Artificial intelligence-based immunoprofiling serves as a potentially predictive biomarker of nivolumab treatment for advanced hepatocellular carcinoma

Jan-Mou Lee; Yi-Ping Hung; Kai-Yuan Chou; Cheng-Yun Lee; Shian-Ren Lin; Ya-Han Tsai; Wan-Yu Lai; Yu-Yun Shao; Chiun Hsu; Chih-Hung Hsu; Yee Chao

doi:10.3389/fmed.2022.1008855

Artificial intelligence-based immunoprofiling serves as a potentially predictive biomarker of nivolumab treatment for advanced hepatocellular carcinoma

Front Med (Lausanne). 2022 Nov 8:9:1008855. doi: 10.3389/fmed.2022.1008855. eCollection 2022.

Authors

Jan-Mou Lee¹, Yi-Ping Hung^{2

3}, Kai-Yuan Chou³, Cheng-Yun Lee³, Shian-Ren Lin³, Ya-Han Tsai³, Wan-Yu Lai³, Yu-Yun Shao^{4

5

6}, Chiun Hsu^{4

6}, Chih-Hung Hsu^{4

6}, Yee Chao^{2

3}

Affiliations

¹ FullHope Biomedical Co., Ltd., New Taipei City, Taiwan.
² Department of Oncology, Taipei Veterans General Hospital, Taipei, Taiwan.
³ School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
⁴ College of Medicine, Graduate Institute of Oncology, National Taiwan University, Taipei, Taiwan.
⁵ Department of Medical Oncology, National Taiwan University Cancer Center, Taipei, Taiwan.
⁶ Department of Oncology, National Taiwan University Hospital, Taipei, Taiwan.

Abstract

Immune checkpoint inhibitors (ICI) have been applied in treating advanced hepatocellular carcinoma (aHCC) patients, but few patients exhibit stable and lasting responses. Moreover, identifying aHCC patients suitable for ICI treatment is still challenged. This study aimed to evaluate whether dissecting peripheral immune cell subsets by Mann-Whitney U test and artificial intelligence (AI) algorithms could serve as predictive biomarkers of nivolumab treatment for aHCC. Disease control group carried significantly increased percentages of PD-L1⁺ monocytes, PD-L1⁺ CD8 T cells, PD-L1⁺ CD8 NKT cells, and decreased percentages of PD-L1⁺ CD8 NKT cells via Mann-Whitney U test. By recursive feature elimination method, five featured subsets (CD4 NKTreg, PD-1⁺ CD8 T cells, PD-1⁺ CD8 NKT cells, PD-L1⁺ CD8 T cells and PD-L1⁺ monocytes) were selected for AI training. The featured subsets were highly overlapping with ones identified via Mann-Whitney U test. Trained AI algorithms committed valuable AUC from 0.8417 to 0.875 to significantly separate disease control group from disease progression group, and SHAP value ranking also revealed PD-L1⁺ monocytes and PD-L1⁺ CD8 T cells exclusively and significantly contributed to this discrimination. In summary, the current study demonstrated that integrally analyzing immune cell profiling with AI algorithms could serve as predictive biomarkers of ICI treatment.

Keywords: artificial intelligence; hepatocellular carcinoma (HCC); immunoprofiling; immunotherapy; nivolumab (PubChem SID: 178103907); predictive biomarker.