Dataset Information

Circulating Osteopontin and Prediction of Hepatocellular Carcinoma Development in a Large European Population.

ABSTRACT: We previously identified osteopontin (OPN) as a promising marker for the early detection of hepatocellular carcinoma (HCC). In this study, we investigated the association between prediagnostic circulating OPN levels and HCC incidence in a large population-based cohort. A nested case-control study was conducted within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. During a mean follow-up of 4.8 years, 100 HCC cases were identified. Each case was matched to two controls and OPN levels were measured in baseline plasma samples. Viral hepatitis, liver function, and ?-fetoprotein (AFP) tests were also conducted. Conditional logistic regression models were used to calculate multivariable odds ratio (OR) and 95% confidence intervals (95% CI) for OPN levels in relation to HCC. Receiver operating characteristics curves were constructed to determine the discriminatory accuracy of OPN alone or in combination with other liver biomarkers in the prediction of HCC. OPN levels were positively associated with HCC risk (per 10% increment, ORmultivariable = 1.30; 95% CI, 1.14-1.48). The association was stronger among cases diagnosed within 2 years of follow-up. Adding liver function tests to OPN improved the discriminatory performance for subjects who developed HCC (AUC = 0.86). For cases diagnosed within 2 years, the combination of OPN and AFP was best able to predict HCC risk (AUC = 0.88). The best predictive model for HCC in this low-risk population is OPN in combination with liver function tests. Within 2 years of diagnosis, the combination of OPN and AFP best predicted HCC development, suggesting that measuring OPN and AFP could identify high-risk groups independently of a liver disease diagnosis. Cancer Prev Res; 9(9); 758-65. ©2016 AACR.

SUBMITTER: Duarte-Salles T

PROVIDER: S-EPMC5010922 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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Circulating Osteopontin and Prediction of Hepatocellular Carcinoma Development in a Large European Population.

Duarte-Salles Talita T Misra Sandeep S Stepien Magdalena M Plymoth Amelie A Muller David D Overvad Kim K Olsen Anja A Tjønneland Anne A Baglietto Laura L Severi Gianluca G Boutron-Ruault Marie-Christine MC Turzanski-Fortner Renee R Kaaks Rudolf R Boeing Heiner H Aleksandrova Krasimira K Trichopoulou Antonia A Lagiou Pagona P Bamia Christina C Pala Valeria V Palli Domenico D Mattiello Amalia A Tumino Rosario R Naccarati Alessio A Bueno-de-Mesquita H B As HB Peeters Petra H PH Weiderpass Elisabete E Quirós J Ramón JR Agudo Antonio A Sánchez-Cantalejo Emilio E Ardanaz Eva E Gavrila Diana D Dorronsoro Miren M Werner Mårten M Hemmingsson Oskar O Ohlsson Bodil B Sjöberg Klas K Wareham Nicholas J NJ Khaw Kay-Tee KT Bradbury Kathryn E KE Gunter Marc J MJ Cross Amanda J AJ Riboli Elio E Jenab Mazda M Hainaut Pierre P Beretta Laura L

Cancer prevention research (Philadelphia, Pa.) 20160623 9

We previously identified osteopontin (OPN) as a promising marker for the early detection of hepatocellular carcinoma (HCC). In this study, we investigated the association between prediagnostic circulating OPN levels and HCC incidence in a large population-based cohort. A nested case-control study was conducted within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. During a mean follow-up of 4.8 years, 100 HCC cases were identified. Each case was matched to two con ...[more]

