AUTHOR=Chen Guangyu , Long Junyu , Zhu Ruizhe , Yang Gang , Qiu Jiangdong , Zhao Fangyu , Liu Yuezhe , Tao Jinxin , Zhang Taiping , Zhao Yupei 

TITLE=Identification and Validation of Constructing the Prognostic Model With Four DNA Methylation-Driven Genes in Pancreatic Cancer

JOURNAL=Frontiers in Cell and Developmental Biology

VOLUME=Volume 9 - 2021

YEAR=2022

URL=https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2021.709669

DOI=10.3389/fcell.2021.709669

ISSN=2296-634X

ABSTRACT=Background
Pancreatic cancer (PC) is a highly aggressive gastrointestinal tumor and has a poor prognosis. Evaluating the prognosis validly is urgent for PC patients. In this study, we utilized the RNA-seq profiles and DNA methylation expression data comprehensively to develop and validate a prognostic signature in patients with PC.
Methods
The integrated analysis of RNA-seq, DNA methylation expression profiles, and relevant clinical information was performed to select 4 DNA methylation-driven genes. Then, a prognostic signature was established by the univariate, multivariate Cox, and LASSO regression analyses in the TCGA dataset. GSE62452 cohort was utilized for external validation. Finally, a nomogram model was set up and evaluated by calibration curves.
Results
9 DNA methylation-driven genes were identified which were related to OS. After multivariate Cox and LASSO regression analyses, 4 of these genes (RIC3, MBOAT2, SEZ6L, and OAS2) were selected to establish the predictive signature. The PC patients were stratified into two groups according to the median risk score of which the low-risk displayed a prominently favorable OS compared to the high-risk in whether the training (P < 0.001) or validation (P < 0.01) cohort. Then, the univariate and multivariate Cox regression analysis showed that age, grade, risk score, and the number of positive lymph nodes were significantly associated with OS in PC patients. Therefore, We used these clinical variables to construct a nomogram, and its performance in predicting the 1-, 2- and, 3-year OS of patients with PC was assessed via calibration curves. 
Conclusion
A prognostic risk score signature was built with the 4 alternative DNA methylation-driven genes. Furthermore, in combination with the risk score, age, grade, and the number of positive lymph nodes, a nomogram was established for conveniently predicting the individualized prognosis of PC patients.