A Novel Ferroptosis-Related Gene Signature Predicts Recurrence in Patients With Pancreatic Ductal Adenocarcinoma

Abstract

Background: Recurrence after surgery is largely responsible for the extremely poor outcomes for patients with pancreatic ductal adenocarcinoma (PDAC). Ferroptosis is implicated in chemotherapy sensitivity and tumor recurrence, we aimed to find out survival-associated ferroptosis-related genes and use them to build a practical risk model with the purpose to predict PDAC recurrence.Methods: Univariate Cox regression analysis was conducted to obtain prognostic ferroptosis-related genes in The Cancer Genome Atlas (TCGA, N = 140) cohort. Multivariate Cox regression analysis was employed to construct a reliable and credible gene signature. The prognostic performance was verified in a MTAB-6134 (N = 286) validation cohort and a PACA-CA (N = 181) validation cohort. The stability of the signature was tested in TCGA and MTAB-6134 cohorts by ROC analyses. Pathway enrichment analysis was adopted to preliminary illuminate the biological relevance of the gene signature.Results: Univariate and multivariate Cox regression analyses identified a 5-gene signature that contained CAV1, DDIT4, SLC40A1, SRXN1 and TFAP2C. The signature could efficaciously stratify PDAC patients with different recurrence-free survival (RFS), both in the training and validation cohorts. Results of subgroup receiver operating characteristic curve (ROC) analyses confirmed the stability and the independence of this signature. Our signature outperformed clinical indicators and previous reported models in predicting RFS. Moreover, the signature was found to be closely associated with several cancer-related and drug response pathways.Conclusion: This study developed a precise and concise prognostic model with the clinical implication in predicting PDAC recurrence. These findings may facilitate individual management of postoperative recurrence in patients with PDAC.

An Inflammatory Response Related Gene Signature Associated with Survival Outcome and Gemcitabine Response in Patients with Pancreatic Ductal Adenocarcinoma

“…In each cohort, patients were divided into the high- or low-risk group according to the median value of the risk score. To compare the survival difference between high- and low-risk groups, Kaplan–Meier survival and receiver operating characteristic (ROC) analyses were conducted by using the R package “survival” and “timeROC.” We also calculated the time-varying concordance index (C-index) of our signature and compared it with six previous published signatures which were based on glycolysis ( Song et al, 2021 ), ferroptosis ( Feng et al, 2021a ), hypoxia ( Ding et al, 2021 ), m6A ( Meng et al, 2020 ), autophagy ( Yu J. et al, 2021 ), and immune ( Mao et al, 2021 ) related genes. The information of these six signatures are listed in Supplementary Table S2 .…”

Genome, Metabolism, or Immunity: Which Is the Primary Decider of Pancreatic Cancer Fate through Non-Apoptotic Cell Death?

“…Various ferroptosis-related genes (FRGs) are identified through the Cancer Genome Atlas (TCGA) and different genome analyses, which are utilized in developing risk models for pancreatic cancer (Table 2). Feng et al developed a risk model based on five FRGs, where CAV1, DDIT4, SRXN1, and TFAP2C indicate better survival, whereas SLC40A1 indicates a more adverse outcome [56]. Using ZNF419, TUBE1, STEAP3, SLC1A4, RRM2, PTGS2, MT1G, MAP3K5, DDIT4, CAPG, CAV1, BAP1, AURKA, and ATG4D, Jiang et al designed a prognostic FRGs risk model, in which it was shown that expression levels of PTGS2, RRM2, AURKA, CAV1, MAP3K5, and STEAPS are higher in tumor samples, and the upregulation of PTGS2 and the downregulation of MT1G, TUBE1, and ATG4D might contribute to tumorigenesis and poor outcomes [57].…”