of cDNA (notably RNA-Seq).
Gene Set Enrichment Analysis
By “ssGSEA” is meant single-sample Gene Set Enrichment Analysis. When analyzing genome-wide transcription profiles from microarray data, a typical goal is to find genes significantly differentially correlated with distinct sample classes defined by a particular phenotype (e.g., tumor vs. normal). These findings can be used to provide insights into the underlying biological mechanisms or to classify (predict the phenotype of) a new sample. Gene Set Enrichment Analysis (GSEA) evaluates whether a priori defined sets of genes, associated with particular biological processes (such as pathways), chromosomal locations, or experimental results are enriched at either the top or bottom of a list of differentially expressed genes ranked by some measure of differences in a gene's expression across sample classes. Examples of ranking metrics are fold change for categorical phenotypes (e.g., tumor vs. normal) and Pearson correlation for continuous phenotypes (e.g., age). Enrichment provides evidence for the coordinate up- or down-regulation of a gene set's members and the activation or repression of some corresponding biological process.
Where GSEA generates a gene set's enrichment score with respect to phenotypic differences across a collection of samples within a dataset, ssGSEA calculates a separate enrichment score for each pairing of sample and gene set, independent of phenotype labeling. In this manner, ssGSEA transforms a single sample's gene expression profile to a gene set enrichment profile. A gene set's enrichment score represents the activity level of the biological process in which the gene set's members are coordinately up- or down-regulated. This transformation allows researchers to characterize cell state in terms of the activity levels of biological processes and pathways rather than through the expression levels of individual genes.
In working with the transformed data, the goal is to find biological processes that are differentially active across the phenotype of interest and to use these measures of process activity to characterize the phenotype. Thus, the benefit here is that the ssGSEA projection transforms the data to a higher-level (pathways instead of genes) space representing a more biologically interpretable set of features on which analytic methods can be applied.
Bone Homing Signature
As described in Table 1, a 29-gene signature was defined herein (7 epithelial and 22 stromal genes), which distinguishes Gleason 6 from Gleason 8, which comprise the “bone homing signature.”
In another case, the “bone homing signature” is described in Table 24, which provides a 24 gene signature that distinguishes low grade from high grade Gleason score.
Exemplary distinguishing genes are provided below.
An exemplary human ALCAM amino acid sequence is set forth the below (SEQ ID NO: 1; GenBank Accession No: AAI37097, Version 1 (GI: 187951595), incorporated herein by reference):
Exemplary regions or fragments of ALCAM include residues 38-113 (immunoglobulin V-type region), 260-330 (immunoglobulin V-type region), 334-412 (immunoglobulin V-type region), and 339-393 (immunoglobulin V-type region).
An exemplary human ALCAM nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 2; GenBank Accession No. BC137096, Version 1 (GI: 187951594), incorporated herein by reference):
Exemplary regions or fragments of ALCAM include bases 125-1876 (activated leukocyte cell adhesion molecule).
An exemplary human LUM amino acid sequence is set forth below (SEQ ID NO: 3; GenBank Accession No. NP_002336, Version 1 (GI: 4505047), incorporated herein by reference):
Exemplary regions or fragments of LUM include residues 1-18 (signal peptide), 37-71 (leucine rich repeats), 66-128 (leucine rich repeats), 75-260 (substrate binding site), and 161-185 (leucine rich repeats).
An exemplary human LUM nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 4; GenBank Accession No. NM_002345, Version 3 (GI: 61742794), incorporated herein by reference):
Exemplary regions or fragments of LUM include bases 2003-2008 (polyA signal sequence), and 1302-1367.
An exemplary human COL1A1 amino acid sequence is set forth below (SEQ ID NO: 5; GenBank Accession No. CAA6726, Version 1 (GI: 1888409), incorporated herein by reference):
Exemplary regions or fragments of COL1A1 include residues 236-295 (triple helix repeat), 452-535 (triple helix repeat), and 701-759 (triple helix repeat).
An exemplary human COL1A1 nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 6; GenBank Accession No. X98705, Version 1 (GI: 1888408), incorporated herein by reference):
Exemplary regions or fragments of COL1A1 include bases 4168-4362, 4501-4535, 4638-4673, 7421-7474, 10309-10603 and 10608-10634.
An exemplary human BGN amino acid sequence is set forth below (SEQ ID NO: 7; GenBank Accession No. NP_001702, Version 1 (GI: 4502403), incorporated herein by reference):
Exemplary regions or fragments of BGN include residues 20-368, 62-94 (leucine rich repeat), 82-102, 92-115 (leucine rich repeat), 95-321, 279-295, and 313-342.
An exemplary human BGN nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 8; GenBank Accession No. NM_001711, Version 4 (GI: 268607602), incorporated herein by reference):
Exemplary regions or fragments of BGN include bases 348-1340 (mature protein), 543-614, 687-749, 1263-1340, 2421-2426 (regulatory site), and 244 (polyA site).
An exemplary human C1QC amino acid sequence is set forth below (SEQ ID NO: 9; GenBank Accession No. AAH09016, Version 1 (GI: 14290496), incorporated herein by reference):
Exemplary regions or fragments of C1QC include residues 43-87 (collagen triple helix repeat and 113-245 (complement component).
An exemplary human C1QC nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 10; GenBank Accession No. BC009016, Version 1 (GI: 14290495), incorporated herein by reference):
Exemplary regions or fragments of C1QC include bases 194-827, 827-911, 1061-1062, and 116-1147.
An exemplary human C1S amino acid sequence is set forth below (SEQ ID NO: 11; GenBank Accession No. AAH56903, Version 1 (GI: 34785163), incorporated herein by reference):
Exemplary regions or fragments of C1S include residues 18-129, 131-171, 175-287, 294-355 and 438-678.
An exemplary human C1S nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 12; GenBank Accession No. BC056903, Version 1 (GI: 34785162), incorporated herein by reference):
Exemplary regions or fragments of C1S include bases 2752-2790. An exemplary human C1QB amino acid sequence is set forth below (SEQ ID NO: 13; GenBank Accession No. 3RPX_B, Version 1 (GI: 332639950), incorporated herein by reference):
Exemplary regions or fragments of C1QB include residues 4-184, 13-20, 114-118, 138-151, and 155-184.
An exemplary human C1QB nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 14; GenBank Accession No. NM_00491, Version 3 (GI: 87298827), incorporated herein by reference):
Exemplary regions or fragments of C1QB include bases 214-216, 334-526, 509-658 and 663-916.
An exemplary human HLA-DRB3 amino acid sequence is set forth below (SEQ ID NO: 15) GenBank Accession No. NP_072049, Version 2 (GI: 17986005), incorporated herein by reference:
Exemplary regions or fragments of HLA-DRB3 include residues 1-29, 30-266, 30-124, 42-116, and 125-227.
An exemplary human HLA-DRB3 nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 16; GenBank Accession No. NM_0022555, Version 3 (GI: 18641371), incorporated herein by reference):
a
agtgcagat gacaatttaa ggaagaatct tctgccccag ctttgcagga tgaaaagctt
Exemplary regions or fragments of HLA-DRB3 include bases 41-841, 41-127, 128-838, 128-412, 141-410, 176-407, 1133-1138 (regulatory site), and 1158 (polyA site).
An exemplary human AEBP1 amino acid sequence is set forth below (SEQ ID NO: 17; GenBank Accession No. BAD92981, Version 1 (GI: 62089074), incorporated herein by reference):
Exemplary regions or fragments of AEBP1 include residues 400-553, 448-483, 574-917, 921-996, and 921-996.
An exemplary human AEBP1 nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 18; GenBank Accession No. AB209744, Version 1 (GI: 62089073), incorporated herein by reference):
Exemplary regions or fragments of AEBP1 include bases 218-3736.
An exemplary human SFRP4 amino acid sequence is set forth below (SEQ ID NO: 19; GenBank Accession No. EAW94085, Version 1 (GI: 119614491), incorporated herein by reference):
Exemplary regions or fragments of SFRP4 include residues 42-168, 210-318, and 311-366.
An exemplary human SFRP4 nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 20; GenBank Accession No. NM_003014, Version 3 (GI: 170784837), incorporated herein by reference):
Exemplary regions or fragments of SFRP4 include bases 387-1427, 387-440, 525-1024, 979-1177, and 1178-1241.
An exemplary human FBLN5 amino acid sequence is set forth below (SEQ ID NO: 21; GenBank Accession No. AAH22280, Version 1 (GI: 18490145), incorporated herein by reference):
Exemplary regions or fragments of FBLN5 include residues 125-165, 207-238 and 258-286.
An exemplary human FBLN5 nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 22; GenBank Accession No. BC022280, Version 1 (GI: 18490144), incorporated herein by reference):
Exemplary regions or fragments of FBLN5 include bases 184-1530 and 1128-1530.
An exemplary human FCGR2C amino acid sequence is set forth below ((SEQ ID NO: 23) GenBank Accession No. NP_963857, Version 3 (GI: 126116592), incorporated herein by reference):
Exemplary regions or fragments of FCGR2C include residues 1-45 (signaling peptide), 43-323, 50-128, 56-128, 138-214, and 224-246.
An exemplary human FCGR2C nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 24; GenBank Accession No. NM_201563, Version 5 (GI: 586946409), incorporated herein by reference):
Exemplary regions or fragments of FCGR2C include bases 100-1071, 100-234, 226-1068, 769-837 and 979-981.
An exemplary human C1QA amino acid sequence is set forth below (SEQ ID NO: 25; GenBank Accession No. EAW95015, Version 1 (GI: 119615421), incorporated herein by reference):
Exemplary regions or fragments of C1QA include residues 48-106, and 108-244.
An exemplary human C1QA nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 26; GenBank Accession No. NM_015991, Version 2 (GI: 87298824), incorporated herein by reference):
Exemplary regions or fragments of C1QA include bases 86-151, 182-184, 200-202, 996-1001 and 249-1098.
An exemplary human SFRP2 amino acid sequence is set forth below (SEQ ID NO: 27; GenBank Accession No. NP_003004, Version 1 (GI: 48475052), incorporated herein by reference):
Exemplary regions or fragments of SFRP2 include residues 1-295, 20-295, 1-19, 36-163 and 169-295.
An exemplary human SFRP2 nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 28; GenBank Accession No. NM_003013, Version 2 (GI: 52630413), incorporated herein by reference):
Exemplary regions or fragments of SFRP2 include bases 1-743, 242-1129, 242-298 and 299-1126.
An exemplary human SULF1 amino acid sequence is set forth below (SEQ ID NO: 29; GenBank Accession No. AAH68565, Version 1 (GI: 46249932), incorporated herein by reference):
Exemplary regions or fragments of SULF1 include residues 1-644, 39-133, 122-147 and 292-439.
