VINIF.2021.DA00212 – Discovery of novel biomarkers to monitor the progression of hepatitis B virus related chronic liver diseases and early diagnosis of hepatocellular carcinoma

Principle Investigator
Dr. Nghiem Xuan Hoan
Host Organization
108 Military Central Hospital

The overall goal of the project is to use mass spectrometry, nuclear magnetic resonance (NMR) analysis and large-scale non-coding gene expression analysis to search for new biomarkers characterize the transition steps of patients with chronic hepatitis or cirrhosis to liver cancer, thereby providing an appropriate mathematical model to support early diagnosis and screening of liver cancer in subjects with hepatitis B virus. Therefore, the specific goals of the project are:

  • Establishment of a panel of biomarkers (including metabolism-related molecules and non-coding miRNAs) with high sensitivity to distinguish different clinical forms of chronic liver diseases related to HBV
  • Optimizing the mathematical model based on newly discovered biomarkers for the purpose of screening and early detection of primary liver cancer in patients with chronic HBV infection.

Main tasks of the project

The research project will be divided into 2 phases as follows

  • Phase 1 (discovery phase): At this stage, the technical process of NMR spectroscopy analysis is used to analyze metabolic markers. A high-throughput quantitative RT-PCR method will be used to detect changes in metabolic profiles and abnormal miRNA expression levels in the tested patients. The expected outcome of the discovery phase will be a novel but optimized biomarker panel consisting of metabolic molecules and miRNAs whose diagnostic performance will be confirmed in a later validation phase.
  • Phase 2 (Validation and Standardization Phase): All testing and analytical parameters from the discovery phase will be applied to the validation phase and standardization of the accuracy capabilities of the diagnostic method based on biomarkers selected from the discovery phase. We plan to collect and analyze 600 patients (300 HCC, 100 LC, 200 CHB) using HPLC (and/or LCMS/MS) and high-throughput qRT-PCR methods. The raw data generated will be further analyzed using an analytical model (sPLS-DA); appropriate machine learning algorithms (random forests, linear support vector machines, PLS-DA and logistic regression) will be applied to build predictive models to monitor the progression of associated liver disease from HBV to HCC and helps support early diagnosis of liver cancer.

Project impact

  • Diagnosis and treatment of cancer in general, including liver cancer, requires multi-modality in which searching for genetic lesions from peripheral blood is only a very small scope and certainly cannot completely solve the problem. Therefore the diagnosis of liver cancer, especially the early diagnosis of liver cancer, requires a combination of many different methods: clinical, imaging, biomarkers, molecular biology… In this project, we will establish prediction models based on metabolic markers and/or expression of miRNAs in liquid biopsy samples to help distinguish different disease stages in people with chronic HBV infection (chronic hepatitis, cirrhosis, liver cancer).
  • Implications in practice: new and meaningful biomarkers to distinguish different disease stages in people with chronic HBV infection and to support early diagnosis of hepatocellular carcinoma in patients with chronic HBV infection is currently an urgent medical need. In this project, we established a panel of metabolic biomarkers and/or expression of miRNAs in liquid biopsy samples that distinguish different disease stages in chronic HBV-infected individuals with high sensitivity for disease progression and more importantly, new biomarker-based models can accurately/accurately detect early liver cancer. Combining research methods on changes in metabolic markers with expression levels of miRNAs provides a potential new tool for diagnosis, prognosis, monitoring and treatment decisions in clinical practice.
Principle Investigator
Dr. Nghiem Xuan Hoan
Host Organization
108 Military Central Hospital

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Expect Progress
15/11/2021
15/11/2022
Phase 1

Clinical database – subclinical data of approximately 450 patient samples with different stages of disease (~170 patients with chronic hepatitis B, ~80 patients with cirrhosis, and ~200 patients with liver cancer).
– A list of approximately 200 miRNAs related to the pathological progression of liver diseases, particularly liver cancer.
– Data on specific primers and probes corresponding to the above miRNA library.
– Databases on miRNA expression levels and associated profiling.
– Reports on the identification of miRNAs that are significant or related to disease progression – prognosis.
– Quantification procedures for miRNAs based on qRT-PCR technique.
– Databases following the analysis of metabolic profiles of patients with chronic hepatitis B, cirrhosis, and liver cancer using nuclear magnetic resonance (NMR).

15/11/2023
Phase 2

– Clinical and subclinical database of approximately 200 patient samples with different stages of disease (50 chronic hepatitis B, 50 cirrhosis, and 100 liver cancer) necessary for data analysis for the project.
– Report on the expression levels of potentially significant miRNAs related to disease progression – prognosis of chronic liver disease, especially distinguishing different disease stages.
– Report on high sensitivity and accuracy methods for quantifying miRNA in serum.
– Report on the establishment of condensed miRNA panels valuable for disease stage diagnosis and prognosis with high sensitivity and specificity – potentially combinable with other biomarkers available in clinical practice.
– Database on metabolic markers of patients with chronic hepatitis B, cirrhosis, and liver cancer using nuclear magnetic resonance (NMR).
– Analytical database on miRNA in the research groups.
– First ISI international article – Q1 with an impact factor (IF) ≥ 4 submitted for publication.
– Metabolic profiles of patients with chronic hepatitis B, cirrhosis, and liver cancer using nuclear magnetic resonance (NMR).
– Procedures for quantifying metabolites based on NMR technology.

15/11/2024
Phase 3

– Report on NMR data processing, statistical analysis, and model building for disease stages, explaining pathogenesis mechanisms and metabolic indicators.
– Results of testing metabolic markers using NMR and HPLC in Denmark.
– Report on optimizing markers on the HPLC system in Denmark.
– Procedure for quantifying metabolites using HPLC technique, verified on 50 liver cancer samples, 50 chronic hepatitis B samples, and 50 cirrhosis samples, repeated at least 3 times.
– Analytical database on metabolic markers based on NMR and UHPLC techniques for the research groups.
– First ISI international article – Q1 accepted for publication.
– Second ISI international article – Q1 with an impact factor (IF) ≥ 4 submitted for publication.
– One patent or a decision of patent application acceptance in Vietnam and/or evidence of content examination request acceptance by the intellectual property authority and the result of patentability search from certified legal entities.
– Second ISI international article – Q1 accepted for publication.
– Achievements in early liver cancer diagnosis solutions using Metabolic-miRNA biomarkers.
– Support for training 1 PhD candidate and 2 Master’s students for units – centers – medical universities.

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