Barbora Šalovská

Baseline cellular state dictates the molecular impact of KRAS mutant variants in pancreatic cancer cells

The paper examines the molecular effects of seven KRAS mutant variants in pancreatic cancer cells and finds that baseline cellular state, not allele identity, primarily drives molecular variation.

The RNA-dependent interactions of phosphatidylinositol 4,5-bisphosphate with intrinsically disordered proteins contribute to nuclear compartmentalization.

This study identifies RNA-dependent PIP2-associated proteins in human cells and shows their role in nuclear compartmentalization through phase separation.

A Comprehensive and Robust Multiplex-DIA Workflow Profiles Protein Turnover Regulations Associated with Cisplatin Resistance

This study introduces a robust multiplex DIA-MS workflow with machine learning and statistical filtering to profile protein turnover in cisplatin-resistant cancer cells, revealing correlations between transcript regulation and protein degradation.

An Extensive Atlas of Proteome and Phosphoproteome Turnover Across Mouse Tissues and Brain Regions

The paper presents Turnover-PPT, a resource mapping protein and phosphoprotein turnover across mouse tissues and brain regions, revealing tissue-specific protein lifetimes and phosphorylation's impact on stability.

BoxCarmax: a high-selectivity data-independent acquisition mass spectrometry method for the analysis of protein turnover and complex samples

BoxCarmax improves DIA-MS analysis of protein turnover and complex samples by enhancing quantitative accuracy in SILAC and pSILAC experiments.

Global impact of phosphorylation on protein endurance

The paper introduces DeltaSILAC, a proteomic method to quantify how phosphorylation affects protein endurance in cancer cells, revealing its global impact on protein turnover and identifying sequence features associated with endurance changes.

Rapid Proteomic Screen of CRISPR Experiment Outcome by Data Independent Acquisition Mass Spectrometry: A Case Study for HMGN1

This study uses DIA-MS to rapidly assess proteomic changes after CRISPR-mediated HMGN1 knockout in cancer cells, identifying 147 significantly altered proteins and their functional impacts.