Chromatin-Remodeling Complex SWI/SNF Controls Multidrug Resistance by Transcriptionally Regulating the Drug Efflux Pump ABCB1

Dubey, Ramin; Lebensohn, Andres M.; Bahrami-Nejad, Zahra; Marceau, Caleb; Champion, Magali; Gevaert, Olivier; Šikić, Branimir I.; Carette, Jan E.; Rohatgi, Rajat

doi:10.1158/0008-5472.can-16-0716

Cited by 34 publications

(34 citation statements)

References 35 publications

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“…Gene expression levels in WT HAP1 cells were determined from previously published data (Dubey et al, 2016). Briefly, the raw RNAseq data for WT HAP1 cells (NCBI Gene Expression Omnibus (GEO) Series accession number GSE75515) was aligned, quantified and analyzed using Partek Flow software, version 4.0 (Partek Inc.).…”

Section: Methodsmentioning

confidence: 99%

Comparative genetic screens in human cells reveal new regulatory mechanisms in WNT signaling

Lebensohn

Dubey

Neitzel

et al. 2016

eLife

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142

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The comprehensive understanding of cellular signaling pathways remains a challenge due to multiple layers of regulation that may become evident only when the pathway is probed at different levels or critical nodes are eliminated. To discover regulatory mechanisms in canonical WNT signaling, we conducted a systematic forward genetic analysis through reporter-based screens in haploid human cells. Comparison of screens for negative, attenuating and positive regulators of WNT signaling, mediators of R-spondin-dependent signaling and suppressors of constitutive signaling induced by loss of the tumor suppressor adenomatous polyposis coli or casein kinase 1α uncovered new regulatory features at most levels of the pathway. These include a requirement for the transcription factor AP-4, a role for the DAX domain of AXIN2 in controlling β-catenin transcriptional activity, a contribution of glycophosphatidylinositol anchor biosynthesis and glypicans to R-spondin-potentiated WNT signaling, and two different mechanisms that regulate signaling when distinct components of the β-catenin destruction complex are lost. The conceptual and methodological framework we describe should enable the comprehensive understanding of other signaling systems.DOI: http://dx.doi.org/10.7554/eLife.21459.001

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Section: Methodsmentioning

confidence: 99%

Comparative genetic screens in human cells reveal new regulatory mechanisms in WNT signaling

Lebensohn

Dubey

Neitzel

et al. 2016

eLife

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142

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“…7b). Other resistance hits included multiple components of the SWI/SNF complex (SMARCA4, SMARCB1 and ARID1A), which has been previously implicated in the regulation of ABCB1 gene expression 36 . Tepoxalin was the only compound tested where high ABCB1 expression was associated with sensitivity rather than resistance to tepoxalin.…”

Section: Inducers Of Pde3a-slfn12 Protein-protein Interactionmentioning

confidence: 99%

Discovering the anticancer potential of non-oncology drugs by systematic viability profiling

et al. 2020

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Anticancer uses of non-oncology drugs have occasionally been found, but such discoveries have been serendipitous. We sought to create a public resource containing the growth-inhibitory activity of 4,518 drugs tested across 578 human cancer cell lines. We used PRISM (profiling relative inhibition simultaneously in mixtures), a molecular barcoding method, to screen drugs against cell lines in pools. An unexpectedly large number of non-oncology drugs selectively inhibited subsets of cancer cell lines in a manner predictable from the molecular features of the cell lines. Our findings include compounds that killed by inducing phosphodiesterase 3A-Schlafen 12 complex formation, vanadium-containing compounds whose killing depended on the sulfate transporter SLC26A2, the alcohol dependence drug disulfiram, which killed cells with low expression of metallothioneins, and the anti-inflammatory drug tepoxalin, which killed via the multidrug resistance protein ATP-binding cassette subfamily B member 1 (ABCB1). The PRISM drug repurposing resource (https://depmap.org/repurposing) is a starting point to develop new oncology therapeutics, and more rarely, for potential direct clinical translation. NATURE CANCER | VOL 1 | FeBRUARY 2020 | 235-248 | www.nature.com/natcancer 235 ResouRce NATuRE CANCER the remaining compounds being either chemotherapeutics (2%) or targeted oncology agents (21%).Screening results. We employed a 2-stage screening strategy whereby drugs were first screened in triplicate at a single dose (2.5 µM); 1,448 drugs screening positives were then rescreened in triplicate in an eight-point dose-response ranging from 10 µM to 610 pM ( Fig. 1c and Supplementary Table 2). Interestingly, most active compounds (774 out of 1,448, 53%) were originally developed for non-oncology clinical indications (Fig. 1d). The primary and secondary screening datasets are available on the Cancer Dependency Map portal (https://depmap.org/repurposing) and figshare (https://doi.org/10.6084/m9.figshare.9393293; Extended Data Figs. 1-4). We compared the PRISM results to two gold standard datasets: GDSC (ref. 2 ) and CTD 2 (ref. 3 ). The three datasets shared 84 compounds tested on a median of 236 common cell lines, yielding 16,650 shared data points. The PRISM dataset had a similar degree of concordance to GDSC and CTD 2 (Pearson correlations of 0.60 and 0.61, respectively over all shared data points), as the GDSC and CTD 2 datasets had to each other (Pearson correlation 0.62) (Extended Data Fig. 5a). The three datasets remained similarly concordant when the analysis was restricted to data points showing evidence of anticancer activity (Extended Data Fig. 5b). We conclude that, despite differences in assay format, sources of compounds 5 and sources of cell lines 6 , the PRISM Repurposing dataset is similarly robust compared to existing pharmacogenomic datasets.At the level of individual compound dose-responses, we note that the PRISM Repurposing dataset tends to be somewhat noisier, with a higher standard error estimated from vehicle contr...

