Identification of a Novel Prognostic Classifier for Platelet-related Genes Characteristics and Prognostic Significance of Aberrant Expression of PAFAH1B3 in Hepatocellular Carcinoma

Background: Complex crosstalk between tumor cells and platelets is closely related to the development, relapse, and drug resistance of hepatocellular carcinoma (HCC). Therefore, an intensive analysis of the relationship between platelet-related genes and the effectiveness of immunotherapy is necessary for improving the poor prognosis of HCC patients. MethodsGenes associated with platelets in the GeneCards database were collected and were used to identified molecular subtypes using a non-negative matrix decomposition algorithm (NMF) and constructed a platelet-related genes-based prognostic stratification model by the LASSO-Cox regression and stepwise Cox regression analysis. The effect of this feature on the immune microenvironment of HCC and the response to immune checkpoint inhibitors was also explored.ResultsAfter identifying two molecular subtypes, we constructed a platelet-related genes-based prognostic stratification model that can be effectively used for immune checkpoint inhibitor (PD1, PD-L1, PD-L2, and CTLA4) efficacy and prognosis prediction in HCC patients, which was subsequently validated using patient samples from ICGC, GSE14520 and a small sample size clinical cohort. We also found downregulation of PAFAH1B3 remarkably inhibited the proliferation and migration ability of Hep3B cells. ConclusionsIn conclusion, we constructed a prognostic classifier based on platelet-related genes that could effectively classify HCC patients for prognostic prediction provide new light on the selection of optimal individualized antiplatelet therapy for HCC patients in future clinical practice.