Dataset Information

The expression profile of Gasdermin C-related genes predicts the prognosis and immunotherapy response of pancreatic adenocarcinoma.

ABSTRACT: Pancreatic adenocarcinoma (PAAD) has a poor prognosis and is relatively unresponsive to immunotherapy. Gasdermin C (GSDMC) induces pyroptosis in cancer cells and inflammation in the tumor microenvironment. However, whether GSDMC expression in PAAD is associated with survival or response to immunotherapy remains unknown. GSDMC expression and the relationship between GSDMC and patient survival or immune infiltration in PAAD were examined using data in the The Cancer Genome Atlas (TCGA), Gene Expression Ominbus (GEO), Genotype-Tissue Expression (GTEx) and Cancer Cell Line Encyclopedia (CCLE) databases. The TCGA PAAD cohort could be divided into two distinct risk groups based on the expression of GSDMC-related genes (GRGs). The TIDE algorithm predicted that the low-risk group was more responsive to immune checkpoint blockade therapy than the high-risk group. A novel 15-gene signature was constructed and could predict the prognosis of PAAD. In addition, the 15-gene signature model predicted the infiltration of immune cells and Immune checkpoint blockade (ICB) treatment response. Immunohistochemical staining assessment of patient-derived human tissue microarray (TMA) from 139 cases of local PAAD patients revealed a positive correlation between GSDMC expression and PD-L1 expression but a negative correlation between GSDMC expression and infiltration of low CD8+ T cells. Moreover, the overexpression of GSDMC was related to poor overall survival (OS). This study suggests that GSDMC is a valuable biomarker for predicting PAAD prognosis and predicts the immunotherapy response of PAAD.

SUBMITTER: Xia XH

PROVIDER: S-EPMC10164816 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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The expression profile of Gasdermin C-related genes predicts the prognosis and immunotherapy response of pancreatic adenocarcinoma.

Xia Xiang-Hou XH Yin Wen-Juan WJ Mao Jie-Fei JF Liu Peng P Qin Chen-Dong CD Hu Jie-Jie JJ Liu Si-Yuan SY Wang Can-Ming CM Zou De-Hong DH Yang Hong-Jian HJ Yu Yang Y Huang Jian J

American journal of cancer research 20230415 4

Pancreatic adenocarcinoma (PAAD) has a poor prognosis and is relatively unresponsive to immunotherapy. Gasdermin C (GSDMC) induces pyroptosis in cancer cells and inflammation in the tumor microenvironment. However, whether GSDMC expression in PAAD is associated with survival or response to immunotherapy remains unknown. GSDMC expression and the relationship between GSDMC and patient survival or immune infiltration in PAAD were examined using data in the The Cancer Genome Atlas (TCGA), Gene Expre ...[more]

PMID: 37168356

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Project description:BackgroundThe tumor microenvironment plays an important role in the progression and malignancy of lung adenocarcinoma and affects the immunotherapy response. There is increasing evidence that long non-coding RNAs (lncRNAs) as competing endogenous RNAs (ceRNAs) have significant functions in the development and treatment response of various kinds of cancer. This study aimed to explore the association between immune-related lncRNA-microRNA (miRNA)-messenger RNA (mRNA)-ceRNA networks, and the prognosis of and immunotherapy response in lung adenocarcinoma.MethodsRNA-sequencing (RNA-seq) and miRNA-seq data from The Cancer Genome Atlas (TCGA) were used to evaluate the infiltration of immune cells in lung adenocarcinoma samples by undertaking a single-sample gene set enrichment analysis (ssGSEA) to divide the cells into high and low immune cell infiltration groups. The differentially expressed mRNA (DEmRNA) was further analyzed by a weighted gene co-expression network analysis (WGCNA), search tool for recurring instances of neighboring genes (STRING), and Cytoscape to select hub genes. The ceRNA network was constructed using Cytoscape. Additionally, survival analyses were conducted to screen out prognostic candidate genes.ResultsSeven thousand five hundred and thirty-eight mRNAs, 540 lncRNAs, and 138 miRNAs were found to be differentially expressed between the high and low immune cell infiltration groups. The two DEmRNA modules most significantly associated with immune cell infiltration were further analyzed, and four clusters, including 179 DEmRNAs, were selected based on Molecular Complex Detection (MCODE) scores. The selected DEmRNAs in the four clusters were mainly enriched in pathways involved in regulating the immune response. Ultimately, a ceRNA network of SNHG6-hsa-miR-30e-5p-CYSLTR1 was identified as being associated with the prognosis of and immunotherapy response in lung adenocarcinoma.ConclusionsThe present study extends understandings of immune-related lncRNA-miRNA-mRNA-ceRNA networks and identifies novel targets and a regulatory pathway for anti-tumor immunotherapy.

Project description:BackgroundLung adenocarcinoma (LUAD) continues to be the leading cause of cancer death worldwide, driven by environmental factors like smoking and genetic predispositions. LUAD has a high mortality rate, and new biomarkers are urgently needed to improve treatment strategies and patient management. Programmed cell death (PCD) is involved in tumor progression and response to treatment. Therefore, there is a need for an extensive study of the role and functions of PCD-related genes (PCDRGs) in lung adenocarcinoma so as to understand the pathophysiologic features of lung adenocarcinoma.MethodsBased on TCGA and GEO databases, this research is aimed at screening differentially expressed PCD-related genes in lung adenocarcinoma. We conducted GO, and KEGG analysis to establish the link between these genes and biological processes. By applying various machine learning algorithms such as CoxBoost analysis, we developed PCD-related indices (PCDI) that were used to verify their ability to predict prognosis with the use of other datasets. This was done in addition to exploring the biological functions of PCD genes associated with lung adenocarcinoma by assessing the relationship between immune cell components of tumor microenvironment and PCD genes together with examining how they affect drug sensitivity.ResultsThe research presented in this article offers significant insights into LUAD. The authors identified 113 PCDRGs that were differentially expressed in LUAD. These genes are implicated in various biological functions, including High risk ing apoptosis, ferroptosis, and pathways specific to non-small cell lung cancer. Notably, the PCDI proved effective in distinguishing between High risk and Low risk LUAD patients, demonstrating a higher accuracy in prognosis prediction compared to traditional clinical indicators such as age and gender. This high prediction accuracy was validated in both test and validation cohorts. Additionally, these genes showed significant correlations with immune cell infiltration and drug sensitivity in LUAD patients.ConclusionWe analysed the expression and function of PCDRGs in LUAD and revealed their correlation with patient survival, the immune microenvironment and drug sensitivity. The constructed PCDI model provides a scientific basis for the personalised treatment of lung adenocarcinoma, and future optimisation of treatment strategies based on these genes may improve patient clinical outcomes.

Dataset Information

The expression profile of Gasdermin C-related genes predicts the prognosis and immunotherapy response of pancreatic adenocarcinoma.

Publications

The expression profile of Gasdermin C-related genes predicts the prognosis and immunotherapy response of pancreatic adenocarcinoma.

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