TIMER2.0 for analysis of tumor-infiltrating immune cells

Nucleic Acids Research, Journal Year: 2020, Volume and Issue: 48(W1), P. W509 - W514

Published: May 17, 2020

Abstract Tumor progression and the efficacy of immunotherapy are strongly influenced by composition abundance immune cells in tumor microenvironment. Due to limitations direct measurement methods, computational algorithms often used infer cell from bulk transcriptome profiles. These estimated infiltrate populations have been associated with genomic transcriptomic changes tumors, providing insight into tumor–immune interactions. However, such investigations on large-scale public data remain challenging. To lower barriers for analysis complex interactions, we significantly improved our previous web platform TIMER. Instead just using one algorithm, TIMER2.0 (http://timer.cistrome.org/) provides more robust estimation infiltration levels The Cancer Genome Atlas (TCGA) or user-provided profiles six state-of-the-art algorithms. four modules investigating associations between infiltrates genetic clinical features, exploring cancer-related TCGA cohorts. Each module can generate a functional heatmap table, enabling user easily identify significant multiple cancer types simultaneously. Overall, server comprehensive visualization functions infiltrating cells.

Language: Английский

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

Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology

Bioinformatics, Journal Year: 2019, Volume and Issue: 35(14), P. i436 - i445

Published: May 9, 2019

The composition and density of immune cells in the tumor microenvironment (TME) profoundly influence progression success anti-cancer therapies. Flow cytometry, immunohistochemistry staining or single-cell sequencing are often unavailable such that we rely on computational methods to estimate immune-cell from bulk RNA-sequencing (RNA-seq) data. Various have been proposed recently, yet their capabilities limitations not evaluated systematically. A general guideline leading research community through cell type deconvolution is missing.We developed a systematic approach for benchmarking assessed accuracy tools at estimating nine different immune- stromal RNA-seq samples. We used dataset ∼11 000 TME simulate samples known proportions, validated results using independent, publicly available gold-standard estimates. This allowed us analyze condense more than hundred thousand predictions provide an exhaustive evaluation across seven over types ∼1800 five simulated real-world datasets. demonstrate performs high well-defined cell-type signatures propose how fuzzy can be improved. suggest future efforts should dedicated refining population definitions finding reliable signatures.A snakemake pipeline reproduce benchmark https://github.com/grst/immune_deconvolution_benchmark. An R package allows perform integrated (https://grst.github.io/immunedeconv).Supplementary data Bioinformatics online.

Language: Английский

EPIC: A Tool to Estimate the Proportions of Different Cell Types from Bulk Gene Expression Data

Methods in molecular biology, Journal Year: 2020, Volume and Issue: unknown, P. 233 - 248

Published: Jan. 1, 2020

Language: Английский

Melanoma plasticity and phenotypic diversity: therapeutic barriers and opportunities

Genes & Development, Journal Year: 2019, Volume and Issue: 33(19-20), P. 1295 - 1318

Published: Oct. 1, 2019

An incomplete view of the mechanisms that drive metastasis, primary cause cancer-related death, has been a major barrier to development effective therapeutics and prognostic diagnostics. Increasing evidence indicates interplay between microenvironment, genetic lesions, cellular plasticity drives metastatic cascade resistance therapies. Here, using melanoma as model, we outline diversity trajectories cell states during dissemination therapy exposure, highlight how understanding magnitude dynamics nongenetic reprogramming in space time at single-cell resolution can be exploited develop therapeutic strategies capitalize on tumor evolution.

Language: Английский

A Gene Signature Predicting Natural Killer Cell Infiltration and Improved Survival in Melanoma Patients

Cancer Immunology Research, Journal Year: 2019, Volume and Issue: 7(7), P. 1162 - 1174

Published: May 14, 2019

Natural killer (NK) cell activity is essential for initiating antitumor responses and may be linked to immunotherapy success. NK cells other innate immune components could exploitable cancer treatment, which drives the need tools methods that identify therapeutic avenues. Here, we extend our gene-set scoring method singscore investigate infiltration by applying RNA-seq analysis samples from bulk tumors. Computational have been developed deconvolution of types within solid We taken gene signatures several such tools, then curated list using a comparative tumors types. Using data The Cancer Genome Atlas (TCGA), show patients with metastatic cutaneous melanoma an improved survival rate if their tumor shows evidence infiltration. Furthermore, these effects are enhanced in higher expression genes encode stimuli as cytokine IL15 this signature, examine transcriptomic stromal influence penetrance into Our results provide play role regulation human highlight potential associated increased activity. computational identifies putative targets value boosting immunity.

