Methods for selecting subjects and treating cancer with IL-2 therapy

Abstract

Described herein are methods for treating cancer in a subject, the methods comprising administering IL-2 therapy to the subject, whereby a set of markers is up- or down-expressed in a sample from the subject.

Description

[Technical field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims the benefit of priority to U.S. Provisional Patent Application No. 63 / 299,113, filed January 13, 2022, the entire contents of which are incorporated herein by reference for all purposes. [Background technology]

[0002] Distinct populations of T cells regulate the immune system to maintain immune homeostasis and immune tolerance. For example, regulatory T (Treg) cells prevent inappropriate responses by the immune system by preventing pathological autoreactivity, while cytotoxic T cells target and destroy infected and / or cancer cells. In some instances, modulating distinct populations of T cells provides options for the treatment of diseases or indications.

[0003] Cytokines include a family of cell signaling proteins such as chemokines, interferons, interleukins, lymphokines, tumor necrosis factors and other growth factors that play a role in the homeostasis of innate and adaptive immune cells. Cytokines are produced by immune cells such as macrophages, B lymphocytes, T lymphocytes and mast cells, endothelial cells, fibroblasts and different stromal cells. In some instances, cytokines regulate the balance between humoral and cell-based immune responses.

[0004] Interleukins are signaling proteins that regulate the development and differentiation of T and B lymphocytes, cells of the monocytic lineage, neutrophils, basophils, eosinophils, megakaryocytes, and hematopoietic cells. Interleukins are produced by helper CD4+ T and B lymphocytes, monocytes, macrophages, endothelial cells, and other tissue-resident cells.

[0005] Interleukin 2 (IL-2) stimulates the proliferation and survival of T cells and NK cells. In some instances, IL-2 signaling is used to modulate T cell responses and subsequently for the treatment of cancer. Following its discovery, immuno-oncologists recognized the potential of IL-2 to generate “lymphokine-activated killer cells (LAKs),” which were later identified as CD8+ T effector cells and NK cells for cancer therapy. Following the discovery of IL-2 and its use in immuno-oncology, a dramatic increase in the understanding of the tumor and immune microenvironment has occurred. These understandings have led to the development of multiple therapeutic approaches for clinical use, including modulators of T cell responses, including checkpoint inhibitor antibodies, T cell receptor engager and stimulatory antibodies, suppressors of regulatory T cells and myeloid-derived suppressor cells (MDSCs), as well as adoptive cell therapy, virotherapy, vaccines, and TLR agonists. Modulation of PD-1 and CTLA-4 with immune checkpoint inhibitors (ICIs) has resulted in responses in a significant proportion of patients, but there remains a need to better understand the mechanisms that drive resistance to such therapy.

[0006] IL-2 has emerged as a potential agent to overcome such resistance, and several IL-2 drugs are undergoing clinical trials as single agents or in combination with checkpoint inhibitors and other targeted immuno-oncology drugs. Examples include NKTR-214, a form of IL-2 reversibly conjugated with multiple PEG chains; PD1-IL2v, a programmed cell death protein 1 (PD-1) mAb / IL-2v fusion variant; RO6874281, a fusion IL-2 variant; sergituzumab·amnaleukin, a fusion IL-2 variant; RO6874281, a fibroblast activation protein (FAP) mAb / IL-2v fusion protein; sergituzumab·amnaleukin, a carcinoembryonic antigen (CEA) mAb / IL-2v fusion variant; and ALKS-4230, a fusion of IL-2 with the extracellular domain of the α chain of the receptor. Summary of the Invention [Means for solving the problem]

[0007] This disclosure describes pre-treatment tumor molecular analysis, including RNA sequencing (RNAseq), combined with clinical annotation from a single-center retrospective cohort of metastatic RCC patients treated as part of an IL-2 clinical program. Genomic signatures common to and unique to response to both IL-2 and anti-PD-1(L) therapy are provided.

[0008] In one aspect, provided herein is a method for treating cancer in a subject, the method comprising administering IL-2 therapy to the subject, wherein a sample from the subject exhibits a particular profile with respect to an immune marker, a myeloid inflammatory marker, or a typing marker.

[0009] Described herein are methods for treating cancer in a subject, the methods comprising administering IL-2 therapy to the subject, where a set of markers are up- or down-regulated in a sample from the subject. Described herein further are methods for treating cancer in a subject, the methods comprising selecting the subject based, at least in part, on the up- or down-regulation of a set of markers in a sample from the subject, and administering IL-2 therapy to the subject. Described herein further are methods for selecting a subject having cancer for IL-2 therapy, the methods comprising selecting the subject based, at least in part, on the up- or down-regulation of a set of markers in a sample from the subject.

[0010] Exemplary embodiments include the following:

[0011]

[0023] Embodiment 1 is a method for treating cancer in a subject, the method comprising administering IL-2 therapy to the subject, wherein a set of upregulated classification markers are upregulated and / or a set of downregulated classification markers are downregulated in a sample from the subject, the set of upregulated classification markers being TUBA3D, NNMT, MEFV, GZMA, FCGR3B, APOBEC3A, FCN1, FPR2, CD300E, S100A9, LILRA5, ANGPTL4, SDC1, F 5, MUC17, EREG, IL1RN, TREM1, CCL2, CXCL2, GJB2, AQP9, CYP1B1, STEAP3, HP, CP, MAP7D2, PCOLCE2, APOL1, LRRN4CL and KIAA1644, and the set of downregulated classification markers includes at least one of HLF, COL4A4, SLITRK4, SHISA9, IGSF9, TJP3, ZNF853, B4GALNT3 and ATP6V1B1.

[0012]

[0023] Embodiment 2 is a method for treating cancer in a subject, the method comprising determining in a sample from the subject that a set of upregulated classification markers are upregulated and / or a set of downregulated classification markers are downregulated, the set of upregulated classification markers being TUBA3D, NNMT, MEFV, GZMA, FCGR3B, APOBEC3A, FCN1, FPR2, CD300E, S100A9, LILRA5, ANGPTL4, SDC1, F5, MUC17, EREG, IL1RN, TREM1, CCL2, CXCL2 , GJB2, AQP9, CYP1B1, STEAP3, HP, CP, MAP7D2, PCOLCE2, APOL1, LRRN4CL and KIAA1644, and the set of downregulated classification markers includes at least one of HLF, COL4A4, SLITRK4, SHISA9, IGSF9, TJP3, ZNF853, B4GALNT3 and ATP6V1B1; and administering IL-2 therapy to the subject.

[0013]

[0023] Embodiment 3 is a method for selecting a subject having cancer for IL-2 therapy, the method comprising: determining in a sample from the subject that a set of upregulated classification markers are upregulated and / or a set of downregulated classification markers are downregulated, the set of upregulated classification markers being TUBA3D, NNMT, MEFV, GZMA, FCGR3B, APOBEC3A, FCN1, FPR2, CD300E, S100A9, LILRA5, ANGPTL4, SDC1, F5, MUC17, EREG, IL1RN , TREM1, CCL2, CXCL2, GJB2, AQP9, CYP1B1, STEAP3, HP, CP, MAP7D2, PCOLCE2, APOL1, LRRN4CL and KIAA1644, and the set of downregulated classification markers includes at least one of HLF, COL4A4, SLITRK4, SHISA9, IGSF9, TJP3, ZNF853, B4GALNT3 and ATP6V1B1.

[0014] Embodiment 4 is the method of embodiment 3, further comprising obtaining a sample from the subject.

[0015] Embodiment 5 is the method of any one of embodiments 3-4, further comprising extracting RNA from the sample.

[0016] Embodiment 6 is the method of any one of embodiments 3 to 5, further comprising measuring the expression of the set of upregulated classification markers and / or the set of downregulated classification markers in the sample.

[0017] Embodiment 7 is the method of embodiment 6, wherein measuring expression comprises sequencing RNA from the sample, performing RT-qPCR using RNA from the sample, performing microarray analysis of the sample, or performing proteomic analysis of the sample.

[0018] Embodiment 8 is the method of any one of embodiments 1 to 7, wherein the set of upregulated classification markers is upregulated.

[0019] In a ninth embodiment, the set of upregulated classification markers is selected from the group consisting of 1, 2, at least 2, 3, at least 3, 4, at least 4, 5, at least 5, 6, at least 6, 7, at least 7, 8, at least 8, 9, at least 10, 12, or at least 14 of TUBA3D, NNMT, MEFV, GZMA, FCGR3B, APOBEC3A, FCN1, FPR2, CD300E, S100A9, LILRA5, ANGPTL4, SDC1, F5, MUC17, EREG, IL1RN, TREM1, CCL2, CXCL2, GJB2, AQP9, CYP1B1, STEAP3, HP, CP, MAP7D2, PCOLCE2, APOL1, LRRN4CL, and KIAA1644. 9. The method of embodiment 8, comprising at least 9, 10, at least 10, 11, at least 11, 12, at least 12, 13, at least 13, 14, at least 14, 15, at least 15, 16, at least 16, 17, at least 17, 18, at least 18, 19, at least 19, 20, at least 20, 21, at least 21, 22, at least 22, 23, at least 23, 24, at least 24, 25, at least 25, 26, at least 26, 27, at least 27, 28, at least 28, 29, at least 29, 30, at least 30 or 31.

[0020] Embodiment 10 is the method of any one of embodiments 1 to 9, wherein the set of downregulated classification markers is downregulated.

[0021] Embodiment 11 is the method of embodiment 10, wherein the set of downregulated classification markers comprises 1, 2, at least 2, 3, at least 3, 4, at least 4, 5, at least 5, 6, at least 6, 7, at least 7, 8, at least 8, 9 of HLF, COL4A4, SLITRK4, SHISA9, IGSF9, TJP3, ZNF853, B4GALNT3 and ATP6V1B1.

