Comprehensive analyses of tumor immunity: implications for cancer immunotherapy

BackgroundUnderstanding the interactions between tumor and the host immune system is critical to finding prognostic biomarkers, reducing drug resistance, and developing new therapies. Novel computational methods are needed to estimate tumor-infiltrating immune cells and understand tumor–immune interactions in cancers.ResultsWe analyze tumor-infiltrating immune cells in over 10,000 RNA-seq samples across 23 cancer types from The Cancer Genome Atlas (TCGA). Our computationally inferred immune infiltrates associate much more strongly with patient clinical features, viral infection status, and cancer genetic alterations than other computational approaches. Analysis of cancer/testis antigen expression and CD8 T-cell abundance suggests that MAGEA3 is a potential immune target in melanoma, but not in non-small cell lung cancer, and implicates SPAG5 as an alternative cancer vaccine target in multiple cancers. We find that melanomas expressing high levels of CTLA4 separate into two distinct groups with respect to CD8 T-cell infiltration, which might influence clinical responses to anti-CTLA4 agents. We observe similar dichotomy of TIM3 expression with respect to CD8 T cells in kidney cancer and validate it experimentally. The abundance of immune infiltration, together with our downstream analyses and findings, are accessible through TIMER, a public resource at http://cistrome.org/TIMER.ConclusionsWe develop a computational approach to study tumor-infiltrating immune cells and their interactions with cancer cells. Our resource of immune-infiltrate levels, clinical associations, as well as predicted therapeutic markers may inform effective cancer vaccine and checkpoint blockade therapies.

[1]  G. Carcelain,et al.  Evidence for in situ amplification of cytotoxic T-lymphocytes with antitumor activity in a human regressive melanoma. , 1993, Cancer research.

[2]  M. Kojiro,et al.  Clinicopathological study on hepatocellular carcinoma with lymphocytic infiltration , 1998, Hepatology.

[3]  Noam Brown,et al.  The role of tumour‐associated macrophages in tumour progression: implications for new anticancer therapies , 2002, The Journal of pathology.

[4]  W. Sakr,et al.  Clinical significance of poor CD3 response in head and neck cancer. , 2002, Clinical cancer research : an official journal of the American Association for Cancer Research.

[5]  Alexander R. Abbas,et al.  Immune response in silico (IRIS): immune-specific genes identified from a compendium of microarray expression data , 2005, Genes and Immunity.

[6]  Gavin P Dunn,et al.  Cancer immunosurveillance and immunoediting: the roles of immunity in suppressing tumor development and shaping tumor immunogenicity. , 2006, Advances in immunology.

[7]  David J. Yang,et al.  The role of human glioma-infiltrating microglia/macrophages in mediating antitumor immune responses. , 2006, Neuro-oncology.

[8]  Cheng Li,et al.  Adjusting batch effects in microarray expression data using empirical Bayes methods. , 2007, Biostatistics.

[9]  Marylène Lejeune,et al.  Tumor-Infiltrated Immune Response Correlates with Alterations in the Apoptotic and Cell Cycle Pathways in Hodgkin and Reed-Sternberg Cells , 2008, Clinical Cancer Research.

[10]  Z. Modrušan,et al.  Deconvolution of Blood Microarray Data Identifies Cellular Activation Patterns in Systemic Lupus Erythematosus , 2009, PloS one.

[11]  Dongxia Gao,et al.  Systematic Analysis of Immune Infiltrates in High-Grade Serous Ovarian Cancer Reveals CD20, FoxP3 and TIA-1 as Positive Prognostic Factors , 2009, PloS one.

[12]  K. Silina,et al.  Sperm-associated Antigens as Targets for Cancer Immunotherapy: Expression Pattern and Humoral Immune Response in Cancer Patients , 2011, Journal of immunotherapy.

[13]  J. Wolchok,et al.  Novel cancer immunotherapy agents with survival benefit: recent successes and next steps , 2011, Nature Reviews Cancer.

[14]  R. Schreiber,et al.  Cancer Immunoediting: Integrating Immunity’s Roles in Cancer Suppression and Promotion , 2011, Science.

[15]  Ian O Ellis,et al.  Tumor-infiltrating CD8+ lymphocytes predict clinical outcome in breast cancer. , 2011, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[16]  S. Rosenberg,et al.  CTLA-4 Blockade with Ipilimumab: Long-term Follow-up of 177 Patients with Metastatic Melanoma , 2012, Clinical Cancer Research.

