bioRxiv Science⌕ Search

Biology subjects

Jasoria, S.

Publications and source records attributed to Jasoria, S..

2 recordsLinked to original sources

Mindin-α-M-Integrin endocytosis activates STAT3 to maintain keratinocyte stemness

Signalling networks rely not only on specific protein interactions but also on the subcellular locales at which these occur. Such spatial control is fundamental to cellular behaviour in both physiological and pathological scenarios. In studying keratinocyte stemness, we previously identified a Mindin-M{beta}2 (CD11b/CD18) interaction that triggers STAT3 activation. Here, we delineate the mechanism underlying this response and show that the F-Spondin domain of Mindin constitutes the minimal integrin-binding module required to initiate downstream signalling. F-Spondin binding to the integrin at the plasma membrane does not elicit the full activation state of the integrin. Instead, it promotes Src-kinase dependent endocytosis of the integrin receptor to the early endosomes. Analysis of integrin conformational dynamics reveals that this compartmental shift is essential as the acidic environment of early endosomes drives the transition into a signalling-competent state. This mechanism extends to pathological contexts, as we demonstrate a requirement for endocytosis in activating STAT3 signalling and preserving stem-like properties in a cancer stem cell model. Together, these findings highlight a previously unrecognized layer of spatial control in integrin signalling, confirming endosomal trafficking as a critical determinant of stem cell behaviour and offering new conceptual and therapeutic opportunities across regenerative biology and cancer.

cell biology↗

PatternExtract: A facile, scalable pipeline for point pattern generation from spatial imaging data

We present PatternExtract, an open-source pipeline that generates accurate spatial point patterns from RGB pathology images and cell coordinate data without relying on composite channels or proprietary software. Using a novel two-kernel tissue segmentation method combined with automated pixel classification in QuPath, PatternExtract precisely excludes tissue artifacts such as necrosis and blood vessels to define spatial windows. Optimized on 568 diffuse large B-cell lymphoma images and validated on an independent cohort, the pipeline enables robust spatial analyses.

bioinformatics↗