Document text
Principal Investigator: Jagpreet Chhatwal
Organization: BAYLOR COLLEGE OF MEDICINE
Fiscal Year: 2024
Award: $433,960
Funding agency: National Cancer Institute
The Translational Research Center (TRC) includes a diverse team of clinical and translational researchers with
a strong track record of working together to reduce hepatocellular cancer (HCC). The TRC uses data from a
unique group of patients with cirrhosis who are being recruited from eight different sites throughout Texas (the
TRC cohort). Our TRC cohort currently includes > 3700 patients with cirrhosis (>10,000 follow up surveillance
visits and >190 HCC cases) who have diverse risk factors, including cured HCV and non-alcoholic fatty liver
disease. These patients are under routine HCC surveillance and their biological samples and clinical and
radiological data for each visit is stored; it is a valuable resource for our research and other Consortium projects.
We also launched a separate prospective cohort of patients with indeterminate liver nodules, which is a high risk
and high priority group for HCC risk stratification and early detection. We are collecting surveys, clinical data,
images and biospecimens from this cohort. The catalytic effects of our TRC are seen in the productivity of our
junior investigators, who started innovative new initiatives and programs. Our work had a broad impact, including
helping develop various society guidelines on HCC surveillance. Using data and the strong network of
investigators and institutions collaborating with our TRC, we have already generated important data on risk
factors and risk stratification for HCC. We also developed and demonstrated the framework for adding patient-
and liver disease-related factors to new blood-biomarker profiles to improve early HCC detection. Here, we
propose to build a novel imaging repository, including MRI images from our cohort. We will annotate and
incorporate data from abdominal ultrasound reports for our TRC cohort using novel, scalable machine learning
pipelines. We will also strengthen our data by appending information from the State cancer registries. Using data
from different sources available to us, we will develop and test new personalized methods to stratify risk that
blends information from clinical factors, blood-based biomarkers, and imaging (radiomics) to predict future
development of HCC in patients with cirrhosis across diverse risk factors (Aim 1). We showed that the HCC
Early Detection Screening (HES) algorithm, when combined with HCC blood-based biomarkers (AFP‐L3, DCP)
in HES version 2.0 (HES v2.0), substantially improved early detection. We will validate and compare HES v2.0
with GALAD, another early detection algorithm, and evaluate their performance versus the current standard
ultrasound-based surveillance (Aim 2). In Aim 3, we will develop a new mathematical model to look at how
useful current and emerging biomarkers are for detecting HCC. We will also assess the risks, costs, and benefits
of HCC surveillance using different cutoffs of existing and novel blood and imaging biomarkers. We will develop
and disseminate an online Simulator so that other investigators can evaluate the potential clinical utility of HCC
early detection biomarkers as potential surveillance tools. Our translational approach will have both an immediate
and long-lasting impact on HCC-related morbidity and mortality.
