Introduction
Liver cancer is the sixth most common cancer and the third leading cause of cancer-related deaths worldwide. In 2020, over 900,000 new cases were diagnosed globally, with more than 800,000 deaths reported. Hepatocellular carcinoma (HCC) accounts for approximately 75-85% of primary liver cancers, posing a significant health burden. Despite advancements in sequencing techniques that allow for molecular characterization of tumors, challenges remain in the collection and analysis of tumor tissue. Liquid biopsy, particularly the analysis of circulating tumor DNA (ctDNA), offers a non-invasive approach for HCC diagnosis and management, potentially overcoming these limitations.
Liquid Biopsy
Interest in liquid biopsy has grown over the years, leading to the approval of blood-based tests for precision cancer care. In 2013, the US FDA approved the CellSearch™ CTC enumeration platform, which paved the way for the implementation of liquid biopsy in clinical trials. Subsequently, in 2016, the Cobas EGFR Mutation Test v2 was developed to detect EGFR-sensitizing mutations in non-small cell lung cancer (NSCLC) patients. With the rise of next-generation sequencing techniques, multigene panels were developed to detect target mutations in several cancer-related genes in advanced cancer. In 2019, the FDA approved liquid biopsy tests like Guardant360 CDx and CancerSEEK, which analyze cfDNA to guide treatment for patients with various cancers.
HCC presents considerable challenges due to pronounced tumor heterogeneity. Multinodular HCCs, diagnosed in approximately 41-75% of patients, limit curative treatment options and often lead to unfavorable prognosis. Liquid biopsy, particularly ctDNA analysis, has revolutionized oncology by enhancing early detection and improving monitoring and targeted treatments through the evaluation of genomic and molecular profiles of tumors. However, the field of liquid biopsy for HCC lacks extensive and comprehensive studies, contributing to challenges in attaining FDA approvals for HCC-related applications.
Circulating Tumor DNA in HCC
cfDNA, first reported in human peripheral blood in 1948, exists as double-stranded fragments of approximately 150 to 200 base pairs. In healthy individuals, cfDNA is present at low levels, but in the presence of tumors, inflammation, or tissue damage, its concentration can increase. ctDNA, a subset of cfDNA, refers specifically to fragmented DNA originating from tumor cells and accounts for a fluctuating proportion of cfDNA. Generally, cfDNA levels are elevated in patients with carcinoma compared to healthy individuals. Significant amounts of ctDNA are released into the circulatory system through tumor cell apoptosis or necrosis, and its quantity can reflect the tumor burden in patients with cancer.
ctDNA for Early HCC Detection
cfDNA and ctDNA hold substantial diagnostic potential in HCC, providing heightened sensitivity and improved clinical correlation. The methylation profile of cfDNA is particularly intriguing, given that epigenetic modifications significantly contribute to tumor initiation and progression. Several studies have reported that changes in methylation patterns of different genes can distinguish HCC from controls. For example, a study by Dong et al. in 2017 found that a combination of methylation of RASSF1A, BVES, and HOXA9 gene promoters in serum and AFP outperformed AFP alone in distinguishing between HCC and chronic hepatitis B patients without HCC.
cfDNA and ctDNA can also harbor key driver mutations in common genes in HCC, serving as potential biomarkers for early detection. In a study by Lin et al. in 2023, mutations in ARID1A, CTNNB1, and TP53 genes were detected in ctDNA, with these mutations being more prevalent in HCC patients compared to chronic hepatitis B patients. Combining the mutation profile of these genes with clinical factors improved the performance of the model for early-stage HCC detection.
Artificial Intelligence in ctDNA-based Liquid Biopsy Tests
Despite the potential of liquid biopsy, challenges such as low DNA yield and difficulty in deciphering mutation signals limit its clinical use. AI can play a crucial role in addressing these limitations by enhancing sensitivity, improving signal-to-noise ratios, and integrating multi-omics data. AI methodologies can seamlessly integrate diverse layers of molecular data, illuminating concealed associations among them. By combining AI algorithms with information derived from liquid biopsy, researchers can gain a deeper understanding of the underlying biology of liver cancer, identify novel biomarkers, and develop more effective treatment strategies.
Conclusion
ctDNA analysis holds solid potential in HCC care, presenting an effective solution to the limitations of tissue biopsy. AI has the transformative potential to revolutionize the field of liquid biopsy for liver cancer by addressing challenges like low DNA yield and difficulty in deciphering mutation signals. This convergence of AI and liquid biopsy expedites discoveries and advancements within liver cancer diagnostics and treatment strategies, ultimately improving patient outcomes and personalizing liver cancer management.
Authors: Inah Marie C. Aquino, Devis Pascut
References
[1] Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209-249.
[2] Singal AG, Lampertico P, Nahon P. Epidemiology and surveillance for hepatocellular carcinoma: new trends. J Hepatol. 2020;72(2):250-261.
