Multiomic profiling of checkpoint inhibitor-treated melanoma: Identifying predictors of response and resistance, and markers of biological discordance

Aguiar, 2016, The role of PD-L1 expression as a predictive biomarker in advanced non-small-cell lung cancer: a network meta-analysis, Immunotherapy, 8, 479, 10.2217/imt-2015-0002 Akbani, 2015, Genomic classification of cutaneous melanoma, Cell, 161, 1681, 10.1016/j.cell.2015.05.044 Alexandrov, 2020, The repertoire of mutational signatures in human cancer, Nature, 578, 94, 10.1038/s41586-020-1943-3 Van Allen, 2015, Genomic correlates of response to CTLA-4 blockade in metastatic melanoma, Science, 350, 207, 10.1126/science.aad0095 Anagnostou, 2020, Integrative tumor and immune cell multi-omic analyses predict response to immune checkpoint blockade in melanoma, Cell Rep. Med., 1, 100139, 10.1016/j.xcrm.2020.100139 Auslander, 2018, Robust prediction of response to immune checkpoint blockade therapy in metastatic melanoma, Nat. Med., 24, 1545, 10.1038/s41591-018-0157-9 Ayers, 2017, IFN-γ-related mRNA profile predicts clinical response to PD-1 blockade, J. Clin. Invest., 127, 2930, 10.1172/JCI91190 Azimi, 2012, Tumor-infiltrating lymphocyte grade is an independent predictor of sentinel lymph node status and survival in patients with cutaneous melanoma, J. Clin. Oncol., 30, 2678, 10.1200/JCO.2011.37.8539 Benjamini, 1995, Controlling the false discovery rate: a practical and powerful approach to multiple testing, J R Stat Soc Series B Methodol, 57, 289 Bolen, 2017, Mutation load and an effector T-cell gene signature may distinguish immunologically distinct and clinically relevant lymphoma subsets, Blood Adv., 1, 1884, 10.1182/bloodadvances.2016000786 Chakravarthy, 2018, Pan-cancer deconvolution of tumour composition using DNA methylation, Nat. Commun., 9, 3220, 10.1038/s41467-018-05570-1 Cingolani, 2012, A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3, Fly (Austin), 6, 80, 10.4161/fly.19695 Coppola, 2011, Unique ectopic lymph node-like structures present in human primary colorectal carcinoma are identified by immune gene array profiling, Am. J. Pathol., 179, 37, 10.1016/j.ajpath.2011.03.007 Cortés-Ciriano, 2020, Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing, Nat. Genet., 52, 331, 10.1038/s41588-019-0576-7 Cristescu, 2018, Pan-tumor genomic biomarkers for PD-1 checkpoint blockade–based immunotherapy, Science, 362, eaar3593, 10.1126/science.aar3593 DeLuca, 2012, RNA-SeQC: RNA-seq metrics for quality control and process optimization, Bioinformatics, 28, 1530, 10.1093/bioinformatics/bts196 Dobin, 2013, STAR: ultrafast universal RNA-seq aligner, Bioinformatics, 29, 15, 10.1093/bioinformatics/bts635 Dummer, 2020, Adjuvant dabrafenib plus trametinib versus placebo in patients with resected, BRAFV600-mutant, stage III melanoma (COMBI-AD): exploratory biomarker analyses from a randomised, phase 3 trial, Lancet Oncol., 21, 358, 10.1016/S1470-2045(20)30062-0 Dutton-Regester, 2013, Melanomas of unknown primary have a mutation profile consistent with cutaneous sun-exposed melanoma, Pigment Cell Melanoma Res., 26, 852, 10.1111/pcmr.12153 Eggermont, 2018, Adjuvant pembrolizumab versus placebo in resected stage III melanoma, N. Engl. J. Med., 378, 1789, 10.1056/NEJMoa1802357 Eisenhauer, 2009, New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1), Eur. J. Cancer, 45, 228, 10.1016/j.ejca.2008.10.026 Eroglu, 2018, High response rate to PD-1 blockade in desmoplastic melanomas, Nature, 553, 347, 10.1038/nature25187 Fehrenbacher, 2016, Atezolizumab versus docetaxel for patients with previously treated non-small-cell lung cancer (POPLAR): a multicentre, open-label, phase 2 randomised controlled trial, Lancet, 387, 1837, 10.1016/S0140-6736(16)00587-0 Gelman, 2008, Scaling regression inputs by dividing by two standard deviations, Stat. Med., 27, 2865, 10.1002/sim.3107 Gentles, 2015, The prognostic landscape of genes and infiltrating immune cells