Discover Oncology (Dec 2024)

Multi-omics joint screening of biomarkers related to M2 macrophages in gastric cancer

  • Xilong Wang,
  • Ying Zhang

DOI
https://doi.org/10.1007/s12672-024-01623-8
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 15

Abstract

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Abstract Background Due to high mortality rate and limited treatments in gastric cancer (GC), call for deeper exploration of M2 macrophages as biomarkers is needed. Methods The 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. Results This 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. Conclusion This study identified three biomarkers and constructed a diagnostic model, providing a new perspective for the research and treatment of GC.

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