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

Improved detection of differentially represented DNA barcodes for high-throughput clonal phenomics

Cellular DNA barcoding has become a popular approach to study heterogeneity of cell populations and to identify clones with differential response to cellular stimuli. However, there is a lack of reliable methods for statistical inference of differentially responding clones. Here, we used mixtures of DNA-barcoded cell pools to generate a realistic benchmark read count dataset for modelling a range of outcomes of clone-tracing experiments. By accounting for the statistical properties intrinsic to the DNA barcode read count data, we implemented an improved algorithm that results in a significantly lower false-positive rate, compared to current RNA-seq data analysis algorithms, especially when detecting differentially responding clones in experiments with strong selection pressure. Building on the reliable statistical methodology, we illustrate how multidimensional phenotypic profiling enables one to deconvolute phenotypically distinct clonal subpopulations within a cancer cell line. The mixture control dataset and our analysis results provide a foundation for benchmarking and improving algorithms for clone-tracing experiments

Generation of angular-momentum-dominated electron beams from a photoinjector

Various projects under study require an angular-momentum-dominated electron beam generated by a photoinjector. Some of the proposals directly use the angular-momentum-dominated beams (e.g. electron cooling of heavy ions), while others require the beam to be transformed into a flat beam (e.g. possible electron injectors for light sources and linear colliders). In this paper, we report our experimental study of an angular-momentum-dominated beam produced in a photoinjector, addressing the dependencies of angular momentum on initial conditions. We also briefly discuss the removal of angular momentum. The results of the experiment, carried out at the Fermilab/NICADD Photoinjector Laboratory, are found to be in good agreement with theoretical and numerical models.Comment: 8 pages, 7 figures, submitted to Phys. Rev. ST Accel. Beam

Protocol to utilize fresh uncultured human lung tumor cells for personalized functional diagnostics

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Effect of stress relieving heat treatment on surface topography and dimensional accuracy of incrementally formed grade 1 titanium sheet parts

The forming of parts with an optimized surface roughness and high dimensional accuracy is important in many applications of incremental sheet forming (ISF). To realize this, the effect of stress relieving heat treatment of grade-1 Ti parts performed before and after forming on the surface finish and dimensional accuracy was studied. It was found that heat treatment at a temperature of 540 °C for 2 h improves the surface finish of formed parts resulting in a surface with little or no visible tool marks. Additionally, it improves the dimensional accuracy of parts after unclamping from the rig used for forming, in particular, that of parts with shallow wall angles (typically <25°). It was also noted that post-forming heat treatment improves the surface finish of parts. The surface topography of formed parts was studied using interferometry to yield areal surface roughness parameters and subsequently using secondary electron imaging. Back-scatter electron microscopy imaging results coupled with energy-dispersive X-ray (EDX) analysis showed that heat treatment prior to forming leads to tool wear as indicated by the presence of Fe in samples. Furthermore, post-forming heat treatment prevents curling up of formed parts due to compressive stresses if the formed part is trimmed

Reciprocal regulation of PKA and rac signaling

Activated G protein-coupled receptors (GPCRs) and receptor tyrosine kinases relay extracellular signals through spatial and temporal controlled kinase and GTPase entities. These enzymes are coordinated by multifunctional scaffolding proteins for precise intracellular signal processing. The cAMP-dependent protein kinase A (PKA) is the prime example for compartmentalized signal transmission downstream of distinct GPCRs. A-kinase anchoring proteins tether PKA to specific intracellular sites to ensure precision and directionality of PKA phosphorylation events. Here, we show that the Rho-GTPase Rac contains A-kinase anchoring protein properties and forms a dynamic cellular protein complex with PKA. The formation of this transient core complex depends on binary interactions with PKA subunits, cAMP levels and cellular GTP-loading accounting for bidirectional consequences on PKA and Rac downstream signaling. We show that GTP-Rac stabilizes the inactive PKA holoenzyme. However, β-adrenergic receptor-mediated activation of GTP-Rac–bound PKA routes signals to the Raf-Mek-Erk cascade, which is critically implicated in cell proliferation. We describe a further mechanism of how cAMP enhances nuclear Erk1/2 signaling: It emanates from transphosphorylation of p21-activated kinases in their evolutionary conserved kinase-activation loop through GTP-Rac compartmentalized PKA activities. Sole transphosphorylation of p21-activated kinases is not sufficient to activate Erk1/2. It requires complex formation of both kinases with GTP-Rac1 to unleash cAMP-PKA–boosted activation of Raf-Mek-Erk. Consequently GTP-Rac functions as a dual kinase-tuning scaffold that favors the PKA holoenzyme and contributes to potentiate Erk1/2 signaling. Our findings offer additional mechanistic insights how β-adrenergic receptor-controlled PKA activities enhance GTP-Rac–mediated activation of nuclear Erk1/2 signaling