across human cancers, Nat. Med., 21, 938, 10.1038/nm.3909 Gershenwald, 2017, Melanoma staging: evidence-based changes in the American Joint committee on cancer eighth edition cancer staging manual, CA Cancer J. Clin., 67, 472, 10.3322/caac.21409 Ghoreschi, 2009, Janus kinases in immune cell signaling, Immunol. Rev., 228, 273, 10.1111/j.1600-065X.2008.00754.x Gide, 2019, Distinct immune cell populations define response to anti-PD-1 monotherapy and anti-PD-1/anti-CTLA-4 combined therapy, Cancer Cell, 35, 238, 10.1016/j.ccell.2019.01.003 Gide, 2021, Clinical and molecular heterogeneity in patients with innate resistance to anti-pd-1 +/− anti-ctla-4 immunotherapy in metastatic melanoma reveals distinct therapeutic targets, Cancers (Basel), 13, 3186, 10.3390/cancers13133186 Goodman, 2017, Tumor mutational burden as an independent predictor of response to immunotherapy in diverse cancers, Mol. Cancer Ther., 16, 2598, 10.1158/1535-7163.MCT-17-0386 Grasso, 2020, Conserved interferon-γ signaling drives clinical response to immune checkpoint blockade therapy in melanoma, Cancer Cell, 38, 500, 10.1016/j.ccell.2020.08.005 Haas, 2021, Acquired resistance to anti-MAPK targeted therapy confers an immune-evasive tumor microenvironment and cross-resistance to immunotherapy in melanoma, Nat. Cancer, 2, 693, 10.1038/s43018-021-00221-9 Hänzelmann, 2013, GSVA: gene set variation analysis for microarray and RNA-Seq data, BMC Bioinformatics, 14, 7, 10.1186/1471-2105-14-7 Hayward, 2017, Whole-genome landscapes of major melanoma subtypes, Nature, 545, 175, 10.1038/nature22071 Higgs, 2018, Interferon gamma messenger RNA Signature in tumor biopsies predicts outcomes in patients with non–small cell lung carcinoma or urothelial cancer treated with durvalumab, Clin. Cancer Res., 24, 3857, 10.1158/1078-0432.CCR-17-3451 Hoof, 2009, NetMHCpan, a method for MHC class i binding prediction beyond humans, Immunogenetics, 61, 1, 10.1007/s00251-008-0341-z Huang, 2018, Detecting presence of mutational signatures in cancer with confidence, Bioinformatics, 34, 330, 10.1093/bioinformatics/btx604 Hugo, 2015, Non-genomic and immune evolution of melanoma acquiring MAPKi resistance, Cell, 162, 1271, 10.1016/j.cell.2015.07.061 Hugo, 2016, Genomic and transcriptomic features of response to anti-PD-1 therapy in metastatic melanoma, Cell, 165, 35, 10.1016/j.cell.2016.02.065 Hundal, 2016, pVAC-Seq: a genome-guided in silico approach to identifying tumor neoantigens, Genome Med., 8, 11, 10.1186/s13073-016-0264-5 Jiang, 2018, Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response, Nat. Med., 24, 1550, 10.1038/s41591-018-0136-1 Johnson, 2003, Single-cell perforin and granzyme expression reveals the anatomical localization of effector CD8+ T cells in influenza virus-infected mice, Proc. Natl. Acad. Sci. U S A, 100, 2657, 10.1073/pnas.0538056100 Johnson, 2016, Targeted next generation sequencing Identifies markers of response to PD-1 blockade, Cancer Immunol. Res., 4, 959, 10.1158/2326-6066.CIR-16-0143 Jönsson, 2010, Gene expression profiling-based identification of molecular subtypes in stage IV melanomas with different clinical outcome, Clin. Cancer Res., 16, 3356, 10.1158/1078-0432.CCR-09-2509 Kakavand, 2015, PD-L1 expression and tumor-infiltrating lymphocytes define different subsets of MAPK inhibitor-treated melanoma patients, Clin. Cancer Res., 21, 3140, 10.1158/1078-0432.CCR-14-2023 Kalaora, 2020, Immunoproteasome expression is associated with better prognosis and response to checkpoint therapies in melanoma, Nat. Commun., 11, 896, 10.1038/s41467-020-14639-9 Kassahn, 2013, Somatic point mutation calling in low cellularity tumors, PLoS One, 8, e74380, 10.1371/journal.pone.0074380 Kreft, 2019, Efficacy of PD-1–based immunotherapy after radiologic progression on targeted therapy in stage IV melanoma, Eur. J. Cancer, 116, 207, 10.1016/j.ejca.2019.05.015 Larkin, 2019, Five-year survival with combined nivolumab and ipilimumab in advanced