An exemplary human SULF1 nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 30; GenBank Accession No. BC068565, Version 1 (GI: 46249931), incorporated herein by reference):
Exemplary regions or fragments of SULF1 include bases 1-3019, 64-1998 and 3005-3019.
An exemplary human THBS2 amino acid sequence is set forth below (SEQ ID NO: 31; GenBank Accession No. AAI50176, Version 1 (GI: 152012473), incorporated herein by reference):
Exemplary regions or fragments of THBS2 include residues 320-374, 440-492, 765-787, 789-823, 802-820, 886-897 and 899-917.
An exemplary human THBS2 nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 32; GenBank Accession No. BC150175, Version 1 (GI: 152012472), incorporated herein by reference):
Exemplary regions or fragments of THBS2 include bases 1-5314, 132-3650 and 136-3650.
An exemplary human MOXD1 amino acid sequence is set forth below (SEQ ID NO: 33; GenBank Accession: AAH18756, Version 1 (GI: 17511810), incorporated herein by reference):
Exemplary regions or fragments of MOXD1 include residues 29-165, 187-318, 333-485 and 1-613.
An exemplary human MOXD1 nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 34; GenBank Accession No. BC018756, Version 1 (GI: 17511809), incorporated herein by reference):
Exemplary regions or fragments of MOXD1 include bases 68-1909 and 2167-2188. An exemplary human SERPING1 amino acid sequence is set forth below (SEQ ID NO: 35; GenBank Accession No. NP_001027466, Version 1 (GI: 7385870), incorporated herein by reference):
Exemplary regions or fragments of SERPING1 include residues 1-22, 23-500, 85-119 and 453-476.
An exemplary human SERPING1 nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 36; GenBank Accession NM_001032295, Version 1 (GI: 73858569), incorporated herein by reference):
Exemplary regions or fragments of SERPING1 include bases 1435-1440, 1069-1288, 292-396 and 40-105.
An exemplary human PRELP amino acid sequence is set forth below (SEQ ID NO: 37; GenBank Accession No. NP_001027466, Version 1 (GI: 7382870), incorporated herein by reference):
Exemplary regions or fragments of PRELP include residues 85-119, 145-495, 453-476 and 466-500.
An exemplary human PRELP nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 38; GenBank Accession No. CR542270, Version 1 (GI: 49457533), incorporated herein by reference):
atg
aggtcac ccctctgctg gctcctccca cttctcatct tggcctcagt ggcccaaggc
Exemplary regions or fragments of PRELP include bases 1-1149.
An exemplary human CD52 amino acid sequence is set forth below (SEQ ID NO: 39; GenBank Accession No. NP_001794, Version 2 (GI: 68342030), incorporated herein by reference):
Exemplary regions or fragments of CD52 include residues 1-61 and 43-61.
An exemplary human CD52 nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 40; GenBank Accession No. BC000644, Version 2 (GI: 37588979), incorporated herein by reference):
Exemplary regions or fragments of CD52 include bases 1-467, 43-228 and 450-467.
An exemplary human LTBP2 amino acid sequence is set forth below (SEQ ID NO: 41; GenBank Accession No. AAH78659, Version 1 (GI: 50927279), incorporated herein by reference):
Exemplary regions or fragments of LTBP2 include residues 622-655, 681-723, 930-961, 970-1005, 1218-1249 and 1774-1808.
An exemplary human LTBP2 nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 42; GenBank Accession No. BC078659, Version 1 (GI: 50927278), incorporated herein by reference):
Exemplary regions or fragments of LTBP2 include bases 294-5759, 779-2795, 6689-6690, and 6886-6901.
An exemplary human ITGA11 amino acid sequence is set forth below (SEQ ID NO: 43; GenBank Accession No. AAD51919, Version 2 (GI: 5915662), incorporated herein by reference):
Exemplary regions or fragments of ITGA11 include residues 163-341, 291-331, 358-449, 635-1070 ad 538-592.
An exemplary human ITGA11 nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 44; GenBank Accession No. AF137378, Version 2 (GI: 5915661), incorporated herein by reference):
Exemplary regions or fragments of ITGA11 include bases 91-3657, 961-963, 1081-1083, 91-156, and 3265-3267.
An exemplary human TNS3 amino acid sequence is set forth below (SEQ ID NO: 45; GenBank Accession No. AAN32667, Version 1 (GI: 23451123), incorporated herein by reference):
Exemplary regions or fragments of TNS3 include residues 72-186, 173-299, 1168-1284, and 1308-1439.
An exemplary human TNS3 nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 46; GenBank Accession No. AF417489, Version 1 (GI: 23451122), incorporated herein by reference):
Exemplary regions or fragments of TNS3 include bases 10-4347.
An exemplary human C12orf51 amino acid sequence is set forth below (SEQ ID NO: 47; GenBank Accession No. AAI43385, Version 1 (GI: 219521788), incorporated herein by reference):
Exemplary regions or fragments of C12orf51 include residues 1-653.
An exemplary human C12orf51 nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 48; GenBank Accession No. BC143384, Version 1 (GI: 219521787), incorporated herein by reference):
Exemplary regions or fragments of C12orf51 include bases 1-2100, and 72-2033.
An exemplary human TMEM205 amino acid sequence is set forth below (SEQ ID NO: 49) GenBank Accession No. NP_940938, Version 1 (GI: 63055043), incorporated herein by reference):
Exemplary regions or fragments of TMEM205 include residues 17-114, 18-38, 81-101, and 166-186.
An exemplary human TMEM205 nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 50; GenBank Accession NM_198536, Version 2 (GI: 224028276), incorporated herein by reference):
Exemplary regions or fragments of TMEM205 include bases 633-635, 687-1256, 843-905 and 927-989.
An exemplary human HSPA9 amino acid sequence is set forth below (SEQ ID NO: 51; GenBank Accession No. AAH24034, Version 1 (GI: 18645123), incorporated herein by reference):
Exemplary regions or fragments of HSPA9 include residues 52-673, 52-428, and 387-391.
An exemplary human HSPA9 nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 52; GenBank Accession No. BC024034, Version 2 (GI: 38196942), incorporated herein by reference):
Exemplary regions or fragments of HSPA9 include bases 43-2082, 263-900, and 2786-2802.
An exemplary human CLDN8 amino acid sequence is set forth below (SEQ ID NO: 53; GenBank Accession No. BAA95567, Version 1 (GI: 7768788), incorporated herein by reference):
Exemplary regions or fragments of CLDN8 include residues 1-225 and 5-182.
An exemplary human CLDN8 nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 54; GenBank Accession No. NM_199328, Version 2 (GI: 297206863), incorporated herein by reference):
Exemplary regions or fragments of CLDN8 include bases 206-208, 248-310, 470-532, 578-640 and 725-787.
An exemplary human PTPLAD1 amino acid sequence is set forth below (SEQ ID NO: 55; GenBank Accession No. AAH35508, Version 1 (GI: 27370575), incorporated herein by reference):
Exemplary regions or fragments of PTPLAD1 include residues 8-115, and 195-358.
An exemplary human PTPLAD1 nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 56; GenBank Accession No. BC035508, Version 1 (GI: 23271044), incorporated herein by reference):
Exemplary regions or fragments of PTPLAD1 include bases 1-5, 149-1231 and 1222-1231.
An exemplary human MAL2 amino acid sequence is set forth below (SEQ ID NO: 57; GenBank Accession No. EAW91981, Version 1 (GI: 119612387), incorporated herein by reference):
Exemplary regions or fragments of MAL2 include residues 1-176 and 32-169.
An exemplary human MAL2 nucleotide sequence (the start and stop codons for the coding sequences are bold and underlined) is set forth below (SEQ ID NO: 58; GenBank Accession No. NM_052886, Version 2 (GI: 109633023), incorporated herein by reference):
Exemplary regions or fragments of MAL2 include bases 1-234, 205-267, 301-363, 409-471, and 550-612.
An exemplary human ANTXR1 nucleotide sequence is set forth below (SEQ ID NO: 59; GenBank Accession No. NM_053034.2, Version 2, incorporated herein by reference):
An exemplary human ANTXR1 amino acid sequence is set for the below (SEQ ID NO: 60; GenBank Accession No: AAH12074.1, Version 1, incorporated herein by reference):
An exemplary human C1R nucleotide sequence is set forth below (SEQ ID NO: 61; GenBank Accession No. NM_001733.4, Version 4, incorporated herein by reference):
An exemplary human C1R amino acid sequence is set for the below (SEQ ID NO: 62; GenBank Accession No: AAA51851.1, Version 1, incorporated herein by reference):
An exemplary human CDH11 nucleotide sequence is set forth below (SEQ ID NO: 63; GenBank Accession No. NM_001797.3, Version 3, incorporated herein by reference):
An exemplary human CDH11 amino acid sequence is set for the below (SEQ ID NO: 64; GenBank Accession No: NP_001317505.1, Version 1, incorporated herein by reference):
An exemplary human COL3A1 nucleotide sequence is set forth below (SEQ ID NO: 65; GenBank Accession No. NM_000090.3, Version 3, incorporated herein by reference):
An exemplary human COL3A1 amino acid sequence is set for the below (SEQ ID NO: 66; GenBank Accession No: AAH28178.1, Version 1, incorporated herein by reference):
An exemplary human FCGR2B nucleotide sequence is set forth below (SEQ ID NO: 67; GenBank Accession No. NM_004001.4, Version 4, incorporated herein by reference):
An exemplary human FCGR2B amino acid sequence is set for the below (SEQ ID NO: 68; GenBank Accession No: AAI46679.1, Version 1, incorporated herein by reference):
An exemplary human HLA-DRB1 nucleotide sequence is set forth below (SEQ ID NO: 69; GenBank Accession No. NM_001243965.1, Version 1, incorporated herein by reference):
An exemplary human HLA-DRB1 amino acid sequence is set for the below (SEQ ID NO: 70; GenBank Accession No: BAO73164.1, Version 1, incorporated herein by reference):
An exemplary human RNASE1 nucleotide sequence is set forth below (SEQ ID NO: 71; GenBank Accession No. NM_198235.2, Version 2, incorporated herein by reference):
An exemplary human RNASE1 amino acid sequence is set for the below (SEQ ID NO: 72; GenBank Accession No: AAH22882.1, Version 1, incorporated herein by reference):
An exemplary human THY1 nucleotide sequence is set forth below (SEQ ID NO: 73; GenBank Accession No. NM_006288.4, Version 4, incorporated herein by reference):
An exemplary human THY1 amino acid sequence is set for the below (SEQ ID NO: 74; GenBank Accession No: AAA61180.1, Version 1, incorporated herein by reference):
An exemplary human TMSB4X nucleotide sequence is set forth below (SEQ ID NO: 75; GenBank Accession No. NM_021109.3, Version 3, incorporated herein by reference):
An exemplary human TMSB4X amino acid sequence is set for the below (SEQ ID NO: 76; GenBank Accession No: AAI51216.1, Version 1, incorporated herein by reference):
As described in detail below, due to the inherent heterogeneity of prostate cancer and the lack of single therapeutic agents that have wide ranging impact on prostate cancer progression, in particular advanced and/or metastatic disease, the interplay between the tumor gland and its surrounding microenvironment (adjacent stroma) provided evidence of how the tumor grows and metastasizes. It also raised implications as to whether monitoring the stromal environment has clinical utility in patients that could relapse or have relapsed. Relapsed patients almost always develop metastatic disease.
