Search

Cells are complex systems in which many functions are performed by different genetically defined and encoded functional modules. To systematically understand how these modules respond to drug or genetic perturbations, we develop a functional module states framework. Using this framework, we (1) define the drug-induced transcriptional state space for breast cancer cell lines using large public gene expression datasets and reveal that the transcriptional states are associated with drug concentration and drug targets, (2) identify potential targetable vulnerabilities through integrative analysis of transcriptional states after drug treatment and gene knockdown-associated cancer dependency, and (3) use functional module states to predict transcriptional state-dependent drug sensitivity and build prediction models for drug response. This approach demonstrates a similar prediction performance as approaches using high-dimensional gene expression values, with the added advantage of more clearly revealing biologically relevant transcriptional states and key regulators. [Display omitted] • FM states framework is developed to understand transcriptomic states • FM states are discovered for cancer cell lines before or after intervention • This tool facilitates drug and target prediction by integrating large data resources Qin et al. develop a functional module states framework to understand the transcriptomic states of samples. This approach reveals transcriptional states of cancer cell lines before or after treatment. It provides valuable and biologically interpretable features for drug sensitivity and target prediction. [ABSTRACT FROM AUTHOR]

Abstract: Quercetin-3-O-amino acid-esters, a new type of quercetin derivatives, were successfully prepared for the first time. Different from quercetin, the novel compounds show higher selectivity as inhibitors against Src tyrosine kinase (IC50 values ranging from 3.2μM to 9.9μM) than against EGFR tyrosine kinase. Molecular docking reveals that both hydrophobic and hydrogen bonding interactions are important to the selectivity. Therefore, this study provides a new promising scaffold for further development of new anticancer drugs targeting Src tyrosine kinase. [Copyright &y& Elsevier]