Establishment of a prognostic prediction system based on tumor microenvironment of pancreatic cancer.

Background: Pancreatic cancer (PC) is an inflammatory tumor. Tumor microenvironment (TME) plays an important role in the development of PC. This study aims to explore hub genes of TME and establish a prognostic prediction system for PC.

Methods: High throughput RNA-sequencing and clinical data of PC were downloaded from The Cancer Genome Atlas and International Cancer Genome Consortium database, respectively. PC patients were divided into high- and low-score group by using stromal, immune scores system based on ESTIMATE. Differentially expressed genes between high- and low-score patients were screened and survival-related differentially expressed genes were identified as candidate genes by univariate Cox regression analysis. Final variables for establishment of the prognostic prediction system were determined by LASSO analysis and multivariate Cox regression analysis. The predictive power of the prognostic system was evaluated by internal and external validation.

Results: A total of 210 candidate genes were identified by stromal, immune scores system, and survival analyses. Finally, the prognostic risk score system was constructed by the following genes: FAM57B, HTRA3, CXCL10, GABRP, SPRR1B, FAM83A, and LY6D. In process of internal validation, Harrell concordance index (C-index) of this prognostic risk score system was 0.73, and the area under the receiver operating characteristic curve value of 1-year, 2-year, and 3-year overall survival period was 0.67, 0.76 and 0.86, respectively. In the external validation set, the survival prediction C-index was 0.71, and the area under the curve was 0.81, 0.72, and 0.78 at 1-year, 2-year, and 3-year, respectively.

Conclusion: This prognostic risk score system based on TME demonstrated a good predictive capacity to the prognosis of PC. It may provide information for the treatment strategy and follow-up for patients with PC.