Literature DB >> 27339170

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

Talita Duarte-Salles1, Sandeep Misra2, Magdalena Stepien3, Amelie Plymoth4, David Muller5, Kim Overvad6, Anja Olsen7, Anne Tjønneland7, Laura Baglietto8, Gianluca Severi9, Marie-Christine Boutron-Ruault10, Renee Turzanski-Fortner11, Rudolf Kaaks11, Heiner Boeing12, Krasimira Aleksandrova12, Antonia Trichopoulou13, Pagona Lagiou13, Christina Bamia13, Valeria Pala14, Domenico Palli15, Amalia Mattiello16, Rosario Tumino17, Alessio Naccarati18, H B As Bueno-de-Mesquita19, Petra H Peeters20, Elisabete Weiderpass21, J Ramón Quirós22, Antonio Agudo23, Emilio Sánchez-Cantalejo24, Eva Ardanaz25, Diana Gavrila26, Miren Dorronsoro27, Mårten Werner28, Oskar Hemmingsson29, Bodil Ohlsson30, Klas Sjöberg31, Nicholas J Wareham32, Kay-Tee Khaw33, Kathryn E Bradbury34, Marc J Gunter35, Amanda J Cross36, Elio Riboli36, Mazda Jenab3, Pierre Hainaut37, Laura Beretta38.   

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 α-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. ©2016 American Association for Cancer Research.

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Year:  2016        PMID: 27339170      PMCID: PMC5010922          DOI: 10.1158/1940-6207.CAPR-15-0434

Source DB:  PubMed          Journal:  Cancer Prev Res (Phila)        ISSN: 1940-6215


  40 in total

1.  Independent risk factors and predictive score for the development of hepatocellular carcinoma in chronic hepatitis B.

Authors:  Man-Fung Yuen; Yasuhito Tanaka; Daniel Yee-Tak Fong; James Fung; Danny Ka-Ho Wong; John Chi-Hang Yuen; David Yiu-Kuen But; Annie On-On Chan; Benjamin Chun-Yu Wong; Masashi Mizokami; Ching-Lung Lai
Journal:  J Hepatol       Date:  2008-09-21       Impact factor: 25.083

Review 2.  Role of osteopontin in the pathophysiology of cancer.

Authors:  Lalita A Shevde; Rajeev S Samant
Journal:  Matrix Biol       Date:  2014-03-19       Impact factor: 11.583

3.  Risk prediction of hepatocellular carcinoma in patients with cirrhosis: the ADRESS-HCC risk model.

Authors:  Jennifer A Flemming; Ju Dong Yang; Eric Vittinghoff; W Ray Kim; Norah A Terrault
Journal:  Cancer       Date:  2014-07-16       Impact factor: 6.860

4.  Diagnostic values of alpha-fetoprotein, dickkopf-1, and osteopontin for hepatocellular carcinoma.

Authors:  Tianxiang Ge; Qiujin Shen; Ning Wang; Yurong Zhang; Zhouhong Ge; Wei Chu; Xiufang Lv; Fengbo Zhao; Weifeng Zhao; Jia Fan; Wenxin Qin
Journal:  Med Oncol       Date:  2015-02-06       Impact factor: 3.064

5.  A new laboratory-based algorithm to predict development of hepatocellular carcinoma in patients with hepatitis C and cirrhosis.

Authors:  Hashem B El-Serag; Fasiha Kanwal; Jessica A Davila; Jennifer Kramer; Peter Richardson
Journal:  Gastroenterology       Date:  2014-01-23       Impact factor: 22.682

6.  Hepatocellular carcinoma risk prediction model for the general population: the predictive power of transaminases.

Authors:  Chi-Pang Wen; Jie Lin; Yi Chen Yang; Min Kuang Tsai; Chwen Keng Tsao; Carol Etzel; Maosheng Huang; Chung Yi Hsu; Yuanqing Ye; Lopa Mishra; Ernest Hawk; Xifeng Wu
Journal:  J Natl Cancer Inst       Date:  2012-10-17       Impact factor: 13.506

7.  European Prospective Investigation into Cancer and Nutrition (EPIC): study populations and data collection.

Authors:  E Riboli; K J Hunt; N Slimani; P Ferrari; T Norat; M Fahey; U R Charrondière; B Hémon; C Casagrande; J Vignat; K Overvad; A Tjønneland; F Clavel-Chapelon; A Thiébaut; J Wahrendorf; H Boeing; D Trichopoulos; A Trichopoulou; P Vineis; D Palli; H B Bueno-De-Mesquita; P H M Peeters; E Lund; D Engeset; C A González; A Barricarte; G Berglund; G Hallmans; N E Day; T J Key; R Kaaks; R Saracci
Journal:  Public Health Nutr       Date:  2002-12       Impact factor: 4.022

8.  Development and validation of a simple NAFLD clinical scoring system for identifying patients without advanced disease.

Authors:  S A Harrison; D Oliver; H L Arnold; S Gogia; B A Neuschwander-Tetri
Journal:  Gut       Date:  2008-04-04       Impact factor: 23.059

9.  Osteopontin and latent-TGF β binding-protein 2 as potential diagnostic markers for HBV-related hepatocellular carcinoma.

