Wu, QiongQiongWuZheng, XubinXubinZhengProf. LEUNG Kwong SakWong, Man-HonMan-HonWongTsui, Stephen, Kwok-WingStephen, Kwok-WingTsuiCheng, LixinLixinCheng2023-02-202023-02-202022Bioinformatics, July 2022, vol. 38 (14), pp. 3513–3522.1367-48031367-4811http://hdl.handle.net/20.500.11861/7385Motivation Hepatocellular carcinoma (HCC) is a primary malignancy with a poor prognosis. Recently, multi-omics molecular-level measurement enables HCC diagnosis and prognosis prediction, which is crucial for early intervention of personalized therapy to diminish mortality. Here, we introduce a novel strategy utilizing DNA methylation and RNA expression data to achieve a multi-omics gene pair signature (GPS) for HCC discrimination. Results The immune genes with negative correlations between expression and promoter methylation are enriched in the highly connected cancer-related pathway network, which are considered as the candidates for HCC detection. After that, we separately construct a methylation GPS (mGPS) and an expression GPS (eGPS), and then assemble them as a meGPS with five gene pairs, in which the significant methylation and expression changes occur between HCC tumor and non-tumor groups. Reliable performance has been validated by independent tissue (age, gender and etiology) and blood datasets. This study proposes a procedure for multi-omics GPS identification and develops a novel HCC signature using both methylome and transcriptome data, suggesting potential molecular targets for the detection and therapy of HCC.enPeer Reviewed Journal Article10.1093/bioinformatics/btac379