Patent Application
20190284640
The presently-disclosed subject matter relates to methods and systems for examining tumor samples, methods and systems for identifying subjects who are likely responders to therapy, and methods for treating cancer. In some embodiments, the presently-disclosed subject matter relates to determining expression of a major histocompatibility complex-II (MHC-II) molecule on a cell from a tumor sample, and further involving determining presence of tumor-infiltrating T cells in the tumor sample, determining the presence of tumor-infiltrating lymphocytes in the tumor sample, detecting chemokine expression in the tumor sample, and/or detecting TP53 mutations in the tumor sample. In some embodiments, the method involves treatment with an immunotherapeutic agent either alone or in combination with an MDM2 antagonist or an MEK inhibitor.
Immunotherapies that have been approved over the last several years have shown success in treatment of cancer; however, they are costly, they can result in patient toxicity, and they do not benefit all subjects. For example, about 20-50% of melanoma and lung cancers will respond significantly to immunotherapies, while others will not. Thus, identifying which subjects are better candidates for immunotherapy is highly advantageous from a health care and patient quality of life perspective.
PD-L1 is a cell surface glycoprotein that is one of two known ligands for Programmed Death 1 (PD-1). Expression of PD-L1 has been observed on the surface of a variety of immune cells, and PD-L1 mRNA is expressed by non- lymphoid tissues including vascular endothelial cells, epithelial cells, muscle cells, and in tonsil and placental tissue. PD-L1 expression has also been observed in a variety of human cancers, and interaction of tumor-cell expressed PD-L 1 with PD-1 can induce inhibition or apoptosis of tumor-specific T cells. In large sample sets of e.g. ovarian, renal, colorectal, pancreatic, liver cancers and melanoma it has been shown that PD-L1 expression correlated with poor prognosis and reduced overall survival irrespective of subsequent treatment. Anti-PD-1 monoclonal antibodies (mAbs) that block binding of PD-L1 to PD-1 have been shown to have anti-tumor activity against a variety of tumor types, with early human clinical data suggesting that patients whose tumors express PD-L1 are more likely to respond to anti-PD-1 therapy. See International Patent Application Publication No. WO 2014/165422.
Although immunostaining for PD-L1 on tumor cells has been reported to be associated with response in clinical trials, the staining protocol often requires frozen tissue, rather than the formalin-fixed industry standard, and is subject to technical difficulties. Further, the overall accuracy of PD-L1 staining was only 62% in a clinical study (NEJM, PMID:22658127), with imperfect negative and positive predictive value (JCO, PMID:24145345).
Accordingly, there remains a need in the art for a methods and systems for predicting response to immunotherapies, which have improved accuracy for independent use or use in tandem with existing predictive methods, such as PD-L1 staining. There also remains a need in the art for improved methods for examining tumor samples, and improved methods and compositions for treating cancer.
Immune checkpoint inhibitors that block the interaction between programmed death-1 (PD-1) and its ligand (PD-L1) have transformed the treatment landscape of numerous solid tumors (1*). These agents unleash restrained preexisting antitumor immune responses, leading to durable disease control in a substantial fraction of treated patients. Despite these advances, intrinsic and acquired resistance curtails clinical benefits in most patients.
MHC-II expression on tumor cells represents an autonomous phenotype that is associated with enhanced response to PD-1-targeted immunotherapy (12*), a finding subsequently validated in other tumor types (13*) and with combination immunotherapy (14*). While MHC-II expression is not required for response to immunotherapy in melanoma, tumors demonstrating this phenotype have particularly frequent and profound clinical responses (12*).
Molecular drivers of therapeutic resistance are incompletely characterized. Described resistance mechanisms include downregulation of antigen machinery by somatic mutations in JAK/STAT pathways (2*, 3*), alternative immune checkpoint expression (4*), loss or lack of immunogenic neoantigens (5*-10*), and tumor-intrinsic gene expression programs involving angiogenesis and wound healing (11*). Identifying effective therapeutic strategies to overcome mechanisms of resistance and characterizing novel drivers remain critical unmet needs.
The presently-disclosed subject matter meets some or all of the above-identified needs, as will become evident to those of ordinary skill in the art after a study of information provided in this document.
This Summary lists several embodiments of the presently disclosed subject matter, and in many cases lists variations and permutations of these embodiments. This
Summary is merely exemplary of the numerous and varied embodiments. Mention of one or more representative features of a given embodiment is likewise exemplary. Such an embodiment can typically exist with or without the feature(s) mentioned, likewise, those features can be applied to other embodiments of the presently disclosed subject matter, whether listed in this Summary or not. To avoid excessive repetition, this Summary does not list or suggest all possible combinations of such features.
In some embodiments, a method of examining a tumor sample from a subject involves (a) detecting cell membrane expression of a MEW molecule on a cell from the tumor sample; and (b) conducting one or more of steps (i)-(iv), including (i) determining the presence of tumor-infiltrating T cells in the tumor sample; (ii) determining the presence of tumor-infiltrating lymphocytes in the tumor sample; (iii) detecting chemokine expression in the tumor sample; and (iv) detecting TP53 mutations in the tumor sample.
In some embodiments of the methods, the MHC molecule is selected from HLA-A, HLA-B, HLA-C, HLA-DO, HLA-DM, HLA-DR, HLA-DP, HLA-DQ, and HLA-DX. In some embodiments, the cell membrane expression of the MEW molecule is detected using at least one method selected from the group consisting of immunohistochemistry, immunofluorescence, flow cytometry, mass-spectroscopy, RNA sequencing, RNA in situ hybridization, polymerase chain reaction (PCR), enzyme-linked immunosorbent assay (ELISA), and combinations thereof. In some embodiments, the cell membrane expression of the MHC molecule is detected by contacting the cell with an antibody targeting the MHC molecule and detecting binding between the MHC molecule and the antibody.
In some embodiments of the methods, the T cells are selected from CD4+ and CD8+ T cells. In some embodiments, the presence of tumor-infiltrating T cells in the tumor sample is detected using at least one method selected from the group consisting of immunohistochemistry, immunofluorescence, flow cytometry, mass-spectroscopy, RNA sequencing, RNA in situ hybridization, polymerase chain reaction (PCR), enzyme-linked immunosorbent assay (ELISA), and combinations thereof.
In some embodiments of the method, the presence of tumor-infiltrating lymphocytes in the tumor sample is detected using Haemotoxylin and Eosin staining.
In some embodiments of the method, the chemokines are selected from the group consisting of CCL5, CXCL9, CXCL10, and CXCL11. In some embodiments, the expression of chemokine expression in the tumor sample is detected using at least one method selected from the group consisting of immunohistochemistry, immunofluorescence, flow cytometry, mass-spectroscopy, RNA sequencing, RNA in situ hybridization, polymerase chain reaction (PCR), enzyme-linked immunosorbent assay (ELISA), and combinations thereof.
In some embodiments of the method, the TP53 mutations are detected by direct sequencing.
In a further embodiment, the method further includes detecting expression of a marker selected from the group consisting of: HLA-A, HLA-B, HLA-C, PD-1, PD-L1, CD8, CD4, CIITA, Foxp3, LAG3, TIM3, Ox40, Ox40L, 41BB, VISTA, Interferon gamma, Granzyme B, CTLA-4, and SOX-10. In one embodiment, the method of detecting cell membrane expression of an MHC molecule in a subject further includes staining for a cancer-specific marker. In another embodiment, the cancer-specific marker is a melanoma-specific marker, such as SOX-10.
The presently-disclosed subject matter further includes a method of identifying a subject as a likely responder to treatment with an immunotherapeutic agent when cell membrane expression of the MHC molecule on the cell is elevated, and at least one of (i)-(iv) is present: (i) a presence of tumor-infiltrating T cells in the tumor sample; (ii) a presence of tumor-infiltrating lymphocytes in the tumor sample; (iii) elevated chemokine expression in the tumor sample; and (iv) the subject has a TP53-mutation.
In some embodiments, the method also involves administering a therapeutically effective amount of an immunotherapeutic agent to the subject. In some embodiments, the immunotherapeutic agent is an antibody or an antigen-binding portion thereof that disrupts the interaction between PD-1 and PD-L1. In some embodiments, the immunotherapeutic agent is an antibody selected from anti-CTLA-4, anti-PD-L1, anti-PD-1, anti-LAG3, anti-TIM3, anti-OX40, anti-4-1BB, or an antigen-binding portion thereof. In some embodiments, the immunotherapeutic agent is administered in combination with an MDM2 antagonist or an MEK inhibitor. In some embodiments, the method involves administering a combination of an immunotherapeutic agent and a MEK, epigenetic DNA methyltransferase, or histone deacetylase inhibitor. In some embodiments, the method involves administering a combination of an anti-PD-L1 antibody and an MDM2 antagonist or an MEK inhibitor. In some embodiments, the method involves administering a combination of Atezolizumab and Cobimetinib. In some embodiments, the method involves administering a combination of comprises Atezolizumab and Idasanutlin.