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“…Identification of Ssn2, a subunit of RNA polymerase II mediator complex, and Gcn2, a kinase for ␣-subunit of eIF2, as regulators of the PDR process is not unexpected as transcriptional regulation can have significant impact on gene expression (38). In both human cell lines and C. albicans, chromatin-remodeling complex, which Ssn2 and Gcn2 interact with, was observed to control expression of PDR transporters (39,40).…”

Section: Discussionmentioning

confidence: 99%

A biosensor-based approach reveals links between efflux pump expression and cell cycle regulation in pleiotropic drug resistance of yeast

Li¹,

K²,

Schlecht³

et al. 2019

Journal of Biological Chemistry

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Edited by Mike ShipstonMultidrug resistance is highly conserved in mammalian, fungal, and bacterial cells, is characterized by resistance to several unrelated xenobiotics, and poses significant challenges to managing infections and many cancers. Eukaryotes use a highly conserved set of drug efflux transporters that confer pleiotropic drug resistance (PDR). To interrogate the regulation of this critical process, here we developed a small molecule-responsive biosensor that couples transcriptional induction of PDR genes to growth rate in the yeast Saccharomyces cerevisiae. Using diverse PDR inducers and the homozygous diploid deletion collection, we applied this biosensor system to genome-wide screens for potential PDR regulators. In addition to recapitulating the activity of previously known factors, these screens identified a series of genes involved in a variety of cellular processes with significant but previously uncharacterized roles in the modulation of yeast PDR. Genes identified as down-regulators of the PDR included those encoding the MAD family of proteins involved in the mitotic spindle assembly checkpoint (SAC) complex. Of note, we demonstrated that genetic disruptions of the mitotic spindle assembly checkpoint elevate expression of PDRmediating efflux pumps in response to exposure to a variety of compounds that themselves have no known influence on the cell cycle. These results not only establish our biosensor system as a viable tool for investigating PDR in a high-throughput fashion, but also uncover critical control mechanisms governing the PDR response and a previously uncharacterized link between PDR and cell cycle regulation in yeast. Figure 4. Disruption of spindle check point leads to elevated PDR activation. a, structures of compounds screened: cbf_5328528 (5), paf C-16 (6), k035-0031 (7), 0180-0423 (8), N,N-dimethylsphingosine (9). b, baseline corrected representative growth curve of ho⌬ and mad deletion in BY4743 background under treatment with 140 M 5. A 600 were measured every 15 min over 30 h. c, dose-response of strains in b over increasing 5 concentrations. Relative growth ϭ AUC 5 /AUC no drug . All wells contain the same DMSO concentration. AUC calculation was performed with a baseline corrected growth curve. The line represents best fit dose-response curve, and error bars represent S.D. (n ϭ 3). d, baseline corrected representative growth curve of ho⌬ and mad deletion in AD1-9 PDR transporter null background under 77.5 M 5 treatment. e, dose-response of strains in d over increasing 5 concentrations. f, qPCR validation of transcription induction of all three transporters under the treatment of all five compounds in a. Methods are identical to those in Fig. 3. Error bars represent S.D. (n ϭ 3). *, indicates p Ͻ 0.05. 1262 Genome-wide dissection of yeast PDR regulation

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Chromatin-Remodeling Complex SWI/SNF Controls Multidrug Resistance by Transcriptionally Regulating the Drug Efflux Pump ABCB1

Cited by 34 publications

References 35 publications

Comparative genetic screens in human cells reveal new regulatory mechanisms in WNT signaling

Comparative genetic screens in human cells reveal new regulatory mechanisms in WNT signaling

Discovering the anticancer potential of non-oncology drugs by systematic viability profiling

A biosensor-based approach reveals links between efflux pump expression and cell cycle regulation in pleiotropic drug resistance of yeast

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