Authors:  Andre Nogueira da Costa; Amelie Plymoth; Daniela Santos-Silva; Sandra Ortiz-Cuaran; Suzy Camey; Paule Guilloreau; Suleeporn Sangrajrang; Thiravud Khuhaprema; Maimuna Mendy; Olufunmilayo A Lesi; Hee-Kyung Chang; Jin-Kyoung Oh; Duk-Hee Lee; Hai-Rim Shin; Gregory D Kirk; Philippe Merle; Laura Beretta; Pierre Hainaut
Journal:  Int J Cancer       Date:  2014-05-15       Impact factor: 7.396

10.  Prediagnostic circulating vitamin D levels and risk of hepatocellular carcinoma in European populations: a nested case-control study.

Authors:  Veronika Fedirko; Talita Duarte-Salles; Christina Bamia; Antonia Trichopoulou; Krasimira Aleksandrova; Dimitrios Trichopoulos; Elisabeth Trepo; Anne Tjønneland; Anja Olsen; Kim Overvad; Marie-Christine Boutron-Ruault; Françoise Clavel-Chapelon; Marina Kvaskoff; Tilman Kühn; Annie Lukanova; Heiner Boeing; Brian Buijsse; Eleni Klinaki; Chrysanthi Tsimakidi; Alessio Naccarati; Giovanna Tagliabue; Salvatore Panico; Rosario Tumino; Domenico Palli; H Bas Bueno-de-Mesquita; Peter D Siersema; Petra H Peters; Eiliv Lund; Magritt Brustad; Karina Standahl Olsen; Elisabete Weiderpass; Raul Zamora-Ros; María-José Sánchez; Eva Ardanaz; Pilar Amiano; Carmen Navarro; J Ramón Quirós; Mårten Werner; Malin Sund; Björn Lindkvist; Johan Malm; Ruth C Travis; Kay-Tee Khaw; Magdalena Stepien; Augustin Scalbert; Isabelle Romieu; Pagona Lagiou; Elio Riboli; Mazda Jenab
Journal:  Hepatology       Date:  2014-08-28       Impact factor: 17.425

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  17 in total

1.  Should AFP (or any biomarkers) be used for HCC surveillance?

Authors:  Hager F Ahmed Mohammed; Lewis R Roberts
Journal:  Curr Hepatol Rep       Date:  2017-04-28

2.  Serum osteopontin is a predictor of prognosis for HBV-associated acute-on-chronic liver failure.

Authors:  Longgen Liu; Jianchun Lu; Chunyan Ye; Lin Lin; Shuqin Zheng; Hongyu Zhang; Qing Lan; Yuan Xue
Journal:  Biomed Rep       Date:  2017-12-13

3.  Acute-Phase Plasma Osteopontin as an Independent Predictor for Poor Outcome After Aneurysmal Subarachnoid Hemorrhage.

Authors:  Yoshinari Nakatsuka; Masato Shiba; Hirofumi Nishikawa; Mio Terashima; Fumihiro Kawakita; Masashi Fujimoto; Hidenori Suzuki
Journal:  Mol Neurobiol       Date:  2018-01-20       Impact factor: 5.590

Review 4.  Osteopontin and Transplantation: Where Are We Now?

Authors:  Beata Kaleta
Journal:  Arch Immunol Ther Exp (Warsz)       Date:  2021-05-21       Impact factor: 4.291

5.  Tailored algorithms for hepatocellular carcinoma surveillance: Is one-size-fits-all strategy outdated?

Authors:  Nicolas Goossens; C Billie Bian; Yujin Hoshida
Journal:  Curr Hepatol Rep       Date:  2017-02-01

Review 6.  Imaging inflammation and its resolution in health and disease: current status, clinical needs, challenges, and opportunities.

Authors:  Christina H Liu; Natalie D Abrams; Danielle M Carrick; Preethi Chander; Johanna Dwyer; Michelle R J Hamlet; Andrei L Kindzelski; Mercy PrabhuDas; Shang-Yi Anne Tsai; Merriline M Vedamony; Chiayeng Wang; Pushpa Tandon
Journal:  FASEB J       Date:  2019-10-09       Impact factor: 5.834

7.  Hepatocellular Carcinoma Risk Stratification by Genetic Profiling in Patients with Cirrhosis.

Authors:  Naoto Fujiwara; Yujin Hoshida
Journal:  Semin Liver Dis       Date:  2019-03-25       Impact factor: 6.512

8.  The Biomarkers for Predicting Viral HepatitisAssociated Hepatocellular Carcinoma.

Authors:  Qing Yang; Changfeng Sun; Yunjian Sheng; Wen Chen; Cunliang Deng
Journal:  Turk J Gastroenterol       Date:  2022-01       Impact factor: 1.555

9.  A Novel Biomarker Panel for the Early Detection and Risk Assessment of Hepatocellular Carcinoma in Patients with Cirrhosis.

Authors:  Ilvira M Khan; Donjeta Gjuka; Jingjing Jiao; Xiaoling Song; Ying Wang; Jing Wang; Peng Wei; Hashem B El-Serag; Jorge A Marrero; Laura Beretta
Journal:  Cancer Prev Res (Phila)       Date:  2021-03-08

Review 10.  Risk factors and prevention of hepatocellular carcinoma in the era of precision medicine.

Authors:  Naoto Fujiwara; Scott L Friedman; Nicolas Goossens; Yujin Hoshida
Journal:  J Hepatol       Date:  2017-10-06       Impact factor: 30.083

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