Clin Mol Hepatol.  2024 Oct;30(4):807-823. 10.3350/cmh.2024.0333.

Genomic biomarkers to predict response to atezolizumab plus bevacizumab immunotherapy in hepatocellular carcinoma: Insights from the IMbrave150 trial

Affiliations
  • 1Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea
  • 2Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, CHA Bundang Medical Center, CHA University, Seongnam, Korea
  • 3Metabolic Regulation Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Korea
  • 4Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
  • 5Department of Surgery, Korea University Guro Hospital, Seoul, Korea
  • 6Department of Obstetrics and Gynecology, Kyung Hee University Hospital at Gangdong, Seoul, Korea
  • 7Department of Obstetrics and Gynecology, Kyung Hee University Hospital at Gangdong, Seoul, Korea
  • 8Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
  • 9Department of Pathology, Yonsei University College of Medicine, Seoul, Korea
  • 10Department of Biomedical Sciences, Dong-A University, Busan, Korea
  • 11Department of Health Sciences, The Graduate School of Dong-A University, Busan, Korea
  • 12Department of Immunology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

Abstract

Background/Aims
Combination immunotherapy, exemplified by atezolizumab plus bevacizumab, has become the standard of care for inoperable hepatocellular carcinoma (HCC). However, the lack of predictive biomarkers and limited understanding of response mechanisms remain a challenge.
Methods
Using data from the IMbrave150plus cohort, we applied an immune signature score (ISS) predictor to stratify HCC patients treated with atezolizumab plus bevacizumab or with sorafenib alone into potential high and low response groups. By applying multiple statistical approaches including a Bayesian covariate prediction algorithm, we refined the signature to 10 key genes (ISS10) for clinical use while maintaining similar predictive power to the full model. We further validated ISS10 in an independent HCC cohort treated with nivolumab plus ipilimumab.
Results
The study identified a significant association between the ISS and treatment response. Among patients classified as high responders, those treated with the atezolizumab plus bevacizumab combination exhibited improved overall and progression-free survival as well as better objective response rate compared to those treated with sorafenib. We also observed a significant correlation between ISS10 and response to nivolumab plus ipilimumab treatment. Analysis of immune cell subpopulations revealed distinct characteristics associated with ISS subtypes. In particular, the ISS10 high subtype displayed a more favorable immune environment with higher proportions of antitumor macrophages and activated T-cells, potentially explaining its better response.
Conclusions
Our study suggests that ISS and ISS10 are promising predictive biomarkers for enhanced therapeutic outcomes in HCC patients undergoing combination immunotherapy. These markers are crucial for refining patient stratification and personalized treatment approaches to advance the effectiveness of standard-of-care regimens.

Keyword

Hepatocellular carcinoma; Immunotherapy; Atezolizumab; Bevacizumab; Transcriptome
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