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Abstract 4703: Applying spatial omics and computational integrative analyses to study drug responses and cancer immune cell interactions

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Cancer responses to drug treatment are highly heterogeneous. We postulate that spatial determinants in the tumour play a critical role in cancer therapy outcomes. Here, we will present two spatial… Click to show full abstract

Cancer responses to drug treatment are highly heterogeneous. We postulate that spatial determinants in the tumour play a critical role in cancer therapy outcomes. Here, we will present two spatial transcriptomics studies on spatial responses to immunotherapy and chemotherapy. Immune checkpoint inhibitors (ICI) are used to treat recurrent metastatic oropharyngeal squamous cell carcinomas (OPSCC). Unfortunately, less than 30% of patients benefit from this therapy. Thus, we performed spatial transcriptomics (ST) and in-situ multiprotein detection (PhenoCycler-Fusion) on tissue isolated from a patient diagnosed with metastatic OPSCC. The patient’s primary oral tumour responded to chemo-radio therapy, followed by nivolumab ICI. However, new soft pallet OPSCCs resurged. Subsequent pembrolizumab combined with lenvatinib (VEGFR inhibitor) treatment had an initial effect, butnew recurrent oral tumours re-emerged suggesting drug resistance. Using ST, we observed high expression of drug resistance genes such as SNAI2, SOX4 and NDRG1 consistent with the disease aggressive behaviour. Although, PD-1/PD-L1 expression was not observed, we identified 13 over-expressed druggable targets (i.e., EGFR, TF, VEGF) and >10 experimental targets. To rank each drug’s potential success, we measured the co-expression of each target ligand-receptor pair (L/R), reducing the candidates to 4 pathways (TF/TFRC> VEGFA/NRP1> PGF/NRP1> TGFB1/VASN>VEGFA/GPC1). Furthermore, TF/TFRC and VEGFA/NRP1 expected downstream genes were differentially over-expressed where positive LR signal was detected. Similarly, we used ST to define the cellular diversity within a sonic hedgehog (SHH) patient-derived model of Medulloblastoma (MB) and identified how cells specific to a transcriptional state or spatial location are pivotal in responses to treatment with the CDK4/6 inhibitor, Palbociclib. We distinguished neoplastic and non-neoplastic cells within tumours and from the surrounding cerebellar tissue, further refining pathological annotation. We identified a regional response to Palbociclib, with reduced proliferation and induced neuronal differentiation in both treated tumours. Additionally, we resolved at cellular resolution a distinct tumour “interface” where the tumour cells contacted neighbouring mouse brain tissue, consisting of abundant astrocytes and microglia, and continued to proliferate despite Palbociclib treatment. Our data highlight the power of a spatial multi-omics approach to characterise the response of a tumour to targeted therapy and provide further insights into the molecular and cellular basis underlying the response and resistance to cancer therapies. Citation Format: Xiao Tan, Andrew Causer, Tuan Quang Anh Vo, Ning Ma, Bassem Ben Cheikh, Laura Genovesi, Jazmina Gonzalez-Cruz, Quan Nguyen, Oliver Braubach. Applying spatial omics and computational integrative analyses to study drug responses and cancer immune cell interactions. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4703.

Keywords: cell; omics computational; spatial omics; drug; applying spatial; cancer

Journal Title: Cancer Research
Year Published: 2023

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