In some embodiments, a method is provided where the tumor sample is collected at a first time point, and a second tumor sample is collected at a second time point, and further involves (a) detecting cell membrane expression of a MHC molecule on a cell from the second tumor sample; and (b) conducting one or more of steps (i)-(iii), including (i) determining the presence of tumor-infiltrating T cells in the second tumor sample; (ii) determining the presence of tumor-infiltrating lymphocytes in the second tumor sample; (iii) detecting chemokine expression in the second tumor sample; and (iv) detecting TP53 mutations in the second tumor sample. In some embodiments, the method also involves calculating differences between the tumor sample and the second tumor sample, including: differences in cell membrane expression levels of the MHC molecule; differences in tumor-infiltrating T cell levels; differences in tumor-infiltrating lymphocyte levels; and differences in chemokine expression levels. In some embodiments, the method and calculated differences can be used to assess response to treatment.
In some embodiments, the tumor sample is from a cancer selected from: melanoma, lung, ovarian, renal, colorectal, head and neck, bladder, endometrial, pancreatic, breast, and liver cancer, leukemia, and lymphoma. In some embodiments, the tumor sample is from a metastatic ER+ breast cancer. In some embodiments, the tumor sample is formalin-fixed. In some embodiments, the tumor sample is not a frozen tissue sample.
Illustrative aspects of embodiments of the present invention will be described in detail with reference to the following figures wherein:
The novel features of the invention are set forth with particularity in the appended claims. A better understanding of the features and advantages of the present invention will be obtained by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the invention are used, and the accompanying drawings of which:
MMTV-Neu cells.
The details of one or more embodiments of the presently-disclosed subject matter are set forth in this document. Modifications to embodiments described in this document, and other embodiments, will be evident to those of ordinary skill in the art after a study of the information provided in this document. The information provided in this document, and particularly the specific details of the described exemplary embodiments, is provided primarily for clearness of understanding and no unnecessary limitations are to be understood therefrom. In case of conflict, the specification of this document, including definitions, will control.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as is commonly understood by one of skill in the art to which the invention(s) belong. All patents, patent applications, published applications and publications, GenBank sequences, databases, websites and other published materials referred to throughout the entire disclosure herein, unless noted otherwise, are incorporated by reference in their entirety. In the event that there is a plurality of definitions for terms herein, those in this section prevail. Where reference is made to a URL or other such identifier or address, it understood that such identifiers can change and particular information on the internet can come and go, but equivalent information can be found by searching the internet. Reference thereto evidences the availability and public dissemination of such information.
Although any methods, devices, and materials similar or equivalent to those described herein can be used in the practice or testing of the presently-disclosed subject matter, representative methods, devices, and materials are now described.
Following long-standing patent law convention, the terms “a”, “an”, and “the” refer to “one or more” when used in this application, including the claims. Thus, for example, reference to “a cell” includes a plurality of such cells, and so forth.
Unless otherwise indicated, all numbers expressing quantities of ingredients, properties such as reaction conditions, and so forth used in the specification and claims are to be understood as being modified in all instances by the term “about”. Accordingly, unless indicated to the contrary, the numerical parameters set forth in this specification and claims are approximations that can vary depending upon the desired properties sought to be obtained by the presently-disclosed subject matter.
As used herein, the term “about,” when referring to a value or to an amount of mass, weight, time, volume, concentration or percentage is meant to encompass variations of in some embodiments ±5%, in some embodiments ±1%, in some embodiments ±0.5%, and in some embodiments ±0.1% from the specified amount, as such variations are appropriate to perform the disclosed method.
As used herein, ranges can be expressed as from “about” one particular value, and/or to “about” another particular value. 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. For example, if the value “10” is disclosed, then “about 10” is also disclosed. 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.
As used herein, “optional” or “optionally” means that the subsequently described event or circumstance does or does not occur and that the description includes instances where said event or circumstance occurs and instances where it does not. For example, an optionally variant portion means that the portion is variant or non-variant.
Unless otherwise indicated, the term “administering” is inclusive of all means known to those of ordinary skill in the art for providing a preparation to a subject, including administration by inhalation, nasal administration, topical administration, intravaginal administration, ophthalmic administration, intraaural administration, intracerebral administration, intravitreous administration, intracameral administration, posterior sub-Tenon administration, posterior juxtascleral administration, subretinal administration, suprachoroidal administration, cell-based administration or production, rectal administration, and parenteral administration, including injectable such as intravenous administration, intra-arterial administration, intramuscular administration, and/or subcutaneous administration. Administration can be continuous or intermittent.
In some embodiments a subject will be administered an effective amount of at least one compound and/or composition provided in the present disclosure. In this respect, the term “effective amount” refers to an amount that is sufficient to achieve the desired result or to have an effect on an undesired condition. For example, a “therapeutically effective amount” refers to an amount that is sufficient to achieve the desired therapeutic result or to have an effect on undesired symptoms, but is generally insufficient to cause adverse side effects. The specific therapeutically effective dose level for any particular patient will depend upon a variety of factors including the disorder being treated and the severity of the disorder; the specific composition employed; the age, body weight, general health, sex and diet of the patient; the time of administration; the route of administration; the rate of excretion of the specific compound employed; the duration of the treatment; drugs used in combination or coincidental with the specific compound employed and like factors well known in the medical arts. For example, it is well within the skill of the art to start doses of a compound at levels lower than those required to achieve the desired therapeutic effect and to gradually increase the dosage until the desired effect is achieved. If desired, the effective daily dose can be divided into multiple doses for purposes of administration. Consequently, single dose compositions can contain such amounts or submultiples thereof to make up the daily dose. The dosage can be adjusted by the individual physician in the event of any contraindications. Dosage can vary, and can be administered in one or more dose administrations daily, for one or several days. Guidance can be found in the literature for appropriate dosages for given classes of pharmaceutical products.
Additionally, the terms “subject” or “subject in need thereof” refer to a target of administration, which optionally displays symptoms related to a cancer. The subject of the herein disclosed methods can be a vertebrate, such as a mammal, a fish, a bird, a reptile, or an amphibian. Thus, the subject of the herein disclosed methods can be a human, non-human primate, horse, pig, rabbit, dog, sheep, goat, cow, cat, guinea pig or rodent. The term does not denote a particular age or sex. Thus, adult and newborn subjects, as well as fetuses, whether male or female, are intended to be covered. A patient refers to a subject afflicted with a disease or disorder. The term “subject” includes human and veterinary subjects.
As will be recognized by one of ordinary skill in the art, the terms “suppression,” “suppressing,” “suppressor,” “inhibition,” “inhibiting” or “inhibitor” do not refer to a complete elimination of angiogenesis in all cases. Rather, the skilled artisan will understand that the term “suppressing” or “inhibiting” refers to a reduction or decrease in angiogenesis. Such reduction or decrease can be determined relative to a control. In some embodiments, the reduction or decrease relative to a control can be about a 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, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, or 100% decrease.
As used herein, the terms “treatment” or “treating” relate to any treatment of a cancer. As such, the terms treatment or treating include, but are not limited to: preventing a condition of interest or the development of a condition of interest; inhibiting the progression of a condition of interest; arresting or preventing the development of a condition of interest; reducing the severity of a condition of interest; ameliorating or relieving symptoms associated with a condition of interest; and causing a regression of the condition of interest or one or more of the symptoms associated with the condition of interest.
The presently-disclosed subject matter includes methods and systems for examining tumor samples, methods and systems for identifying subjects who are likely responders to treatment, and methods for treating cancer. In some embodiments, the presently-disclosed subject matter relates to determining expression of a major histocompatibility complex-II (MHC-II) molecule on a cell from a tumor sample, and further involving determining presence of tumor-infiltrating T cells in the tumor sample, determining the presence of tumor-infiltrating lymphocytes in the tumor sample, detecting chemokine expression in the tumor sample, and/or detecting TP53 mutations in the tumor sample. In some embodiments, the method involves treatment with an immunotherapeutic agent either alone or in combination with an MDM2 antagonist or an MEK inhibitor. Also disclosed are kits useful for treating and/or predicting whether a subject is likely to benefit from treatment with an immunotherapy.