The genotype of prostate epithelial tumors is considered the most important determinant of prostate cancer growth and metastasis (Chung L W. et al., J Urol. 173, 10-20 (2005). However, the tumor microenvironment has garnered increasing amounts of attention as a critical driver and enhancer of prostate cancer progression (Ganguly S S, et al., Front Oncol. 2014 4:364). The environment that surrounds benign, PIN, and malignant epithelia is comprised of fibroblasts, myofibroblasts, as well as endothelial, nerve, immune and inflammatory cells (Niu Y N, et al., Asian J Androl. 11, 28-35 (2009)). The bidirectional signaling between epithelial cells and stromal constituents during normal prostate homeostasis is disrupted early in tumorigenesis (Tuxhorn J A, et al., J Urol. 166, 2472-83 (2001) and Tuxhorn J A et al., Cancer Res. 62, 6021-5 (2002)) when the stromal compartment becomes disorganized and normal fibroblasts begin to be replaced by cancer-associated fibroblasts (CAF's).
Xenografts and tissue recombination experiments have contributed to the definition of the role of stromal cells in prostate carcinogenesis. In fact, benign prostate epithelial cells undergo transformation when recombined with prostate cancer-derived CAFs (Hayward S W, et al., Cancer Res. 61, 8135-42 (2001)).
Signaling factors from the microenvironment influence epithelial cells to acquire properties such as increased motility, proliferation or migratory and invasive behavior (Thiery J P. et al., Nat Rev Cancer. 2, 442-54 (2002), Koeneman K S, et al., Prostate. 39, 246-61 (1999), and Leach D A, et al., Oncotarget. 2015 Apr. 19). TGFβ and Wnt signaling pathways play important regulatory roles in stromal-epithelial interactions in prostate development and prostatic carcinogenesis (Lee C, Jia Z, et al., Biomed Res Int. 2014; 2014:502093. doi: 10.1155/2014/502093. Epub 2014 Jun. 25, Yang F, et al., Oncotarget. 5, 10854-69 (2014), and Macheda M L, et al., Curr Cancer Drug Targets. 8, 454-65 (2008)). A variety of growth factors, PDGF, VEGF, IGF, FGF and HGH are involved in angiogenesis (Bhomick N A, et al., Nature. 432, 332-7 (2004), Muir C, et al., Clin Exp Metastasis. 23, 75-86 (2006), Johansson A, et al., Prostate. 67, 1664-76 (2007), Ohlson N, et al., Prostate. 67, 32-40 (2007), and Knudsen B S, et al., Adv Cancer Res. 91, 31-67 (2004)) and soluble cytokine and chemokine factors strongly influence the interaction between the epithelial and stromal compartment during prostate cancer progression (Wang J, et al., Cell Signal. 17, 1578-92 (2005), and Ao M, et al., Cancer Res. 67, 4244-53 (2007)). Extracellular Matrix (ECM) and cell adhesion molecule (CAM) degradation mediated through integrin-binding is involved in cancer cell invasion and metastasis (Ingber D E Differentiation. 70, 547-60 (2002)).
Transcriptome analysis has revealed many dysregulated genes that impact prostate cancer progression (Singh D, et al., Cancer Cell. 1, 203-9 (2002), Lapointe J, et al., Proc Natl Acad Sci. 101, 811-16 (2004), Yu Y P, et al., J Clin Oncol. 22, 2790-9 (220040), Tomlins S A, Nat Genet. 39, 41-51 (2007), Wallace T A, et al., Cancer Res. 68, 927-36 (2008), Penney K L, et al., J Clin Oncol. 29, 2391-6 (2011) and Grasso C S, et al., Nature. 487, 239-43 (2012)). However, prior to the invention described herein, there was a lack of knowledge regarding the extent to which the stroma contributes to the overall expression signature.
Laser-capture microdissection (LCM) has facilitated the isolation and study of specific cellular populations within the prostate tumor microenvironment. This technology, however, is labor-intensive, limiting large-scale efforts being undertaken. To date, differences between the tumor and its adjacent stroma in prostate cancer (Gregg J L, et al., BMC Cancer. 10, 1-14 (2010)) between normal and reactive stroma (Dakhova O, et al., Clin Cancer Res. 15, 3979-89 (2009)), epithelial differences between benign and tumor epithelium (Tomlins S A, et al., Nature Genetics 39, 41-51 (2007), and Furusato B, et al., Prostate Cancer Prostatic Dis. 11, 194-7 (2008) have been addressed utilizing LCM, albeit on a small scale.
The Gregg study utilized laser capture microdissection and whole transcriptome hybridization arrays in a small number of radical prostatectomy cases to look at differentially expressed genes between the tumor gland and its surrounding stromal area. The Gregg signature of upregulated stromal genes was recapitulated on the data set describecd herein, when comparing the tumor and its adjacent stroma.
As described herein, the progression of normal prostate to PIN to invasive cancer driven by molecular alterations in both epithelium and stroma, and that changes in the microenvironment contribute to tumor initiation, maintenance and progression. Therefore, as described below, it was assessed whether, in gene expression space, 1) epithelium and stroma (benign and malignant) were different; 2) whether non transformed epithelial and stromal tissues differed in prostates with and without tumor, and finally 3) how the stromal genes behaved in prostate cancer progression.
Pharmaceutical Therapeutics
For therapeutic uses, the compositions or agents described herein may be administered systemically, for example, formulated in a pharmaceutically-acceptable buffer such as physiological saline. Preferable routes of administration include, for example, subcutaneous, intravenous, interperitoneally, intramuscular, or intradermal injections that provide continuous, sustained levels of the drug in the patient. Treatment of human patients or other animals will be carried out using a therapeutically effective amount of a therapeutic identified herein in a physiologically-acceptable carrier. Suitable carriers and their formulation are described, for example, in Remington's Pharmaceutical Sciences by E. W. Martin. The amount of the therapeutic agent to be administered varies depending upon the manner of administration, the age and body weight of the patient, and with the clinical symptoms of the neoplasia, i.e., the prostate cancer. Generally, amounts will be in the range of those used for other agents used in the treatment of other diseases associated with neoplasia, although in certain instances lower amounts will be needed because of the increased specificity of the compound. For example, a therapeutic compound is administered at a dosage that is cytotoxic to a neoplastic cell.
Formulation of Pharmaceutical Compositions
The administration of a compound or a combination of compounds for the treatment of a neoplasia, e.g., a prostate cancer, may be by any suitable means that results in a concentration of the therapeutic that, combined with other components, is effective in ameliorating, reducing, or stabilizing a neoplasia. The compound may be contained in any appropriate amount in any suitable carrier substance, and is generally present in an amount of 1-95% by weight of the total weight of the composition. The composition may be provided in a dosage form that is suitable for parenteral (e.g., subcutaneously, intravenously, intramuscularly, or intraperitoneally) administration route. The pharmaceutical compositions may be formulated according to conventional pharmaceutical practice (see, e.g., Remington: The Science and Practice of Pharmacy (20th ed.), ed. A. R. Gennaro, Lippincott Williams & Wilkins, 2000 and Encyclopedia of Pharmaceutical Technology, eds. J. Swarbrick and J. C. Boylan, 1988-1999, Marcel Dekker, New York).
Human dosage amounts can initially be determined by extrapolating from the amount of compound used in mice, as a skilled artisan recognizes it is routine in the art to modify the dosage for humans compared to animal models. In certain embodiments it is envisioned that the dosage may vary from between about 1 μg compound/Kg body weight to about 5000 mg compound/Kg body weight; or from about 5 mg/Kg body weight to about 4000 mg/Kg body weight or from about 10 mg/Kg body weight to about 3000 mg/Kg body weight; or from about 50 mg/Kg body weight to about 2000 mg/Kg body weight; or from about 100 mg/Kg body weight to about 1000 mg/Kg body weight; or from about 150 mg/Kg body weight to about 500 mg/Kg body weight. In other cases, this dose may be about 1, 5, 10, 25, 50, 75, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 800, 850, 900, 950, 1000, 1050, 1100, 1150, 1200, 1250, 1300, 1350, 1400, 1450, 1500, 1600, 1700, 1800, 1900, 2000, 2500, 3000, 3500, 4000, 4500, or 5000 mg/Kg body weight. In other aspects, it is envisaged that doses may be in the range of about 5 mg compound/Kg body to about 20 mg compound/Kg body. In other embodiments, the doses may be about 8, 10, 12, 14, 16 or 18 mg/Kg body weight. Of course, this dosage amount may be adjusted upward or downward, as is routinely done in such treatment protocols, depending on the results of the initial clinical trials and the needs of a particular patient.
Pharmaceutical compositions according to the invention may be formulated to release the active compound substantially immediately upon administration or at any predetermined time or time period after administration. The latter types of compositions are generally known as controlled release formulations, which include (i) formulations that create a substantially constant concentration of the drug within the body over an extended period of time; (ii) formulations that after a predetermined lag time create a substantially constant concentration of the drug within the body over an extended period of time; (iii) formulations that sustain action during a predetermined time period by maintaining a relatively, constant, effective level in the body with concomitant minimization of undesirable side effects associated with fluctuations in the plasma level of the active substance (sawtooth kinetic pattern); (iv) formulations that localize action by, e.g., spatial placement of a controlled release composition adjacent to or in contact with the thymus; (v) formulations that allow for convenient dosing, such that doses are administered, for example, once every one or two weeks; and (vi) formulations that target a neoplasia by using carriers or chemical derivatives to deliver the therapeutic agent to a particular cell type (e.g., neoplastic cell). For some applications, controlled release formulations obviate the need for frequent dosing during the day to sustain the plasma level at a therapeutic level.
Any of a number of strategies can be pursued in order to obtain controlled release in which the rate of release outweighs the rate of metabolism of the compound in question. In one example, controlled release is obtained by appropriate selection of various formulation parameters and ingredients, including, e.g., various types of controlled release compositions and coatings. Thus, the therapeutic is formulated with appropriate excipients into a pharmaceutical composition that, upon administration, releases the therapeutic in a controlled manner. Examples include single or multiple unit tablet or capsule compositions, oil solutions, suspensions, emulsions, microcapsules, microspheres, molecular complexes, nanoparticles, patches, and liposomes.
