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Sigouros, M.

Publications and source records attributed to Sigouros, M..

2 recordsLinked to original sources

The Interplay between Mutagenesis and Extrachromosomal DNA Shapes Urothelial Cancer Evolution

Advanced urothelial cancer is a frequently lethal disease characterized by marked genetic heterogeneity. In this study, we investigate the evolution of the genomic signatures caused by endogenous and external mutagenic stimuli and their interplay with complex structural variants. We superimposed mutational signatures and phylogenetic analyses of matched serial tumors from patients with urothelial cancer to define the evolutionary patterns of these processes. We show that APOBEC3-induced mutations are clonal and early, whereas mutational bursts comprising hundreds of late subclonal mutations are induced by chemotherapy. Using a novel genome graph computational paradigm, we observed frequent circular high copy-number amplicons characteristic of extrachromosomal DNA (ecDNA) involving double-minutes, breakage-fusion-bridge, and tyfonas events. We characterized the distinct temporal patterns of APOBEC3 mutations and chemotherapy-induced mutations within ecDNA, gaining new insights into the timing of these events relative to ecDNA biogenesis. Finally, we discovered that most CCND1 amplifications in urothelial cancer arise within circular ecDNA amplicons. These CCND1 ecDNA amplification events persisted and increased in complexity incorporating additional DNA segments potentially contributing selective fitness advantage to the evolution of treatment resistance. Our findings define fundamental mechanisms driving urothelial cancer evolution and have therapeutic implications for treating this disease.

genomics↗

Weakly-Supervised Tumor Purity Prediction FromFrozen H&E Stained Slides

Estimating tumor purity is especially important in the age of precision medicine. Purity estimates have been shown to be critical for correction of tumor sequencing results, and higher purity samples allow for more accurate interpretations from next-generation sequencing results. In addition, tumor purity has been shown to be correlated with survival outcomes for several diseases. Molecular-based purity estimates using computational approaches require sequencing of tumors, which is both time-consuming and expensive. Here we propose an approach, weakly-supervised purity (wsPurity), which can accurately quantify tumor purity within a slide, using multiple and different types of cancer. This approach allows for a flexible analysis of tumors from whole slide imaging (WSI) of histology hematoxylin and eosin (H&E) slides. Our model predicts tumor type with high accuracy (greater than 80% on an independent test cohort), and tumor purity at a higher accuracy compared to a comparable fully-supervised approach (0.1335 MAE on an independent test cohort). In addition to tumor purity prediction, our approach can identify high resolution tumor regions within a slide, to enrich tumor cell selection for downstream analyses. This model could also be used in a clinical setting, to stratify tumors into high and low tumor purity, using different thresholds, in a cancer-dependent manner, depending on what purity levels correlate with worse disease outcomes. In addition, this approach could be used in clinical practice to select the best tissue block for sequencing. Overall, this approach can be used in several different ways to analyze WSIs of tumor H&E sections.

bioinformatics↗