Woods, L. M. | Search bioRxiv

bioRxiv2025

Comparative ASCL1 interactome analysis reveals CDK2-Cyclin A2 as suppressors of differentiation in MYCN-amplified neuroblastoma

Neuroblastoma is a heterogeneous paediatric cancer arising from developmentally arrested neuronal precursors, where restoring differentiation offers therapeutic promise. ASCL1, a pro-neural transcription factor, is widely expressed in neuroblastoma and can drive either proliferation or differentiation depending on the cellular context. Here, we show that distinct MYCN-amplified neuroblastoma cell lines exhibit differing cell cycle and differentiation responses to ASCL1 overexpression. By comparing genome-wide ASCL1 chromatin binding, transcriptional changes, and protein-protein interactions, we found that ASCL1 binds more extensively to neuronal proteins in a cell line that is more susceptible to ASCL1-driven differentiation, but associates with cell cycle regulators in less responsive cells. We show that CDK2-Cyclin A2 bind ASCL1 in less responsive cells, with CDK-mediated phosphorylation of ASCL1 limiting the ability of ASCL1 to drive differentiation. Our study reveals that context-dependent interactions of ASCL1 with protein partners on the chromatin control its ability to re-engage a differentiation program in neuroblastoma.

cancer biology↗

bioRxiv2017

Species abundance plays a dominant role in local and regional extinctions in freshwater communities and allows the identification of selective extinctions

Recent declines in global biodiversity emphasize that understanding the factors that determine extinction risk should be a priority for ecologists and conservation biologists. A key question is whether extinctions are nonrandom and selective, in which case knowledge of selectivity may help predict and prevent future extinction. We suggest, however, that a premature focus on the identification of selective, trait-based determinants of extinctions risk is problematic if the potential importance of stochastic extinction processes are not first considered. Within this context we aimed to determine the roles that stochastic extinction and species abundance play in extinction risk by applying a rarefaction-based null model approach to analyzing biodiversity declines and extinctions in an experimental system. We focused on aquatic macroinvertebrate declines and extinction caused by predation by fish (Lepomis cyanellus) in semi-natural freshwater mesocosms. We found that null-predicted local extirpations based on the random loss of individuals were a significant predictor of observed local extirpations, and that the majority of observed extinctions were consistent with stochastic mechanisms of extinction, as predicted by a rarefaction model. We were able to identify a number of selective extinctions that were not predicted by the rarefaction model, and while these were relatively rare, they contributed to greater-than-expected loss of diversity at both local (mesocosm) and regional (whole experiment) spatial scales. Our results confirm that species abundance and occupancy are among the most important factors in identifying extinction risk in response to a disturbance. Moreover, owing to our use of a stochastic null model, we also conclude that measures of abundance are important indicators of extinction probability because they are operated on by the random loss of individuals, suggesting that stochastic extinction is an important process in this system and in biodiversity loss in general.

ecology↗