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Extending inflamed-class signature to predict immune checkpoint inhibitor-based combination therapy in hepatocellular carcinoma
  1. Wenhua You1,2,3,4,5,6,
  2. Chupeng Hu2,
  3. Mengya Zhao2,
  4. Yuhan Zhang1,2,
  5. Jinying Lu2,
  6. Yedi Huang2,
  7. Ling Li3,
  8. Yun Chen1,2,3,4,5,6
  1. 1School of Chemistry and Chemical Engineering, Center of Interventional Radiology and Vascular Surgery, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, Jiangsu, China
  2. 2The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center & Department of Immunology, School of Basic Medical Sciences, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
  3. 3Department of Endocrinology, Zhongda Hospital, School of Medicine, Key Laboratory of Environmental Medicine Engineering of Ministry of Education, Southeast University, Nanjing, Jiangsu, China
  4. 4National Innovation Platform for Integration of Medical Engineering Education (NMEE), Southeast University, Nanjing, Jiangsu, China
  5. 5Basic Medicine Research and Innovation Center of Ministry of Education, Zhongda Hospital, Southeast University, Nanjing, Jiangsu, China
  6. 6State Key Laboratory of Digital Medical Engineering, Southeast University, Nanjing, China
  1. Correspondence to Professor Yun Chen, Department of Immunology, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, Jiangsu, China; chenyun{at}njmu.edu.cn; Professor Ling Li, Department of Endocrinology, Zhongda Hospital, School of Medicine, Key Laboratory of Environmental Medicine Engineering of Ministry of Education, Southeast University, Nanjing, Jiangsu, China; lingli{at}seu.edu.cn

https://doi.org/10.1136/gutjnl-2024-333375

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    Recently, we were intrigued by a recent study by Montironi et al,1 in which they discovered that an inflamed subclass in hepatocellular carcinoma (HCC) patients is associated with a response to immunotherapy. The authors used a 20-gene signature to distinguish these patients and further found different immune infiltration between inflamed and non-inflamed class at the bulk level. We commend the authors for undertaking this study, which holds significant clinical implications. We also observed that Li et al2 have validated the predictive value of inflamed class in two additional RNA-seq datasets from patients who received anti-PD1 therapy. However, the use of combination immunotherapy, which includes dual immune checkpoint inhibitors or is combined with anti-VEGF agents, has become a growing trend in HCC.3–6 Here, we first performed unsupervised clustering on the RNA-seq data from 289 patients enrolled in the GO30140 Ph1b and IMbrave150 PhIII trials who received a combination of anti-PD-L1 and anti-VEGF therapy7 (figure 1). The results indicated that the subclass (C1), which exhibited high expression of genes associated with B/plasma cells and fibroblasts, had a higher inflamed-class score and better therapeutic efficacy (figure 1B–D). The performance of inflamed-class gene signature in predicting combination therapy response showed anarea under …

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    Footnotes

    • LL and YC are joint senior authors.

    • WY, CH, MZ and JL are joint first authors.

    • Contributors LL and YC are joint senior authors. WY, CH, MZ and JL are joint first authors. YC conceived, designed and revised the project. WY, CH and MZ analysed the data and drafted the manuscript. WY, JL and YZ assisted with the collection and visualisation of the data. JL, YH and YZ contributed to the design of methodology. LL revised and polished the manuscript. Final version of this manuscript was approved by all the authors before publication.

    • Funding This study was funded by The National Natural Science Foundation of China (82071767, 82230059, 82102876, 82130060 and 82403111),the Jiangsu Provincial Key Research Development Program of China (BE2022770), China Postdoctoral Science Foundation (2024M751488), Major Program of Wuxi Medical Center, Nanjing Medical University (WMCM20230), Jiangsu Provincial Medical Innovation Center (CXZX202219) and the Open Project of Key Laboratory of Environmental Medicine Engineering of Ministry of Education (2024EME001).

    • Competing interests None declared.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.