Hepatocellular carcinoma (HCC) is the sixth most common cancer and the third most common cause of cancer mortality worldwide. Infection with hepatitis B virus (HBV) and/or hepatitis C virus (HCV) is the most predominant cause of HCC. Concerns arise for the presence of additional risk factors, as there is still a large proportion of patients without HBV or HCV infection. Previous studies have reported that higher intake of fruits and vegetables and reduced consumption of red/processed meat might play a protective role in HCC etiology, though the nationwide proof is limited. Hence, we studied multiple risk factors including food habit, lifestyle, and clinical implications of HCC patients in Bangladeshi. Demographic, clinical, and biochemical data, as well as data on food habits, were collected in this study. Our results indicated that a high intake of rice (AOR 4.28, 95% CI 1.48 to 14.07, p = 0.011), low intake of fruits (AOR = 4.41 95% CI 1.48-15.46; p = 0.012), leafy vegetables (AOR = 2.80, 95% CI 1.32-6.08; p = 0.008), and fish (AOR = 4.64 95% CI 2.18-10.23; p<0.001) increased the HCC risk. Moreover, a high intake of eggs (AOR = 2.07 95% CI 0.98-4.43; p = 0.058) also showed an increased risk. Roti, non-leafy vegetables, red meat, and tea were found to have no association with HCC risk. This study revealed that food habit patterns and lifestyle may have a profound effect on HCC development among Bangladeshi patients in addition to well established risk factors.

High-throughput tests for early cancer detection can revolutionize public health and reduce cancer morbidity and mortality. Here we show a DNA methylation signature for hepatocellular carcinoma (HCC) detection in liquid biopsies, distinct from normal tissues and blood profiles. We developed a classifier using four CpG sites, validated in TCGA HCC data. A single F12 gene CpG site effectively differentiates HCC samples from other blood samples, normal tissues, and non-HCC tumors in TCGA and GEO data repositories. The markers were validated in a separate plasma sample dataset from HCC patients and controls. We designed a high-throughput assay using next-generation sequencing and multiplexing techniques, analyzing plasma samples from 554 clinical study participants, including HCC patients, non-HCC cancers, chronic hepatitis B, and healthy controls. HCC detection sensitivity was 84.5% at 95% specificity and 0.94 AUC. Implementing this assay for high-risk individuals could significantly decrease HCC morbidity and mortality.

Robust cost effective and high-throughput tests for early detection of cancer in otherwise healthy people could potentially revolutionize public-health and the heavy personal and public burden of the morbidity and mortality from cancer. Several studies have delineated tumor specific DNA methylation profiles that could serve as biomarkers for early detection of Hepatocellular Carcinoma (HCC) as well as other cancers in liquid biopsies. Several published DNA methylation markers fail to distinguish HCC DNA from DNA from other tissues and other cancers that are potentially present in plasma. We describe a set of DNA methylation signatures in HCC that are “categorically” distinct from normal tissues and blood DNA methylation profiles. We develop a classifier combined of 4 CG sites that is sufficient to detect HCC in TCGA HCC data set at high accuracy. A single CG site at the F12 gene is sufficient to differentiate HCC samples from thousands of other blood samples, normal tissues and 31 tumors in the TCGA and Gene Expression Omnibus (GEO) data repository (n = 11,704). A “next generation sequencing”-targeted-multiplexed high-throughput assay was developed, which was used to examine in a clinical study plasma samples from HCC, chronic hepatitis B (CHB) patients and healthy controls (n = 398). The sensitivity for HCC detection was 84.5% at a specificity of 95% and AUC of 0.94. Applying this assay for routine follow up of people who are at high risk for developing HCC could have a significant impact on reducing the morbidity and mortality from HCC.

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