[3] Adeniji N, Dhanasekaran R. Current and emerging tools for hepatocellular carcinoma surveillance. Hepatol Commun. 2021;5(12):1972-1986.
[4] Dhanasekaran R, Bandoh S, Roberts LR. Molecular pathogenesis of hepatocellular carcinoma and impact of therapeutic advances. F1000Research. 2016;5:879.
[5] Malone ER, Oliva M, Sabatini PJB, et al. Molecular profiling for precision cancer therapies. Genome Med. 2020;12(1):8.
[6] El-Deiry WS, Goldberg RM, Lenz H, et al. The current state of molecular testing in the treatment of patients with solid tumors, 2019. CA Cancer J Clin. 2019;69(4):305-343.
[7] Cheng ML, Pectasides E, Hanna GJ, et al. Circulating tumor DNA in advanced solid tumors: clinical relevance and future directions. CA Cancer J Clin. 2021;71(2):176-190.
[8] De Rubis G, Rajeev Krishnan S, Bebawy M. Liquid biopsies in cancer diagnosis, monitoring, and prognosis. Trends Pharmacol Sci. 2019;40(3):172-186.
[9] Corcoran RB, Chabner BA. Application of cell-free DNA analysis to cancer treatment. Obstet Gynecol Surv. 2018;379(18):1754-1765.
[10] Ye Q, Ling S, Zheng S, Xu X. Liquid biopsy in hepatocellular carcinoma: circulating tumor cells and circulating tumor DNA. Mol Cancer. 2019;18(1):114.
[11] Chan HT, Chin YM, Nakamura Y, Low SK. Clonal hematopoiesis in liquid biopsy: from biological noise to valuable clinical implications. Cancers. 2020;12(8):2277.
[12] Arechederra M, Avila MA, Berasain C. Liquid biopsy for cancer management: a revolutionary but still limited new tool for precision medicine. Adv Lab Med Av En Med Lab. 2020;1(3):20200009.
[13] de Wit S, van Dalum G, Terstappen LWMM. Detection of circulating tumor cells. Scientifica. 2014;2014:819362.
[14] Kwapisz D. The first liquid biopsy test approved. Is it a new era of mutation testing for non-small cell lung cancer? Ann Transl Med. 2017;5(3):46.
[15] Kalasekar SM, VanSant-Webb CH, Evason KJ. Intratumor heterogeneity in hepatocellular carcinoma: challenges and opportunities. Cancers. 2021;13(21):5524.
[16] Coto-Llerena M, Benjak A, Gallon J, et al. Circulating cell-free DNA captures the intratumor heterogeneity in multinodular hepatocellular carcinoma. JCO Precis Oncol. 2022;6:e2100335.
[17] Weng J, Atyah M, Zhou C, Ren N. Prospects and challenges of circulating tumor DNA in precision medicine of hepatocellular carcinoma. Clin Exp Med. 2020;20(3):329-337.
[18] Wu X, Li J, Gassa A, et al. Circulating tumor DNA as an emerging liquid biopsy biomarker for early diagnosis and therapeutic monitoring in hepatocellular carcinoma. Int J Biol Sci. 2020;16(9):1551-1562.
[19] Hu N, Fan XP, Fan YC, et al. Hypomethylated ubiquitin-conjugating Enzyme2 Q1 (UBE2Q1) gene promoter in the serum is a promising biomarker for hepatitis B virus-associated hepatocellular carcinoma. Tohoku J Exp Med. 2017;242(2):93-100.
[20] Dong X, Hou Q, Chen Y, Wang X. Diagnostic value of the methylation of multiple gene promoters in serum in hepatitis B virus-related hepatocellular carcinoma. Dis Markers. 2017;2017:2929381.
[21] Kisiel JB, Dukek BA, Kanipakam R, et al. Hepatocellular carcinoma detection by plasma methylated DNA: discovery, phase I pilot, and phase II clinical validation. Hepatology. 2019;69(3):1180-1192.
[22] An Y, Guan Y, Xu Y, et al. The diagnostic and prognostic usage of circulating tumor DNA in operable hepatocellular carcinoma. Am J Transl Res. 2019;11(10):6462-6474.
[23] Lin D, Luo R, Ye Z, et al. Genomic characterization of early-stage hepatocellular carcinoma patients with Hepatitis B using circulating tumor DNA. Clin Res Hepatol Gastroenterol. 2023;47(7):102161.
[24] Oversoe SK, Clement MS, Pedersen MH, et al. TERT promoter mutated circulating tumor DNA as a biomarker for prognosis in hepatocellular carcinoma. Scand J Gastroenterol. 2020;55(12):1433-1440.
