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J Cancer 2020; 11(21):6299-6318. doi:10.7150/jca.47629 This issue Cite

Research Paper

Development and validation of a metastasis-related Gene Signature for predicting the Overall Survival in patients with Pancreatic Ductal Adenocarcinoma

Mengwei Wu, Xiaobin Li, Rui Liu, Hongwei Yuan, Wei Liu^✉, Ziwen Liu^✉

Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.

✉ Corresponding authors: Ziwen Liu, No. 1 Shuaifuyuan, Dongcheng District, Beijing, China. E-mail: liuziwencn; Phone: +86-010-69152600; Wei Liu, No. 1 Shuaifuyuan, Dongcheng District, Beijing, China. E-mail: liuwei3359cn; Phone: +86-010-69152600. More

Abstract

Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly fatal, aggressive cancer characterized by invasiveness and metastasis. In this study, we aimed to propose a gene prediction model based on metastasis-related genes (MTGs) to more accurately predict PDAC prognosis.

Methods: Differentially expressed MTGs (DE-MTGs) were identified via integrated analysis of gene expression omnibus (GEO) datasets and Human Cancer Metastasis Database (HCMDB). Overall survival (OS) related DE-MTGs were then identified and a prognostic gene signature was established using Lasso-Cox regression with TCGA-PAAD datasets. Tumor immunity was analyzed using ESTIMATE and CIBERSORT algorithms. Finally, a nomogram predicting 1-year, 2-year, and 3-year OS of PDAC patients was established based on the prognostic gene signature and relevant clinical parameters using a stepwise Cox regression model.

Results: A total of 36 DE-MTGs related to OS were identified in PDAC. Consequently, an MTG-based gene signature comprising of RACGAP1, RARRES3, TPX2, MMP28, GPR87, KIF14, and TSPAN7 was established to predict the OS of PDAC. The MTG-based gene signature was able to distinguish high-risk patients with significantly poorer prognosis and accurately predict OS of PDAC in both the training and external validation datasets. Cox regression analysis indicated that the MTG-based gene signature was an independent prognostic factor in PDAC. The gene set enrichment analysis (GSEA) showed that molecular alterations in the high-risk group were associated with multiple oncological pathways. Moreover, analysis of tumor immunity revealed significantly higher levels of follicular helper T cells and M0 macrophage infiltration, and lower levels of infiltrating naïve B cells, CD8 T cells, monocytes, and resting dendritic cells in the high-risk group. Immune cell infiltration levels were significantly associated with the expression of the seven DE-MTGs. Finally, a nomogram was established by incorporating the prognostic gene signature and clinical parameters, which was superior to the AJCC staging system in predicting the OS of PDAC patients.

Conclusions: The DE-MTGs we identified were closely associated with the progress and prognosis of PDAC and are potential therapeutic targets. The MTG-based gene signature and nomogram may serve to improve the individualized prediction of survival, assisting in clinical decision-making.

Keywords: Gene Expression Omnibus, The Cancer Genome Atlas Program, pancreatic ductal adenocarcinoma, overall survival, nomogram

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