Pd09-07 Spatial Transcriptomic Signature From Mutated Benign Ancestral Clone Predicts High Risk Prostate Cancer

You have accessJournal of UrologyProstate Cancer: Basic Research & Pathophysiology II (PD09)1 May 2024PD09-07 SPATIAL TRANSCRIPTOMIC SIGNATURE FROM MUTATED BENIGN ANCESTRAL CLONE PREDICTS HIGH RISK PROSTATE CANCER Thineskrishna Anbarasan, Wencheng Yin, Sandy Figiel, Ian Mills, and Alastair Lamb Thineskrishna AnbarasanThineskrishna Anbarasan , Wencheng YinWencheng Yin , Sandy FigielSandy Figiel , Ian MillsIan Mills , and Alastair LambAlastair Lamb View All Author Informationhttps://doi.org/10.1097/01.JU.0001008572.33286.63.07AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Prostate cancer (PCa) is a multifocal disease driven by heterogenous spatial and temporal branching evolution of tumour clones (Erickson, Nature 2022). Spatial transcriptomic analysis has revealed clonally distributed copy number alterations even in histologically benign regions (Erickson, Eur Urol Oncol 2021). We aimed to evaluate if a genetic signature comprised within these genetically aberrant histologically benign regions, or "ancestral clones" may predict presence of high-risk disease. METHODS: Fresh-frozen, radical prostatectomy specimen was profiled using the 10x Genomics Visium Spatial Gene Expression platform. Via hierarchical clustering, spatial tumour clonal relations were inferred. Differentially expressed genes (DEGs) between tumour and histologically benign ancestral clones were identified. DEGs (|log2FC| >0.75) were input into a LASSO regression algorithm with normalised mRNA expression of normal adjacent tissue from the TCGA PCa database to train a genetic risk model to predict presence of high risk PCa (Gleason >8). We then validated the genetic risk score on an external cohort (Taylor 2010, GSE21032). RESULTS: A total of 683 DEGs were identified. These were enriched for organic acid metabolic pathways. Regression analysis on 57 normal adjacent tissue samples from TCGA PCa dataset was performed to develop a predictive model comprising of 3 genes (SLC22A3, CRIP2, LSAMP). External validation of the genetic risk score on matched histologically benign tissue from 131 patients (Figure 1C) with localised PCa, had good performance for prediction of high-risk disease (Gleason >8) (AUC 0.807; 95% CI 0.693-0.921). CONCLUSIONS: Our study demonstrates the predictive significance of spatially informed transcriptomic changes within histologically benign ancestral clones that give rise to clinically significant PCa. Our model has good performance for predicting high-risk disease from matched normal or low risk PCa tissue. This offers the translational possibility of predicting un-sampled high-risk disease from histologically benign biopsy cores. Download PPT Source of Funding: NIHR UK - Academic Clinical Fellowship Funding for Thineskrishna Anbarasan © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e181 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Thineskrishna Anbarasan More articles by this author Wencheng Yin More articles by this author Sandy Figiel More articles by this author Ian Mills More articles by this author Alastair Lamb More articles by this author Expand All Advertisement PDF downloadLoading ...