Based on Molecular Subtypes, Immune Characteristics and Genomic Variation to Constructing and Verifying Multi-Gene Prognostic Characteristics of Colorectal Cancer

Gu, Lei; Jiang, Chunhui; Xu, Chunjie; Liu, Ye

doi:10.3389/fcell.2022.828415

Cited by 1 publication

(1 citation statement)

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“…With the advancement of genetic testing technology, it has been realized that tumors belong to a class of highly heterogeneous and complex diseases, and personalized prognostic analysis needs to be performed for different patients’ genomic characteristics. Because single-gene/factor prediction models have low accuracy, more studies have explored the value of polygene-based models in identifying novel immunotherapy targets and predicting cancer prognosis ( 6 , 7 ).…”

Section: Introductionmentioning

confidence: 99%

A pyroptosis-related gene signature that predicts immune infiltration and prognosis in colon cancer

Hao

Wang

et al. 2023

Front. Oncol.

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BackgroundColon cancer (CC) is a highly heterogeneous malignancy associated with high morbidity and mortality. Pyroptosis is a type of programmed cell death characterized by an inflammatory response that can affect the tumor immune microenvironment and has potential prognostic and therapeutic value. The aim of this study was to evaluate the association between pyroptosis-related gene (PRG) expression and CC.MethodsBased on the expression profiles of PRGs, we classified CC samples from The Cancer Gene Atlas and Gene Expression Omnibus databases into different clusters by unsupervised clustering analysis. The best prognostic signature was screened and established using least absolute shrinkage and selection operator (LASSO) and multivariate COX regression analyses. Subsequently, a nomogram was established based on multivariate COX regression analysis. Next, gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were performed to explore the potential molecular mechanisms between the high- and low-risk groups and to explore the differences in clinicopathological characteristics, gene mutation characteristics, abundance of infiltrating immune cells, and immune microenvironment between the two groups. We also evaluated the association between common immune checkpoints and drug sensitivity using risk scores. The immunohistochemistry staining was utilized to confirm the expression of the selected genes in the prognostic model in CC.ResultsThe 1163 CC samples were divided into two clusters (clusters A and B) based on the expression profiles of the 33 PRGs. Genes with prognostic value were screened from the DEGs between the two clusters, and an eight PRGs prognostic model was constructed. GSEA and GSVA of the high- and low-risk groups revealed that they were mainly enriched in inflammatory response-related pathways. Compared to those in the low-risk group, patients in the high-risk group had worse overall survival, an immunosuppressive microenvironment, and worse sensitivity to immunotherapy and drug treatment.ConclusionOur findings provide a foundation for future research targeting pyroptosis and new insights into prognosis and immunotherapy from the perspective of pyroptosis in CC.

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Section: Introductionmentioning

confidence: 99%