[0022] Embodiment 12 is the method of any one of embodiments 1 to 11, wherein the set of upregulated classification markers comprises at least one of GZMA, CD300E, LILRA5, IL1RN, CCL2 and CXCL2.

[0023] Embodiment 13 is the method of embodiment 12, wherein the set of upregulated classification markers comprises two, at least two, three, at least three, four, at least four, five, at least five, or six of GZMA, CD300E, LILRA5, IL1RN, CCL2, and CXCL2.

[0024] Embodiment 14 is the method of any one of embodiments 1 to 13, wherein the set of upregulated classification markers comprises at least one of FPR2, S100A9, IL1RN, and CCL2.

[0025] Embodiment 15 is the method of embodiment 14, wherein the set of upregulated classification markers comprises two, at least two, three, at least three, or four of FPR2, S100A9, IL1RN, and CCL2.

[0026] Embodiment 16 is a method for treating cancer, the method comprising the steps of: (a) determining whether the set of upregulated classification markers is a first-line treatment for cancer; (b) determining whether the set of upregulated classification markers is a first-line treatment for cancer; and (c) determining whether the set of upregulated classification markers is a first-line treatment for cancer. 16. The method of any one of embodiments 1-15, wherein the set of downregulated classification markers comprises at least X of: LCE2, APOL1, LRRN4CL, and KIAA1644, and the set of downregulated classification markers comprises at least X of: HLF, COL4A4, SLITRK4, SHISA9, IGSF9, TJP3, ZNF853, B4GALNT3, and ATP6V1B1, where X is 2, 3, 4, 5, 6, 7, 8, or 9.

[0027] Embodiment 17 is a method for treating cancer, the method comprising the steps of: determining whether the set of upregulated classification markers is a first step; determining whether the set of upregulated classification markers is a first step; determining whether the set of upregulated classification markers is a second step; determining whether the set of upregulated classification markers is a first step; determining whether the set of upregulated classification markers is a second step; determining whether the set of upregulated classification markers is a third step; determining whether the set of upregulated classification markers is a first step; determining whether the set of upregulated classification markers is a third step; determining whether the set of upregulated classification markers is a third step; determining whether the set of upregulated classification markers is a third step; determining whether the set of upregulated classification markers is a third step; determining whether the set of upregulated classification markers is a third step; determining whether the set of upregulated classification markers is a fourth ... 17. The method of any one of embodiments 1-16, wherein the set of downregulated classification markers comprises at least 2X of CE2, APOL1, LRRN4CL and KIAA1644, and the set of downregulated classification markers comprises at least X of HLF, COL4A4, SLITRK4, SHISA9, IGSF9, TJP3, ZNF853, B4GALNT3 and ATP6V1B1, where X is 2, 3, 4, 5, 6, 7, 8 or 9.

[0028] Embodiment 18 is a method for treating cancer, the method comprising the steps of: (a) determining whether the set of upregulated classification markers is a marker selected from the group consisting of TUBA3D, NNMT, MEFV, GZMA, FCGR3B, APOBEC3A, FCN1, FPR2, CD300E, S100A9, LILRA5, ANGPTL4, SDC1, F5, MUC17, EREG, IL1RN, TREM1, CCL2, CXCL2, GJB2, AQP9, CYP1B1, STEAP3, HP, CP, MAP7D2, PCOL 18. The method of any one of embodiments 1-17, wherein the set of downregulated classification markers comprises at least 3X of CE2, APOL1, LRRN4CL and KIAA1644, and the set of downregulated classification markers comprises at least X of HLF, COL4A4, SLITRK4, SHISA9, IGSF9, TJP3, ZNF853, B4GALNT3 and ATP6V1B1, where X is 2, 3, 4, 5, 6, 7, 8 or 9.

[0029] Embodiment 19 is the method of any one of embodiments 1 to 18, wherein the cancer is renal cancer.

[0030] Embodiment 20 is the method of any one of embodiments 1-19, wherein the cancer is renal cell carcinoma.

[0031] Embodiment 21 is the method of any one of embodiments 1-20, wherein the cancer is renal cell carcinoma of the subtype clear cell B (ccB).

[0032] Embodiment 22 is the method of any one of embodiments 1 to 21, wherein the cancer is metastatic.

[0033] Embodiment 23 is the method of any one of embodiments 1 to 22, wherein the subject has not received any prior IL-2 therapy.

[0034] Embodiment 24 is the method of any one of embodiments 1 to 23, wherein the IL-2 therapy comprises a polypeptide having at least 80%, 85%, 90%, 95%, 96%, 97%, 98%, 99% or 100% sequence identity to SEQ ID NO:1.

[0035] Embodiment 25 is the method of any one of embodiments 1-24, wherein the IL-2 therapy is aldesleukin.

[0036] Embodiment 26 is the method of any one of embodiments 1 to 25, wherein IL-2 therapy is administered to the subject by subcutaneous administration.

[0037] Embodiment 27 is the method of any one of Embodiments 1 to 26, wherein the IL-2 therapy is administered to the subject by intravenous administration.

[0038] Embodiment 28 is the method of any one of embodiments 1 to 27, further comprising refraining from administering a PD-1 targeted therapy or a PD-L1 targeted therapy to the subject.

[0039] Embodiment 29 is the method of any one of embodiments 1 to 28, further comprising refraining from administering a PD-1 targeted therapy to the subject.

[0040] Embodiment 30 is the method of any one of embodiments 1 to 29, wherein the sample comprises tumor tissue.

[0041] Embodiment 31 is the method of any one of embodiments 1 to 30, wherein the sample comprises a primary tumor tissue or a metastatic tumor tissue.

[0042] Embodiment 32 is the method of any one of embodiments 1 to 31, wherein the sample comprises formalin-fixed paraffin embedded (FFPE) tumor tissue.

[0043] Embodiment 33 is the method of any one of embodiments 1 to 32, wherein the sample comprises immune tissue.

[0044] Embodiment 34 is any one of the methods of embodiments 1 to 33, wherein the set of upregulated classification markers is upregulated and / or the set of downregulated classification markers is downregulated according to nearest centroid analysis.

[0045] Embodiment 35 is the method of embodiment 34, wherein the nearest neighbor centroid analysis comprises determining a first distance and a second distance, wherein the first distance is between a sample vector comprising expression values ​​of the set of upregulated and / or the set of downregulated classifier markers and a first reference centroid of the set of upregulated and / or the set of downregulated classifier markers determined from expression values ​​from an IL-2 non-resistant subject, and the second distance is between the sample vector and a second reference centroid determined from expression values ​​of the set of upregulated and / or the set of downregulated classifier markers from an IL-2 refractory subject.

[0046] Embodiment 36 is the method of any one of embodiments 1 to 35, wherein the upregulation and / or downregulation is determined using the log (e.g., log2) median expression value of the set of upregulated and / or downregulated classification markers.

[0047] Embodiment 37 is an IL-2 therapy for use in the method of any one of embodiments 1-36.

[0048] Embodiment 38 is the use of IL-2 therapy for the manufacture of a medicament for the method of any one of embodiments 1 to 36.

[0049] 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 utilized, and the accompanying drawings. [Brief description of the drawings]

[0050] [Figure 1A] A heatmap showing the expression of a set of cell-associated genes (rows) and individual genes (columns) in pre-IL-2 tumors is shown. [Figure 1B] Box plots of cell-associated genes and sets of individual genes in pre-dose tumor samples are shown, with open circles colored by clinical response. [Figure 2A] Heatmap showing expression of 40 markers (rows) in the classifier in pre-IL-2 tumors. [Figure 2B] Box plots of selected markers in pre-dose tumor samples are shown, with open circles colored by clinical response. [Figure 2C] Volcano plot of over-representation analysis of 40 markers and associated gene sets in the classifier. [Figure 3A] 1 shows a Kaplan-Meier plot of TCGA KIRC tumor samples (n=253) based on the 40 marker IL-2 response classifier of Example 2. [Figure 3B] Kaplan-Meier plot of TCGA KIRC tumor samples (n=253) based on canonical intrinsic subtype of RCC (immunohistolytic ccB). [Figure 3C] Kaplan-Meier plots of tumor samples from RCC patients receiving HD-IL-2 (n=36) based on canonical intrinsic subtype of RCC (immunohistotropic ccB) with clinical response comparisons. [Figure 4A]Heatmap showing expression of a set of cell-associated genes and individual genes (columns) in pre-IL-2 tumors (heatmap rows on the left) and anti-PD-1 (heatmap on the right). [Figure 4B] Statistical results for cell-associated genes and individual gene sets comparing pretreatment responding tumors (CR+PR) with non-responding tumors (SD+PD) for IL-2 and anti-PD-1 treated patients are shown. [Figure 4C] Heatmap showing expression of markers (rows) in pre-IL-2 tumors (rows, heatmap on the left) and anti-PD-1 (right) tumors. [Figure 4D] Statistical results for markers comparing pretreatment responding tumors (CR+PR) with non-responding tumors (SD+PD) for IL-2 and anti-PD-1 treated patients are shown. [Figure 4E] Scatter plots showing the relationship between myeloid inflammatory signatures (myeloid) and T cell effector (Teff) signatures for IL-2 and anti-PD-1 pretreated tumors, respectively. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0051] definition 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 the claimed subject matter belongs. It should be understood that the general description above and the detailed description below are exemplary and explanatory only and are not intended to limit any claimed subject matter. To the extent that any material incorporated herein as part of this specification conflicts with the language of this disclosure, the language will control. In this application, the use of the singular includes the plural unless specifically stated otherwise. As used in this specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise. In this application, the use of "or" means "and / or" unless the context requires otherwise. Furthermore, the use of terms such as "including," as well as other forms such as "include," "includes," and "included" are not limiting.

