Machine-Learning-Based Clinical Biomarker Using Cell-Free DNA for Hepatocellular Carcinoma (HCC)
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Materials
2.2. Human Study Design and Population
2.3. Human Data Collection
2.4. PDA-SiO2 Beads’ Preparation for cfDNA Capture
2.5. cfDNA Capture
2.6. Real-Time Quantitative Polymerase Chain Reaction (qPCR)
2.7. Statistical Analysis
3. Results and Discussion
3.1. Capture of cfDNA and AFP DNA for Analysis Using a New Bead-Based System
3.2. Baseline Clinical Characteristics
3.3. cfDNA as a Potential Biomarker for the Diagnosis of HCC Tumor
3.4. cfDNA as a Potential Biomarker for Determining the Pathological Features of HCC Tumors
3.5. cfDNA as a Potential Biomarker for Predicting Survival Outcomes of Patients with HCC
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Llovet, J.M.; Kelley, R.K.; Villanueva, A.; Singal, A.G.; Pikarsky, E.; Roayaie, S.; Lencioni, R.; Koike, K.; Zucman-Rossi, J.; Finn, R.S. Hepatocellular carcinoma. Nat. Rev. Dis. Primers 2021, 7, 6. [Google Scholar] [CrossRef] [PubMed]
- Villanueva, A. Hepatocellular carcinoma. N. Engl. J. Med. 2019, 380, 1450–1462. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Li, L.; Wang, H. Heterogeneity of liver cancer and personalized therapy. Cancer Lett. 2016, 379, 191–197. [Google Scholar] [CrossRef] [PubMed]
- Akinyemiju, T.; Abera, S.; Ahmed, M.; Alam, N.; Alemayohu, M.A.; Allen, C.; Al-Raddadi, R.; Alvis-Guzman, N.; Amoako, Y.; Artaman, A.; et al. The Burden of Primary Liver Cancer and Underlying Etiologies from 1990 to 2015 at the Global, Regional, and National Level: Results from the Global Burden of Disease Study 2015. JAMA Oncol. 2017, 3, 1683–1691. [Google Scholar]
- Ho, D.W.; Lo, R.C.; Chan, L.K.; Ng, I.O. Molecular Pathogenesis of Hepatocellular Carcinoma. Liver Cancer 2016, 5, 290–302. [Google Scholar] [CrossRef]
- Mittal, S.; El-Serag, H.B. Epidemiology of hcc: Consider the population. J. Clin. Gastroenterol. 2013, 47, S2–S6. [Google Scholar] [CrossRef] [Green Version]
- Fujiwara, N.; Friedman, S.L.; Goossens, N.; Hoshida, Y. Risk factors and prevention of hepatocellular carcinoma in the era of precision medicine. J. Hepatol. 2018, 68, 526–549. [Google Scholar] [CrossRef] [Green Version]
- Herbst, D.A.; Reddy, K.R. Risk factors for hepatocellular carcinoma. Clin. Liver Dis. 2012, 1, 180–182. [Google Scholar] [CrossRef]
- Ye, Q.; Ling, S.; Zheng, S.; Xu, X. Liquid biopsy in hepatocellular carcinoma: Circulating tumor cells and circulating tumor DNA. Mol. Cancer 2019, 18, 114. [Google Scholar] [CrossRef]
- Hennedige, T.; Venkatesh, S.K. Imaging of hepatocellular carcinoma: Diagnosis, staging and treatment monitoring. Cancer Imaging 2012, 12, 530–547. [Google Scholar] [CrossRef] [Green Version]
- Forner, A.; Vilana, R.; Ayuso, C.; Bianchi, L.; Solé, M.; Ayuso, J.R.; Boix, L.; Sala, M.; Varela, M.; Llovet, J.M.; et al. Diagnosis of hepatic nodules 20 mm or smaller in cirrhosis: Prospective validation of the noninvasive diagnostic criteria for hepatocellular carcinoma. Hepatology 2008, 47, 97–104. [Google Scholar] [CrossRef] [PubMed]
