Abstract 159P
Background
ICIs targeting PD-1 and its ligand 1 (PD-L1) revolutionized the management of many types of tumors. However, a portion of treated patients develops severe irAEs potentially causing prolonged sequelae. As a result, there is the need for biomarkers to identify which patients have a higher likelihood of developing irAEs.
Methods
We assessed the role of PD-1 SNPs as biomarkers for predicting the occurrence of irAEs in advanced cancer patients treated with ICIs. Selected PD-1 SNPs were genotyped by RT-PCR. To assess the mechanism underlying the predictive role of the identified PD-1 SNP, we employed peripheral blood mononuclear cells (PBMCs) isolated from two cancer patients, transfected with specific miRNAs and co-cultured with HaCat cells.
Results
Seventy-two patients including non-small cell lung cancer (49), renal cell carcinoma (9), head and neck squamous cell carcinoma (8) and melanoma (6) were treated with anti-PD-1/PD-L1 therapy. Grade 1-2 and grade 3-4 irAEs were reported in 45 (69.23%) and 6 (9.23%) of the treated patients, respectively. Among selected PD-1 SNPs, rs10204525 exhibited a significant association with grade 1-2 (P < 0.005) and grade 3-4 irAEs (P < 0.002). Indeed, patients carrying allele C reported a higher rate of irAEs than those carrying allele T. rs10204525 mapped on the 3'-UTR region of the PD-1 affecting the binding affinity of specific miRNAs. Specifically, miR-4717 strongly bound to rs10204525 in presence of allele C but not in presence of allele T. The differential binding of miR-4717 to rs10204525, in turn differentially modulated the expression of PD-1 on PMBCs both under basal conditions and following treatment with IFN-ɣ. Moreover, a decreased cell viability, an increased IFN-ɣ release and induction of apoptosis of HaCat cells when co-cultured with miR-4717-transfected PBMCsC/C were reported. In contrast, no significant difference when HaCat cells were co-cultured with PBMCsC/T was found.
Conclusions
Our findings have high clinical relevance since identify rs10204525 as an efficient biomarker for predicting the occurrence of irAEs in advanced cancer patients treated with ICIs.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
University of Salerno.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
173P - Unveiling a novel EpCAM-CD24+ circulating cells with unidentified origin associated with breast cancer distant metastasis
Presenter: Evgeniya Grigoryeva
Session: Poster session 08
174P - Prognostic value of the immune and metabolic profile in the response to neoadjuvant treatment with ICIs in triple-negative breast cancer patients (TNBC)
Presenter: Lucía Serrano García
Session: Poster session 08
175P - Utility of artificial intelligence (AI) in Ki67 scoring of a breast cancer (BC) patient population
Presenter: Xavier Pichon
Session: Poster session 08
176P - ERBB2 amplifications across sex, race, and cancer types
Presenter: Marc Machaalani
Session: Poster session 08
177P - HER2 testing in multiple solid tumors: Concordance between 3 scoring algorithms
Presenter: Wentao Yang
Session: Poster session 08
178P - PD-L1 expression in ER-low versus triple-negative (TN) advanced breast cancer (aBC), and according to phenotypic evolution from primary to recurrent disease
Presenter: Federica Miglietta
Session: Poster session 08
179P - Multimodal deep learning integrating MRI and molecular profiles for predicting outcomes in triple-negative breast cancer
Presenter: Seong Hwan Park
Session: Poster session 08
181P - Molecular characterization and immune microenvironment analysis of MSI-H patients with or without MMR gene mutations
Presenter: Mengxi Ge
Session: Poster session 08
182P - Multi-modal artificial intelligence outperforms image-based approaches for mutation prediction from H&E tissue images in colorectal cancer
Presenter: Marc Päpper
Session: Poster session 08