Abstract 155P
Background
Dynamic peripheral blood biomarkers for response to immune checkpoint blockade (ICB) are lacking. Lymphocyte count stability post-initiation of treatment (the ‘Lymphocyte Stability Index’, LSI) is significantly associated with progression-free and overall survival (OS) in metastatic melanoma (MM), as well as NSCLC and renal cell cancer. Notably, a single nucleotide polymorphism at rs16906115 (intronic to IL7) is associated with increased LSI, indicating non-tumour effects of systemic immunity. We sought to test the effect of treatment on LSI in MM and explore underlying molecular mechanisms.
Methods
Using treatment, blood count and survival data from 318 patients, we investigated the association between LSI and OS in MM, subdivided by treatment received and development of toxicity. We performed bulk (n=250) and single cell (n=18) RNA sequencing on peripheral blood from a cohort of patients with MM treated with ICB, correlating molecular findings with LSI.
Results
LSI was significantly associated with improved OS regardless of whether single agent PD-1, single-agent CTLA-4 or combination PD-1 and CTLA-4 blockade was received (HR 0.41, 0.23 and 0.34, respectively. All p<0.001), or whether toxicity developed. There was no difference in OS between patients with stable LSI, regardless of treatment received. CD8+ T cells from patients with high LSI had a unique gene expression profile, with a positive correlation between LSI and expression of gene sets relevant to anti-tumour immune responses. Conversely, patients with low LSI showed activation of Type I Interferon gene expression. Analysis of cellular dynamics within single cell data demonstrated unique innate-adaptive interactions via specific receptor-ligand pairs, suggesting potentiation of T cell responses by monocytic populations.
Conclusions
The LSI is a simple dynamic peripheral biomarker for survival following ICB treatment that reflects innate, primarily non-tumour factors. Activation of Type I interferons correlates with lymphocyte instability, providing a novel avenue for therapeutic intervention. Further, LSI may permit effective on-treatment stratification of immunotherapy.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
The Wellcome Trust, CRIS Cancer Foundation, NIHR, Cancer Research UK.
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