WO2015081067A2 - Metastatic melanoma biomarkers - Google Patents

Abstract

The invention provides, inter alia, methods that are diagnostic and/or prognostic for cancer, particularly metastatic cancer, more particularly metastatic melanoma. These methods entail measuring the expression levels of immunokines— such as ILla, IL1 β, IL4, IL5, IL6, IL10, IL12, IL13, IL8, CCL3, CCL4, CCL5, CCL1 1, CCL17, CCL22, CXCL9, and CCXCL10— in a biological sample from a subject. Related kits, systems and methods of treatment are also provided.

Description

METASTATIC MELANOMA BIOMARKERS RELATED APPLICATION(S)

[0001] This application claims the benefit of U.S. Provisional Application No. 61/909,023, filed on November 26, 2013. The entire teachings of the above application(s) are incorporated herein by reference.

GOVERNMENT SUPPORT

[0002] This invention was made with government support under R56AI085131 from the National Institute of Allergy and Infectious Diseases. The government has certain rights in the invention.

BACKGROUND OF THE INVENTION

[0003] The ability of melanoma to successfully metastasize to the brain, like malignant tumors elsewhere, depends on the complex tumor microenvironment they establish to facilitate their survival and progression. Genetic abnormalities within the melanoma cells themselves, such as AKT over-expression and BRAF,p53, CDKN2A, and PTEN mutations, as well as epigenetic silencing, are thought to promote cellular transformation. However, melanoma metastases require the additional interplay between the cancer cells and stromal cells, together with the presence of various elements within the tissue environment that they invade, for successful tumor translocation, extravasation, survival, and proliferation. A key requirement for the subversion of normal cells and tissue within the metastatic site involves the recruitment of myofibroblasts, innate and adaptive immune cells. Many of these cell types are of bone marrow origin and may be recruited to tumors in response to cytokine and chemokine production by the melanoma, stromal cells or both. In turn, these newly recruited cells also secrete immunokines that attract additional cells and/or modulate the activity of cells within the tumor.

[0004] Traditionally, the cerebrospinal fluid (CSF) has been thought to merely maintain the homeostatic environment required for normal functions of the brain. In addition to providing a homeostatic environment, the CSF also provides a conduit for transmitting signals during neurodevelopment and progression of primary and metastatic brain tumors. Therefore, given the potential importance of immune signaling in modulating the function of metastatic melanoma of the brain, and the immense personal and economic toll of melanoma for patients, their support system, and society at large, a need exists for improved methods of detecting and/or classifying cancer, such as melanoma. Preferably, such methods should be minimally invasive and use readily obtainable biological samples, such as a sample containing CSF.

SUMMARY OF THE INVENTION

[0005] The invention provides, inter alia, methods of detecting and/or classifying cancer, such as melanoma. The methods provided by the invention are relatively simple and minimally invasive, using biological samples containing CSF.

[0006] Accordingly, in a first aspect, the invention provides methods of detecting and/or classifying cancer (such as a cancer localized to the brain, or that has metastasized to the brain, such as metastatic melanoma) in a mammalian subject. These methods entail measuring the expression levels of two or more immunokines in an isolated biological sample from the subject, where the biological sample comprises cerebrospinal fluid, comparing the measured expression levels of the two or more immunokines to suitable controls and determining the presence of cancer, or classifying the cancer, on the basis of the comparison, where the two or more immunokines are selected from ILla, ILlp, IL4, IL5, IL6, IL10, IL12, IL13, IL8, CCL3, CCL4, CCL5, CCL11 , CCL17, CCL22, CXCL9, and CCXCL10, and expression levels of the two or more immunokines differ between a cancer sample and a non- cancer sample.

[0007] In some embodiments, elevated expression levels of ILip and, optionally, globally reduced immunokine expression levels classifies the subject in cluster 1, while elevated expression levels of IL1 β and reduced expression levels of IL1 β classifies the subject in cluster 2. In certain embodiments, elevated expression levels of 1, 2, or all 3 of CXCL10, CCL4, and CCL17; and reduced expression levels of IL1 β classifies the subject in cluster 3, optionally wherein the subject exhibits reduced expression levels of 1, 2, 3, or all 4 of ILla, IL4, IL5, and CCL22, further optionally wherein the subject further exhibits elevated expression levels of CCL3 and/or reduced levels of IL12. In some embodiments, elevated expression levels of CCL17 and reduced expression levels of IL1 β and/or IL6 classifies the subject in cluster 4, optionally wherein the subject further exhibits reduced expression levels 1, 2, 3, or all 4 of ILla, IL4, IL5, and CCL22. In certain embodiments, elevated expression levels of 1, 2, 3, or all 4 of CCL3, CCL5, IL10 and IL13 and reduced expression levels of ILip classifies the subject in cluster 5.

[0008] In another aspect the invention provides methods of detecting metastatic melanoma in a human subject. These methods entail measuring the protein expression levels of the immunokines CXCL10, CCL4, CCL17, IL8, CCL22, ILla, IL4, and IL5 in an isolated biological sample from the subject, where the biological sample comprises cerebrospinal fluid, comparing the measured expression levels of the immunokines to suitable controls and determining the presence of metastatic melanoma, or classifying the metastatic melanoma, on the basis of the comparison, where elevated protein expression levels of one or more of CXCL10, CCL4, CCL17, and IL8; and/or reduced protein levels of one or more of CCL22, ILla, IL4, and IL5 indicate the presence of metastatic melanoma.

[0009] In another aspect, the invention provides kits for performing the methods of any one of the methods provided by the invention. In some embodiments, the kit comprises reagents for detecting the expression levels of two or more immunokines, and optionally further including, e.g. , positive and/or negative controls.

[0010] In yet another aspect, the invention provides a method of treating cancer (such as a localized brain cancer or a cancer metastasized to the brain, such as metastatic melanoma) in a subject by providing a suitable treatment to the subject on the basis of the diagnosis or classification by any one of the methods provided by the invention.

[0011] In a further aspect, the invention provides non-transient computer-readable media. The media contain instructions that, if executed by a processor, cause the processor to perform steps including accepting data representing the levels of two or more immunokines in an isolated biological sample from the subject, wherein the biological sample comprises cerebrospinal fluid, comparing the measured levels of the two or more immunokines to suitable controls, and determining the presence of cancer, or classifying the cancer, on the basis of the comparison, where the two or more immunokines are selected from ILla, ILip, IL4, IL5, IL6, IL10, IL12, IL13, IL8, CCL3, CCL4, CCL5, CCL11, CCL17, CCL22, CXCL9, and CCXCL10. The invention also provides systems comprising these media and a processor, as well as methods of performing the methods provided by the invention on the system.

[0012] Described herein is the first study showing a global immune suppression in the brain as a result of melanoma and melanoma metastasis and that by analyzing patient CSF diagnostic and prognostic information can be determined.

[0013] As a result of the invention described herein, and in particular, by measuring and evaluating the expression levels of the immunokines in a patient's CSF sample, courses of therapy/ therapeutic interventions can be more accurately defined. For example, if a patient presents with symptoms consistent with a brain tumor, a healthcare provider can perform the CSF analysis described herein and determine whether melanoma is present in the brain without performing a biopsy. This provides a significant diagnostic advantage in that such a

determination of melanoma in the brain can be made without biopsy, especially if the suspicious tumor is present in an area inaccessible for biopsy such as the spinal cord or brain stem.

Sampling of the CSF can also be performed at multiple time points to permit real-time reassessment and re-evaluation of tumor status in a minimally invasive fashion. Based on the analysis of expression levels of the immunokines in the CSF sample performed as described herein, the healthcare provider may determine that, for example, a brain scan or invasive biopsy should be performed on the patient.

[0014] Moreover, the analysis of expression levels of immunokines described herein can be predictive of outcome of the selected therapy or therapeutic treatment and, therefore, provides a means of personalized or individualized treatment. For example, certain clusters, as described here, would be more appropriately matched to certain therapies. Certain biologies would be selected for treatment over other forms of drug therapy, or vice-versa. Alternatively, palliative care might be more appropriate over further treatment.

BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.

[0016] The foregoing will be apparent from the following more particular description of example embodiments of the invention, as illustrated in the accompanying drawings in which like reference characters refer to the same parts throughout the different views. The drawings are not necessarily to scale, emphasis instead being placed upon illustrating embodiments of the present invention.

[0017] FIGs. 1A-1B are scatter plots illustrating that Breslow depth correlates with melanoma aggressiveness in patient set. FIG. 1 A depicts Breslow depth versus time from diagnosis to brain metastasis. FIG. IB depicts Breslow depth versus overall survival (time from diagnosis to death).