[25] Zhao W, Qiu L, Liu H, et al. Circulating tumor DNA as a potential prognostic and predictive biomarker during interventional therapy of unresectable primary liver cancer. J Gastrointest Oncol. 2020;11(5):1065-1077.
[26] Ikeda S, Lim JS, Kurzrock R. Analysis of tissue and circulating tumor DNA by next generation sequencing of hepatocellular carcinoma: implications for targeted therapeutics. Mol Cancer Ther. 2018;17(5):1114-1122.
[27] Ikeda S, Tsigelny IF, Skjevik AA, et al. Next-generation sequencing of circulating tumor DNA reveals frequent alterations in advanced hepatocellular carcinoma. The Oncologist. 2018;23(5):586-593.
[28] Alunni-Fabbroni M, Rönsch K, Huber T, et al. Circulating DNA as prognostic biomarker in patients with advanced hepatocellular carcinoma: a translational exploratory study from the SORAMIC trial. J Transl Med. 2019;17(1):328.
[29] Ge Z, Helmijr JCA, Jansen MPHM, et al. Detection of oncogenic mutations in paired circulating tumor DNA and circulating tumor cells in patients with hepatocellular carcinoma. Transl Oncol. 2021;14(7):101073.
[30] Fu Y, Yang Z, Hu Z, et al. Preoperative serum ctDNA predicts early hepatocellular carcinoma recurrence and response to systemic therapies. Hepatol Int. 2022;16(4):868-878.
[31] Yang JC, Hu JJ, Li YX, et al. Clinical applications of liquid biopsy in hepatocellular carcinoma. Front Oncol. 2022;12:781820.
[32] Rothwell DG, Ayub M, Cook N, et al. Utility of ctDNA to support patient selection for early phase clinical trials: the TARGET study. Nat Med. 2019;25(5):738-743.
[33] Abbosh C, Birkbak NJ, Swanton C. Early stage NSCLC — challenges to implementing ctDNA-based screening and MRD detection. Nat Rev Clin Oncol. 2018;15(9):577-586.
[34] Liu L, Chen X, Petinrin OO, et al. Machine learning protocols in early cancer detection based on liquid biopsy: a survey. Life. 2021;11(7):638.
[35] Roth P, Wischhusen J, Happold C, et al. A specific miRNA signature in the peripheral blood of glioblastoma patients: Glioblastoma-associated miRNA profile in peripheral blood. J Neurochem. 2011;118(3):449-457.
[36] Liu S, Wu J, Xia Q, et al. Finding new cancer epigenetic and genetic biomarkers from cell-free DNA by combining SALP-seq and machine learning. Comput Struct Biotechnol J. 2020;18:1891-1903.
[37] Chen L, Abou-Alfa GK, Zheng B, et al. Genome-scale profiling of circulating cell-free DNA signatures for early detection of hepatocellular carcinoma in cirrhotic patients. Cell Res. 2021;31(5):589-592.
[38] Choi GH, Yun J, Choi J, et al. Development of machine learning-based clinical decision support system for hepatocellular carcinoma. Sci Rep. 2020;10(1):14855.
[39] Visser E, Genet SAAM, De Kock RPPA, et al. Liquid biopsy-based decision support algorithms for diagnosis and subtyping of lung cancer. Lung Cancer. 2023;178:28-36.
[40] Klein EA, Richards D, Cohn A, et al. Clinical validation of a targeted methylation-based multi-cancer early detection test using an independent validation set. Ann Oncol. 2021;32(9):1167-1177.
[41] Jamshidi A, Liu MC, Klein EA, et al. Evaluation of cell-free DNA approaches for multi-cancer early detection. Cancer Cell. 2022;40(12):1537-1549.e12.
[42] National Library of Medicine. The Circulating Cell-free Genome Atlas Study (CCGA). ClinicalTrials.gov; 2022. Published August 3, Accessed July 22, 2023 https://clinicaltrials.gov/study/NCT02889978.
[43] Fernandez-Uriarte A, Pons-Belda OD, Diamandis EP. Cancer screening companies are rapidly proliferating: are they ready for business? Cancer Epidemiol Biomarkers Prev. 2022;31(6):1146-1150.
[44] Pons-Belda OD, Fernandez-Uriarte A, Diamandis EP. Multi cancer early detection by using circulating tumor DNA—the galleri test. reply to klein et al. the promise of multicancer early detection. comment on “pons-Belda et al. can circulating tumor DNA support a successful screening test for early cancer detection? The grail paradigm. diagnostics 2021, 11, 2171.”. Diagnostics. 2022;12(5):1244.
[45] Oestmann PM, Wang CJ, Savic LJ, et al. Deep learning−assisted differentiation of pathologically proven atypical and typical hepatocellular carcinoma (HCC) versus non-HCC on contrast-enhanced MRI of the liver. Eur Radiol. 2021;31(7):4981-4990.