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Potential Circulating Biomarkers of Recurrence after Hepatic Resection or Liver Transplantation in Hepatocellular Carcinoma Patients.

ABSTRACT: Background: Improving surgical outcomes in hepatocellular carcinoma (HCC) patients would greatly benefit from biomarkers. Angiogenesis and inflammation are hallmarks of HCC progression and therapeutic targets. Methods: We retrospectively evaluated preoperative clinical variables and circulating (plasma) biomarkers of angiogenesis and inflammation in a cohort of HCC patients who underwent liver resection (LR) or transplantation (LT). Biomarker correlation with outcomes-freedom of liver recurrence (FLR), disease-free survival (DFS) and overall survival (OS)-was tested using univariate and multivariate Cox regression analyses. Results: Survival outcomes associated with sVEGFR1, VEGF and VEGF-C in LT patients and with IL-10 in LR patients. Moreover, in LT patients within Milan criteria, higher plasma VEGF and sVEGFR1 were associated with worse outcomes, while in those outside Milan criteria lower plasma VEGF-C associated with better outcomes. Multivariate analysis indicated that adding plasma VEGF or VEGF-C to a predictive model including Milan criteria and AFP improved prediction of DFS and OS (all p < 0.05). Conclusion: Survival outcomes after LR or LT differentially associated with angiogenic and inflammatory biomarkers. High plasma VEGF correlated with poorer prognosis within Milan criteria while low plasma VEGF-C associated with better prognosis outside Milan criteria. These candidate biomarkers should be further validated to improve patient stratification.

SUBMITTER: Duda DG

PROVIDER: S-EPMC7281651 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Potential Circulating Biomarkers of Recurrence after Hepatic Resection or Liver Transplantation in Hepatocellular Carcinoma Patients.

Duda Dan G DG Dima Simona O SO Cucu Dana D Sorop Andrei A Klein Sebastian S Ancukiewicz Marek M Kitahara Shuji S Iacob Speranta S Bacalbasa Nicolae N Tomescu Dana D Herlea Vlad V Tanase Cristiana C Croitoru Adina A Popescu Irinel I

Cancers 20200518 5

<i>Background:</i> Improving surgical outcomes in hepatocellular carcinoma (HCC) patients would greatly benefit from biomarkers. Angiogenesis and inflammation are hallmarks of HCC progression and therapeutic targets. <i>Methods:</i> We retrospectively evaluated preoperative clinical variables and circulating (plasma) biomarkers of angiogenesis and inflammation in a cohort of HCC patients who underwent liver resection (LR) or transplantation (LT). Biomarker correlation with outcomes-freedom of li ...[more]

PMID: 32443546

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Project description:BackgroundThere is a growing need for new improved classifiers of prognosis in hepatocellular carcinoma (HCC) patients to stratify them effectively.MethodsA deep learning model was developed on a total of 1118 patients from 4 independent cohorts. A nucleus map set (n = 120) was used to train U-net to capture the nuclear architecture. The training set (n = 552) included HCC patients that had been treated by resection. The liver transplantation (LT) set (n = 144) contained patients with HCC that had been treated by LT. The train set and its nuclear architectural information extracted by U-net were used to train the MobileNet V2-based classifier (MobileNetV2_HCC_class). The classifier was then independently tested on the LT set and externally validated on the TCGA set (n = 302). The primary outcome was recurrence free survival (RFS).ResultsThe MobileNetV2_HCC_class was a strong predictor of RFS in both LT set and TCGA set. The classifier provided a hazard ratio of 3.44 (95% CI 2.01-5.87, p < 0.001) for high risk versus low risk in the LT set, and 2.55 (95% CI 1.64-3.99, p < 0.001) when known prognostic factors, remarkable in univariable analyses on the same cohort, were adjusted. The MobileNetV2_HCC_class maintained a relatively higher discriminatory power [time-dependent accuracy and area under curve (AUC)] than other factors after LT or resection in the independent validation set (LT and TCGA set). Net reclassification improvement (NRI) analysis indicated MobileNetV2_HCC_class exhibited better net benefits for the Stage_AJCC beyond other independent factors. A pathological review demonstrated that tumoral areas with the highest recurrence predictability featured the following features: the presence of stroma, a high degree of cytological atypia, nuclear hyperchromasia, and a lack of immune cell infiltration.ConclusionA prognostic classifier for clinical purposes had been proposed based on the use of deep learning on histological slides from HCC patients. This classifier assists in refining the prognostic prediction of HCC patients and identifies patients who have been benefited from more intensive management.

Project description:BackgroundCancer-related inflammation has been correlated with cancer prognosis. This study evaluated inflammatory biomarkers, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and lymphocyte-to-monocyte ratio (LMR), programmed death ligand (PD-L) 1 expression, and tumour microenvironment in relation to prognosis and clinicopathological features of patients with hepatocellular carcinoma (HCC) undergoing curative hepatic resection.MethodsPatients who had liver resection for HCC in 2000-2011 were analysed. Univariable and multivariable analyses were conducted for overall (OS) and recurrence-free (RFS) survival. Immunohistochemical analyses of PD-L1, CD8 and CD68 expression were performed. HCC cell lines were evaluated for PD-L1 expression. A subgroup analysis was conducted to determine patient features, survival and the tumour microenvironment. Results were validated in a cohort of patients with HCC treated surgically in 2012-2016.ResultsSome 281 patients who underwent hepatic resection for HCC were included. Multivariable analysis showed that low LMR was an independent prognostic factor of OS (hazard ratio (HR) 1·59, 95 per cent c.i. 1·00 to 2·41; P = 0·045) and RFS (HR 1·47, 1·05 to 2·04; P = 0·022) after resection. Low preoperative LMR values were correlated with higher α-fetoprotein values (P < 0·001), larger tumour size (P < 0·001), and high rates of poor differentiation (P = 0·035) and liver cirrhosis (P = 0·008). LMR was significantly lower in PD-L1-positive patients than in those with PD-L1 negativity (P < 0·001). Results were confirmed in the validation cohort. PD-L1 expression was upregulated in HCC cell lines treated with interferon-γ and co-cultured with THP-1 monocyte cells.ConclusionLMR is an independent predictor of survival after hepatic resection in patients with HCC. Modulation of the immune checkpoint pathway in the tumour microenvironment is associated with a low LMR.

Dataset Information

Potential Circulating Biomarkers of Recurrence after Hepatic Resection or Liver Transplantation in Hepatocellular Carcinoma Patients.

Publications

Potential Circulating Biomarkers of Recurrence after Hepatic Resection or Liver Transplantation in Hepatocellular Carcinoma Patients.

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