Cancer Cell Drug Response Transcriptomes in 3D

The relevance of different in vitro culture models of cancer cells is a hot topic, but few systematic and definitive analyses in this area exist. In this issue of Cell Chemical Biology, Senkowski et al. (2016) address this issue by studying the transcriptomic profiles of drug-treated cancer cells cultured in two-dimensional and three-dimensional cultures. They describe biological findings with potential therapeutic implications and provide a unique data resource to mine.Non peer reviewe

Rho and Rac Take Center Stage

Many features of cell behavior are regulated by Rho family GTPases, but the most profound effects of these proteins are on the actin cytoskeleton and it was these that first drew attention to this family of signaling proteins. Focusing on Rho and Rac, we will discuss how their effectors regulate the actin cytoskeleton. We will describe how the activity of Rho proteins is regulated downstream from growth factor receptors and cell adhesion molecules by guanine nucleotide exchange factors and GTPase activating proteins. Additionally, we will discuss how there is signaling crosstalk between family members and how various bacterial pathogens have developed strategies to manipulate Rho protein activity so as to enhance their own survival

A normalized drug response metric improves accuracy and consistency of anticancer drug sensitivity quantification in cell-based screening

Accurate quantification of drug effects is crucial for identifying pharmaceutically actionable cancer vulnerabilities. Current cell viability-based measurements often lead to biased response estimates due to varying growth rates and experimental artifacts that explain part of the inconsistency in high-throughput screening results. We developed an improved drug scoring model, normalized drug response (NDR), which makes use of both positive and negative control conditions to account for differences in cell growth rates, and experimental noise to better characterize drug-induced effects. We demonstrate an improved consistency and accuracy of NDR compared to existing metrics in assessing drug responses of cancer cells in various culture models and experimental setups. Notably, NDR reliably captures both toxicity and viability responses, and differentiates a wider spectrum of drug behavior, including lethal, growth-inhibitory and growth-stimulatory modes, based on a single viability readout. The method will therefore substantially reduce the time and resources required in cell-based drug sensitivity screening. Abhishekh Gupta et al. present a normalized drug response (NDR) metric for accurate quantification of drug sensitivity in cell-based high-throughput assays. They show that NDR captures both toxicity and viability responses to improve drug effect classification over existing methods.Peer reviewe

Searching for Drug Synergy in Complex Dose–Response Landscapes Using an Interaction Potency Model

Corrigendum: Comput. Struct. Biotechnol. J. 2017, vol. 15, 387-387. DOI: 10.1016/j.csbj.2017.07.003Peer reviewe

What is synergy? The Saariselka agreement revisited

Many biological or chemical agents when combined interact with each other and produce a synergistic response that cannot be predicted based on the single agent responses alone. However, depending on the postulated null hypothesis of non-interaction, one may end up in different interpretations of synergy. Two popular reference models for null hypothesis include the Bliss independence model and the Loewe additivity model, each of which is formulated from different perspectives. During the last century, there has been an intensive debate on the suitability of these synergy models, both of which are theoretically justified and also in practice supported by different schools of scientists. More than 20 years ago, there was a community effort to make a consensus on the terminology one should use when claiming synergy. The agreement was formulated at a conference held in Saariselka, Finland in 1992, stating that one should use the terms Bliss synergy or Loewe synergy to avoid ambiguity in the underlying models. We review the theoretical relationships between these models and argue that one should combine the advantages of both models to provide a more consistent definition of synergy and antagonism.Peer reviewe

Phenotypic Screening Combined with Machine Learning for Efficient Identification of Breast Cancer-Selective Therapeutic Targets

The lack of functional understanding of most mutations in cancer, combined with the non-druggability of most proteins, challenge genomics-based identification of oncology drug targets. We implemented a machine-learning-based approach (idTRAX), which relates cell-based screening of small-molecule compounds to their kinase inhibition data, to directly identify effective and readily druggable targets. We applied idTRAX to triple-negative breast cancer cell lines and efficiently identified cancer-selective targets. For example, we found that inhibiting AKT selectively kills MFM-223 and CAL148 cells, while inhibiting FGFR2 only kills MFM-223. Since the effects of catalytically inhibiting a protein can diverge from those of reducing its levels, targets identified by idTRAX frequently differ from those identified through gene knockout/knockdown methods. This is critical if the purpose is to identify targets specifically for small-molecule drug development, whereby idTRAX may produce fewer false-positives. The rapid nature of the approach suggests that it may be applicable in personalizing therapy.Peer reviewe

