부산대학교 도서관

ABSTRACT: The potential association between the prognosis of the pancreatic adenocarcinoma (PAAD) and its microenvironment is unclear. This study aims to construct a prognostic index (PI) model of the PAAD microenvironment to predict PAAD patient survival outcomes.The mRNA sequencing and the clinical parameters data were obtained from The Cancer Genome Atlas. Immune and stromal scores were computed using the expression data algorithm to capture infiltration of immune and stromal cells in the PAAD tissue, where patients were categorized as high and low score groups according to these scores. Differentially expressed genes were identified using the R package LIMMA. Univariate and multivariate Cox regression analysis were conducted to select candidate survival-correlated gene signatures from the tumor microenvironment for constructing a model. The Kaplan-Meier method was used to access overall survival of the primary and validation cohorts. The immunological features of the PI model was explored using the Tumor Immune Estimation Resource (TIMER) database. Bioinformatic analyses were conducted based on the DAVID database.A total of 1266 overlapping differentially expressed genes and 49 prognosis-associated genes were identified. A 7-mRNA signature (GBP5, BICC1, SLC7A14, CYSLTR1, P2RY6, VENTX, and RAB39B) was screened for the construction of a PI model (area under the curve = 0.791). In both the primary and validation cohorts, Kaplan Meier analysis revealed that the overall survival of the high-risk group was significantly worse compared to the low-risk group (P < .0001, P = .0028 respectively). The TIMER database described that the 7 signature genes were correlated with immune infiltrating cells and tumor purity. Bioinformatic analyses revealed that these prognosis-associated genes were significantly enriched during inflammation, the defense response, would response, calcium ion transport, and plasma membrane part.A list of the prognosis-correlated genes was generated based on the PAAD microenvironment. A 7-mRNA PI model may be used for predicting the prognosis of PAAD patients.