Parenteral Compositions
The pharmaceutical composition may be administered parenterally by injection, infusion or implantation (subcutaneous, intravenous, intramuscular, intraperitoneal, or the like) in dosage forms, formulations, or via suitable delivery devices or implants containing conventional, non-toxic pharmaceutically acceptable carriers and adjuvants. The formulation and preparation of such compositions are well known to those skilled in the art of pharmaceutical formulation. Formulations can be found in Remington: The Science and Practice of Pharmacy, supra.
Compositions for parenteral use may be provided in unit dosage forms (e.g., in single-dose ampoules), or in vials containing several doses and in which a suitable preservative may be added (see below). The composition may be in the form of a solution, a suspension, an emulsion, an infusion device, or a delivery device for implantation, or it may be presented as a dry powder to be reconstituted with water or another suitable vehicle before use. Apart from the active agent that reduces or ameliorates a neoplasia, the composition may include suitable parenterally acceptable carriers and/or excipients. The active therapeutic agent(s) may be incorporated into microspheres, microcapsules, nanoparticles, liposomes, or the like for controlled release. Furthermore, the composition may include suspending, solubilizing, stabilizing, pH-adjusting agents, tonicity adjusting agents, and/or dispersing, agents.
As indicated above, the pharmaceutical compositions according to the invention may be in the form suitable for sterile injection. To prepare such a composition, the suitable active antineoplastic therapeutic(s) are dissolved or suspended in a parenterally acceptable liquid vehicle. Among acceptable vehicles and solvents that may be employed are water, water adjusted to a suitable pH by addition of an appropriate amount of hydrochloric acid, sodium hydroxide or a suitable buffer, 1,3-butanediol, Ringer's solution, and isotonic sodium chloride solution and dextrose solution. The aqueous formulation may also contain one or more preservatives (e.g., methyl, ethyl or n-propyl p-hydroxybenzoate). In cases where one of the compounds is only sparingly or slightly soluble in water, a dissolution enhancing or solubilizing agent can be added, or the solvent may include 10-60% w/w of propylene glycol.
Controlled Release Parenteral Compositions
Controlled release parenteral compositions may be in form of aqueous suspensions, microspheres, microcapsules, magnetic microspheres, oil solutions, oil suspensions, or emulsions. Alternatively, the active drug may be incorporated in biocompatible carriers, liposomes, nanoparticles, implants, or infusion devices.
Materials for use in the preparation of microspheres and/or microcapsules are, e.g., biodegradable/bioerodible polymers such as polygalactin, poly-(isobutyl cyanoacrylate), poly(2-hydroxyethyl-L-glutam-nine) and, poly(lactic acid). Biocompatible carriers that may be used when formulating a controlled release parenteral formulation are carbohydrates (e.g., dextrans), proteins (e.g., albumin), lipoproteins, or antibodies. Materials for use in implants can be non-biodegradable (e.g., polydimethyl siloxane) or biodegradable (e.g., poly(caprolactone), poly(lactic acid), poly(glycolic acid) or poly(ortho esters) or combinations thereof).
Kits or Pharmaceutical Systems
The present compositions may be assembled into kits or pharmaceutical systems for use in ameliorating a neoplasia (e.g., prostate cancer). Kits or pharmaceutical systems according to this aspect of the invention comprise a carrier means, such as a box, carton, tube or the like, having in close confinement therein one or more container means, such as vials, tubes, ampoules, or bottles. The kits or pharmaceutical systems of the invention may also comprise associated instructions for using the agents of the invention.
The practice of the present invention employs, unless otherwise indicated, conventional techniques of molecular biology (including recombinant techniques), microbiology, cell biology, biochemistry and immunology, which are well within the purview of the skilled artisan. Such techniques are explained fully in the literature, such as, “Molecular Cloning: A Laboratory Manual”, second edition (Sambrook, 1989); “Oligonucleotide Synthesis” (Gait, 1984); “Animal Cell Culture” (Freshney, 1987); “Methods in Enzymology” “Handbook of Experimental Immunology” (Weir, 1996); “Gene Transfer Vectors for Mammalian Cells” (Miller and Calos, 1987); “Current Protocols in Molecular Biology” (Ausubel, 1987); “PCR: The Polymerase Chain Reaction”, (Mullis, 1994); “Current Protocols in Immunology” (Coligan, 1991). These techniques are applicable to the production of the polynucleotides and polypeptides of the invention, and, as such, may be considered in making and practicing the invention. Particularly useful techniques for particular embodiments will be discussed in the sections that follow.
The following examples are put forth so as to provide those of ordinary skill in the art with a complete disclosure and description of how to make and use the assay, screening, and therapeutic methods of the invention, and are not intended to limit the scope of what the inventors regard as their invention.
Clinical Specimens
61 of the 135 enrolled patients fulfilled 3 primary selection criteria. Prostate cancer, PIN and normal or hyperplastic prostate tissue, all surrounded by significant intervening stroma were required to be present in the same histological block. Pure low grade (Gleason 6) or high grade (Gleason ≥8) prostate cancer in the whole prostate was pathologically defined. Cases with comprehensive Gleason 7 were excluded by definition. Enough material for micro-dissection and nucleic acid extraction in the epithelial and stromal compartments of at least one block was required.
135 prostate cancer patients who underwent radical prostatectomy were recruited from the various medical institutions. 5 prostates from cysto-prostatectomy cases, included in the PROPP-Study, were collected from patients with bladder cancer were also included in the study as normal controls. All cases with incidental prostate cancer or excessive inflammation in the stromal counterpart or atrophy in the epithelial counterpart were excluded.
Digi-Pathology
A pathology review of all the histological slides was centralized in Italy. The slides selected according to the stated criteria were scanned with an Aperio instrument in Bologna and put on a dedicated proprietary website protected by regulated access. Circling of the epithelial and stromal counterparts in cancer, PIN and normal tissue areas was performed on digitized H&Es (
Laser Capture Microdissection (LCM) and Formalin-Fixed, Paraffin-Embedded (FFPE) RNA Extraction
The LCM workflow comprised preliminary ROI review by digital annotation, tissue block sectioning and staining, 2 hr of microdissection on the Arcturus platform (Life Technologies), overnight incubation in lysis buffer/Proteinase K and subsequent RNA extraction by AllPrep (Qiagen) and quantification by RiboGreen assay (Life Technology), a sample tracking and digital inventory, comprising over 450 RNA extracts and >1500 corresponding images (pre-, post- and cap). See, Yuan, et al., Nature Protocols, v. 7, no. 5, 2012; and Kelly et al., PLoS One, 6, 10, e25357, each of which is incorporated herein by reference.
Labeling and Gene Hybridization Array
To accommodate the low RNA concentration and yields associated with microdissected tissues, the SensationPlus FFPE method was adopted as a suitable labeling technique. 20 ng total RNA at a concentration of 2.5 ng/ul, reliably and reproducibly measured RNA expression across the whole transcriptome on the Affymetrix Gene Array STA 1.0.
Normalization and Differential Gene Expression Analysis
Normalization and rigorous quality control of the gene expression data was performed. A normalization method was developed that adjusted raw data at the probe level for technical variables, such as batches, overall median of the fluorescence intensities in each array prior to normalization using the RMA (robust multichip average) method. The QC did not identify any failing samples, and there were no extreme outliers. Thus, all assayed samples were retained and ROIs for further analysis. Because of a relatively large sample size, profiling was performed in two batches, a correction to minimize false positive findings due to potential batch effects and to increase the power of discovering true differential expression was implemented by adjusting the raw data as described above.
The random effects linear models approach was implemented to account for correlations between compartments within cases. Differentially expressed genes within the epithelial, within the stromal, and between the epithelial and stromal morphological regions of interest were expressed as log fold-changes. P-values for the tests were adjusted using the Benjamin-Hochberg method, thus controlling False Discovery Rate (FUR) in multiple comparisons. A FDR≤0.05 was considered significant. The data sets were filtered to exclude genes where the fold-changes did not exceed 1.5.
GEO Datasets
Publicly available data was downloaded as preprocessed from the original publications from GEO. Using microarray annotations as supplied in the GSE datasets available probesets were extracted that corresponded to the genes in the signature. These data were used to perform hierarchical clustering, principal component analysis, and to compute single sample gene set enrichment scores (ssGSEA).
Using single sample Gene Sets Enrichment Analysis (Barbie D A, et al. Nature. 2009; 462:108-112) algorithm, epithelial, stromal and combined scores were computed for the gene expression data from the Physicians' Health Study (PHS) (120 indolent, 30 lethal cases), and Health Professionals Follow-Up Study (HPFS) (171 indolent, 83 lethal cases) (i.e. cohorts where outcomes were known). An epithelial score was computed by applying ssGSEA to epithelial genes from the signature with epithelialy expressed genes as a reference. The stromal score was computed by applying ssGSEA to stromal genes from the signature with stromally expressed genes as a reference. The combined score was defined as the maximum between standardized epithelial and standardized stromal scores. The scores were studied for both a complete 29 gene signature and for a manually reduced set of only bone-related genes. As described above, an exemplary bone-related subset of genes includes PRELP, LTBP2, FBLN5, ITGA11, COL1A1, ALCAM, SFRP2, TNS3, SULF1, BGN, and/or THBS2. These scores predicted the outcomes (i.e. lethal or indolent disease). The areas under the ROC curves for these predictions are shown in Table 22.
Enrichment and Pathway Assessment
Differentially expressed genes from the epithelial-stromal data sets of interest were mapped onto gene ID's of functional ontologies represented by pathway maps and networks derived from the MetaCore portal (portal.genego.com) and the public ontology, Gene Ontology (GO; geneontology.org). In MetaCore™, the enrichment analysis workflow tool was utilized to conduct the Ontology Enrichment (EO), by mapping gene IDs of the dataset of interest onto gene IDs in entities of built-in functional ontologies such as pathway maps, networks, diseases, etc. The terms in a given ontology were ranked based on “relevance” in the dataset. The statistical relevance procedure, a p-value of hypergeometric distribution, was calculated as the probability of a match to occur by chance, given the size of the ontology, the dataset and the particular entity. The lower the p-value, the higher is the “non-randomness” of finding the intersection between the dataset and the particular ontology term. That, in turn, translated into a higher ranking for the entity matched. The more genes/proteins belong to a process/pathway, the lower the p-value. In EA proprietary ontologies (canonical pathway maps, cellular processes, toxicities, disease biomarkers etc.) were used and public ontologies such as Gene Ontology (cellular processes, protein functions, localizations).
Molecular Signatures Database v5.0
The Molecular Signatures Database (MSigDB) is a collection of annotated gene sets for use with GSEA software, comprised of 8 major gene collections.
The Molecular Signatures Database (MSigDB) is a collection of annotated gene sets for use with GSEA software. MSigDB assists with investigating gene sets and computing overlaps.
