Systematic Analysis of Tumor Stem Cell-related Gene Characteristics to Predict the PD-L1 Immunotherapy and Prognosis of Gastric Cancer
- Authors: Wang C.1, Chen Y.2, Zhou R.3, Yang Y.1, Fang Y.4
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Affiliations:
- Department of Gastrointestinal Medical Oncology, Fudan University Shanghai Cancer Center
- Department of Oncology, Tongren Hospital, Shanghai Jiao Tong University School of Medicine,
- Department of General Surgery,, Ruijin Hospital Luwan Branch, Shanghai Jiaotong University School of Medicine
- Department of Oncology, Shanghai Medical College, Fudan University
- Issue: Vol 31, No 17 (2024)
- Pages: 2467-2482
- Section: Anti-Infectives and Infectious Diseases
- URL: https://rjeid.com/0929-8673/article/view/644520
- DOI: https://doi.org/10.2174/0109298673278775231101064235
- ID: 644520
Cite item
Full Text
Abstract
Aims:We aimed to develop a prognostic model with stemness-correlated genes to evaluate prognosis and immunotherapy responsiveness in gastric cancer (GC).
Background:Tumor stemness is related to intratumoral heterogeneity, immunosuppression, and anti-tumor resistance. We developed a prognostic model with stemness-correlated genes to evaluate prognosis and immunotherapy responsiveness in GC.
Objective:We aimed to develop a prognostic model with stemness-correlated genes to evaluate prognosis and immunotherapy responsiveness in GC.
Methods:We downloaded single-cell RNA sequencing (scRNA-seq) data of GC patients from the Gene-Expression Omnibus (GEO) database and screened GC stemness- related genes using CytoTRACE. We characterized the association of tumor stemness with immune checkpoint blockade (ICB) and immunity. Thereafter, a 9-stemness signature-based prognostic model was developed using weighted gene co-expression network analysis (WGCNA), univariate Cox regression analysis, and the least absolute shrinkage and selection operator (LASSO) regression analysis. The model predictive value was evaluated with a nomogram.
Results:Early GC patients had significantly higher levels of stemness. The stemness score showed a negative relationship to tumor immune dysfunction and exclusion (TIDE) score and immune infiltration, especially T cells and B cells. A stemness-based signature based on 9 genes (ERCC6L, IQCC, NKAPD1, BLMH, SLC25A15, MRPL4, VPS35, SUMO3, and CINP) was constructed with good performance in prognosis prediction, and its robustness was validated in GSE26942 cohort. Additionally, nomogram and risk score exhibited the most powerful ability for prognosis prediction. High-risk patients exhibited a tendency to develop immune escape and low response to PD-L1 immunotherapy.
Conclusion:We developed a stemness-based gene signature for prognosis prediction with accuracy and reliability. This signature also helps clinical decision-making of immunotherapy for GC patients.
About the authors
Chenchen Wang
Department of Gastrointestinal Medical Oncology, Fudan University Shanghai Cancer Center
Email: info@benthamscience.net
Ying Chen
Department of Oncology, Tongren Hospital, Shanghai Jiao Tong University School of Medicine,
Email: info@benthamscience.net
Ru Zhou
Department of General Surgery,, Ruijin Hospital Luwan Branch, Shanghai Jiaotong University School of Medicine
Email: info@benthamscience.net
Yanan Yang
Department of Gastrointestinal Medical Oncology, Fudan University Shanghai Cancer Center
Email: info@benthamscience.net
Yantian Fang
Department of Oncology, Shanghai Medical College, Fudan University
Author for correspondence.
Email: info@benthamscience.net
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