Biology subjects

Beesabathuni, N. S.

Publications and source records attributed to Beesabathuni, N. S..

3 recordsLinked to original sources

bioRxiv2023

A new vulnerability to BET inhibition due to enhanced autophagy in BRCA2 deficient pancreatic cancer

Pancreatic cancer is one of the deadliest diseases in human malignancies. Among total pancreatic cancer patients, [~]10% of patients are categorized as familial pancreatic cancer (FPC) patients, carrying germline mutations of the genes involved in DNA repair pathways (e.g., BRCA2). Personalized medicine approaches tailored toward patients mutations would improve patients outcome. To identify novel vulnerabilities of BRCA2-deficient pancreatic cancer, we generated isogenic Brca2-deficient murine pancreatic cancer cell lines and performed high-throughput drug screens. High-throughput drug screening revealed that Brca2-deficient cells are sensitive to Bromodomain and Extraterminal Motif (BET) inhibitors, suggesting that BET inhibition might be a potential therapeutic approach. We found that BRCA2 deficiency increased autophagic flux, which was further enhanced by BET inhibition in Brca2-deficient pancreatic cancer cells, resulting in autophagy-dependent cell death. Our data suggests that BET inhibition can be a novel therapeutic strategy for BRCA2-deficient pancreatic cancer.

cancer biology↗

bioRxiv2023

Image-based temporal profiling of autophagy-related phenotypes

Autophagy is a dynamic process that is critical in maintaining cellular homeostasis. Dysregulation of autophagy is linked to many diseases and is emerging as a promising therapeutic target. High-throughput methods to characterize autophagy are essential for accelerating drug discovery and characterizing mechanisms of action. In this study, we developed a highly scalable image-based profiling approach to characterize [~]900 morphological features at a single cell level with high temporal resolution. We differentiated drug treatments based on morphological profiles using a random forest classifier with [~]90% accuracy and identified the key features that govern the classification. Additionally, temporal morphological profiles accurately predicted biologically relevant changes in autophagy after perturbation, such as total cargo degradation. Therefore, this study acts as proof-of-principle for using image-based profiling to differentiate autophagy perturbations in a high-throughput manner and identify biologically relevant autophagy phenotypes, which can accelerate drug discovery.

systems biology↗

bioRxiv2021

Quantitative and temporal measurement of dynamic autophagy rates

Autophagy is a multistep degradative process that is essential for maintaining cellular homeostasis. Systematically quantifying flux through this pathway is critical for gaining fundamental insights and effectively modulating this process that is dysregulated during many diseases. Established methods to quantify flux use steady state measurements, which provide limited information about the perturbation and the cellular response. We present a theoretical and experimental framework to measure autophagic steps in the form of rates under non-steady state conditions. We use this approach to measure temporal responses to rapamycin and wortmannin treatments, two commonly used autophagy modulators. We quantified changes in autophagy rates in as little as 10 minutes, which can establish direct mechanisms for autophagy perturbation before feedback begins. We identified concentration-dependent effects of rapamycin on the initial and temporal progression of autophagy rates. We also found variable recovery time from wortmannins inhibition of autophagy, which is further accelerated by rapamycin. In summary, this new approach enables the quantification of autophagy flux with high sensitivity and temporal resolution and facilitates a comprehensive understanding of this process.

systems biology↗