- Mann, J.; Reeves, H.L.; Feldstein, A.E. Liquid biopsy for liver diseases. Gut 2018, 67, 2204–2212. [Google Scholar] [CrossRef] [PubMed]
- Marrero, J.A.; Kulik, L.M.; Sirlin, C.B.; Zhu, A.X.; Finn, R.S.; Abecassis, M.M.; Roberts, L.R.; Heimbach, J.K. Diagnosis, Staging, and Management of Hepatocellular Carcinoma: 2018 Practice Guidance by the American Association for the Study of Liver Diseases. Hepatology 2018, 68, 723–750. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Heimbach, J.K.; Kulik, L.M.; Finn, R.S.; Sirlin, C.B.; Abecassis, M.M.; Roberts, L.R.; Zhu, A.X.; Murad, M.H.; Marrero, J.A. AASLD guidelines for the treatment of hepatocellular carcinoma. Hepatology 2018, 67, 358–380. [Google Scholar] [CrossRef] [Green Version]
- Bialecki, E.S.; Di Bisceglie, A.M. Diagnosis of hepatocellular carcinoma. HPB 2005, 7, 26–34. [Google Scholar] [CrossRef] [Green Version]
- Manuc, D.; Preda, C.M.; Sandra, I.; Baicus, C.; Cerban, R.; Constantinescu, I.; Olteanu, A.O.; Ciora, C.A.; Manuc, T.; Chiriac, D.E.; et al. Signification of Serum Alpha-Fetoprotein Levels in Cases of Compensated Cirrhosis and Hepatitis C Virus without Hepatocellular Carcinoma. J. Med. Life 2020, 13, 68–74. [Google Scholar] [CrossRef]
- Chen, R.; Xu, X.; Tao, Y.; Qian, Z.; Yu, Y. Exosomes in hepatocellular carcinoma: A new horizon. Cell Commun. Signal. 2019, 17, 1. [Google Scholar] [CrossRef] [Green Version]
- Bu, J.; Nair, A.; Kubiatowicz, L.J.; Poellmann, M.J.; Jeong, W.-J.; Reyes-Martinez, M.; Armstrong, A.J.; George, D.J.; Wang, A.Z.; Zhang, T.; et al. Surface engineering for efficient capture of circulating tumor cells in renal cell carcinoma: From nanoscale analysis to clinical application. Biosens. Bioelectron. 2020, 162, 112250. [Google Scholar] [CrossRef]
- Banini, B.A.; Sanyal, A.J. The use of cell free DNA in the diagnosis of HCC. Hepatoma Res. 2019, 2019, 5. [Google Scholar] [CrossRef]
- Bu, J.; Cho, Y.-H.; Han, S.-W. Enhancement of isolation sensitivity for the viable heterogeneous circulating tumor cells swelled by hypo-osmotic pressure. RSC Adv. 2017, 7, 49684–49693. [Google Scholar] [CrossRef] [Green Version]
- Bu, J.; Kang, Y.-T.; Lee, Y.-S.; Kim, J.; Cho, Y.-H.; Moon, B.-I. Lab on a fabric: Mass producible and low-cost fabric filters for the high-throughput viable isolation of circulating tumor cells. Biosens. Bioelectron. 2017, 91, 747–755. [Google Scholar] [CrossRef] [PubMed]
- Bu, J.; Shim, J.-E.; Lee, T.H.; Cho, Y.-H. Multi-modal liquid biopsy platform for cancer screening: Screening both cancer-associated rare cells and cancer cell-derived vesicles on the fabric filters for a reliable liquid biopsy analysis. Nano Converg. 2019, 6, 39. [Google Scholar] [CrossRef] [PubMed]
- Poellmann, M.J.; Nair, A.; Bu, J.; Kim, J.K.H.; Kimple, R.J.; Hong, S. Immunoavidity-Based Capture of Tumor Exosomes Using Poly(amidoamine) Dendrimer Surfaces. Nano Lett. 2020, 20, 5686–5692. [Google Scholar] [CrossRef] [PubMed]
- Holmila, R.; Sklias, A.; Muller, D.; degli Esposti, D.; Guilloreau, P.; McKay, J.; Sangrajrang, S.; Srivatanakul, P.; Hainaut, P.; Merle, P.; et al. Targeted deep sequencing of plasma circulating cell-free DNA reveals Vimentin and Fibulin 1 as potential epigenetic biomarkers for hepatocellular carcinoma. PLoS ONE 2017, 12, e0174265. [Google Scholar] [CrossRef] [Green Version]
