Construction and comprehensive analysis of a novel prognostic signature associated with pyroptosis molecular subtypes in patients with pancreatic adenocarcinoma

Abstract

BackgroundTreatment of cancer with pyroptosis is an emerging strategy. Molecular subtypes based on pyroptosis-related genes(PRGs) seem to be considered more conducive to individualized therapy. It is meaningful to construct a pyroptosis molecular subtypes-related prognostic signature (PMSRPS) to predict the overall survival (OS) of patients with pancreatic adenocarcinoma(PAAD) and guide treatment.MethodsBased on the transcriptome data of 23 PRGs, consensus clustering was applied to divide the TCGA and GSE102238 combined cohort into three PRGclusters. Prognosis-related differentially expressed genes(DEGs) among PRGclusters were subjected to LASSO Cox regression analysis to determine a PMSRPS. External cohort and in vitro experiments were conducted to verify this PMSRPS. The CIBERSORT algorithm, the ESTIMATE algorithm and the Immunophenoscore (IPS) were used to analyze the infiltrating abundance of immune cells, the tumor microenvironment (TME), and the response to immunotherapy, respectively. Wilcoxon analysis was used to compare tumor mutational burden (TMB) and RNA stemness scores (RNAss) between groups. RT-qPCR and in vitro functional experiments were used for evaluating the expression and function of SFTA2.ResultsBased on three PRGclusters, 828 DEGs were obtained and a PMSRPS was subsequently constructed. In internal and external validation, patients in the high-risk group had significantly lower OS than those in the low-risk group and PMSRPS was confirmed to be an independent prognostic risk factor for patients with PAAD with good predictive performance. Immune cell infiltration abundance and TME scores indicate patients in the high-risk group have typical immunosuppressive microenvironment characteristics. Analysis of IPS suggests patients in the high-risk group responded better to novel immune checkpoint inhibitors (ICIs) than PD1/CTLA4. The high-risk group had higher TMB and RNAss. In addition, 10 potential small-molecule compounds were screened out. Finally, we found that the mRNA expression of SFTA2 gene with the highest risk coefficient in PMSRPS was significantly higher in PAAD than in paracancerous tissues, and knockdown of it significantly delayed the progression of PAAD.ConclusionsPMSRPS can well predict the prognosis, TME and immunotherapy response of patients with PAAD, identify potential drugs, and provide treatment guidance based on individual needs.

Currently Debated Topics on Surgical Treatment of Pancreatic Ductal Adenocarcinoma: A Narrative Review on Surgical Treatment of Borderline Resectable, Locally Advanced, and Synchronous or Metachronous Oligometastatic Tumor

“…However, the assumption that the anatomical characteristics used to define PDAC resectable, BR and LA, correspond to its well-defined behavior and that all patients who share the same anatomical profile must undergo the same sequence of treatments does not take into account the biological characteristics of PDAC [50][51][52]. Unfortunately, we are still waiting for an adequate definition of the role of different biomarkers in evaluating the prognosis of PDAC and its possible response to NAT, while there is not yet a generally accepted panel of immunohistochemical and/or biological biomarkers predictive of the evolution of the disease [53][54][55][56][57][58][69][70][71][73][74][75][76][77][78][79]. Furthermore, clinical decision making for patients with BR-PDAC may be altered by possible variability in the interpretation of CT images by radiologists and surgeons [34].…”

“…The assumption that the anatomical characteristics used to define resectable, BR, and LA PDAC are a marker of cancer behavior and that all patients who share a common anatomical profile should undergo the same sequence of treatments omits to consider the biological features of PDAC [50][51][52]. Furthermore, thanks to a study on the gene expression of PDAC, groups of patients with a low, intermediate, or high risk of invasion and metastasis, propensity for metastatic recurrence, and poor OS were identified [53][54][55][56][57][58]. Therefore, the rationale for choosing between UFS followed by adjuvant therapy and NAT followed by resection and adjuvant therapy for patients with BR-PDAC needs to be clearly defined.…”

The development of prognostic gene markers associated with disulfidptosis in gastric cancer and their application in predicting drug response

“…The correlation between risk score and MSI status was examined using the R software packages “plyr”, “ggpubr”, and “ggplot2” [ 17 ]. Stem cell correlation analysis was performed using R software packages “limma”, “ggpubr”, “ggplot2″, and “ggExtra”, employing Spearman's test [ [18] , [19] , [20] ].…”

SLC8A1, a novel prognostic biomarker and immunotherapy target in RSA and UCEC based on scRNA-seq and pan-cancer analysis

“…Immune, stromal, and ESTIMATE scores were calculated for UCEC patients using expression data (ESTIMATE) algorithms to estimate stromal and immune cells [22]. Based on the Cell Type Identi cation by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm, enrichment levels of 22 immune cells were calculated [23]. Each sample's immune activity can be determined accurately by single sample GSEA (ssGSEA) [24].…”