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Updated: Dec 29, 2025

Identifying PD-1/PD-L1 Inhibitors with Surface Plasmon Resonance Technology
Published on: May 2, 2025
Predictive biomarkers and mechanisms underlying resistance to PD1/PD-L1 blockade cancer immunotherapy
Daixi Ren1,2,3, Yuze Hua1,2,3, Boyao Yu1,2,3
1NHC Key Laboratory of Carcinogenesis and Hunan Key Laboratory of Translational Radiation Oncology, Hunan Cancer Hospital and The Affiliated Cancer Hospital, Xiangya School of Medicine, Central South University, Changsha, Hunan, China.
Abstract:
Immune checkpoint blockade targeting PD-1/PD-L1 has promising therapeutic efficacy in a variety of tumors, but resistance during treatment is a major issue. In this review, we describe the utility of PD-L1 expression levels, mutation burden, immune cell infiltration, and immune cell function for predicting the efficacy of PD-1/PD-L1 blockade therapy. Furthermore, we explore the mechanisms underlying immunotherapy resistance caused by PD-L1 expression on tumor cells, T cell dysfunction, and T cell exhaustion. Based on these mechanisms, we propose combination therapeutic strategies. We emphasize the importance of patient-specific treatment plans to reduce the economic burden and prolong the life of patients. The predictive indicators, resistance mechanisms, and combination therapies described in this review provide a basis for improved precision medicine.
Insights
Immune checkpoint blockade targeting PD-1/PD-L1 shows promise but faces resistance. This review explores predictive biomarkers, resistance mechanisms, and combination therapies for improved precision medicine in cancer treatment.
Area of Science:
- Oncology
- Immunology
- Precision Medicine
Background:
- Immune checkpoint inhibitors targeting PD-1/PD-L1 offer therapeutic benefits for various cancers.
- Treatment resistance remains a significant challenge in PD-1/PD-L1 blockade therapy.
Purpose of the Study:
- To review predictive biomarkers for PD-1/PD-L1 blockade efficacy.
- To explore mechanisms of immunotherapy resistance.
- To propose combination therapeutic strategies for enhanced cancer treatment.
Main Methods:
- Analysis of PD-L1 expression levels.
- Assessment of tumor mutation burden.
- Evaluation of immune cell infiltration and function.
- Review of mechanisms of T cell dysfunction and exhaustion.
Main Results:
- PD-L1 expression, mutation burden, and immune cell status are key predictors of treatment response.
- Tumor cell PD-L1 expression, T cell dysfunction, and exhaustion contribute to resistance.
- Combination therapies can overcome resistance mechanisms.
Conclusions:
- Personalized treatment plans incorporating predictive biomarkers and combination strategies are crucial for effective precision medicine.
- Understanding resistance mechanisms guides the development of novel therapeutic approaches.
- This review provides a framework for optimizing PD-1/PD-L1 blockade therapy.
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