Abstract 5067: Concurrent spatial transcriptomics and metabolomics map differential effects of drug across brain cancer tissues

Abstract The spatial heterogeneity of tumors poses significant challenges for effective treatment, resulting in varied therapeutic responses across different regions of the same tumor. This challenge is especially pronounced in brain cancers, where uneven drug distribution—largely due to biological barriers like the blood-brain barrier—complicates treatment. Techniques that overlay drug distribution with transcriptional profiles would enable a comprehensive, unbiased investigation of drug effects. In this study, we present a spatial multiomics approach that integrates spatial metabolomics and spatial transcriptomics within the same tissue section of mouse brain samples treated with Palbociclib, a selective CDK4/6 inhibitor with potential for targeting various cancers, including breast cancer and medulloblastoma (MB). Our high-resolution (2-55 µm) concurrent multiomics maps reveal that the differential distribution of Palbociclib results in heterogeneous effects, promoting differentiation and reducing proliferation in specific tumor regions. Through this approach, we identified tissue regions exhibiting distinct transcriptional and metabolic signatures, including areas unaffected by drug treatment, which could contribute to recurrence. To support this analysis, we developed SpaMTP, a state-of-the-art software package providing a comprehensive pipeline for in-depth analysis of spatial metabolomics for integrating spatial multiomics data. This package bridges processing functionalities for metabolomic data from Cardinal with user-friendly cell-centric analyses implemented in Seurat. SpaMTP’s comprehensive analysis pipeline covers (1) automated mass-to-charge ratio (m/z) metabolite annotation, (2) a wide range of downstream statistical analyses including differential metabolite expression and metabolic pathway analysis, and (3) integrative spatial-omics analysis. For broad implementation and interoperability, SpaMTP includes various functions for data visualisation, data object conversion and data import/export. Overall, our work describes novel experimental and analytical methods to map drug distribution and its transcriptional impacts directly, offering critical insights into the heterogeneous effects of Palbociclib across brain tumor tissues. Citation Format: Tuan Vo, Cedric Cui, Andrew Causer, Xiao Tan, Eunju Kim, Zherui Xiong, Hani Vu, Mark Hodson, Tianyao Lu, Saskia Freytag, Jenny Fung, John Lee, Quan Nguyen. Concurrent spatial transcriptomics and metabolomics map differential effects of drug across brain cancer tissues [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5067.