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MiRNAs: new tools for molecular classification, diagnosis and prognosis of hepatocellular carcinoma.

ABSTRACT: Hepatocellular carcinoma (HCC) remains one of the most common malignancies worldwide, ranking as the third leading cause of cancer-related death. With recent advances in understanding HCC biology, progress has been made in early detection and management of HCC; however, its prognosis remains dismal. Novel biomarkers for HCC that are acceptable for clinical utility are urgently in need. Recently, miRNA has emerged as an important class of gene regulator that controls various cellular processes including cancer development. In HCC, miRNAs are frequently dysregulated, and studies have shown great promises of miRNAs as biomarkers for tumor classification, diagnosis and prognosis. Given miRNAs are highly stable in blood plasma and serum, they are suggested as a new class of noninvasive biomarker for detection of HCC. In this article, we provide an up-to-date review of the recent findings of the use of miRNAs in molecular classification of HCC tumors, diagnosis and prognosis.

SUBMITTER: Liu AM

PROVIDER: S-EPMC6095413 | biostudies-other | 2014 Jun

REPOSITORIES: biostudies-other

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miRNAs: new tools for molecular classification, diagnosis and prognosis of hepatocellular carcinoma.

Liu Angela M AM Wang Wei W Luk John M JM

Hepatic oncology 20140601 3

Hepatocellular carcinoma (HCC) remains one of the most common malignancies worldwide, ranking as the third leading cause of cancer-related death. With recent advances in understanding HCC biology, progress has been made in early detection and management of HCC; however, its prognosis remains dismal. Novel biomarkers for HCC that are acceptable for clinical utility are urgently in need. Recently, miRNA has emerged as an important class of gene regulator that controls various cellular processes in ...[more]

PMID: 30190966

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Project description:Background & aimsHepatocellular carcinoma (HCC) is the second most lethal cancer caused by lack of effective therapies. Although promising, HCC molecular classification, which enriches potential responders to specific therapies, has not yet been assessed in clinical trials of anti-HCC drugs. We aimed to overcome these challenges by developing clinicopathological surrogate indices of HCC molecular classification.MethodsHepatocellular carcinoma classification defined in our previous transcriptome meta-analysis (S1, S2 and S3 subclasses) was implemented in an FDA-approved diagnostic platform (Elements assay, NanoString). Ninety-six HCC tumours (training set) were assayed to develop molecular subclass-predictive indices based on clinicopathological features, which were independently validated in 99 HCC tumours (validation set). Molecular deregulations associated with the histopathological features were determined by pathway analysis. Sample sizes for HCC clinical trials enriched with specific molecular subclasses were determined.ResultsHepatocellular carcinoma subclass-predictive indices were steatohepatitic (SH)-HCC variant and immune cell infiltrate for S1 subclass, macrotrabecular/compact pattern, lack of pseudoglandular pattern, and high serum alpha-foetoprotein (>400 ng/ml) for S2 subclass, and microtrabecular pattern, lack of SH-HCC and clear cell variants, and lower histological grade for S3 subclass. Macrotrabecular/compact pattern, a predictor of S2 subclass, was associated with the activation of therapeutically targetable oncogene YAP and stemness markers EPCAM/KRT19. BMP4 was associated with pseudoglandular pattern. Subclass-predictive indices-based patient enrichment reduced clinical trial sample sizes from 121, 184 and 53 to 30, 43 and 22 for S1, S2 and S3 subclass-targeting therapies respectively.ConclusionsHepatocellular carcinoma molecular subclasses can be enriched by clinicopathological indices tightly associated with deregulation of therapeutically targetable molecular pathways.

Dataset Information

MiRNAs: new tools for molecular classification, diagnosis and prognosis of hepatocellular carcinoma.

Publications

miRNAs: new tools for molecular classification, diagnosis and prognosis of hepatocellular carcinoma.

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