4.8 Article

An immune-related gene prognostic risk index for pancreatic adenocarcinoma

期刊

FRONTIERS IN IMMUNOLOGY
卷 13, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fimmu.2022.945878

关键词

pancreatic adenocarcinoma; immune gene; prognosis; immunotherapy; CTLA4

资金

  1. Natural Science Research Plan of Huaian [HAB202022]
  2. National Natural Science Foundation of China [81972719, 82003164]
  3. National science research in Universities of Jiangsu Province [21KJA320008, 20KJB320032, 21KJB320021]
  4. Jiangsu Province Natural Science Foundation [BK20210910, BK20201012, BK20210913]
  5. Innovative and Entrepreneurial Doctor Project of Jiangsu Province [JSSCBS20211256]
  6. Key Research & Developement Plan of Xuzhou [KC18102]
  7. Science and Technology Project of Xuzhou [KC20126]
  8. Scientific Research Foundation of Xuzhou Medical University [D2019050]

向作者/读者索取更多资源

The study aims to construct an immune-related gene prognostic risk index (IRGPRI) for pancreatic adenocarcinoma (PAAD) and investigate the immune and molecular features in IRGPRI-defined PAAD subgroups and the benefit of immune checkpoint inhibitors (ICIs) therapy. By analyzing gene expression data and survival data, 16 immune-related hub genes were identified and an IRGPRI was constructed and validated in different datasets. Further analysis revealed that low IRGPRI patients had better overall survival and more clinical treatment benefits, while high IRGPRI patients were more inclined towards cancer-related pathways. These findings provide important information for prognosis assessment and ICIs treatment in PAAD.
ObjectiveOur goal is to construct an immune-related gene prognostic risk index (IRGPRI) for pancreatic adenocarcinoma (PAAD), and to clarify the immune and molecular features in IRGPRI-defined PAAD subgroups and the benefit of immune checkpoint inhibitors (ICIs) therapy. MethodThrough differential gene expression analysis, weighted gene co-expression network analysis (WGCNA), and univariate Cox regression analysis, 16 immune-related hub genes were identified using the Cancer Genome Atlas (TCGA) PAAD dataset (n = 182) and immune gene set. From these genes, we constructed an IRGPRI with the Cox regression method and the IRGPRI was verified based on the Gene Expression Omnibus (GEO) dataset (n = 45). Then, we analyzed the immune and molecular features and the benefit of ICI therapy in IRGPRI-defined subgroups. ResultsFive genes, including S100A16, CD40, VCAM1, TNFRSF4 and TRAF1 were used to construct IRGPRI. As with the results of the GEO cohort, the overall survival (OS) was more favorable in low IRGPRI patients versus high IRGPRI patients. The composite results pointed out that low IRGPRI was associated with immune response-related pathways, high level of CTLA4, low KRAS and TP53 mutation rate, more infiltration of activated memory CD4(+) T cells, CD8(+) T cells, and more benefits from ICIs therapy. In comparison, high IRGPRI was associated with cancer-related pathways, low expression of CTLA4, high KRAS and TP53 mutation rate, more infiltration of M2 macrophages, and less benefit from ICIs therapies. ConclusionThis IRGPRI is an encouraging biomarker to define the prognosis, immune and molecular features, and benefits from ICIs treatments in PAAD.

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