[0052] References herein to "some embodiments," "a embodiment," "one embodiment," or "other embodiments" mean that a particular feature, structure, or characteristic described in connection with an embodiment is included in at least some embodiments, but not necessarily all embodiments of the disclosure.

[0053] As used herein, ranges and amounts may be expressed as "about" a particular value or range. Approximately also includes the exact amount. Thus, "about 5 μL" means "about 5 μL" and "5 μL." In general, terms such as "about" include amounts that are expected to be within experimental error, for example, within 15%, 10%, or 5%.

[0054] The section headings used herein are for organizational purposes only and should not be construed in any way as limiting the subject matter described.

[0055] As used herein, the terms "subject" and "patient" refer to any mammal. In some embodiments, the mammal is a human. In some embodiments, the mammal is a non-human. None of the terms require or are limited to a situation characterized by the supervision (e.g., constant or intermittent) of a medical professional (e.g., a physician, registered nurse, clinical nurse, physician assistant, nursing assistant, or hospice worker).

[0056] As used herein, terms such as "unnatural amino acid" refer to an amino acid other than one of the 20 naturally occurring amino acids. Exemplary unnatural amino acids are described in Young et al., "Beyond the canonical 20 amino acids: expanding the genetic lexicon," J. of Biological Chemistry 285(15):11039-11044 (2010), the disclosure of which is incorporated herein by reference.

[0057] As used herein, "nucleotide" refers to a compound that includes a nucleoside moiety and a phosphate moiety. Exemplary natural nucleotides include adenosine triphosphate (ATP), uridine triphosphate (UTP), cytidine triphosphate (CTP), guanosine triphosphate (GTP), adenosine diphosphate (ADP), uridine diphosphate (UDP), cytidine diphosphate (CDP), guanosine diphosphate (GDP), adenosine monophosphate (AMP), uridine monophosphate (UMP), cytidine monophosphate (CMP) and guanosine monophosphate (GMP), deoxyadenosine triphosphate (dATP), deoxythymidine, cytidine diphosphate (CDP), guanosine diphosphate (GDP), adenosine monophosphate (AMP), uridine monophosphate (UMP), cytidine monophosphate (CMP), and guanosine monophosphate (GMP), deoxyadenosine triphosphate (dATP), deoxythymidine, cytidine diphosphate (CDP), guanosine diphosphate (GDP), cytidine diphosphate (CDP), guanosine diphosphate (GDP), cytidine diphosphate (CDP), guanosine diphosphate (GDP), cytidine diphosphate (CDP), guanosine diphosphate (GDP), cytidine diphosphate (CDP), guanosine diphosphate (GMP), deoxyadenosine triphosphate (dATP), deoxythymidine, cytidine diphosphate (CDP ...cytidine diphosphate (CDP), cytidine diphosphate Deoxyribonucleotides that include, but are not limited to, deoxyribose triphosphate (dTTP), deoxycytidine triphosphate (dCTP), deoxyguanosine triphosphate (dGTP), deoxyadenosine diphosphate (dADP), thymidine diphosphate (dTDP), deoxycytidine diphosphate (dCDP), deoxyguanosine diphosphate (dGDP), deoxyadenosine monophosphate (dAMP), deoxythymidine monophosphate (dTMP), deoxycytidine monophosphate (dCMP), and deoxyguanosine monophosphate (dGMP). Exemplary naturally occurring deoxyribonucleotides that include deoxyribose as the sugar moiety include dATP, dTTP, dCTP, dGTP, dADP, dTDP, dCDP, dGDP, dAMP, dTMP, dCMP, and dGMP. Exemplary naturally occurring ribonucleotides that contain ribose as the sugar moiety include ATP, UTP, CTP, GTP, ADP, UDP, CDP, GDP, AMP, UMP, CMP, and GMP.

[0058] As used herein, "base" and "nucleobase" refer to at least the nucleobase portion of a nucleoside or nucleotide (nucleosides and nucleotides include ribovariants or deoxyribovariants), which may in some cases contain further modifications to the sugar portion of the nucleoside or nucleotide. In some cases, "base" is also used to represent the entire nucleoside or nucleotide (e.g., a "base" may be incorporated into DNA by a DNA polymerase or into RNA by an RNA polymerase). However, terms such as "base" should not be construed as necessarily representing the entire nucleoside or nucleotide unless otherwise required by context. In the chemical structures of bases or nucleobases provided herein, only the base of the nucleoside or nucleotide is shown, and for clarity, the sugar portion and, optionally, any phosphate residues are omitted. As used in the chemical structures of bases or nucleobases provided herein, the wavy line represents the bond to the nucleoside or nucleotide, and the sugar portion of the nucleoside or nucleotide may be further modified. In some embodiments, the wavy line represents the attachment of a base or nucleobase to a sugar moiety, such as a pentose, of a nucleoside or nucleotide. In some embodiments, the pentose is a ribose or deoxyribose.

[0059] In some embodiments, the nucleobase is generally the heterocyclic base portion of a nucleoside. The nucleobase may be naturally occurring, modified, or may not have any similarity to natural bases, and / or may be synthesized, for example, by organic synthesis. In certain embodiments, the nucleobase comprises any atom or group of atoms in a nucleoside or nucleotide that can interact with a base of another nucleic acid, with or without the use of hydrogen bonds. In certain embodiments, the non-natural nucleobase is not derived from a natural nucleobase. It should be noted that non-natural nucleobases do not necessarily have basicity, but are referred to as nucleobases for simplicity. In some embodiments, when referring to a nucleobase, "(d)" indicates that the nucleobase may be bound to deoxyguanosine or ribose, but "d" without parentheses indicates that the nucleobase is bound to deoxyribose.

[0060] As used herein, a "nucleoside" is a compound that includes a nucleobase portion and a sugar portion. Nucleosides include, but are not limited to, naturally occurring nucleosides (found in DNA and RNA), basic nucleosides, modified nucleosides, and nucleosides with mimetic bases and / or sugar groups. Nucleosides include nucleosides that include any of a variety of substituents. Nucleosides can be glycosidic compounds formed by a glycosidic bond between a nucleobase and a reducing group of a sugar.

[0061] As used herein, an "analog" of a chemical structure refers to a chemical structure that retains substantial similarity to the parent structure, even if it is not readily synthetically derived from the parent structure. In some embodiments, a nucleotide analog is a non-natural nucleotide. In some embodiments, a nucleoside analog is a non-natural nucleotide. Related chemical structures that are readily synthetically derived from a parent chemical structure are referred to as "derivatives."

[0062] As used herein, "expression" refers to the RNA or protein levels of a set of markers (i.e., at least one marker). In some embodiments, a marker comprises a single RNA or protein, and in such instances, expression is the RNA or protein level of a single RNA or protein. In some embodiments, a marker comprises a set of RNAs or proteins, and in such instances, expression is the mean or median RNA or protein levels.

[0063] As used herein, "reduced expression" refers to (i) expression of a set of markers (i.e., at least one marker) in a sample from a subject having a median or mean expression value that is lower (e.g., statistically significantly lower) than the expression of the same set of markers in a sample from another subject with cancer for which IL-2 therapy is ineffective, or a statistical threshold (e.g., mean or median value) calculated from a population of samples from subjects with cancer for which IL-2 therapy is ineffective, or (ii) for a set of markers that includes multiple markers, the expression of the set of markers in a sample from a subject is closer to a first reference centroid than to a second reference centroid, where the first reference centroid is determined for a set of markers from an individual or population with cancer for which IL-2 therapy is not ineffective, and the second reference centroid is determined for a set of markers from an individual or population with cancer for which IL-2 therapy is ineffective. In some embodiments, the expression value is the logarithmic (e.g., log2) median expression value. Nearest centroid analysis is described in detail in Dabney, Bioinformatics 21:4148-4154 (2005), doi:10.1093 / bioinformatics / bti681. Briefly, vectors (which may be thought of as sets of n-dimensional coordinates, where n is the number of markers in the set) are formed from each set of gene expression values ​​to be compared, and the vectors formed from the set of markers from individuals or populations with cancers that are not IL-2 refractory and the set of markers from individuals or populations with cancers that are IL-2 refractory are the first and second reference centroids, respectively. When populations are used, the centroids can be vectors of mean or median values. Distances in n-dimensional space from the first and second reference centroids are determined for vectors (sample vectors) formed from the expression of the set of markers in samples from the subject. If the sample vector is closer to the first reference centroid than the second reference centroid, this indicates under-expression. The nearest centroid approach can also be applied to simultaneously determine down-regulation for the first set of markers and up-regulation for the second set of markers using a vector / centroid containing both the first set of markers and the second set of markers.In such a case, if the sample vector is closer to the first reference centroid than to the second reference centroid, it would be indicative of both under-expression of the first set of markers and over-expression of the second set of markers. For each of the methods described and claimed herein, the person performing the method does not need to measure expression of the set of markers in other subjects or other samples from the population. Instead, expression can be obtained by any means, such as from a database.

