ArticleHereditas2025
Identification of biomarkers associated with proliferation and differentiation of mesenchymal stem cells in pulmonary adenocarcinoma and establishment of prognostic models.
Article in Hereditas, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- The bibliometric and visualized analysis on cancer stem cells in the early 21st century.International journal of surgery (London, England) · 2026Review
- [Integrative Analysis of Multi-source Public Databases to Screen Core Genes for Constructing A Prognostic Risk Model in Lung Adenocarcinoma].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundMesenchymal stem cells (MSCs) hold potential as therapeutic agents in cancer, but their mechanisms in lung adenocarcinoma (LUAD) remain poorly understood. This study aimed to identify biomarkers associated with MSC proliferation and differentiation (MSCPD) and investigate their regulatory roles in LUAD.
methodsUsing the TCGA-LUAD and GSE72094 datasets, MSCPD-related gene (MSCPD-RG) scores were calculated, and samples were divided into high and low subgroups. Differentially expressed genes (DEGs1: between subgroups; DEGs2: tumor vs. normal) and module genes derived from weighted gene co-expression network analysis (WGCNA) were examined. Overlapping genes were subjected to Cox and LASSO regression to identify potential biomarkers. A prognostic risk model was developed and validated, followed by functional, immune, and drug sensitivity analyses.
resultsFour biomarkers (MS4A2, IGSF10, NTRK3, MFAP3L) were identified from 1,061 DEGs1, 6,604 DEGs2, and 610 module genes. The risk model based on these biomarkers accurately stratified prognosis. Both T stage and risk score were independent prognostic factors, and a nomogram integrating these factors demonstrated high predictive accuracy. These biomarkers were notably enriched in pathways related to ribosome function, cell cycle regulation, and oxidative phosphorylation. Immune cell analysis revealed significant differences in nine immune cell types (e.g., plasma cells, CD4 memory T cells) between LUAD and normal tissues.
conclusionIn this study, four key biomarkers closely related to mesenchymal stem cell proliferation/differentiation (MSCPD) were identified in lung adenocarcinoma (LUAD), namely MS4A2, IGSF10, NTRK3, and MFAP3L. Through multi-omics integrated analysis and independent cohort validation, it was confirmed that these markers not only affect disease progression by regulating mesenchymal - epithelial transition (MET) and tumor microenvironment remodeling but can also effectively predict patient prognosis and response to immunotherapy.
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