Wang Xilong, Zhang Ying
Tumor Hematology Department, Liaoyang Central Hospital, Liaoyang, 111000, China.
General Surgery Department, Liaoyang Central Hospital, Liaoyang, 111000, China.
Discov Oncol. 2024 Dec 2;15(1):738. doi: 10.1007/s12672-024-01623-8.
Due to high mortality rate and limited treatments in gastric cancer (GC), call for deeper exploration of M2 macrophages as biomarkers is needed.
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.
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.
This study identified three biomarkers and constructed a diagnostic model, providing a new perspective for the research and treatment of GC.
由于胃癌（GC）死亡率高且治疗手段有限，因此需要更深入地探索M2巨噬细胞作为生物标志物。
本研究的数据来自基因表达综合数据库（GEO）和基因组数据共享库（GDC）。利用Seurat软件包进行单细胞RNA测序（scRNA-seq）分析。使用FindAllMarkers来识别不同细胞亚群中高表达的基因。利用DESeq2软件包筛选差异表达基因（DEG），同时使用limma软件包识别差异表达蛋白（DEP）。使用KOBAS-i数据库对基因进行富集分析。应用MultipleROC评估生物标志物的诊断潜力，并使用rms软件包构建诊断模型。利用hTFtarget数据库预测潜在的转录因子（TF）。最后，进行基于细胞的实验以验证筛选出的关键标志物的表达及潜在生物学功能。
本研究发现M2巨噬细胞在蛋白质、内质网和病毒相关途径中富集。通过筛选共获得4146个DEG和1946个DEP，其中有254个共同的DEG/DEP。基因功能富集分析结果表明，其可能通过DNA复制和细胞周期影响GC的发生发展。本研究鉴定出三个生物标志物，即HSPH1、HSPD1和IFI30，并基于这三个基因构建了诊断模型。AUC值大于0.8证明了该模型的可靠性。通过筛选TF，发现SPI1和KLF5是这三个生物标志物的共同TF。IFI30、HSPD1和HSPH1这三个基因在GC细胞中表达上调，且IFI30可能在GC细胞的迁移和侵袭中起促进作用。
本研究鉴定出三个生物标志物并构建了诊断模型，为GC的研究和治疗提供了新的视角。
