Best practices for bioinformatic characterization of neoantigens for clinical utility

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

Published: Aug. 28, 2019

Neoantigens are newly formed peptides created from somatic mutations that capable of inducing tumor-specific T cell recognition. Recently, researchers and clinicians have leveraged next generation sequencing technologies to identify neoantigens create personalized immunotherapies for cancer treatment. To a vaccine, must be computationally predicted matched tumor-normal data, then ranked according their capability in stimulating response. This candidate neoantigen prediction process involves multiple steps, including mutation identification, HLA typing, peptide processing, peptide-MHC binding prediction. The general workflow has been utilized many preclinical clinical trials, but there is no current consensus approach few established best practices. In this article, we review recent discoveries, summarize the available computational tools, provide analysis considerations each step, prediction, prioritization, delivery, validation methods. addition reviewing state analysis, practical guidance, specific recommendations, extensive discussion critical concepts points confusion practice characterization use. Finally, outline necessary areas development, need improve class II typing accuracy, expand software support diverse sources, incorporate response data algorithms. ultimate goal workflows vaccines patient outcomes types.

Language: Английский

m⁶A regulator-based methylation modification patterns characterized by distinct tumor microenvironment immune profiles in colon cancer

Theranostics, Journal Year: 2020, Volume and Issue: 11(5), P. 2201 - 2217

Published: Dec. 16, 2020

Recent studies have highlighted the biological significance of RNA N6-methyladenosine (m6A) modification in tumorigenicity and progression. However, it remains unclear whether m6A modifications also potential roles immune regulation tumor microenvironment (TME) formation. Methods: In this study, we curated 23 regulators performed consensus molecular subtyping with NMF algorithm to determine patterns m6A-related gene signature colon cancer (CC). The ssGSEA CIBERSORT algorithms were employed quantify relative infiltration levels various cell subsets. An PCA based m6Sig scoring scheme was used evaluate individual tumors an response. Results: Three distinct identified among 1307 CC samples, which associated different clinical outcomes pathways. TME characterization revealed that highly consistent three known profiles: immune-inflamed, immune-excluded, immune-desert, respectively. Based on score, extracted from genes, patients can be divided into high low score subgroups. Patients lower characterized by prolonged survival time enhanced infiltration. Further analysis indicated correlated greater mutation loads, PD-L1 expression, higher rates SMGs (e.g., PIK3CA SMAD4). addition, scores showed a better responses durable benefits independent immunotherapy cohorts. Conclusions: This study highlights is significantly diversity complexity. Quantitatively evaluating will strengthen our understanding characteristics promote more effective strategies.

Language: Английский

Deconvoluting tumor-infiltrating immune cells from RNA-seq data using quanTIseq

Methods in enzymology on CD-ROM/Methods in enzymology, Journal Year: 2019, Volume and Issue: unknown, P. 261 - 285

Published: June 22, 2019

Language: Английский

Pan-Cancer Analysis of Immune Cell Infiltration Identifies a Prognostic Immune-Cell Characteristic Score (ICCS) in Lung Adenocarcinoma

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

Published: June 30, 2020

Background: The tumor microenvironment (TME) consists of heterogeneous cell populations, including malignant cells and nonmalignant that support proliferation, invasion, metastasis through extensive crosstalk. intra-tumor immune landscape is a critical factor influencing patient survival response to immunotherapy. Methods: Gene expression data were downloaded from Cancer Genome Atlas Expression Omnibus databases. Immune infiltration was determined by single-sample gene set enrichment analysis (ssGSEA) depending on the integrated sets published studies. Univariate used determine prognostic value infiltrated cells. LASSO regression performed screen for most survival-relevant An immune-cell characteristic score (ICCS) model constructed using multivariate Cox analysis. Results: patterns across 32 cancer types identified, patients in high cluster had worse overall (OS) but better progression-free interval (PFI) compared low cluster. However, showed inconsistent type. High indicated prognosis LGG, GBM, UVM, favorable ACC, CESE, CHOL, HNSC, LIHC, LUAD, SARC, SKCM. LUAD significantly influenced 13 types, with all Th2 correlating prognosis. ICCS based 6 populations generated classified into low- high-ICCS groups good poor respectively. stratified further revealed an independent LUAD. Conclusions: quantified considerable heterogeneity observed relevance these different types. competent performance, which can deepen our understanding lung adenocarcinoma have implications

Language: Английский

Comprehensive Benchmarking and Integration of Tumor Microenvironment Cell Estimation Methods

Cancer Research, Journal Year: 2019, Volume and Issue: 79(24), P. 6238 - 6246

Published: Oct. 22, 2019

Various computational approaches have been developed for estimating the relative abundance of different cell types in tumor microenvironment (TME) using bulk RNA data. However, a comprehensive comparison across diverse datasets that objectively evaluates performance these has not conducted. Here, we benchmarked seven widely used tools and gene sets introduced Consensus

