Dataset Information

The transcriptomic G1-G6 signature of hepatocellular carcinoma in an Asian population: Association of G3 with microvascular invasion.

ABSTRACT: In this study, a transcriptomic group classification based on a European population is tested on a Singapore cohort. The results highlight the genotype/phenotype correlation in a Southeast Asian population. The G1-G6 transcriptomic classification derived from hepatocellular carcinoma (HCC) resected from European patients, robustly reflected group-specific clinical/pathological features. We investigated the application of this molecular classification in Southeast Asian HCC patients.Gene expression analysis was carried out on HCC surgically resected in Singapore patients who were grouped into G1-G6 transcriptomic categories according to expression of 16 predictor genes (illustrated in Supplementary Table 1, http://links.lww.com/MD/B413 and Supplementary Fig. 1, http://links.lww.com/MD/B413) using quantitative reverse transcription polymerase chain reaction (RT-PCR). Univariate and multivariate polytomous logistic regression was used to investigate association between clinical variables and pooled transcriptomic classes G12, G3, and G456.HCC from Singapore (n?=?82) were distributed (%) into G1 (13.4), G2 (24.4), G3 (15.9), G4 (24.4), G5 (14.6), and G6 (7.3) subgroups. Compared to the European data, the Singapore samples were relatively enriched in G1-G3 versus G4-G6 tumors (53.7% vs 46.3%) reflecting the higher proportion of hepatitis B virus (HBV) patients in Singapore versus Europe samples (43% vs 30%). Pooled classes were defined as G12, G3, and G456. G12 was associated with higher alpha-fetoprotein (AFP) concentrations (OR?=?1.69, 95% CI: 1.30-2.20; P?

SUBMITTER: Allen JC

PROVIDER: S-EPMC5134855 | biostudies-other | 2016 Nov

REPOSITORIES: biostudies-other

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The transcriptomic G1-G6 signature of hepatocellular carcinoma in an Asian population: Association of G3 with microvascular invasion.

Allen John Carson JC Nault Jean-Charles JC Zhu Guili G Khor Andrew Yu Keat AYK Liu Jin J Lim Tony Kiat Hon TKH Zucman-Rossi Jessica J Chow Pierce K H PKH

Medicine 20161101 47

In this study, a transcriptomic group classification based on a European population is tested on a Singapore cohort. The results highlight the genotype/phenotype correlation in a Southeast Asian population. The G1-G6 transcriptomic classification derived from hepatocellular carcinoma (HCC) resected from European patients, robustly reflected group-specific clinical/pathological features. We investigated the application of this molecular classification in Southeast Asian HCC patients.Gene expressi ...[more]

PMID: 27893662

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Project description:BackgroundEfforts have been made to classify Hepatocellular Carcinoma (HCC) at surgically curable stages because molecular classification, which is prognostically informative, can accurately identify patients in need of additional early therapeutic interventions. Recently, HCC classification based French studies on the expression of 16 genes and 5 genes were proposed. In 16-gene classification, transcriptomic signatures (G1-G6) were used to classify HCC patients into clinical, genomic and pathway-specific subgroups. In 5-gene score classification, the good or poor prognosis of HCC patients was predicted. The patient's cohort in these studies was mainly from Caucasian and African populations. Here, we aimed to validate G1-G6 and 5-gene score signatures in 205 Korean HCC patients since genomic profiles of Korean patients are distinct from other regions.MethodsIntegrated analyses using whole-exome sequencing, copy number variation and clinical data was performed against these two signatures to find statistical correlations. Kaplan-Meier, univariate and multivariate COX regression analysis were performed for Disease-Specific Survival (DSS) and Recurrence-Free Survival (RFS).ResultsThe G2 and G3 subgroups of transcriptomic signature were significantly associated with TP53 mutations while G5 and G6 subgroups were significantly associated with CTNNB1 mutations which is in concordance with original French studies. Similarly, the poor prognosis group of 5-gene score showed shorter DSS (p = 0.045) and early RFS (p = 0.023) as well as a significant association with microvascular invasion, tumor size (> 5 cm), elevated AFP levels, and RB1 mutations. However, the 5-gene score was not an independent prognostic factor for survival.ConclusionThe G1-G6 and 5-gene signatures showed significant concordance between genetic profiles of Korean HCC patients and patients in original French studies. Thus, G1-G6 and 5-gene score signatures can be targeted as potential therapeutic biomarkers against HCC patients worldwide.

Project description:BackgroundRadiomics has emerged as a new approach that can help identify imaging information associated with tumor pathophysiology. We developed and validated a radiomics nomogram for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC).MethodsTwo hundred and eight patients with pathologically confirmed HCC (training cohort: n = 146; validation cohort: n = 62) who underwent preoperative gadoxetic acid-enhanced magnetic resonance (MR) imaging were included. Least absolute shrinkage and selection operator logistic regression was applied to select features and construct signatures derived from MR images. Univariate and multivariate analyses were used to identify the significant clinicoradiological variables and radiomics signatures associated with MVI, which were then incorporated into the predictive nomogram. The performance of the radiomics nomogram was evaluated by its calibration, discrimination, and clinical utility.ResultsHigher α-fetoprotein level (p = 0.046), nonsmooth tumor margin (p = 0.003), arterial peritumoral enhancement (p < 0.001), and the radiomics signatures of hepatobiliary phase (HBP) T1-weighted images (p < 0.001) and HBP T1 maps (p < 0.001) were independent risk factors of MVI. The predictive model that incorporated the clinicoradiological factors and the radiomic features derived from HBP images outperformed the combination of clinicoradiological factors in the training cohort (area under the curves [AUCs] 0.943 vs. 0.850; p = 0.002), though the validation did not have a statistical significance (AUCs 0.861 vs. 0.759; p = 0.111). The nomogram based on the model exhibited C-index of 0.936 (95% CI 0.895-0.976) and 0.864 (95% CI 0.761-0.967) in the training and validation cohort, fitting well in calibration curves (p > 0.05). Decision curve analysis further confirmed the clinical usefulness of the nomogram.ConclusionsThe nomogram incorporating clinicoradiological risk factors and radiomic features derived from HBP images achieved satisfactory preoperative prediction of the individualized risk of MVI in patients with HCC.

Dataset Information

The transcriptomic G1-G6 signature of hepatocellular carcinoma in an Asian population: Association of G3 with microvascular invasion.

Publications

The transcriptomic G1-G6 signature of hepatocellular carcinoma in an Asian population: Association of G3 with microvascular invasion.

Similar Datasets

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