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Background Late detection of hepatocellular carcinoma (HCC) results in an overall 5-year survival rate of less than 16%. Liquid biopsy (LB) assays based on detecting circulating tumor DNA (ctDNA) might provide an opportunity to detect HCC early noninvasively. Increasing evidence indicates that ctDNA detection using mutation-based assays is significantly challenged by the abundance of white blood cell-derived mutations, non-tumor tissue-derived somatic mutations in plasma, and the mutational tumor heterogeneity. Methods Here, we employed concurrent analysis of cancer-related mutations, and their fragment length profiles to differentiate mutations from different sources. To distinguish persons with HCC (PwHCC) from healthy participants, we built a classification model using three fragmentomic features of ctDNA through deep sequencing of thirteen genes associated with HCC. Results Our model achieved an area under the curve (AUC) of 0.88, a sensitivity of 89%, and a specificity of 82% in the discovery cohort consisting of 55 PwHCC and 55 healthy participants. In an independent validation cohort of 54 PwHCC and 53 healthy participants, the established model achieved comparable classification performance with an AUC of 0.86 and yielded a sensitivity and specificity of 81%. Conclusions Our study provides a rationale for subsequent clinical evaluation of our assay performance in a large-scale prospective study.

BackgroundHereditary cancer syndromes (HCS) are responsible for 5-10% of cancer cases. Genetic testing to identify pathogenic variants associated with cancer predisposition has not been routinely available in Vietnam. Consequently, the prevalence and genetic landscape of HCS remain unknown.Methods1165 Vietnamese individuals enrolled in genetic testing at our laboratory in 2020. We performed analysis of germline mutations in 17 high- and moderate- penetrance genes associated with HCS by next generation sequencing.ResultsA total of 41 pathogenic variants in 11 genes were detected in 3.2% individuals. The carrier frequency was 4.2% in people with family or personal history of cancer and 2.6% in those without history. The percentage of mutation carriers for hereditary colorectal cancer syndromes was 1.3% and for hereditary breast and ovarian cancer syndrome was 1.6%. BRCA1 and BRCA2 mutations were the most prevalent with the positive rate of 1.3% in the general cohort and 5.1% in breast or ovarian cancer patients. Most of BRCA1 mutations located at the BRCA C-terminus domains and the top recurrent mutation was NM_007294.3:c.5251C>T (p.Arg1751Ter). One novel variant NM_000038.6(APC):c.6665C>A (p.Pro2222His) was found in a breast cancer patient with a strong family history of cancer. A case study of hereditary cancer syndrome was illustrated to highlight the importance of genetic testing.ConclusionThis is the first largest analysis of carrier frequency and mutation spectrum of HCS in Vietnam. The findings demonstrate the clinical significance of multigene panel testing to identify carriers and their at-risk relatives for better cancer surveillance and management strategies.

Aim: This study exploited hepatocellular carcinoma (HCC)-specific circulating DNA methylation profiles to improve the accuracy of a current screening assay for HCC patients in high-risk populations. Methods: Differentially methylated regions in cell-free DNA between 58 nonmetastatic HCC and 121 high-risk patients with liver cirrhosis or chronic hepatitis were identified and used to train machine learning classifiers. Results: The model could distinguish HCC from high-risk non-HCC patients in a validation cohort, with an area under the curve of 0.84. Combining these markers with the three serum biomarkers (AFP, lectin-reactive AFP, des-γ-carboxy prothrombin) in a commercial test, μTASWako®, achieved an area under the curve of 0.87 and sensitivity of 68.8% at 95.8% specificity. Conclusion: HCC-specific circulating DNA methylation markers may be added to the available assay to improve the early detection of HCC.

IntroductionBreast cancer causes the most cancer-related death in women and is the costliest cancer in the US regarding medical service and prescription drug expenses. Breast cancer screening is recommended by health authorities in the US, but current screening efforts are often compromised by high false positive rates. Liquid biopsy based on circulating tumor DNA (ctDNA) has emerged as a potential approach to screen for cancer. However, the detection of breast cancer, particularly in early stages, is challenging due to the low amount of ctDNA and heterogeneity of molecular subtypes.MethodsHere, we employed a multimodal approach, namely Screen for the Presence of Tumor by DNA Methylation and Size (SPOT-MAS), to simultaneously analyze multiple signatures of cell free DNA (cfDNA) in plasma samples of 239 nonmetastatic breast cancer patients and 278 healthy subjects.ResultsWe identified distinct profiles of genome-wide methylation changes (GWM), copy number alterations (CNA), and 4-nucleotide oligomer (4-mer) end motifs (EM) in cfDNA of breast cancer patients. We further used all three signatures to construct a multi-featured machine learning model and showed that the combination model outperformed base models built from individual features, achieving an AUC of 0.91 (95% CI: 0.87-0.95), a sensitivity of 65% at 96% specificity.DiscussionOur findings showed that a multimodal liquid biopsy assay based on analysis of cfDNA methylation, CNA and EM could enhance the accuracy for the detection of early- stage breast cancer.