Language: Английский

Computational recognition of lncRNA signature of tumor-infiltrating B lymphocytes with potential implications in prognosis and immunotherapy of bladder cancer

Briefings in Bioinformatics, Journal Year: 2020, Volume and Issue: 22(3)

Published: March 9, 2020

Abstract Long noncoding RNAs (lncRNAs) have been associated with cancer immunity regulation and the tumor microenvironment (TME). However, functions of lncRNAs tumor-infiltrating B lymphocytes (TIL-Bs) their clinical significance not yet fully elucidated. In present study, a machine learning-based computational framework is presented for identification lncRNA signature TIL-Bs (named ‘TILBlncSig’) through integrative analysis immune, profiles. The TILBlncSig comprising eight (TNRC6C-AS1, WASIR2, GUSBP11, OGFRP1, AC090515.2, PART1, MAFG-DT LINC01184) was identified from list 141 B-cell-specific lncRNAs. capable distinguishing worse compared improved survival outcomes across different independent patient datasets also other covariates. Functional characterization revealed it to be an indicator infiltration mononuclear immune cells (i.e. natural killer cells, B-cells mast cells), hallmarks cancer, as well immunosuppressive phenotype. Furthermore, predictive value outcome immunotherapy response patients anti-programmed death-1 (PD-1) therapy added significant power current checkpoint gene markers. study has highlighted cell in TME RNA perspective strengthened potential application biomarkers response, which warrants further investigation.

Language: Английский

Next-generation computational tools for interrogating cancer immunity

Nature Reviews Genetics, Journal Year: 2019, Volume and Issue: 20(12), P. 724 - 746

Published: Sept. 12, 2019

Language: Английский

Applications of single-cell and bulk RNA sequencing in onco-immunology

European Journal of Cancer, Journal Year: 2021, Volume and Issue: 149, P. 193 - 210

Published: April 16, 2021

The rising interest for precise characterization of the tumour immune contexture has recently brought forward high potential RNA sequencing (RNA-seq) in identifying molecular mechanisms engaged response to immunotherapy. In this review, we provide an overview major principles single-cell and conventional (bulk) RNA-seq applied onco-immunology. We describe standard preprocessing statistical analyses data obtained from such techniques highlight some computational challenges relative individual cells. notably examples gene expression as differential analysis, dimensionality reduction, clustering enrichment analysis. Additionally, used public sets exemplify how deconvolution algorithms can identify quantify multiple subpopulations either bulk or RNA-seq. give machine deep learning models predict patient outcomes treatment effect high-dimensional data. Finally, balance strengths weaknesses regarding their applications clinic.

Language: Английский

Innate Immunity and Cancer Pathophysiology

Annual Review of Pathology Mechanisms of Disease, Journal Year: 2021, Volume and Issue: 17(1), P. 425 - 457

Published: Nov. 18, 2021

Chronic inflammation increases the risk of several cancers, including gastric, colon, and hepatic cancers. Conversely, tumors, similar to tissue injury, trigger an inflammatory response coordinated by innate immune system. Cellular molecular mediators modulate tumor growth directly influencing adaptive response. Depending on balance cell types signals within microenvironment, can support or restrain tumor. Adding complexity, research from past two decades has revealed that cells are highly heterogeneous plastic, with variable phenotypes depending type, stage, treatment. The field is now cusp being able harness this wealth data (

Language: Английский

Neutrophil Heterogeneity in Cancer: From Biology to Therapies

Frontiers in Immunology, Journal Year: 2019, Volume and Issue: 10

Published: Sept. 20, 2019

Neutrophils have been extensively described in the pathophysiology of autoimmune and infectious diseases. Accumulating evidence also suggests important role neutrophils cancer progression through their interaction with immune cells blood tumor microenvironment (TME). Most studies as key drivers progression, due to involvement various promoting functions including proliferation, aggressiveness dissemination, well suppression. However, such were focusing on late-stages tumorigenesis, which chronic inflammation had already developed. The tumor-associated (TANs) at early stages development remains poorly described, though recent findings indicate that early-stage TANs may display anti-tumor properties. Beyond site, supported by NLR retrospective functional analyses suggest could actively contribute tumorigenesis. Hence, it appears phenotype vary greatly during highlighting heterogeneity. origin pro- or is generally believed arise following a change cell state, from resting activated. Moreover, fate involve distinct differentiation programs yielding subsets pro neutrophils. In this review, we will discuss current knowledge heterogeneity across different tissues impact neutrophil-based therapeutic strategies shown promising results pre-clinical studies, paving way for design next generation immunotherapy.

Language: Английский