mQC: A Heuristic Quality-Control Metric for High-Throughput Drug Combination Screening

Chen, Lu; Wilson, Kelli; Goldlust, Ian S.; Mott, Bryan T.; Eastman, Richard T.; Davis, Mindy I.; Zhang, Xiaohu; McKnight, Crystal; Klumpp‐Thomas, Carleen; Shinn, Paul; Simmons, John K.; Gormally, Mike; Michael, Sam; Thomas, Craig J.; Ferrer, Marc; Guha, Rajarshi

doi:10.1038/srep37741

Cited by 8 publications

(7 citation statements)

References 30 publications

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“…In collaboration with the National Center for Advancing Translational Sciences, we previously performed a viability matrix combination screen of their MIPE library of ∼1900 oncology-focused compounds [42] to identify anti-NBL, synergistic combinations with two BETi (JQ1 and IBET151) in two MYCN -amplified, TP53 mutant NBL cell lines (Lan-1 and SK-N-BE(2)C [hereafter referred to as BE(2)C]) [40] . In general, an interpretable, matrix-level quality control measure mQC (described in reference 43 ), confirmed confidence in the results, with the vast majority of drug combinations in both cell lines rating “good,” (>95% of BE(2)C combinations and 80% of Lan-1 combinations). Over half of all drugs in the MIPE library demonstrated some degree of synergy with the BETi, as demonstrated by a delta Bliss Sum Negative (DBSumNeg) value that was < 0 based on the Bliss Independence model of synergy determination [44] .…”

Section: Resultssupporting

confidence: 56%

The synergy of BET inhibitors with aurora A kinase inhibitors in MYCN-amplified neuroblastoma is heightened with functional TP53

Sias-Garcia

Nasholm

et al. 2021

Neoplasia

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Amplification of MYCN is a poor prognostic feature in neuroblastoma (NBL) indicating aggressive disease. We and others have shown BET bromodomain inhibitors (BETi) target MYCN indirectly by downregulating its transcription. Here we sought to identify agents that synergize with BETi and to identify biomarkers of resistance. We previously performed a viability screen of ∼1,900 oncology-focused compounds combined with BET bromodomain inhibitors against MYCN -amplified NBL cell lines. Reanalysis of our screening results prominently identified inhibitors of aurora kinase A (AURKAi) to be highly synergistic with BETi. We confirmed the anti-proliferative effects of several BETi+AURKAi combinations in MYCN -amplified NBL cell lines. Compared to single agents, these combinations cooperated to decrease levels of N-myc. We treated both TP53 -wild type and mutant, MYCN -amplified cell lines with the BETi JQ1 and the AURKAi Alisertib. The combination had improved efficacy in the TP53 -WT context, notably driving apoptosis in both genetic backgrounds. JQ1+Alisertib combination treatment of a MYCN -amplified, TP53 -null or TP53 -restored genetically engineered mouse model of NBL prolonged survival better than either single agent. This was most profound with TP53 restored, with marked tumor shrinkage and apoptosis induction in response to combination JQ1+Alisertib. BETi+AURKAi in MYCN -amplified NBL, particularly in the context of functional TP53 , provided anti-tumor benefits in preclinical models. This combination should be studied more closely in a pediatric clinical trial.

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Section: Resultssupporting

confidence: 56%

The synergy of BET inhibitors with aurora A kinase inhibitors in MYCN-amplified neuroblastoma is heightened with functional TP53

Sias-Garcia

Nasholm

et al. 2021

Neoplasia

Self Cite

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“…Many measures have been proposed to evaluate assay quality. These can be related to plate level controls and sample level controls (Chen et al, 2016). Z factor is the most commonly used measure of screening assay quality indicating the ''assay window'', which refers to the space between positive and negative control where screening factors should exhibit their activity.…”

Section: Secretome Analysis and Target Identificationmentioning

confidence: 99%

“…Recently, strict standard mean difference (SSMD) has been proposed for assessing data quality in screening assays (Zhang, 2007(Zhang, , 2008. Similar to Z -factor, SSMD characterizes the performance of the controls on an individual plate (Chen et al, 2016). However, the advantage of SSMD lies in probabilistic interpretation and statistical estimation and inference (Zhang, 2008).…”

Section: Secretome Analysis and Target Identificationmentioning

confidence: 99%

“…Since the utility of individual QC measures is not sufficient to assess the assay quality, it is common to report multiple QC measures for a screening (Chen et al, 2016). For example, Zfactor can be used in conjunction with CV, S/B, or S/N to give a more concise assessment of the assay variation and performance.…”

Section: Secretome Analysis and Target Identificationmentioning

confidence: 99%

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Harnessing the Neural Stem Cell Secretome for Regenerative Neuroimmunology

Willis

Nicaise

Hamel

et al. 2020

Front. Cell. Neurosci.