In some embodiments, a method of examining a tumor sample from a subject involves (a) detecting cell membrane expression of a MHC molecule on a cell from the tumor sample; and (b) conducting one or more of steps (i)-(iv), including (i) determining the presence of tumor-infiltrating T cells in the tumor sample; (ii) determining the presence of tumor-infiltrating lymphocytes in the tumor sample; (iii) detecting chemokine expression in the tumor sample; and (iv) detecting TP53 mutations in the tumor sample. The method can be performed ex vivo or in vitro.
With regard to the step of detecting cell membrane expression of a MHC molecule, the expression can be determined, for example, by providing a tumor sample from the subject, and determining the level of cell membrane expression of a MHC molecule, which can be an MHC-I or MHC-II molecule. In some embodiments, the MHC molecule is selected from HLA-A, HLA-B, HLA-C, HLA-DO, HLA-DM, HLA-DR, HLA-DP, HLA-DQ, and HLA-DX. In some embodiments, multiple distinct MHC molecules, or markers, are detected. For example, in one embodiment, the MHC molecule includes HLA-DR. In another embodiment, the MHC molecule includes HLA-DR and at least one of HLA-A, HLA-B, HLA-C, PD-1, or PD-L1.
In some embodiments, the cell membrane expression of the MHC molecule is detected using at least one method selected from the group consisting of immunohistochemistry, immunofluorescence, flow cytometry, mass-spectroscopy, RNA sequencing, RNA in situ hybridization, polymerase chain reaction (PCR), enzyme-linked immunosorbent assay (ELISA), and combinations thereof. In some embodiments, the cell membrane expression of the MHC molecule is detected by contacting the cell with an antibody targeting the MHC molecule and detecting binding between the MHC molecule and the antibody.
In some embodiments of the methods, the T cells are selected from CD4+ and CD8+ T cells. In some embodiments, the presence of tumor-infiltrating T cells in the tumor sample is detected using at least one method selected from the group consisting of immunohistochemistry, immunofluorescence, flow cytometry, mass-spectroscopy, RNA sequencing, RNA in situ hybridization, polymerase chain reaction (PCR), enzyme-linked immunosorbent assay (ELISA), and combinations thereof.
In some embodiments of the method, the presence of tumor-infiltrating lymphocytes in the tumor sample is detected using Haemotoxylin and Eosin staining.
In some embodiments of the method, the chemokines are selected from the group consisting of CCL5, CXCL9, CXCL10, and CXCL11. In some embodiments, the expression of chemokine expression in the tumor sample is detected using at least one method selected from the group consisting of immunohistochemistry, immunofluorescence, flow cytometry, mass-spectroscopy, RNA sequencing, RNA in situ hybridization, polymerase chain reaction (PCR), enzyme-linked immunosorbent assay (ELISA), and combinations thereof.
In some embodiments of the method, the TP53 mutations are detected by direct sequencing.
In some embodiments of the methods disclosed herein, it can be beneficial to also probe for a cancer-specific marker, e.g., a dual stain, to facilitate identification of cancer cells in the sample. For one non-limiting example, the cancer-specific marker could be a melanoma-specific marker, such as SOX-10.
Additionally or alternatively, the markers may include, but are not limited to, CD8, CD4, CIITA, Foxp3, LAG3, TIM3, Ox40, Ox40L, 41BB, VISTA, Interferon gamma, Granzyme B, interferon gamma response gene signatures, CTLA-4, SOX-10, or a combination thereof.
In some embodiments, the methods disclosed herein involve identifying likely responders to treatment with an immunotherapy or combination therapy. For example, in some embodiments, the method involves identifying a subject as a likely responder when cell membrane expression of the MHC molecule on the cell is elevated, and at least one of (i)-(iv) is present: (i) a presence of tumor-infiltrating T cells in the tumor sample; (ii) a presence of tumor-infiltrating lymphocytes in the tumor sample; (iii) elevated chemokine expression in the tumor sample; and (iv) the subject has a TP53-mutation. Elevated levels can be determined relative to a control, or with reference to a predetermined standard.
A “predetermined standard” or “reference” can include, for example, a specific expression level threshold. In some embodiments, the reference can include control data. Control data, when used as a reference, can comprise compilations of data, such as may be contained in a table, chart, graph, e.g., standard curve, or database, which provides amounts or levels of expression considered to be threshold levels or control levels. Such data can be compiled, for example, by obtaining expression levels from one or more tumor samples (e.g., an average of amounts or levels from multiple samples) from one or more individuals with the cancer of interest or without the cancer of interest.
In some embodiments of the presently-disclosed subject matter, a likely responder/a subject can be identified as being likely to benefit from treatment is administered such treatment. In this regard, some embodiments of the methods further include administration of an immunotherapeutic agent. In some embodiments, the immunotherapeutic agent is an antibody or an antigen-binding portion thereof that disrupts the interaction between PD-1 and PD-L1. In some embodiments, the immunotherapeutic agent is an antibody selected from anti-CTLA-4, anti-PD-L1, anti-PD-1, anti-LAG3, anti-TIM3, anti-Ox40, anti-4-1BB, or an antigen-binding portion thereof.
In some embodiments, the method optionally involves administering a MEK, epigenetic DNA methyltransferase, and/or histone deacetylase inhibitor. Examples of MEK inhibitors include, but are not limited to, Selumetinib (AstraZeneca), PD0325901 (Pfizer), Pimasertib, MEK inhibitor AS703026 (Merck Serono), Cobimetinib (Exelixis), Trametinib (Mekinist), binimetinib (Array BioPharma Inc), MEK inhibitor WX-554 (Wilex), refametinib (Ardea Biosciences), and AZD8330 (AstraZeneca).
In some embodiments, the immunotherapeutic agent is administered in combination with an MDM2 antagonist or an MEK inhibitor. In some embodiments, the method involves administering a combination of an immunotherapeutic agent and a MEK, epigenetic DNA methyltransferase, or histone deacetylase inhibitor. In some embodiments, the method involves administering a combination of an anti-PD-L1 antibody and an MDM2 antagonist or an MEK inhibitor. In some embodiments, the method involves administering a combination of Atezolizumab and Cobimetinib. In some embodiments, the method involves administering a combination of comprises Atezolizumab and Idasanutlin.
In some embodiments, a method is provided where the tumor sample is collected at a first time point, and a second tumor sample is collected at a second time point, and further involves (a) detecting cell membrane expression of a MEW molecule on a cell from the second tumor sample; and (b) conducting one or more of steps (i)-(iii), including (i) determining the presence of tumor-infiltrating T cells in the second tumor sample; (ii) determining the presence of tumor-infiltrating lymphocytes in the second tumor sample; (iii) detecting chemokine expression in the second tumor sample; and (iv) detecting TP53 mutations in the second tumor sample. In some embodiments, the method also involves calculating differences between the tumor sample and the second tumor sample, including: differences in cell membrane expression levels of the MHC molecule; differences in tumor-infiltrating T cell levels; differences in tumor-infiltrating lymphocyte levels; and differences in chemokine expression levels. In some embodiments, the method and calculated differences can be used to assess response to treatment.
The presently-disclosed subject matter further includes kits useful for treating and/or predicting whether a subject is likely to benefit from treatment with an immunotherapy. In some embodiments, the kit includes a probe for a MHC molecule, selected from an MHC-I or MHC-II molecule. The kit can optionally include standards to which the level of cell membrane expression of the MHC molecule in the tissue sample from the subject is compared. In some embodiments, wherein the MHC molecule is selected from one or more of HLA-A, HLA-B, HLA-C, HLA-DA, HLA-DM, HLA-DR, HLA-DP, HLA-DQ, and HLA-DX.
The term “cancer” refers to all types of cancer or neoplasm or malignant tumors found in animals, including leukemias, carcinomas, melanoma, and sarcomas. Examples of cancers include, but are not limited to, melanoma, lung, ovarian, renal, colorectal, head and/or neck, bladder, endometrial, pancreatic, breast cancer, including metastatic ER+ breast cancer, liver cancer, leukemia, and lymphoma.
The presently-disclosed subject matter has the benefit of being useful in connection with a variety of tissue preparations. For example, while the methods disclosed herein can be used in connection with frozen tissue, frozen tissue is not required. Indeed, the methods can be used in connection with a formalin-fixed sample.
The probe included in the kit can be, for example, an antibody or an antigen-binding portion thereof that binds specifically to the cell surface-expressed MHC molecule. In some embodiments, the antibody or an antigen-binding portion thereof binds specifically to the cell surface-expressed MHC molecule in a formalin-fixed, paraffin-embedded (FFPE) tissue sample. The antibody or an antigen-binding portion can optionally include a tag, such as a fluorescent tag. In some embodiments, the kit includes a secondary antibody including a tag.