PMID: 27339170

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Project description:Background and aimsHepatic arterial infusion chemotherapy (HAIC) using the FOLFOX regimen (oxaliplatin plus fluorouracil and leucovorin) is a promising option for large hepatocellular carcinoma (HCC). However, post-HAIC prognosis can vary in different patients due to tumor heterogeneity. Herein, we established two nomogram models to assess the survival prognosis of patients after HAIC combination therapy.MethodsA total of 1082 HCC patients who underwent initial HAIC were enrolled between February 2014 and December 2021. We built two nomogram models for survival prediction: the preoperative nomogram (pre-HAICN) using preoperative clinical data and the postoperative nomogram (post-HAICN) based on pre-HAICN and combination therapy. The two nomogram models were internally validated in one hospital and externally validated in four hospitals. A multivariate Cox proportional hazards model was used to identify risk factors for overall survival (OS). The performance outcomes of all models were compared by area under the receiver operating characteristic curve (AUC) analysis with the DeLong test.ResultsMultivariable analysis identified larger tumor size, vascular invasion, metastasis, high albumin-bilirubin grade, and high alpha-fetoprotein as indicators for poor prognosis. With these variables, the pre-HAICN provided three risk strata for OS in the training cohort: low risk (5-year OS, 44.9%), middle risk (5-year OS, 20.6%), and high risk (5-year OS, 4.9%). The discrimination of the three strata was improved significantly in the post-HAICN, which included the above-mentioned factors and number of sessions, combination with immune checkpoint inhibitors, tyrosine kinase inhibitors, and local therapy (AUC, 0.802 versus 0.811, p < 0.001).ConclusionsThe nomogram models are essential to identify patients with large HCC suitable for treatment with HAIC combination therapy and may potentially benefit personalized decision-making.Lay summaryHepatic arterial infusion chemotherapy (HAIC) provides sustained higher concentrations of chemotherapy agents in large hepatocellular carcinoma (HCC) by hepatic intra-arterial, result in better objective response outperformed the intravenous administration. HAIC is significantly correlated with favorable survival outcome and obtains extensive support in the effective and safe treatment of intermediate advanced-stage HCC. In view of the high heterogeneity of HCC, there is no consensus regarding the optimal tool for risk stratification before HAIC alone or HAIC combined with tyrosine kinase inhibitors or immune checkpoint inhibitors treatment in HCC. In this large collaboration, we established two nomogram models to estimate the prognosis and evaluate the survival benefits with different HAIC combination therapy. It could help physicians in decision-making before HAIC and comprehensive treatment for large HCC patients in clinical practice and future trials.

Project description:BackgroundStudies using metabolomic data have identified metabolites from several compound classes that are associated with disease-related lifestyle factors.ObjectiveIn this study, we identified metabolic signatures reflecting lifestyle patterns and related them to the risk of hepatocellular carcinoma (HCC) in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.DesignWithin a nested case-control study of 147 incident HCC cases and 147 matched controls, partial least squares (PLS) analysis related 7 modified healthy lifestyle index (HLI) variables (diet, BMI, physical activity, lifetime alcohol, smoking, diabetes, and hepatitis) to 132 targeted serum-measured metabolites and a liver function score. The association between the resulting PLS scores and HCC risk was examined in multivariable conditional logistic regression models, where ORs and 95% CIs were computed.ResultsThe lifestyle component's PLS score was negatively associated with lifetime alcohol, BMI, smoking, and diabetes, and positively associated with physical activity. Its metabolic counterpart was positively related to the metabolites sphingomyelin (SM) (OH) C14:1, C16:1, and C22:2, and negatively related to glutamate, hexoses, and the diacyl-phosphatidylcholine PC aaC32:1. The lifestyle and metabolomics components were inversely associated with HCC risk, with the ORs for a 1-SD increase in scores equal to 0.53 (95% CI: 0.38, 0.74) and 0.28 (0.18, 0.43), and the associated AUCs equal to 0.64 (0.57, 0.70) and 0.74 (0.69, 0.80), respectively.ConclusionsThis study identified a metabolic signature reflecting a healthy lifestyle pattern which was inversely associated with HCC risk. The metabolic profile displayed a stronger association with HCC than did the modified HLI derived from questionnaire data. Measuring a specific panel of metabolites may identify strata of the population at higher risk for HCC and can add substantial discrimination compared with questionnaire data. This trial was registered at clinicaltrials.gov as NCT03356535.

Dataset Information

Circulating Osteopontin and Prediction of Hepatocellular Carcinoma Development in a Large European Population.

Publications

Circulating Osteopontin and Prediction of Hepatocellular Carcinoma Development in a Large European Population.

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