[0064] As used herein, "upregulated expression" refers to (i) expression of a set of markers (i.e., at least one marker) in a sample from a subject having a median or mean expression value that is higher (e.g., statistically significantly lower) than the expression of the same set of markers in a sample from another subject with cancer for which IL-2 therapy is ineffective, or a statistical threshold (e.g., mean or median value) calculated from a population of samples from subjects with cancer for which IL-2 therapy is ineffective, or (ii) for a set of markers that includes multiple markers, the expression of the set of markers in a sample from a subject is closer to a first reference centroid than to a second reference centroid, where the first reference centroid is determined for a set of markers from an individual or population with cancer for which IL-2 therapy is not ineffective, and the second reference centroid is determined for a set of markers from an individual or population with cancer for which IL-2 therapy is ineffective. In some embodiments, the expression value is the logarithmic (e.g., log2) median expression value. The nearest centroid analysis is as described above. The nearest centroid approach can also be applied using a vector / centroid containing both the first set of markers and the second set of markers to simultaneously determine the under-expression for the first set of markers and the up-expression for the second set of markers. In such a case, if the sample vector is closer to the first reference centroid than the second reference centroid, it would be indicative of both under-expression of the first set of markers and up-expression of the second set of markers. For each of the methods described and claimed herein, the person performing the method does not need to measure the expression of the set of markers in other samples from other subjects. Instead, the expression can be obtained by any means, such as from a database. For each of the methods described and claimed herein, the person performing the method does not need to measure the expression of the set of markers in other samples from other subjects or populations. Instead, the expression can be obtained by any means, such as from a database.

[0065] Conversely, although various features of the invention may be described in the context of a single embodiment, the features may also be provided separately or in any suitable combination. Conversely, although the invention may be described herein for clarity in the context of separate embodiments, the invention may also be implemented in a single embodiment.

[0066] IL-2 Interleukin 2 (IL-2) is a pleiotropic type 1 cytokine whose structure contains a four α-helical bundle of 15.5 kDa. The precursor form of IL-2 is 153 amino acid residues in length, with the first 20 amino acids forming a signal peptide and residues 21-153 forming the mature form. IL-2 is produced primarily by CD4+ T cells after antigen stimulation, and to a lesser extent by CD8+ cells, Natural Killer (NK) and Natural Killer T (NKT) cells, activated dendritic cells (DCs) and mast cells. IL-2 signaling occurs through interaction with a specific combination of IL-2 receptor (IL-2R) subunits, IL-2Rα (also known as CD25), IL-2Rβ (also known as CD122) and IL-2Rγ (also known as CD132). The interaction of IL-2 with IL-2Rα is approximately 10 -8 K of M d The interaction of IL-2 with IL-2Rβ and IL-2Rγ forms a “low affinity” IL-2 receptor complex with approximately 10 -9 K of M d The interaction of IL-2 with all three subunits, IL-2Rα, IL-2Rβ, and IL-2Rγ, is approximately 10 -11 Super M K d The IL-2 receptor forms a "high affinity" IL-2 receptor having the following structure:

[0067] In some instances, IL-2 signaling through the "high affinity" IL-2Rαβγ complex regulates the activation and proliferation of regulatory T cells. Regulatory T cells, or CD4+ CD25 + Foxp3 + Regulatory T (Treg) cells are CD4 + T cells, CD8 + They mediate immune homeostasis by suppressing effector cells such as T cells, B cells, NK cells, and NKT cells. In some instances, Treg cells are generated from the thymus (tTreg cells) or derived from peripheral naive T cells (pTreg cells). In some cases, Treg cells are considered mediators of peripheral tolerance. In fact, one study showed that CD25-depleted peripheral CD4 + The transfer of T cells induced a variety of autoimmune diseases in nude mice, but CD4 + CD25 + Co-transfer of T cells suppressed the development of autoimmunity (Sakaguchi, et al., "Immunologic self-tolerance maintained by activated T cells expressing IL-2 receptor alpha-chains (CD25)," J. Immunol. 155(3):1151-1164 (1995), the disclosure of which is incorporated herein by reference). Increasing the Treg cell population down-regulates the proliferation of effector T cells and suppresses autoimmunity and anti-tumor T cell responses.

[0068] IL-2 signaling through the "intermediate affinity" IL-2Rβγ complex is conserved in the CD8 + Regulates the activation and proliferation of effector T (Teff) cells, NK cells and NKT cells. CD8 + Teff cells (also known as cytotoxic T cells, Tc cells, cytotoxic T lymphocytes, CTLs, T killer cells, cytolytic T cells, Tcon or killer T cells) are T lymphocytes that recognize and kill damaged cells, cancer cells and pathogen-infected cells. NK cells and NKT cells are CD8 + Teff cells are a type of lymphocyte that specifically target cancer cells and pathogen-infected cells.

[0069] In some instances, IL-2 signaling is used to regulate T cell responses and subsequently utilized for the treatment of cancer. For example, IL-2 is administered in high dose form to induce expansion of Teff cell population to treat cancer. However, high dose IL-2 also results in co-stimulation of Treg cells that reduces anti-tumor immune responses. High dose IL-2 induces toxic adverse events mediated by binding of IL-2Rα chain expressing cells of the vasculature, including type 2 innate immune cells (ILC-2), eosinophils and endothelial cells. This results in eosinophilia, capillary leak syndrome and vascular leak syndrome (VLS).

[0070] IL-2 therapy In some embodiments, the IL-2 therapy comprises: [ka] In some embodiments, an IL-2 therapy that can be used in the methods provided herein comprises aldesleukin.

[0071] Methods of treatment and methods for selecting subjects for treatment In some embodiments, provided herein is a method for treating cancer in a subject, the method comprising administering IL-2 therapy to the subject, wherein a set of upregulated classifier markers are upregulated and / or a set of downregulated classifier markers are downregulated in a sample from the subject, the set of upregulated classifier markers being TUBA3D, NNMT, MEFV, GZMA, FCGR3B, APOBEC3A, FCN1, FPR2, CD300E, S100A9, LILRA5, ANGPTL4, S and the set of downregulated classification markers comprises at least one of HLF, COL4A4, SLITRK4, SHISA9, IGSF9, TJP3, ZNF853, B4GALNT3, and ATP6V1B1.

[0072] In some embodiments, provided herein is a method for treating cancer in a subject, the method comprising: detecting in a sample from the subject a set of upregulated classifier markers that are upregulated and / or a set of downregulated classifier markers that are downregulated, the set of upregulated classifier markers being TUBA3D, NNMT, MEFV, GZMA, FCGR3B, APOBEC3A, FCN1, FPR2, CD300E, S100A9, LILRA5, ANGPTL4, SDC1, F5, MUC17, EREG, IL1RN, TREM1, CCL 2, CXCL2, GJB2, AQP9, CYP1B1, STEAP3, HP, CP, MAP7D2, PCOLCE2, APOL1, LRRN4CL, and KIAA1644, and the set of downregulated classification markers includes at least one of HLF, COL4A4, SLITRK4, SHISA9, IGSF9, TJP3, ZNF853, B4GALNT3, and ATP6V1B1; and administering IL-2 therapy to the subject.

[0073] In some embodiments, provided herein is a method for selecting a subject having cancer for IL-2 therapy, the method comprising determining whether a set of upregulated classifier markers are upregulated and / or a set of downregulated classifier markers are downregulated in a sample from the subject, the set of upregulated classifier markers being TUBA3D, NNMT, MEFV, GZMA, FCGR3B, APOBEC3A, FCN1, FPR2, CD300E, S100A9, LILRA5, ANGPTL4, SDC1 , F5, MUC17, EREG, IL1RN, TREM1, CCL2, CXCL2, GJB2, AQP9, CYP1B1, STEAP3, HP, CP, MAP7D2, PCOLCE2, APOL1, LRRN4CL and KIAA1644, and the set of downregulated classification markers includes at least one of HLF, COL4A4, SLITRK4, SHISA9, IGSF9, TJP3, ZNF853, B4GALNT3 and ATP6V1B1.

[0074] In some embodiments, any of the methods provided herein further comprises obtaining a sample from the subject. In some embodiments, the sample comprises tumor tissue. In some embodiments, the sample comprises primary tumor tissue or metastatic tumor tissue. In some embodiments, the sample comprises formalin-fixed paraffin-embedded (FFPE) tumor tissue. In some embodiments, the sample comprises immune tissue.

[0075] In some embodiments, any of the methods provided herein further comprises extracting RNA from the sample. In some embodiments, any of the methods provided herein further comprises extracting DNA from the sample. In some embodiments, extracting RNA from the sample and / or extracting DNA from the sample comprises a dual DNA / RNA extraction.

[0076] In some embodiments, any of the methods provided herein further comprises measuring expression of upregulated and / or downregulated classification markers, in some embodiments, measuring expression comprises performing RNA expression analysis.

[0077] In some embodiments the set of upregulated classification markers is one, at least one, two, at least two, three, at least three, four, at least four, five, at least five, six, at least six, seven, at least seven, eight or more of TUBA3D, NNMT, MEFV, GZMA, FCGR3B, APOBEC3A, FCN1, FPR2, CD300E, S100A9, LILRA5, ANGPTL4, SDC1, F5, MUC17, EREG, IL1RN, TREM1, CCL2, CXCL2, GJB2, AQP9, CYP1B1, STEAP3, HP, CP, MAP7D2, PCOLCE2, APOL1, LRRN4CL, and KIAA1644. , at least 8, 9, at least 9, 10, at least 10, 11, at least 11, 12, at least 12, 13, at least 13, 14, at least 14, 15, at least 15, 16, at least 16, 17, at least 17, 18, at least 18, 19, at least 19, 20, at least 20, 21, at least 21, 22, at least 22, 23, at least 23, 24, at least 24, 25, at least 25, 26, at least 26, 27, at least 27, 28, at least 28, 29, at least 29, 30, at least 30 or 31.

[0078] In some embodiments the set of upregulated classification markers comprises one, at least one, two, at least two, three, at least three, four, at least four, five, at least five, or six of GZMA, CD300E, LILRA5, IL1RN, CCL2 and CXCL2.

