Development and Validation of Early Detection Biomarkers for Liver Cancer
Objective/Hypsothesis: Our long-term research goal is to decrease liver cancer morbidity and mortality. Our objective for this proposal is to define and independently validate blood protein biomarkers that are novel, non-invasive, highly accurate for pre-diagnostic liver cancer detection at the earliest, currently feasible time, when earlier intervention may result in prolonged survival or cure.
Specific Aims: Built upon our NIH-funded study that identified multiple proteins in cancer-associated pathways and a predictor model, we now propose the following aims for pre-diagnostic liver cancer detection:
Aim 1. Develop a parsimonious biomarker risk stratification model for early detection of liver cancer through identifying a series of novel, minimally invasive, highly specific and sensitive biomarkers; the model will be using multiplex immunoassay analysis (i.e., ELISA) of SomaScan-derived liver cancer associated biomarkers.
Aim 2. Validate the risk stratification model in an independent clinical cohort of patients with liver cirrhosis.
Study Design: We will leverage two independent data sources that features both healthy individuals and patients with liver cirrhosis: (1) two cohort studies of the general population (i.e., initially healthy individuals); and (2) a novel cohort of patients with liver cirrhosis with long term follow-up, capitalizing on the existing infrastructure of a biobank. We will develop a robust biomarker predictors for liver cancer and further advance non-invasive early detection of liver cancer from bench to the bedside.
Upon completion of this study, we expect to define and validate a panel of novel circulating biomarkers that advance early detection of liver cancer from bench to the bedside. These findings will bridge opportunities for future, multi-institutional studies in evaluation of the clinical validity and utility for early detection, and complement other diagnostic tools for liver cancer diagnosis. Ultimately, this knowledge could transform clinical care and management of liver cancer and reduce the mortality of this deadly disease.
In the US, the annual incidence of hepatocellular carcinoma (HCC), the most common type of liver cancer, has tripled since 1980. HCC is projected to become the third leading cause of cancer death by 2040. Despite significant efforts, accurate early detection of HCC using non-invasive, highly specific and sensitive biomarkers remains elusive and tools such as alpha-fetoprotein (AFP), ultrasonography, or both for monitoring development of HCC are not highly accurate for clinical diagnosis.
Our long-term research goal is to decrease liver cancer morbidity and mortality. Our objective for this proposal is to define and independently validate novel, non-invasive, highly accurate blood protein biomarkers for pre-diagnostic liver cancer detection, when earlier intervention may result in prolonged survival or cure. Innovative, high-throughput analytical platforms measuring a significant slice of the proteome have recently emerged as new tools to discover biomarkers at low concentrations in blood. The most comprehensive among those next generation proteomics platforms, SomaScan, an aptamer-based immuno-like biomarker discovery technology, simultaneously measures thousands different proteins across the entire dynamic range (>10 logs) with high sensitivity, accuracy, and reproducibility in plasma. Applying SomaScan in our pilot study based on our funded NIH/NCI R21 (CA238651) project to the Nurses’ Health Study (NHS) and Health Professionals Follow-up Study (HPFS), we identified protein signatures in pre-diagnostic plasma associated with subsequent HCC diagnosis. We further confirmed the enhanced expression of four of these proteins in individuals diagnosed with liver cancer by ELISA, providing strong support for these proteins being elevated in initially healthy individuals years before liver cancer diagnosis. To expand on these intriguing results, we now propose to use ELISA for analysis of the SomaScan derived HCC proteins and to leverage two independent data sources: (1) two cohort studies of initially healthy individuals: the Southern Community Cohort Study (SCCS), and Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial cohort; and (2) a novel cohort of patients with liver cirrhosis with long term follow-up, capitalizing on the existing infrastructure of the Mass General Brigham Biobank. Our specific aims are to:
Aim 1. Develop a parsimonious biomarker risk stratification model for early detection of liver cancer using multiplex immunoassay analysis (i.e., ELISA) of SomaScan-derived liver cancer associated biomarkers. We hypothesize that:
1a) ELISA will confirm that all selected protein biomarkers are associated with HCC in the SCCS and PLCO cohorts (~400 HCC cases and ~800 matched healthy controls).
1b) An ELISA-based proteomic classifier model will be developed that predicts HCC prior to clinical diagnosis and differentiates people who develop HCC from those who remain healthy.
Aim 2. Validate the risk stratification model for early detection of liver cancer in an independent clinical cohort of patients with liver cirrhosis (~200 HCC cases and ~400 cirrhosis controls). We hypothesize that:
2a) Via ELISA, we will validate the set of protein biomarkers discovered in Aim 1.
2b) An ELISA-based risk stratification model developed in the initial healthy individuals (Aim 1) will perform with similar high prediction accuracy and discriminant value for high risk individuals with liver cirrhosis.
Xuehong Zhang (Harvard Medical School and Brigham and Women's Hospital)
Towia Libermann (Beth Israel Deaconess Medical Center and Harvard Medical School)
Long Ngo (Beth Israel Deaconess Medical Center and Harvard Medical School)
Staci Sudenga (Vanderbilt University Medical Center)