[0018] FIG.s 2A-2D are graphs and micrographs of cytokine levels showing that, inter alia, CXCLIO in the CSF is tumor derived. In FIG. 2A, both CXCLIO and IL8 were significantly up- regulated in melanoma CSF, while in FIG. 2B, ILla, ILlp, IL4, IL5, IL13, CCL1 1 , CCL22 and CXCL9 were suppressed. P values were derived from the Wilcoxon rank sum test. In FIG. 2C, measurement of C-reactive protein, a highly abundant serum protein not normally found in the CSF, showed 100-fold lower levels in both control and melanoma CSF samples compared to a reference non-disease serum sample, suggesting the absence of significant leak between these two compartments. The reference non-disease serum was 3.70

while the control CSF had a median CRP of 0.00 [95%CI 0.00-0.01] μ^πύ and melanoma CSF had a median CRP of 0.01

[95%CI 0.00-0.01] μ^πύ (P=0.3179). In FIG. 2D, immunohistochemistry for CXCL10 was performed on primary tumor sections of patient M3 showing staining in the parenchyma of the tumor but not in tumor infiltrating lymphocytes. Right panel showed no primary control. Scale bar = 100 μπι.

[0019] FIGs. 3 A-3B are dendrograms and heat maps illustrating that melanoma brain metastasis results in immunological reconfiguration in the CNS. FIG. 3 A shows unsupervised hierarchical clustering and heat map analysis of 17 relevant immunokines. The melanoma and control CSF samples were separated distinctly from each other. Significant suppression of ILl a, IL4, IL5 and CCL22 were noted in nearly all melanoma CSF samples but not in controls (Group A). Immunokines CCL4, CXCL10 and CCL17 seemed to aggregate together in the clustergram (Group B) and both CCL3 and IL8 chemokines also appeared to cluster near them. Patients clustered into five distinct groups (clusters 1-5) based on their immunokine patterns. Prior to CSF was sampled, patients M3, M9, Mi l , M12, M14, M15, M16, M17 and M21 received dexamethasone while all had immunotherapy except for M5, M6, M7, M14, M19 and M22. In FIG. 3B, K-Mean dendrogram analysis showed distinct separation of melanoma and control CSF samples. K-Means hierarchical cluster analysis was performed using R to validate the initial cluster analysis performed using the MATLAB Bioinformatics Toolbox. Ward's method was used to compute the linkage between clusters and a dendrogram of the results was created.

DETAILED DESCRIPTION OF THE INVENTION

[0020] The invention provides, inter alia, methods that are diagnostic and/or prognostic for cancer, particularly metastatic cancer, more particularly metastatic melanoma. These methods entail measuring the expression levels of immunokines in a biological sample from a subject, where the biological sample contains cerebrospinal fluid (CSF), and comparing the immunokine levels to suitable controls to determine the presence and/or classification of the cancer.

[0021 ] "Immunokine" encompasses both cytokines and chemokines. Cytokines are exemplified by, for example, ILla, ILl p, IL2, IL4, IL5, IL6, IL8, IL 10, IL12, IL13, IFN-γ, and tumor necrosis factor-alpha (TNF-a). "Chemokines" are cytokines that stimulate chemotaxis in responsive cells and are typically shorter cytokines that have a particular four cysteine topology. Exemplary chemokines include CCL2 (Monocyte Chemotactic Protein 1, MCP1), CCL3 (Macrophage Inflammatory Protein la, MlPla), CCL4 (Macrophage Inflammatory Protein 1β, ΜΙΡΙ β), CCL5 (Regulated upon Activation, Normal T-cell Expressed and Secreted, RANTES), CCL1 1 (Eotaxin), CCL17 (Thymus and Activation Regulated Chemokine, TARC), CCL22 (Macrophage Derived Chemokine, MDC), CCL23 (Myeloid Progenitor Inhibitory Factor 1, MPIF1), CXCL1 (Growth Regulated Oncogene a, GROa), CXCL5 (Epithelial Neutrophil Activating peptide 78), CXCL9 (Monokine Induced by Gamma interferon, MIGl), and CXCLI O (Induced Protein 10, IP- 10).

[0022] In some embodiments, particular immunokines relevant to the invention are described in Table A. Table A, below, provides NCBI human genelDs and RefSeq mRNA and protein sequences for these immunokines. Where multiple isoforms of the RefSeqs are available, isoform 1 is presented as an example. These identifiers may be used to retrieve, inter alia, publicly-available annotated mRNA or protein sequences from sources such as the NCBI website, which may be found at the following uniform resource locator (URL):

//www.ncbi.nlm.nih.gov. The information associated with these identifiers, including reference sequences and their associated annotations, are all incorporated by reference. Additional useful tools for converting IDs or obtaining additional information on a gene are known in the art and include, for example, DAVID, Clone/GenelD converter and SNAD. See Huang et al, Nature Protoc. 4(l):44-57 (2009), Huang et al, Nucleic Acids Res. 37(1): 1-13 (2009), Alibes et al, BMC Bioinformatics 8:9 (2007), and Sidorov et al., BMC Bioinformatics 10:251 (2009).

Table A

Analysis

[0023] "Measuring" an expression level, such as of an immunokine, requires contacting a sample with isolated analytic tools that are a product of man, such as laboratory equipment for measuring the level, and, in certain embodiments, additional isolated reagents, such as isolated oligonucleotides, microarrays, sequencing reagents (such as cloned enzymes, detectably labeled dNTPs, et cetera), antibodies (including antigen-binding fragments thereof, including recombinantly-produced antibodies or antigen-binding fragments thereof; optionally where the antibody or antigen-binding fragment thereof is detectably labeled) to measure the level of a gene expression product by an analytical laboratory method. In particular embodiments, the reagents (such as antibodies or nucleic acids, such as synthetic oligonucleotides) are artificially and/or detectably labeled— i.e. , the reagents are products of man that do not exist in nature. Measuring a level of a gene expression product may be done directly in the course of the analytical laboratory methods or, in some embodiments, by evaluating the quantitative output of the analytical laboratory methods. Accordingly, in another aspect, the invention provides isolated analytes (i.e. , immunokine gene expression products, such as those described in Table A), such as a panel of analytes (e.g. , combinations and subcombinations of those described in Table A) in association with analytical tools (e.g. , antibodies, nucleic acids, or laboratory equipment).

[0024] "Level of expression," "expression level," "gene expression level" and the like, refers to the amount of a gene expression product (e.g., mR A or protein). Expression levels can be absolute measures and may be optionally normalized by any means (e.g. , as percentage of maximal values, mean/variance normalized), or transformed by any means (e.g. , log

transformed, using any suitable base, e.g. , base 2, base 10, base e).

[0025] "Gene expression product" encompasses both nucleic acid (e.g., mRNA or cDNA derived from it) and protein products of expression of a gene, such as an immunokine. Nucleic acid expression products may or may not include subsequences that do not encode and/or get translated into protein. Gene expression product encompass both full-length, naturally occurring molecules, as well as fragments thereof, provided the fragments permit identification of the gene expression product, relative to other molecules expected to be present in the sample being analyzed.

[0026] A "panel" of immunokine expression levels refers to a combination or

subcombination of two or more immunokine expression levels— such as combinations of the immunokines in Table A.

[0027] A "suitable control" includes, for example, reference values previously compiled from samples determined— by any means— to be in a given state— e.g. , cancerous or noncancerous. For example, reference values for one or more immunokines can be compiled and used to develop a binary or probabilistic classification algorithm that is then used to diagnose or classify cancer based on a sample, and the use of such classification algorithms therefore entails comparison to suitable controls. Exemplary controls (both positive and negative) for melanoma, and levels thereof, are provided in Table 2. Levels substantially similar to those in Table 2, as assessed by, e.g. , the mean, median, or ranges of those in Table 2, can be used as well.

Substantially similar levels to those in Table 2 can be within (i.e. , higher or lower) about: 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35 percent, or more; e.g. , about 1.5, 2.0, 2.5, or 3.0-fold, or more, of the values in Table 2. Comparison to controls can also, in some embodiments, entail clustering or other classification algorithms, e.g. , to classify the sample as cancerous or noncancerous, or more particularly, for example, in one of the clusters described in the Examples. Expression levels (e.g. , for one or more immunokines) can be evaluated and classified by a variety of means such as general linear model (GLM), ANOVA, regression (including logistic regression), support vector machines (SVM), linear discriminant analysis (LDA), principal component analysis (PCA), k-nearest neighbor (k N), neural network (NN), nearest

mean/centroid (NM), and baysian covariate predictor (BCP). A classification model can be developed using any of the subsets and combinations of immunokines described herein based on the teachings of the invention. Suitable cutoffs for evaluating an immunokine expression levels, such as a panel, (e.g., for classification as abnormal (cancer or high risk) or normal (non-cancer or low risk)) can be determined using routine methods, such as ROC (receiver operating characteristic) analysis, and may be adjusted to achieve the desired sensitivity (e.g. , at least about 50, 52, 55, 57, 60, 62, 65, 67, 70, 72, 75, 77, 80, 82, 85, 87, 90, 92, 95, 97, or 99% sensitivity) and specificity (e.g. , at least about 50, 52, 55, 57, 60, 62, 65, 67, 70, 72, 75, 77, 80, 82, 85, 87, 90, 92, 95, 97, or 99% specificity).

[0028] A difference (e.g., an increase or a decrease) in the expression level of an

immunokine, or panel of immunokines, in the sample relative to the corresponding control level is indicative of the patient having a cancer, such as metastatic melanoma. As used herein, "difference" refers to any difference— either statistically significant and/or practically

significant— in the level of a given immunokine, or panel of immunokines, in a test sample relative to the expression level of the same immunokine in a suitable control.