When gene sets share genes, examination of how they overlap may highlight common processes, pathways, and underlying biological themes. This tool evaluates the overlap of a user provided gene set, and provides an estimate of the statistical significance, with as many MSigDB collections as chosen.
Due to the characteristics of the hypergeometric distribution there are limits to the size the user provided gene set may be to still produce meaningful significance estimates. At most 2940 genes will be allowed, anything larger will be rejected.
A list of gene identifiers is entered in the box provided, and a pull down menu below the box allows input of how the identifying genes are specified. Overlaps are computed using HUGO gene symbols and any required conversion is done automatically by the tool. The “compute overlaps” button displays the results, including:
Statistics:
The number of overlaps shown lists the number of overlapping gene sets displayed in the report.
By default, the report displays the 10 gene sets in the collection that best overlap with the gene set of interest. To compute overlaps from the Investigate Gene Sets page, the number of overlapping gene sets to display in the report is chosen. The number of gene sets in the collection lists the total number of gene sets being analyzed, the number of genes in comparison lists the number of genes in the gene set of interest, and the number of genes in the collection lists the number of unique genes in the gene sets being analyzed.
Descriptions of the overlapping gene sets, including: link to the gene set page, number of genes in the gene set, description of the gene set, number of genes in the overlap between this gene set and the gene set, P value from the hypergeometric distribution for (k−1, K, N−K, n) where k is the number of genes in the intersection of the query set with a set from MSigDB, K is the number of genes in the set from MSigDB, N is the total number of gene universe (all known human gene symbols), and n is the number of genes in the query set, FDR q-value. This is the false discovery rate analog of hypergeometric p-value after correction for multiple hypothesis testing according to Benjamini and Hochberg. Color bar shading from light green to black, where lighter colors indicate more significant q-values (<0.05) and black indicates less significant q-values (≥0.05). Overlap matrix showing the genes in the overlapping gene sets, rows list the genes in the gene set, with gene descriptions and links to gene annotations, and columns list the overlapping gene sets, with links to the gene set pages
A 25 case cohort was selected, comprising 12 pure 3+3 low grade and 13≥4+4 high grade radical prostatectomy (RP) specimens. In addition, 5 cystoprostatectomy (CP) specimens with no prostate cancer were used. Common clinical characteristics available from all sites were collected to include pre-operative PSA levels, age at diagnosis pathological disease stage, nodal status and patient follow-up. The mean age of patients in the study cohort was 63.7±1. The pre-operative PSA levels were significantly higher in the Gleason 4 case group, where p value <0.035 (Median PSA 10.2±1.9). Clinical characteristics are shown in Table 2. Laser capture microdissection of 165 regions of interest from normal prostate tissue, prostatic intraepithelial neoplasia and invasive tumor, each with its immediately surrounding stroma, were used for gene expression profiling (GEP). Regions of interest in each case comprised tumor (T), high-grade PIN (P) and benign (B) glands and adjacent (sT, sP, sB) stroma. Normal benign tissue and adjacent stroma samples from cystoprostatectomy cases were denoted as HB and HsB, respectively, where H stands for healthy. The differences between glands and stroma within and between the two cellular compartments were studied. Using these comparisons, the role of epithelial and stromal-expressing genes in prostate cancer initiation, progression and advanced disease and the complex interactions that arise at the epithelium-stroma interface were investigated.
Direct comparison of benign epithelia from the Cystoprostatectomy (CP) and radical prostatectomy (RP) tissues (B-HB) HB found 6 differentially expressed genes (
Initial attention was paid to the global expression profiling trends to explore differences between the epithelial and stromal compartments (
ERG is a prominent over-expressed prostate tumor gene that is frequently fused with the promoter region of the TMPRSS2 gene. A series of ERG regulated genes such as CACNA1D, PLA1A, TDRD1 and HLA-DMB follow the same trend (
From the annotated, web accessible H&E's (
Differentially expressed genes within the epithelial and stromal compartments comparing T-P, T-B and P-B and then sT-sP, sT-sB and sP-sB were evaluated (
Prior to investigating differentially expressed genes in the T-B comparison in the microdissected tissues, known epithelial tumor and benign associated prostate cancer genes were evaluated utilizing an enriched Oncomine signature comprised of gene expression data from 6 prostate cancer studies (Singh D, et al., Cancer Cell. 1, 203-9 (2002), Lapointe J, et al., Proc Natl Acad Sci. 101, 811-16 (2004), Yu Y P, et al., J Clin Oncol. 22, 2790-9 (220040), Tomlins S A, Nat Genet. 39, 41-51 (2007), Wallace T A, et al., Cancer Res. 68, 927-36 (2008), and Penney K L, et al., J Clin Oncol. 29, 2391-6 (2011)) in the data. The results of which are shown in
Within the epithelial compartment (Table 6), 176/234 genes were differentially expressed in the T-B comparison only, of which 79 were upregulated and 97 downregulated. 5/24 genes were differentially expressed in the T-P comparison only, of which all 5 were downregulated. 13/52 genes were differentially expressed in the P-B comparison only, of which 8 were upregulated and 5 downregulated. 22 genes were upregulated (all small nucleolar RNA's with the exception of HPN and TRIB1) and 14 genes downregulated in both the P-B and T-B comparisons. Prostate tumor-expressing genes, ERG, AMACR and OR51E1 were upregulated and 15 genes (mostly methallothioneins and keratins) downregulated in both the T-P and T-B comparisons. PTCH2, the tumor suppressor gene, was upregulated in the P-B, T-P and T-B comparisons and when plotted resulted in a decreasing expression associated with progression from B to P to T.
Within the stromal compartment (Table 7), 49 genes were differentially expressed in the sT-sB comparison of which 36 were upregulated and 13 downregulated. A number of prostate cancer associated genes were up-regulated, including NKX3-1, KLK2, KLK3, ERG, FOXA1 and EPCAM. For each of these genes, it was confirmed that the stroma mRNA expression level was lower than that of the tumor epithelium. IGF1 and IGF2 were 2/13 genes downregulated in the sT-sB comparison, where loss of imprinting (LOI) has long been associated with tumorigenesis. NELL2, a glycoprotein containing EGF-like domains with similarities to thrombospondin was found to be downregulated in both the sP-sB and sT-sB comparisons. BMP5, a member of the TGFβ superfamily, was upregulated in the sP-sB comparison only. The mean expression of hgPIN (high-grade PIN) tissues had a large variance, which made tracking prostate cancer progression trends somewhat challenging. It did open up the concept that hgPIN has benign and tumor characteristics, and perhaps even a subset of unique transcriptional programs that were not well defined prior to the invention described herein.
Comparisons across the epithelial and the stromal compartments (
Table 8. Across compartment differentialy expressed genes of statistical significance for the B-sB, P-sP and T-sT epithelial-stromal comparisons.
This was expanded across compartment analysis to include the cystoprostatectomy H-HsB comparison, the results of which are represented by Venn diagram in
Table 9. Enrichment analysis uusing the GeneGo database, to determine pathways, networks and cellular processes, for the genes found to be differentially expressed in the B-sB, P-sP, T-sB and HB-HsB epithelial-stromal comparisons, where H indicates healthy.
By filtering out the cystoprostatectomy associated differentially expressed genes between the healthy benign and its adjacent stroma (represented as the shaded HB-HsB area on the Venn diagram), genes that were exclusively associated with prostate malignancy were evaluated. 46 genes were identified as differentially expressed in the B-sB, P-sP and T-sT comparisons, exclusive of HB-HsB. Only 4 genes, FOHL1 (PSMA), FBXO25, CLDN7 and AGR2, were upregulated, indicating that stromal associated expression is prevalent and influential on prostate carcinogenesis. These stromal expressing genes, such as IL-2RB, CCL2 and CXCR4, LIF, HLA-DPA1 were predominantly associated with inflammation and the immune response (Table 10). 62 genes were exclusively differentially expressed in the T-sT comparison (blue box in Venn diagram,
An enrichment analysis was conducted of the DE genes that were found in a single comparison, namely, P-sP only (68 genes). The GO cellular processes for all three comparisons are shown in
Table 10. 46 genes differentially expressed in malignant tissue comparisons, B-sB, P-sP and T-sT, exclusive of healthy, HB-HsB comparison
Table 11. Enrichment analysis using the GeneGo database, to determine pathways, networks and cellular processes, for the genes found to be upregulated in the stroma, found exclusively in the T-sT comparison in malignant tissue
Gleason grade is one of the strongest clinical predictors of prostate cancer progression and outcomes (Penney K L, et al., J Clin Oncol. 29, 2391-6 (2011)). Men with low-grade Gleason ≤6 tumors, have a low metastatic potential, even in the absence of therapy; in contrast, men with high-grade Gleason 8 to 10 tumors have a high likelihood of progression, even with curative therapies. Genes were identified that were associated with low and high Gleason scores in the different compartments. Three comparisons were performed to identify differentially expressed genes that were associated with a Gleason score. The first compared the Gleason 6 and Gleason 8 tumors within the epithelium, T8-T6. The second compared the Gleason 6 and Gleason 8 within the stroma, sT8-sT6. Third, the magnitude of the differential expression between the compartments, (sT8-T8)-(sT6-T6) associated with Gleason score were assessed. A TGF-β-responsive marker and functional regulator of prostate cancer metastasis to bone, ALCAM (Hansen A G, et al., Cancer Res. 74, 1404-15 (2014)) was identified as the only significantly differentially expressed gene in the epithelium comparison. 16 differentially expressed genes were associated with Gleason within the stromal compartment, (sT8-sT6). 22 genes (including 9 of the 16 above) were significant in the (sT8-T8)-(sT6-T6) comparison. The interaction gene set also contained ALCAM and an additional 6 epithelial genes that further augment the ability to elucidate the influence and processes associated with the epithelium and stroma independently and in conjunction with each other. A total of 29 genes were inspected graphically and assigned to the epithelial or stromal compartment based on which compartment contributed more to the observed difference between the low and high grade.
Next, the compartment of origin of the discriminating genes was assessed by classifying them as stromal or epithelial based on the direction of their fold-changes in the global comparisons of epithelium versus stroma. Overall a 29-gene signature was defined (7 epithelial and 22 stromal genes), which distinguishes Gleason 6 from Gleason 8 (Table 1), which comprise a “bone homing signature”.
