Overcoming resistance to anti-PD-L1 immunotherapy: mechanisms, combination strategies, and future directions

Sep 23, 2026

Cancer cells evade immune surveillance by upregulating programmed cell death-ligand 1 (PD-L1), which binds PD-1 on T cells and impairs their function. Although anti-PD-1/PD-L1 therapies improve outcomes for many patients, overall efficacy remains limited and resistance is a major barrier. This review details PD-L1 biology, including regulators of its expression and tumor-immune interactions, and synthesizes resistance mechanisms to anti-PD-L1 treatment. It also summarizes combination strategies, tumor microenvironment modulation, neoantigen targeting, and dynamic biomarker monitoring. High-resolution imaging, machine learning, multi-omics profiling, and liquid biopsy for soluble PD-L1 are highlighted to improve patient stratification. Clinical trial landscapes integrating checkpoint therapy with chemotherapy, radiotherapy, targeted therapy, CAR-T, and metabolic immunotherapy are examined to inform more personalized care.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages52

Reading Time2 h 11 min

AccessFree to download

Abstract

Introduction

Cancer and therapeutic heterogeneity

Immune evasion and immune concepts (three Es, three Cs)

Mandal etal. Molecular Cancer (2025) 24:246 [https://doi.org/10.1186/s12943-025-02400-z](https://doi.org/10.1186/s12943-025-02400-z) Molecular Cancer REVIEW Open Access Overcoming resistance to anti-PD-L1 immunotherapy: mechanisms, combination strategies, and future directions Kartik Mandal1,2 , Ganesh Kumar Barik3,4 and Manas Kumar Santra1* Abstract Cancer cells express high levels of programmed cell death-ligand 1 (PD-L1) to evade immune surveillance. PD-L1 interacts with PD-1 onT cells to make them non-functional. Thus, PD-L1 and PD-1 are pivotal targets in cancer immunotherapy. While anti-PD-1/PD-L1 therapies have offered renewed hope for many patients, their modest efficacy remains a critical concern. This underscores the urgent need to unravel the intricate mechanisms that govern both therapeutic responses as well as resistance to immunotherapy. This review explores the multifaceted nature of PD-L1, including factors that regulate its expression, tumor-immune interactions, and the resistance mechanisms associated with anti-PD-L1 immunotherapy. Several promising strategies have been explored to overcome these challenges, such as combination therapies, modulation of the tumor microenvironment, neoantigen targeting, and dynamic biomarker monitoring. Outcomes of these approaches, integrating advanced technologies like highresolution imaging, machine learning, multi-omics profiling, and liquid biopsy for soluble PD-L1 detection emerge as a powerful means to refine patient stratification. Together, these innovations pave the way toward more precise and personalized immunotherapy, maximizing clinical benefits for cancer patients. Additionally, the evolving landscape of clinical trials involving anti-PD-1/PD-L1 monoclonal antibodies has been explored, emphasizing the integration of immune checkpoint therapies with chemotherapy, radiotherapy, targeted therapy, CAR-T, and metabolic immunotherapy to overcome resistance in refractory cancers. By embarking on these challenges and leveraging novel therapeutic strategies, this review intends to advance the understanding of more effective, personalized cancer immunotherapies, ultimately improving outcomes for a broader range of patients. Keywords PD-L1, PD-1, Immune checkpoint inhibitors, Cancer immunotherapy resistance, SPD-L1, Tumor mutational burden, Combination therapy, Metabolomics, Artificial intelligence, Machine learning, Multi-omics *Correspondence: Manas Kumar Santra[manas@nccs. res.in](manas@nccs. res.in) Full list of author information is available at the end of the article © The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit [http://creativecommons.org/licenses/by-nc-nd/4.0/](http://creativecommons.org/licenses/by-nc-nd/4.0/.)[.](http://creativecommons.org/licenses/by-nc-nd/4.0/.) Mandal etal. Molecular Cancer (2025) 24:246 Page 2 of 52 Graphical abstract Introduction Cancer is characterized by uncontrolled cell proliferation resulting from dynamic alterations in the genome and post-genomic events, leading to the formation

FAQs

How do PD-L1 and PD-1 contribute to resistance to immunotherapy?

Cancer cells express high PD-L1 to evade immune surveillance. PD-L1 binding to PD-1 renders T cells non-functional, making PD-L1/PD-1 central targets and also a key axis for resistance.

What strategies does the review discuss to overcome anti-PD-L1 immunotherapy resistance?

The review highlights combination therapies, modulation of the tumor microenvironment, neoantigen targeting, and dynamic biomarker monitoring.

Which advanced technologies are proposed to improve patient stratification?

It emphasizes high-resolution imaging, machine learning, multi-omics profiling, and liquid biopsy approaches for detecting soluble PD-L1 to refine stratification and support personalized immunotherapy.

Sep 23, 2026

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