Enhanced sensitivity to glucocorticoids in cytarabine-resistant AML

We sought to identify drugs that could counteract cytarabine resistance in acute myeloid leukemia (AML) by generating eight resistant variants from MOLM-13 and SHI-1 AML cell lines by long-term drug treatment. These cells were compared with 66 ex vivo chemorefractory samples from cytarabine-treated AML patients. The models and patient cells were subjected to genomic and transcriptomic profiling and high-throughput testing with 250 emerging and clinical oncology compounds. Genomic profiling uncovered deletion of the deoxycytidine kinase (DCK) gene in both MOLM-13- and SHI-1-derived cytarabine-resistant variants and in an AML patient sample. Cytarabine-resistant SHI-1 variants and a subset of chemorefractory AML patient samples showed increased sensitivity to glucocorticoids that are often used in treatment of lymphoid leukemia but not AML. Paired samples taken from AML patients before treatment and at relapse also showed acquisition of glucocorticoid sensitivity. Enhanced glucocorticoid sensitivity was only seen in AML patient samples that were negative for the FLT3 mutation (P = 0.0006). Our study shows that development of cytarabine resistance is associated with increased sensitivity to glucocorticoids in a subset of AML, suggesting a new therapeutic strategy that should be explored in a clinical trial of chemorefractory AML patients carrying wild-type FLT3.Peer reviewe

Target Inhibition Networks: Predicting Selective Combinations of Druggable Targets to Block Cancer Survival Pathways

A recent trend in drug development is to identify drug combinations or multi-target agents that effectively modify multiple nodes of disease-associated networks. Such polypharmacological effects may reduce the risk of emerging drug resistance by means of attacking the disease networks through synergistic and synthetic lethal interactions. However, due to the exponentially increasing number of potential drug and target combinations, systematic approaches are needed for prioritizing the most potent multi-target alternatives on a global network level. We took a functional systems pharmacology approach toward the identification of selective target combinations for specific cancer cells by combining large-scale screening data on drug treatment efficacies and drug-target binding affinities. Our model-based prediction approach, named TIMMA, takes advantage of the polypharmacological effects of drugs and infers combinatorial drug efficacies through system-level target inhibition networks. Case studies in MCF-7 and MDA-MB-231 breast cancer and BxPC-3 pancreatic cancer cells demonstrated how the target inhibition modeling allows systematic exploration of functional interactions between drugs and their targets to maximally inhibit multiple survival pathways in a given cancer type. The TIMMA prediction results were experimentally validated by means of systematic siRNA-mediated silencing of the selected targets and their pairwise combinations, showing increased ability to identify not only such druggable kinase targets that are essential for cancer survival either individually or in combination, but also synergistic interactions indicative of nonadditive drug efficacies. These system-level analyses were enabled by a novel model construction method utilizing maximization and minimization rules, as well as a model selection algorithm based on sequential forward floating search. Compared with an existing computational solution, TIMMA showed both enhanced prediction accuracies in cross validation as well as significant reduction in computation times. Such cost-effective computational-experimental design strategies have the potential to greatly speed-up the drug testing efforts by prioritizing those interventions and interactions warranting further study in individual cancer cases

Identification of selective cytotoxic and synthetic lethal drug responses in triple negative breast cancer cells

Background: Triple negative breast cancer (TNBC) is a highly heterogeneous and aggressive type of cancer that lacks effective targeted therapy. Despite detailed molecular profiling, no targeted therapy has been established. Hence, with the aim of gaining deeper understanding of the functional differences of TNBC subtypes and how that may relate to potential novel therapeutic strategies, we studied comprehensive anticancer-agent responses among a panel of TNBC cell lines.Method: The responses of 301 approved and investigational oncology compounds were measured in 16 TNBC cell lines applying a functional profiling approach. To go beyond the standard drug viability effect profiling, which has been used in most chemosensitivity studies, we utilized a multiplexed readout for both cell viability and cytotoxicity, allowing us to differentiate between cytostatic and cytotoxic responses.Results: Our approach revealed that most single-agent anti-cancer compounds that showed activity for the viability readout had no or little cytotoxic effects. Major compound classes that exhibited this type of response included anti-mitotics, mTOR, CDK, and metabolic inhibitors, as well as many agents selectively inhibiting oncogene-activated pathways. However, within the broad viability-acting classes of compounds, there were often subsets of cell lines that responded by cell death, suggesting that these cells are particularly vulnerable to the tested substance. In those cases we could identify differential levels of protein markers associated with cytotoxic responses. For example, PAI-1, MAPK phosphatase and Notch-3 levels associated with cytotoxic responses to mitotic and proteasome inhibitors, suggesting that these might serve as markers of response also in clinical settings. Furthermore, the cytotoxicity readout highlighted selective synergistic and synthetic lethal drug combinations that were missed by the cell viability readouts. For instance, the MEK inhibitor trametinib synergized with PARP inhibitors. Similarly, combination of two non-cytotoxic compounds, the rapamycin analog everolimus and an ATP-competitive mTOR inhibitor dactolisib, showed synthetic lethality in several mTOR-addicted cell lines.Conclusions: Taken together, by studying the combination of cytotoxic and cytostatic drug responses, we identified a deeper spectrum of cellular responses both to single agents and combinations that may be highly relevant for identifying precision medicine approaches in TNBC as well as in other types of cancers