Discover oncology · 2026
Integrated scissor and CIBERSORTx analyses reveals fibroblast subpopulations and biomarkers in stomach adenocarcinoma.
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Wu Siyi, Cai Manzhong, Cai Jiajia, Chen Yong'an
Аннотация
BACKGROUND: Stomach adenocarcinoma (STAD) represents a significant global health challenge, characterized by high heterogeneity in its tumor microenvironment. This study aimed to create a cell composition assessment tool and identify STAD-associated biomarkers by combined analysis of single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data.
METHODS: A new signature matrix was constructed using CIBERSORTx for deconvolution analysis to gauge cell subpopulation proportions in bulk RNA-seq cohorts, followed by survival analysis to identify key cells. Weighted gene co-expression network analysis (WGCNA) was implemented to recognize key cell-related genes, which were further combined with differential expression analysis and survival analysis to determine biomarkers. Functional characterization was explored through enrichment analysis. The expression differences of biomarkers between STAD and normal groups were detected by quantitative real time polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC).
RESULTS: Fibroblasts were identified as the cell type most associated with STAD survival, among which cell-substrate junction fibroblasts (SJFs) were identified as the key subpopulation using our custom CIBERSORTx signature matrix. In patients with STAD, low expression levels of cysteine and glycine-rich protein 1 (CSRP1), lipoma-preferred partner (LPP), Nexilin (NEXN), palladin cytoskeletal associated protein (PALLD), and transforming growth factor beta 1-induced transcript 1 (TGFB1I1) were significantly associated with higher survival rates, indicating that low expression of these biomarkers predicted favorable prognosis. Functional analysis revealed that these biomarkers were involved in oxidative phosphorylation and Wnt signaling pathways. Moreover, CSRP1, LPP, NEXN, PALLD and TGFB1I1 were significantly upregulated in STAD samples at both mRNA and protein levels.
CONCLUSION: Characterization of cellular composition via a custom signature matrix identified SJFs as a key subpopulation in the STAD tumor microenvironment. The identified biomarkers (CSRP1, LPP, NEXN, PALLD, and TGFB1I1) offered valuable insights into STAD microenvironment regulation. Trial registration Not applicable.
METHODS: A new signature matrix was constructed using CIBERSORTx for deconvolution analysis to gauge cell subpopulation proportions in bulk RNA-seq cohorts, followed by survival analysis to identify key cells. Weighted gene co-expression network analysis (WGCNA) was implemented to recognize key cell-related genes, which were further combined with differential expression analysis and survival analysis to determine biomarkers. Functional characterization was explored through enrichment analysis. The expression differences of biomarkers between STAD and normal groups were detected by quantitative real time polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC).
RESULTS: Fibroblasts were identified as the cell type most associated with STAD survival, among which cell-substrate junction fibroblasts (SJFs) were identified as the key subpopulation using our custom CIBERSORTx signature matrix. In patients with STAD, low expression levels of cysteine and glycine-rich protein 1 (CSRP1), lipoma-preferred partner (LPP), Nexilin (NEXN), palladin cytoskeletal associated protein (PALLD), and transforming growth factor beta 1-induced transcript 1 (TGFB1I1) were significantly associated with higher survival rates, indicating that low expression of these biomarkers predicted favorable prognosis. Functional analysis revealed that these biomarkers were involved in oxidative phosphorylation and Wnt signaling pathways. Moreover, CSRP1, LPP, NEXN, PALLD and TGFB1I1 were significantly upregulated in STAD samples at both mRNA and protein levels.
CONCLUSION: Characterization of cellular composition via a custom signature matrix identified SJFs as a key subpopulation in the STAD tumor microenvironment. The identified biomarkers (CSRP1, LPP, NEXN, PALLD, and TGFB1I1) offered valuable insights into STAD microenvironment regulation. Trial registration Not applicable.