[0079] In some embodiments, the set of upregulated classification markers comprises one, at least one, two, at least two, three, at least three, or four of FPR2, S100A9, IL1RN, and CCL2.

[0080] In some embodiments the set of downregulated classification markers includes 1, 2, at least 2, 3, at least 3, 4, at least 4, 5, at least 5, 6, at least 6, 7, at least 7, 8, at least 8, 9 of HLF, COL4A4, SLITRK4, SHISA9, IGSF9, TJP3, ZNF853, B4GALNT3 and ATP6V1B1.

[0081] In some embodiments, the reduced expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 10% lower than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the reduced expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 20% lower than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the reduced expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 30% lower than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the reduced expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 40% lower than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the reduced expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 50% lower than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the reduced expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 60% lower than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the reduced expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 70% lower than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the reduced expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 80% lower than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective.In some embodiments, the reduced expression comprises an expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 90% lower than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the reduced expression comprises an expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 95% lower than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the reduced expression comprises an expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 99% lower than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. For each of the methods provided herein, the person performing the method does not need to measure the expression of the set of markers in other samples from other subjects. Instead, the expression can be obtained by any means, such as by being obtained from a database.

[0082] In some embodiments, elevated expression comprises expression of a set of markers (i.e., at least one marker) in a sample from a subject that is at least 10% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, elevated expression comprises expression of a set of markers (i.e., at least one marker) in a sample from a subject that is at least 20% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, elevated expression comprises expression of a set of markers (i.e., at least one marker) in a sample from a subject that is at least 30% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, elevated expression comprises expression of a set of markers (i.e., at least one marker) in a sample from a subject that is at least 40% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, elevated expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 50% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, elevated expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 60% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, elevated expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 70% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, elevated expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 80% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective.In some embodiments, elevated expression comprises expression of a set of markers (i.e., at least one marker) in a sample from a subject that is at least 90% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, elevated expression comprises expression of a set of markers (i.e., at least one marker) in a sample from a subject that is at least 95% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, elevated expression comprises expression of a set of markers (i.e., at least one marker) in a sample from a subject that is at least 100% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, elevated expression comprises expression of a set of markers (i.e., at least one marker) in a sample from a subject that is at least 200% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the elevated expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 300% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the elevated expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 400% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the elevated expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 500% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the elevated expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 600% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective.In some embodiments, the elevated expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 700% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the elevated expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 800% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the elevated expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 900% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the elevated expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 1,000% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the elevated expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 2,000% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the elevated expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 3,000% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the elevated expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 4,000% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the elevated expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 5,000% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective.In some embodiments, the elevated expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 6,000% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the elevated expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 7,000% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the elevated expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 8,000% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, the elevated expression comprises expression of the set of markers (i.e., at least one marker) in a sample from a subject that is at least 9,000% higher than the expression of the same set of markers in another sample from another subject with cancer for which IL-2 therapy is ineffective. In some embodiments, increased expression comprises expression of a set of markers (i.e., at least one marker) in a sample from a subject that is at least 10,000% higher than the expression of the same set of markers in another sample from another subject with cancer in which IL-2 therapy is ineffective. For each of the methods provided herein, the person performing the method does not need to measure expression of the set of markers in other samples from other subjects. Instead, expression can be obtained by any means, such as from a database.

[0083] In some embodiments, the subject has not received any prior IL-2 therapy. In some embodiments, the subject has received prior IL-2 therapy.

[0084] In some embodiments, the method further comprises refraining from administering a PD-1 targeted therapy (such as an anti-PD-1 antibody, e.g., pembrolizumab, nivolumab, cemiplimab, atezolizumab, dostarlimab, durvalumab, or avelumab) or a PD-L1 targeted therapy (such as an anti-PD-L1 antibody, e.g., atezolizumab, avelumab, or durvalumab) to the subject. In some embodiments, the method further comprises refraining from administering a PD-1 targeted therapy (such as an anti-PD-1 antibody, e.g., pembrolizumab, nivolumab, cemiplimab, atezolizumab, dostarlimab, durvalumab, or avelumab) to the subject. In some embodiments, the method further comprises refraining from administering a PD-L1 targeted therapy (such as an anti-PD-L1 antibody, e.g., atezolizumab, avelumab, or durvalumab) to the subject.

[0085] In some embodiments, provided herein is the use of an IL-2 therapy described herein for any of the methods for treating cancer in a subject or the methods for selecting a subject who has cancer as disclosed herein. In some embodiments, provided herein is the use of an IL-2 therapy described herein for the manufacture of a medicament for any of the methods for treating cancer in a subject or the methods for selecting a subject who has cancer as disclosed herein.

[0086] The embodiments described in the following sections apply to any of the above aspects.

[0087] Type of Cancer In some embodiments, the cancer is renal cancer. In some embodiments, the cancer is renal cell carcinoma. In some embodiments, the cancer is clear cell renal cell carcinoma. In some embodiments, the cancer is non-clear cell renal cell carcinoma. In some embodiments, the non-clear cell renal cell carcinoma is chromophobe renal carcinoma, collecting duct renal cell carcinoma, multilocular cystic renal cell carcinoma, medullary carcinoma, renal mucinous tubular spindle cell carcinoma, or neuroblastoma-associated renal cell carcinoma. In some embodiments, the cancer is transitional cell carcinoma, Wilms tumor, or renal sarcoma. In some embodiments, the cancer is renal cell carcinoma of the subtype clear cell B (ccB). For a description of ccB renal cell carcinoma, see, e.g., Brannon et al., Genes Cancer 1(2):152-163 (2010) (doi:10.1177 / 1947601909359929;<https: / / www.ncbi.nlm.nih.gov / pmc / articles / PMC2943630 / > See the documentation available at

[0088] In some embodiments, the cancer is metastatic.

[0089] Administration 1. Route In some embodiments, IL-2 therapy is administered to the subject by intravenous, subcutaneous, intramuscular, intracerebral, intranasal, intra-arterial, intra-articular, intradermal, intravitreal, intra-osseous, intraperitoneal or intrathecal administration. In some embodiments, IL-2 therapy is administered to the subject by intravenous, subcutaneous or intramuscular administration. In some embodiments, IL-2 therapy is administered to the subject by intravenous administration. In some embodiments, IL-2 therapy is administered to the subject by subcutaneous administration. In some embodiments, IL-2 therapy is administered to the subject by intramuscular administration.

[0090] 2. Schedule and Dosage IL-2 therapy may be administered two or more times, e.g., two, three, four, five or more times. In some embodiments, the administration period is up to 24 months, such as 1 month, 2 months, 3 months, 6 months, 9 months, 12 months, 15 months, 18 months, 21 months, or 24 months. In some embodiments, the administration period is further extended for up to an additional 24 months.

[0091] In some embodiments, IL-2 therapy is administered to a subject in need thereof, for example, about once every 8 hours for 5 days or about 14 doses. This period may be followed by about 9 days without administration of IL-2 therapy. The application cycle may then be repeated, for example, about once every 8 hours for 5 days or 14 infusions. After the second dose set, there may be a rest period of about 7 weeks or more, followed by another administration cycle or a pair of administration cycles.

[0092] In some instances, IL-2 therapy is administered at a dose of 600,000 International Units / kg IV (eg, every 8 hours during the dosing schedule above).

[0093] In some embodiments, about 18 million international units / m 2 100 mg / day IV is administered, for example, by continuous IV infusion over two 5-day cycles. The cycles may be separated by a drug-free period of about 3 to 7 days. After the second cycle, there may be a drug-free period of about 7 weeks or more, followed by another dosing cycle or pair of dosing cycles.

[0094] In some embodiments, from about 1800 International Units / m to about 18 million International Units / m 2 is applied subcutaneously once daily for five days, followed by a two-day rest period. This schedule may be repeated weekly for about six to eight weeks. Therapy may then be resumed after a rest period of about three to four weeks.

[0095] Kit / manufactured product In certain embodiments, kits and articles of manufacture are disclosed herein for use with one or more of the methods and compositions described herein. Such kits include carriers, packages, or containers that are compartmentalized to receive one or more containers, such as vials, tubes, etc., each of which contains one of the separate elements used in the methods described herein. Suitable containers include, for example, bottles, vials, syringes, and test tubes. In one embodiment, the containers are formed from a variety of materials, such as glass or plastic.

[0096] The kit typically includes a label listing the contents and / or instructions for use, and a package insert containing the instructions. A set of instructions is also usually included.

[0097] In one embodiment, the label is on or associated with the container. In one embodiment, the label is on the container when letters, numbers or other characters forming the label are affixed, molded or etched into the container itself, and is associated with the container when present in a receptacle or carrier that also holds the container, e.g., as a package insert. In one embodiment, the label is used to indicate that the contents are to be used for a particular therapeutic application. The label also provides instructions for the use of the contents, such as in the methods described herein.

[0098] In certain embodiments, the pharmaceutical compositions are provided in a pack or dispenser device containing one or more unit dosage forms containing a compound provided herein. For example, the pack contains metal or plastic foil, such as a blister pack. In one embodiment, the pack or dispenser device is accompanied by instructions for administration. In one embodiment, the pack or dispenser device is also accompanied by a notice associated with the container in a form prescribed by a government agency regulating the manufacture, use, or sale of pharmaceuticals. This notice reflects the approval by the agency of the drug form for administration to humans or veterinary animals. Such notice is, for example, a label approved by the U.S. Food and Drug Administration, or an approved product insert. In one embodiment, a composition containing a compound provided herein formulated in a compatible pharmaceutical carrier is also prepared, placed in a suitable container, and labeled for the treatment of an indicated condition. EXAMPLES

[0099] These examples are provided for illustrative purposes only and are not intended to limit the scope of the claims provided herein.

