AUTHOR=Yuan Mingjie , Jia Yanfei , Xing Yuanxin , Wang Yunshan , Liu Yunyun , Liu Xiangdong , Liu Duanrui 

TITLE=Screening and validation of platelet activation-related lncRNAs as potential biomarkers for prognosis and immunotherapy in gastric cancer patients

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.965033

DOI=10.3389/fgene.2022.965033

ISSN=1664-8021

ABSTRACT=Background: Platelets (PLT) have a significant effect in promoting cancer progression and hematogenous metastasis. However, the effect of platelet activation-related lncRNAs (PLT-related lncRNAs) in gastric cancer (GC) is still poorly understood. 
Methods: Getting relevant datasets from the Cancer Genome Atlas (TCGA) and Gene Ontology (GO) Resource Database. Pearson correlation analysis was used to identify PLT-related lncRNAs. By univariate, least absolute shrinkage and selection operator (LASSO) Cox regression analyses, we constructed the PLT-related lncRNAs model. Then, using Kaplan-Meier survival analysis, univariate, multivariate Cox regression analysis and nomogram to verify the model. GSEA enrichment analysis, drug screening, tumor immune microenvironment analysis, epithelial-mesenchymal transition (EMT) and DNA methylation regulators correlation analysis were performed in high- and low-risk groups.  Patients were regrouped based on risk model, candidate compounds and immunotherapeutic response aimed at GC subgroups were also identified. And by PCR, the expression of 7 PLT-related lncRNAs were certified in clinical medical samples.
Results: In this study, a prediction model was established using 7 PLT-related lncRNAs (AL355574.1, LINC01697, AC002401.4, AC129507.1, AL513123.1, LINC01094, AL356417.2), whose expression were validated in gastric cancer patients. Kaplan-Meier survival analysis, ROC analysis, univariate, multivariate Cox regression analysis verified the accuracy of the model. Patients in the high-risk group had poorer prognosis are accompanied by low infiltration of immune killer cells, activation of immunosuppressive pathways and poor response to immunotherapy. In addition, we revealed a close relationship between risk scores and EMT and DNA methylation regulators. The nomogram basing on risk score suggested a good ability to predict prognosis and high clinical benefits.
Conclusions: Our findings provided new insights of how PLT-related lncRNA affects the prognosis and immunotherapy. And these lncRNAs may become potential therapeutic targets for GC patients.