The overall goal of the proposed research is to improve survival for hepatocellular (liver) cancer (HCC) and to support the continued development of the candidate into an independent investigator. With an average five year survival of 12%, the prognosis of HCC is poor and, in contrast to most cancers in the United States, mortality is increasing. Unfortunately, liver resection is often not possible due to liver dysfunction from cirrhosis. Orthotopic liver transplant (OLT) improves survival for HCC patients meeting the Milan criteria. However, there is a national liver donor shortage and more than 20% of candidates lose OLT eligibility (and the chance for cure) while waiting, usually due to HCC progression. Liver-directed therapies attempt to cure patients or """"""""bridge"""""""" them until OLT but are suboptimal for HCC >3cm. In addition, evaluation of long-term efficacy is constrained by few prospective trials. For HCC greater than 3cm in size, successful liver directed treatment with radiofrequency ablation (RFA) is limited by the heat sink effect of blood flow. Invasive occlusion of liver blood flow improves RFA efficacy, but adds morbidity and mortality risks. Thus, there is a critical unmet clinical need. Antiangiogenic agents, such as sorafenib, reduce tumor blood flow and improve RFA efficacy in animals. This approach has not yet been tested in humans. This proposal hypothesizes that sorafenib reduces HCC blood flow and improves RFA efficacy and that liver directed therapies with better local control also improve survival for HCC tumors greater than 3cm in size. The proposed research will test these hypotheses with three methods that integrate the strengths of clinical trial and modeling approaches. A Phase II randomized, controlled trial will determine the effect of sorafenib on RFA efficacy for HCC greater than 3cm in size (AIM 1). The size of the ablation zone and the change in tumor blood flow after sorafenib will be measured on radiologic images. In addition, a computer model will be built to analyze the long-term consequences of single and combination (concurrent and sequential) liver-directed therapy for HCC >3cm (AIM 2). National OLT data, an institutional HCC database, and the literature will inform model parameters and model calibration. The effect of each liver directed strategy on overall survival (OS) and OLT wait list drop out will be determined. Results form extensive sensitivity analysis will help inform the development of future HCC trials (AIM 3). Because there is minimal long-term efficacy data for existing liver-directed strategies, the proposed research will advance knowledge about antiangiogenic therapy and RFA in HCC and will add to our understanding of appropriate HCC management and HCC trial design issues. The candidate's immediate career goal is to advance the field of HCC treatment through efficient identification and development of therapies that optimize long-term patient outcomes. The candidate's long- term academic career goal is to found and direct an academic research center of investigators who integrate clinical trial and outcomes modeling research in order to advance cancer care and clinical trials. In order to achieve these research and career goals, the candidate is supported by mentors with expertise in the key areas of the proposed research. In addition to frequent research discussion with mentors, the candidate will pursue additional advanced training through advanced clinical trial, mathematics, statistics and modeling coursework. In summary, with the support of the K23 Patient Oriented Mentored Research Award, the candidate will achieve the specific aims of the research, advance the field of HCC treatment and will gain the skills and experience necessary to become a leading independent investigator.

Public Health Relevance

Although the incidence of liver cancer is rising in the United States, it remains a deadly and difficult to treat cancer. The proposed research will evaluate a novel method to approve local treatment of liver cancer in a clinical trial. In addition, a computer model will be built to better evaluate the long-term outcomes of local treatment of liver cancer and to guide the design of future liver cancer trials.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Mentored Patient-Oriented Research Career Development Award (K23)
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Study Section
Subcommittee G - Education (NCI)
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Lim, Susan E
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Beth Israel Deaconess Medical Center
United States
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