[0029] Classification of cancer, such as metastatic melanoma can, in some embodiments, be substantially as described in the Exemplification. For example, elevated expression levels of IL1 β and, optionally, globally reduced immunokine expression levels classifies the subject in cluster 1. In more particular embodiments, both elevated expression levels of IL1 β and globally reduced immunokine expression levels classifies the subject in cluster 1. In some embodiments, elevated expression levels of IL1 β and reduced expression levels of IL1 β classifies the subject in cluster 2. In certain embodiments, elevated expression levels of 1 , 2, or all 3 of CXCLI O, CCL4, and CCL17; and reduced expression levels of IL1 β classifies the subject in cluster 3, while optionally, the subject can exhibit reduced expression levels of 1 , 2, 3, or all 4 of ILl a, IL4, IL5, and CCL22, and further optionally the subject further may exhibit elevated expression levels of CCL3 and/or reduced levels of IL12. In some embodiments, elevated expression levels of CCL17 and reduced expression levels of IL1 β and/or IL6 classifies the subject in cluster 4, optionally the subject may further exhibit reduced expression levels of 1 , 2, 3, or all 4 of ILla, IL4, IL5, and CCL22. In some embodiments, elevated expression levels of 1 , 2, 3, or all 4 of CCL3, CCL5, IL10 and IL13 and reduced expression levels of ILip classifies the subject in cluster 5.

[0030] A "subject" refers to a mammal, including primates (e.g. , humans or monkeys), cows, sheep, goats, horses, dogs, cats, rabbits, guinea pigs, rats, mice, or other bovine, ovine, equine, canine, feline, rodent or murine species. Examples of suitable subjects include, but are not limited to, human patients. In particular embodiments, the subject is a human subject, and in more particular embodiments the human subject has, is suspected of having, or is at increased risk of developing cancer, more particularly a cancer that has metastasized to the brain or is localized to the brain, in certain embodiments, the cancer is melanoma, and still more

particularly the cancer is metastatic melanoma. While subjects may be of any stage of life and any age, e.g., neonate, infant, toddler, child, young adult, adult, or geriatric, in particular embodiments the subject is an adult, e.g. , a human adult, i.e., about 18 years old, or older, e.g., about: 18-70 years old, 20-60 years old, 25-55 years old, 25-50 years old, 30-50 years old, or 25- 65 years old, as well as greater than about: 30 years old, 40 years old, 50 years old, 60 years old, 70 years old, 80 years old or 90 years old. In particular embodiments, the subject exhibits AKT overexpression and/or a mutation in one or more of BRAF, p53, CDKN2A, or PTEN. Other groups at increased risk of developing melanoma include subjects with one or more of: fair skin, light hair color, light eye color, or a combination thereof; experienced sunburns at a young age, use tanning bed, or have exposure to UV radiation; family history of melanoma; with high number of moles or have a previous melanoma or non-melanoma skin cancer diagnosis; a weakened immune system or old age. Additional risk factors are described at the URL:

//www.melanoma.org/melanoma-risk-factors. In certain embodiments, a subject to

[0031] Subjects can, in some embodiments, be further evaluated, e.g. , by measuring the levels of C reactive protein, surgery, molecular phenotyping, histological analysis, et cetera. The subject diagnosed and/or prognosed by the methods provided by the invention can also be undergoing concurrent treatments, e.g. , with dexamethasone (ChemID 5743), adjuvant therapy, alkylating chemotherapy (e.g. , comprising decarbazine (ChemlDs 2942, 5353562)), biologic therapy (IL2 (human GenelD No. 3558), IFNa (human GenelD No. 3439), ipilmumab (e.g. , substancelD 131273201), lambrolizumab (e.g. , substancelD 164150083 ), or a combination thereof), or a combinations thereof.

[0032 ] "Melanoma" is a malignant tumor of melanocytes and encompasses both localized melanomas as well as metastatic melanomas. The melanoma can be at any stage. In particular embodiments, the melanoma is stage III or IV melanoma that can metastasize to the brain or other organs in the body. Additional melanoma stages are described at the URL

://www.melanoma.org/understand-melanoma/diagnosing-melanoma/stages-of-diagnosis.

Measurements

[0033] Expression levels of immunokines can be measured at either the nucleic acid or protein level and by any means. Expression levels can be measured at the nucleic acid level by, for example, quantitative polymerase chain reaction (qPCR), quantitative real-time polymerase chain reaction (qRTPCR), digital droplet PGR, (ddPCR), SAGE (serial analysis of gene expression), sequencing (including next-generation sequencing, such as sequencing by synthesis, pyrosequencing, dideoxy sequencing, and sequencing by ligation, or any other methods known in the art, such as discussed in Shendure et al. , Nat. Rev. Genet. 5:335-44 (2004) or Nowrousian, Euk. Cell 9(9):1300-1310 (2010), including such specific platforms as HELICOS^®, ROCHE^® 454, ILLUMINA^® /SOLEXA^®, ABI SOLiD^®, and POLONATOR^® sequencing), northern blotting, microarrays, or Southern blotting.

[0034] Expression levels can be determined by measuring and/or testing the reference nucleic acid sequences listed in Table A— as well as complements, fragments, and similar nucleic acid sequences of the reference nucleic acid sequences listed in Table A— including any combination described in the application. "Similar nucleic acid sequences" can be naturally occurring (e.g. , allelic variants or homologous sequences from other species) or engineered variants (e.g. , for use as positive or negative controls) relative to the reference nucleic acid sequences in Table A and, in some embodiments, will be at least about 60, 65, 70, 75, 80, 85, 90, 95, 96, 97, 98, 99% or more identical (or hybridize under highly stringent hybridization conditions to a complement of a nucleic acid sequence listed in Table A) over a length of at least about 10, 20, 40, 60, 80, 100, 150, 200 or more nucleotides or over the entire length of the reference nucleic acid sequences in Table A. Fragments of the reference nucleic acid sequences in Table A— or similar nucleic acid sequences— can be of any length sufficient to distinguish the fragment from other sequences expected to be present in a mixture, e.g. , at least 5, 10, 15, 20, 40, 60, 80, 100, 150, 200 or more nucleotides or at least about 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 95 % of the length of the reference nucleic acid sequences in Table A. "Highly stringent hybridization" means hybridization conditions comprising about 6X SSC and 1% SDS at 65°C, with a first wash for 10 minutes at about 42°C with about 20% (v/v) formamide in 0.1X SSC, and with a subsequent wash with 0.2 X SSC and 0.1% SDS at 65°C.

[0035] Expression levels can be measured at the protein level by, for example, immunoassay (optionally including electrochemical readout), Western blotting, ELISA (enzyme-linked immunosorbent assay), MSIA (mass spectrometric immunoassay), MS/MS (tandem mass spectrometry), RIA (radioimmunoassay), peptide sequencing, flow cytometry, surface plasmon resonance, aptamer-based assay, LUMINEX ®, bead based detection systems, spectroscopic method, interferometry, chromatographic method, colorimetric methods or HPLC.

[0036] Protein gene expression products measured in the methods provided by the invention can be of the genes listed in Table A, as well as fragments of these sequences, similar peptide sequences, and fragments of similar peptide sequences. "Similar peptide sequences" can be naturally occurring (e.g. , allelic variants or homologous sequences from other species) or engineered variants (e.g. , for use as positive or negative controls) to the genes in Table A and will exhibit substantially the same biological function and/or will be at least about 60, 65, 70, 75, 80, 85, 90, 95, 96, 97, 98, 99% or more homologous (i.e. , conservative substitutions (see, e.g. , Heinkoff and Heinkoff, PNAS 89(22):10915-10919 (1992) and Styczynski et a!., Nat. Biotech. 26(3):274-275 (BLOSUM, e.g., BLOSUM 45, 62 or 80) or Dayhoff et al, Atlas of protein sequence and structure (volume 5, supplement 3 ed.), Nat. Biomed. Res. Found, pp. 345-358 (PAM, e.g., PAM 30 or 70))) or identical at the amino acid level over a length of at least about 10, 20, 40, 60, 80, 100, 150, 200 or more amino acids or over the entire length of a protein product of the genes in Table A. Fragments of protein products of the genes in Table A— or similar peptide sequences— can be of any length sufficient to distinguish the fragment from other sequences expected to be present in a mixture, e.g., at least 5, 10, 20, 40, 60, 80, 100, 150, 200 or more amino acids or at least about 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 95 % of the length of protein products of the genes in Table A.

