Abstract
Hepatocellular carcinoma (HCC) is one of the major cancer-related deaths worldwide. Genomic instability is correlated with the prognosis of cancers. A biomarker associated with genomic instability might be effective to predict the prognosis of HCC. In the present study, data of HCC patients from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases were used. A total of 370 HCC patients from the TCGA database were randomly classified into a training set and a test set. A prognostic signature of the training set based on nine overall survival (OS)–related genomic instability–derived genes (SLCO2A1, RPS6KA2, EPHB6, SLC2A5, PDZD4, CST2, MARVELD1, MAGEA6, and SEMA6A) was constructed, which was validated in the test and TCGA and ICGC sets. This prognostic signature showed more accurate prediction for prognosis of HCC compared with tumor grade, pathological stage, and four published signatures. Cox multivariate analysis revealed that the risk score could be an independent prognostic factor of HCC. A nomogram that combines pathological stage and risk score performed well compared with an ideal model. Ultimately, paired differential expression profiles of genes in the prognostic signature were validated at mRNA and protein level using HCC and paratumor tissues obtained from our institute. Taken together, we constructed and validated a genomic instability–derived gene prognostic signature, which can help to predict the OS of HCC and help us to explore the potential therapeutic targets of HCC.
Highlights
Hepatocellular carcinoma (HCC) is the sixth most prevalent cancer, and its mortality remains the fourth cancer-related deaths worldwide (Bray et al, 2018)
509 genes were identified to be differentially expressed in both the The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) sets, which were defined as genomic instability– derived genes (GIGs) in the present study (Figure 1C)
Based on the expression levels of the 509 GIGs, unsupervised hierarchical clustering analysis was performed on 374 samples of the TCGA set (Supplementary Figure 1C) and 237 samples of the ICGC set (Supplementary Figure 1D)
Summary
Hepatocellular carcinoma (HCC) is the sixth most prevalent cancer, and its mortality remains the fourth cancer-related deaths worldwide (Bray et al, 2018). The overall survival (OS) rate for HCC remains low because of its late stage at diagnosis and high recurrence after curative treatment (Bruix et al, 2014; Joliat et al, 2017; Zheng et al, 2017). Serum alpha-fetoprotein (AFP) is the traditional biomarker for diagnosis, outcome prediction, and evaluation of response to therapy in HCC. AFP is lack of sufficient specificity and sensitivity for diagnosis of HCC. The prognosis of HCC patients remains highly heterogeneous. Some effective and sensitive new biomarkers are needed to improve the prognosis of HCC patients
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