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Updated: Nov 17, 2025

Multiplexed Immunofluorescence Analysis and Quantification of Intratumoral PD-1+ Tim-3+ CD8+ T Cells
Published on: February 8, 2018
Emerging dynamics pathways of response and resistance to PD-1 and CTLA-4 blockade: tackling uncertainty by
Allan Relecom1, Maysaloun Merhi1, Varghese Inchakalody1
1Department of Medical Oncology, Translational Research Institute, National Center for Cancer Care and Research, Hamad Medical Corporation, Doha, Qatar.
Abstract:
Immune checkpoint inhibitors provide considerable therapeutic benefit in a range of solid cancers as well as in a subgroup of hematological malignancies. Response rates are however suboptimal, and despite considerable efforts, predicting response to immune checkpoint inhibitors ahead of their administration in a given patient remains elusive. The study of the dynamics of the immune system and of the tumor under immune checkpoint blockade brought insight into the mechanisms of action of these therapeutic agents. Equally relevant are the mechanisms of adaptive resistance to immune checkpoint inhibitors that have been uncovered through this approach. In this review, we discuss the dynamics of the immune system and of the tumor under immune checkpoint blockade emanating from recent studies on animal models and humans. We will focus on mechanisms of action and of resistance conveying information predictive of therapeutic response.
Insights
Predicting patient response to immune checkpoint inhibitors remains challenging. This review explores immune system and tumor dynamics under blockade, focusing on action and resistance mechanisms for predicting therapeutic success.
Area of Science:
- Immunology
- Oncology
- Cancer Therapy
Background:
- Immune checkpoint inhibitors (ICIs) offer therapeutic benefits in various cancers.
- Suboptimal response rates and lack of predictive biomarkers limit ICI efficacy.
- Understanding resistance mechanisms is crucial for improving treatment outcomes.
Purpose of the Study:
- To review the dynamics of the immune system and tumors under ICI therapy.
- To elucidate mechanisms of action and adaptive resistance to ICIs.
- To identify predictive markers for therapeutic response.
Main Methods:
- Analysis of recent studies on animal models and human patients.
- Focus on immune system and tumor microenvironment changes.
- Integration of data on mechanisms of action and resistance.
Main Results:
- ICI therapy induces complex immune and tumor dynamics.
- Adaptive resistance mechanisms can emerge under ICI pressure.
- Specific dynamics and resistance patterns may predict treatment response.
Conclusions:
- Understanding ICI action and resistance dynamics is key to improving patient selection.
- Further research into predictive biomarkers is warranted.
- Tailoring ICI therapy based on dynamic responses could enhance efficacy.
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