# Risk Stratification for and Early Detection of Liver Cancer > **NIH NIH U01** · BAYLOR COLLEGE OF MEDICINE · 2021 · $688,269 ## Abstract The Translational Research Center (TRC) includes a multidisciplinary team of clinical and translational researchers that has a strong track record of collaborative work, with the collective mission of reducing the burden of HCC. At the center of the proposed TRC lie two unique active prospective (in-HCC surveillance) cohorts of patients with cirrhosis. One of the cohorts comes from a Cancer Prevention and Research Institute of Texas (CPRIT) funded ongoing prospective multicenter study (Texas HCC Consortium) that is on target to recruit > 3000 patients with cirrhosis (>12,000 surveillance episodes and 200 expected HCC cases) from diverse etiologies (including cured HCV and non-alcoholic fatty liver disease). These patients are under routine bi-annual surveillance at 5 medical centers in Texas. The second is a cohort of >700 patients (>1,300 visits surveillance episodes and 33 incident HCC cases as of September 2017) recruited from and prospectively followed at the Houston VA, most with cured HCV. The TRC will leverage, extend follow up, and harmonize data and samples from both cohorts, collectively resulting in a > 23,000 episodes of HCC surveillance (and > 300 expected HCC) with bio-banked specimens, clinical and radiological data for each episode, rendering it an invaluable resource for the proposed research and other trans-consortium projects. Using data from these cohorts, we will develop and test novel personalized risk stratification indices for predicting the future ‐ development to HCC in patients with cirrhosis across diverse etiologies (Aim 1). We will also develop and evaluate an early detection algorithm that combines existing HCC blood based biomarkers (e.g., AFP, AFP L3, DCP), their longitudinal changes over time and select host features (age, etiology) in a phase 3 study. We will also examine the performance of this algorithm in patients at different HCC risk strata (Aim 2). Our work will set the framework for incorporating other patient and liver disease related factors into (new) biomarker profiles, an area that is likely to remain highly relevant irrespective of the type of biomarker. We will evaluate highly promising methylated DNA markers (MDMs, liquid biopsy) as an independent test for HCC risk prediction in Aim 3. These markers have been identified in tissue case control phase 1 studies, reliable assays have been developed and they have excellent performance for HCC detection in phase 2 studies. We will validate individual markers in the study cohort and train an algorithm that combines the MDM to achieve maximum performance. In a phase 3 biomarker study, we will validate the algorithm in the test sample overall and in key subgroups based on HCC risk strata. Our approach (optimizing available markers while simultaneously maintaining a strong forward outlook) will have both an immediate and long-lasting impact on HCC related morbidity and mortality. The TRC will build on established and strong infra-structure and relationships... ## Key facts - **NIH application ID:** 10239079 - **Project number:** 5U01CA230997-04 - **Recipient organization:** BAYLOR COLLEGE OF MEDICINE - **Principal Investigator:** FASIHA KANWAL - **Activity code:** U01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $688,269 - **Award type:** 5 - **Project period:** 2018-09-13 → 2023-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10239079 ## Citation > US National Institutes of Health, RePORTER application 10239079, Risk Stratification for and Early Detection of Liver Cancer (5U01CA230997-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10239079. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*