关键词:
standardized process
genetic big data
prognostic biomarkers
Kaplan-Meier survival analysis
hepatocellular carcinoma
摘要:
The paper utilized a standardized methodology to identify prognostic biomarkers in hepatocellular carcinoma(HCC)by analyzing transcriptomic and clinical data from The Cancer Genome Atlas(TCGA)*** approach,which included stringent data preprocessing,differential gene expression analysis,and Kaplan-Meier survival analysis,provided valuable insights into the genetic underpinnings of *** comprehensive analysis of a dataset involving 370 HCC patients uncovered correlations between survival status and pathological characteristics,including tumor size,lymph node involvement,and distant *** processed transcriptome dataset,comprising 420 samples and annotating 26,783 genes,served as a robust platform for identifying differential gene expression *** the significant differential expression genes,the key genes such as FBXO43,HAGLROS,CRISPLD1,***,and ERN2,were pinpointed,which showed significant associations with patient survival outcomes,indicating their potential as novel prognostic *** study can not only enhance the understanding of HCC’s genetic landscape but also establish a blueprint for a standardized process to discover prognostic biomarkers of various diseases using genetic big *** research should focus on validating these biomarkers through independent cohorts and exploring their utility in the development of personalized treatment strategies.