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Updated: May 2, 2026
Detection of Rare Mutations in CtDNA Using Next Generation Sequencing
Published on: August 24, 2017
Genome-wide transcriptional sequencing identifies novel mutations in metabolic genes in human hepatocellular
Daoud M Meerzaman1, Chunhua Yan, Qing-Rong Chen
1Center for Biomedical Informatics & Information Technology, 9609 Medical Center Drive, 1W466, Rockville, MD 20850, U.S.A. meerzamd@mail.nih.gov.
Abstract:
We report on next-generation transcriptome sequencing results of three human hepatocellular carcinoma tumor/tumor-adjacent pairs. This analysis robustly examined ∼12,000 genes for both expression differences and molecular alterations. We observed 4,513 and 1,182 genes demonstrating 2-fold or greater increase or decrease in expression relative to their normal, respectively. Network analysis of expression data identified the Aurora B signaling, FOXM1 transcription factor network and Wnt signaling pathways pairs being altered in HCC. We validated as differential gene expression findings in a large data set containing of 434 liver normal/tumor sample pairs. In addition to known driver mutations in TP53 and CTNNB1, our mutation analysis identified non-synonymous mutations in genes implicated in metabolic diseases, i.e. diabetes and obesity: IRS1, HMGCS1, ATP8B1, PRMT6 and CLU, suggesting a common molecular etiology for HCC of alternative pathogenic origin.
Insights
Next-generation sequencing reveals significant gene expression changes and novel mutations in hepatocellular carcinoma (HCC). These findings link metabolic diseases like diabetes and obesity to HCC
Area of Science:
- Genomics
- Molecular Biology
- Oncology
Background:
- Hepatocellular carcinoma (HCC) is a significant global health concern.
- Understanding the molecular basis of HCC is crucial for developing effective treatments.
Purpose of the Study:
- To investigate gene expression differences and molecular alterations in human HCC.
- To identify novel genetic drivers and pathways implicated in HCC development.
Main Methods:
- Next-generation transcriptome sequencing of three human HCC tumor/adjacent pairs.
- Analysis of approximately 12,000 genes for expression and mutations.
- Network analysis to identify altered signaling pathways.
- Validation of differential gene expression in a larger cohort (434 samples).
Main Results:
- Identified 4,513 upregulated and 1,182 downregulated genes (≥2-fold change) in HCC.
- Network analysis highlighted alterations in Aurora B, FOXM1, and Wnt signaling pathways.
- Discovered non-synonymous mutations in metabolic disease-associated genes (IRS1, HMGCS1, ATP8B1, PRMT6, CLU) alongside known mutations (TP53, CTNNB1).
Conclusions:
- Gene expression profiles and molecular alterations provide insights into HCC pathogenesis.
- Metabolic disease-related genes may play a role in HCC development.
- Findings suggest a common molecular etiology for HCC with diverse origins.