[0037] In particular embodiments, the expression levels are measured by an immunoassay. An "immunoassay" is an analytical assay that employs antibodies for detecting an analyte, e.g. , an immunokine. "Antibody" encompasses both immunoglobulins (as well as antigen-binding fragments thereof) and non-immunoglobulin scaffolds that can be adapted and used similar to immunoglobulins— so-called "antibody-mimetics." Exemplary antibody mimetics include those based on fibronectin 3 domains (Fn3 domains; also known as monobodies; see, e.g. , Koide and Koide, Methods Mol. Biol. 352:95-109 (2007)), Z domains of protein A (also known as affibodies; see, e.g., Nygren, FEBSJ. 275(1 1):2668-76 (2008)), gamma-B crystalline or ubiquitin (afflins; see, e.g. , Ebersbach, et al. , J. Mol. Biol. 372(1): 172— 85 (2007)), lipocalins (anticalins; see, e.g. , Skerra, FEBS J. 275(11):2677-83(2008)); A domains of membrane receptors (avimers; see, e.g. , Silverman, et al. , Nat. Biotechnol. 23 ( 12) : 1556—61 (2005)); ankryn repeats (darpins; see, e.g. , Stumpp, et al., Drug Discov. Today 13(15-16):695— 701 (2008)); SH3 domain of Fyn (fynomers; see, e.g., Grabulovski, et al. , J. Biol. Chem. 282(5):3196- 3204(2007)), and Kunitz type domains (Kunitz domain peptides; see, e.g. , Nixon and Wood CR, Curr. Opin. Drug Discov. Devel. 9(2):261-8 (2006)).

[0038] In particular embodiments, the antibody is an immunoglobulin. "Immunoglobulin" refers to both full-length immunoglobulins, as well as antigen-binding fragments of

immunoglobulins, such as Fab, F(ab')2, Fv, scFv, Fd, dAb, and other immunoglobulin fragments that retain antigen-binding function. Immunoglobulins will have at least 3 CDRs

(complementarity determining regions) in their antigen-binding domain, and, in more particular embodiments, 4, 5, or 6 CDRS, and, still more particularly, 6 CDRs in an antigen-binding domain. Immunoglobulins for use in the invention include, for example, human, orangutan, mouse, rat, goat, sheep, rabbit and chicken antibodies. Immunoglobulins may be polyclonal, monoclonal, monospecific, polyspecific, non-specific, humanized, camelized, single-chain, chimeric, synthetic, recombinant, hybrid, mutated, or CDR-grafted.

[0039] Expression levels of immunokines can be measured at a single time point, or multiple time points (i. e. , in a time series), to, for example, monitor a subject over time. For example, a subject that previously had cancer, or is at increased risk of developing cancer (or having their cancer metastasize), can be monitored over time by the methods provided by the invention to detect changes relating to the cancer (e.g. , diagnosis, recurrence, staging, metastasis, et cetera). Related aspects

[0040] In a related aspect, the invention provides kits for performing the methods provided by the invention, where the kit comprises reagents for detecting the levels of the immunokines, and optionally, e.g. , further including positive and/or negative controls, instructions for use, elements (e.g. , tools and/or reagents) for obtaining or processing a biological sample, et cetera.

[0041] Similarly, the invention provides computer-readable media with instructions that, if executed by a processor, cause the processor to perform the analytical steps of any of the methods provided by the invention, optionally providing a user-readable display of the results. In related aspects, the invention provides systems for performing the methods provided by the invention, where the system includes a processor and the computer-readable media.

[0042] In a further aspect, the invention provides methods of treating cancer, by providing a suitable treatment to a subject determined to have cancer, such as melanoma (more particularly metastatic melanoma), by a method provided by the invention. In some aspects, a healthcare provider can administer or instruct another healthcare provider to administer a therapy to treat a cancer, such as melanoma. A healthcare provider can implement or instruct another healthcare provider or patient to perform one or more of the following actions: obtain a sample, process a sample, submit a sample, receive a sample, transfer a sample, analyze or measure a sample, quantify a sample, provide the results obtained after analyzing/measuring/quantifying a sample, receive the results obtained after analyzing/measuring/quantifying a sample, compare/score the results obtained after analyzing/measuring/quantifying one or more samples, provide the comparison/score from one or more samples, obtain the comparison/score from one or more samples, administer a therapy (e.g. , a therapeutic agent that treats a cancer, such as melanoma), commence the administration of a therapy, cease the administration of a therapy, continue the administration of a therapy, temporarily interrupt the administration of a therapy, increase the amount of an administered therapeutic agent, decrease the amount of an administered therapeutic agent, continue the administration of an amount of a therapeutic agent, increase the frequency of administration of a therapeutic agent, decrease the frequency of administration of a therapeutic agent, maintain the same dosing frequency on a therapeutic agent, replace a therapy or therapeutic agent by at least another therapy or therapeutic agent, combine a therapy or therapeutic agent with at least another therapy or additional therapeutic agent.

[0043] As used herein, the terms "treat," "treating," or "treatment" mean to counteract a medical condition so that the medical condition is improved according to a clinically acceptable standard. In certain embodiments, the treatment comprises providing a therapy. In particular embodiments, the therapy comprises providing a therapeutically effective amount of a therapeutic agent.

[0044] As used herein, a "therapeutically effective amount" is an amount sufficient to achieve the desired therapeutic or prophylactic effect under the conditions of administration, such as an amount sufficient to treat a given condition. The effectiveness of a therapy can be determined by one skilled in the art using standard measures and routine methods.

[0045] As used herein, the term "therapy" includes any means for eliminating, reducing, preventing or slowing the growth of a cancer, such as metastatic melanoma, including, for example, therapeutic agents and surgical procedures. In this respect, the term therapy encompasses any protocol, method and/or therapeutic or diagnostic that can be used in eliminating, reducing, preventing or slowing the growth of a cancer, such as metastatic melanoma. In some aspects, the term "therapy" refers to administering a therapeutically effective amount of a therapeutic agent that is capable of eliminating, reducing, preventing or slowing the growth of a cancer, such as metastatic melanoma in a patient in need thereof. [0046] Suitable therapies for cancer, such as a localized brain cancer or a cancer

metastasized to the brain, such as metastatic melanoma, are known in the art and can serve as an indication for certain methods provided by the invention (e.g. , methods of diagnosis or classification, to monitor treatment progress) or, in certain embodiments, the methods provided by the invention can act as an indication for treatment (e.g. , that treatment is necessary, on the basis of a diagnosis, and/or that a particular treatment or change in treatment is warranted, based on a classification of the cancer). Suitable therapies include one or more (e.g. , 1, 2, 3, 4, 5, or more) of surgery, immunokine-specific treatments (such as anti-CXCLlO, anti-IL-8, anti-CCL3, anti-CCL4, anti-CCL17, anti-ILl O, and IL-13), small molecule tyrosine kinase inhibitors, or immunotherapies, such as monoclonal antibodies, toxin-conjugated monoclonal antibodies, radiolabeled monoclonal antibodies, vaccines or chimeric antigen receptor (CAR) engineered lymphocytes. Additional treatments can include one or more of dexamethasone, adjuvant therapy, alkylating chemotherapy (e.g. , comprising decarbazine), biologic therapy (IL2, IFNa, ipilmumab, lambrolizumab), or a combination thereof), or a combinations thereof.

EXEMPLIFICATION

[0047] The aggressiveness of melanoma is thought to correlate with tumor-stroma associated immune cells. Cytokines and chemokines act to recruit and then modulate the activities of these cells, ultimately affecting disease progression. Because melanoma frequently metastasizes to the brain, it was investigated if global differences in immunokine profiles could be detected in the cerebrospinal fluid (CSF) of melanoma patients and reveal aspects of tumor biology that correlate with patient outcomes. The levels of 12 cytokines and 12 chemokines were measured in melanoma patient CSF and the resulting data were analyzed to develop unsupervised hierarchical clustergrams and heat maps. Unexpectedly, the overall profiles of immunokines found in these samples showed a generalized reconfiguration of their expression in melanoma patient CSF, resulting in the segregation of individuals with melanoma brain metastasis from non-disease controls. Chemokine CCL22 and cytokines ILla, IL4, and IL5 were reduced in most samples, while a subset including CXCLIO, CCL4, CCL17 and IL8 exhibited increased expression. Further, analysis of clusters identified within the melanoma patient set comparing patient outcome suggests that suppression of ILla, IL4, IL5 and CCL22, with concomitant elevation of CXCLIO, CCL4 and CCL17, were associated with more aggressive development of brain metastasis. These results suggest that global immunokine suppression in the host, together with selective increase in specific chemokines, constitute predominant immunomodulatory features of melanoma brain metastasis. These alterations likely drive the course of this disease in the brain and variations in the immune profiles of individual patients may predict outcomes.

Materials and Methods

Patients and CSF

[0048] Individual CSF samples from 22 patients with melanoma brain metastases and 5 non- disease controls were collected at the time of neurological evaluation when there was an indication for lumbar puncture or sampling from a ventricular reservoir. Informed consent was obtained from patients for CSF storage and analysis under institutional review board- approved protocols. CSF samples were stored in -80°C until analysis.

