Impact of deep sequencing on hepatocellular carcinoma utilizing high-throughput technology

Abstract

In the medical sciences, bioinformatics typically include compiling expression data for cells affected by various diseases, like cancer. Hepatocellular carcinoma (HCC) is a tumor of the liver, which is generally emerging in the setting of chronic liver diseases. Clinical behavior of hepatocellular carcinoma is difficult to estimate. Therefore, there is a critical demand to obtain new techniques that can assess the prognosis of hepatic cancer patients. Methods: this work produces a genomic study that spotlights on applying bioinformatics technologies to predict and deal with the molecular reasons for hepatocellular carcinoma by the examination whole-genome sequence of the chromosomal variations of the genomic copy number to grand correct diagnoses of this kind of disease. In this study, next-generation sequence (NGS) is utilized by applying OncoSNP-SEQ technique to a number of human chromosomes for analyzing hepatic cancer data that identify genome-wide mutations in copy number of the genomic information data. The outcomes referred to a certain number of chromosome aberrations detected with significant genes such as: SHC, TCP1, CCT3, SHC1, EPHA5, UGT2B28, UBE1L2, and also strike (CREB3L4, RAB1, MAGI2) genes which are discovered lately in 2013, tumor suppressors SHC1 and CKS1B, LRP1B, as well as oncogene UBE1L2, all of which may play a central role in cancer cell survival during the progress of metastases. Recently, the development of next-generation sequence empowers simultaneous assessment of copy number of hundred thousands of locales in a genome, more precise estimation of copy numbers, higher coverage, accurate confirmation of change points, and higher tendency to distinguish new alteration regions.