A 15-Gene Immune, Stromal, and Proliferation Gene Signature that Significantly Associates with Poor Survival in Patients with Pancreatic Ductal Adenocarcinoma

Abstract

Purpose: Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease with dismal survival rates. Tumor microenvironment (TME), comprising of immune cells and cancer-associated fibroblasts, plays a key role in driving poor prognosis and resistance to chemotherapy. Herein, we aimed to identify a TME-associated, risk-stratification gene biomarker signature in PDAC. Experimental Design: The initial biomarker discovery was performed in The Cancer Genome Atlas (TCGA, n ¼ 163) transcriptomic data. This was followed by independent validation of the gene signature in the International Cancer Genome Consortium (ICGC, n ¼ 95), E-MTAB-6134 (n ¼ 288), and GSE71729 (n ¼ 123) datasets for predicting overall survival (OS), and for its ability to detect poor molecular subtypes. Clinical validation and nomogram establishment was undertaken by performing multivariate Cox regression analysis. Results: Our biomarker discovery effort identified a 15-gene immune, stromal, and proliferation (ISP) gene signature that significantly associated with poor OS [HR, 3.90; 95% confidence interval (CI), 2.36–6.41; P < 0.0001]. This signature also robustly predicted survival in three independent validation cohorts ICGC [HR, 2.63 (1.56–4.41); P < 0.0001], E-MTAB-6134 [HR, 1.53 (1.14–2.04); P ¼ 0.004], and GSE71729 [HR, 2.33 (1.49–3.63); P < 0.0001]. Interestingly, the ISP signature also permitted identification of poor molecular PDAC subtypes with excellent accuracy in all four cohorts; TCGA (AUC ¼ 0.94), ICGC (AUC ¼ 0.91), E-MTAB-6134 (AUC ¼ 0.80), and GSE71729 (AUC ¼ 0.83). The ISP-derived high-risk patients exhibited significantly poor OS in a clinical validation cohort [n ¼ 119; HR, 2.62 (1.50–4.56); P ¼ 0.0004]. A nomogram was established which included the ISP, CA19-9, and T- and N-stage for eventual clinical translation. Conclusions: We report a novel gene signature for risk-stratification and robust identification of patients with PDAC with poor molecular subtypes.