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Hepatocellular carcinoma (HCC) is a primary liver cancer with poor survival rates. Gene expression data of HCC are investigated to screen target genes and core genes, which are employed to propose a new strategy for the treatment of HCC. New concepts such as gene data streams, gene characteristic strength (CS), gene impact factor (GIF) and gene force (GF) are proposed. Together with gene community network (GCN), a novel algorithm, that is, called gene force algorithm (GFA), is presented to screen feature genes, target genes and core genes. The fifteen target genes are obtained, which can be divided into three clustering sets including HAMP Cluster = {HAMP, Trans, AQP4, VIPR1}, MT Cluster ={MT1H, MT1B, MT1G, MT1E, MTIL, RNAHP, DNASE1L3} and GPC3 Cluster ={GPC3}. The core genes of each clusters are HAMP, Metallothionein genes (MTs) and GPC3 respectively, where MTs is a general name for a group of metallothionein genes. According to the relationship between the three core genes and the metals including copper, iron and zinc, a treatment strategy for HCC is proposed, namely, "Supplement Zinc after surgery" for HCC patients. The proposed treatment method can be used to regulate the expression levels of HCC core genes.

Zinc Supplementation May Reduce The Risk of Hepatocellular Carcinoma Using Big Data Network Analysis