Predicting Outcome of Transplant-Eligible Patients with Hepatocellular Carcinoma

Abstract

In recent years, significant advancements in systemic therapies for hepatocellular carcinoma (HCC) have markedly improved overall survival rates, expanding the scope of curative treatment options like resection and transplantation, which were previously limited to early-stage HCC. However, a key challenge in clinical practice remains the accurate identification of patients most likely to achieve successful long-term responses to these therapies. This study aims to address this challenge by developing a multi-modal prognostic algorithm that integrates radiographic data and innovative blood-based tumor markers to predict treatment responses and identify potential candidates for liver transplantation. The study cohort comprises HCC patients initially considered ineligible for transplantation due to their elevated baseline tumor burdens, but who subsequently undergo liver-directed treatments and immunotherapy. Our comprehensive approach involves the analysis of blood and urine samples for circulating tumor cells and circulating tumor DNA, as well as the detailed evaluation of MRI and CT images to extract valuable radiographic information. Over the course of one year, patients are closely monitored, and outcomes are assessed as they either achieve transplantation eligibility through down-staging or experience disease progression. This ongoing study holds the potential to pinpoint individuals who can benefit from early, more aggressive interventions, thereby acting as a bridge to liver transplantation and preventing further deterioration of liver function. It represents a significant stride forward in the realms of HCC treatment and transplantation eligibility assessment.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2023
Accession Number
AD1225468

Entities

People

  • Amy K. Kim
  • Boyoung Cha
  • Harry Luu
  • Kanako Yoshida

Organizations

  • Johns Hopkins University

Tags

Fields of Study

  • Medicine

Readers

  • Molecular and Cellular Biology
  • Oncology

Technology Areas

  • Biotechnology