Koumenis, C. | Search bioRxiv

bioRxiv2023

p53 promotes revival stem cells in the regenerating intestine after severe radiation injury

Ionizing radiation induces cell death in the gastrointestinal (GI) epithelium by activating p53. However, p53 also prevents animal lethality caused by radiation-induced GI injury. Through single-cell RNA-sequencing of the irradiated mouse intestine, we find that p53 target genes are specifically enriched in stem cells of the regenerating epithelium, including revival stem cells that promote animal survival after GI damage. Accordingly, in mice with p53 deleted specifically in the GI epithelium, ionizing radiation fails to induce revival stem cells. Using intestinal organoids, we show that transient p53 expression is required for the induction of revival stem cells that is controlled by an Mdm2-mediated negative feedback loop. These results suggest that p53 suppresses severe radiation-indued GI injury by promoting intestinal epithelial cell reprogramming. One-Sentence SummaryAfter severe radiation injury to the intestine, transient p53 activity induces revival stem cells to promote regeneration.

cell biology↗

bioRxiv2022

The Radiogenomic and Spatiogenomic Landscapes of Glioblastoma, and Their Relationship to Oncogenic Drivers

Glioblastoma (GBM) is well-known for its molecular and spatial heterogeneity, which poses a challenge for precision therapies and clinical trial stratification. Here, in a comprehensive radiogenomics study of 358 GBMs, we investigated the associations between the imaging and spatial characteristics of the tumors with their cancer gene mutation status, as well as with the cross-sectionally inferred likely order of mutational events. We show that cross-validated machine learning analysis of multi-parametric MRI scans results in distinctive in vivo imaging signatures of several mutations, which are relatively more distinctive in homogeneous tumors which harbor only one of these mutations. These imaging signatures offer mechanistic insights into how various mutations influence the phenotype of the tumor and its surrounding infiltrated brain tissue via neovascularization and vascular leakage, increased cell density, invasion and migration, and other characteristics captured by respective imaging features. Furthermore, we found that spatial location and tumor distribution vary, depending on the GBMs molecular characteristics. Finally, distinct imaging and spatial characteristics were associated with cross-sectionally estimated evolutionary trajectories of the tumors. Collectively, our study establishes a panel of in vivo and clinically accessible imaging-AI biomarkers of GBM that reflect their molecular composition and oncogenic drivers.

bioengineering↗