Abstract B028: Multimodal approach to characterization of metabolism and immune modulation with insights from spatial metabolomics and transcriptomics
Authors: Rahiman Chelsea L. , Ribas Roberto , Vij Manan , An Julia , McCann Patrick J. , Cham Jason , Liu Chang , Shah Parin , Martin Rosa , Chen Ariel , Cheng Simon , Obradovic Aleksandar Z. , Sun Ramon C. , Spina Catherine S. 
Published: January 2025

Abstract
Background: Spatial integration of metabolic pathways with single cell-level transcriptomic data in human tumor and normal tissue may elucidate mechanisms supporting tumorigenesis for therapeutic targeting. The suppressive adenosine signaling pathway is an emerging potential target for combination with radiotherapy. This study aims to create an in situ map of the pathway in non-small cell lung cancer (NSCLC) tumor and adjacent normal tissue. We seek to define how distinct cellular compartments cooperate and contribute to adenosine signaling within the tumor microenvironment (TME). Methods: Using Matrix-Assisted Laser Desorption/Ionization mass spectrometry imaging, we examined the spatial distribution of metabolites in paired human NSCLC compared to normal tissue from the same patient (n=15). In situ metabolite quantification and pathway enrichment analysis were performed. Second, we performed single nuclear RNA-sequencing (snRNA-seq) on NSCLC patient samples (n=4) to characterize the transcriptomic landscape of the tumors, including quantification of key members of the adenosine signaling pathway: ADORA2A (A2AR), ADORA2B (A2BR), ENTPD1 (CD39), NT5E (CD73), and ENPP1. Leveraging the average gene expression per cell subtype and pathologist-annotated H&E-stained tissue sections, we are integrating transcriptomic data with the spatial metabolomics to generate an in situ pathway map. Results: In NSCLC tissue, UMP, AMP, and ADP levels were significantly higher in tumor compared to normal tissue (p&lt;0.0001), with mean percentage increases of 79%, 89%, and 73%, respectively. Metabolites downstream of adenosine, adenine and inosine, showed no significant differences (p&gt;0.05). Single nuclear RNA-seq analyses revealed expression of the adenosine 2B receptor, ADORA2B, was highest in fibroblasts, lower in tumor, and absent in the immune compartment. ENTPD1 was expressed by all immune cells and tumor. NT5E was absent in T cells and ENPP1 was absent in macrophages, but expressed in all other immune compartments and tumor. Integration of snRNA-seq data with spatial metabolomics is underway to correlate metabolite abundance and gene expression within distinct cellular compartments to define cell type-specific contribution to adenosine signaling. Conclusion: Our study offers a multimodal approach to spatially resolve metabolic and transcriptomic data in situ relying on frozen NSCLC and normal lung tissue. This has significant translational implications, enabling analysis of biospecimens from multi-institutional clinical trials that precludes processing fresh tissue for single-cell analyses. Herein, we are able to localize key metabolites in untreated tumor and normal tissue and quantify the expression of pathway members at the cellular level. Through spatial integration of these data, we aim to decipher the relationship between distinct cell types within the TME and their contribution to adenosine-driven suppressive changes, then extend to radiotherapy-treated tumors.
Citation Format: Chelsea L. Rahiman, Roberto Ribas, Manan Vij, Julia An, Patrick J. McCann, Jason Cham, Chang Liu, Parin Shah, Rosa Martin, Ariel Chen, Simon Cheng, Aleksandar Z. Obradovic, Ramon C. Sun, Catherine S. Spina. {Abstract title} [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Targeted Therapies in Combination with Radiotherapy; 2025 Jan 26-29; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(2_Suppl):Abstract nr B028.