In
A stromal microenvironment surrounding Gleason 8 tumors that is altered is described. This altered state is bone-like, featuring wound healing and metastasis markers (ALCAM, SFRP2, SFRP4, THBS2), stem cell and hematopoietic bone marrow markers (ITGA11, LTBP2, SULF1, FBLN5, COL1A1) and immune cell markers (C1S, C1Q, Serping1, HLA-DRB3, FCGR2C, HSPA9). A full description of the 29-gene signature is provided in Table 12, where genes are categorized into 1 or more of bone, metastasis, immune, stemness and metabolism with supporting literature citations. Immune response dominates the top 10 enriched pathways, network and processes shown to be statistically significant. The next most prevalent characteristics determined from the enrichment analysis is association to bone-related pathways (Hedgehog associated bone development and osteoporosis) and inflammation, cartilage development and bone remodeling networks. These in conjunction with the wealth of literature support for each gene or subset of genes within the 29-gene Gleason signature describe a stromal microenvironment surrounding Gleason 8 tumors that is altered and this alteration looks remarkably bone-like harboring bone-specific markers, stem cell and hematopoetic associated bone marrow associated markers and immune cell markers. Plots showing trends across benign to PIN to tumor samples for each gene within the 29-gene signature are shown in
The 29-gene signature is heavily comprised of stromal expressing genes, where increasing expression from healthy to benign to PIN to tumor was observed in Gleason 8 samples, for a subset of 13 genes, including C1QA, C1QB, C1QC, CD52, FCGR2C, LTBP2, ITGA11, MAXD1, THBS2, SFRP4, TNS3, BGN and HLA-DRB3. In Gleason 6 samples, expression levels in stroma were predominantly unchanged, with the exception being a subset of 4 genes with a decreasing trend from healthy to benign to PIN to tumor, PRELP, SerpinG1, FBLN5 and SULF1. Of the 7 epithelial expression genes, ALCAM, MAL2, CLDN8 and C12orf51 have increasing expression from healthy to benign to PIN to tumor in Gleason 8 samples. HSPA9 and PTPLAD1 were only increased in the Gleason 8 tumor epithelial samples. No trends were observed in Gleason 8 samples (
Genes were identified for which expression levels within the different compartments (T8 vsT6 and sT8 vs sT6) or the magnitude of the differential expression between the compartments (sT8-T8) vs (sT6-T6) (an interaction term in the linear model) were associated with low and high Gleason scores. The stromal or epithelial compartment of origin of these 22 genes was assigned based on the direction of their fold-changes in the comparisons of all epithelial versus all stromal ROIs. The assigned compartment contributed more to the observed difference between the low and high grade by visually inspecting interaction plots.
The compartment of origin of the discriminating genes was confirmed by classifying them as contingently stromal or epithelial based on the direction of their fold-changes in the global comparisons of epithelium vs stroma (T+B+S)/3−(sT+sB+sP)/3, and in comparisons within benign and malignant tissue (B-sB and T-sT respectively) (Table 20). Genes that were significant with fold-changes of 1.5 and above were classified as ‘strongly’ epithelial or stromal, genes with fold-changes below 1.5 were called ‘weakly’ epithelial or stromal, and genes that were not statistically significant in these comparisons were classified as ‘unclear’. The Protein Atlas database was used as a benchmark for compartmental expression by standard chromogenic IHC in prostate tumor tissue cores (Uhlen M, et al. Tissue-based map of the human proteome, Science, 2015, 347, 6220. DOI: 10.1126/science.1260419). The cancer tissue atlas contains a multitude of human cancer specimens representing the 20 most common forms of cancer, including breast-, colon-, prostate-, lung-, urothelial-, skin-, endometrial- and cervical cancer. Altogether, 216 different cancer samples are used to generate protein expression profiles for all proteins using immunohistochemistry. The data is presented as pathology-based annotation of protein expression levels in tumor cells, along with the images underlying the annotation. This enables the identification of a potential protein signature for each given type of cancer. This provides a starting point for further analyses of cancer type-specific proteins. Because the cancer atlas contains a large number of cancer samples the protein profiles provide a starting point for further analysis and identification of new potential cancer biomarkers.
The GAB-SUB crosstalk model facilitated the discovery of tumor-stroma gene associations that separate Gleason 8 from Gleason 6 cases that were not found by standard comparative analysis of differentially expressed genes. 22% of the crosstalk interactions represented the top 10 stroma-expressed genes, whereas 55% of all crosstalk interactions were associated with the top 10 tumor-expressing genes. The most prominent stroma-expressed gene was NPNT, found in 13 crosstalk interactions. The most prominent tumor-expressed gene was ST6GAL1, found in 61 crosstalk interactions as shown in
Table 13. Top 10 “tumor-expressing” and “stroma-expressing” genes in the cross-correlation GAPSUB model
Table 14. 29-gene signature representation in the cross-correlation GAPSUB model
Table 15. Enrichment analysis using the GeneGo database, to determine pathways, networks and cellular processes, for the genes found to be differentially expressed in 29-gene signature in the cross-correlation GAP-SUB model
Table 16. Utilization of the MSigDB Hallmark gene sets to compute overlaps in the 29-gene signature in the cross-correlation GAP-SUB model
To establish whether the 29-gene signature could be associated with metastasis to the bone, two clinical studies were assessed that looked at the transcriptional landscape of breast and prostate bone metastatic tissues and/or biopsies, respectively. The first study (GEO Data Set: GSE 14776) was described by Clemons et al. in Clin Exp Metastasis in 2014 (Cawthorn T R, Clin Exp Metastasis. 26, 935-40 (2009)). Bone metastatic and disseminated tumor cells from breast cancer patient biopsies were obtained and gene expression profiles were compared. In
The 29-gene signature has also been recapitulated in osteosarcoma gene expression studies, as shown in
The Human Protein Atlas (HPA) program is a scientific research program to explore the whole human proteome using an antibody-based approach. The project has a gene-centric approach with the effort to map and characterize a representative protein for each protein-coding human gene (approximately 20,000 genes). Antibodies, both in-house produced and external (commercial and from collaborators), are validated in the HPA workflow and used for protein characterization.
Representative normal included by way of reference point. Only high grade tumor cases were used for staining assessment. In the Protein Atlas analysis of the 29-gene signature, ALCAM (
While progression from normal prostatic epithelium to invasive cancer is driven by molecular alterations, tumor cells and cells in the cancer microenvironment are co-dependent and co-evolve. As described herein, gene expression profiling of laser capture microdissected normal non-neoplastic prostate (cystoprostatectomies) epithelial tissue was performed and compared to non-transformed and neoplastic low and high grade prostate epithelial tissue from radical prostatectomies, each with its immediately surrounding stroma. Whereas benign epithelium in prostates with and without tumor were similar in gene expression space, stroma away from tumor was significantly different from that in prostates without cancer. A stromal gene signature reflecting bone remodeling and immune-related pathways was upregulated in high compared to low Gleason score cases. In validation data, the signature discriminated cases that developed metastasis from those that did not. These data suggest that the microenvironment may influence prostate cancer initiation, maintenance, and metastatic progression.
The prostate consists of the glandular epithelium and supporting stroma. This connective stroma is comprised of fibroblasts, myofibroblasts, smooth muscle cells, vascular endothelial cells, nerve cells, and inflammatory cells. While prostate cancer arises from the epithelial component of the gland, the surrounding stroma is increasingly recognized as an important contributor in the process of carcinogenesis and a driver of cancer progression (Bhowmick, N. A., et al. Science 303, 848-851 (2004); Olumi, A. F., et al. Cancer research 59, 5002-5011 (1999)). Experimental models demonstrate that altered stromal cells can induce tumor formation in non-cancerous prostate epithelial cells and in cell lines derived from prostate cancer (Olumi, A. F., et al. Cancer research 59, 5002-5011 (1999)). Benign prostate epithelial cells proliferate more and ultimately undergo transformation when combined with prostate cancer-derived fibroblasts (Olumi, A. F., et al. Cancer research 59, 5002-5011 (1999); Hayward, S. W., et al. Cancer Res 61, 8135-8142 (2001)). It is also clear that the stroma can morphologically and functionally change in the presence of cancer and other insults. Compared to normal stroma, there is a switching of the cellular phenotype, remodeling of the extracellular matrix (Morrison, C., Thornhill, J. & Gaffney, E. Urol Res 28, 304-307 (2000)), increases in expression of growth factors and proteases (Giri, D., Ropiquet, F. & Ittmann, M. Clin Cancer Res 5, 1063-1071 (1999)) increased angiogenesis (Rowley, D. R. Cancer Metastasis Rev 17, 411-419 (1998)), and change in inflammatory cells (Shimura, S., et al. Cancer Res 60, 5857-5861 (2000)). The bidirectional signaling between epithelial cells and stromal constituents during normal prostate homeostasis is disrupted early in tumorigenesis (Barron, D. A. & Rowley, D. R. Endocr Relat Cancer 19, R187-204 (2012)). The consequences are diverse and range from deposition of extracellular matrix, to recruitment of inflammatory cells, production of miRNA, promotion of tissue regeneration and angiogenesis, ultimately resulting in stimulation of growth and survival of tumor cells (Hanahan D, W. R. Cell, 646-674 (2011); Josson et al., Clin Cancer Res (2014)). When the stromal compartment becomes reactive normal fibroblasts are replaced by cancer-associated fibroblasts (CAFs). The increase of CAFs, which begins around in situ lesions, evolves during prostate tumorigenesis and is inversely proportional to tumor differentiation (Tuxhorn, et al., J Urol 166, 2472-2483 (2001)).
Signaling factors from the microenvironment influence epithelial cells to acquire properties such as increased motility, proliferation or migratory and invasive behavior. To this end, TGFbeta and Wnt signaling pathways have been shown to play important regulatory roles in stromal-epithelial interactions in both prostate development and tumorigenesis (Barron, D. A. & Rowley, D. R. The reactive stroma microenvironment and prostate cancer progression. Endocr Relat Cancer 19, R187-204 (2012); Carstens J L, S. P., Van Tsang S, Smith B, Creighton C J, Zhang Y, Seamans A, Seethammagari M, Vedula I, Levitt J M, Ittmann M M, Rowley D R, Spencer D M. FGFR1-WNT-TGF-β signaling in prostate cancer mouse models recapitulates human reactive stroma. Cancer Res (2014); Smith B N, B. N. Role of EMT in Metastasis and Therapy Resistance. J Clin Med (2016). A variety of additional growth factors produced by stromal cells have been shown to affect tumor cell survival (Shiao S L, C. G., Chung L W. Regulation of prostate cancer progression by the tumor microenvironment. Cancer Lett (2016)). In addition, soluble cytokine and chemokines influence the interaction between the epithelial and stromal compartment during prostate cancer progression. For example, peri-prostatic adipose tissue can affect migration of prostate cancer cells via secretion of CCL7 by adipocytes (Laurent V, G. A., Mazerolles C, Le Gonidec S, Toulet A, Nieto L, Zaidi F, Majed B, Garandeau D, Socrier Y, Golzio M, Cadoudal T, Chaoui K, Dray C, Monsarrat B, Schiltz O, Wang Y Y, Couderc B, Valet P, Malavaud B, Muller C. Periprostatic adipocytes act as a driving force for prostate cancer progression in obesity. Nat Commun (2016). Finally, androgen receptor, expressed by a subset of myofibroblasts in the prostate stroma, may regulate the expression of growth factors secreted by these cells. Thus, tumor growth and biologic behavior is strongly regulated by the extracellular milieu.