[17]  E. Mardis,et al.  Cancer Exome Analysis Reveals a T Cell Dependent Mechanism of Cancer Immunoediting , 2012, Nature.

[18]  F. Marincola,et al.  Cancer classification using the Immunoscore: a worldwide task force , 2012, Journal of Translational Medicine.

[19]  C. Sautès-Fridman,et al.  The immune contexture in human tumours: impact on clinical outcome , 2012, Nature Reviews Cancer.

[20]  A. McKenna,et al.  Absolute quantification of somatic DNA alterations in human cancer , 2012, Nature Biotechnology.

[21]  Drew M. Pardoll,et al.  The blockade of immune checkpoints in cancer immunotherapy , 2012, Nature Reviews Cancer.

[22]  Jun Z. Li,et al.  Genomic Estimates of Aneuploid Content in Glioblastoma Multiforme and Improved Classification , 2012, Clinical Cancer Research.

[23]  Tom C Freeman,et al.  An expression atlas of human primary cells: inference of gene function from coexpression networks , 2013, BMC Genomics.

[24]  Z. Trajanoski,et al.  Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. , 2013, Immunity.

[25]  M. Maio,et al.  Long-term survival and immunological parameters in metastatic melanoma patients who responded to ipilimumab 10 mg/kg within an expanded access programme , 2013, Cancer Immunology, Immunotherapy.

[26]  S. Gabriel,et al.  Pan-cancer patterns of somatic copy-number alteration , 2013, Nature Genetics.

[27]  J. Galon,et al.  Imaging , Diagnosis , Prognosis Prognostic and Predictive Values of the Immunoscore in Patients with Rectal Cancer , 2014 .

[28]  Benjamin J. Raphael,et al.  Multiplatform Analysis of 12 Cancer Types Reveals Molecular Classification within and across Tissues of Origin , 2014, Cell.

[29]  Z. Modrušan,et al.  Predicting immunogenic tumour mutations by combining mass spectrometry and exome sequencing , 2014, Nature.

[30]  R. Emerson,et al.  PD-1 blockade induces responses by inhibiting adaptive immune resistance , 2014, Nature.

[31]  H. Kohrt,et al.  Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients , 2014, Nature.

[32]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[33]  Bo Li,et al.  A general framework for analyzing tumor subclonality using SNP array and DNA sequencing data , 2014, Genome Biology.

[34]  M. Dhodapkar,et al.  Induction of Antigen-Specific Immunity with a Vaccine Targeting NY-ESO-1 to the Dendritic Cell Receptor DEC-205 , 2014, Science Translational Medicine.

[35]  S. Rosenberg,et al.  Cancer Immunotherapy Based on Mutation-Specific CD4+ T Cells in a Patient with Epithelial Cancer , 2014, Science.

[36]  Charles G. Drake,et al.  Breathing new life into immunotherapy: review of melanoma, lung and kidney cancer , 2014, Nature Reviews Clinical Oncology.

[37]  K. Cibulskis,et al.  Systematic identification of personal tumor-specific neoantigens in chronic lymphocytic leukemia. , 2014, Blood.

[38]  Ash A. Alizadeh,et al.  Abstract PR09: The prognostic landscape of genes and infiltrating immune cells across human cancers , 2015 .

[39]  N. Hacohen,et al.  Molecular and Genetic Properties of Tumors Associated with Local Immune Cytolytic Activity , 2015, Cell.

[40]  Steven J. M. Jones,et al.  Comprehensive genomic characterization of head and neck squamous cell carcinomas , 2015, Nature.

[41]  Pornpimol Charoentong,et al.  Characterization of the immunophenotypes and antigenomes of colorectal cancers reveals distinct tumor escape mechanisms and novel targets for immunotherapy , 2015, Genome Biology.

[42]  K. Akashi,et al.  The Coordinated Actions of TIM-3 on Cancer and Myeloid Cells in the Regulation of Tumorigenicity and Clinical Prognosis in Clear Cell Renal Cell Carcinomas , 2015, Cancer Immunology Research.

[43]  Ash A. Alizadeh,et al.  Robust enumeration of cell subsets from tissue expression profiles , 2015, Nature Methods.

[44]  Wolfgang Schramm,et al.  Team , 2018, Spaces of Intensity.