Abstract 6604: Spatial transcriptomics delineates tumor heterogeneity in NACT triple-negative breast cancer
Authors: Wall Isobelle , Quist Jelmar , Pinder Sarah ,   KCL Cancer Biobank, Irshad Sheeba , Gillet Cheryl , Seewaldt Victoria , Mukund Kavitha , Frankhouser David , Subramaniam Shankar , Parsons Maddy , Grigoriadis Anita 
Published: March 2024

Abstract
BACKGROUND: Triple-Negative Breast Cancer (TNBC) is a highly aggressive subtype of breast cancer and only ~40% of TNBC patients achieve a pathological complete response (pCR) following neoadjuvant chemotherapy (NACT). Since molecular heterogeneity of TNBC may contribute to variable responses to NACT, we aimed to deconvolute TNBC’s histological and spatial transcriptomics (ST) patterns.
METHODS: In total, 90 pre-treatment biopsies were collected from NACT-treated TNBC patients from archival samples and the ongoing FORCE (NCT03238144) clinical trial at Guy’s Hospital, London, UK. Of these, 38 achieved pCR (Responder), 46 had residual disease (Non-Responder) whilst 6 are currently undergoing NACT; 46 post-treatment surgical resections were collected from Non-Responders.Each sample was H&E stained, imaged, and annotated by a pathologist. A 6-digit classifier was designed to capture the histology of each region of interest (ROI), characterizing the tumour region, epithelial type and immune cell localization, population, distribution, and abundance.H&Es were used to guide ST profiling of serial sections which was performed on the GeoMx Digital Spatial Profiler. Tissues were stained with fluorescent antibodies against PanCK and CD45 to visualize the tissue, select ROIs and illuminate spatially resolved tumor and immune-enriched compartments, defined as PanCK+/CD45- and PanCK-/CD45+, respectively.Data analysis was performed in R 4.3.1 using the limma, dplyr, EdgeR, GeoMx Tools, GeoMx Workflows, RUV4, Spatial Experiment, SpatialDecon and GSVA packages, facilitating quality control, batch correction, differential and topographical gene expression, immune cell deconvolution and gene set enrichment analysis (GSEA), respectively.
RESULTS: To date, we have performed ST profiling of 120 TNBC samples from 82 patients (46 Non-Responders; 36 Responders), totaling 3917 tumor or immune-cell enriched regions. Preliminary analyses revealed KEGG pathways involved in tissue adhesion are upregulated in tumor compartments of Non-Responders compared to Responders, whilst those involved in genomic integrity are suppressed. Unsupervised clustering of PanCK+CD45- regions in Non-Responders identified tumor clusters present in both pre- and post-NACT samples, suggesting potential chemo-resistant properties. Moreover, immune cell deconvolution of the PanCK-/CD45+ regions revealed spatially distinct patters of immune cell composition mapped to histological annotations identified by our ROI classifier.
CONCLUSION: (S)Large scale ST of TNBC before and after NACT reveals novel patterns associated with response to treatment. We have designed a novel ROI classifier to spatially resolved transcriptomes of histological features, as such provide an in-depth characterization of the histo-genomics of TNBC.
Citation Format: Isobelle Wall, Jelmar Quist, Sarah Pinder, KCL Cancer Biobank, Sheeba Irshad, Cheryl Gillet, Victoria Seewaldt, Kavitha Mukund, David Frankhouser, Shankar Subramaniam, Maddy Parsons, Anita Grigoriadis. Spatial transcriptomics delineates tumor heterogeneity in NACT triple-negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6604.