[0100] Example 1. Immune markers in responders to high-dose IL-2 (HD-IL-2) Patient samples Patients were retrospectively identified as having metastatic renal cell carcinoma (mRCC) and received HD-IL-2 (aldesleukin) therapy between December 2009 and August 2013 within the Levine Cancer Institute / Atrium Health hospital system (Charlotte, NC). Eligible patients had available archived pre-treatment formalin-fixed paraffin-embedded (FFPE) tumor tissue samples from primary or metastatic sites that contained sufficient material to extract RNA and DNA. A total of 36 patients met study criteria.

[0101] Table 1 below shows the demographics of the study population, and Table 2 shows the disease outcomes and tumor characteristics of the population.

[0102] In Table 1, the TNM classification of malignant tumors was used to describe the size and location of the tumor using a "T" plus a letter or number (0-4). T1 means the tumor was found only in the kidney and was 7 cm or less at its greatest area. T2 means the tumor was found only in the kidney and was larger than 7 cm at its greatest area. T3 means the tumor grew into a major vein in the kidney or its surrounding tissues, but not into the adrenal gland on the same side of the body as the tumor, and did not spread beyond Gerota's fascia. For primary tumors, NA means that a tumor classification was not available. "N" in the TNM classification means lymph nodes. NX means that the regional lymph nodes could not be evaluated. N0 means that the cancer did not spread to the regional lymph nodes. N1 means that the cancer had spread to the regional lymph nodes. N2 means that the cancer had spread to distant lymph nodes (i.e., lymph nodes in at least one part of the body other than near the kidney). For regional lymph nodes, NA means that a lymph node classification was not available.

[0103] [Table 1]

[0104] [Table 2]

[0105] Clinical annotation Demographics and clinical indices were collected from the medical records and entered into a dedicated auditable database (REDCap; www.project-redcap.org) designed with a predefined data dictionary. Data entry and subsequent quality control (QC) were performed for each individual. Clinical indices were recorded at the initiation of IL-2 therapy, if applicable. HD-IL-2 was administered as a bolus IV injection (720,000 IU / kg) every 8 hours for up to 14 doses, followed by a washout period of 9–14 days, followed by another week of systemic HD-IL-2 (up to 14 doses). Overall survival (OS) was defined as the time from the initiation of IL-2 administration to the patient's death. Whenever possible, the Social Insurance Death Registry was examined when the date of death was not available. Progression-free survival (PFS) from IL-2 administration was defined as the time between the initiation of the first IL-2 administration and disease progression, or the date of death if no disease progression was noted. If patients were still alive or the date of death was unknown, the date of last contact was used instead to estimate censored OS / PFS. Clinical benefit was defined as complete response (CR), partial response (PR), or stable disease (SD). A total of 35 of 36 patients were evaluable for clinical response.

[0106] RNA sequencing Hematoxylin and eosin (H&E) stained FFPE sections underwent microscopic QC review by an anatomic pathologist to confirm histological diagnosis and assess tumor nuclei percentage (required ≥ 5%), necrosis percentage and cell type prior to microdissection and underwent dual DNA / RNA extraction using the truXTRAC FFPE Total Nucleic Acid Kit (Covaris). RNA quantification was performed by Qubit measurement using Ribogreen staining. RNA was qualitatively assessed for integrity by Agilent TapeStation gel electrophoresis. RNA samples approved for analysis (required 200ng by Ribogreen quantification and TapeStation DV200 value ≥ 20%) underwent library preparation using the Agilent SureSelect XT RNA Direct Prep Kit. A no template control (NTC) and a positive control sample (NA12878 FFPE RNA) were included in each experiment. Libraries were captured individually, reviewed for appropriate size using Bioanalyzer or TapeStation traces, and quantified (KAPA library quantification) before equimolar pooling. Sequencing was performed on an Illumina NovaSeq6000 sequencer using an S1 flow cell, generating approximately 50M, 2x100bp paired-end reads. RNA-Seq data was qualified and analyzed against other datasets in the GeneCentric archive. RNA sequencing was successfully performed on 35 of 36 patients.

[0107] RNA expression analysis Expression values ​​for samples were derived from raw RNAseq fastq files. Reads were aligned with the STAR aligner (GrCH38 version 22) against the human assembly using the STAR / Salmon pipeline. Expression was quantified using the RSEM package and the GrCH38 human transcriptome reference. Genes were filtered for minimum expression counts (at least 10 reads in at least 5 samples) and for protein-coding annotation by Ensemble (final set of genes = 16,901). Differential expression was assessed for this filtered set of genes using the DESeq2 package. For all other analyses, all expression values ​​were log2(1+x) transformed, median centered, and top quartile scaled.

[0108] Tumor microenvironment immune activation Examination of immune differences by objective response was performed using previously published immune markers (Charoentong et al., Cell Rep. 18(1):248-262(2017); Bindea et al., Immunity 39(4):782-795(2013)) and proprietary immune markers (Faruki et al., J. Thorac. Oncol. 12(6):943-953(2017)), calculated as the average expression value (arithmetic mean) of all genes in each set of genes. Markers include activated B cells, activated CD4 T cells, activated CD8 T cells, activated dendritic cells, CD56bright natural killer cells, CD56dim natural killer cells, central memory CD4 T cells, central memory CD8 T cells, effector memory CD4 T cells, effector memory CD8 T cells, eosinophils, gamma delta T cells, immature B cells, immature dendritic cells, macrophages, mast cells, MDSCs, memory B cells, monocytes, natural killer cells, natural killer T cells, neutrophils, plasmacytoid dendritic cells, regulatory T cells, T follicular helper cells, type 1 T helper cells, type 17 T helper cells, type 2 T helper cells, IFNgamma, and 40 individual genes: Cd274 (PD-L1 ), Pdcd1 (PD-1), Pdcd1lg2 (PD-L2), Ctla4, IL-2ra, IL-2rb, IL-2rg, Cxcl9, Cxcl10, Ifi27, ​​Ifit1, Ifit2, Ifit3, Mx1, Mx2, Oas2, Stat1, Stat2, Stat3, Stat4, Stat5a (STAT5), Tbx21, Itga1 (CD49A), Itgae (CD103), Cd28, Tnfrsf9 (4-1BB), Cd40, Nfat5 (NFAT), and expression signatures based on type I interferons (Ifna14, Ifna13, Ifna6, Ifna7, Ifna5, Ifna4, Ifna1, Ifna2, Ifna16, Ifnab1, Ifnk, Il6).

[0109] Gene sets and individual genes were represented as heatmaps based on values ​​generated using the log2 median expression values ​​of genes that make up the various immune markers and individual genes. Boxplots showing individual immune activation markers or individual gene expression levels were also generated, and pairwise comparisons were performed using p-values ​​indicated when the p-value of the Wilcoxon rank sum test was less than 0.05. Heatmaps and boxplots were generated using the R program (version 3.5.3). Boxplots showed lower quartile, median and upper quartile expression data. Boxplots showed the complete distribution of expression data.

[0110] statistics OS and PFS analyses were performed using Cox-Proportional Hazard (CPH) models with right-censored endpoints. Associations between response and genomic markers were examined using Kruskal-Wallis and Fisher's exact tests for quantitative and qualitative markers. Associations between response and clinical characteristics were assessed using Fisher's exact test. Multiple logistic regression models were used to test whether molecular subtypes predicted response when adjusted for various genomic markers. All statistical analyses were performed using R3.6 software (http: / / cran.R-project.org).

[0111] Associations between categorical and continuous variables were assessed using t-tests or analysis of variance (ANOVA), depending on the number of categorical variable levels.

[0112] result A select panel of immune markers, including cell-associated genes and sets of individual genes, were evaluated in HD-IL-2 pre-treated tumor specimens. Immune markers were increased in patients responding to IL-2 therapy compared to non-responders. Figure 1A shows a heatmap depicting the expression of a set of cell-associated genes (rows) and individual genes (columns) in IL-2 pre-treated tumors. Values ​​are log2 median expression values. Sample annotation bars represent clinical response. Figure 1B shows a box plot of the set of cell-associated genes and individual genes in pre-treated tumor samples, with open circles colored by clinical response.

[0113] Most tumors associated with clinical benefit (CR, PR, SD) had significantly higher expression levels of most markers (Figures 1 and 4B), suggesting a higher immune infiltration in responding tumors. Elevated levels of immune markers in responding tumors included several associated with immune suppression, such as a set of genes associated with myeloid-derived suppressor cells (MDSCs) (p=0.01), neutrophils (p=0.01), and regulatory T cells (p=0.02). Individual genes such as CD274 (PD-L1) (p=0.04) and CTLA4 (p=0.01), as well as a set of genes associated with effector cell types such as activated CD8+ T cells (p=0.05) and natural killer (NK) cells (p=0.05), were also significantly elevated in responders based on pretreatment tumor samples.

[0114] Example 2. Immune-related gene sets are over-represented in expression classifiers of HD-IL-2 responses. IL-2 dose-response nearest-neighbor centroid classifier To evaluate immune markers in an orthogonal manner and to begin the process of prioritizing genes that may help identify patients likely to respond to IL-2 therapy, the 35 patients from Example 1 with clinical response data and corresponding tumor RNAseq expression profiles were used to develop a nearest centroid classifier for IL-2 therapy response (e.g., clinical benefit (CR / PR vs. SD / PD)). Feature selection of approximately 3,500 maximally expressed, highly varianced genes based on cross-validation identified 40 markers that were suitable for classifying samples. The 40 markers included TUBA3D, NNMT, MEFV, GZMA, FCGR3B, APOBEC3A, FCN1, FPR2, CD300E, S100A9, LILRA5, ANGPTL4, SDC1, F5, MUC17, EREG, IL1RN, TREM1, CCL2, CXCL2, GJB2, AQP9, CYP1B1, STEAP3, HP, CP, MAP7D2, PCOLCE2, APOL1, LRRN4CL, and KIAA1644, HLF, COL4A4, SLITRK4, SHISA9, IGSF9, TJP3, ZNF853, B4GALNT3, and ATP6V1B1.