In some embodiments, the kit can optionally include a cancer-specific marker. For example, the cancer-specific marker could be a melanoma-specific marker, such as SOX-10.
In some embodiments of the kit, an immunotherapeutic agent is also provided. For example, the immunotherapeutic agent can be an antibody or an antigen-binding portion thereof that disrupts the interaction between PD-1 and PD-L1. In some embodiments, the immunotherapeutic agent is an antibody selected from anti-CTLA-4, anti-PD-L1, anti-PD-1, anti-LAG3, anti-TIM3, anti-Ox40, anti-4-1BB, or an antigen-binding portion thereof.
In some embodiments of the kit, a MEK, epigenetic DNA methyltransferase, and/or hi stone deacetylase inhibitor is also provided. Examples of MEK inhibitors include, but are not limited to, Selumetinib (AstraZeneca), PD0325901 (Pfizer), Pimasertib, MEK inhibitor AS703026 (Merck Serono), Cobimetinib (Exelixis), Trametinib (Mekinist), binimetinib (Array BioPharma Inc), MEK inhibitor WX-554 (Wilex), refametinib (Ardea Biosciences), and AZD8330 (AstraZeneca).
The presently-disclosed subject matter further includes a cell surface-expressed MHC molecule, as disclosed herein, in complex with an antibody or an antigen-binding portion thereof that binds specifically to the MHC molecule, as disclosed herein.
The presently-disclosed subject matter is further illustrated by the following specific but non-limiting examples. The following examples may include compilations of data that are representative of data gathered at various times during the course of development and experimentation related to the present invention.
Melanoma-specific MHC-II expression represents a tumor-autonomous phenotype and predicts response to anti-PD-1/PD-L1 therapy.
Abstract
Anti-PD-1 therapy yields objective clinical responses in 30-40% of advanced melanoma patients. Since most patients do not respond, predictive biomarkers to guide treatment selection are needed. In view thereof, this example examines whether MHC-I/II expression is required for tumor antigen presentation and may predict response to anti-PD-1 therapy. Across 60 melanoma cell lines, bimodal expression patterns of MHC-II were found, while MHC-I expression was ubiquitous. A unique subset of melanomas are capable of expressing MHC-II under basal or IFNγ stimulated conditions. Using pathway analysis, it was found that MHC-II(+) cell lines demonstrate signatures of ‘PD-1 signaling’, ‘allograft rejection’, and ‘T-cell receptor signaling’, among others. In two independent cohorts of anti-PD-1-treated melanoma patients, MHC-II positivity on tumor cells was strongly associated with response to therapy, progression-free survival, and overall survival. MHC-II positivity also correlated with CD4+ and CD8+ tumor infiltrate. Accordingly, it was concluded that some melanomas demonstrate an autonomous MHC-II signature that correlates with anti-PD-1 response and enhanced T-cell infiltrate. MHC-II+ tumors can be robustly identified by routine melanoma-specific immunohistochemistry using commercially available antibodies for HLA-DR to improve anti-PD-1 patient selection.
Introduction
Monoclonal antibodies blocking the programmed death-1 (PD-1) receptor or its ligand (PD-L1) relieve the suppression of anti-tumor immune responses in a variety of cancers. Durable remissions occur in sizable fractions of patients with melanoma (30-40%), non-small cell lung cancer (15-20%), renal cell carcinoma (20-30%), bladder urothelial carcinoma (30%), Hodgkin lymphoma (80-90%), and others including head and neck squamous cell carcinoma and triple negative breast cancer. Accurate predictive markers of therapeutic efficacy are needed to optimize patient selection, improve treatment decision-making, and minimize costs. To date, several candidate approaches have been identified in melanoma. These include tumor or immune cell expression of PD-L1, identification of neo-antigens through next generation sequencing techniques, and T-cell receptor clonality profiling. While quite promising, these assays are technically challenging and require specialized tissue processing.
Tumors evade immune surveillance by immune checkpoint expression (PD-L1 and others), immunosuppressive cytokine profiles, tolerogenic immune cell recruitment (regulatory T-cells and others), and cancer-specific cell signaling. In addition, cancer cells can lose the ability to present tumor antigens, thus avoiding recognition by cytotoxic T cells and antigen presenting cells. Down-regulation of major histocompatibility class I and II (MHC-I and MHC-II) has been linked to immune suppression, metastatic progression, and a poor prognosis in numerous malignancies.
Despite the established importance of tumor-specific antigen expression, the influence of MHC-I and MHC-II expression on response to new immune therapies, particularly anti-PD-1/PD-L1, has not been explored. Specifically, HLA-DR is frequently expressed on melanoma and has unclear functional and prognostic significance. Without wishing to be bound by theory, it is believed that MHC-I and MHC-II expression, particularly HLA-DR, are required for anti-PD-1/PD-L1 activity and serve as technically and clinically feasible predictive biomarkers for therapeutic efficacy. As shown in this example, melanoma-specific expression of HLA-DR marks tumors with unique inflammatory signals that are more responsive to PD-1 targeted therapy. Accordingly, it is believed that tumor-specific HLA-DR expression may be used as a biomarker of high likelihood of response to these agents.
Results
Antigen presenting MHC-I and MHC-II pathways in melanoma cell lines. Based on the known biological interactions of PD-1/PD-L1 signaling, antigen presentation by tumor or professional antigen-presenting cells is hypothesized to be a requirement for immune recognition of the malignant cell. MHC-I presents antigen to CD8+ cytotoxic T lymphocytes (CTL) and is ubiquitously expressed by most cells. Loss of MHC-I is typically thought to trigger natural-killer (NK) cell checkpoints, resulting in NK-mediated cytotoxicity. In contrast, MHC-II, which presents antigen to CD4+ T helper cells, is typically restricted to professional antigen-presenting cells (APCs) such as dendritic cells and B cells. HLA-DR, the primary antigen-presenting molecule of the MHC-II pathway is expressed in some cancers, particularly in response to CTL-secreted interferon-gamma (IFNγ). Some data suggest that non-immune cells, including cancer cells can function as MHC-II+ APCs. Given the heterogeneity of the tumor milieu, a question arose as to whether MHC-I and II were expressed in in vitro cell line models of melanoma (rather than in resected melanoma tumors), where the contribution of stromal and infiltrating immune cells could be excluded.
Using the Cancer Cell Line Encyclopedia (CCLE) melanoma panel of 60 cell lines, it was determined that MHC-I mRNA expression (using HLA-A as the prototype) was ubiquitously high across almost all melanoma cell lines (
Since mRNA expression does not imply functional protein expression, and because micro-environmental IFNγ is known to influence MHC-I, MHC-II and PD-L1 expression, representative cell lines from HLA-DRA-expressing (cluster Ia and Ib,
Interestingly, PD-L1 expression was potently induced with stimulation in all cell lines, though the HLA-DR+ cell lines exhibited greater populations of cells that were PD-L1 positive in the absence of IFNγ (
HLA-DR expression by genotype. HLA-DRA expression was specifically enriched in cell lines harboring NRAS mutations (
HLA-DR expression in patients receiving anti-PD-1/PD-L 1. The instant inventors previously observed that in a diverse collection of melanoma cell lines, patterns of HLA-DR expression were 1) constitutively high, 2) heterogeneous, but inducible by IFNγ, or 3) constitutively off. Similar patterns were observed in a cohort of unselected melanoma tumors, and thus it was hypothesized that these patterns may be predictive of benefit to immunotherapy.
To test this hypothesis, patient-derived xenograft (PDX) models were utilized from the tumor resections of two melanoma patients who subsequently received anti-PD1 therapy; patient 1 (PT1; non-responder, 0% HLA-DR-positive, class II/III) and patient 2 (PT2; partial responder, heterogeneous 15% HLA-DR-positive, class Ib) (
In order to determine whether MHC-II expression on melanoma tumors is associated with clinical response to PD-1/PD-L1 targeted therapy, archival pre-treatment biopsy or resection specimens were obtained from 30 patients treated with anti-PD-1 (nivolumab, pembrolizumab) or anti-PD-L1 (MPDL3280A; n=2). The median age was 56 years, the median number of prior therapies was 1, and 14 (47%) had failed ipilimumab (Table 3). Twenty-three patients (77%) had stage IV M1c disease and 12 (40%) had elevated serum lactate dehydrogenase (LDH).