Individual and Multiplexed Enzyme-Linked Immunosorbent Assay (ELISA)

[0049] Twelve-Plex Cytokine and Chemokine Infrared Searchlight ELISA kits (Aushon Biosystems) were used to quantify the levels of CSF immunokines, most of which were known to interact with melanoma. Cytokines analyzed included interleukins such as ILlct, ILlp, IL2, IL4, IL5, IL6, IL8, IL10, IL12, IL13, as well as interferon- gamma (IFN-γ), and tumor necrosis factor- alpha (TNF-a), which are common mediators of inflammation. The frequent

inflammatory chemokines analyzed included CCL2 (Monocyte Chemotactic Protein 1 , MCP1), CCL3 (Macrophage Inflammatory Protein la, MlPla), CCL4 (Macrophage Inflammatory Protein 1 β, ΜΙΡΙ β), CCL5 (Regulated upon Activation, Normal T-cell Expressed and Secreted, RANTES), CCL11 (Eotaxin), CCL17 (Thymus and Activation Regulated Chemokine, TARC), CCL22 (Macrophage Derived Chemokine, MDC), CCL23 (Myeloid Progenitor Inhibitory Factor 1, MPIFl), CXCL1 (Growth Regulated Oncogene a, GROa), CXCL5 (Epithelial Neutrophil Activating peptide 78), CXCL9 (Monokine Induced by Gamma interferon, MIGl), and CXCLIO (Induced Protein 10, IP- 10).

Statistical Analysis

[0050] The prognostic factors of our cohort, such as age < 60 and > 60 years, initial cutaneous melanoma stage from 0 to 4, and Breslow depth measured in centimeters, were evaluated by the Wilcoxon rank sum test. Analysis of the ELISA data on the 24 immunokines was performed by, first, normalizing each data point to a Gaussian distribution using Z-scores. These normalized values were then input into the MATLAB Bioinformatics Toolbox to generate unsupervised heat maps and clustergrams, with the former showing the relatedness of patients based on their chemokine and cytokine profile while the latter showing the relatedness of each marker relative of all markers tested. Distinct clusters were defined based on a relative metric unit distance away from the origin of the corresponding patient dendrogram that allowed the segregation of noticeable subgroups. Additionally, a K-Means hierarchical cluster analysis was performed using R to validate the initial cluster analysis carried out by the MATLAB

Bioinformatics Toolbox. Ward's method was used to compute the linkage between clusters, which minimizes the variance within clusters, and a dendrogram of the results was created.

[0051] Each individual cluster of the heat map was then compared to patient outcomes, including (1) survival time from diagnosis of melanoma to the date of first brain metastasis, (2) survival time from date of first brain metastasis to date of death, (3) overall survival time from the diagnosis date of melanoma to date of death, and (4) response to biologies treatment.

Wilcoxon rank-sum test was used to determine if any significant differences in patient outcome exist between individual clusters based on their overall immunokine profiles.

Results

The melanoma cohort has known clinical prognostic factors

[0052] The clinical characteristics of our cohort are summarized in Table 1. The median age was 54 (range 25-84) years. Patient age (< 60 versus > 60) did not have a statistically significant effect on overall survival (P=0.2740). The patient population was then assessed to confirm that it conformed to known prognostic variables for metastatic melanoma. Although only 16 of 22 patients had data on Breslow depth of the cutaneous melanoma at initial diagnosis, there was a trend associating increased Breslow depth with decreased time from diagnosis to brain metastasis (R2=0.3051) and with decreased overall survival (R2=0.2349) (Table 1 & FIG. 1). The median overall survival of patients, from initial melanoma diagnosis to death, was 78.0 (range 33.9-324.6) months for stage 1 disease (n=8), 349.5 (range 19.7-87.3) months for stage 2 disease (n=5), 22.5 (range 15.7-73.8) months for stage 3 disease (n=6), and 25.6 (range 19.1- 73.3) months for stage 4 disease (n=3). Patients with stage 1 disease had a significantly prolonged overall survival as compared to those with stage 3 disease (P=0.0080). Furthermore, there is a significantly prolonged interval from the time of first melanoma diagnosis to brain metastasis in stage 1 patients (median=61.5 months, range 22.6-306.1 months) as compared to stage 3 patients (median=13.8 months, range 4.9-45.7 months) (P=0.0047) and stage 4 patients (median 0.6 months, range 0.0-23.6 months) (P=0.0242). There was no statistical difference between patients with stage 1 versus 2 (P=0.2844), 2 versus 3 (P=0.0519), 2 versus 4

(P=0.1429), or 3 versus 4 (P=0.3810) disease. The findings on the clinical characteristics of our cohort are, therefore, consistent with respect to known prognostic factors for cutaneous melanoma. CXCL10 and IL8 chemokines are upregulated in melanoma CSF

[00531 Cancerous tumors secrete immunokines to effect immune subversion. To test whether the presence of melanoma metastases within the brain leads to detectable alterations in the expression of immunokines within the CSF, we determined the expression profile of 24 cytokines and chemokines in the CSF (Table 2). Using a less stringent criteria of 10% chance or less, or P<0.1, of the observed difference between the melanoma and control cohorts, we identified 8 cytokines and 9 chemokines whose levels varied significantly in our melanoma patient cohort versus our set of non-disease controls. Among them, CXCL10 and IL8 levels were significantly higher in the melanoma cohort than controls, 92.4 [range 17.5-587.9] pg/ml versus 3.5 [range 0.0-3.9] pg/ml (P=0.0007) and 53.7 [range 13.0-775.0] pg/ml versus 5.0 [range 0.0-29.5] pg/ml (P=0.0007, FIG. 2A), respectively. Elevated levels of IL6 (n=4), CCL17 (n=l 1), CCL3 (n=5), and CCL4 (n=l 1) were also detected in the melanoma CSF samples.

CSF from patients with melanoma brain metastasis exhibit global reconfiguration of CSF immunokine profiles

[0054] Upon examining the global levels of immunokines in our melanoma CSF samples, a generalized suppression of multiple immunokines, including ILla, ΙΙΤβ, IL4, IL5, IL10, IL12, IL13, CCL5, CXCL9, CCL1 1 and CCL22 relative to levels seen in controls, but not IL2, TNFa, IFN-γ, CCL2, CCL23, CXCL1 and CXCL5 was observed (FIG. 2B). To obtain a more global view of possible differences in the relative immunokine levels that may exist between melanoma patients and controls, an unsupervised clustergram and heat map based on the concentrations of the subset of immunokines found to vary between these two populations was generated (FIG. 3A). The resulting analysis revealed that melanoma patients were segregated away from the controls based on their immunokine profiles. Generation of a hierarchical K-Mean dendrogram from these data also revealed a segregation of these two groups (FIG. 3B). These data suggest that the presence of tumor metastasis in the brain significantly alters host immunity within the central nervous system (CNS). Specifically, generalized suppression of ILla, IL4, IL5, and CCL22 was detected in nearly all melanoma CSF samples, suggesting the presence of global immunosuppression as part of a strategy aimed at evading host immunity against the melanoma metastasis. Furthermore, in a subset of patients, we observed the selective elevation of the three chemokines CXCL10, CCL4 and CCL17, raising the possibility of selective chemokine activation for the purpose of oncogenesis.

[0055] Because tumors in the brain can have a disrupted blood brain barrier, circulating chemokines in the blood could have leaked across the barrier causing elevation of these chemokines in the CSF. Because concurrent serum samples from the cohort were not available, the C reactive protein (CRP) was measured. CRP is synthesized primarily in the liver and is present at high concentration in the serum with the 95^th percentile concentration at 9.50

but is generally excluded from the CSF. Compared to a reference non-disease serum sample with CRP measured 3.70 μg/ml, all of the melanoma CSF samples had CRP of <0.02 μ /ηι1 (FIG. 2C), demonstrating that intratumoral compromise of the blood brain barrier was insufficient to explain the observed immunokine elevation in the CSF. In addition,

immunostaining of the primary melanoma tumor from patient M3, which demonstrated high level of CXCL10, showed staining in the tumor parenchyma (FIG. 2D), further suggesting the tumor origin of this chemokine.

[0056] It is possible that the differences observed between melanoma CSF samples and controls was due to prior therapies in the patient population. Dexamethasone use is an important temporalizing treatment for cerebral edema that is often associated with brain metastasis and the most likely therapeutic intervention that might account for the results. However, only 9 of 22 patients were prescribed dexamethasone at the time of CSF collection, having a median daily dose of 4 [range 2-16] mg, and therefore dexamethasone was unlikely to be a contributing factor for the observed immunokine suppression. Furthermore, alkylating chemotherapies, such as dacarbazine that is being used in conjunction with biologic agents (biochemotherapy), can potentially cause an immunosuppressive state in patients. Notably, serum levels of IL6, IL10, and IFN-γ in patients treated with dacarbazine-based chemotherapy combinations are

significantly lower than those treated with dacarbazine-based biochemotherapy. However, in our cohort only 2 patients received dacarbazine and 1 had thiotepa, while 12 patients did not receive any systemic treatment prior to CSF sampling. Therefore, alkylating chemotherapy was unlikely to cause the suppressed immunokine levels in the patient set.