[0115] result Figure 2A is a heatmap showing expression of 40 markers (rows) in the classifier in IL-2 pre-treated tumors. Values ​​are log2 median expression values. Sample annotation bars represent clinical response. Figure 2B shows box plots of selected markers in pre-treated tumor samples with open circles colored by clinical response. Figure 2C shows a volcano plot of over-representation analysis of the 40 markers and associated gene sets in the classifier.

[0116] Although the number of patients (n=35 with evaluable clinical response data) limited our ability to split samples into training and test sets, the genes driving the classifiers reflected the immune markers observed (Figure 1). In the heatmap in Figure 2A, many markers in the immune-related classifiers were upregulated in samples associated with clinical response, including CXCL2, CD300E, LILRA5, CCL2, and GZMA (selected boxplot, Figure 2B). Over-representation analysis of the 40 markers in the classifier yields a limited set of immune-related genes (Figure 2C). The immune markers and IL-2 response classifiers suggest that patients with clinical response to HD-IL-2 had higher pre-treatment levels of many immune-related genes.

[0117] This classifier was subsequently evaluated in a larger Cancer Genome Atlas (TCGA) cohort of RCC patients undergoing a wide range of treatment modalities, revealing significant differences in survival between classifier-positive and -negative patients. Classifier-positive and -negative patients were identified based on nearest neighbor centroid analysis using the 40 markers shown in Figure 2C, with first and second reference centroids determined from IL-2 non-responsive and IL-2 refractory subpopulations of the set of 35 patients analyzed herein.

[0118] Example 3. Worse overall survival in RCC is based on higher immunoclassification in general, but not in patients receiving HD-IL-2. RCC has historically been notable for its high immune gene signature, which fails to predict clinically favorable outcomes. This includes intrinsic molecular subtypes based on gene expression, but RCC subtypes are characterized by high lymphocytes and macrophages (clear cell B subtype or "ccB") associated with worse overall survival. Furthermore, immune infiltrates associated with poor prognosis have characteristically been associated with immune suppressive cell types such as those reflected by the gene signature (e.g., neutrophils, macrophages, and B cells).

[0119] A 34-gene ccA / ccB renal cell carcinoma (RCC) classifier was developed using The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA KIRC) data (n=380) and the 34-gene list based on Brooks et al., Eur Urol. 66(1):77-84 (2014). Training was performed on ⅔ of the samples and testing on the remaining ⅓. Centroids were fitted directly using the central training set and all available genes.

[0120] result Figure 3A shows Kaplan-Meier plots of TCGA KIRC tumor samples (n=253) based on the 40 marker IL-2 response classifier from Example 2. "Yes" indicates tumor samples classified as patients in the IL-2 cohort with high immune infiltration and better clinical response. Figure 3B shows Kaplan-Meier plots of TCGA KIRC tumor samples (n=253) based on canonical intrinsic subtype of RCC (immune-high ccB). Figure 3C shows Kaplan-Meier plots of tumor samples from RCC patients treated with HD-IL-2 (n=36) based on canonical intrinsic subtype of RCC (immune-high ccB) with clinical response comparison.

[0121] When applying the 34-gene ccA / ccB classifier to RCC patients from TCGA, consistent with the content association of the IL-2 response classifier (trained on 253 randomized samples from TCGA KIRC samples), patients called responders "yes" had a worse overall survival (p=0.05, Figure 3A), which was similar to the worse overall survival in immune subtype ccB patients (p=0.001, Figure 3B). However, surprisingly, from the current study, when applying the ccA / ccB classifier to RCC patients treated with HD-IL-2, the overall survival of ccB subtype patients was not further worse (p=0.7, Figure 3C), and the majority of patients (11 out of 13) with clinical response (CR / PR) were within the ccB subtype (p=0.07). The closure of the survival curves of HD-IL-2 patients and the trend towards clinical response (PR / CR) in a significant number of ccB subtypes could be the result of "IL-2 rescue" of this subtype.

[0122] Thus, by several lines of investigation, the markers identified in this RCC HD-IL-2-treated cohort project poor prognosis and are consistent with the large and extensive RCC literature, but also raise the possibility that IL-2 therapy, such as HD-IL-2, may ameliorate the poor prognostic trajectory of select groups of RCC patients.

[0123] Example 4. Immune checkpoint responders exhibited a distinct immunogenomic profile from IL-2 responders. Higher pretreatment immune infiltration or immune markers, such as PD-L1, have been reported to be associated with response against some tumor types, although for RCC, reports suggest more subtle differences in pretreatment immunogenomic profiles, where specific combinations of signatures or cell types predict either non-response or response.

[0124] To evaluate possible immunogenomic signatures between high PD-(L)1 and HD-IL-2 responders, RNA sequencing data from the anti-PD-1 treated cohort (which has a similar distribution of responses as the HD-IL-2 cohort) was compared to the HD-IL-2 responders. Specifically, a separate dataset of whole transcriptome gene expression and clinical response data from a separate cohort of RCC patients treated with the anti-PD-1 inhibitor nivolumab was evaluated as supplemental data by Miao et al., Science 359(6377):801-806(2018) and compared to the current HD-IL-2 cohort.

[0125] result FIG. 4A is a heatmap showing expression of a set of cell-associated genes and individual genes (columns) in pre-IL-2 (heatmap rows on the left) and anti-PD-1 (heatmap on the right). Values ​​are log2 median expression values. Sample annotation bars represent clinical response. FIG. 4B shows statistical results for a set of cell-associated genes and individual genes comparing pre-responsive (CR+PR) and non-responsive (SD+PD) tumors for IL-2 and anti-PD-1 treated patients. FIG. 4C is a heatmap showing expression of markers (rows) in pre-IL-2 (heatmap rows on the left) and anti-PD-1 (right) tumors. Values ​​are log2 median expression values. Sample annotation bars represent clinical response. Bright blue bars highlight abundance of myeloid inflammatory genes for corresponding tumors. Figure 4D shows statistical results for markers comparing pre-treated responding (CR+PR) and non-responding (SD+PD) tumors for IL-2 and anti-PD-1 treated patients. Figure 4E shows scatter plots showing the relationship between myeloid inflammatory signatures (myeloid) and T cell effector (Teff) signatures for IL-2 and anti-PD-1 pre-treated tumors, respectively.

[0126] In Figure 4A-B, abundance across response categories of the cohort appears similar, but statistical analysis showed different significance and t-statistics. Anti-PD-1 and IL-2 responders shared several effector cell signatures, such as specific CD4 and helper T cell signatures (i.e., central memory CD4 T cells and type 1 T helper cell signatures, respectively). In contrast, we observed notable characteristics, including a signature associated with immune suppressor cell types that was most significantly elevated in HD-IL-2 responders. In addition, increased expression of CD8 T cells (a set of activated CD8 T cell-associated genes) was increased in mRCC patients who responded to HD-IL-2 compared to non-responders, but this was not observed in patients responding to anti-PD-1 administration (Figure 4B).

[0127] To evaluate the anti-PD-(L)1 myeloid signature results in the context of immunosuppressive myeloid markers observed in the HD-IL-2 cohort, markers used in the IMmotion150 Phase II trial (McDermott et al., Nat. Med. 24(6):749-757(2018)) were evaluated in pretreatment RCC specimens from the HD-IL-2 and anti-PD1 cohorts. Figures 4C-4E reflect a similar profile to that reported in the IMmotion150 trial, but the anti-PD-1 treatment cohort responders had lower levels of markers that define the immunosuppressive signature, and were evident in the anti-PD1 cohort. HD-IL-2 partial responders had higher levels of induction of these markers (Figure 4C). The myeloid signature is composed of six markers, but one of the markers, the myeloid chemokine CXCL2, is present among the 40 genes in the response classifier of Example 2. Six markers in the myeloid classifier are primarily chemokines that play a central role in myeloid mobilization. Similarly, markers in the HD-IL-2 response classifier, such as CCL2, FPR2, L1RN, and S100A9, drive gene set enrichment for factors such as myeloid leukocyte migration, neutrophil chemotaxis, and leukocyte chemotaxis. Thus, in addition to the shared CXCL2, these other shared myeloid features were differentially present in anti-PD-(L)1 and IL-2 responders.

[0128] While preferred embodiments of the present invention have been shown and described herein, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Numerous variations, changes, and substitutions will occur to those skilled in the art without departing from the present invention. It will be understood that various alternatives to the embodiments of the present invention described herein may be utilized in carrying out the present invention. It is intended that the following claims define the scope of the present invention, and that methods and structures within the scope of these claims and their equivalents are covered thereby. All disclosures of the patent and scientific literature cited herein are expressly incorporated herein in their entirety as part of this specification.

Claims

1. 1. A method for treating cancer in a subject, the method comprising: administering IL-2 therapy to said subject; A set of upregulated classification markers are upregulated and / or a set of downregulated classification markers are downregulated in the sample from the subject, the set of upregulated classification markers comprising at least one of TUBA3D, NNMT, MEFV, GZMA, FCGR3B, APOBEC3A, FCN1, FPR2, CD300E, S100A9, LILRA5, ANGPTL4, SDC1, F5, MUC17, EREG, IL1RN, TREM1, CCL2, CXCL2, GJB2, AQP9, CYP1B1, STEAP3, HP, CP, MAP7D2, PCOLCE2, APOL1, LRRN4CL and KIAA1644; The set of downregulated classification markers comprises at least one of HLF, COL4A4, SLITRK4, SHISA9, IGSF9, TJP3, ZNF853, B4GALNT3 and ATP6V1B1.

