Germinal Immunogenetics predict treatment outcome for PD-1/PD-L1 checkpoint inhibitors

Autor: Jocelyn Gal, Patrick Brest, Gérard Milano, Emmanuel Chamorey, Frederic Peyrade, Sadal Refae, Delphine Borchiellini, Josiane Otto, Nathalie Ebran, Esma Saada-Bouzid
Přispěvatelé: Oncopharmacology Unit [Nice], Centre de Lutte contre le Cancer Antoine Lacassagne [Nice] (UNICANCER/CAL), UNICANCER-Université Côte d'Azur (UCA)-UNICANCER-Université Côte d'Azur (UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA), UNICANCER-Université Côte d'Azur (UCA), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA), Laboratory of Solid Tumors Genetics, Nice University Hospital, Infection bactérienne, inflammation, et carcinogenèse digestive, Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-IFR50-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Côte d'Azur (UCA), Institut de Recherche sur le Cancer et le Vieillissement (IRCAN), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Institut National de la Santé et de la Recherche Médicale (INSERM), Centre National de la Recherche Scientifique (CNRS), Département de pharmacogénomique, UNICANCER-Université Côte d'Azur (UCA)-UNICANCER-Université Côte d'Azur (UCA)
Jazyk: angličtina
Rok vydání: 2020
Předmět:
0301 basic medicine
Oncology
Adult
Male
medicine.medical_specialty
In silico
[SDV]Life Sciences [q-bio]
Programmed Cell Death 1 Receptor
Single-nucleotide polymorphism
[SDV.CAN]Life Sciences [q-bio]/Cancer
Immunogenetics
B7-H1 Antigen
03 medical and health sciences
0302 clinical medicine
Antineoplastic Agents
Immunological
Internal medicine
PD-L1
Neoplasms
Gene expression
medicine
Biomarkers
Tumor
Humans
Pharmacology (medical)
Adverse effect
Gene
Germ-Line Mutation
ComputingMilieux_MISCELLANEOUS
Aged
Retrospective Studies
Pharmacology
Aged
80 and over
biology
business.industry
Middle Aged
Prognosis
3. Good health
Pharmacogenomic Testing
Survival Rate
030104 developmental biology
030220 oncology & carcinogenesis
Expression quantitative trait loci
biology.protein
Female
Immunotherapy
business
Follow-Up Studies
Zdroj: Investigational New Drugs
Investigational New Drugs, Springer Verlag, 2020, 38 (1), pp.160-171. ⟨10.1007/s10637-019-00845-w⟩
ISSN: 0167-6997
1573-0646
DOI: 10.1007/s10637-019-00845-w⟩
Popis: Background Checkpoint inhibitors bring marked benefits but only in a minority of patients and may also be associated with severe adverse events. Treatment outcome still cannot be faithfully predicted. The following study hypothesized that host genetics could be applied as predictive biomarkers for checkpoint inhibitor response and immune-related adverse events. We conducted a study based on germinal polymorphisms from genes coding for proteins involved in immune regulation. Methods Germinal DNA was obtained from advanced cancer patients treated with anti-PD-1/PD-L1 checkpoint inhibitors. DNA was genotyped using a custom panel of 166 single nucleotide polymorphisms covering 86 preselected immunogenetic-related genes. Computational analysis using a GTEX portal was made to determine potential expression Quantitative Trait Loci in tissues. Results Ninety-four consecutive patients were included. Objective response rate (complete or partial response) was significantly correlated to tumor microenvironment-related SNPs concerning CCL2, NOS3, IL1RN, IL12B, CXCR3 and IL6R genes. Toxicity were linked to target-related gene SNPs including UNG, IFNW1, CTLA4, PD-L1 and IFNL4 genes. The Area Under the ROC curve (AUC) was 0.81 (95% CI: 0.72–0.9) for response and 0.89 (95% CI: 0.76–1.00) for toxicity. In silico functionality exploring pointed rs4845618 (IL6R), rs10964859 (IFNW1) and rs3087243 (CTLA4) as potentially impacting gene expression. Conclusion These results strongly support a role for distinct immunogenetic-related gene SNPs able to predict efficacy and safety of anti-PD1/PD-L1 therapies. The results highlight the existence of patient-specific, germinal biomarkers able predict response to checkpoint inhibitor efficacy and, possibly, to predict treatment-related adverse events.
Databáze: OpenAIRE
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