A TP53-associated immune prognostic signature for the prediction of the overall survival and therapeutic responses in pancreatic cancer

Yi Liu; Long Cheng; Xiangyang Song; Chao Li; Jiantao Zhang; Lei Wang; Yi Liu; Long Cheng; Xiangyang Song; Chao Li; Jiantao Zhang; Lei Wang

doi:10.3934/mbe.2022010

Mathematical Biosciences and Engineering

2022, Volume 19, Issue 1: 191-208. doi: 10.3934/mbe.2022010

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A TP53-associated immune prognostic signature for the prediction of the overall survival and therapeutic responses in pancreatic cancer

1.
Department of Colorectal and Anal Surgery, The First Hospital of Jilin University, Changchun, Jilin, China
2.
Department of Orthopedics, The First Hospital of Jilin University, Changchun, Jilin, China
3.
Department of Hepatobiliary and Pancreatic Surgery, The First Hospital of Jilin University, Street Xinmin 71, Changchun, China

Academic Editor: Xiangtao Li

Received: 08 August 2021 Accepted: 22 October 2021 Published: 09 November 2021

Pancreatic cancer (PC) is a highly fatal disease correlated with an inferior prognosis. The tumor protein p53 (TP53) is one of the frequent mutant genes in PC and has been implicated in prognosis. We collected somatic mutation data, RNA sequencing data, and clinical information of PC samples in the Cancer Genome Atlas (TCGA) database. TP53 mutation was an independent prognostic predictor of PC patients. According to TP53 status, Gene set enrichment analysis (GSEA) suggested that TP53 mutations were related to the immunophenotype of pancreatic cancer. We identified 102 differentially expressed immune genes (DEIGs) based on TP53 mutation status and developed a TP53-associated immune prognostic model (TIPM), including Epiregulin (EREG) and Prolactin receptor (PRLR). TIPM identified the high-risk group with poor outcomes and more significant response potential to cisplatin, gemcitabine, and paclitaxel therapies. And we verified the TIPM in the International Cancer Genome Consortium (ICGC) cohort (PACA-AU) and Gene Expression Omnibus (GEO) cohort (GSE78229 and GSE28735). Finally, we developed a nomogram that reliably predicts overall survival in PC patients on the bias of TIPM and other clinicopathological factors. Our study indicates that the TIPM derived from TP53 mutation patterns might be an underlying prognostic therapeutic target. But more comprehensive researches with a large sample size is necessary to confirm the potential.
- pancreatic cancer,
- TP53 mutation,
- TP53-associated immune prognostic model,
- nomogram,
- the cancer genome atlas,
- international cancer genome consortium
Citation: Yi Liu, Long Cheng, Xiangyang Song, Chao Li, Jiantao Zhang, Lei Wang. A TP53-associated immune prognostic signature for the prediction of the overall survival and therapeutic responses in pancreatic cancer[J]. Mathematical Biosciences and Engineering, 2022, 19(1): 191-208. doi: 10.3934/mbe.2022010

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Abstract

Pancreatic cancer (PC) is a highly fatal disease correlated with an inferior prognosis. The tumor protein p53 (TP53) is one of the frequent mutant genes in PC and has been implicated in prognosis. We collected somatic mutation data, RNA sequencing data, and clinical information of PC samples in the Cancer Genome Atlas (TCGA) database. TP53 mutation was an independent prognostic predictor of PC patients. According to TP53 status, Gene set enrichment analysis (GSEA) suggested that TP53 mutations were related to the immunophenotype of pancreatic cancer. We identified 102 differentially expressed immune genes (DEIGs) based on TP53 mutation status and developed a TP53-associated immune prognostic model (TIPM), including Epiregulin (EREG) and Prolactin receptor (PRLR). TIPM identified the high-risk group with poor outcomes and more significant response potential to cisplatin, gemcitabine, and paclitaxel therapies. And we verified the TIPM in the International Cancer Genome Consortium (ICGC) cohort (PACA-AU) and Gene Expression Omnibus (GEO) cohort (GSE78229 and GSE28735). Finally, we developed a nomogram that reliably predicts overall survival in PC patients on the bias of TIPM and other clinicopathological factors. Our study indicates that the TIPM derived from TP53 mutation patterns might be an underlying prognostic therapeutic target. But more comprehensive researches with a large sample size is necessary to confirm the potential.

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