- Shim, J.-E.; Bu, J.; Lee, M.-K.; Cho, Y.-H.; Kim, T.-H.; Bu, J.-U.; Han, S.-W. Viable and high-throughput isolation of heterogeneous circulating tumor cells using tapered-slit filters. Sens. Actuators B Chem. 2020, 321, 128369. [Google Scholar] [CrossRef]
- Kim, Y.; Bu, J.; Cho, Y.-H.; Son, I.T.; Kang, S.-B. A viable circulating tumor cell isolation device with high retrieval efficiency using a reversibly deformable membrane barrier. J. Micromech. Microeng. 2016, 27, 025015. [Google Scholar] [CrossRef]
- Suh, D.H.; Kim, M.; Choi, J.Y.; Bu, J.; Kang, Y.-T.; Kwon, B.S.; Lee, B.; Kim, K.; No, J.H.; Kim, Y.-B.; et al. Circulating tumor cells in the differential diagnosis of adnexal masses. Oncotarget 2017, 8, 77195–77206. [Google Scholar] [CrossRef] [Green Version]
- Alborelli, I.; Generali, D.; Jermann, P.; Cappelletti, M.R.; Ferrero, G.; Scaggiante, B.; Bortul, M.; Zanconati, F.; Nicolet, S.; Haegele, J.; et al. Cell-free DNA analysis in healthy individuals by next-generation sequencing: A proof of concept and technical validation study. Cell Death Dis. 2019, 10, 534. [Google Scholar] [CrossRef]
- Bu, J.; Lee, T.H.; Jeong, W.-J.; Poellmann, M.J.; Mudd, K.; Eun, H.S.; Liu, E.W.; Hong, S.; Hyun, S.H. Enhanced detection of cell-free DNA (cfDNA) enables its use as a reliable biomarker for diagnosis and prognosis of gastric cancer. PLoS ONE 2020, 15, e0242145. [Google Scholar] [CrossRef]
- Li, Y.; Zheng, Y.; Wu, L.; Li, J.; Ji, J.; Yu, Q.; Dai, W.; Feng, J.; Wu, J.; Guo, C. Current status of ctdna in precision oncology for hepatocellular carcinoma. J. Exp. Clin. Cancer Res. 2021, 40, 140. [Google Scholar] [CrossRef]
- Bu, J.; Lee, T.H.; Poellmann, M.J.; Rawding, P.A.; Jeong, W.; Hong, R.S.; Hyun, S.H.; Eun, H.S.; Hong, S. Tri-modal liquid biopsy: Combinational analysis of circulating tumor cells, exosomes, and cell-free DNA using machine learning algorithm. Clin. Transl. Med. 2021, 11, e499. [Google Scholar] [CrossRef] [PubMed]
- Labgaa, I.; Villanueva, A.; Dormond, O.; Demartines, N.; Melloul, E. The Role of Liquid Biopsy in Hepatocellular Carcinoma Prognostication. Cancers 2021, 13, 659. [Google Scholar] [CrossRef] [PubMed]
- Yang, J.-C.; Hu, J.-J.; Li, Y.-X.; Luo, W.; Liu, J.-Z.; Ye, D.-W. Clinical Applications of Liquid Biopsy in Hepatocellular Carcinoma. Front. Oncol. 2022, 12, 781820. [Google Scholar] [CrossRef] [PubMed]
- Yousefi, B.; LaRiviere, M.J.; Cohen, E.A.; Buckingham, T.H.; Yee, S.S.; Black, T.A.; Chien, A.L.; Noël, P.; Hwang, W.-T.; Katz, S.I.; et al. Combining radiomic phenotypes of non-small cell lung cancer with liquid biopsy data may improve prediction of response to EGFR inhibitors. Sci. Rep. 2021, 11, 9984. [Google Scholar] [CrossRef]
- Meng, Y.; Liu, P.; Zhou, W.; Ding, J.; Liu, J. Bioorthogonal DNA Adsorption on Polydopamine Nanoparticles Mediated by Metal Coordination for Highly Robust Sensing in Serum and Living Cells. ACS Nano 2018, 12, 9070–9080. [Google Scholar] [CrossRef]
- Sherlock, S.; Dooley, J. Diseases of the Liver and Biliary System; John Wiley & Sons, Incorporated: Chichester, UK, 2002. [Google Scholar]
