Glycolysis-Related Gene Expression Profiling Screen for Prognostic Risk Signature of Pancreatic Ductal Adenocarcinoma

Abstract

Objective: Pancreatic ductal adenocarcinoma (PDAC) is highly lethal. Although progress has been made in the treatment of PDAC, its prognosis remains unsatisfactory. This study aimed to develop novel prognostic genes related to glycolysis in PDAC and to apply these genes to new risk stratification.Methods: In this study, based on the Cancer Genome Atlas (TCGA) PAAD cohort, the expression level of glycolysis-related gene at mRNA level in PAAD and its relationship with prognosis were analyzed. Non-negative matrix decomposition (NMF) clustering was used to cluster PDAC patients according to glycolytic genes. Prognostic glycolytic genes, screened by univariate Cox analysis and LASSO regression analysis were established to calculate risk scores. The differentially expressed genes (DEGs) in the high-risk group and the low-risk group were analyzed, and the signal pathway was further enriched to analyze the correlation between glycolysis genes. In addition, based on RNA-seq data, CIBERSORT was used to evaluate the infiltration degree of immune cells in PDAC samples, and ESTIMATE was used to calculate the immune score of the samples.Results: A total of 319 glycolysis-related genes were retrieved, and all PDAC samples were divided into two clusters by NMF cluster analysis. Survival analysis showed that PDAC patients in cluster 1 had shorter survival time and worse prognosis compared with cluster 2 samples (P < 0.001). A risk prediction model based on 11 glycolysis genes was constructed, according to which patients were divided into two groups, with significantly poorer prognosis in high-risk group than in low-risk group (P < 0.001). Both internal validation and external dataset validation demonstrate good predictive ability of the model (AUC = 0.805, P < 0.001; AUC = 0.763, P < 0.001). Gene aggregation analysis showed that DEGs highly expressed in high-risk group were mainly concentrated in the glycolysis level, immune status, and tumor cell proliferation, etc. In addition, the samples in high-risk group showed immunosuppressed status and infiltrated by relatively more macrophages and less CD8+T cell.Conclusions: These findings suggested that the gene signature based on glycolysis-related genes had potential diagnostic, therapeutic, and prognostic value for PDAC.

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

“…Previously, several valuable PDAC prognostic signatures have been constructed by using bioinformatics analysis. For example, signatures based on glycolysis, m6A, ferroptosis, immune, and extracellular vesicle predict 1-year OS for PDAC with AUC at 0.805, 0.736, 0.81, 0.755, and 0.640, respectively, which were similar to our study ( Xu et al, 2020 ; Chen et al, 2021 ; Song et al, 2021 ; Xu et al, 2021 ; Yuan et al, 2021 ). However, the number of patients included in the abovementioned studies ranged from 183 to 441 and were relatively low.…”

“…The GSEA analysis indicated that hypoxia and glycolysis pathways were upregulated in the high-risk group. Recent studies have documented that hypoxia and glycolysis-related gene signatures were associated with tumor microenvironment and might be used to predict the prognosis of PDAC patients ( Ding et al, 2021 ; Song et al, 2021 ). Hypoxia has been considered as an indicator of the inflamed tumor microenvironment and leads to activation of tumor-promoting inflammatory responses ( Triner and Shah, 2016 ).…”

“…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 .…”

A prognostic Risk Score model for oral squamous cell carcinoma constructed by 6 glycolysis-immune-related genes

“…The Kaplan–Meier survival demonstrated that patients in the high-risk group had lower survival rates than those in the low-risk group, indicating the relatively reliable performance of the Risk Score. The Risk Score models constructed by glycolysis-related genes have been proven prognostic values in pancreatic ductal adenocarcinoma [ 46 ]. Prognostic models basing on immune-related genes have also been identified in renal papillary cell carcinoma [ 47 ].…”

Association of aging-related genes with prognosis and immune infiltration in pancreatic adenocarcinoma

“…However, the relationships between aging-related genes (ARGs) and prognoses as well as immune infiltrations of PAAD patients remain unclear. In previous studies, ferroptosis-related signatures ( Jiang et al, 2021 ), immune-related signatures ( Wang et al, 2020 ), and glycolysis-related signatures ( Song et al, 2021 ) have been constructed to predict the OS of PAAD patients. Therefore, in this study, our purpose was to identify molecular subtypes as well as establish a risk signature based on ARGs to predict prognoses and immune microenvironments of PAAD patients.…”