Hepatocellular Carcinoma Detection by Plasma Methylated DNA: Discovery, Phase I Pilot, and Phase II Clinical Validation

Early detection improves hepatocellular carcinoma (HCC) outcomes, but better noninvasive surveillance tools are needed. We aimed to identify and validate methylated DNA markers (MDMs) for HCC detection. Reduced representation bisulfite sequencing was performed on DNA extracted from 18 HCC and 35 control tissues. Candidate MDMs were confirmed by quantitative methylation‐specific PCR in DNA from independent tissues (74 HCC, 29 controls). A phase I plasma pilot incorporated quantitative allele‐specific real‐time target and signal amplification assays on independent plasma‐extracted DNA from 21 HCC cases and 30 controls with cirrhosis. A phase II plasma study was then performed in 95 HCC cases, 51 controls with cirrhosis, and 98 healthy controls using target enrichment long‐probe quantitative amplified signal (TELQAS) assays. Recursive partitioning identified best MDM combinations. The entire MDM panel was statistically cross‐validated by randomly splitting the data 2:1 for training and testing. Random forest (rForest) regression models performed on the training set predicted disease status in the testing set; median areas under the receiver operating characteristics curve (AUCs; and 95% confidence interval [CI]) were reported after 500 iterations. In phase II, a six‐marker MDM panel (homeobox A1 [HOXA1], empty spiracles homeobox 1 [EMX1], AK055957, endothelin‐converting enzyme 1 [ECE1], phosphofructokinase [PFKP], and C‐type lectin domain containing 11A [CLEC11A]) normalized by beta‐1,3‐galactosyltransferase 6 (B3GALT6) level yielded a best‐fit AUC of 0.96 (95% CI, 0.93‐0.99) with HCC sensitivity of 95% (88%‐98%) at specificity of 92% (86%‐96%). The panel detected 3 of 4 (75%) stage 0, 39 of 42 (93%) stage A, 13 of 14 (93%) stage B, 28 of 28 (100%) stage C, and 7 of 7 (100%) stage D HCCs. The AUC value for alpha‐fetoprotein (AFP) was 0.80 (0.74‐0.87) compared to 0.94 (0.9‐0.97) for the cross‐validated MDM panel (P < 0.0001). Conclusion: MDMs identified in this study proved to accurately detect HCC by plasma testing. Further optimization and clinical testing of this promising approach are indicated.

[1]  Detection of Cholangiocarcinoma by Assay of Methylated DNA Markers in Plasma , 2017 .

[2]  J. Marrero,et al.  Meta‐analysis: surveillance with ultrasound for early‐stage hepatocellular carcinoma in patients with cirrhosis , 2009, Alimentary pharmacology & therapeutics.

[3]  M. Choti,et al.  Detection of Circulating Tumor DNA in Early- and Late-Stage Human Malignancies , 2014, Science Translational Medicine.

[4]  Roderick J. A. Little,et al.  Statistical Analysis with Missing Data: Little/Statistical Analysis with Missing Data , 2002 .

[5]  D. Ahlquist,et al.  Stool DNA Testing for the Detection of Pancreatic Cancer: Identification and Assessment of Methylation Marker Candidates , 2011 .

[6]  Amit G. Singal,et al.  Early Detection, Curative Treatment, and Survival Rates for Hepatocellular Carcinoma Surveillance in Patients with Cirrhosis: A Meta-analysis , 2014, PLoS medicine.

[7]  Ludmila V. Danilova,et al.  Detection and localization of surgically resectable cancers with a multi-analyte blood test , 2018, Science.

[8]  E. Rose,et al.  Alpha-fetoprotein levels in normal adults. , 1992, The American journal of the medical sciences.

[9]  W W Lautt,et al.  Conceptual review of the hepatic vascular bed , 1987, Hepatology.

[10]  M. Raimondo,et al.  New DNA Methylation Markers for Pancreatic Cancer: Discovery, Tissue Validation, and Pilot Testing in Pancreatic Juice , 2015, Clinical Cancer Research.

[11]  Rochelle L. Tiedemann,et al.  Epigenetic signatures of alcohol abuse and hepatitis infection during human hepatocarcinogenesis , 2014, Oncotarget.

