ArticleDiscover oncology2024
Multi-omics joint screening of biomarkers related to M2 macrophages in gastric cancer.
Article in Discover oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Decoding Dementia Mechanisms: Identification of Key Oligodendrocyte- Associated Genes through Integrative Bioinformatics and Machine Learning.Current topics in medicinal chemistry · 2026Article
- Diagnostic Biomarkers and Targeted Drug Prediction for Acute Kidney Injury: A Computational ApproachEndocrine, metabolic & immune disorders drug targets · 2026Article
- Single-cell multi-omics in biliary tract cancers: decoding heterogeneity, microenvironment, and treatment strategies.Molecular biomedicine · 2025Review
- Screening and validation of diagnostic markers for keloids via bioinformatics analysis.Biochemistry and biophysics reports · 2025Article
- Identification and analysis of pyroptosis-related key genes in heart failure.Journal of cardiothoracic surgery · 2025Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDue to high mortality rate and limited treatments in gastric cancer (GC), call for deeper exploration of M2 macrophages as biomarkers is needed.
methodsThe data for this study were obtained from the Gene Expression Omnibus (GEO) and Genomic Data Commons (GDC). The Seurat package was utilized for single-cell RNA sequencing (scRNA-seq) analysis. FindAllMarkers was used to identify genes highly expressed among different cell subsets. DESeq2 package was leveraged to screen differentially expressed genes (DEGs), while limma package was utilized for identifying differentially expressed proteins (DEPs). Enrichment analyses of the genes were conducted using KOBAS-i database. MultipleROC was applied to evaluate the diagnostic potential of biomarkers, and rms package was utilized to construct diagnostic models. hTFtarget database was utilized to predict potential transcription factors (TFs). Finally, cell-based assays were performed to validate the expression and potential biological functions of the screened key markers.
resultsThis study found that M2 macrophages were enriched in protein, endoplasmic reticulum, and virus-related pathways. A total of 4146 DEGs and 1946 DEPs were obtained through screening, with 254 common DEGs/DEPs. The results of gene function enrichment analysis suggested that it may affect the occurrence and development of GC through DNA replication and cell cycle. This study identified three biomarkers, HSPH1, HSPD1, and IFI30, and constructed a diagnostic model based on these three genes. The AUC value greater than 0.8 proved the reliability of the model. Through screening TFs, SPI1 and KLF5 were found to be the common TFs for the three biomarkers. The expression of the three genes IFI30, HSPD1 and HSPH1 was up-regulated in GC cells, and IFI30 may play a facilitating role in the migration and invasion of GC cells.
conclusionThis study identified three biomarkers and constructed a diagnostic model, providing a new perspective for the research and treatment of GC.
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