Wu Chao, Wu Zuowei, Tian Bole
Department of Pancreatic Surgery, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, Sichuan Province, China.
BMC Surg. 2020 Sep 17;20(1):207. doi: 10.1186/s12893-020-00856-y.
Although genes have been previously detected in pancreatic cancer (PC), aberrant genes that play roles in resectable pancreatic cancer should be further assessed.
Messenger RNA samples and clinicopathological data corrected with PC were downloaded from The Cancer Genome Atlas (TCGA). Resectable PC patients were randomly divided into a primary set and a validation set. Univariable Cox regression analysis, lasso-penalized Cox regression analysis, and multivariable Cox analysis were implemented to distinguish survival-related genes (SRGs). A risk score based on the SRGs was calculated by univariable Cox regression analysis. A genomic-clinical nomogram was established by integrating the risk score and clinicopathological data to predict overall survival (OS) in resectable PC.
Five survival-related genes (AADAC, DEF8, HIST1H1C, MET, and CHFR) were significantly correlated with OS in resectable PC. The resectable PC patients, based on risk score, were sorted into a high-risk group that showed considerably unfavorable OS (p < 0.001) than the low-risk group, in both the primary set and the validation set. The concordance index (C-index) was calculated to evaluate the predictive performance of the nomogram were respectively in the primary set [0.696 (0.608-0.784)] and the validation set [0.682 (0.606-0.758)]. Additionally, gene set enrichment Analysis discovered several meaningful enriched pathways.
Our study identified five prognostic gene biomarkers for OS prediction and which facilitate postoperative molecular target therapy for the resectable PC, especially the nomic-clinical nomogram which may be used as an effective model for the postoperative OS evaluation and also an optimal therapeutic tool for the resectable PC.
尽管此前已在胰腺癌(PC)中检测到基因,但在可切除胰腺癌中发挥作用的异常基因仍需进一步评估。
从癌症基因组图谱(TCGA)下载经PC校正的信使核糖核酸样本和临床病理数据。将可切除PC患者随机分为一个主要数据集和一个验证数据集。采用单变量Cox回归分析、套索惩罚Cox回归分析和多变量Cox分析来鉴别生存相关基因(SRGs)。通过单变量Cox回归分析计算基于SRGs的风险评分。通过整合风险评分和临床病理数据建立基因组临床列线图,以预测可切除PC的总生存期(OS)。
五个生存相关基因(AADAC、DEF8、HIST1H1C、MET和CHFR)与可切除PC的OS显著相关。在主要数据集和验证数据集中,根据风险评分,可切除PC患者被分为高风险组和低风险组,高风险组的OS明显比低风险组差(p < 0.001)。计算一致性指数(C指数)以评估列线图在主要数据集[0.696(0.608 - 0.784)]和验证数据集[0.682(0.606 - 0.758)]中的预测性能。此外,基因集富集分析发现了几个有意义的富集途径。
我们的研究鉴定了五个用于OS预测的预后基因生物标志物,这有助于可切除PC的术后分子靶向治疗,尤其是基因组临床列线图,其可作为术后OS评估的有效模型,也是可切除PC的最佳治疗工具。