Abstract 544P
Background
Immune checkpoint inhibitors (ICI) have revolutionized the treatment landscape. While programmed death-ligand 1 expression serves as a predictive biomarker, uncovering extra ICI response markers is pivotal. Immune cell transcriptomic analysis is a promising path for identifying such markers. Our study aims to find an ICI response predictor in lung adenocarcinoma patients' peripheral blood mononuclear cells (PBMC) through single-cell RNA sequencing (scRNA-seq).
Methods
We prospectively collected PBMC from 38 patients with stage IV lung adenocarcinoma, both before (0-7 days) and after (1-3 weeks) treatment with anti-PD(L)-1 therapy. Among the patients, 17 achieved a partial response, 4 had stable disease, and 17 experienced disease progression. Patients with a partial response or stable disease were classified as responders, while those with disease progression were classified as non-responders. We performed scRNA-seq on PBMC to unravel the molecular landscape.
Results
Subgroup analysis of NKT cells in pre-treated state revealed upregulated RNA expression related to activator protein 1 (AP-1) signals in NK cell subtypes (CD56lowCD16int NK cell, CCL4 NK cell, PTGDS NK cell) in responders. CD56 high CD16 low expressing NK cells were increased in responder after treatment with ICI. Additionally, we found an increased proportion of monocytes with high CXCL10 expression in the responder group. Signals associated with chemokine ligands and interferon-inducible proteins were upregulated in monocyte subtypes prior to ICI treatment.
Conclusions
Our scRNA-seq analysis of PBMC from lung adenocarcinoma patients provided valuable insights into the immune landscape. Upregulation of AP-1 signals in NK cells and chemokine ligand expression, as well as interferon-inducible signals in monocytes, were observed in responders prior to ICI treatment. Moreover, the expansion of monocytes with high CXCL10 expression in the responder group suggests the potential involvement of these circulating immune cell populations in the anti-tumor immune response. These findings contribute to our understanding of ICI response and offer promise for the future development of predictive biomarkers.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
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