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Search: authors:"Karen A. Ryall"

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An integrated bioinformatics analysis to dissect kinase dependency in triple negative breast cancer

Background Triple-Negative Breast Cancer (TNBC) is an aggressive disease with a poor prognosis. Clinically, TNBC patients have limited treatment options besides chemotherapy. The goal of this study was to determine the kinase dependency in TNBC cell lines and to predict compounds that could inhibit these kinases using integrative bioinformatics analysis. Results We integrated...

Identifying kinase dependency in cancer cells by integrating high-throughput drug screening and kinase inhibition data

Motivation: Targeted kinase inhibitors have dramatically improved cancer treatment, but kinase dependency for an individual patient or cancer cell can be challenging to predict. Kinase dependency does not always correspond with gene expression and mutation status. High-throughput drug screens are powerful tools for determining kinase dependency, but drug polypharmacology can make...

Systems biology approaches for advancing the discovery of effective drug combinations

Complex diseases like cancer are regulated by large, interconnected networks with many pathways affecting cell proliferation, invasion, and drug resistance. However, current cancer therapy predominantly relies on the reductionist approach of one gene-one disease. Combinations of drugs may overcome drug resistance by limiting mutations and induction of escape pathways, but given...

PD-L1 immunostaining scoring for non-small cell lung cancer based on immunosurveillance parameters

technical support at Merck KGaA. Author Contributions Conceptualization: Manuel A. Silva. Formal analysis: Karen A. Ryall, Janet C. Patterson-Kane. Investigation: Manuel A. Silva. Methodology: Claudia ... Wilm, Jenifer Caldara, Janet C. Patterson-Kane. Software: Jenifer Caldara, Janet C. Patterson-Kane. Writing ± original draft: Manuel A. Silva, Karen A. Ryall, Claudia Wilm, Jenifer Caldara, Janet C