AUTHOR=Yin Zhenhua , Qiao Yating , Shi Jianping , Bu Limei , Ao Li , Tang Wenqing , Lu Xiaolan 

TITLE=Identification of Costimulatory Molecule–Related lncRNAs Associated With Gastric Carcinoma Progression: Evidence From Bioinformatics Analysis and Cell Experiments

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.950222

DOI=10.3389/fgene.2022.950222

ISSN=1664-8021

ABSTRACT=Costimulatory molecules (CMGs) play essential roles in multiple cancers. However, the lncRNAs regulating costimulatory molecules have not been fully explored in gastric cancer (GC). Public data of GC patients were obtained from The cancer genome atlas database. R software v4.1.1, SPSS v13.0 and GraphPad Prism 8 were used to perform all the analysis. Limma package was used for differential expression analysis. Survival package was used for patients prognosis analysis. Gene set enrichment analysis (GSEA), gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) analysis was used for pathway enrichment analysis. qRT-PCR was used to detect the RNA level of target lncRNA. CCK8 and colony formation assay was used to assess the proliferation ability of GC cells. Transwell assay was used to evaluate the invasion and migration ability of GC cells. We firstly identified CMGs-related lncRNAs (CMLs) through co-expression analysis. Then, an eight CMLs based signature was constructed to predict patients overall survival (OS), which showed satisfactory predictive efficiency (Training cohort: 1-year AUC = 0.764, 3-year AUC = 0.810, 5-year AUC = 0.840; Validation cohort: 1-year AUC = 0.661, 3-year AUC = 0.718, 5-year AUC = 0.822). The patients in high risk group tend to have a worse prognosis. GSEA analysis showed that epithelial-mesenchymal transition, KRAS signaling, angiogenesis was aberrantly activated in high risk patients. GO and KEGG analysis indicated that the biological difference between high and low risk patients was mainly enriched in extracellular matrix. Immune infiltration analysis showed that macrophages (M1, M2), dendritic cells, monocytes, Tregs and T regulatory cells were positively correlated with the riskscores, partly responsible for the worse OS of high risk patients. Finally, the lncRNA AP000695.2 was selected for further experiments. The result showed that AP000695.2 was upregulated in GC cell lines and could facilitate the proliferation, invasion and migration of GC cells. In summary, this study established an effective prognosis model based on eight CMLs, which would be helpful for further therapy options for cancer. Also, we found that AP000695.2 could promote GC cell malignant phenotype, making it an underlying therapy target in GC.