TY  - JOUR
TI  - Bioinformatics Data Analyses Revealed Novel Prognostic Biomarker Candidates For Hepatocellular Carcinoma
AB  - Objective: Hepatocellular carcinoma (HCC) is a frequently diagnosed cancer type with low overallsurvival (OS) rates. Known prognostic biomarkers of HCC are inefficient to monitor diseaseprogression. Therefore, identification of novel patient OS time predictive biomarkers is needed.Materials and Methods: Cbioportal, OncoLnc, and dbDEMC tools were utilized to analyse DNAsequencing, mRNA-sequencing and miRNA-sequencing data of HCC patients in The CancerGenome Atlas (TCGA) database. Integrated molecular interactions network of the novel biomarkercandidates were generated using NetworkAnalyst and MiRNet tools.Results: Next generation sequencing data analyses revealed expression profiles of 11 frequentlymutated and differentially expressed genes as well as two differentially expressed miRNAs, whichpredict OS time. Transcriptional upregulation of GPATCH4 gene (P:0.009) and downregulation offour genes (PPARGC1A P:0.000013, PIK3R1 P:0.002, COL18A1 P:0.009, and A1BG P:0.01) werecorrelated with poor prognosis of HCC patients, for the first time. Integrated network of thesemolecules also revealed novel regulatory molecules and interactions associated with prognosis ofHCC.Conclusion: As a resul of this study, in silico data that can benefit the development of novelmolecularly targeted diagnostic and therapeutic applications specific to HCC have been obtained.
AU  - YILDIZ, Gokhan
PY  - 2020
JO  - Fırat Üniversitesi Sağlık Bilimleri Tıp Dergisi
VL  - 34
IS  - 2
SN  - 1308-9315
SP  - 123
EP  - 129
DB  - TRDizin
UR  - http://search/yayin/detay/428830
ER  -