Construction of a Pyroptosis-Related Genes Signature to Improve the Prognostic Prediction and Therapeutic Drugs Selection in Patients with Pancreatic Cancer

Abstract

Changjuan Li,1,2 Min Wang,3 Junwei Wei,2 Wenjuan Zhang,2 Haitao Liu,2 Dongqiang Zhao1 1Department of Gastroenterology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, People’s Republic of China; 2Department of Gastroenterology, The First Hospital of Handan City, Handan, Hebei Province, People’s Republic of China; 3Department of Anorectal Surgery, The First Hospital of Handan City, Handan, Hebei Province, People’s Republic of ChinaCorrespondence: Dongqiang Zhao, Department of Gastroenterology, The Second Hospital of Hebei Medical University, No. 215, He ping West Road, Xinhua District, Shijiazhuang, Hebei, People’s Republic of China, Email [email protected]: Effective prognostic assessment and appropriate drug selection are important for the clinical management of pancreatic cancer (PaC). Here, we aimed to establish a pyroptosis-associated genes (PRGs) signature to predict the prognostic outcomes of PaC and guide clinical drug therapy.Methods: We identified the differentially expressed PRGs between pancreatic adenocarcinoma (n = 178) and control pancreas samples (n = 171) obtained from different databases, and performed Lasso and Cox regression analysis to create a prognosis signature. Kaplan–Meier (K-M) survival curves and time-dependent receiver operating characteristics were further constructed to assess the utility of the risk model. The International Cancer Genome Consortium (ICGC) PACA-AU cohort (n = 95) was used as a validation dataset to examine the validity of this prognostic model. The correlations of risk score (RS) with clinical features, immune cell infiltration, tumor mutation burden and half-maximal inhibitory concentrations (IC50) of chemotherapeutic drugs were analyzed, and the expression levels of PRGs in cell lines were detected.Results: A prognostic signature was constructed, which consisted of 4 PRGs (AIM2, IL18, GSMDC and PLCG1). K-M analysis demonstrated a remarkable difference in overall survival (OS) time between low-risk (LR) and high-risk (HR) groups (P < 0.001). The RS contributed to the progression of PaC, and could be a significant independent factor for prognostic prediction. The validation of the ICGC cohort confirmed the effectiveness of the proposed signature. The patients with a HR score in the TCGA cohort had higher tumor mutation burden and more sensitivity to paclitaxel, gemcitabine, 5-fluorouracil and cisplatin than those with a LR score. The differential expression levels of signature genes were verified in vitro.Conclusion: The PRGs signature can be applied for predicting the prognosis of PaC, and may provide useful information for selection of therapeutic drugs.Keywords: pancreatic cancer, pyroptosis-related genes, TCGA, prognosis, bioinformatics analysis, tumor mutation burden

Keywords

• pancreatic cancer
• pyroptosis-related genes
• tcga
• prognosis
• bioinformatics analysis
• tumor mutation burden