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 liver cancer-related deaths reported. Hepatocellular carcinoma (HCC) accounts for about 75%-85% of primary liver cancers, posing a significant health burden worldwide. 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. This article explores the potential of liquid biopsy in HCC care and the role of artificial intelligence (AI) in overcoming its 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 Food and Drug Administration (FDA) approved the CellSearchTM CTC enumeration platform, which enumerates epithelial circulating tumor cells (CTCs). This groundbreaking approval paved the way for the implementation of liquid biopsy in clinical trials, such as the METABREAST trial, where CTC counts were used as a criterion for selecting first-line treatment in metastatic breast cancer.
Subsequently, in 2016, the first ctDNA-based companion diagnostic test, known as the Cobas EGFR Mutation Test v2, was developed to detect epidermal growth factor receptor (EGFR)-sensitizing mutations in non-small cell lung cancer (NSCLC) patients. This test played a crucial role in guiding the use of EGFR-tyrosine kinase inhibitors as a targeted therapy. 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, FDA approved some liquid biopsy tests, including the Guardant360 CDx, which analyzes a 73-gene panel of cell-free DNA (cfDNA) to guide treatment for patients with NSCLC.
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 length. In healthy individuals, cfDNA derived from apoptotic myeloid and lymphoid cells is present at low levels. However, in the presence of tumors, inflammation, tissue damage, or after surgery, the concentration of cfDNA can increase in the bloodstream. 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 have been identified as significant contributors 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 Ras association domain family 1A (RASSF1A), blood vessel epicardial substance (BVES), and homeobox (HOXA9) gene promoters in serum and AFP outperformed AFP alone in distinguishing between HCC and chronic hepatitis B patients without HCC.
ctDNA to Monitor HCC Progression and Treatment Response
The analysis of ctDNA finds multiple applications in the clinical management of HCC patients. Oversoe et al. in 2020 detected the presence of telomerase reverse transcriptase (TERT) C228T mutation in the ctDNA derived from 44% of the HCC patients enrolled in the study, while it was absent in patients with cirrhosis. After adjustment for potential confounders, the presence of TERT mutation in plasma was associated with a higher mortality rate. Additionally, the researchers established a positive correlation between the presence of TERT mutation in plasma and advanced TNM stage or vascular invasion.
ctDNA has been used as a reliable biomarker to monitor tumor progression and assess treatment efficacy. Due to the invasiveness of tissue biopsy, this procedure is highly discouraged to monitor tumor progression, thus liquid biopsy provides an ideal option for real-time monitoring of the disease. A prospective study conducted by Zhao et al. in 2020 enrolled 42 patients with unresectable liver cancer, 39 of which had HCC. The primary objective of the study was to investigate the relationship between ctDNA abundance and tumor characteristics, as well as the significance of TP53 mutations on response to interventional therapy. The results revealed a strong correlation between ctDNA abundance and tumor size, highlighting the potential of ctDNA as a marker for quantifying tumor burden.
Artificial Intelligence Can Improve ctDNA-Based Liquid Biopsy Tests
Despite the potential of liquid biopsy, particularly ctDNA, some limitations exist that limit its clinical use. AI can play a crucial role in addressing these limitations during the study design, during the analytical phase, and in the interpretation of the results through AI-powered clinical decision support systems (CDSS). CDSS can aid in early detection, treatment selection, and monitoring of the response to treatment, leading to personalized management of the patient.
Liquid Biopsy and AI Boosts the Development of Clinical Decision Support Systems
AI-based CDSS have the potential to transform the field of liquid biopsy for liver cancer. By analyzing large-scale patient data, including ctDNA profiles, treatment responses, and clinical outcomes, AI algorithms can generate predictive models and treatment recommendations. CDSS powered by AI can aid clinicians in making informed decisions, selecting appropriate therapies, and monitoring treatment responses. Several groups have explored this potential and have reported promising results.
Conclusion
In conclusion, ctDNA analysis holds solid potential in HCC care. The use of ctDNA as a non-invasive alternative presents an effective solution to the limitations of tissue biopsy, including invasiveness, tumor heterogeneity, and limited tumor content. The diagnostic potential of ctDNA becomes evident in its capability to detect early-stage HCC through the analysis of methylation patterns and specific gene mutations. Additionally, ctDNA has proven to be a valuable prognostic indicator, correlating with tumor burden, disease progression, and treatment response.
AI holds the transformative potential to revolutionize the field of liquid biopsy for liver cancer. By addressing challenges like low DNA yield and the difficulty in deciphering mutation signals, AI algorithms can enhance sensitivity, improve signal-to-noise ratios, integrate multi-omics data, and develop clinical decision support systems. This convergence of AI and liquid biopsy expedites discoveries and advancements within liver cancer diagnostics and treatment strategies.
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