Mutational landscapes have been measured in an attempt to predict biologic behavior of human prostate tumors (Network, C.G.A.R. Cell (2015); Robinson et al., Cell (2015)). In addition, epigenetic and transcriptional signatures are associated with the degree of differentiation and are an important adjunct in predicting aggressive and indolent behavior (Penney, K. L., et al. J Clin Oncol 29, 2391-2396 (2011); Sinnott, J. A., et al. Clin Cancer Res (2016); Zhao et al., Clin Cancer Res (2016)). These are turning out to be invaluable tools to guide therapeutic options in prostate cancer patients but could be further improved by knowledge of the contribution of stromal elements. While it has been recently shown that stroma adjacent to prostate cancer epithelium does not harbor clonal DNA alterations and appears to be genetically stable (Bianchi-Frias, D., et al. Mol Cancer Res 14, 374-384 (2016)), biological behavior of the epithelial component of the tumor, may be affected by variability of gene expression in the stroma. In turn, epithelial alterations may condition stromal behavior. For instance, hyperactivated focal adhesion kinase (FAK) activity has been shown to be an important regulator of the fibrotic and immunosuppressive stromal microenvironment in pancreatic cancer (Jiang et al., Nat Med (2016)). Additionally, it has previously been shown that stromal gene expression signatures predict outcome in breast (Finak, G., et al. Nat Med 14, 518-527 (2008); Roman-Perez, E., et al. Breast Cancer Res 14, R51 (2012); Winslow, S. Breast Cancer Res 17, 23 (2015) and colorectal (Calon, A., et al. Nat Genet 47, 320-329 (2015)) cancer patients.
Laser-capture microdissection (LCM) has facilitated the isolation and study of specific cellular populations within the prostate tumor microenvironment. This labor-intensive technology, however, limits large-scale efforts. Prior to the invention described herein, differences between the tumor and its adjacent stroma in prostate cancer (Gregg et al., BMC Cancer. (2010)) between normal and reactive stroma (Dakhova, O., et al. Clin Cancer Res 15, 3979-3989 (2009)), and differences between benign and tumor epithelium (Dakhova, O., et al. Clin Cancer Res 15, 3979-3989 (2009); Furusato et al., Prostate Cancer Prostatic Dis (2008); Tomlins, S. A., et al. Nat Genet 39, 41-51 (2007)) have been addressed utilizing LCM, albeit on a small scale. Analyses were centered predominantly on the epithelial compartment. Limited studies of stromal gene expression using high-throughput assays exist for prostate cancer aggressiveness. One such study showed alterations in neurogenesis, axonogenesis, and DNA damage/repair pathway to be associated with grade 3 reactive stroma (Dakhova, O., et al. Clin Cancer Res 15, 3979-3989 (2009)).
Here, it was hypothesized that progression of normal prostate to PIN to invasive cancer is driven by molecular alterations in both epithelium and stroma, and that changes in the microenvironment can potentially contribute to tumor initiation, maintenance and progression. Thus, it was asked whether gene expression of non-transformed epithelial and stromal tissues differ in prostates with and without tumor, and how the stromal genes are associated with prostate cancer progression and aggressiveness (Gleason score).
The results from this example are described in detail below.
Gene expression profiling was performed on laser capture microdissected tissue specimens from 25 radical prostatecomy (RP) and 5 ‘healthy’ cystoprostatectomy cases. For each RP case, 6 regions of interest were examined: tumor (T), PIN (P) and benign (B) epithelium each with the adjacent stroma (sT, sP, sB). For cystoprostatectomy, benign epithelium and adjacent stroma (H.B and H.sB) was examined. Cystoprostatectomies were confirmed not to harbor prostate cancer foci through review of the entire submitted specimen. Clinicopathological features of the cohort are described in Table 23.
Gene Expression Differences Between Compartments Across Progression
As expected from the experimental design, the major share of variability in gene expression was explained by differences between epithelial and stromal tissue compartments (
Gene Expression Differences within Compartments Across Progression
As proof of principle examples, P63, a marker of normal basal cells of the prostate gland was upregulated in benign microdissected epithelial samples compared to invasive cancer, while AMACR and ERG were all upregulated in the tumor microdissected epithelial samples compared to benign epithelium and, to a lesser extent, PIN.
Gene set analysis in tumor epithelium showed pathways associated with nucleotide metabolism, translation, and RNA processing (
Gene Expression Differences Between RP and Cystoprostatectomy Cases
The benign epithelial glands from the cystoprostatectomy and RP (B-H.B) were compared and 15 differentially-expressed probesets (FDR<0.05, FC>=1.5;
Interestingly, the hierarchical clustering revealed greater similarity in the expression of stromal genes between stroma adjacent to benign epithelium in the prostates with no tumor (cystoprostatectomies) and the benign stroma from prostates with high grade tumors, even though the physical distance between sB regions selected for analysis and the closest tumor focus, on average was smaller for high grade cases (t-test; p=0.04). This might suggest, that stroma surrounding Gleason 3+3 cases is inherently different. In the direct comparisons of the sB from high and low grade cases no genes reached statistical significance.
Gene Expression Differences Between High and Low Grade Tumors.
Gleason grade is one of the strongest clinical predictors of prostate cancer progression and outcomes. As described herein, genes differentially expressed between high and low grade epithelium (T.high−T.low) and in adjacent stroma (sT.high−sT.low) were identified. A TGF-β-responsive marker and functional regulator of prostate cancer metastasis to bone, ALCAM (FDR=0.005) (Hansen A G, A. S., Jiang M, Palmer T D, Ketova T, Merkel A, Pickup M, Samaras S, Shyr Y, Moses H L, Hayward S W, Sterling J A, Zijlstra A. ALCAM/CD166 Is a TGF-β Responsive Marker and Functional Regulator of Prostate Cancer Metastasis to Bone. Cancer Res (2014)) was identified as the only significantly differentially expressed gene in the epithelium comparison. Differences between gene expression in the sT.high−sT.low comparison, however, were more striking. 27 transcript clusters corresponding to 24 unique gene symbols were differentially expressed in stroma (Table 24). All genes were upregulated in high Gleason grade cases. The genes comprising this stromal signature include a group of genes overexpressed in osteoblasts and osteoblast-like cells, as well as some gene overexpressed in macrophages, T and B cells. Immune response as well as complement activation GO biological processes were significantly enriched in the signature (all corresponding FDR values <10−5). This signature features wound healing and metastasis markers (SFRP2, SFRP4, THBS2), hematopoietic bone marrow markers (SULF1, COL1A1), immune cell markers (C1S, HLA-DRB1, FCGR2C), and complement cascade genes (C1QA, C1QB, C1QC).
The single sample gene set enrichment (ssGSEA) score was calculated for the genes in the tumor-associated stroma, comparing the high and low Gleason score cases, and the difference in the score was highly statistically significant (
Signature Validation in External Data.
Next the stromal signature (Table 24) was applied to the prostate data from The Cancer Genome Atlas (Network, C.G.A.R. The Molecular Taxonomy of Primary Prostate Cancer. Cell (2015)). TCGA prostate samples were comprehensively re-reviewed by a group of GU pathologists. A large variation in tumor purity was reported for 333 TCGA samples. Specimens with low purity contain a lot of stroma, which made them good candidates for preliminary validation of this stromal signature associated with Gleason grade. Cases were grouped into those with relatively high stromal content (tumor cellularity ≤40%) and cases enriched for tumor epithelium (tumor cellularity ≥80%). ssGSEA score of the stromal gene signature was calculated. Interestingly, a significant difference of the ssGSEA signature score between 3+3 and 8+ Gleason in both low (
Similarly, the signature was applied to stromally enriched samples from the publicly available gene expression data from the Mayo clinic cohort (GSE46691). The signature was significantly different between high and low Gleason grade samples (t-test, p<2*10−10), and between cases that did or did not develop metastasis (
Validation Using Immunohistochemistry
Protein expression of selected genes in the signature was tested by immunohistochemistry (IHC) to verify cell of origin. Only genes with IHC-validated antibodies were tested. As examples, the only significant gene in the epithelial compartment, ALCAM was overexpressed in the epithelial component of Gleason 8 tumors (
The traditional consensus is that tumorigenesis is caused by mutations exclusive to epithelial cells that promote increased growth and invasive capacity, eventually resulting in metastasis. For some time, compelling data primarily derived from pre-clinical models have suggested that the microenvironment within which the cancer cells reside plays a pivotal role in cancer initiation and progression. Further, altered microenvironment may even precede genetic alterations in epithelial cells. The results presented herein show that changes in the microenvironment are important contributors to tumor initiation and may affect progression.
It was observed that stromal, but not the epithelial gene expression, obtained from benign areas (away from invasive tumors) in RP specimen differs significantly from that of prostates without cancer. Pathways such as N-glycosylation and the unfolded protein response (UPR) were upregulated in RP benign stroma compared to cystoprostatectomy specimens. These pathways are important in a variety of biological processes such as nutrient sensing or control of lipogenesis and are commonly altered in cancer. For instance, UPR can be an androgen responsive process in prostate cells and an aberrant UPR can lead to suppression of apoptosis, increased protein expression, and survival of prostate cancer cells. Metabolic challenges such as fluctuations in nutrient availability, hypoxia and increased demand on protein synthesis, can lead to perturbation of endoplasmic reticulum (ER) function, accumulation of misfolded proteins, and ER stress. In an attempt to restore ER homeostasis, the cell mounts a response called the UPR, a set of intracellular signaling pathways that aim to adjust the protein folding capacity of the cell (Storm M, S. X., Arnoldussen Y J, Saatcioglu F. Prostate cancer and the unfolded protein response. Oncotarget (2016)). Translational control of protein synthesis is therefore important for prostate cancer cell proliferation and survival, but the role of stromal cells in this regard is new, perhaps suggesting that a stromal environment exists in some individuals that is permissive for survival and proliferation of transformed epithelial cells.
Gleason grade is one of the strongest clinical predictors of prostate cancer progression and outcomes. An mRNA signature associated with Gleason grade improves risk stratification (Sinnott, J. A., et al. Prognostic Utility of a New mRNA Expression Signature of Gleason Score. Clin Cancer Res (2016)). Only one gene was identified as differentially expressed between high and low grade tumor epithelium, ALCAM, a TGF beta responsive gene, previously shown to be associated with metastasis (Hansen A G, A. S., Jiang M, Palmer T D, Ketova T, Merkel A, Pickup M, Samaras S, Shyr Y, Moses H L, Hayward S W, Sterling J A, Zijlstra A. ALCAM/CD166 Is a TGF-βResponsive Marker and Functional Regulator of Prostate Cancer Metastasis to Bone. Cancer Res (2014)). It is well known that TGF beta signaling has been shown to play important regulatory roles in stromal-epithelial interactions in both prostate development and tumorigenesis. Differences between gene expression in stroma adjacent to high and low grade cancer were much more striking: 25 genes were differentially expressed. All genes comprising this stromal signature of Gleason were more highly expressed in stroma from high Gleason cases than those from low grade. The fact that gene expression from stroma across Gleason grades is more different than epithelial tumor confirms the importance of the microenvironment and suggests that more work to develop drugs that specifically target the stroma is warranted.
