Biology subjects

Blagg, B. S. J.

Publications and source records attributed to Blagg, B. S. J..

2 recordsLinked to original sources

bioRxiv2025

AHA1 regulates Aβ production via modulation of APP expression and γ-secretase assembly

Deposition of amyloid {beta}-protein (A{beta}) is a hallmark of Alzheimers disease (AD), produced by {gamma}-secretase-mediated cleavage of amyloid precursor protein (APP). The 90-kDa heat shock protein (Hsp90) co-chaperone, activator of Hsp90 ATPase homolog 1 (AHA1), is known to promote the accumulation of toxic tau species; however, its effects on A{beta} production remain unclear. Here, we show that knockdown of endogenous AHA1 decreases A{beta} generation and reduces APP and {gamma}-secretase components, whereas AHA1 overexpression elevates A{beta} production and the expression of these proteins. The AHA1-E67K mutant, which has impaired Hsp90 binding, lowers A{beta} production and the levels of APP and {gamma}-secretase components compared with wild-type AHA1. AHA1 associates with APP and immature {gamma}-secretase components, including anterior pharynx-defective phenotype 1 (APH1), indicating its role in APP proteolysis and A{beta} production. Disruption of the AHA1/Hsp90 complex--through AHA1 knockdown, the E67K mutant, or a small-molecule inhibitor--reduces {gamma}-secretase assembly. Familial AD mutations in APP-C99 and presenilin-1 (PS1) increase AHA1, Hsp90, APP, and APH1 expression, enhancing A{beta} production. Importantly, AHA1 knockdown decreases abnormal A{beta} generation and C99, PS1-CTF, and APH1 levels in mutant APP cells, while AHA1 overexpression enhances A{beta} production in PS1 mutant cells. Collectively, these findings reveal that AHA1 regulates A{beta} production by modulating APP expression and {gamma}-secretase assembly, establishing AHA1 as a potential target for therapeutic intervention in AD.

neuroscience↗

bioRxiv2025

Integrated Genomic Profiling Reveals Mechanisms of Broad Drug Resistance and Opportunities for Phenotypic Reprogramming in Cancer Cells

Broad drug resistance is a major barrier to effective cancer therapy, driven by diverse genetic, transcriptional, and metabolic adaptations across tumor types. Here, we developed an integrative computational framework that leverages PRISM drug sensitivity profiles from DepMap, multi-omic datasets, and perturbagen libraries to systematically characterize and identify strategies to reverse broad resistance in cancer cell lines. We found that resistant lines exhibit transcriptional programs enriched for extracellular matrix remodeling, stress adaptation, and survival signaling, with NFE2L2 emerging as a central regulatory hub linked to upstream mutations and downstream oxidative stress pathways. Integrated metabolomics and transcriptomics highlighted metabolic reprogramming as a hallmark of resistance, while mutation analyses revealed convergence on growth factor and ECM-related pathways. These features were also reflected in patient cohorts, where resistance-associated mutations correlated with reduced progression-free survival across diverse cancer types. Computational perturbagen screening identified candidate compounds predicted to reverse resistance-associated gene expression profiles, converging on actionable targets including NFE2L2, ABCB1, and CYP3A4, with compounds such as brefeldin A and nocodazole predicted to have strong activity in resistant lines. This study establishes a scalable, mechanism-informed framework for rationally identifying and prioritizing compounds to overcome broad drug resistance in cancer, providing a roadmap for targeted re-sensitization strategies.

cancer biology↗