[12]  M. Manns,et al.  Role of the GALAD and BALAD-2 Serologic Models in Diagnosis of Hepatocellular Carcinoma and Prediction of Survival in Patients. , 2016, Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association.

[13]  Mathieu Laversanne,et al.  International trends in liver cancer incidence, overall and by histologic subtype, 1978–2007 , 2016, International journal of cancer.

[14]  N. Dubrawsky.  Cancer statistics , 1989, CA: a cancer journal for clinicians.

[15]  J. Marrero,et al.  Alpha-fetoprotein, des-gamma carboxyprothrombin, and lectin-bound alpha-fetoprotein in early hepatocellular carcinoma. , 2009, Gastroenterology.

[16]  W. Huber,et al.  Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 , 2014, Genome Biology.

[17]  A. Villanueva,et al.  Liquid biopsy in liver cancer. , 2015, Discovery medicine.

[18]  Saurabh Baheti,et al.  SAAP-RRBS: streamlined analysis and annotation pipeline for reduced representation bisulfite sequencing , 2012, Bioinform..

[19]  H. Allawi,et al.  Clinical performance of an automated stool DNA assay for detection of colorectal neoplasia. , 2013, Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association.

[20]  J. Bruix,et al.  Prognosis of Hepatocellular Carcinoma: The BCLC Staging Classification , 1999, Seminars in liver disease.

[21]  Qi Zhao,et al.  Circulating tumour DNA methylation markers for diagnosis and prognosis of hepatocellular carcinoma. , 2017, Nature materials.

[22]  A. Jemal,et al.  Cancer statistics, 2016 , 2016, CA: a cancer journal for clinicians.

[23]  B. Graubard,et al.  Population attributable fractions of risk factors for hepatocellular carcinoma in the United States , 2016, Cancer.

[24]  Peter J. Richardson,et al.  Determinants of serum alpha-fetoprotein levels in hepatitis C-infected patients. , 2012, Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association.

[25]  Diane M. Griffiths,et al.  THE REGENTS OF THE UNIVERSITY OF CALIFORNIA , 2007 .

[26]  Jia Fan,et al.  Detecting Circulating Tumor DNA in Hepatocellular Carcinoma Patients Using Droplet Digital PCR Is Feasible and Reflects Intratumoral Heterogeneity , 2016, Journal of Cancer.

[27]  William M. Lee,et al.  Utilization of Hepatocellular Carcinoma Surveillance Among American Patients: A Systematic Review , 2012, Journal of General Internal Medicine.

[28]  Zhao-You Tang,et al.  Randomized controlled trial of screening for hepatocellular carcinoma , 2004, Journal of Cancer Research and Clinical Oncology.

[29]  D. Ransohoff,et al.  Multitarget stool DNA testing for colorectal-cancer screening. , 2014, The New England journal of medicine.

[30]  E. Ma,et al.  Plasma DNA tissue mapping by genome-wide methylation sequencing for noninvasive prenatal, cancer, and transplantation assessments , 2015, Proceedings of the National Academy of Sciences.

[31]  P. Rosenberg,et al.  Future of Hepatocellular Carcinoma Incidence in the United States Forecast Through 2030. , 2016, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[32]  H. Allawi,et al.  Quantification of methylated markers with a multiplex methylation-specific technology. , 2012, Clinical chemistry.

[33]  A. Jemal,et al.  Global cancer statistics, 2012 , 2015, CA: a cancer journal for clinicians.

[34]  M. Abecassis,et al.  AASLD guidelines for the treatment of hepatocellular carcinoma , 2018, Hepatology.

[35]  A. Jemal,et al.  Cancer statistics, 2017 , 2017, CA: a cancer journal for clinicians.

[36]  Carlos Caldas,et al.  Analysis of circulating tumor DNA to monitor metastatic breast cancer. , 2013, The New England journal of medicine.

[37]  A. Jemal,et al.  Global cancer statistics , 2011, CA: a cancer journal for clinicians.

[38]  Russell V. Lenth,et al.  Statistical Analysis With Missing Data (2nd ed.) (Book) , 2004 .

[39]  D. Woodfield.  Hepatocellular carcinoma. , 1986, The New Zealand medical journal.

[40]  D. Ahlquist,et al.  Stool DNA testing for the detection of pancreatic cancer , 2012, Cancer.

[41]  E. DeLong,et al.  Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. , 1988, Biometrics.