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Increasing evidence foresees the secretome of neural stem cells (NSCs) to confer superimposable beneficial properties as exogenous NSC transplants in experimental treatments of traumas and diseases of the central nervous system (CNS). Naturally produced secretome biologics include membrane-free signaling molecules and extracellular membrane vesicles (EVs) capable of regulating broad functional responses. The development of high-throughput screening pipelines for the identification and validation of NSC secretome targets is still in early development. Encouraging results from pre-clinical animal models of disease have highlighted secretome-based (acellular) therapeutics as providing significant improvements in biochemical and behavioral measurements. Most of these responses are being hypothesized to be the result of modulating and promoting the restoration of key inflammatory and regenerative programs in the CNS. Here, we will review the most recent findings regarding the identification of NSC-secreted factors capable of modulating the immune response to promote the regeneration of the CNS in animal models of CNS trauma and inflammatory disease and discuss the increased interest to refine the pro-regenerative features of the NSC secretome into a clinically available therapy in the emerging field of Regenerative Neuroimmunology.

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“…Newly developed drug sensitivity assays should first be optimized to establish signal dynamic range using quality control metrics (QCM; e.g. Analysis of Variance (ANOVA), Z-factor (Z), Signal window (SW) and coefficient of variation (CV)) in single wells or on a plate level, followed by implementation of the optimized experimental parameters using a well-established drug and cell line [19][20][21] . Thereafter, the optimized assay should be validated and the results reported using suitable drug response metrics (e.g.…”

mentioning

confidence: 99%

Optimization of cell viability assays to improve replicability and reproducibility of cancer drug sensitivity screens

Larsson

Engqvist

Biermann

et al. 2020

Sci Rep

141

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cancer drug development has been riddled with high attrition rates, in part, due to poor reproducibility of preclinical models for drug discovery. Poor experimental design and lack of scientific transparency may cause experimental biases that in turn affect data quality, robustness and reproducibility. Here, we pinpoint sources of experimental variability in conventional 2D cell-based cancer drug screens to determine the effect of confounders on cell viability for MCF7 and HCC38 breast cancer cell lines treated with platinum agents (cisplatin and carboplatin) and a proteasome inhibitor (bortezomib). Variance component analysis demonstrated that variations in cell viability were primarily associated with the choice of pharmaceutical drug and cell line, and less likely to be due to the type of growth medium or assay incubation time. Furthermore, careful consideration should be given to different methods of storing diluted pharmaceutical drugs and use of DMSO controls due to the potential risk of evaporation and the subsequent effect on dose-response curves. Optimization of experimental parameters not only improved data quality substantially but also resulted in reproducible results for bortezomib-and cisplatin-treated HCC38, MCF7, MCF-10A, and MDA-MB-436 cells. Taken together, these findings indicate that replicability (the same analyst re-performs the same experiment multiple times) and reproducibility (different analysts perform the same experiment using different experimental conditions) for cell-based drug screens can be improved by identifying potential confounders and subsequent optimization of experimental parameters for each cell line. Cancer drug candidates currently have the lowest overall success rates and are 23% less likely to succeed in phase III clinical trials compared with other therapeutic areas 1-3. At a cost of approximately $3 billion per approved drug, over a decade may have passed from target discovery to drug approval (long development time) and tens of thousands of drug candidates would have likely been dropped due to drug safety and/or efficacy issues 4. Cell-based pharmacogenomics screens are commonly used during the preclinical drug screening process to identify druggable targets by characterizing the biological effects associated with drug response and toxicity. However, low interlaboratory reproducibility of cell-based pharmacogenomics screens, lack of robust disease models that recapitulate the natural progression of human cancers, and drug-associated toxicity issues contribute to the high drug attrition rates in oncology 5-13. Biomedical researchers and the pharmaceutical industry are, therefore, developing strategies to improve early-phase drug screening, e.g. novel preclinical models of disease and drug repurposing 9,14. Drug-dose response assays (e.g. MTT assay) performed in two-dimensional (2D) cell culture are typically used to evaluate drug efficacy and potency in cells exposed to a drug for up to 72 hours 15-17. However, it has been challenging to develop robust drug sensitivi...

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mQC: A Heuristic Quality-Control Metric for High-Throughput Drug Combination Screening

Cited by 8 publications

References 30 publications

The synergy of BET inhibitors with aurora A kinase inhibitors in MYCN-amplified neuroblastoma is heightened with functional TP53

The synergy of BET inhibitors with aurora A kinase inhibitors in MYCN-amplified neuroblastoma is heightened with functional TP53

Harnessing the Neural Stem Cell Secretome for Regenerative Neuroimmunology

Optimization of cell viability assays to improve replicability and reproducibility of cancer drug sensitivity screens

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