4.7 Article

Network-based identification of key master regulators associated with an immune-silent cancer phenotype

期刊

BRIEFINGS IN BIOINFORMATICS
卷 22, 期 6, 页码 -

出版社

OXFORD UNIV PRESS
DOI: 10.1093/bib/bbab168

关键词

transcription regulator; master regulator analysis; immunologic constant of rejection; immune exclusion; gene regulatory networks

资金

  1. Qatar Foundation, Qatar National Research Fund [NPRP-100126-170262, NPRP11S-0121-180351]
  2. Sidra Precision Medicine Program [SDR400123, SDR100035]
  3. AIRC [IG 2018-ID 21846]

向作者/读者索取更多资源

An active T-helper 1/cytotoxic response in different tumors is associated with immunotherapy responsiveness and favorable prognosis. However, in some cancers, intratumoral immune activation does not prevent progression or relapse. Defining mechanisms of immune evasion is crucial for refining stratification algorithms, guiding treatment decisions, and identifying candidates for immune-targeted therapy.
A cancer immune phenotype characterized by an active T-helper 1 (Th1)/cytotoxic response is associated with responsiveness to immunotherapy and favorable prognosis across different tumors. However, in some cancers, such an intratumoral immune activation does not confer protection from progression or relapse. Defining mechanisms associated with immune evasion is imperative to refine stratification algorithms, to guide treatment decisions and to identify candidates for immune-targeted therapy. Molecular alterations governing mechanisms for immune exclusion are still largely unknown. The availability of large genomic datasets offers an opportunity to ascertain key determinants of differential intratumoral immune response. We follow a network-based protocol to identify transcription regulators (TRs) associated with poor immunologic antitumor activity. We use a consensus of four different pipelines consisting of two state-of-the-art gene regulatory network inference techniques, regularized gradient boosting machines and ARACNE to determine TR regulons, and three separate enrichment techniques, including fast gene set enrichment analysis, gene set variation analysis and virtual inference of protein activity by enriched regulon analysis to identify the most important TRs affecting immunologic antitumor activity. These TRs, referred to as master regulators (MRs), are unique to immune-silent and immune-active tumors, respectively. We validated the MRs coherently associated with the immune-silent phenotype across cancers in The Cancer Genome Atlas and a series of additional datasets in the Prediction of Clinical Outcomes from Genomic Profiles repository. A downstream analysis of MRs specific to the immune-silent phenotype resulted in the identification of several enriched candidate pathways, including NOTCH1, TGF-beta, Interleukin-1 and TNF-alpha signaling pathways. TGFB1I1 emerged as one of the main negative immune modulators preventing the favorable effects of a Th1/cytotoxic response.

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