Predictive biomarkers of response to immune checkpoint inhibitors
Objective: The present paper provides a literature review aimed at identifying the tumor-dependent factors capable of influencing a subject’s response to immune checkpoint inhibitors, with a special emphasis on those that may act as predictive biomarkers. Method: A search was performed of the t...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2020-07-01
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| Series: | Farmacia Hospitalaria |
| Subjects: | |
| Online Access: | http://www.aulamedica.es/fh/pdf/11328.pdf |
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| Summary: | Objective: The present paper provides a literature review aimed at identifying the tumor-dependent factors capable of influencing a subject’s response to immune checkpoint inhibitors, with a special emphasis on those that may act as predictive biomarkers.
Method: A search was performed of the terms biomarkers, PD-1, PD- L1, CTLA-4, and checkpoint inhibitors in the title and the abstract of the records in the PubMed database. Articles including relevant information on the tumor-dependent factors capable of influencing a subject’s response of immune checkpoint inhibitors were selected. Priority was given to studies in humans (clinical trials and reviews) published between January 2015 and June 2019, in English and Spanish.
Results: The literature review exposed the complex relationship that xists between the immune system and tumors. It also revealed that the factors capable of influencing a subject’s response to immune checkpoint inhibitors are multiple, heterogeneous and ill understood, which makes it difficult to obtain simple and/or universal predictive biomarkers.
Conclusions: The only biomarkers currently used in clinical practice include the expression of the programmed cell death ligand-1 and microsatellite instability/ deficient DNA mismatch repair, but their usefulness is limited. Tumor mutational burden and gene signatures associated to IFN-γ could become useful biomarkers once determination techniques and cutoff points are systematized. |
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| ISSN: | 1130-6343 2171-8695 |