Terms: <AFP><AFP gene><AI system><Abdomen><Active Follow-up><African American group><African American individual><African American people><African American population><African Americans><Algorithms><Applications Grants><Artificial Intelligence><Behavioral><Biological><Biological Markers><Biological Specimen Banks><Biological Substance Banks><Blinded><Blood><Blood Reticuloendothelial System><Blood Serum><Cancer Detection><Cancers><Center for Translational Science Activities><Cirrhosis><Clinical><Clinical Data><Clinical/Radiologic><Collaborations><Computer Reasoning><Costs and Benefits><DNA><Data><Decision Analysis><Deoxyribonucleic Acid><Development><Dimensions><Disease><Disorder><EDRN><Early Detection Research Network><Early Diagnosis><Enrollment><Ensure><Equilibrium><Evaluation><FETA><Fats><Fatty acid glycerol esters><Fibrosis><Funding><Future><Genetic Markers><Germ Lines><Goals><Grant Proposals><Guidelines><HCV><HCV infection><HPAFP><Health Care Systems><Healthcare Systems><Hepatic Cancer><Hepatic Disorder><Hepatitis C><Hepatitis C virus><Hepatitis C virus infection><Hepatitis, Viral, Non-A, Non-B, Parenterally-Transmitted><Hepatitus C><Hepatocarcinoma><Hepatocellular Carcinoma><Hepatocellular cancer><Hepatoma><Hispanic Populations><Hispanic group><Hispanic individual><Hispanic people><Hispanics><Image><Image data archive><Infrastructure><Institution><Investigators><Liver><Liver Cells Carcinoma><Liver Fibrosis><Liver diseases><MR Imaging><MR Tomography><MRI><MRIs><Machine Intelligence><Magnetic Resonance Imaging><Malignant Neoplasms><Malignant Tumor><Malignant neoplasm of liver><Maps><Math Models><Medical Imaging, Magnetic Resonance / Nuclear Magnetic Resonance><Metabolic Marker><Methods><Modality><Modeling><Morbidity><Morbidity - disease rate><NAFLD><NMR Imaging><NMR Tomography><National Detection Research Network><Nodule><Nuclear Magnetic Resonance Imaging><Patients><Pattern><Performance><Phase><Phase III study><Portal Hypertension><Primary carcinoma of the liver cells><Productivity><Prospective cohort><Reporting><Research><Research Personnel><Research Resources><Researchers><Resources><Risk><Risk Assessment><Risk Factors><Sampling><Science><Screening for Hepatocellular Cancer><Screening for cancer><Serum><Severities><Site><Societies><Source><Spleen><Spleen Reticuloendothelial System><Subgroup><Survey Instrument><Surveys><Testing><Texas><Underrepresented Groups><Underrepresented Populations><Visceral fat><Visit><Work><Zeugmatography><active followup><balance><balance function><bio-markers><biobank><biologic><biologic marker><biological specimen repository><biomarker><biomarker array><biomarker panel><biomarker validation><biorepository><biosample repository><biospecimen bank><biospecimen repository><blood-based biomarker><blood-based marker><cancer biomarkers><cancer markers><cancer registry><cirrhotic><clinical decision-making><clinical practice><cohort><comparative><cost><cost effectiveness><design><designing><detection sensitivity><developmental><early biomarkers><early cancer detection><early detection><early detection biomarkers><early detection markers><early liver cancer detection><enroll><ethnic diversity><ethnically diverse><fibrotic liver><follow up><follow-up><followed up><followup><gene biomarker><gene expression biomarker><gene marker><gene signature biomarker><genetic biomarker><hep C><hepatic body system><hepatic disease><hepatic fibrosis><hepatic organ system><hepatitis non A non B><hepatopathy><high risk><image archival system><image archive><image library><image repository><imaging><imaging biomarker><imaging marker><imaging repository><imaging-based biological marker><imaging-based biomarker><imaging-based marker><improved><infection by hepatitis c virus><innovate><innovation><innovative><liver cancer><liver cancer detection><liver carcinoma><liver disorder><liver function><liver imaging><liver malignancy><liver scanning><machine learning based pipeline><machine learning pipeline><malignancy><malignant liver tumor><marker panel><marker validation><mathematic model><mathematical model><mathematical modeling><mortality><multidisciplinary><muscle bulk><muscle form><muscle mass><neoplasm registry><neoplasm/cancer><non A, non B hepatitis><non-A, non-B hepatitis><non-alcohol fatty liver disease><non-alcoholic fatty liver disease><non-alcoholic liver disease><nonalcoholic fatty liver disease><novel><phase 3 study><picture archive><programs><prospective><racial diversity><racially diverse><radiomics><recruit><risk stratification><sample collection><screening><screening cancer patients><screening for liver cancer><screenings><specimen bank><specimen collection><specimen repository><stratify risk><subcutaneous><subdermal><surveillance strategy><tool><translation strategy><translational approach><translational investigator><translational research center><translational researcher><translational sciences center><translational scientist><translational strategy><ultrasound><under representation of groups><under represented groups><under represented people><under represented populations><underrepresentation of groups><underrepresented people><virtual>