Correlation between patient clusters and clinical outcome

[0057] Next, it was asked whether different melanomas impose distinct immunokine signatures in the CSF. Indeed, unsupervised clustergram and heat map suggested the presence of 5 separate clusters of patients with distinct immunokine profiles in the samples (FIG. 3A). As immunokines have been suggested to be important in driving tumor progression and metastasis, it was attempted to determine if an association could be detected between any of these apparent clusters and patient outcome. Three epochs for the analysis were chosen: (i) time from diagnosis of melanoma to brain metastasis, (ii) time from brain metastasis to death, and (iii) overall survival. First, cluster 3 demonstrated the shortest interval from melanoma diagnosis to brain metastasis with a median time of 11.2 [range 0.0-306.1] months versus 31.2 [range 0.6-81.9] months for the rest of the melanoma cohort (P=0.2873, Table 3 A). However, on closer inspection, this cluster contains the patient M21 that had a time interval of 306.1 months or 4.1 standard deviations from the mean, which was clearly an outlier when compared to the other patients in the sample set [range 0.0-81.9 months]. Upon exclusion of M21 , cluster 3 possessed a statistically significant shortened time from melanoma diagnosis to brain metastasis or 4.9 [range 0.0-17.5] months (P=0.0307). Notably, the remaining members in this re-calculated cluster, Ml 3, Ml 9, and M22, all had elevated levels of CXCLI O, CCL4, and CCL17 while ILla, IL4, IL5, and CCL22 were markedly suppressed. Both CXCLI O and CCL4 are potent chemoattractant for CD8⁺ effector T cells, suggesting that these inflammatory proteins may play a role in promoting the formation of brain metastasis. Taken together, the CSF immunokine profile in these members of cluster 3 may support a propensity for the development of melanoma brain metastasis.

[0058] Second, analysis was performed to determine if any of the clusters exhibited correlations with clinical outcome subsequent to the detection of brain metastasis. Cluster 4 showed a trend of decreased time interval from brain metastasis to death with a median time of 4.1 [range 1.9-28.0] months versus 15.1 [range 2.6-73.3] months for the rest of the melanoma cohort (P=0.117, Table 3B). Interestingly, only CCL17 was elevated in all members of this cluster while IL1 β and IL6 were suppressed in addition to the commonly observed ILl , IL4, IL5, and CCL22 immunokine suppression. Therefore, these patients' apparent poor clinical outcome may arise from a more effectively tumor-subverted immune function relative to that in the rest of our melanoma cohort. Third, there was no detectable difference in the overall survival among the five patient clusters (Table 3C). This is likely because overall survival is influenced by the extent of the systemic malignancy rather than the number and size of the brain metastases or their treatment.

Correlation between patient clusters and prior biologies treatment

[0059] Because treatment with biologies and immune-checkpoint inhibitors can suppress or eradicate systemic melanoma, it was next analyzed whether these interventions would alter patient outcomes or associate with any of the identified patients in the previous analysis. There was no difference detected with respect to time from melanoma diagnosis to brain metastasis (P=0.6318), time from brain metastasis to death (P=0.3195), and overall survival (P=0.8538) based on treatment with biologies such as high-dose IL2 and/or IFN-a. However, among patients who received biologies, those in cluster 1 appeared to exhibit a marked shortening of the interval from diagnosis to brain metastasis, with a median time of 22.0 [range 0.6-38.9] months versus 34.7 [range 4.9-306.1] months for the rest of the melanoma cohort (P=0.1773). This trend may represent the selection pressure imposed onto the systemic melanomas that leaves some of the surviving clones with a higher propensity of metastasizing to the brain. Similarly, patients in cluster 4 who were treated with biologies exhibit a trend towards shortened time from brain metastasis to death, with a median time of 7.8 [range 1.9-28.0] months versus 15.9 [range 5.2- 39.0] months for the rest of the melanoma cohort (P=0.1275), suggesting that the brain metastases in this cluster are particularly aggressive after selection by biologies treatment.

Discussion

[0060] This is the first analysis of broad immunokine profiling in the CSF of patients with melanoma metastasis to the brain, a concept similar to immunoprofiling and establishing an immunoscore for systemic malignancies. This immunoscore is predictive of the efficacy of cancer treatments and allows for personalized immunotherapy. The melanoma samples differed significantly from non-disease controls in cytokine and chemokine levels, including a marked suppression of ILla, IL4, IL5 and CCL22 in nearly all of our samples. It is important to note that while this constitutes a generalized suppression of immunokine levels as compared to control CSF, we also detected elevation of CXCLIO, CCL4 and CCL17 in a large subset of our melanoma CSF. Immuno staining of the tumor origin of CXCLIO, as well as our analysis of CSF versus serum CRP in control and melanoma CSF samples, also supports that these immunokine changes are specifically altered in the brain and not coming from the serum. Together, these data demonstrate a global response within the CNS to the presence of melanoma metastasis. There are potentially two explanations for this observation. First, this difference may reflect the altered activities of tumor-associated immune cells that impose immune suppression on the rest of the CNS through the secretion of soluble factors. This may result in suppression of resident immune cells resulting in lowered levels of inflammatory cytokines observed in the current study. Such a general suppression has been shown for ILip, IL4, and IL5 in melanoma-positive sentinel lymph nodes relative to melanoma-negative controls. Second, the down-regulation of inflammatory cytokines could be a consequence of dexamethasone use or treatment by alkylating chemotherapies. However, our analysis demonstrated that neither is likely to cause the observed immunosuppressive profile in the CSF. Prior biologies treatment may result in unpredicted responses in the immune system similar to those observed in our patient set. However, most patients, 16 out of 22, were treated with IL-2 and/or IFN-a, while 6 were not, and there was no difference in the immunokine profiles between these two groups. Taken together, the immune suppression observed in the patients is likely imposed by the metastases rather than arising as a result of prior therapies.

[0061] Another important observation derived from our data is that CXCL10 and IL8 are up- regulated in the CNS of a majority of our melanoma patients. There is a striking, statistically significant 30-fold and 10-fold increase of CXCL10 and IL8, respectively, in melanoma CSF as compared to controls. We were able to detect CXCL10 immunohistochemical staining in the parenchyma of a primary melanoma, suggesting that the melanoma metastasis in the brain may also secret this chemokine in an effort to recruit inflammatory effector CD8⁺ T cells into the tumor microenvironment for its own survival and proliferation. Additionally, CXCL10 may be secreted by microglia and astrocytes. This is because CXCL10 up-regulation has also been detected in Alzheimer's dementia, which has an inflammatory component likely driven by microglia resulting in a protracted course of clinical deterioration. In experimental autoimmune encephalitis, the source of CXCL10 has been shown to originate from astrocytes within the brain, cerebellum, and spinal cord. Therefore, both tumor and brain derived CXCL10 may facilitate the survival and proliferation of melanoma brain metastasis. Furthermore, the IL8 chemokine is a potent mediator for angiogenesis. Melanoma tumor cells can also secrete IL8 but the level of expression may be regulated by the local tissue microenvironment. It is also secreted by activated microglia in the brain and its level is elevated in the CSF of patients with acute and chronic inflammatory neurological disorders, including HIV-associated dementia and

opticospinal multiple sclerosis. Taken together, both tumor and brain derived IL8 may also facilitate the development of angiogenesis, which is critical to ensure the survival and proliferation of melanoma brain metastasis.

[0062] A survey of the patient clusters in the heat map revealed that despite the presence of generalized immunokine suppression there is variability in the relative chemokine levels in the CSF with the expression of several is actually enhanced in specific clusters of melanoma patients relative to controls. High levels of chemokines CCL4, CXCL10 and CCL17 seem to aggregate together in the clustergram, and both CCL3 and IL8 chemokines also appear to cluster near these 3 chemokines. Notably, cluster 3 has the highest levels of CCL4, CXCL10 and CCL17 and it has the shortest time interval from melanoma diagnosis to the development of brain metastasis. CCL17 has been shown to be expressed by brain tissue and it is a potent chemokine for Tn2-type CD4+ CD25+ Treg cells because they have the corresponding CCR4 receptor. In patients with Vogt-Koyanagi-Harada disease, a rare autoimmune disease directed against tyrosinase and other melanocyte antigens that results in uveitis and neurological deficits, the CSF level of CCL17 was also significantly elevated when compared to control patients without the disease. Therefore, in this setting, over-expression of CCL17 may help the recruitment of Treg cells that provide a counter-regulatory mechanism against the inflammatory reaction within the brain and eyes. It is also noteworthy that the serum level of CCL17 was lower in Vogt-Koyanagi-Harada patients than controls, suggesting that CCL17 is a chemokine specifically over-expressed in the brain. In melanoma patients however, CCL17-mediated recruitment of Treg cells to the brain may attenuate anti-melanoma protective immunity and enables tolerance to melanoma metastasis. Interestingly, certain melanoma cells also have the CCR4 receptor for the CCL17 ligand and they may therefore co-opt the CCL17 chemokine axis for their own migration into the brain suggesting a more complex role for this chemokine in promoting brain metastasis.

[0063] CCL3 and CCL4 are members of the IL8 chemokine superfamily and both may therefore aid the survival and proliferation of melanoma brain metastasis. They are expressed in the brain during the acute phase of experimental autoimmune encephalitis and neutralization of CCL3 by anti-CCL3 antibody limits the extent of brain damage in this model. In patients with ovarian carcinoma, elevated levels of CCL3 and CCL4 are associated with the presence of CD4+ T cells in the ascitic fluid while melanoma patients had a predominance of CD8+ T cells in biopsy samples taken from the brain, lung, skin and small bowel. These T cells most likely have a bias towards the T_H1 response because CCL3 and CCL4 are known to activate antigen presenting cells via the CCR5 receptor and during this process IL-12 is up-regulated. However, within cluster 3 where CCL4 is elevated in all while CCL3 is high in some patients, only one member, Ml 9, had elevated IL12 in the CSF while the rest is average or low. The high CCL4 with or without elevated CCL3, together with low IL12, suggests that there may be yet unknown mechanisms of attenuating the T_H1 response in patients with melanoma brain metastasis.

