Abstract B073: Leveraging micronuclei DNA from erythrocytes for early detection of hepatocellular carcinoma
Authors: Lin Hui , Sun Haobo , Yao Xingyun , Fan Xiaoxiao , Meng Fei , Liang Honghao , Gao Xiaofei 
Published: November 2024

Background: Hepatocellular carcinoma (HCC) is the most common form of liver cancer and accounts for ∼90% of cases globally. Detection of early-stage HCC is vital as it allows for potentially curative treatment, yet remains a significant challenge. Micronuclei (MN) are a hallmark of genomic instability. An increased frequency of MN is commonly observed in tumor cells as well as other somatic cells, including erythrocytes, in cancer patients. Here, we have established a technique (WO2021/228246 A1), for the isolation and analysis of micronuclei DNA (MN-DNA) in erythrocytes from peripheral blood. Significant changes in read densities at specific genomic locations within MN-DNA were identified in patients, termed as tumor- associated MN-DNA (taMN-DNA) features. This study evaluates the potential of these taMN- DNA features for early-stage HCC detection across human and murine model. Methods: To explore the potential of MN-DNA in cancer detection, we first collected 1-2 mL of whole blood from HDs (N = 53) and HCC patients (N = 53). MN-DNA was isolated and purified from erythrocytes, followed by whole-genome sequencing. Participants were randomly divided into training, test cohorts in an 8:2 ratio. We applied machine learning algorithms to leverage these features for cancer detection in the human model. Additionally, to investigate the formation of taMN-DNA features, we employed a well-established mouse model that mimics HCC development. Mice were injected with the genotoxic agent diethylnitrosamine (DEN) 2 weeks after birth, and developed malignant macroscopic liver nodules at approximately 40 weeks of age. Results: In the human cohort, we enrolled 106 participants, with more than half of the HCC cases were diagnosed at early-stage (stage 0-II). The cancer detection model utilizing taMN- DNA features achieved an overall accuracy of 86.3%, with a sensitivity of 81.8% and specificity of 90.9%. For early-stage, the model demonstrated sensitivities of 54.5% at a specificity of 90.9%. In the DEN-induced HCC mouse model, unsupervised hierarchical clustering based on these selected taMN-DNA features clearly separated WT and tumor mice into two distinct groups. Notably, mice that were not tumorigenic at 36 weeks post-treatment in the DEN-treated group fell into the WT group when classified by the same taMN-DNA features, indicating that the formation of taMN-DNA signatures is associated with the presence of tumors specifically. Conclusions: This pilot study highlights the potential of MN-DNA as a promising tool for early HCC detection. Leveraging these taMN-DNA features can accurately distinguish early-stage HCC patients from HDs with high sensitivity. In both human and murine models, there is a significant relationship between these signatures and tumor presence, suggesting that taMN- DNA features might reflect the diseased state across mammalian species. Research sponsor: Timing Biotech.

Citation Format: Hui Lin, Haobo Sun, Xingyun Yao, Xiaoxiao Fan, Fei Meng, Honghao Liang, Xiaofei Gao. Leveraging micronuclei DNA from erythrocytes for early detection of hepatocellular carcinoma [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B073.