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Correlations Between Tumor Mutation Burden and Immunocyte Infiltration and Their Prognostic Value in Colon Cancer.
Zhou, Zhangjian; Xie, Xin; Wang, Xuan; Zhang, Xin; Li, Wenxin; Sun, Tuanhe; Cai, Yifan; Wu, Jianhua; Dang, Chengxue; Zhang, Hao.
Afiliación
  • Zhou Z; Department of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
  • Xie X; Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
  • Wang X; Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
  • Zhang X; Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
  • Li W; Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
  • Sun T; Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
  • Cai Y; Department of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
  • Wu J; Department of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
  • Dang C; Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
  • Zhang H; Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Front Genet ; 12: 623424, 2021.
Article en En | MEDLINE | ID: mdl-33664769
BACKGROUND: Colon cancer has a huge incidence and mortality worldwide every year. Immunotherapy could be a new therapeutic option for patients with advanced colon cancer. Tumor mutation burden (TMB) and immune infiltration are considered critical in immunotherapy but their characteristics in colon cancer are still controversial. METHODS: The somatic mutation, transcriptome, and clinical data of patients with colon cancer were obtained from the TCGA database. Patients were divided into low or high TMB groups using the median TMB value. Somatic mutation landscape, differentially expressed genes, and immune-related hub genes, Gene Ontology and KEGG, gene set enrichment, and immune infiltration analyses were investigated between the two TMB groups. Univariate and multivariate Cox analyses were utilized to construct a prognostic gene signature. The differences in immune infiltration, and the expression of HLA-related genes and checkpoint genes were investigated between the two immunity groups based on single sample gene set enrichment analysis. Finally, a nomogram of the prognostic prediction model integrating TMB, immune infiltration, and clinical parameters was established. Calibration plots and receiver operating characteristic curves (ROC) were drawn, and the C-index was calculated to assess the predictive ability. RESULTS: Missense mutations and single nucleotide polymorphisms were the major variant characteristics in colon cancer. The TMB level showed significant differences in N stage, M stage, pathological stage, and immune infiltration. CD8+ T cells, activated memory CD4+ T cells, activated NK cells, and M1 macrophages infiltrated more in the high-TMB group. The antigen processing and presentation signaling pathway was enriched in the high-TMB group. Two immune related genes (CHGB and SCT) were identified to be correlated with colon cancer survival (HR = 1.39, P = 0.01; HR = 1.26, P = 0.02, respectively). Notably, the expression of SCT was identified as a risk factor in the immune risk model, in which high risk patients showed poorer survival (P = 0.04). High immunity status exhibited significant correlations with immune response pathways, HLA-related genes, and immune checkpoint genes. Finally, including nine factors, our nomogram prediction model showed better calibration (C-index = 0.764) and had an AUC of 0.737. CONCLUSION: In this study, we investigated the patterns and prognostic roles of TMB and immune infiltration in colon cancer, which provided new insights into the tumor microenvironment and immunotherapies and the development of a novel nomogram prognostic prediction model for patients with colon cancer.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Genet Año: 2021 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Genet Año: 2021 Tipo del documento: Article País de afiliación: China
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