Nevertheless, for patients in cluster 3, treatments that can drive down CCL3 and CCL4 may be useful therapeutic strategies. Furthermore, M21 is an outlier having the longest time interval within the entire patient set. In contrast to other members of the cluster, this patient's CSF has a low level of CCL17 and a high level of ILip. It is possible that relatively lower level of CCL17 in M21 impairs the migration of melanoma cells into the brain while elevated ILip may be cytotoxic to the ones that arrived there by means other than the CCL17 chemokine axis and others that survived there because of impaired ¾1 adaptive immunity. Therefore, treatment that can lower CCL17 levels may prevent the development of melanoma brain metastasis.

[0064] Members within cluster 4 have suppressed ILl and IL6 cytokines in addition to the generalized ILla, IL4, IL5 and CCL22 immunokine suppression. Furthermore, only CCL17 chemokine was increased in this cluster. Patients within this cluster have poor survival once brain metastasis is established, irrespective of prior biologies treatment. We speculate that the severe immunokine suppression in the CSF represents a similar state of immunosuppression within the brain that provides a favorable environment for melanoma brain metastases to grow and proliferate. The extent of suppression is somewhat surprising and may arise from the immunologically sequestered nature of the CNS where smaller amounts of tumor -derived immunosuppressive factors can achieve global effect. Finally, cluster 1 has a trend for shortened time from melanoma diagnosis to brain metastasis and this only occurred in those who received biologies treatment. It is possible that biologies treatment places selection pressure on the systemic melanoma and that the surviving clones have a high propensity of metastasizing to the brain.

[0065] The robust segregation of melanoma CSF from controls as seen in both

clustergram/heat map and K-Mean dendrogram analyses strongly suggests that melanoma metastasis to the brain causes global changes in the immunokine milieu within the CNS that can be detected in the CSF. There is generalized immunokine suppression while specific CXCL10 and IL8 chemokine levels are increased. Therefore, these findings provide the necessary foundation for the identification of immunokines and their relative levels of expression in the CSF, as well as their utility as diagnostic biomarkers for melanoma brain metastasis.

Table 1 : Characteristics of patients with melanoma brain metastasis and non-disease controls (N/A = not available; na = not applicable)

Brain Metastasis

Cutaneous to

Breslow Melanoma to First Date of Death or Overall

Sample Depth Brain Metastasis Last Follow Up Survival !D Age Sex Stage {em}_. {Months) {Months) (Months)

M1 64 M 3 9.0 17,2 5.2 22,4

M2 SI F 3 1 1 20. S 3.3 23.8

M3 72 M 2 5.0 38.9 13.3 52.3

M4 72 M 2 1.8 70.7 16.6 87.3

M5 58 M 2 1.4 59.9 4.1 64.0 6 46 M 1 0.5 53.1 17.0 70.1

M7 51 F 1 1.5 27.6 6.3 33.9

M8 45 3 3,8 9,3 13.3 22.6

9 69 F 1 1.1 81.9 39 0 120.9 10 60 F 1 0.6 22.6 15.1 37.7

M11 28 F 3 5.0 4S.7 28.0 73.8

M12 38 F 4 7.7 0.6 18..S 19.1

13 33 F 3 5.0 4,9 13.2 18.1

M14 44 F 2 3.9 21-7 2,6 24.3

M15 25 F 3 2.7 10.3 5.4 15,7

M 16 56 F 4 N/A 23.6 1.9 25,6

M17 4? M 1 N/A 34.7 34.5 63,2

M18 67 F 1 N/A 73.5 12.4 85.9

19 84 M 4 N/A 0.0 73.3 73.3

M20 4 F 1 0.5 69.6 23.6 99.4

M21 60 M 1 N/A 306. 1 18 5 324.6

22 64 F 2 N/A 17.5 2.1 19.7

M1 57 F na na n a na na 2 39 F 113 na na na na 3 75 na na 11 a na na

N4 86 F na na na na na 5 22 M na na na na na

Table 2: Wilcoxon rank sum analysis of individual immunokines

[0066] Using a probability for the observed difference was due to chance in 10% or less of the time (or P<0.1), there were notable differences between melanoma CSF and controls in 8 cytokines and 9 chemokines. The 8 cytokines include ILla, ILip, IL4, IL5, IL6, IL10, IL12, and IL13. The 9 chemokines include IL8, CCL3, CCL4, CCL5, CCL11 , CCL17, CCL22, CXCL9, and CCXCLlO.

Table 3: Analysis of clusters derived from cluster analysis and patient outcome (A: Time of first melanoma diagnosis to development of brain metastasis; B: Time from brain metastasis to death; C: Overall survival or from time of first melanoma diagnosis to death)

A. Time from first melanoma diagnosis to development of brain metastasis

Mean Median Range

Cluster n {months) (months) (months) P value

1 6 27.4 31.2 0 6 - 53.1 0.5803

2 4 34 1 22.2 10,3 - 81.9 0 9SS1

3 4 82 1 11 2 0.0 - 306,1 0 2873

4 5 44.7 45 7 20.5 - 73.5 0,3084

5 3 S2.S 69.8 17.2 - 70 7 0,444

B, Time from, brain metastasis to death

Mean Median Range

Cluster n (months) (months) (months) R alue

1 6 17..2 15.2 6.3 - 34,5 0,3195

2 4 15.5 10.2 2.6 - 39,0 0.8984

3 4 26 S 15.9 2 1 - 73 3 0 7657

4 5 9.9 4 1 1 9 - 28 0 0 1170

5 3 17.1 16.6 5,2 - 29.6 0.7019

C. Overall s j rvival

Mean Median Range

Cluster il (months} (months) (months) P value

1 6 44.5 43 1 19.1 - 70, 1 0 5309

2 4 49.7 31.0 15.7 - 120.9 0.7017

3 4 108.9 46.5 18.1 - 324.6 0.8984

4 5 54.6 64 0 23 8 - 85, 9 0 S333

5 3 69.7 87.3 22,4 · 99.4 0.3892

[0067] It should be understood that for all numerical bounds describing some parameter in this application, such as "about," "at least," "less than," and "more than," the description also necessarily encompasses any range bounded by the recited values. Accordingly, for example, the description "at least 1, 2, 3, 4, or 5" also describes, inter alia, the ranges 1-2, 1 -3, 1 -4, 1 -5, 2- 3, 2-4, 2-5, 3-4, 3-5, and 4-5, et cetera.

[0068] For all patents, applications, or other reference cited herein, such as non-patent literature and reference sequence information, it should be understood that they are incorporated by reference in their entirety for all purposes as well as for the proposition that is recited. Where any conflict exists between a document incorporated by reference and the present application, this application will control. All information associated with reference gene sequences disclosed in this application, such as GenelDs or accession numbers (typically referencing NCBI accession numbers), including, for example, genomic loci, genomic sequences, functional annotations, allelic variants, and reference mRNA (including, e.g. , exon boundaries or response elements) and protein sequences (such as conserved domain structures), as well as chemical references (e.g. , Pub Chem compound, Pub Chem substance, or Pub Chem Bioassay entries, including the annotations therein, such as structures and assays, et cetera), are hereby incorporated by reference in their entirety.

[0069] Headings used in this application are for convenience only and do not affect the interpretation of this application.

[0070] Preferred features of each of the aspects provided by the invention are applicable to all of the other aspects of the invention mutatis mutandis and, without limitation, are exemplified by the dependent claims and also encompass combinations and permutations of individual features (e.g. , elements, including numerical ranges and exemplary embodiments) of particular embodiments and aspects of the invention, including the working examples. For example, particular experimental parameters exemplified in the working examples can be adapted for use in the claimed invention piecemeal without departing from the invention. For example, for materials that are disclosed, while specific reference of each various individual and collective combination and permutation of these compounds may not be explicitly disclosed, each is specifically contemplated and described herein. Thus, if a class of elements A, B, and C are disclosed as well as a class of elements D, E, and F and an example of a combination of elements A-D is disclosed, then even if each is not individually recited, each is individually and collectively contemplated. Thus, in this example, each of the combinations A-E, A-F, B-D, B-E, B-F, C-D, C-E, and C-F are specifically contemplated and should be considered disclosed from disclosure of A, B, and C; D, E, and F; and the example combination A-D. Likewise, any subset or combination of these is also specifically contemplated and disclosed. Thus, for example, the sub-group of A-E, B-F, and C-E are specifically contemplated and should be considered disclosed from disclosure of A, B, and C; D, E, and F; and the example combination A-D. This concept applies to all aspects of this application, including elements of a composition of matter and steps of method of making or using the compositions.

