The predictive and prognostic role of single nucleotide gene variants of PD-1 and PD-L1 in patients with advanced melanoma treated with PD-1 inhibitors.

PD-1 PD-L1 SNV melanoma single nucleotide gene variant

Journal

Immuno-oncology technology
ISSN: 2590-0188
Titre abrégé: Immunooncol Technol
Pays: England
ID NLM: 9918281581106676

Informations de publication

Date de publication:
Dec 2023
Historique:
medline: 9 1 2024
pubmed: 9 1 2024
entrez: 9 1 2024
Statut: epublish

Résumé

Despite having revolutionized the treatment paradigm for advanced melanoma, not all patients benefit from immune checkpoint inhibitor therapy. To date, there are no predictive biomarkers for response or the occurrence of immune-related adverse events (irAEs) to programmed cell death protein 1 (PD-1) inhibitors. Our aim was to investigate the predictive and prognostic role of single nucleotide variants (SNVs) of genes involved in the PD-1 axis. We analysed, in metastatic melanoma patients treated with nivolumab or pembrolizumab, five PD-1 SNVs, namely PD1.3 G>A (rs11568821), PD1.5 C>T (rs2227981), PD1.6 G>A (rs10204525), PD1.7 T>C(rs7421861), PD1.10 C>G (rs5582977) and three programmed death-ligand 1 (PD-L1) SNVs: +8293 C>A (rs2890658), PD-L1 C>T (rs2297136) and PD-L1 G>C (rs4143815). Association of SNV genotypic frequencies with best overall response to PD-1 inhibitors and development of irAEs were estimated through a modified Poisson regression. A Cox regression modelling approach was applied to evaluate the SNV association with OS. A total of 125 patients with advanced melanoma were included in the analysis. A reduction in irAEs risk was observed in patients carrying the PD-L1 +8293 C/A genotype compared with those carrying the C/C genotype (risk ratio = 0.45; 95% CL 0.22-0.93; Our study showed that PD-1.5 and PD-L1 +8293 SNVs may play a role as a predictive biomarker of development of irAEs to PD-1 inhibitors. PD1.7 SNV may also be associated with a reduction of the risk of death, although further translational research is needed to confirm these results.

Sections du résumé

Background UNASSIGNED
Despite having revolutionized the treatment paradigm for advanced melanoma, not all patients benefit from immune checkpoint inhibitor therapy. To date, there are no predictive biomarkers for response or the occurrence of immune-related adverse events (irAEs) to programmed cell death protein 1 (PD-1) inhibitors. Our aim was to investigate the predictive and prognostic role of single nucleotide variants (SNVs) of genes involved in the PD-1 axis.
Methods UNASSIGNED
We analysed, in metastatic melanoma patients treated with nivolumab or pembrolizumab, five PD-1 SNVs, namely PD1.3 G>A (rs11568821), PD1.5 C>T (rs2227981), PD1.6 G>A (rs10204525), PD1.7 T>C(rs7421861), PD1.10 C>G (rs5582977) and three programmed death-ligand 1 (PD-L1) SNVs: +8293 C>A (rs2890658), PD-L1 C>T (rs2297136) and PD-L1 G>C (rs4143815). Association of SNV genotypic frequencies with best overall response to PD-1 inhibitors and development of irAEs were estimated through a modified Poisson regression. A Cox regression modelling approach was applied to evaluate the SNV association with OS.
Results UNASSIGNED
A total of 125 patients with advanced melanoma were included in the analysis. A reduction in irAEs risk was observed in patients carrying the PD-L1 +8293 C/A genotype compared with those carrying the C/C genotype (risk ratio = 0.45; 95% CL 0.22-0.93;
Conclusions UNASSIGNED
Our study showed that PD-1.5 and PD-L1 +8293 SNVs may play a role as a predictive biomarker of development of irAEs to PD-1 inhibitors. PD1.7 SNV may also be associated with a reduction of the risk of death, although further translational research is needed to confirm these results.

Identifiants

pubmed: 38192613
doi: 10.1016/j.iotech.2023.100408
pii: S2590-0188(23)00036-9
pmc: PMC10772261
doi:

Types de publication

Journal Article

Langues

eng

Pagination

100408

Informations de copyright

© 2023 The Author(s).

Auteurs

A Boutros (A)

Skin Cancer Unit, Medical Oncology 2, IRCCS Ospedale Policlinico San Martino, Genoa.
Department of Internal Medicine and Medical Specialties (DiMI), School of Medicine, University of Genova, Genoa.

R Carosio (R)

Tumor Epigenetics Unit, IRCCS Ospedale Policlinico San Martino, Genoa.

D Campanella (D)

Clinical Epidemiology Unit, IRCCS Ospedale Policlinico San Martino, Genoa.

F Spagnolo (F)

Skin Cancer Unit, Medical Oncology 2, IRCCS Ospedale Policlinico San Martino, Genoa.
Department of Surgical Sciences and Integrated Diagnostics (DISC), Plastic Surgery Division, University of Genova, Genoa.

B Banelli (B)

Tumor Epigenetics Unit, IRCCS Ospedale Policlinico San Martino, Genoa.

A Morabito (A)

Tumor Epigenetics Unit, IRCCS Ospedale Policlinico San Martino, Genoa.

M P Pistillo (MP)

Tumor Epigenetics Unit, IRCCS Ospedale Policlinico San Martino, Genoa.

E Croce (E)

Skin Cancer Unit, Medical Oncology 2, IRCCS Ospedale Policlinico San Martino, Genoa.
Department of Internal Medicine and Medical Specialties (DiMI), School of Medicine, University of Genova, Genoa.

F Cecchi (F)

Skin Cancer Unit, Medical Oncology 2, IRCCS Ospedale Policlinico San Martino, Genoa.

P Pronzato (P)

Skin Cancer Unit, Medical Oncology 2, IRCCS Ospedale Policlinico San Martino, Genoa.

P Queirolo (P)

Division of Melanoma Sarcoma and Rare Tumors, IRCCS European Institute of Oncology, Milan, Italy.

E Raposio (E)

Department of Surgical Sciences and Integrated Diagnostics (DISC), Plastic Surgery Division, University of Genova, Genoa.

V Fontana (V)

Clinical Epidemiology Unit, IRCCS Ospedale Policlinico San Martino, Genoa.

E T Tanda (ET)

Skin Cancer Unit, Medical Oncology 2, IRCCS Ospedale Policlinico San Martino, Genoa.

Classifications MeSH