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作者

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

作者单位

Affiliations ¹ Department of Clinical Laboratory, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China. ² Department of Laboratory, Jinan Central Hospital Affiliated to Shandong First Medical University, Jinan, China. ³ Research Center of Basic Medicine, Jinan Central Hospital, Shandong First Medical University, Jinan, China. ⁴ Research Center of Basic Medicine, Jinan Central Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.

刊名

Frontiers in genetics

年份

2022

卷号

Vol.13

页码

965033

ISSN

1664-8021

关键词

gastric cancer immunotherapy lncRNA platelet prognosis

摘要

Background: Platelets have a significant effect in promoting cancer progression and hematogenous metastasis. However, the effect of platelet activation-related lncRNAs in gastric cancer is still poorly understood. In this study, we screened and validated PLT-related lncRNAs as potential biomarkers for prognosis and immunotherapy in GC patients. Methods: We obtained relevant datasets from the Cancer Genome Atlas and Gene Ontology Resource Database. Pearson correlation analysis was used to id...更多

Background: Platelets have a significant effect in promoting cancer progression and hematogenous metastasis. However, the effect of platelet activation-related lncRNAs in gastric cancer is still poorly understood. In this study, we screened and validated PLT-related lncRNAs as potential biomarkers for prognosis and immunotherapy in GC patients. Methods: We obtained relevant datasets from the Cancer Genome Atlas and Gene Ontology Resource Database. Pearson correlation analysis was used to identify PLT-related lncRNAs. By using the univariate, least absolute shrinkage and selection operator Cox regression analyses, we constructed the PLT-related lncRNAs model. Kaplan-Meier survival analysis, univariate, multivariate Cox regression analysis, and nomogram were used to verify the model. The Gene Set Enrichment Analysis , drug screening, tumor immune microenvironment analysis, epithelial-mesenchymal transition , and DNA methylation regulators correlation analysis were performed in the high- and low-risk groups. Patients were regrouped based on the risk model, and candidate compounds and immunotherapeutic responses aimed at GC subgroups were also identified. The expression of seven PLT-related lncRNAs was validated in clinical medical samples using quantitative reverse transcription-polymerase chain reaction . Results: In this study, a risk prediction model was established using seven PLT-related lncRNAs -, whose expression were validated in GC patients. Kaplan-Meier survival analysis, the receiver operating characteristic curve analysis, univariate, multivariate Cox regression analysis verified the accuracy of the model. We screened multiple targeted drugs for the high-risk patients. Patients in the high-risk group had a poorer prognosis since 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 based on risk score suggested a good ability to predict prognosis and high clinical benefits. Conclusion: Our findings provide new insights into how PLT-related lncRNAs biomarkers affect prognosis and immunotherapy. Also, these lncRNAs may become potential biomarkers and therapeutic targets for GC patients.收起

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