2. 1. A method for treating cancer in a subject, the method comprising: A set of upregulated classification markers are upregulated and / or a set of downregulated classification markers are downregulated in the sample from the subject, the set of upregulated classification markers comprising at least one of TUBA3D, NNMT, MEFV, GZMA, FCGR3B, APOBEC3A, FCN1, FPR2, CD300E, S100A9, LILRA5, ANGPTL4, SDC1, F5, MUC17, EREG, IL1RN, TREM1, CCL2, CXCL2, GJB2, AQP9, CYP1B1, STEAP3, HP, CP, MAP7D2, PCOLCE2, APOL1, LRRN4CL and KIAA1644; selecting the subject based, at least in part, on the set of downregulated classification markers comprising at least one of HLF, COL4A4, SLITRK4, SHISA9, IGSF9, TJP3, ZNF853, B4GALNT3, and ATP6V1B1; administering IL-2 therapy to said subject.

3. 1. A method for selecting a subject having cancer for IL-2 therapy, the method comprising: A set of upregulated classification markers are upregulated and / or a set of downregulated classification markers are downregulated in the sample from the subject, the set of upregulated classification markers comprising at least one of TUBA3D, NNMT, MEFV, GZMA, FCGR3B, APOBEC3A, FCN1, FPR2, CD300E, S100A9, LILRA5, ANGPTL4, SDC1, F5, MUC17, EREG, IL1RN, TREM1, CCL2, CXCL2, GJB2, AQP9, CYP1B1, STEAP3, HP, CP, MAP7D2, PCOLCE2, APOL1, LRRN4CL and KIAA1644; selecting the subject at least in part based on the set of downregulated classification markers comprising at least one of HLF, COL4A4, SLITRK4, SHISA9, IGSF9, TJP3, ZNF853, B4GALNT3 and ATP6V1B1.

4. The method of claim 3, further comprising obtaining a sample from the subject.

5. The method of any one of claims 3 to 4, further comprising extracting RNA from the sample.

6. The method of any one of claims 3 to 5, further comprising measuring the expression of said set of upregulated classification markers and / or said set of downregulated classification markers in said sample.

7. 7. The method of claim 6, wherein the measuring of expression comprises sequencing RNA from the sample, performing RT-qPCR with RNA from the sample, performing microarray analysis of the sample, or performing proteomic analysis of the sample.

8. The method of any one of claims 1 to 7, wherein the set of upregulated classification markers is upregulated.

9. The set of upregulated classification markers is selected from the group consisting of 1, 2, at least 2, 3, at least 3, 4, at least 4, 5, at least 5, 6, at least 6, 7, at least 7, 8, at least 8, 9, at least 10, 12, 14, 16, 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, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 1 9, 10, at least 10, 11, at least 11, 12, at least 12, 13, at least 13, 14, at least 14, 15, at least 15, 16, at least 16, 17, at least 17, 18, at least 18, 19, at least 19, 20, at least 20, 21, at least 21, 22, at least 22, 23, at least 23, 24, at least 24, 25, at least 25, 26, at least 26, 27, at least 27, 28, at least 28, 29, at least 29, 30, at least 30 or 31.

10. The method of any one of claims 1 to 9, wherein the set of downregulated classification markers is under-expressed.

11. 11. The method of claim 10, wherein the set of downregulated classification markers comprises 1, 2, at least 2, 3, at least 3, 4, at least 4, 5, at least 5, 6, at least 6, 7, at least 7, 8, at least 8, or 9 of HLF, COL4A4, SLITRK4, SHISA9, IGSF9, TJP3, ZNF853, B4GALNT3, and ATP6V1B1.

12. The method of any one of claims 1 to 11, wherein the set of upregulated classification markers comprises at least one of GZMA, CD300E, LILRA5, IL1RN, CCL2 and CXCL2.

13. 13. The method of claim 12, wherein the set of upregulated classification markers comprises two, at least two, three, at least three, four, at least four, five, at least five, or six of GZMA, CD300E, LILRA5, IL1RN, CCL2, and CXCL2.

14. The method of any one of claims 1 to 13, wherein the set of upregulated classification markers comprises at least one of FPR2, S100A9, IL1RN and CCL2.

15. 15. The method of claim 14, wherein the set of upregulated classification markers comprises two, at least two, three, at least three, or four of FPR2, S100A9, IL1RN, and CCL2.

16. The set of upregulated classification markers is selected from the group consisting of TUBA3D, NNMT, MEFV, GZMA, FCGR3B, APOBEC3A, FCN1, FPR2, CD300E, S100A9, LILRA5, ANGPTL4, SDC1, F5, MUC17, EREG, IL1RN, TREM1, CCL2, CXCL2, GJB2, AQP9, CYP1B1, STEAP3, HP, CP, MAP7D2, PCOLC 16. The method of any one of claims 1 to 15, wherein the set of downregulated classification markers comprises at least X of the following: HLF, COL4A4, SLITRK4, SHISA9, IGSF9, TJP3, ZNF853, B4GALNT3 and ATP6V1B1, where X is 2, 3, 4, 5, 6, 7, 8 or 9.

17. The set of upregulated classification markers are: TUBA3D, NNMT, MEFV, GZMA, FCGR3B, APOBEC3A, FCN1, FPR2, CD300E, S100A9, LILRA5, ANGPTL4, SDC1, F5, MUC17, EREG, IL1RN, TREM1, CCL2, CXCL2, GJB2, AQP9, CYP1B1, STEAP3, HP, CP, MAP7D2, PCOLCE 2, APOL1, LRRN4CL and KIAA1644, and the set of downregulated classification markers comprises at least X of HLF, COL4A4, SLITRK4, SHISA9, IGSF9, TJP3, ZNF853, B4GALNT3 and ATP6V1B1, where X is 2, 3, 4, 5, 6, 7, 8 or 9.

18. The set of upregulated classification markers are: TUBA3D, NNMT, MEFV, GZMA, FCGR3B, APOBEC3A, FCN1, FPR2, CD300E, S100A9, LILRA5, ANGPTL4, SDC1, F5, MUC17, EREG, IL1RN, TREM1, CCL2, CXCL2, GJB2, AQP9, CYP1B1, STEAP3, HP, CP, MAP7D2, PCOLCE 2, APOL1, LRRN4CL and KIAA1644, and the set of downregulated classification markers comprises at least X of HLF, COL4A4, SLITRK4, SHISA9, IGSF9, TJP3, ZNF853, B4GALNT3 and ATP6V1B1, where X is 2, 3, 4, 5, 6, 7, 8 or 9.

19. The method of any one of claims 1 to 18, wherein the cancer is renal cancer.

20. The method of any one of claims 1 to 19, wherein the cancer is renal cell carcinoma.

21. The method of any one of claims 1 to 20, wherein the cancer is renal cell carcinoma of the subtype clear cell B (ccB).

22. The method of any one of claims 1 to 21, wherein the cancer is metastatic.

23. The method of any one of claims 1 to 22, wherein the subject has not received any prior IL-2 therapy.

24. 24. The method of any one of claims 1 to 23, wherein the IL-2 therapy comprises a polypeptide having at least 80%, 85%, 90%, 95%, 96%, 97%, 98%, 99% or 100% sequence identity to SEQ ID NO:

1.

25. The method of any one of claims 1 to 24, wherein the IL-2 therapy comprises aldesleukin.

26. The method of any one of claims 1 to 25, wherein the IL-2 therapy is administered to the subject by subcutaneous administration.

27. The method of any one of claims 1 to 26, wherein the IL-2 therapy is administered to the subject by intravenous administration.

28. The method of any one of claims 1 to 27, further comprising refraining from administering a PD-1 targeted therapy or a PD-L1 targeted therapy to the subject.

29. 29. The method of any one of claims 1 to 28, further comprising withholding PD-1 targeted therapy from the subject.

30. The method of any one of claims 1 to 29, wherein the sample comprises tumor tissue.

31. The method of any one of claims 1 to 30, wherein the sample comprises primary tumor tissue or metastatic tumor tissue.

32. The method of any one of claims 1 to 31, wherein the sample comprises formalin-fixed paraffin-embedded (FFPE) tumor tissue.

33. The method of any one of claims 1 to 32, wherein the sample comprises immune tissue.

34. The method of any one of claims 1 to 33, wherein the set of upregulated classification markers is upregulated and / or the set of downregulated classification markers is downregulated according to a nearest centroid analysis.

35. 35. The method of claim 34, wherein said nearest neighbor centroid analysis comprises determining a first distance and a second distance, wherein said first distance is between a sample vector comprising expression values ​​of the set of upregulated and / or the set of downregulated classifier markers and a first reference centroid of the set of upregulated and / or the set of downregulated classifier markers determined from expression values ​​from IL-2 non-refractory subjects, and said second distance is between said sample vector and a second reference centroid determined from expression values ​​of the set of upregulated and / or the set of downregulated classifier markers from IL-2 refractory subjects.

36. 36. The method of any one of claims 1 to 35, wherein up- and / or down-expression is determined using the logarithmic (e.g. log2) median expression value of the set of upregulated and / or the set of downregulated classifier markers.

37. IL-2 therapy for use in the method of any one of claims 1 to 36.

38. Use of IL-2 therapy for the manufacture of a medicament for the method according to any one of claims 1 to 36.

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