Background And Objective: Molecular classification of upper tract urothelial carcinoma (UTUC) can provide insight into divergent clinical outcomes and provide a biological rationale for clinical decision-making. As such, we performed multi-omic analysis of UTUC tumors to identify molecular features associated with disease recurrence and response to immune checkpoint blockade (ICB).
Methods: Targeted DNA and whole transcriptome RNA sequencing was performed on 100 UTUC tumors collected from patients undergoing nephroureterectomy.
Small cell carcinomas (SMC) of the lung are now molecularly classified based on the expression of transcriptional regulators (NEUROD1, ASCL1, POU2F3, and YAP1) and DLL3, which has emerged as an investigational therapeutic target. PLCG2 has been shown to identify a distinct subpopulation of lung SMC with stem cell-like and prometastasis features and poor prognosis. We analyzed the expression of these novel neuroendocrine markers and their association with traditional neuroendocrine markers and patient outcomes in a cohort of bladder neuroendocrine carcinoma (NEC) consisting of 103 SMC and 19 large cell NEC (LCNEC) assembled in tissue microarrays.
View Article and Find Full Text PDFBackground: Web-based digital slide viewers for pathology commonly use OpenSlide and OpenSeadragon (OSD) to access, visualize, and navigate whole-slide images (WSI). Their standard settings represent WSI as deep zoom images (DZI), a generic image pyramid structure that differs from the proprietary pyramid structure in the WSI files. The transformation from WSI to DZI is an additional, time-consuming step when rendering digital slides in the viewer, and inefficiency of digital slide viewers is a major criticism for digital pathology.
View Article and Find Full Text PDF