Evidence map›Paper›PMID 42065054›Full record

ArticleOncology research2026

Integrative Machine Learning and Experimental Validation Identify MYBL2 as a Prognostic Biomarker and Therapeutic Target in Hepatocellular Carcinoma.

Ya-Ling Yang, Ying-Hsien Huang, Hung-Yu Lin

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Article in Oncology research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Ya-Ling YangDepartment of Anesthesiology, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan.
Ying-Hsien HuangDepartment of Pediatrics, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan.
Hung-Yu LinDepartment of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hepatocellular carcinoma (HCC) presents with poor treatment outcomes, creating an urgent need for novel biomarkers to improve diagnosis, prognosis, and precision medicine. While the MYB family of oncogenes is implicated in cancer, the role and regulatory mechanisms of its member, particularly MYB proto-oncogene like 2 (MYBL2), remain underexplored in HCC. Therefore, this study aimed to systematically validate the clinical significance of MYBL2, elucidate its functional role in tumor progression and drug sensitivity, and identify its upstream regulatory mechanisms using an integrative machine learning and experimental framework. Methods: We applied an integrative pipeline combining LASSO-based feature selection on TCGA and GEO cohorts, single-cell transcriptomics, pharmacogenomic surveys, and CRISPR dependency screens. These computational approaches were complemented by Results: MYBL2 robustly discriminated tumor from normal liver (AUC = 0.968), and high expression was associated with adverse features, including higher grade, microvascular invasion, HBV positivity, nonresponse to TACE, and worse survival. A nomogram combining MYBL2 with AJCC stage improved 1-, 3-, and 5-year AUCs versus stage alone. MYBL2 correlated with proliferative biomarkers (AFP, MKI67, PCNA, BIRC5) and CRISPR knockout inhibited growth in most HCC lines. High MYBL2 expression was associated with greater sensitivity to sorafenib in pharmacogenomic screens and was linked to an immunosuppressive microenvironment and higher MSI. Mechanistically, miR-29a was shown to suppress MYBL2 translation by directly binding to its 3 Conclusions: MYBL2 is a potent diagnostic and prognostic biomarker in HCC that also predicts sorafenib sensitivity. Our findings establish a clear regulatory link where MYBL2 is a direct and functionally important target of the tumor-suppressive miR-29a. This positions MYBL2 as a tractable target for miR-29a-based therapeutic strategies, warranting clinical validation for patient stratification and treatment development in HCC.

Indexed as

Biomarkers, TumorCarcinoma, HepatocellularCell Cycle ProteinsLiver NeoplasmsMachine LearningAnimalsGene Expression Regulation, NeoplasticHep G2 CellsHumansMaleMiceMice, TransgenicMicroRNAsPrognosisProto-Oncogene MasSorafenibBiomarkers, TumorCell Cycle ProteinsMAS1 protein, humanMicroRNAsMIRN29a microRNA, humanMYBL2 protein, humanProto-Oncogene MasSorafenibTrans-ActivatorsbiomarkerHepatocellular carcinomamiR-29aMYBL2precision medicineprognosistumor microenvironment

Identifiers

PMID42065054
PMCPMC13126373

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.