MHC-II+ from MHC-II- samples were differentiated using a cutoff of >1% of tumor (SOX10+) membranes showing staining. However, the vast majority of positive samples were positive in greater than 5% of tumor cells in the entire section; only one positive sample within the cohort scored at the 2% range. HLA-DR staining strongly correlated with response to therapy. Among 14 patients with positive HLA-DR staining (>1% estimation of positive tumor membranes in the entire tissue section), 11 patients (79%) had complete (n=3) or partial (n=8) response (
Progression-free survival (PFS) between patient groups in both datasets was also compared, when survival data were available. The median PFS was superior in the HLA-DR (+) group (median not reached vs. 3.2 months, log-rank p=0.01;
MHC-II antibody specificity and concordance of assessment. To investigate the possibility of alternative MHC class II molecule expression, IHC was performed using a second monoclonal antibody targeting a common epitope to HLA-DR-DP-DQ and -DX (pan-MHC-II) on all samples. Results largely correlated with HLA-DR (
Other Clinical Correlates. To investigate the impact of MHC class I expression on response to anti-PD-1/PD-L1, HLA-A IHC was performed on the same pre-treatment samples. As observed in melanoma cell line models, HLA-A expression was nearly ubiquitous across all tumors and expression level was not statistically associated with response to therapy (
Discussion
Targeting the PD-1/PD-L1 signaling axis produces durable responses in a subset of melanoma patients. Although a genetic basis for clinical response to CTLA-4 inhibition in melanoma has recently been suggested, so far few studies have suggested a tumor-cell autonomous basis for response to PD-1/PD-L1 monoclonal antibodies. Herein, a unique inflammatory transcriptional signature in melanoma cell lines that can be identified by tumor cell-specific MHC-II/HLA-DR expression has been identified. Interestingly, heterogeneity in MHC-II expression among panels of melanoma lines has been previously noted. Without wishing to be bound by theory, it is believed that MHC-II expression is either 1) a functional antigen-presenting molecule that can promote CD4 T helper cell aid to the antitumor milieu or 2) a non-functional marker of the inflammatory state of the cell or tumor milieu. The presence of heterogeneity among cell lines grown ex vivo argues against the latter. Yet another alternative hypothesis is that MHC-II expression on melanoma cells could be instrumental in promoting Treg differentiation in a process that requires PD-1/PD-L1 interaction; thus interruption of this signaling could be beneficial in MHC-II+ tumors. Although different CD4 subsets (Th1, Th2, Th17, Treg) were not assessed, superior clinical outcomes with anti-PD-1/PD-L1 therapy was nonetheless observed in patients harboring melanomas with MHC-II expression. A limited analysis of FoxP3 staining in 10 specimens from the cohort with CD4 positivity showed no association of FoxP3 or FoxP3:CD4 ratio with response to PD-1-targeted therapy or with HLA-DR tumor cell positivity (data not shown).
In a bioinformatics analysis of MHC-II expression in melanoma cell lines, which rules out contaminating stromal and immune contribution, a number of gene expression pathways were found to be up-regulated in melanoma cell lines expressing MHC-II (
Although MHC-I is ubiquitously expressed in most cell types, MHC-II is typically restricted to the immune system, as the MHC-II pathway is thought to utilize extracellular antigens (released from apoptotic or necrotic cells and engulfed by professional APCs). However, tumor-specific MHC-II expression has been noted in a number of malignancies, including breast, colon, and melanoma. Experimentally, MHC-II(+) epithelial cells can present antigen to CD4(+) T-helper cells and enforced expression of MHC-II in tumor cells can promote anti-tumor immunity and tumor rejection in vivo. Collectively these data support a role for aberrant HLA-DR/MHC-II expressing tumors as being a uniquely immunogenic subtype (with the ability to stimulate CD4(+) T-helper cells) which may adapt by expressing PD-L1. Thus, although some MHC-II(-) tumors may express PD-L1, this alone may not permit anti-tumor immunity through PD-1/PD-L1 inhibition.
In this study, HLA-DR expression strongly correlated with response to anti-PD-1. Critically, other relevant variables also co-occurred with HLA-DR expression, demonstrated through in silico cell line analysis (Gene Set Analysis, total somatic mutational burden), flow cytometry of well-characterized melanoma cell lines (PD-L1 expression and CIITA expression), and pre-treatment melanoma samples (CD4 and CD8 T cell infiltration). Together, these data strongly argue that HLA-DR plays a causal or correlative role in anti-PD-1/PD-L1 responses. Interestingly, HLA-A expression did not statistically correlate with CD8 expression in the study (
Although data point toward a functional role of MHC-II expression as contributing to sensitivity to PD-1/PD-L1 axis inhibition, it is important to note that some tumors responded to PD-1 targeted therapy, despite having no detectable MHC-II expression. There are several possible explanations for this observation: 1) that tumor sampling heterogeneity limited the ability to detect HLA-DR in the tumor and/or 2) that these tumors may be similar to the Ib (Interferon-inducible) group and PD-1 inhibition in these patients may increase CD8 infiltration and local IFNγ secretion, inducing HLA-DR, which could be detected by an on-treatment assessment. Of course, this is hypothetical, and also assumes that HLA-DR is a functional biomarker, rather than a surrogate, which remains to be experimentally proven. Yet a third hypothesis would be that other inflammatory/antigenic factors mediated by MHC-I (such as mutational burden and neo-antigen presence) could be sufficiently high in some cases to circumvent or abrogate an MHC-II requirement. Nonetheless, the potential role of MHC-II as a surrogate biomarker for response cannot be overlooked.
In order to demonstrate a functional role of MHC-II in promoting response to PD-1/PD-L1 therapy, Ciita was overexpressed in B16/F0 melanoma cells to determine whether constitutive tumor cell MHC-II expression would enhance response to PD-L1 mAB in vivo. Despite previous reports of successful constitutive MHC-II (IA/IE) expression by lentivirally-mediated Ciita overexpression, the instant inventors were unable to establish a stable population of MHC-II+ cells in culture, despite repeated rounds of selection and flow sorting (
Nonetheless, either control (LacZ-expressing) or Ciita/MHC-II+ B16 cells (ranging from 10-30% MHC-II+ at the time of injection) was injected into the flank of C57/B16 mice and monitored tumor growth and survival with either IgG (isotype) control or anti-PD-L1 mAB, given twice weekly, beginning on day +1 following tumor cell challenge. The subgroup of Ciita+ B16 melanoma cells with the highest degree of MHC-II positivity (30%) at the time of injection, treated with anti-PD-L1, had slower tumor formation and prolonged survival, although the effect was marginal (
Conflicting reports of stromal versus tumor PD-L1 staining, coupled with lack of standardization, proprietary nature, and the difficulties associated with PD-L1 as an IHC antigen have precluded the routine use of this marker in the clinic. In the study, a relatively low number of samples stained positively for PD-L1, despite appropriate positive controls (human placenta). The low proportion of samples with PD-L1 staining and lack of correlation of positivity with patient benefit reinforce the problems of using PD-L1 as a clinical biomarker. In contrast, HLA-DR can be robustly identified on tumor cells through use of dual-color IHC using well-established commercially available antibodies. Thus, it is proposed that with additional validation, melanoma HLA-DR expression may be a rapidly translatable biomarker for patient stratification of PD-1/PD-L1 immunotherapy which can easily be performed in standard pathology laboratories at most institutions at low cost. This marker, if validated, could be envisioned to stratify patients toward anti-PD-1 monotherapy and away from the more toxic but potentially more clinically-active combination of ipilimumab and nivolumab. Furthermore, understanding the biological basis for differential MHC-II expression among melanomas may identify agents that induce MHC-II positivity and can be used in combination with PD-1/PD-L1 targeted therapy to enhance response rates.
Methods
Immunoblotting was performed as previously described32 Briefly, cells were washed in cold phosphate-buffered saline, collected and lysed in 1×RIPA buffer (50 mM Tris (pH 7.4), 1% NP-40, 150 mM NaCl, 1 mM EDTA, 0.1% SDS, 0.25% sodium deoxycholate, 5 mM NaF, 5 mM Na3VO4, 10% glycerol, 1M phenylmethyl-sulphonylfluoride and protease inhibitors) for 30 min on ice. Lysates were sonicated for 2-3 s to shear DNA and cleared by centrifugation at 13,200 r.p.m. for 15 min. Protein concentrations of the lysates were determined by BCA assay (Bio-Rad, Hercules, Calif.). Samples were separated by SDS-PAGE and transferred to nitrocellulose membrane. Membranes were blocked with 5% non-fat dry milk or 5% bovine serum albumin in tris-buffered saline with 0.1% Tween-20 for 1 h at room temperature and then incubated overnight at 4° C. with the appropriate antibody as indicated. Following incubation with appropriate horseradish peroxidase-conjugated secondary antibodies, proteins were visualized using an enhanced chemiluminescence detection system. This study was performed using the following antibodies: p-STAT1 (Cell Signaling Technology. #7649, 1:5000) STAT1 (Santa Cruz Biotechnology. # SC592. 1:5000), p-ERK1/2 (Cell Signaling Technology #9101, 1:5000), ERK1/2 (Cell Signaling Technology #9102. 1 5000), CIITA (Cell Signaling Technology #3793, 1:1000) HLA-DR (Santa Cruz, sc-53319., 1:5000).
