(P 200) DISSECTING INTRATUMORAL HETEROGENEITY IN GIST USING SPATIAL TRANSCRIPTOMICS

Objective: Gastrointestinal stromal tumors (GISTs) are characterized by driver mutations, primarily in the KIT and PDGFRA genes, leading to the abnormal activation of these receptor tyrosine kinases. Approximately 40% of high-risk patients experience relapse after adjuvant imatinib therapy, emphasizing the importance of better understanding tumor biology and heterogeneity, and their influence on prognosis and resistance.

Methods: We have applied Visium 10x Genomics spatial transcriptomics technology on formalin-fixed paraffin-embedded (FFPE) samples from seven treatment-naive GISTs. Our approach integrates deconvolution analysis to delineate distinct spatial transcriptomic niches, to identify specific cell types within the tumor and its microenvironment. Preliminary analyses focused on characterizing transcriptomic profiles within the tumor area and across patients, supplemented by inferred DNA copy number changes from gene expression data.

Results: The inclusion of normal tissue was essential for enhancing our analyses and defining cell types within the tumor microenvironments. Our findings revealed significant intratumoral heterogeneity, with distinct spatial domains displaying unique transcriptional landscapes. Despite the uniformity of KIT mutations among patients, we observed substantial variability in gene expression profiles, suggesting potential differences in the activation of downstream pathways. Additionally, areas of localized chromosome copy number changes were linked to signatures associated with aggressive disease behavior.

Conclusion: This study highlights the complex transcriptional and genomic heterogeneity in GISTs, which may have significant implications for patient stratification and the development of personalized therapeutic strategies. Future work will integrate single-cell RNA sequencing to further dissect this heterogeneity and correlate it with clinical outcomes. A deeper understanding of the molecular mechanisms driving heterogeneity in GISTs will be crucial for enhancing targeted therapies and reducing the risk of relapse in high-risk patients.