Pan-cancer immunogenomic analyses reveal genotype-immunophenotype relationships and predictors of response to checkpoint blockade

[1]  John Quackenbush,et al.  Genesis: cluster analysis of microarray data , 2002, Bioinform..

[2]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[3]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[4]  C. Blank,et al.  Immune resistance orchestrated by the tumor microenvironment , 2006, Immunological reviews.

[5]  Z. Trajanoski,et al.  Type, Density, and Location of Immune Cells Within Human Colorectal Tumors Predict Clinical Outcome , 2006, Science.

[6]  O. Lund,et al.  NetMHCpan, a Method for Quantitative Predictions of Peptide Binding to Any HLA-A and -B Locus Protein of Known Sequence , 2007, PloS one.

[7]  Joseph T. Glessner,et al.  PennCNV: an integrated hidden Markov model designed for high-resolution copy number variation detection in whole-genome SNP genotyping data. , 2007, Genome research.

[8]  Geoffrey E. Hinton,et al.  Visualizing Data using t-SNE , 2008 .

[9]  Ben S. Wittner,et al.  Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1 , 2009, Nature.

[10]  Pornpimol Charoentong,et al.  ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks , 2009, Bioinform..

[11]  Andrew J. G. Simpson,et al.  CTdatabase: a knowledge-base of high-throughput and curated data on cancer-testis antigens , 2008, Nucleic Acids Res..

[12]  F. Garrido,et al.  “Hard” and “soft” lesions underlying the HLA class I alterations in cancer cells: Implications for immunotherapy , 2010, International journal of cancer.

[13]  C. Perou,et al.  Allele-specific copy number analysis of tumors , 2010, Proceedings of the National Academy of Sciences.

[14]  Zlatko Trajanoski,et al.  Histopathologic-based prognostic factors of colorectal cancers are associated with the state of the local immune reaction. , 2011, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[15]  G. Getz,et al.  Accurate estimation of homologue-specific DNA concentration-ratios in cancer samples allows long-range haplotyping , 2011 .

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

[17]  P. A. Futreal,et al.  Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. , 2012, The New England journal of medicine.

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

[19]  Benjamin J. Raphael,et al.  Mutational landscape and significance across 12 major cancer types , 2013, Nature.

[20]  E. Lander,et al.  Lessons from the Cancer Genome , 2013, Cell.

[21]  A. McKenna,et al.  Evolution and Impact of Subclonal Mutations in Chronic Lymphocytic Leukemia , 2012, Cell.

[22]  M. Stratton,et al.  Tumor exome analysis reveals neoantigen-specific T-cell reactivity in an ipilimumab-responsive melanoma. , 2013, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[23]  Pia Kvistborg,et al.  The cancer antigenome , 2012, The EMBO journal.

[24]  Steven A. Roberts,et al.  Mutational heterogeneity in cancer and the search for new cancer genes , 2014 .

[25]  Jimmy Lin,et al.  Mining Exomic Sequencing Data to Identify Mutated Antigens Recognized by Adoptively Transferred Tumor-reactive T cells , 2013, Nature Medicine.

[26]  A. Bouchard-Côté,et al.  PyClone: statistical inference of clonal population structure in cancer , 2014, Nature Methods.

[27]  Benjamin Schubert,et al.  OptiType: precision HLA typing from next-generation sequencing data , 2014, Bioinform..

[28]  P. Coulie,et al.  Tumour antigens recognized by T lymphocytes: at the core of cancer immunotherapy , 2014, Nature Reviews Cancer.

[29]  Steven J. M. Jones,et al.  Integrated Genomic Characterization of Papillary Thyroid Carcinoma , 2014, Cell.

[30]  Noemi Andor,et al.  EXPANDS: expanding ploidy and allele frequency on nested subpopulations , 2013, Bioinform..

[31]  Scott D. Brown,et al.  Neo-antigens predicted by tumor genome meta-analysis correlate with increased patient survival , 2014, Genome research.

[32]  E. Oikonomou,et al.  BRAF vs RAS oncogenes: are mutations of the same pathway equal? differential signalling and therapeutic implications , 2014, Oncotarget.

[33]  Michael A. Choti,et al.  Whole-exome sequencing of pancreatic cancer defines genetic diversity and therapeutic targets , 2015, Nature Communications.

[34]  S. Gabriel,et al.  Genomic correlates of response to CTLA-4 blockade in metastatic melanoma , 2015, Science.

[35]  Steven J. M. Jones,et al.  Genomic Classification of Cutaneous Melanoma , 2015, Cell.

[36]  J. Gartner,et al.  Immunogenicity of somatic mutations in human gastrointestinal cancers , 2015, Science.

[37]  J. Wolchok PD-1 Blockers , 2015, Cell.

[38]  D. Schadendorf,et al.  Pooled Analysis of Long-Term Survival Data From Phase II and Phase III Trials of Ipilimumab in Unresectable or Metastatic Melanoma. , 2015, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[39]  Michael P. Schroeder,et al.  In silico prescription of anticancer drugs to cohorts of 28 tumor types reveals targeting opportunities. , 2015, Cancer cell.

[40]  M. Maio,et al.  Antitumor activity of epigenetic immunomodulation combined with CTLA-4 blockade in syngeneic mouse models , 2015, Oncoimmunology.

[41]  Trevor J Pugh,et al.  Oncotator: Cancer Variant Annotation Tool , 2015, Human mutation.

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

[43]  L. Spinelli,et al.  BubbleGUM: automatic extraction of phenotype molecular signatures and comprehensive visualization of multiple Gene Set Enrichment Analyses , 2015, BMC Genomics.

[44]  T. Schumacher,et al.  Neoantigens in cancer immunotherapy , 2015, Science.

[45]  Martin L. Miller,et al.  Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer , 2015, Science.

[46]  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.

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

[48]  Chris Sander,et al.  An Integrated Metabolic Atlas of Clear Cell Renal Cell Carcinoma. , 2016, Cancer cell.

[49]  Pornpimol Charoentong,et al.  Computational genomics tools for dissecting tumour–immune cell interactions , 2016, Nature Reviews Genetics.

[50]  Antoni Ribas,et al.  The “cancer immunogram” , 2016, Science.

[51]  Nicolai J. Birkbak,et al.  Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade , 2016, Science.

[52]  S. Ganesan,et al.  Biomarkers for Immunotherapy: Current Developments and Challenges. , 2016, American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting.

[53]  J. Sosman,et al.  Genomic and Transcriptomic Features of Response to Anti-PD-1 Therapy in Metastatic Melanoma , 2016, Cell.

[54]  M. Vetizou,et al.  Resistance Mechanisms to Immune-Checkpoint Blockade in Cancer: Tumor-Intrinsic and -Extrinsic Factors. , 2016, Immunity.

[55]  Nuno A. Fonseca,et al.  Expression Atlas update—an integrated database of gene and protein expression in humans, animals and plants , 2015, Nucleic Acids Res..

[56]  Jun S. Liu,et al.  Comprehensive analyses of tumor immunity: implications for cancer immunotherapy , 2016, Genome Biology.

[57]  C. Perou,et al.  Genomic Analysis of Immune Cell Infiltrates Across 11 Tumor Types. , 2016, Journal of the National Cancer Institute.