Standard Flow Cytometry. Flow cytometry was performed using the following antibodies: HLA-DR/PE-Cy7 (Biolegend, clone L243. 1:20). CD274/PD-L1/APC (Biolegend, clone 29E.2A3, 1:200) and HLA-A/B/C-Alexa Fluor488 (1:100, Biolegend, clone W6/32) mouse MHC-II (I-A/I-E 1:20 Biolegend, clone M5/114.15.2). DAPI was used as a viability dye. Samples were analyzed on an Aria III laser system (BD Biosciences)
Phospho-flow cytometry. Melanoma cell lines were treated with Accutase™ (EMD Millipore, # SCR005) for 10 minutes at 37° C. to dissociate them from the plate. Dissociated cell lines were rested at 37° C. in a CO2 incubator for 30 minutes prior to stimulation. After resting, cells were stimulated by adding IFNy (Cell Signaling) at a final concentration of 100 ng/mL. During signaling, cells were kept in a 37° C. CO2 incubator. After 15 minutes of signaling, cells were fixed for 10 minutes at room temperature with a final concentration of 1.6% paraformaldehyde (Electron Microscopy Services). Cells were then pelleted and permeabilized by resuspension in 2 ml of methanol and stored over night at −20° C. Flow cytometry was performed using the following antibodies: HLA-DR/BV421 (BD Horizon™, clone G46-6, 1:40), p-STAT5/PE-Cy7 pY694 (BD Phosflow™, clone 47, 1:10), and p-STAT1/PerCP-Cy5.5 pY701 (BD Phosflow™, clone 4A, 1:10). Samples were analyzed on a LSRII system (BD Biosciences).
Immunohistochemistry. For HLA-DR (Santa Cruz [sc-53319], 1:1000)/SOX10 (LsBio [LS-C312170], 1:30), HLA-DR-DP-DQ-DX (Santa Cruz [sc53302), 1:1000)/SOX10, HLA-A (Santa Cruz [sc-365485], 1:1300)/SOX10, and PD-L1 (Cell Signaling #13684, 1:500)/SOX10 dual IHC tumor sections were stained overnight at 4° C. with both antibodies. Antigen retrieval was performed using Citrate Buffer (pH 6) using a Biocare Decloaking Chamber. The visualization system utilized was MACH2 (Biocare) using DAB (Dako) and Warp Red (Elmore), and counterstained with hematoxylin.
For CD4 and CD8 staining, slides were placed on a Leica Bond Max IHC stainer. All steps besides dehydration, clearing and coverslipping are performed on the Bond Max. Heal induced antigen retrieval was performed on the Bond Max using their Epitope Retrieval 2 solution for 20 minutes. Slides were incubated with anti-CD4 (PA0427, Leica, Buffalo Grove, Ill.) or anti-CD8 (MS-457-R7, ThermoScientific. Kalamazoo. Mich.) for one hour. The Bond Polymer Refine detection system was used for visualization. CD4 and CD8 were scored as % infiltrating CD4(+) or CD8(+) cells in the tumor area.
HLA-DR scoring determination. Two pathologists (MVE and RS) who were unaware of clinical response data made independent visual estimations of the percentage of tumor membrane-specific positivity for HLA-DR, in SOX10(+) nuclei areas, in the whole tumor section focusing at the tumor hot spots. For all staining batches positive and negative controls (human tonsil; HLA-DR is positive in germinal and non-germinal center cells and negative in squamous epithelial cells) were included and stained appropriately and reproducibly in all cases. Furthermore, nearly all cases had positive-staining stromal cells (presumably B-cells and macrophages) as an internal control. In concordant cases (both investigators scored as ‘negative’ (1% or less of all tumor cells in the entire tissue section staining positive; i.e. all analyzable fields of view) or ‘positive’ (>1% of tumor cells in the entire tissue section staining positive; i.e. all analyzable fields of view)), the result was averaged. For discordant cases {i.e. positive vs. negative interpretation, or any concerns on evaluable nature of the specimen) the investigators reviewed the case together to reach a final conclusion or consensus. If no consensus could be agreed upon, the sample was listed as non-evaluable.
Cancer Cell Line Encyclopedia analysis. Gene expression data (Affymetrix hg133p1us2) from the Cancer Cell Line Encyclopedia (CCLE) were downloaded from the Broad Institute (broadinstitute.org) and analyzed in R (r-project.org/). RMA-normalized melanoma cell line data were collapsed to the gene level and filtered using the ‘genefilter’ package. Differentially expressed genes were identified using a t-test with a false-discovery rate correction. Hierarchical clustering was performed using 1-Spearman's rank correlation and complete linkage. Gene Set Analysis was performed using the GSA package in R and the maxmean statistic. Gene sets in the molecular signatures database curated gene sets C2 collection (version 3.0) were utilized for GSA.
Cell and tumor culture. SKMEL-28 and WM115 cell lines were obtained from Dr. Kimberly Dahlman (Vanderbilt University), CHL-1 and HMCB melanoma cell lines were obtained from the laboratory of William Pao (Vanderbilt University). Cell line nature was not directly authenticated, but protein marker expression was consistent with published HLA-DIM mRNA expression patterns (CCLE). Cell lines were confirmed mycoplasma-free and cultured in DMEM containing 10% FBS. Stimulation with recombinant human IFNγ (R&D Systems) was performed at 100 ng/mL. For PDX models and ex-vivo organotypic culture, tumors were freshly resected and sectioned using an Alto tissue matrix sectioner (Roboz Surgical, Gaithersburg, Md.).
Patients. Patient samples and data were procured based on availability of tissue and were not collected according to a pre-specified power analysis. All patients were consented on IRB approved protocols (Vanderbilt IRB #030220 and 100178). Tumor samples for the TMA and for the HLA-DR staining cohort were obtained from tumor biopsies or tumor resections obtained for clinical purposes. Samples were obtained within 2 years of start of anti-PD-1/PD-L1 therapy (nivolumab, pembrolizumab, MPDL3280a). Only patients with available tumor samples and evaluable responses were included. In cases where multiple tissues were available for the same patient, the evaluable sample collected closest to PD-1 therapy was utilized for scoring. Clinical characteristics and objective response data were obtained by retrospective review of the electronic medical record. All responses were investigator assessed, RECIST defined responses or (in a single case) prolonged stable disease with clinical benefit lasting >3 years.
For the validation set, all patients were consented to an IRB-approved tissue banking protocol (for MGH patients as part of either Dana Farber Harvard Cancer Center protocols 02-017 and 11-181). Samples were obtained prior to therapy with anti-PD-1/PD-L1 monoclonal antibodies for research (as opposed to clinical) purposes. A linked database was prospectively maintained and regularly updated with clinical characteristics, response to therapy, date of progression (if applicable), and date of death or last follow up visit.
Statistical analysis. The tests of hypotheses concerning between two groups comparisons were completed using either two-sample Student t-test or non-parametric Wilcoxon rank sum test for continuous variables of interest. The Analysis of Variance (ANOVA) with Tukey's multiple comparison adjustment was used for comparisons of more than two independent groups. Dichotomous data were compared using the chi-square test ith the Yates correction or Fisher's exact test when appropriate. The Kolmogorov-Smirnov test (KS-test) was used to determine if the distribution of the datasets differed significantly. For progression free survival (PFS) analysis, the survival curves were estimated using the Kaplan-Meier method with the log-rank test to examine the statistically significant differences between study groups. For gene analysis, the FDR adjusted Student t-test was used to identify the “winner genes” then followed by the complete linkage cluster analysis based on 1-Spearman correlation. Statistical analyses were performed using R or GraphPad Prism. All P values reported were 2-sided.
Reduced tumor lymphocytic infiltration in the residual disease (RD) of post-neoadjuvant chemotherapy (NAC) triple-negative breast cancers (TNBC) is associated with Ras/MAPK activation and poorer survival.