Integrin signaling to the actin cytoskeleton

Integrin engagement stimulates the activity of numerous signaling molecules, including the Rho family of GTPases, tyrosine phosphatases, cAMP-dependent protein kinase and protein kinase C, and stimulates production of PtdIns(4,5)P2. Integrins promote actin assembly via the recruitment of molecules that directly activate the actin polymerization machinery or physically link it to sites of cell adhesion

Identification of novel regulators of STAT3 activity

STAT3 mediates signalling downstream of cytokine and growth factor receptors where it acts as a transcription factor for its target genes, including oncogenes and cell survival regulating genes. STAT3 has been found to be persistently activated in many types of cancers, primarily through its tyrosine phosphorylation (Y705). Here, we show that constitutive STAT3 activation protects cells from cytotoxic drug responses of several drug classes. To find novel and potentially targetable STAT3 regulators we performed a kinase and phosphatase siRNA screen with cells expressing either a hyperactive STAT3 mutant or IL6-induced wild type STAT3. The screen identified cell division cycle 7-related protein kinase (CDC7), casein kinase 2, alpha 1 (CSNK2), discoidin domain-containing receptor 2 (DDR2), cyclin-dependent kinase 8 (CDK8), phosphatidylinositol 4-kinase 2-alpha (PI4KII), C-terminal Src kinase (CSK) and receptor-type tyrosine-protein phosphatase H (PTPRH) as potential STAT3 regulators. Using small molecule inhibitors targeting these proteins, we confirmed dose and time dependent inhibition of STAT3-mediated transcription, suggesting that inhibition of these kinases may provide strategies for dampening STAT3 activity in cancers.Peer reviewe

Serine Phosphorylation Negatively Regulates RhoA in Vivo

Previous work indicates that RhoA phosphorylation on Ser188 by cAMP or cGMP-dependent kinases inhibits its activity. However, these studies lacked the possibility to directly study phosphorylated RhoA activity in vivo. Therefore, we created RhoA proteins containing phosphomimetic residues in place of the cAMP/cGMP-dependent kinase phosphorylation site. RhoA phosphorylation or phosphomimetic substitution did not affect Rho guanine nucleotide exchange factor, GTPase activating protein, or geranylgeranyl transferase activity in vitro but promoted binding to the Rho guanine-dissociation inhibitor as measured by exchange factor competition assays. The in vitro similarities between RhoA phosphomimetic proteins and phosphorylated RhoA allowed us to study function of phosphorylated RhoA in vivo. RhoA phosphomimetic proteins display depressed GTP loading when transiently expressed in NIH 3T3 cells. Stable-expressing RhoA and RhoA(S188A) clones spread significantly slower than mock-transfected or RhoA(S188E) clones. RhoA(S188A) clones were protected from the morphological effects of a cAMP agonist, whereas phosphomimetic clones exhibit stress fiber disassembly similar to control cells. Together, these data provide in vivo evidence that addition of a charged group to Ser188 upon phosphorylation negatively regulates RhoA activity and indicates that this occurs through enhanced Rho guanine-dissociation inhibitor interaction rather than direct perturbation of guanine nucleotide exchange factor, GTPase activating protein, or geranylgeranyl transferase activity

Chemogenomic Analysis of the Druggable Kinome and Its Application to Repositioning and Lead Identification Studies

Owing to the intrinsic polypharmacological nature of most small-molecule kinase inhibitors, there is a need for computational models that enable systematic exploration of the chemogenomic landscape underlying druggable kinome toward more efficient kinome-profiling strategies. We implemented Virtual-KinomeProfiler, an efficient computational platform that captures distinct representations of chemical similarity space of the druggable kinome for various drug discovery endeavors. By using the computational platform, we profiled approximately 37 million compound-kinase pairs and made predictions for 151,708 compounds in terms of their repositioning and lead molecule potential, against 248 kinases simultaneously. Experimental testing with biochemical assays validated 51 of the predicted interactions, identifying 19 small-molecule inhibitors of EGFR, HCK, FLT1, and MSK1 protein kinases. The prediction model led to a 1.5-fold increase in precision and 2.8-fold decrease in false-discovery rate, when compared with traditional single-dose biochemical screening, which demonstrates its potential to drastically expedite the kinome-specific drug discovery process.Peer reviewe