Biology direct · 2026
Identification and prognostic analysis of genes related to CTNNB1 mutations in hepatocellular carcinoma.
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Zhu Ningqi, Zhang Guo, Shen Xiaotian, Chen Zule, Li Ying, Chen Diyu, Jia Huliang
Аннотация
BACKGROUND: Mutations in CTNNB1 are recognized oncogenic drivers of hepatocellular carcinoma (HCC); however, the downstream effector molecules and their prognostic significance remain incompletely defined. In this study, we developed a mutant CTNNB1 gene signature (MCGS) to predict CTNNB1 mutation status and to evaluate the prognostic relevance of the constituent genes.
METHODS: Hydrodynamic tail vein injection mouse models of HCC were generated by co-expressing Sleeping Beauty transposon/transposase and mutant CTNNB1 with either AKT-c-Myc or AKT-NRASG12V, followed by RNA sequencing of tumor tissues. Cross-species differential expression analyses were performed by integrating data from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). Machine-learning models were trained to identify MCGS. The prognostic value of signature genes was validated using public transcriptomic datasets and immunohistochemistry on an institutional tissue microarray (TMA) cohort.
RESULTS: Mutant CTNNB1 markedly accelerated hepatocarcinogenesis in mice, leading to earlier tumor development and reduced survival. Transcriptomic profiling revealed enrichment of the Hippo and MAPK signaling pathways in CTNNB1-mutant HCCs. We established a 15-gene MCGS using a Categorical Boosting algorithm, which accurately predicted CTNNB1 mutation status (AUC = 0.957 in TCGA; 0.893 in ICGC). Among these genes, metallothionein-3 (MT3) emerged as a prognostic marker, with high expression independently associated with poorer overall survival in public datasets. Consistently, elevated MT3 protein expression on the TMA was also independently associated with worse overall and recurrence-free survival in our institutional cohort.
CONCLUSION: We identified a robust mutant CTNNB1 gene signature capable of accurately predicting CTNNB1 mutation status, and uncovered MT3 as a novel, clinically relevant prognostic biomarker in HCC.
METHODS: Hydrodynamic tail vein injection mouse models of HCC were generated by co-expressing Sleeping Beauty transposon/transposase and mutant CTNNB1 with either AKT-c-Myc or AKT-NRASG12V, followed by RNA sequencing of tumor tissues. Cross-species differential expression analyses were performed by integrating data from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). Machine-learning models were trained to identify MCGS. The prognostic value of signature genes was validated using public transcriptomic datasets and immunohistochemistry on an institutional tissue microarray (TMA) cohort.
RESULTS: Mutant CTNNB1 markedly accelerated hepatocarcinogenesis in mice, leading to earlier tumor development and reduced survival. Transcriptomic profiling revealed enrichment of the Hippo and MAPK signaling pathways in CTNNB1-mutant HCCs. We established a 15-gene MCGS using a Categorical Boosting algorithm, which accurately predicted CTNNB1 mutation status (AUC = 0.957 in TCGA; 0.893 in ICGC). Among these genes, metallothionein-3 (MT3) emerged as a prognostic marker, with high expression independently associated with poorer overall survival in public datasets. Consistently, elevated MT3 protein expression on the TMA was also independently associated with worse overall and recurrence-free survival in our institutional cohort.
CONCLUSION: We identified a robust mutant CTNNB1 gene signature capable of accurately predicting CTNNB1 mutation status, and uncovered MT3 as a novel, clinically relevant prognostic biomarker in HCC.