Abstract
Hepatocellular carcinoma (HCC) is a disease with unique management complexity because it displays high heterogeneity of molecular phenotypes. We herein aimed to characterize the molecular features of HCC by the development of a classification system that was based on the gene expression profile of metabolic genes. Integrative analysis was performed with a metadata set featuring 371 and 231 HCC human samples from the Cancer Genome Atlas and the International Cancer Genome Consortium, respectively. All samples were linked with clinical information. RNA sequencing data of 2752 previously characterized metabolism‐related genes were used for non‐negative matrix factorization clustering, and three subclasses of HCC (C1, C2, and C3) were identified. We then analyzed the metadata set for metabolic signatures, prognostic value, transcriptome features, immune infiltration, clinical characteristics, and drug sensitivity of subclasses, and compared the resulting subclasses with previously published classifications. Subclass C1 displayed high metabolic activity, low α‐fetoprotein (AFP) expression, and good prognosis. Subclass C2 was associated with low metabolic activities and displayed high expression of immune checkpoint genes, demonstrating drug sensitivity toward cytotoxic T‐lymphocyte‐associated protein‐4 inhibitors and the receptor tyrosine kinase inhibitor cabozantinib. Subclass C3 displayed intermediate metabolic activity, high AFP expression level, and bad prognosis. Finally, a 90‐gene classifier was generated to enable HCC classification. This study establishes a new HCC classification based on the gene expression profiles of metabolic genes, thereby furthering the understanding of the genetic diversity of human HCC.
Highlights
Hepatocellular carcinoma (HCC) is one of the most prevalent malignancies worldwide and the second leading cause of cancer-related deaths
Considering that the classification was based on metabolism-relevant genes, we further explored whether distinct subclasses had different metabolic characteristics
To identify HCC subgroup associated with metabolic processes and good prognosis, HCC classification was established in this study based on 2752 metabolic genes screened from previous publications
Summary
Hepatocellular carcinoma (HCC) is one of the most prevalent malignancies worldwide and the second leading cause of cancer-related deaths. On the basis of annual projections, more than 1 million patients will die from HCC in 2030 according to the World Health Organization estimation (Karb and Sclair, 2019). Despite the current new treatments and diagnostic methods for HCC, its prognosis is still dismal (Hoshida et al, 2014). It is critical to unravel the underlying molecular mechanisms of HCC diversity to develop targeted therapies (de Bono and Ashworth, 2010). Genome-wide analyses of mRNA expression profiles have been devoted to this purpose (Boyault et al, 2007; Chiang et al, 2008; Hoshida et al, 2009; Lee et al, 2004). Clinical samples were stratified in each transcriptome study, the correlations between the molecular and clinicopathological features have not been elucidated thoroughly
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