Language: Английский

Tumor-Infiltrating Lymphocytes and Their Prognostic Value in Cutaneous Melanoma

Frontiers in Immunology, Journal Year: 2020, Volume and Issue: 11

Published: Sept. 10, 2020

Recent breakthroughs in tumor immunotherapy such as immune checkpoint blockade (ICB) antibodies, have demonstrated the capacity of system to fight cancer a number malignancies melanoma and lung cancer. The numbers, localization phenotypes tumor-infiltrating lymphocytes (TIL) are not only predictive response but also key modulators disease progression. In this review, we focus on TIL profiling cutaneous using histopathological approaches highlight observed prognostic value primary subsets. quantification formalin-fixed samples ranges from visual scoring lymphocytic infiltrates H&E multiplex immunohistochemistry immunofluorescence followed by enumeration image analysis software. Nevertheless, current literature primarily relies upon single marker analyses major lymphocyte subsets conventional T cells (CD3, CD4, CD8), regulatory (FOXP3) B (CD20). We review studies associations between patient survival. cover recent findings with respect existence ectopic lymphoid aggregates found TME which termed tertiary structures (TLS) generally positive feature. addition their significance, various sub-populations has been reported predict patient's ICB. Thus, potential patients receiving ICB discussed. Finally, describe recently developed state-of-the-art for infiltrating digital pathology algorithms (e.g. Immunoscore) proteomics-based immunophenotyping platforms imaging mass cytometry). Translating these novel technologies revolutionize immunopathology leading altering our understanding immunology dramatically improving outcomes patients.

Language: Английский

Immune cell infiltration as a biomarker for the diagnosis and prognosis of stage I–III colon cancer

Cancer Immunology Immunotherapy, Journal Year: 2018, Volume and Issue: 68(3), P. 433 - 442

Published: Dec. 18, 2018

Tumour-infiltrating immune cells are a source of important prognostic information for patients with resectable colon cancer. We developed novel model based on systematic assessments the landscape inferred from bulk tumor transcriptomes stage I-III cancer patients. The "Cell type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT)" algorithm was used to estimate fraction 22 cell types six microarray public datasets. random forest method and least absolute shrinkage selection operator were then establish immunoscores diagnosis prognosis. comparing compositions in samples 870 70 normal controls, we constructed diagnostic model, designated risk score (dIRS), that showed high specificity sensitivity both training [area under curve (AUC) = 0.98, p < 0.001] validation (AUC 0.96, 0.001) sets. also established (pIRS) found be an independent factor relapse-free survival every series (training: HR 2.23; validation: 1.65; entire: 2.01; 0.001 all), which better value than TNM stage. In addition, integration pIRS clinical characteristics composite nomogram improved accuracy relapse prediction, providing higher net benefit stage, well-fitted calibration curves. proposed dIRS models represent promising signatures prognosis prediction

Language: Английский

A guide for the diagnosis of rare and undiagnosed disease: beyond the exome

Genome Medicine, Journal Year: 2022, Volume and Issue: 14(1)

Published: Feb. 28, 2022

Abstract Rare diseases affect 30 million people in the USA and more than 300–400 worldwide, often causing chronic illness, disability, premature death. Traditional diagnostic techniques rely heavily on heuristic approaches, coupling clinical experience from prior rare disease presentations with medical literature. A large number of patients remain undiagnosed for years many even die without an accurate diagnosis. In recent years, gene panels, microarrays, exome sequencing have helped to identify molecular cause such diseases. These technologies allowed diagnoses a sizable proportion (25–35%) patients, actionable findings. However, these undiagnosed. this review, we focus that can be adopted if is unrevealing. We discuss benefits whole genome additional benefit may offered by long-read technology, pan-genome reference, transcriptomics, metabolomics, proteomics, methyl profiling. highlight computational methods help regionally distant similar phenotypes or genetic mutations. Finally, describe approaches automate accelerate genomic analysis. The strategies discussed here are intended serve as guide clinicians researchers next steps when encountering non-diagnostic exomes.

Language: Английский

The tale of TILs in breast cancer: A report from The International Immuno-Oncology Biomarker Working Group

npj Breast Cancer, Journal Year: 2021, Volume and Issue: 7(1)

Published: Dec. 1, 2021

The advent of immune-checkpoint inhibitors (ICI) in modern oncology has significantly improved survival several cancer settings. A subgroup women with breast (BC) immunogenic infiltration lymphocytes expression programmed death-ligand 1 (PD-L1). These patients may potentially benefit from ICI targeting the death (PD-1)/PD-L1 signaling axis. use tumor-infiltrating (TILs) as predictive and prognostic biomarkers been under intense examination. Emerging data suggest that TILs are associated response to both cytotoxic treatments immunotherapy, particularly for triple-negative BC. In this review International Immuno-Oncology Biomarker Working Group, we discuss (a) biological understanding TILs, (b) their analytical clinical validity efforts toward utility BC, (c) current status PD-L1 TIL testing across different continents, including experiences low-to-middle-income countries, incorporating also view a patient advocate. This information will help set stage future approaches optimize utilization analysis

Language: Английский