melanoma, N. Engl. J. Med., 381, 1535, 10.1056/NEJMoa1910836 Lee, 2008, Inferring pathway activity toward Precise disease classification, PLoS Comput. Biol., 4, e1000217, 10.1371/journal.pcbi.1000217 Lee, 2020, Transcriptional downregulation of MHC class I and melanoma de- differentiation in resistance to PD-1 inhibition, Nat. Commun., 11, 1897, 10.1038/s41467-020-15726-7 Li, 2013, Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM, ArXiv Li, 2011, RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome, BMC Bioinformatics, 12, 323, 10.1186/1471-2105-12-323 Li, 2009, The sequence alignment/map format and SAMtools, Bioinformatics, 25, 2078, 10.1093/bioinformatics/btp352 Liberzon, 2015, The molecular signatures database Hallmark gene set collection, Cell Syst., 1, 417, 10.1016/j.cels.2015.12.004 Liu, 2019, Integrative molecular and clinical modeling of clinical outcomes to PD1 blockade in patients with metastatic melanoma, Nat. Med., 25, 1916, 10.1038/s41591-019-0654-5 Mann, 2013, BRAF mutation, NRAS mutation, and the absence of an immune-related expressed gene profile predict poor outcome in patients with stage III melanoma, J. Invest. Dermatol., 133, 509, 10.1038/jid.2012.283 Martin, 2011, Cutadapt removes adapter sequences from high-throughput sequencing reads, EMBnet J., 17, 3, 10.14806/ej.17.1.200 Mason, 2020, Combined ipilimumab and nivolumab first-line and after BRAF-targeted therapy in advanced melanoma, Pigment Cell Melanoma Res., 33, 358, 10.1111/pcmr.12831 McGranahan, 2016, Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade, Science, 351, 1463, 10.1126/science.aaf1490 McKenna, 2010, The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data, Genome Res., 20, 1297, 10.1101/gr.107524.110 McLaren, 2016, The Ensembl variant effect predictor, Genome Biol., 17, 122, 10.1186/s13059-016-0974-4 Miao, 2018, Genomic correlates of response to immune checkpoint therapies in clear cell renal cell carcinoma, Science, 359, 801, 10.1126/science.aan5951 Micevic, 2019, PD-L1 methylation regulates PD-L1 expression and is associated with melanoma survival, Pigment Cell Melanoma Res., 32, 435, 10.1111/pcmr.12745 Morris, 2014, ChAMP: 450k chip analysis methylation pipeline, Bioinformatics, 30, 428, 10.1093/bioinformatics/btt684 Murali, 2012, Number of primary melanomas is an independent predictor of survival in patients with metastatic melanoma, Cancer, 118, 4519, 10.1002/cncr.27693 Newell, 2019, Whole-genome landscape of mucosal melanoma reveals diverse drivers and therapeutic targets, Nat. Commun., 10, 3163, 10.1038/s41467-019-11107-x Newman, 2015, Robust enumeration of cell subsets from tissue expression profiles, Nat. Methods, 12, 453, 10.1038/nmeth.3337 Nordlund, 2013, Genome-wide signatures of differential DNA methylation in pediatric acute lymphoblastic leukemia, Genome Biol., 14, r105, 10.1186/gb-2013-14-9-r105 Ock, 2017, Genomic landscape associated with potential response to anti-CTLA-4 treatment in cancers, Nat. Commun., 8, 1050, 10.1038/s41467-017-01018-0 Pan, 2018, A major chromatin regulator determines resistance of tumor cells to T cell-mediated killing, Science, 359, 770, 10.1126/science.aao1710 Patel, 2015, PD-L1 expression as a predictive biomarker in cancer immunotherapy, Mol. Cancer Ther., 14, 847, 10.1158/1535-7163.MCT-14-0983 Peng, 2016, Loss of PTEN promotes resistance to T cell–mediated immunotherapy, Cancer Discov., 6, 202, 10.1158/2159-8290.CD-15-0283 Pérez-Guijarro, 2020, Multimodel preclinical platform predicts clinical response of melanoma to immunotherapy, Nat. Med., 26, 781, 10.1038/s41591-020-0818-3 Pires da Silva, 2021, Ipilimumab alone or ipilimumab plus anti-PD-1 therapy in patients with metastatic melanoma resistant to anti-PD-(L)1 monotherapy: a multicentre, retrospective, cohort study, Lancet Oncol., 22, 836, 10.1016/S1470-2045(21)00097-8 Powles, 2018, TGFβ attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells, Nature, 387, 544 Raine, 