- Pratt, D.S.; Kaplan, M.M. Evaluation of Abnormal Liver-Enzyme Results in Asymptomatic Patients. N. Engl. J. Med. 2000, 342, 1266–1271. [Google Scholar] [CrossRef]
- Kim, T.-H.; Kim, S.Y.; Tang, A.; Lee, J.M. Comparison of international guidelines for noninvasive diagnosis of hepatocellular carcinoma: 2018 update. Clin. Mol. Hepatol. 2019, 25, 245–263. [Google Scholar] [CrossRef] [Green Version]
- Raoul, J.-L.; Forner, A.; Bolondi, L.; Cheung, T.T.; Kloeckner, R.; de Baere, T. Updated use of TACE for hepatocellular carcinoma treatment: How and when to use it based on clinical evidence. Cancer Treat. Rev. 2019, 72, 28–36. [Google Scholar] [CrossRef]
- Lang, Z.; Wu, Y.; Li, C.; Li, X.; Wang, X.; Qu, G. Multifocal and Multicentric Breast Carcinoma: A Significantly More Aggressive Tumor than Unifocal Breast Cancer. Anticancer Res. 2017, 37, 4593–4598. [Google Scholar] [CrossRef] [Green Version]
- von Felden, J.; Craig, A.J.; Garcia-Lezana, T.; Labgaa, I.; Haber, P.K.; D’Avola, D.; Asgharpour, A.; Dieterich, D.; Bonaccorso, A.; Torres-Martin, M.; et al. Mutations in circulating tumor DNA predict primary resistance to systemic therapies in advanced hepatocellular carcinoma. Oncogene 2021, 40, 140–151. [Google Scholar] [CrossRef]
- Wheler, J.J.; Janku, F.; Naing, A.; Li, Y.; Stephen, B.; Zinner, R.; Subbiah, V.; Fu, S.; Karp, D.; Falchook, G.S.; et al. TP53 Alterations Correlate with Response to VEGF/VEGFR Inhibitors: Implications for Targeted Therapeutics. Mol. Cancer Ther. 2016, 15, 2475–2485. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Oversoe, S.K.; Clement, M.S.; Pedersen, M.H.; Weber, B.; Aagaard, N.K.; Villadsen, G.E.; Grønbæk, H.; Hamilton-Dutoit, S.J.; Sorensen, B.S.; Kelsen, J. TERT promoter mutated circulating tumor DNA as a biomarker for prognosis in hepatocellular carcinoma. Scand. J. Gastroenterol. 2020, 55, 1433–1440. [Google Scholar] [CrossRef] [PubMed]
- Howell, J.; Atkinson, S.R.; Pinato, D.J.; Knapp, S.; Ward, C.; Minisini, R.; Burlone, M.E.; Leutner, M.; Pirisi, M.; Büttner, R.; et al. Identification of mutations in circulating cell-free tumour DNA as a biomarker in hepatocellular carcinoma. Eur. J. Cancer 2019, 116, 56–66. [Google Scholar] [CrossRef] [PubMed]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Lee, T.; Rawding, P.A.; Bu, J.; Hyun, S.; Rou, W.; Jeon, H.; Kim, S.; Lee, B.; Kubiatowicz, L.J.; Kim, D.; et al. Machine-Learning-Based Clinical Biomarker Using Cell-Free DNA for Hepatocellular Carcinoma (HCC). Cancers 2022, 14, 2061. https://doi.org/10.3390/cancers14092061
Lee T, Rawding PA, Bu J, Hyun S, Rou W, Jeon H, Kim S, Lee B, Kubiatowicz LJ, Kim D, et al. Machine-Learning-Based Clinical Biomarker Using Cell-Free DNA for Hepatocellular Carcinoma (HCC). Cancers. 2022; 14(9):2061. https://doi.org/10.3390/cancers14092061
Chicago/Turabian StyleLee, Taehee, Piper A. Rawding, Jiyoon Bu, Sunghee Hyun, Woosun Rou, Hongjae Jeon, Seokhyun Kim, Byungseok Lee, Luke J. Kubiatowicz, Dawon Kim, and et al. 2022. "Machine-Learning-Based Clinical Biomarker Using Cell-Free DNA for Hepatocellular Carcinoma (HCC)" Cancers 14, no. 9: 2061. https://doi.org/10.3390/cancers14092061