Interestingly, among the 25 stromal genes differentially expressed across high and low grade were genes expressed by the immune system including complement, as well as many genes that are expressed in osteoblasts and osteoblast-like cells. The complement cascade is known to be an effector arm of innate immunity, playing a role in clearance of pathogens as well as in tumor immune surveillance. The complement system also plays a role in cartilage and bone development, as well as in regenerative pathways in injured tissue (Rutkowski M J, S. M., Kane A J, Ahn B J, Fang S, Parsa A T. The complement cascade as a mediator of tissue growth and regeneration. Inflamm Res. (2010)). Of note, some complement proteins are distributed throughout immature, developing bone and appear to be important in osteogenesis. Uncontrolled complement activation can also promote inflammation. Consistent with these findings, bone remodeling pathways were upregulated only in stroma adjacent to malignant epithelium, and not in benign or PIN adjacent stroma. The stromal genes lumican (LUM), COL1A1 and BGN, belonging to both the signature reported here and comprising all stromal genes in the commercial OncoDx kit (Klein et al., European urology 66, e117-118 (2014)), are also interesting in terms of the theme of bone remodelling. COL1A1 is an osteoblastic differentiation marker and BGN modulates angiogenesis and bone formation during fracture healing. As prostate cancer most commonly metastasizes to bone, and Gleason 8 tumors are more likely to metastasize than Gleason 6, the finding of the overexpression of bone remodeling pathways in high grade stroma is particularly interesting. The interaction of prostate cancer with the bone microenvironment contributes to self-perpetuating progression of cancer in bone and the osteoclast-targeted agents zoledronic acid and denosumab decrease metastases to bone in metastatic castration-resistant prostate cancer (Gartrell et al., European Urology 68 (2015) 850-858). This prostate stromal environment may prepare cells from high grade tumors to thrive in bone.
Next, the association of this Gleason signature was validated with Gleason score in TCGA data. Not surprisingly, the signature was more strongly associated with Gleason in tumors with lower purity that have a higher percentage of stromal tissue. The signature was also significantly associated with lethal disease in expression data from the Mayo clinic cohort, although its prognostic power is likely to be suboptimal in this patient dataset because the Mayo clinic data was designed to be enriched for epithelium. As the analysis of TCGA data suggests, it was expected that stronger performance of the signature for prostate cancer prognosis would be identified in the stroma enriched specimens.
Interestingly, this Gleason signature was also borderline significantly different in stroma from benign areas of the prostates with high and low grade tumors. Additionally, when examining all gene expression data, it was observed that benign stroma from men with high grade tumors was more similar to cystoprostatectomy stroma than low grade benign stroma, despite the fact that in the samples benign stroma from high grade cases was physically closer to a tumor focus than in low grade cases. This could suggest that there is a “prostate-wide” difference in the stroma of men who develop low grade disease that allows for the development of well differentiated cancer with low malignant potential. Additional larger scale studies with benign stroma from healthy individuals and prostate cancer patients' samples taken repeatedly at different distances from tumor foci would validate these findings. However, this provides convincing evidence that it might be possible to identify a prognostic signature from stroma from biopsies that do not contain malignant epithelial cells. In prostate cancer, negative biopsies are a common occurrence and a significant clinical problem that results from random sampling in a PSA screened population. After a man has had an elevated PSA, but a negative biopsy, the normal stroma could be used to determine if he seems at risk only for low grade disease. This could help determine if and when he should return for a follow-up biopsy. In addition, a stromal signature in biopsies without neoplastic tissue may be of importance in the context of active surveillance.
While the results presented herein focused on comparing patients with Gleason scores 6 and 8+, many men are diagnosed with Gleason score 7 disease. The data from this study do not permit comment on how the stroma behaves in these patients, but from the Mayo cohort data and TCGA data, it appears that the stromal signature in Gleason score 7 tumors falls in between Gleason score 6 and 8, suggesting an intermediate state of Gleason 7 stroma. A further investigation of the stroma in Gleason score 7 cases would confirm the contributions of the low and high grade patterns within Gleason 7.
This study is the first to comprehensively assess gene expression from microdissected prostate tissue specimens, focusing on epithelial and stromal compartments across progression.
The following methods were utilized in this example.
Clinical Specimens
25 patients were selected with either pure low grade (Gleason ≤6) or pure high grade (Gleason ≥8) prostate cancer in the whole prostate who underwent radical prostatectomy from the following Institutions' cohorts: Harvard School of Public Health, Boston, USA; King's College London, UK; Prostate Cancer Research Consortium, Ireland; Orebro University Hospital, Sweden; S.Orsola-Malpighi Hospital Bologna, Italy. Each case had enough material for micro-dissection and nucleic acid extraction in the epithelial and stromal compartments, and areas of prostate cancer, PIN and normal or hyperplastic prostate tissue, all surrounded by significant intervening stroma were present in the same histological block. 5 prostates from cysto-prostatectomy cases, included in the PROPP-Study, collected from patients with bladder cancer were included in the study as normal controls for prostate. Cystoprostatectomy patients were not treated with BCG and none of the cases had incidental prostate cancer or excessive inflammation in the stromal component or atrophy in the epithelial component. All patients were consented and approved by each local IRB and research ethics committees.
A pathology review of all the histological slides was centralized in Italy. The slides selected for microdis section were scanned with an Aperio instrument in Bologna and put on a dedicated proprietary website protected by regulated access. Circling of the epithelial and stromal counterparts in cancer, PIN and normal tissue areas was performed on digitized H&Es by MF. Annotated pathological scans were remotely accessed for the laser capture microdissection.
Laser Capture Microdissection and Gene Expression Profiling
The LCM workflow comprised preliminary ROI review by digital annotation, tissue block sectioning and staining, 2 hr of microdissection on the Arcturus platform (Life Technologies), overnight incubation in lysis buffer/Proteinase K and subsequent RNA extraction by AllPrep (Qiagen) and quantification by RiboGreen assay (Life Technology). To accommodate the low RNA concentration and yields associated with microdissected tissues, the SensationPlus FFPE method was adopted as a suitable labeling technique. 20 ng total RNA at a concentration of 2.5 ng/ul, was used to measure RNA expression across the whole transcriptome on the Affymetrix Gene Array STA 1.0.
Normalization and Differential Gene Expression Analysis
Preprocessing of the microarray data consisted of adjusting raw data at the probe level for technical variables, such as batches, overall median of the fluorescence intensities in each array and fraction of the probes with intensity higher than background levels. Adjusted values were normalized using RMA (robust multichip average) method 40. There were no extreme outliers or failing samples, therefore all assayed samples and ROIs were retained for further analysis. For the analysis we retained transcript clusters from the ‘main’ category with log-median intensity of 3 in at least one of the ROIs.
Random effects linear models approach was utilized to account for correlations between compartments within cases using Bioconductor package limma 41. Multiple comparisons was adjusted for using the Benjamini-Hochberg False Discovery Rate (FDR) method. A FDR≤0.05 was considered significant. Significantly differentially expressed genes with the fold-changes not exceeding 1.5 were not reported.
Pathway Analysis
For pathway analysis a Wilcoxon test implemented in geneSetTest function in limma was used, signed and unsigned moderated t-statistics from linear model fits were used to rank the genes. Gene Ontology Biological Processes annotations were downloaded from MSigDb42 and Enrichment Map Gene Sets collections (download.baderlab.org/EM_Genesets/). For analysis, only gene sets with less than 200 and more than 20 genes were considered. Benjamini-Hocheberg FDR method was used to correct for multiple comparisons.
ssGSEA Signature Score
ssGSEA scores were computed using GSVA Bioconductor package. The genes that were significantly upregulated in sT vs T comparison were used as a reference set (log FC thresholding was not applied here). For the TCGA and GSE46697 data sets both signature genes and reference set were subsetted to the genes measured in each study.
Publicly Available Data
Annotations for 333 TCGA prostate cancer samples were downloaded from cBioPortal (cbioportal.org/study?id=prad_tcga_pub #summary) and corresponding RSEM normalized gene expression values from FireHose portal (firebrowse.org/?cohort=PRAD&download_dialog=true). Mayo clinic cohort data were downloaded from Gene Expression Omnibus, accession number GSE46691.
Selection of Stromally Enriched Samples
In order to identify stromally enriched GSE46691 samples ssGSEA scores of the genes found to be significantly different with negative log FC in T-sT comparison (3000 genes) in the LCM data were computed using all measured genes as reference set. The scores computed on this set of genes had high correlations 0.34 and 0.82 with 1-Tumor Cellularity values inferred by pathologist and RNA-Seq-based computational estimates in TCGA data. Stromally enriched samples were defined as those having score above the median of the distribution of the score across all samples.
While the invention has been described in conjunction with the detailed description thereof, the foregoing description is intended to illustrate and not limit the scope of the invention, which is defined by the scope of the appended claims. Other aspects, advantages, and modifications are within the scope of the following claims.
The patent and scientific literature referred to herein establishes the knowledge that is available to those with skill in the art. All United States patents and published or unpublished United States patent applications cited herein are incorporated by reference. All published foreign patents and patent applications cited herein are hereby incorporated by reference. Genbank and NCBI submissions indicated by accession number cited herein are hereby incorporated by reference. All other published references, documents, manuscripts and scientific literature cited herein are hereby incorporated by reference.
While this invention has been particularly shown and described with references to preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the scope of the invention encompassed by the appended claims.
This application is a national stage application, filed under 35 U.S.C. § 371, of International Application No. PCT/US2016/061519, filed on Nov. 11, 2016, which claims the benefit of priority under 35 U.S.C. § 119(e) to U.S. Provisional Application No. 62/254,925, filed Nov. 13, 2015, each of which is incorporated herein by reference in its entirety.
This invention was made with government support under grant number R01CA131945 awarded by the National Institutes of Health, under grant number R01CA187918, awarded by the National Institutes of Health, under grant number DoD PC130716, awarded by the National Institutes of Health, under grant number P50 CA90381, awarded by the National Institutes of Health, and under grant number R01CA174206, awarded by the National Institutes of Health. The government has certain rights in the invention.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/US2016/061519 | 11/11/2016 | WO | 00 |
| Publishing Document | Publishing Date | Country | Kind |
|---|---|---|---|
| WO2017/083640 | 5/18/2017 | WO | A |
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| 62254925 | Nov 2015 | US |
