The Immune Landscape of Cancer

Immunity, Journal Year: 2018, Volume and Issue: 48(4), P. 812 - 830.e14

Published: April 1, 2018

We performed an extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled TCGA. Across types, we identified six immune subtypes—wound healing, IFN-γ dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-β dominant—characterized differences in macrophage or signatures, Th1:Th2 cell ratio, extent intratumoral heterogeneity, aneuploidy, neoantigen load, overall proliferation, expression immunomodulatory genes, prognosis. Specific driver mutations correlated with lower (CTNNB1, NRAS, IDH1) higher (BRAF, TP53, CASP8) leukocyte levels across all cancers. Multiple control modalities the intracellular extracellular networks (transcription, microRNAs, copy number, epigenetic processes) were involved tumor-immune interactions, both within subtypes. Our immunogenomics pipeline to characterize these heterogeneous resulting are intended serve as a resource for future targeted studies further advance field.

Language: Английский

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Maftools: efficient and comprehensive analysis of somatic variants in cancer

Genome Research, Journal Year: 2018, Volume and Issue: 28(11), P. 1747 - 1756

Published: Oct. 19, 2018

Numerous large-scale genomic studies of matched tumor-normal samples have established the somatic landscapes most cancer types. However, downstream analysis data from mutations entails a number computational and statistical approaches, requiring usage independent software numerous tools. Here, we describe an R Bioconductor package, Maftools, which offers multitude visualization modules that are commonly used in studies, including driver gene identification, pathway, signature, enrichment, association analyses. Maftools only requires variants Mutation Annotation Format (MAF) is larger alignment files. With implementation well-established methods, facilitates data-driven research comparative to discover novel results publicly available sets. In present study, using three well-annotated cohorts The Cancer Genome Atlas (TCGA), application reproduce known results. More importantly, show can also be uncover findings through integrative analysis.

Language: Английский

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Oncogenic Signaling Pathways in The Cancer Genome Atlas

Cell, Journal Year: 2018, Volume and Issue: 173(2), P. 321 - 337.e10

Published: April 1, 2018

Highlights•Alteration map of 10 signaling pathways across 9,125 samples from 33 cancer types•Reusable, curated pathway templates that include a catalogue driver genes•57% tumors have at least one potentially actionable alteration in these pathways•Co-occurrence alterations suggests combination therapy opportunitiesSummaryGenetic control cell-cycle progression, apoptosis, and cell growth are common hallmarks cancer, but the extent, mechanisms, co-occurrence differ between individual tumor types. Using mutations, copy-number changes, mRNA expression, gene fusions DNA methylation profiled by The Cancer Genome Atlas (TCGA), we analyzed mechanisms patterns somatic ten canonical pathways: cycle, Hippo, Myc, Notch, Nrf2, PI-3-Kinase/Akt, RTK-RAS, TGFβ signaling, p53 β-catenin/Wnt. We charted detailed landscape types, stratified into 64 subtypes, identified mutual exclusivity. Eighty-nine percent had pathways, 57% targetable currently available drugs. Thirty multiple alterations, indicating opportunities for therapy.Graphical abstract

Language: Английский

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Comprehensive Characterization of Cancer Driver Genes and Mutations

Cell, Journal Year: 2018, Volume and Issue: 173(2), P. 371 - 385.e18

Published: April 1, 2018

Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithms to identify now exist, but systematic attempts combine and optimize them on large datasets are few. We report a PanCancer PanSoftware analysis spanning 9,423 tumor exomes (comprising all 33 of The Cancer Genome Atlas projects) using 26 computational tools catalog driver genes mutations. 299 with implications regarding their anatomical sites cancer/cell types. Sequence- structure-based analyses identified >3,400 putative missense mutations supported by multiple lines evidence. Experimental validation confirmed 60%–85% predicted as likely drivers. found that >300 MSI tumors associated high PD-1/PD-L1, 57% analyzed harbor clinically actionable events. Our study represents the most comprehensive discovery date will serve blueprint future biological clinical endeavors.

