134P - Unraveling functionally distinct metabolic programs to predict immunotherapy response in non-small cell lung cancer (NSCLC)

Background

NSCLC accounts for most lung cancers and has a poor 5-year survival. With an increasing number of systemic and targeted therapies, including immune checkpoint inhibitors (ICIs), it is becoming more important to develop predictive biomarkers to identify patient response to ICIs. Additionally, targeting cancer and stromal cell metabolism could be the key to overcoming immune checkpoint blockade (ICB) resistance.

Methods

Retrospective cohort of 28 nivolumab-treated NSCLC tissue cores (n = 28; 10/18 responders/non-responders) was profiled using a custom 44-plex immunofluorescence panel (incl. functional/metabolic markers) with the Phenocycler Fusion platform (Akoya Biosciences). We applied an unbiased spatial analytics and explainable AI pipeline, SpaceIQ, to capture emergent metabolic programs in spatial arrangements of unbiased cell types (microdomains, μD1 and μD2) predictive of ICI response. Predictive spatial networks implicated in known metabolic pathways are currently being verified by spatial transcriptomics.

Results

Non-responders had higher proportions of CD4 T cells with upregulated TCA cycle/downregulated glycolysis and pentose phosphate pathway (PPP). μD1 and μD2 were spatially anchored around tumor cells with upregulated TCA cycle and oxidative phosphorylation (OXPHOS) with additional NK cells and dendritic cells along with upregulated PPP in μD2. Each microdomain had distinct metabolic programs relating to catabolic (energy utilization) and anabolic (cellular biogenesis) pathways. μD1/μD2 were prognostic for overall survival (mean AUC = 0.86/0.82, +/-0.11), with median sensitivity (80%/80%) and specificity (66%/88%) for nivolumab-treated response.

Conclusions

The SpaceIQ platform infers distinct metabolic programs revealing spatially mediated roles for anabolic/catabolic pathways to predict immunotherapy response in NSCLC. Unbiased discrete cell typing allowed for functional characterization of tumor/stromal cells. Distinct spatial organization of metabolic activity encompassing glycolysis, TCA cycle, PPP, and OXPHOS may play a significant role in affecting clinical outcomes induced by ICI therapy.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

PredxBio, Inc.

Funding

PredxBio, Inc.

Disclosure

R. Yan, S. Quinn, B. Falkenstein, S.C. Chennubhotla, F. Pullara: Financial Interests, Personal, Full or part-time Employment: PredxBio. All other authors have declared no conflicts of interest.