TIMER: A Web Server for Comprehensive Analysis of Tumor-Infiltrating Immune Cells

Cancer Research, Journal Year: 2017, Volume and Issue: 77(21), P. e108 - e110

Published: Oct. 31, 2017

Recent clinical successes of cancer immunotherapy necessitate the investigation interaction between malignant cells and host immune system. However, elucidation complex tumor-immune interactions presents major computational experimental challenges. Here, we present Tumor Immune Estimation Resource (TIMER; cistrome.shinyapps.io/timer) to comprehensively investigate molecular characterization interactions. Levels six tumor-infiltrating subsets are precalculated for 10,897 tumors from 32 types. TIMER provides 6 analytic modules that allow users interactively explore associations infiltrates a wide spectrum factors, including gene expression, outcomes, somatic mutations, copy number alterations. user-friendly web interface dynamic analysis visualization these associations, which will be broad utilities researchers. Cancer Res; 77(21); e108-10. ©2017 AACR.

Language: Английский

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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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Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response

Nature Medicine, Journal Year: 2018, Volume and Issue: 24(10), P. 1550 - 1558

Published: Aug. 13, 2018

Language: Английский

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xCell: digitally portraying the tissue cellular heterogeneity landscape

Genome biology, Journal Year: 2017, Volume and Issue: 18(1)

Published: Nov. 15, 2017

Tissues are complex milieus consisting of numerous cell types. Several recent methods have attempted to enumerate subsets from transcriptomes. However, the available used limited sources for training and give only a partial portrayal full cellular landscape. Here we present xCell, novel gene signature-based method, use it infer 64 immune stromal We harmonized 1822 pure human type transcriptomes various employed curve fitting approach linear comparison types introduced spillover compensation technique separating them. Using extensive in silico analyses cytometry immunophenotyping, show that xCell outperforms other methods. is at http://xCell.ucsf.edu/ .

Language: Английский

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The evolving landscape of biomarkers for checkpoint inhibitor immunotherapy

Nature reviews. Cancer, Journal Year: 2019, Volume and Issue: 19(3), P. 133 - 150

Published: Feb. 12, 2019

Language: Английский

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Immune Checkpoint Inhibitors for the Treatment of Cancer: Clinical Impact and Mechanisms of Response and Resistance

Annual Review of Pathology Mechanisms of Disease, Journal Year: 2020, Volume and Issue: 16(1), P. 223 - 249

Published: Nov. 16, 2020

Immune checkpoint inhibitors (ICIs) have made an indelible mark in the field of cancer immunotherapy. Starting with approval anti-cytotoxic T lymphocyte-associated protein 4 (anti-CTLA-4) for advanced-stage melanoma 2011, ICIs-which now also include antibodies against programmed cell death 1 (PD-1) and its ligand (PD-L1)-quickly gained US Food Drug Administration treatment a wide array types, demonstrating unprecedented extension patient survival. However, despite success ICIs, resistance to these agents restricts number patients able achieve durable responses, immune-related adverse events complicate treatment. Thus, better understanding requirements effective safe antitumor immune response following ICI therapy is needed. Studies both tumoral systemic changes system yielded insight into basis efficacy resistance. Ultimately, by building on insights, researchers should be combine ICIs other agents, or design new immunotherapies, broader more as well greater safety. Here, we review history clinical utility mechanisms therapy, local associated outcome.

Language: Английский

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Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data

Genome Medicine, Journal Year: 2019, Volume and Issue: 11(1)

Published: May 24, 2019

We introduce quanTIseq, a method to quantify the fractions of ten immune cell types from bulk RNA-sequencing data. quanTIseq was extensively validated in blood and tumor samples using simulated, flow cytometry, immunohistochemistry data.quanTIseq analysis 8000 revealed that cytotoxic T infiltration is more strongly associated with activation CXCR3/CXCL9 axis than mutational load deconvolution-based scores have prognostic value several solid cancers. Finally, we used show how kinase inhibitors modulate contexture reveal immune-cell underlie differential patients' responses checkpoint blockers.Availability: available at http://icbi.at/quantiseq .

Language: Английский

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Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data

eLife, Journal Year: 2017, Volume and Issue: 6

Published: Nov. 13, 2017

Immune cells infiltrating tumors can have important impact on tumor progression and response to therapy. We present an efficient algorithm simultaneously estimate the fraction of cancer immune cell types from bulk gene expression data. Our method integrates novel profiles each major non-malignant type found in tumors, renormalization based cell-type-specific mRNA content, ability consider uncharacterized possibly highly variable types. Feasibility is demonstrated by validation with flow cytometry, immunohistochemistry single-cell RNA-Seq analyses human melanoma colorectal specimens. Altogether, our work not only improves accuracy but also broadens scope absolute predictions data, provides a unique experimental benchmark for immunogenomics research (http://epic.gfellerlab.org).

Language: Английский

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Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Cell Reports, Journal Year: 2018, Volume and Issue: 23(1), P. 181 - 193.e7

Published: April 1, 2018

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings tumor-infiltrating lymphocytes (TILs) based on H&E from 13 tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches images. Affinity propagation revealed local spatial structure in patterns correlation with overall survival. map structural were grouped standard histopathological parameters. enriched particular T cell subpopulations molecular measures. densities differentially among types, immune subtypes, implying that infiltrate state could reflect aberration states. Obtaining lymphocytic linked rich genomic characterization demonstrates one use for image archives insights into tumor-immune microenvironment.

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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