Future directions in imaging and biomarkerbased HCC surveillance
Future directions in imaging and biomarkerbased HCC surveillance in NAFLD-related liver disease Sven M. A. Francque, MD, Ph. D Chair, Department of Gastroenterology and Hepatology Antwerp University Hospital, Belgium Professor of Hepatology Chair, Translational Sciences in Inflammation and Immunology (TWI 2 N) University of Antwerp, Belgium
Disclosures consultancy and/or speaker for Abbvie, Gilead, MSD, BMS, Roche, Bayer, Aktelion, Janssen, Intercept, Genfit, Inventiva, GSK, Boehringer Ingelheim, Galmed, Genentech, Galapagos, Enyo, Aligos, Novo Nordisk. 2
• Biomarkers in NAFLD - Diagnosis/screening/case finding - Monitoring of disease progression - Monitoring of treatment response • Biomarkers in (NAFLD-associated) HCC Context of use FDA BEST Criteria - Surveillance and early diagnosis - Prognosis - Treatment response • Prediction • Monitoring - Predictive of future HCC development/risk stratification? • NAFLD-cirrhosis • HCC in non-cirrhotic NAFLD 3
Biomarkers in NAFLD 4
Dulai et al. Hepatology 2017 5
• Fibrosis is the strongest predictor of outcome - Overall mortality and liver-related mortality - Read-out of long-standing active disease • NASH is the driver of disease progression - Progression of liver disease towards cirrhosis and HCC - Extrahepatic consequences of disease Francque et al. J Hep 2016 6
Courtesy P. Bedosssa Schuppan et al. J Hep 2018 7
Biomarkers in NAFLD • Serum biomarkers - Single markers - Combination pannels & scores • clinical parameters • Imaging biomarkers • Fat/fibrosis/NASH/… • US, MRI… 8
• Steatosis - CAP MR spectroscopy MR PDFF … • Elasto - US - MRE - … • NASH - c. T 1 in multiparametric MR? 9
Verlinden, Francque et al. Hepatology 2016 10
Angulo et al. Gastroenterol. 2013 Vergniol et al. Gastroenterol. 2011 Naveau et al. Hepatol. 2009 11
Masuzaki et al. Hepatol. 2009 Kyu et al. Hepatol. 2011 12
Boyle M, Anstee Q et al. J Hep Reports 2019 13
Nucleic acids and combination pannels • DNA - DNA methylation • RNA - Non-coding RNA 14
non-coding RNA • Long non-coding RNAs (lnc. RNAs) - > 200 bases • Small non-coding RNAs (snc. RNAs) - ≤ 200 bases - Small nucleolar NRNAs (sno. RNAs) Small nuclear RNAs (sn. RNAs) Piwi-RNAs (pi. RNAs) Micro RNAs (mi. RNAs) • 21 -25 nucleotides • Regulate gene expression post-transcriptionnaly 15
Kinet et al. Frontiers in Genetics 2013 16
Thomou et al. Nature 2017 19
• Circulating exosomal mi. RNA is mainly derived from adipose tissue • Non-exosomal circulating mi. RNA less dominated by AT-derived mi. RNA • Differences between different AT depots • AT-derived exosomal but not free mi. RNA regulate liver FGF 21 expression and circulating FGF 21 levels • AT-derived exosomal but not free mi. RNA influence on IR and glucose tolerance • Mice & human (lipodystrophy) data Thomou et al. Nature 2017 20
> 1000 biopsy proven patients NIS 4 • Alpha 2 macroglobuline • Mir 34 a • Hb. A 1 C • YKL-40 (CHI 3 L 1) Intended use • Diagnosis of “at risk” NASH - • In NAFLD Activity NAS ≥ 4 and fibrosis stage ≥ 2 populations with clinical risk factors for NASH - obesity, T 2 DM, AHT, dyslipidaemia Harrison, Francque et al, ILC 2017, LBP-534 22
• mi. R-34 a - targets proteins involved in regulating • cell death • oxidative stress • metabolism - Increased expression + circulating levels NAFLD • mi. R-34 a ↓ Castro et al, J Hep 2013 Cheung et al, Hepatology 2008 Yamada et al, Clin Chim Acta 2013 - ↓ steatosis via PPAR ↑ and SIRT 1 ↑ Ding et al, Nature Sci Rep 2015 Francque et al, J Hep 2015 23
Correlation of NIS 4 changes and histological changes *** • There was a significant correlation between change in NIS and change in Activity Index. • Similar results were obtained in the whole population and in the sub-population of patients with NAS≥ 4 and F≥ 2 at inclusion. ** ** ** Harrison et al. ILC 2017. LBP-534 25
www. antwerpnafldguide. com 26
Francque et al. Acta Gastroenterol Belg 2018 27
Newsome et al. ILC 2018 28
Some take-home messages • Take into account the context of use - Surveillance / monitoring disease evolution • Individual biomarkers vs. pannels vs. combinations • Combination of serum and imaging biomarkers - Sequential or simultaneous • Progress mainly for amount of fat and fibrosis - Diagnosis of NASH and ”activity” remains difficult • Large international consortia - LITMUS, Liver Investigation: Testing Marker Utility in Steatohepatitis (IMI) NIMBLE, Non-Invasive Biomarkers of Metabolic Liver Disease (FNIH) • Clinical trials include biomarkers exploratory testing - FDA & EMA requirement 29
Biomarkers in NAFLD-HCC 30
• Limitations of current surveillance in NAFLD - US image quality in patients with overweight/obesity - HCC on background of non-cirrhotic NAFLD • • Surveillance and early diagnosis Prognosis Treatment response Predict future development – risk stratification 31
Blood biomarkers to diagnose HCC Aetiology-specific? 32
• mi. R-122 - Primarily expressed hepatocytes Regulates hepatic lipid metabolism Liver expression in NASH patients Serum levels in NASH patients • In Ago 2 -free complexes and EV - Related to obesity and IR Cermelli et al, PLo. S ONE 2011 Yamada et al, Clin Chim Acta 2015 Pirola et al, Gut 2015 Wang et al, Eur J Endocrinol 2015 • Entanglement with metabolic syndrome and CVD 33
• HBV - Combination mi. RNA panel • mi. R-122, mi. R-192, mi. R-21, mi. R-223, mi. R-26 a, mi. R-27 a and mi. R-801 • high diagnostic accuracy • differentiate » » HCC Healthy controls chronic non-cirrhotic hepatitis B Cirrhosis - Combination mi. R-122 and lat-7 b • Differentiate dysplastic nodules from HCC • HCV - Combination of mi. R-19 a, mi. R-195, mi. R-192 and mi. R-146 a • Early diagnosis of HCC 34
Non-coding RNA Koduru et al. Sci Rep 2018 35
Koduru et al. Sci Rep 2018 36
3 7 Biomarker validation Preclinical, exploratory studies Development of clinical diagnostic assays Retrospective cohort studies Prospective cohort studies Randomised, controlled trials Pepe MS. J Natl Cancer Inst 2001 37
NAFLD and HCC development prediction Liver disease Torres et al. , Clin Gastroenterol Hepatol 2012 38
Some take-home messages • Technological innovations offer new perspectives - Still a long way to go… • Caution with interpretation - Technical aspects: what is exactly measured? - Quality issues - Tissue analysis: small series • Predictive vs. diagnostic vs. prognostic vs. treatment response - Predictive -> tailored surveillance • Collaborative efforts needed - Clinical trials - Observational cohorts 39
June 12, 2018 – 1 st International NASH st 1 International NASH Day June 12, 2018 SAVE THE DATE ! www. the-nash-education-program. com 40 40
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