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Updated: Nov 6, 2025
Multiplexed Immunofluorescence Analysis and Quantification of Intratumoral PD-1+ Tim-3+ CD8+ T Cells
Published on: February 8, 2018
[Predictive diagnostics for checkpoint inhibitors]
Hans-Ulrich Schildhaus1, Wilko Weichert2
1Institut für Pathologie, Universitätsklinikum Essen, Essen, Deutschland.
Abstract:
Checkpoint inhibitors have revolutionized oncological treatment in many cancers and added a new immuno-oncological treatment pillar to the medicinal arsenal of conventional and molecularly targeted therapies. In monotherapy and in combination therapies, however, not all patients respond equally well, even in generally responsive tumor entities. Therefore, since the introduction of these therapies, a major focus has been the research on and implementation of predictive markers for patient selection. The first established biomarker, the expression of the target molecule PD-L1, has found its way into routine diagnostics in a large number of unfortunately very divergent diagnostic constellations in multiple entities. In addition, some molecular predictors, including the measurement of microsatellite instability and tumor mutational burden, have also been suggested and in some cases are already implemented into routine diagnostics. Additional molecular parameters have been proposed but most of them have not yet found their way into routine patient care. This review article discusses the current status and recent developments in the field of diagnostic response predictors in the context of an immune checkpoint blockade.
Insights
Checkpoint inhibitors are revolutionizing cancer treatment, but patient response varies. Research focuses on predictive biomarkers like PD-L1, microsatellite instability, and tumor mutational burden to guide immune checkpoint blockade therapy selection.
Area of Science:
- Oncology
- Immunology
- Medical Diagnostics
Background:
- Immune checkpoint inhibitors represent a significant advancement in cancer therapy.
- However, variable patient responses necessitate the identification of predictive biomarkers.
- Current diagnostic approaches for selecting patients for these therapies are diverse and evolving.
Purpose of the Study:
- To review the current landscape of diagnostic response predictors for immune checkpoint blockade.
- To discuss recent developments in identifying biomarkers for patient selection.
- To highlight the challenges and future directions in this field.
Main Methods:
- Literature review of current research on predictive markers for immune checkpoint inhibitors.
- Analysis of established and emerging biomarkers such as PD-L1, microsatellite instability, and tumor mutational burden.
- Discussion of their implementation in routine clinical diagnostics.
Main Results:
- Programmed Death-Ligand 1 (PD-L1) expression is an established biomarker but used in varied diagnostic contexts.
- Microsatellite instability (MSI) and tumor mutational burden (TMB) are also utilized, with some implemented in diagnostics.
- Numerous other molecular parameters have been proposed but are not yet in routine use.
Conclusions:
- Predictive markers are crucial for optimizing immune checkpoint blockade therapy.
- While PD-L1, MSI, and TMB are key biomarkers, further research is needed for broader application.
- The development and validation of novel biomarkers will enhance patient stratification and treatment efficacy.