Language: Английский

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Defining T Cell States Associated with Response to Checkpoint Immunotherapy in Melanoma

Cell, Journal Year: 2018, Volume and Issue: 175(4), P. 998 - 1013.e20

Published: Nov. 1, 2018

Language: Английский

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Genomic and Functional Approaches to Understanding Cancer Aneuploidy

Cancer Cell, Journal Year: 2018, Volume and Issue: 33(4), P. 676 - 689.e3

Published: April 1, 2018

Aneuploidy, whole chromosome or arm imbalance, is a near-universal characteristic of human cancers. In 10,522 cancer genomes from The Cancer Genome Atlas, aneuploidy was correlated with TP53 mutation, somatic mutation rate, and expression proliferation genes. Aneuploidy anti-correlated immune signaling genes, due to decreased leukocyte infiltrates in high-aneuploidy samples. Chromosome arm-level alterations show cancer-specific patterns, including loss 3p squamous We applied genome engineering delete lung cells, causing rescued part by 3 duplication. This study defines genomic phenotypic correlates provides an experimental approach aneuploidy.

Language: Английский

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RETRACTED ARTICLE: Microbiome analyses of blood and tissues suggest cancer diagnostic approach

Nature, Journal Year: 2020, Volume and Issue: 579(7800), P. 567 - 574

Published: March 11, 2020

Language: Английский

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Conserved pan-cancer microenvironment subtypes predict response to immunotherapy

Cancer Cell, Journal Year: 2021, Volume and Issue: 39(6), P. 845 - 865.e7

Published: May 20, 2021

Language: Английский

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High tumor mutation burden fails to predict immune checkpoint blockade response across all cancer types

Annals of Oncology, Journal Year: 2021, Volume and Issue: 32(5), P. 661 - 672

Published: March 18, 2021

•TMB-H failed to predict improved or clinically relevant response ICB in all cancer types.•Cancer types where TMB-H does not generally show no relationship between tumor neoantigen load and CD8 T-cell infiltration.•Further studies should be carried out before application of as a biomarker for types. BackgroundHigh mutation burden (TMB-H) has been proposed predictive immune checkpoint blockade (ICB), largely due the potential mutations generate immunogenic neoantigens. Despite recent pan-cancer approval treatment any tumor, assessed by targeted FoundationOne CDx assay nine types, utility this fully demonstrated across cancers.Patients methodsData from over 10 000 patient tumors included The Cancer Genome Atlas were used compare approaches determine TMB identify correlation predicted T cells. Association with outcomes was analyzed both objective rates (ORRs, N = 1551) overall survival (OS, 1936).ResultsIn levels positively correlated load, such melanoma, lung, bladder cancers, exhibited 39.8% ORR [95% confidence interval (CI) 34.9-44.8], which significantly higher than that observed low (TMB-L) [odds ratio (OR) 4.1, 95% CI 2.9-5.8, P < 2 × 10−16]. In showed breast cancer, prostate glioma, achieve 20% (ORR 15.3%, 9.2-23.4, 0.95), lower relative TMB-L (OR 0.46, 0.24-0.88, 0.02). Bulk ORRs different two categories (P 0.10) cohorts assessed. Equivalent results obtained analyzing OS treating continuous variable.ConclusionsOur analysis support solid Further type-specific are warranted. High cancers. Data 1936). variable. Our

Language: Английский

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Comprehensive Analysis of Alternative Splicing Across Tumors from 8,705 Patients

Cancer Cell, Journal Year: 2018, Volume and Issue: 34(2), P. 211 - 224.e6

Published: Aug. 1, 2018

Our comprehensive analysis of alternative splicing across 32 The Cancer Genome Atlas cancer types from 8,705 patients detects events and tumor variants by reanalyzing RNA whole-exome sequencing data. Tumors have up to 30% more than normal samples. Association somatic with confirmed known trans associations in SF3B1 U2AF1 identified additional trans-acting (e.g., TADA1, PPP2R1A). Many tumors thousands not detectable samples; on average, we ≈930 exon-exon junctions ("neojunctions") typically found GTEx normals. From Clinical Proteomic Tumor Analysis Consortium data available for breast ovarian samples, ≈1.7 neojunction- ≈0.6 single nucleotide variant-derived peptides per sample that are also predicted major histocompatibility complex-I binders ("putative neoantigens").

Language: Английский

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