AUTHOR=Huo Junyu , Wu Liqun , Zang Yunjin 

TITLE=Development and Validation of a Novel Metabolic-Related Signature Predicting Overall Survival for Pancreatic Cancer

JOURNAL=Frontiers in Genetics

VOLUME=Volume 12 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2021.561254

DOI=10.3389/fgene.2021.561254

ISSN=1664-8021

ABSTRACT=Recently, growing evidences have revealed the significant effect of reprogrammed metabolism on pancreatic cancer regarding the carcinogenesis, progression, and treatment. However, the prognostic value of metabolism-related genes in pancreatic cancer has not been fully revealed. we identified 379 differentially expressed metabolic-related genes(DEMRGs) by comparing 178 pancreatic cancer tissues with 171 normal pancreatic tissues in The Cancer Genome Atlas(TCGA) and Genotype-Tissue Expression project(GTEx) databases. Then we used univariate cox regression analysis together with lasso regression for constructing an prognostic model consist of 15 metabolic-genes. The unified risk score formula and cutoff value were taken into account to divide patients into two groups, group with a high risk and group with a low risk, with the former exhibiting an obviously worse prognosis compared with the latter. The external validation results of International Cancer Genome Consortium (IGCC) cohort and Gene Expression Omnibus (GEO) cohort further confirm the effectiveness of this prognostic model. As shown in the receiver operating characteristic(ROC) curve, the Area Under Curve(AUC) values of riskscore for overall survival (OS), the disease-specific survival (DSS) and the progression-free survival(PFS) were 0.871, 0.885 and 0.886, respectively. Based on the Gene Set Enrichment Analysis (GSEA), the 15-gene signature can affect some important biological processes and pathways of pancreatic cancer. In addition, the prognostic model was significantly correlated with tumor immune microenvironment (immune cell infiltration, immune checkpoint expression, etc.) and clinicopathological features (pathological stage, lymph node and metastasis, etc.). We also built a nomogram based on three independent prognostic predictor(including individual neoplasm status, lymph node metastasis and riskscore) for prediction of 1year, 3year, 5year overall survival of pancreatic cancer. which may help to further improve the treatment strategy of pancreatic cancer.