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Systematic Assessment of Transcriptomic Biomarkers for Immune Checkpoint Blockade Response in Cancer Immunotherapy
Shangqin Sun1, Liwen Xu1, Xinxin Zhang1
1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Background:
Immune checkpoint blockade (ICB) therapy has yielded successful clinical responses in treatment of a minority of patients in certain cancer types. Substantial efforts were made to establish biomarkers for predicting responsiveness to ICB. However, the systematic assessment of these ICB response biomarkers remains insufficient.
Methods:
We collected 22 transcriptome-based biomarkers for ICB response and constructed multiple benchmark datasets to evaluate the associations with clinical response, predictive performance, and clinical efficacy of them in pre-treatment patients with distinct ICB agents in diverse cancers.
Results:
Overall, "Immune-checkpoint molecule" biomarkers PD-L1, PD-L2, CTLA-4 and IMPRES and the "Effector molecule" biomarker CYT showed significant associations with ICB response and clinical outcomes. These immune-checkpoint biomarkers and another immune effector IFN-gamma presented predictive ability in melanoma, urothelial cancer (UC) and clear cell renal-cell cancer (ccRCC). In non-small cell lung cancer (NSCLC), only PD-L2 and CTLA-4 showed preferable correlation with clinical response. Under different ICB therapies, the top-performing biomarkers were usually mutually exclusive in patients with anti-PD-1 and anti-CTLA-4 therapy, and most of biomarkers presented outstanding predictive power in patients with combined anti-PD-1 and anti-CTLA-4 therapy.
Conclusions:
Our results show these biomarkers had different performance in predicting ICB response across distinct ICB agents in diverse cancers.
Insights
Biomarkers like PD-L1 and CYT show promise for predicting immune checkpoint blockade (ICB) therapy response. Their effectiveness varies across cancers and ICB agents, highlighting the need for tailored biomarker assessment.
Area of Science:
- Immunology
- Oncology
- Biomarker Discovery
Background:
- Immune checkpoint blockade (ICB) therapy benefits only a subset of cancer patients.
- Predictive biomarkers for ICB response are crucial but lack systematic evaluation.
- Current assessment of ICB response biomarkers is insufficient for clinical application.
Purpose of the Study:
- To systematically evaluate 22 transcriptome-based biomarkers for ICB response prediction.
- To assess biomarker associations with clinical response, predictive performance, and efficacy.
- To analyze biomarker utility across diverse cancers and ICB agents.
Main Methods:
- Collected 22 transcriptome-based biomarkers associated with ICB response.
- Constructed benchmark datasets for evaluating biomarker performance.
- Analyzed biomarker associations with clinical response in pre-treatment cancer patients.
Main Results:
- PD-L1, PD-L2, CTLA-4, IMPRES, and CYT demonstrated significant associations with ICB response and outcomes.
- IFN-gamma and immune-checkpoint biomarkers showed predictive ability in melanoma, urothelial, and renal cell cancers.
- Biomarker performance varied by cancer type (e.g., PD-L2 and CTLA-4 in NSCLC) and ICB therapy (anti-PD-1 vs. anti-CTLA-4 vs. combination).
Conclusions:
- The predictive performance of ICB response biomarkers differs significantly across various ICB agents and cancer types.
- This study underscores the need for context-specific evaluation of biomarkers for personalized ICB therapy.
