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Multiplexed Immunofluorescence Analysis and Quantification of Intratumoral PD-1+ Tim-3+ CD8+ T Cells
Published on: February 8, 2018
Identification of responders to immune checkpoint therapy: which biomarkers have the highest value?
1Institute of Toxicology, University Medical Center Mainz at the Johannes Gutenberg, University of Mainz, Mainz, Germany.
Abstract:
Evasion of immune recognition by the innate and acquired immune system is a major principle of tumour cells and belongs to the hallmarks of cancer. Immune checkpoint inhibitor-based cancer therapies targeting the co-inhibitory receptors CTLA-4 or PD-1 have received enormous scientific and clinical attention during the last few years, because of promising clinical results observed in the treatment of different cancer entities including melanoma and cutaneous squamous cell carcinoma. However, the enthusiasm about the effects of the immune checkpoint inhibitors is muted as only a subfraction of patients shows a stable clinical response. To predefine the patient cohorts that may benefit from immune checkpoint therapy, rigorous biomarker analyses, which predict the response to these novel therapies, need to be performed. In addition, combination of immune checkpoint therapy with classical DNA-damaging chemotherapy or radiotherapy, which positively affects tumour neo-antigen presentation, appears to be a promising approach in optimizing patients' response. In this review, we briefly summarize important biomarkers for patient stratification and discuss the current limitations of these biomarkers in defining responders vs. non-responders to immune checkpoint therapy.
Insights
Cancer cells evade immune detection, but immune checkpoint inhibitors targeting CTLA-4 or PD-1 show limited patient response. Biomarker analysis is crucial for identifying patients who will benefit from these therapies.
Area of Science:
- Oncology
- Immunology
- Cancer Research
Background:
- Tumor cells evade immune surveillance, a hallmark of cancer.
- Immune checkpoint inhibitors (ICIs) targeting CTLA-4 and PD-1 have shown promise in treating cancers like melanoma.
- However, only a fraction of patients respond to ICI therapy, necessitating predictive biomarkers.
Purpose of the Study:
- To review key biomarkers for stratifying patients for immune checkpoint inhibitor therapy.
- To discuss the limitations of current biomarkers in predicting treatment response.
- To explore combination strategies to enhance patient response to ICIs.
Main Methods:
- Literature review of immune checkpoint inhibitor therapy.
- Analysis of biomarkers for patient stratification.
- Discussion of combination therapies with chemotherapy or radiotherapy.
Main Results:
- Immune evasion is a key cancer mechanism.
- ICI therapy shows variable patient response rates.
- Biomarker identification is essential for personalized treatment.
Conclusions:
- Predictive biomarkers are critical for optimizing immune checkpoint inhibitor therapy.
- Combination therapies may improve patient outcomes.
- Further research is needed to overcome limitations in current biomarker strategies.

