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Biology subjects

Hosseini, M. S.

Publications and source records attributed to Hosseini, M. S..

2 recordsLinked to original sources

Spatial multi-omics resolve epithelium-fibroblast gradients and highlight NESTIN-NOTCH1-expressing subepithelial fibroblasts during human pancreatic tumorigenesis

Intraductal papillary mucinous neoplasms (IPMNs) are cystic precursors of pancreatic ductal adenocarcinoma undergoing dynamic epithelial and stromal remodeling during progression. In this study, we integrated computational pathology, cyclic immunofluorescence, and Xenium spatial transcriptomics to define the spatial organization of the IPMN microenvironment. We queried cell-based histopathological features and identified stromal patterns strongly associated with epithelium proximity. Cyclic immunofluorescence and Xenium revealed a subepithelial gradient extending from myofibroblasts to inflammatory fibroblasts. Xenium further identified a distinct subepithelial NOTCH1-NESTIN-expressing fibroblast subset in myofibroblasts that expands with tumor progression. By recapitulating the spatial remodeling event using human pancreatic tumor cells and primary myofibroblast co-culture models, we demonstrated the capacity of pancreatic tumor cells to induce a NESTIN-expressing state in neighboring myofibroblasts. These findings reveal new dynamic epithelial-stromal interactions through subepithelial NESTIN+ fibroblasts associated with pancreatic tumorigenesis and immediate microenvironment remodeling by active tumor cells, highlighting the power of computational pathology integrated with spatial transcriptomics.

cancer biology↗

Whole Slide Preview Image Segmentation and Setup for Digital Pathology Scanners

The problem of tissue finding is of special interest in automating WSI scanners where it decomposes the preview image of tissue glass slides into a simplified and abstract level of localization and identification to setup WSI scanner for high-resolution scan. Prior to such scanning, a preview image is captured to calibrate the scanners parameters. Scan parameters such as focus depth and scan region are determined using a tissue finding software package. This paper introduces a series of pipelines (e.g. binary mask segmentation, tissue/artifact classification, region-of-interest allocation) to automate tissue preview segmentation in both brightfield and darkfield microscopy.

pathology↗