2016, ascatNgs: identifying somatically acquired copy-number alterations from whole-genome sequencing data, Curr. Protoc. Bioinforma., 56, 15.9.1, 10.1002/cpbi.17 Riaz, 2016, Recurrent SERPINB3 and SERPINB4 mutations in patients who respond to anti-CTLA4 immunotherapy, Nat. Genet., 48, 1327, 10.1038/ng.3677 Riaz, 2017, Tumor and microenvironment evolution during immunotherapy with nivolumab, Cell, 171, 934, 10.1016/j.cell.2017.09.028 Rizvi, 2015, Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer, Science, 348, 124, 10.1126/science.aaa1348 Robinson, 2010, edgeR: a Bioconductor package for differential expression analysis of digital gene expression data, Bioinformatics, 26, 139, 10.1093/bioinformatics/btp616 Roh, 2017, Integrated molecular analysis of tumor biopsies on sequential CTLA-4 and PD-1 blockade reveals markers of response and resistance, Sci. Transl. Med., 9, eaah3560, 10.1126/scitranslmed.aah3560 Rooney, 2015, Molecular and genetic properties of tumors associated with local immune cytolytic activity, Cell, 160, 48, 10.1016/j.cell.2014.12.033 Rozeman, 2021, Survival and biomarker analyses from the OpACIN-neo and OpACIN neoadjuvant immunotherapy trials in stage III melanoma, Nat. Med., 27, 256, 10.1038/s41591-020-01211-7 Sade-Feldman, 2017, Resistance to checkpoint blockade therapy through inactivation of antigen presentation, Nat. Commun., 8, 1136, 10.1038/s41467-017-01062-w Sade-Feldman, 2018, Defining T cell states associated with response to checkpoint immunotherapy in melanoma, Cell, 175, 998, 10.1016/j.cell.2018.10.038 Schachter, 2017, Pembrolizumab versus ipilimumab for advanced melanoma: final overall survival results of a multicentre, randomised, open-label phase 3 study (KEYNOTE-006), Lancet, 390, 1853, 10.1016/S0140-6736(17)31601-X Shen, 2018, ARID1A deficiency promotes mutability and potentiates therapeutic antitumor immunity unleashed by immune checkpoint blockade, Nat. Med., 24, 556, 10.1038/s41591-018-0012-z Shin, 2017, Primary resistance to PD-1 blockade mediated by JAK1/2 mutations, Cancer Discov., 7, 188, 10.1158/2159-8290.CD-16-1223 Snyder, 2014, Genetic basis for clinical response to CTLA-4 blockade in melanoma, N. Engl. J. Med., 371, 2189, 10.1056/NEJMoa1406498 Spranger, 2015, Melanoma-intrinsic β-catenin signalling prevents anti-tumour immunity, Nature, 523, 231, 10.1038/nature14404 Subramanian, 2005, Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles, Proc. Natl. Acad. Sci. U S A, 102, 15545, 10.1073/pnas.0506580102 Szolek, 2014, OptiType: precision HLA typing from next-generation sequencing data, Bioinformatics, 30, 3310, 10.1093/bioinformatics/btu548 Tate, 2019, COSMIC: the catalogue of somatic mutations in cancer, Nucleic Acids Res., 47, D941, 10.1093/nar/gky1015 Teschendorff, 2013, A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data, Bioinformatics, 29, 189, 10.1093/bioinformatics/bts680 Tumeh, 2014, PD-1 blockade induces responses by inhibiting adaptive immune resistance, Nature, 515, 568, 10.1038/nature13954 Vilain, 2017, Dynamic changes in PD-L1 expression and immune infiltrates early during treatment predict response to PD-1 blockade in Melanoma, Clin. Cancer Res., 23, 5024, 10.1158/1078-0432.CCR-16-0698 Wang, 2016, BAM-matcher: a tool for rapid NGS sample matching, 2699 Weber, 2017, Adjuvant nivolumab versus ipilimumab in resected stage III or IV melanoma, N. Engl. J. Med., 377, 1824, 10.1056/NEJMoa1709030 Wolf, 2019, UVB-induced tumor heterogeneity diminishes immune response in melanoma, Cell, 179, 219, 10.1016/j.cell.2019.08.032 Yarchoan, 2017, Tumor mutational burden and response rate to PD-1 inhibition, N. Engl. J. Med., 377, 2500, 10.1056/NEJMc1713444 Zaretsky, 2016, Mutations associated with acquired resistance to PD-1 blockade in melanoma, N. Engl. J. Med., 375, 819, 10.1056/NEJMoa1604958 Zhou, 2017, Comprehensive characterization, annotation and innovative use of Infinium DNA methylation BeadChip probes, Nucleic Acids Res., 45, e22