Unraveling Glioblastoma Heterogeneity: Introducing SP2G Method for Identifying Invasive Sub-Populations

Abstract

AbstractGlioblastomas exhibit remarkable heterogeneity at various levels, including motility modes and mechanoproperties that contribute to tumor resistance and recurrence. In a recent study using gridded micropatterns mimicking the brain vasculature, we linked glioblastoma cell motility modes, mechanical properties, formin content, and substrate chemistry. We now introduce SP2G (SPheroid SPreading on Grids), an analytic platform designed to identify the migratory modes of patient-derived glioblastoma cells and rapidly pinpoint the most invasive sub-populations. Tumorspheres are imaged as they spread on gridded micropatterns and analyzed by our semi-automated, open-source, Fiji macro suite that characterizes migration modes accurately. With SP2G, we could reveal intra-patient motility heterogeneity with molecular correlations to specific integrins and EMT markers. Thus, our system presents a versatile and potentially pan-cancer workflow to detect diverse invasive tumor sub-populations in patient-derived specimens and offers a valuable tool for therapeutic evaluations at the individual patient level.TeaserCracking the inter and intra-patient diversity in Glioblastoma migration profiles