[0071] The forgoing aspects of the invention, as recognized by the person having ordinary skill in the art following the teachings of the specification, can be claimed in any combination or permutation to the extent that they are novel and non-obvious over the prior art— thus, to the extent an element is described in one or more references known to the person having ordinary skill in the art, they may be excluded from the claimed invention by, inter alia, a negative proviso or disclaimer of the feature or combination of features.

(0072] The described computer-readable implementations may be implemented in software, hardware, or a combination of hardware and software. Examples of hardware include computing or processing systems, such as personal computers, servers, laptops, mainframes, and microprocessors. In addition, one of ordinary skill in the art will appreciate that the records and fields shown in the figures may have additional or fewer fields, and may arrange fields differently than the figures illustrate. Any of the computer-readable implementations provided by the invention may, optionally, further comprise a step of providing a visual output to a user, such as a visual representation of, for example, results, e.g. , to a physician, optionally including suitable diagnostic summary and/or treatment options or recommendations.

[0073] While this invention has been particularly shown and described with references to example embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the scope of the invention encompassed by the appended claims.

Claims

CLAIMS What is claimed is:

1. A method of detecting and/or classifying metastatic melanoma in a mammalian subject, comprising:

measuring the expression levels of two or more immunokines in an isolated biological sample from the subject, wherein the biological sample comprises

cerebrospinal fluid;

comparing the measured expression levels of the two or more immunokines to suitable controls; and

determining the presence of metastatic melanoma, or classifying the metastatic melanoma, on the basis of the comparison,

wherein the two or more immunokines are selected from ILla, ILip, IL4, IL5, IL6, IL10, IL12, IL13, IL8, CCL3, CCL4, CCL5, CCLl l , CCL17, CCL22, CXCL9, and CCXCL10, and expression levels of the two or more immunokines differ between a metastatic melanoma sample and a non- metastatic melanoma sample.

2. The method of Claim 1 , wherein the two or more immunokines are selected from ILla, ILlp, IL4, IL5, IL6, IL12, IL8, CCL3, CCL4, CCL1 1, CCL17, CCL22, and CCXCL10.

3. The method of Claim 2, wherein the expression levels of any 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or all 13 immunokines are measured.

4. The method of any one of the preceding claims, wherein the expression levels of at least 2, 3, 4, 5, 6, 7, 8, 9, or all 10 of CXCL10, IL8, ILla, ILl p, IL4, IL5, IL13, CCLl l, CCL22, and CXCL9 are measured and compared to suitable controls.

5. The method of any one of the preceding claims, wherein the expression levels of at least 2, 3, 4, 5, 6, 7, or all 8 of CXCL10, CCL4, CCL17, IL8, CCL22, ILl a, IL4, and IL5 are measured and compared to suitable controls.

6. The method of any one of the preceding claims, wherein the expression levels of

CXCL10 and IL8 are measured and compared to suitable controls.

7. The method of Claim 6, further comprising measuring the expression levels of ILl and IL6 and comparing the measured expression levels to suitable controls.

8. The method of any one of the preceding claims, further comprising measuring the

expression level of CCL3 and comparing the measured level to suitable controls.

9. The method of any one of the preceding claims, further comprising measuring the

expression level of IL12 and comparing the measured level to suitable controls.

10. The method of any one of the preceding claims, wherein elevated expression levels, relative to the suitable control, of 1 , 2, 3, or all 4 of CXCLIO, CCL4, CCL17, and IL8 is associated with metastatic melanoma.

11. The method of any one of the preceding claims, wherein reduced expression levels of 1, 2, 3, or all 4 of CCL22, ILla, IL4, and IL5 is associated with metastatic melanoma.

12. The method of any one of the preceding claims, wherein the melanoma the originated in the skin, eyes, ears, gastrointestinal tract, leptomeninges, oral mucus membrane, or genital mucus membrane.

13. The method of any one of the preceding claims, wherein:

elevated expression levels of ILl and, optionally, globally reduced immunokine expression levels classifies the subject in cluster 1 ;

elevated expression levels of ILl and reduced expression levels of ILl p classifies the subject in cluster 2;

elevated expression levels of 1 , 2, or all 3 of CXCLIO, CCL4, and CCL17; and reduced expression levels of ILl p classifies the subject in cluster 3, optionally wherein the subject exhibits reduced expression levels of 1, 2, 3, or all 4 of ILla, IL4, IL5, and CCL22, further optionally wherein the subject further exhibits elevated expression levels of CCL3 and/or reduced levels of IL12; or

elevated expression levels of CCL17 and reduced expression levels of ILl p and/or IL6 classifies the subject in cluster 4, optionally wherein the subject further exhibits reduced expression levels 1 , 2, 3, or all 4 of ILl a, IL4, IL5, and CCL22; elevated expression levels of 1, 2, 3, or all 4 of CCL3, CCL5, IL10 and IL13 and reduced expression levels of IL1 β classifies the subject in cluster 5.

14. The method of Claim 13, wherein the subject is classified in cluster 3 and thereby has a reduced expected time from diagnosis to brain metastasis, relative to other metastatic melanoma clusters.

15. The method of Claim 14, wherein the subj ect is a candidate for a therapy that reduces expression levels of CCL3, CCL4, CCL17, or a combination of 2 or 3 of the foregoing.

16. The method of Claim 13, wherein the subject is classified in cluster 4 and thereby has a reduced expected time from metastasis to death, relative to other metastatic melanoma clusters.

17. The method of Claim 13, wherein the subject was a candidate for treatment with one or more biologies selected from IL2 and IFNa, and the one or more biologies are withheld on the basis of the classification.

18. The method of Claim 17, wherein the subject is classified in cluster 1 or cluster 4.

19. The method of any one of the preceding claims, wherein the expression levels of the immunokines are measured at the nucleic acid level.

20. The method of Claim 19, wherein expression levels are measured by quantitative

polymerase chain reaction (qPCR), quantitative real-time polymerase chain reaction (qRTPCR), digital droplet PCR, (ddPCR), SAGE (serial analysis of gene expression), sequencing, northern blotting, microarrays, or Southern blotting.

21. The method of any one of Claims 1-18, wherein the expression levels of the

immunokines are measured at the protein level.

22. The method of Claim 21 , wherein the expression levels are measured by immunoassay (optionally including electrochemical readout), Western blotting, ELISA (enzyme-linked immunosorbent assay), MSIA (mass spectrometric immunoassay), MS/MS (tandem mass spectrometry), RIA (radioimmunoassay), peptide sequencing, flow cytometry, surface plasmon resonance, aptamer-based assay, Luminex, bead based detection systems, spectroscopic method, interferometry, chromatographic method, colorimetric methods or HPLC.

23. The method of Claim 21, wherein the expression levels of the immunokines are measured by an immunoassay.

24. A method of detecting metastatic melanoma in a human subject, comprising:

measuring the protein expression levels of the immunokines CXCL10, CCL4, CCL17, IL8, CCL22, ILla, IL4, and IL5 in an isolated biological sample from the subject, wherein the biological sample comprises cerebrospinal fluid;

comparing the measured expression levels of the immunokines to suitable controls; and

determining the presence of metastatic melanoma, or classifying the metastatic melanoma, on the basis of the comparison,

wherein elevated protein expression levels of one or more of CXCL10, CCL4, CCL17, and IL8; and/or reduced protein levels of one or more of CCL22, ILla, IL4, and IL5 indicate the presence of metastatic melanoma.

25. The method of any one of the preceding claims, further comprising measuring the levels of C reactive protein in the biological sample.

26. The method of any one of the preceding claims, wherein the subject is undergoing

treatment with dexamethasone, adjuvant therapy, alkylating chemotherapy, biologic therapy, immunotherapy, targeted therapy, small molecule tyrosine kinase inhibitors, vaccines, chimeric antigen receptor (CAR) engineered lymphocytes, or a combination of two or more of the foregoing.

27. A kit for performing the methods of any one of the preceding claims, wherein the kit comprises reagents for detecting the expression levels of the two or more immunokines, and optionally further including positive and or negative controls.

28. A method of treating metastatic melanoma in a mammalian subject, comprising providing a suitable treatment to the subject on the basis of the metastatic melanoma detected and/or classified by the method of any one of Claims 1-26.

29. The method of Claim 30, wherein the subject is human.

30. A non- transient computer-readable medium comprising instructions that, if executed by a processor, causes the processor to perform steps comprising:

accepting data representing the levels of two or more immunokines in an isolated biological sample from the subject, wherein the biological sample comprises

cerebrospinal fluid;

comparing the measured levels of the two or more immunokines to suitable controls; and

determining the presence of metastatic melanoma, or classifying the metastatic melanoma, on the basis of the comparison,

wherein the two or more immunokines are selected from ILla, ILip, IL4, IL5, IL6, IL10, IL12, IL13, IL8, CCL3, CCL4, CCL5, CCLl 1 , CCLl 7, CCL22, CXCL9, and CCXCL10.

31. The computer-readable medium of Claim 30 suitable for performing the method of any one of Claims 1-26.

32. A system comprising the computer-readable medium of Claim 30 or Claim 31 and a processor for executing the instructions.

33. The system of Claim 32, further comprising a user-readable display for displaying the measured expression levels and/or the diagnosis and/or classification.