Background: Tumor-infiltrating lymphocytes (TILs) are associated with improved prognosis in TNBCs, with several retrospective analyses demonstrating that TNBCs with high baseline TILs have higher rates of pathologic complete response (pCR) to NAC. Moreover, the TIL burden in the RD of patients who do not achieve pCR to NAC is also correlated with prognosis. However, insight into the molecular pathways in TNBC which modulate heterogeneity in host anti-tumor immune responses is lacking. To address this gap in knowledge, TILs were analyzed retrospectively in a cohort of clinically and molecularly characterized TNBCs with RD after NAC.
Methods: TILs were scored in H&E stained slides by expert pathologists in the post-treatment tumors of 92 NAC-treated TNBC patients with RD at the time of resection and in 44 matched baseline diagnostic biopsies. Genomic alterations in the RD were assayed using targeted next-generation sequencing (tNGS) while selected transcriptional signatures were evaluated by NanoString as previously published (Balko et al, Cancer Discovery 2014). Differences in pre- and post-NAC TILs were compared between tumors harboring alterations in cell cycle, PI3K/mTOR, growth factor receptors, Ras/MAPK and DNA repair pathways. Associations of TILs with transcriptional signatures were also tested.
Results: A strong positive association of TILs in NAC-treated specimens was observed with RFS (coxPH p=0.0001, relative risk reduction of 3.4% for each % of TILs) and OS (p=0.0016; relative risk reduction of 2.8% for each % of TILs). In multivariate analysis with stage, age, node status and RD tumor cellularity, TILs in the post-NAC disease remained a significant predictor of RFS and OS (p=0.0008 and p=0.007, respectively). TILs tended to decrease with NAC in paired samples, although this decrease was not statistically significant (p=0.07).
Genetic alterations in the Ras/MAPK (amplifications in KRAS, BRAF, RAFT and truncations in NF1) and cell cycle pathway (alterations in CCND 1-3, CDK4, CDK6, CCNE1, RB, AURKA and CDKN2A) were associated with lower TILs in RD (p=0.005 and p=0.05, respectively). A significant inverse linear correlation was detected between a transcriptional signature of Ras/MAPK activation (Pratilas et al, PNAS 2009) and TILs in the RD (Spearman's r=−0.42; p=0.00028). Total number of alterations of likely functional significance detected by tNGS showed no association with TILs, suggesting that the association of Ras/MAPK deregulation and cell cycle alterations with TILs may be a pathway-specific effect.
In TNBC cell lines, chemical inhibition of MEK transcriptionally up-regulated MHC-I and MHC-II molecules, while simultaneously down-regulating mRNA expression of the immune checkpoint inhibitor PD-L1 (MDA-231 p=0.00002, BT549 p=0.0003, and SUM159PT p=0.009). In vivo experiments confirming these associations are underway.
Conclusions: The data suggest a strong correlation of Ras/MAPK pathway activation with immune-evasion and outcome in TNBC. With additional mechanistic understanding, rational design of clinical trials combining MEK inhibitors with PD-L1 antibodies in TNBC may be warranted.
Preliminary data for use of tumor membrane-specific HLA-DR expression as a biomarker of response to PD-1/PD-L1 directed therapy.
Goal: To determine the rate of prediction of tumor cells expressing HLA-DR on response to PD-1/PD-L1 directed therapy.
Methods: 12 sections from excisional biopsies or surgical resections of melanoma were immune-stained for HLA-DR (TAL-1B5, commercially available for research from multiple vendors). These 12 sections represented 11 patients; 5 responders to anti-PD-1/PD-L1 therapy and 6 non-responders. Two samples were from sequential biopsies, one from prior to a clinical response, and one upon acquisition of resistance (relapse) on therapy.
Tumor sections were stained overnight at 4 C at a 1:1000 dilution. Antigen retrieval was performed using Citrate Buffer (pH6) using a Biocare Dechloaking Chamber. The Visualization System utilized was Envision-Mouse using DAB chromogen and counterstained with Hematoxylin.
Results: Of 6 non-responders, 0/6 exhibited conclusive tumor-specific membrane staining of HLA-DR (
Conclusion: HLA-DR expression on the tumor seems to be a useful biomarker for prediction of response to PD-1/PD-L1 targeted therapy.
Formalin fixed paraffin embedded melanoma tumor sections were stained with anti-HLA-DR antibody and anti-SOX10 antibody and reviewed by a pathologist for dual positive tumor cells. Two sample sets were stained independently comprising a total of 35 patients. Patients were then classified by their clinical response to targeted immunotherapy, where known. 32 patients were evaluable, with 3 additional considered equivocal due to uncharacteristic features of HLA-DR staining or lack of SOX10 staining in the perceived tumor region (
Melanoma-specific MHC-II expression predicts response to α-PD-1 therapy.
Background. αPD-1 therapy yields objective clinical responses in 30-40% of advanced melanoma (MEL) patients. While promising, many patients do not benefit clinically. As such, predictive biomarkers to guide patient selection are needed. A number of predictive biomarkers have been suggested in the literature, including tumor or immune cell expression of PD-L1, identification of neo-antigens through next generation sequencing techniques, and T-cell receptor sequencing. While quite promising, these assays are technically challenging and require specialized tissue processing or bioinformatics.
Methods. MHC-I/II mRNA was profiled across 60 MEL cell lines. The transcriptional characteristics of MHC-II+ cell lines were analyzed by Gene Set Analysis. Cell surface expression of MHC-I and MHC-II was confirmed by flow cytometry (FC) in a subset of cell lines under basal and stimulated (IFNγ) conditions. In 26 tumor samples from αPD-1 treated MEL patients, immunohistochemistry (IHC) was performed for HLA-DR (MHC-II) or HLA-A (MHC-I), SOX10, CD4 and CD8. IHC results were correlated with response and progression-free survival (PFS).
Results. MHC-I mRNA was expressed in all cell lines while MHC-II expression was bimodal (60% positive). MHC-Ir cell lines had transcriptional signatures of the PD-1 signaling, allograft rejection, and T-cell receptor signaling. By FC, MHC-II+ (mRNA) cell lines were constitutive and inducible (IFNγ stimulation) for HLA-DR while MHC-II− cells did not express or induce HLA-DR. In contrast, all tested cell lines significantly upregulated PD-L1 with IFNγ stimulation. Of 26 patients treated with αPD-1, 10 were MHC-II+. All 10 MHC-II+ (100%) patients had partial, complete, or mixed responses (MR), while only 7/16 (44%) of MHC-II− patients benefited (Fisher's exact p=0.004). Excluding MR patients (n=2), median PFS for MHC-II+ was 728 days, while the median PFS for MHC-II− tumors was 98 days (log-rank p=0.01). MHC-II+ tumors had enhanced CD4 and CD8 infiltrate (Pearson's correlation p=0.000002 and p=0.03, respectively). MHC-I positivity was ubiquitous and not associated with response.
Conclusions. A subset of MEL demonstrates an MHC-II signature that correlates with αPD-1 response and enhanced CD4/CD8 T-cell infiltrate. Without wishing to be bound theory, this is believed to indicate that tumor antigen presentation (MHC-II expression) is a requirement of αPD-1 benefit, and presence of these cell surface markers is predictive benefit. MHC-II+ tumors can be robustly identified by routine melanoma-specific IHC for HLA-DR to guide patient selection. Combining HLA-DR IHC with other biomarkers, including PD-L1 expression may further improve patient selection.
