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Identification and validation of Cystatin A as a novel promising therapeutic target for gastric cancer.
Xu, Qingyu; Xue, Shuai; Zhang, Yaqiong; Li, Jian; Qian, Peiyu; Zhang, Yanyan; Feng, Li.
Affiliation
  • Xu Q; Endoscopy Center, Minhang Hospital Affiliated to Fudan University, Shanghai, China.
  • Xue S; Endoscopy Center, Minhang Hospital Affiliated to Fudan University, Shanghai, China.
  • Zhang Y; Endoscopy Center, Minhang Hospital Affiliated to Fudan University, Shanghai, China.
  • Li J; Endoscopy Center, Minhang Hospital Affiliated to Fudan University, Shanghai, China.
  • Qian P; Endoscopy Center, Minhang Hospital Affiliated to Fudan University, Shanghai, China.
  • Zhang Y; Endoscopy Center, Minhang Hospital Affiliated to Fudan University, Shanghai, China.
  • Feng L; Endoscopy Center, Minhang Hospital Affiliated to Fudan University, Shanghai, China.
J Gastrointest Oncol ; 15(3): 873-889, 2024 Jun 30.
Article in En | MEDLINE | ID: mdl-38989439
ABSTRACT

Background:

The effect of pharmacological treatment of gastric cancer (GC) is limited, thus, it holds significant scientific importance to thoroughly investigate the molecular mechanisms underlying GC development and identify novel molecules capable of substantially extending patients' survival. This study utilized bioinformatics techniques to identify 11 genes associated with recurrence-free survival (RFS) in GC patients and investigated the potential biological functions of these genes through single-cell transcriptomic analysis. Subsequently, a single gene Cystatin A (CSTA) was selected for further analysis to explore its impact on signaling pathways and treatment.

Methods:

Differentially expressed genes (DEGs) were identified and overlapped in the analysis of RFS to identify potential prognostic genes for GC patients, based on data from the Cancer Genome Atlas-stomach adenocarcinoma (TCGA-STAD) and GSE54129. Subsequently, a prognostic model based on RFS in GC patients was established. Single-cell sequencing data were employed to explore the potential functions of these model genes. CSTA, one of the RFS-related genes, was further investigated using immunohistochemistry (IHC), Cell Counting Kit 8 (CCK-8), transwell, scratch, colony formation assays, flow cytometry, and Western blotting methods.

Results:

Through bioinformatics analysis, we identified 23 RFS-related genes in GC. Using the least absolute shrinkage and selection operator (LASSO)-Cox method, an RFS prognostic model was developed which pinpointed 11 GC prognosis-related (GPR) genes as significant factors influencing RFS in GC patients. The single-cell analysis revealed their potential role in affecting differentiation and maturation of pre-fibroblasts thereby impacting RFS in GC patients. CSTA exhibited low expression levels in GC tissues. Overexpression of CSTA promoted apoptosis in GC cells through the caspase-dependent apoptotic pathway and enhanced their response to cisplatin via this same pathway.

Conclusions:

The 11 GPR genes are primarily enriched within a specific type of stromal cell exhibiting heightened communication, metabolism, and differentiation levels. The gene signature of these stromal cells has implications for patient prognosis. Additionally, CSTA, a gene related to prognosis, has been shown to influence apoptosis levels in GC cells.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: J Gastrointest Oncol Year: 2024 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: J Gastrointest Oncol Year: 2024 Document type: Article