MHC-II+ tumors are enriched with gene expression patterns of adaptive immunity. Melanomas with constitutive tumor cell-autonomous MHC-II/HLA-DR expression are associated with high CD4 and CD8 infiltration and enhanced responses to PD-1-targeted immunotherapy (59, 62), a finding subsequently confirmed by others (61). Furthermore, MHC-II+ melanoma cell lines (grown in the absence of stroma or IFN-γ-expressing cells) demonstrate intrinsic gene expression patterns of inflammation and autoimmunity (59). However, HLA-DR expression by melanoma cells in vivo could be due to membrane exchange (trogocytosis) in an inflammatory milieu (63). To confirm that HLA-DR is endogenously expressed by tumor cells, dual RNA-in situ/IHC analysis for CIITA and HLA-DR, respectively, was performed on melanoma specimens. As shown in
RNA-sequencing analysis was performed on a series of anti-PD-1-treated melanoma and non-small cell lung cancers (n=58, including 50 pre-anti-PD-1 samples and 8 samples obtained after anti-PD-1 following acquired resistance) and scored tumor-specific HLA-DR expression by IHC (HLA-DR staining available on 41 of 58;
To explore the effects of tumor cell-autonomous MHC-II expression on antigen presentation machinery and immune checkpoints, HLA-DR expression was correlated (scored by IHC) with genes associated with MHC-II (HLA-DRA), MHC-I (HLA-A), T cell repression (PD-1/PDCD1, PD-L1/CD274, IDOL TIM-3/HAVCR2, and LAG3), T cell activation (IFNG), monocyte infiltration (CD68), and a ubiquitous marker (TP53) as a control (FIG. 17D). The expression of most immune-related genes were positively correlated with one another. HLA-DR IHC expression, as scored only in the tumor compartment, also correlated with most immune genes, but less strongly with the myeloid marker CD68. Interestingly, all examined immune checkpoint receptor genes also highly correlated with HLA-DR positivity, and the most significant of these was LAG3. These associations were also evident when stratifying tumors by MHC-II+≥5% (
To determine what cell types in the melanoma microenvironment express LAG-3, was performed mass cytometry (CyTOF) on two human patient melanoma resections as well as PBMCs from a healthy individual. viSNE analyses of resected melanomas demonstrated the following observations (
Next, the association between gene expression of checkpoint molecules and ligands with annotated clinical response to anti-PD-1 in these patients was examined. Included in this analysis were 49 pretreatment tumors as well as tumor samples available from patients who initially responded to anti-PD-1 therapy but subsequently progressed (i.e., relapsed) (n=6 patients and n=8 samples, with 3 isolated resections/biopsies from a single patient). When comparing treatment response groups, LAG3 and HAVCR2 (encoding Tim-3) showed differential expression by ANOVA. Of interest, neither LAG3 nor HAVCR2 expression obviously correlated with intrinsic resistance (in responding vs. nonresponding patients), but they were significantly higher in progression (relapse) specimens (i.e., acquired resistance) (
Association of MHC-II expression with inflammation and LAG-3 expression in breast cancer. Tumor cell-autonomous MHC-II expression as an important biomarker in breast cancer was previously identified. MHC-II+ breast tumors were found to have a greater degree of TILs after neoadjuvant chemotherapy, which correlates with improved outcomes after surgical resection (67). Since this series of 112 triple-negative breast cancers (TNBCs) were previously molecularly characterized for MHC-II/HLA-DR expression in the tumor compartment (67), to determine whether a similar association of MHC-II+ tumors with LAG-3+ TILs (
Enforced expression of MHC-II promotes tumor rejection, CD4+ T cell recruitment, and a specific pathway to immune evasion. To better understand the direct role of MHC-II expression on the tumor microenvironment, expression of MHC-II on MMTV-neu breast tumor cells was enforced through transduction of Ciita, the master regulator of MHC-II. Cells transduced with Ciita were strongly IA-IE+ (murine MHC-II), by flow cytometry analysis (
Enforced expression of MHC-II has been shown to result in increased antitumor inflammation, Th1 differentiation, and antigen-specific CD4+ T cells (68-71). Consistent with this, it was found that tumors that did form in the presence of enforced MHC-II had greater fractions of CD4+ T cells (normalized to total TILs), with no change in the regulatory compartment (Foxp3+) (
MHC-II expression promotes the expression of T cell-recruiting chemokines. The mechanism behind recruitment of T cells to the immune microenvironment of MHC-II+ tumors is unclear. However, known T cell chemoattractant cytokines (e.g., Cxcl13, Ccl5) were elevated in MHC-II+ MMTV-neu tumors (
Similar elevation of these markers was present in MHC-II+ melanomas (
A combination of PD-1 and Lag-3 immune checkpoint inhibitor therapy enhances antitumor immunity in MHC-II+ tumors. MMTV-neu tumor cells were utilized transduced to enforce expression of Ciita (or vector control), as above, according to the experimental design shown in
Alternative MHC-II ligands are upregulated in MHC-II+ tumors and promote suppression of effector cell cytotoxicity. MHC-II receptors on lymphocytes may exist with similar functionality to Lag-3. FCRL6 is an immunoreceptor that is structurally related to classical Ig-binding leukocyte Fc receptors but was also shown to be a ligand for MHC-II (74). FCRL6 is an ITIM-bearing Ig superfamily member expressed by cytotoxic NK cells and effector memory CD8+ T cells (75, 76). Thus, FCRL6 may function as a novel immune checkpoint to suppress effector cell activity when engaged with MHC-II. The regulation of NK cell cytotoxicity by MHC class I molecules has been well characterized, but evidence also exists that MHC class II expression can protect target cells from NK cell-mediated killing. Enforced expression of HLA-DR by K562 cells, a classic human erythroleukemic MHC-II-negative target cell line, was found to inhibit lysis by freshly isolated human NK cells in vitro (77). Furthermore, transplantation of K562 cells into NOD/SCID mice followed by adoptive transfer of human PBMCs demonstrated that K562 tumors expressing HLA-DR were dramatically protected from elimination by human NK cells in vivo (78).
Because FCRL6 is downregulated upon exposure to IL-2 or IL-15 (75), using expanded primary human NK or T cell clones was not a feasible approach for studying its function. In order to determine whether FCRL6 inhibits NK cell-mediated killing of HLA-DR-expressing tumor cells, the NK-92 human cytotoxic NK cell line, which does not endogenously express FCRL6 on its surface, was transduced with either FCRL6 or a vector control (
Since mouse FCRL6 differs structurally and functionally from its human relative (79), it is not a viable interspecies translational model for study. To test the hypothesis that the FCRL6/HLA-DR interaction might also inhibit CD8+ T cell responses, the effect of FCRL6 blockade during pathogen-specific peptide stimulation in vitro was examined. This analysis employed an anti-FCRL6 mAb (1D8) that is capable of blocking FCRL6 activation in coculture assays and obstructing FCRL6-Fc binding to HLA-DR transductants (74). Blood mononuclear cells from healthy donors were stimulated with pooled antigenic MHC class I-restricted peptides from CMV, EBV, and influenza virus epitopes (CEF peptide pool) in the presence of anti-FCRL6 or anti-PD-L1 (a positive control). Following a 6-day culture period, cells were collected, restimulated with CEF, and assayed for cytokine production by intracellular staining. A significantly higher frequency of CD8+ T cells produced IFN-γ and TNF-α when cultured with the FCRL6 or PD-L1 mAbs compared with controls (
FCRL6, but not its relative FCRL3, was significantly more highly expressed in MHC-II melanoma and lung cancers (
Table 7 shows the biomarkers in a series of 100 residual TNBCs after neo-adjuvant chemotherapy
There are correlations between CD4+ and CD8+ T-cells which demonstrate that tumor infiltrating lymphocytes are likely composed of CD4+ and CD8+ T-cells.
0.0001
0.002
0.005
0.007
0.0006
0.003
0.15
0.004
0.05
0.005
0.04
0.22
0.04
0.02
0.004
0.0004
0.05
0.09
0.06
0.94
0.04
0.67
0.13
0.84
Univariate analysis for parameters collected by IHC or IF and association (Cox proportional hazards) with RFS and OS. Italicized p-values represent a beneficial association, bolded p-values represent a detrimental association. The paradoxical finding that GZMB+ CD8+ T cells are a negative prognostic factor for long term outcome in NAC-treated TNBC is an intriguing result. Table 8.
0.00902
0.0441
All significant and marginally significant parameters from univariate analyses were used to construct a multivariate model to test independence of variables in predicting RFS. Post-treatment TILs and CD8+ T cells lost significance in the presence of PD-L1, GZMB+CD8+ cells, and CD4+ T cells. Italicized p-values represent a beneficial association, bolded p-values represent a detrimental association. Table 9. In a multivariate analysis, total CD4 cells were a positive predictor of RFS on post-NAC TNBC, while CD8+GZMB+ cells and stromal PD-L1 were negative predictors.
TP53 mutations have distinct chemokine and immune expression signatures.
TP53 mutant mouse breast cancer cells lines induce cytokine expression hollowing doxorubicin treatment.
Doxorubicin induces T cell recruiting chemokines in p53 altered MMTV-Neu cells.
Mined data from the Cancer Genome Atlas (TCGA) showing higher expression of chemokines in human breast tumors with TP53 gene mutations.
All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference, including the references set forth in the following list:
It will be understood that various details of the presently disclosed subject matter can be changed without departing from the scope of the subject matter disclosed herein. Furthermore, the foregoing description is for the purpose of illustration only, and not for the purpose of limitation.
This application U.S. Provisional Application Ser. No. 62/643,599 filed Mar. 15, 2018, the entire disclosures of which are incorporated herein by this reference.
This invention was made with government support under P50 CA98131 awarded by the National Institutes of Health. The government has certain rights in the invention.
| Number | Date | Country | |
|---|---|---|---|
| 62643599 | Mar 2018 | US |
