Neuronal differentiation and cell-cycle programs mediate response to BET-bromodomain inhibition in MYC-driven medulloblastoma

Bandopadhayay, Pratiti; Piccioni, Federica; O’Rourke, Ryan; Ho, Patricia; Gonzalez, Elizabeth M.; Buchan, Graham; Qian, Kenin; Gionet, Gabrielle; Girard, Emily J.; Coxon, Margo; Rees, Matthew G.; Brenan, Lisa; Dubois, Frank; Shapira, Ofer; Greenwald, Noah F.; Pagès, Mélanie; Iniguez, Amanda Balboni; Paolella, Brenton R.; Meng, Alice; Sinai, Claire; Roti, Giovanni; Dharia, Neekesh V.; Creech, Amanda L.; Tanenbaum, Benjamin; Khadka, Prasidda; Tracy, Adam; Tiv, Hong L.; Hong, Andrew L.; Coy, Shannon; Rashid, Rumana; Lin, Jia-Ren; Cowley, Glenn S.; Lam, Fred C.; Goodale, Amy; Lee, Yenarae; Schoolcraft, Kathleen; Vázquez, Francisca; Hahn, William C.; Tsherniak, Aviad; Bradner, James E.; Yaffe, Michael B.; Milde, Till; Pfister, Stefan M.; Qi, Jun; Schenone, Monica; Carr, Steven A.; Ligon, Keith L.; Kieran, Mark W.; Santagata, Sandro; Olson, James M.; Gokhale, Prafulla C.; Jaffe, Jacob D.; Root, David E.; Stegmaier, Kimberly; Johannessen, Cory M.; Beroukhim, Rameen

doi:10.1038/s41467-019-10307-9

Cited by 42 publications

(43 citation statements)

References 60 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this system, each clone is tagged with a library of random CRISPR sgRNAs [10]. In the absence of Cas9 expression, the sgRNA-barcodes serve as inert labels that are propagated upon cell division, similar to previously reported clonal barcoding strategies [8],[5]. The relative abundance of each clone can be quantified by deep sequencing of the DNA-integrated sgRNA-barcode.…”

Section: Resultsmentioning

confidence: 99%

“…S1a). To test the clone tracking capacity of sgRNA-barcodes, we applied the 26-nt barcode library to monitor clonal resistance to the BET-bromodomain inhibitor JQ1, in D458, a MYC-amplified medulloblastoma cell line known to contain pre-existing resistant clones to a chemotherapeutic [5]. We first transduced D458 cells with the 26-nt barcode library at low MOI (< 0.3).…”

Section: Resultsmentioning

confidence: 99%

“…Heritable and plastic cellular features can drive selection outcomes. For example, genetic features can change with mutagens, such as DNA-damaging chemotherapies, and epigenetic states can rapidly shift in response to drug exposure [5]or environment [6]. Metastatic clones may alter their epigenetic profiles upon seeding a metastatic site [7], obscuring the preexisting features that enabled them to metastasize.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

CloneRetriever: retrieval of rare clones from heterogeneous cell populations

Feldman

Tsai

Garrity

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

Conclusions 44CloneRetriever provides a means to track and access specific and rare clones of 45 interest across dynamic changes in population structure to comprehensively explore the 46 basis of these changes. 47 48 Keywords 49 Cellular heterogeneity, Viable clone-specific cells recovery, Clonal fitness tracking, 50 CRISPR sgRNA-barcode DNA library 51 52 causal drivers of clone fitness could give rich insights into the molecular mechanisms of 62 selection and suggest potential interventions. 63 Heritable and plastic cellular features can drive selection outcomes. For example, 64 genetic features can change with mutagens, such as DNA-damaging chemotherapies, 65 and epigenetic states can rapidly shift in response to drug exposure [5]or environment 66 [6]. Metastatic clones may alter their epigenetic profiles upon seeding a metastatic site 67[7], obscuring the preexisting features that enabled them to metastasize. However, 68 existing methods to identify these features tend to rely on comparing populations in bulk 69 before and after selection, which limits their usefulness in detecting pre-existing features 70 that changed during selection. A useful alternative approach would be to identify clones 71 based upon their response to selective pressure, and then isolate representative 72 untreated cells from each clone for genomic and functional characterization. 73 Genomically integrated DNA barcodes provide a scalable methodology to track rare 74 clones by measuring relative barcode abundance over time [8]. However, relative clone 75 fitness alone cannot elucidate mechanisms of selection. Single-cell technologies can 76 provide genomic profiles of heterogeneous cells within a population. Clone identity can 77 be incorporated into single-cell RNA-seq (scRNA-seq) profiles by capturing transcribed 78 barcodes, linking clonal history and cell fate [9]. However, single-cell genomic profiling 79 is inherently destructive. Both DNA barcoding and single-cell approaches have a limited 80 ability to probe functional differences between clones, whereas retrieval of viable cells 81 from clones would enable a wide range of genomic and functional analysis. 82 488 R.B. and P.B. receive grant funding from the Novartis Institute of Biomedical Research 489 for an unrelated project. C.M.J. is currently a full-time employee and stockholder of 490

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

CloneRetriever: retrieval of rare clones from heterogeneous cell populations

Feldman

Tsai

Garrity

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…In this system, each clone is tagged with a library of random CRISPR sgRNAs [13]. In the absence of spCas9 expression, the sgRNAbarcodes serve as inert labels that are propagated upon cell division, similar to previously reported clonal barcoding strategies [5,9]. The relative abundance of each clone can be quantified by deep sequencing of the DNAintegrated sgRNA-barcode.…”

Section: Overview Of the Barcoding And Retrieval Strategymentioning

confidence: 99%

CloneSifter: enrichment of rare clones from heterogeneous cell populations

et al. 2020

Self Cite

View full text Add to dashboard Cite

Background Many biological processes, such as cancer metastasis, organismal development, and acquisition of resistance to cytotoxic therapy, rely on the emergence of rare sub-clones from a larger population. Understanding how the genetic and epigenetic features of diverse clones affect clonal fitness provides insight into molecular mechanisms underlying selective processes. While large-scale barcoding with NGS readout has facilitated cellular fitness assessment at the population level, this approach does not support characterization of clones prior to selection. Single-cell genomics methods provide high biological resolution, but are challenging to scale across large populations to probe rare clones and are destructive, limiting further functional analysis of important clones. Results Here, we develop CloneSifter, a methodology for tracking and enriching rare clones throughout their response to selection. CloneSifter utilizes a CRISPR sgRNA-barcode library that facilitates the isolation of viable cells from specific clones within the barcoded population using a sequence-specific retrieval reporter. We demonstrate that CloneSifter can measure clonal fitness of cancer cell models in vitro and retrieve targeted clones at abundance as low as 1 in 1883 in a heterogeneous cell population. Conclusions CloneSifter provides a means to track and access specific and rare clones of interest across dynamic changes in population structure to comprehensively explore the basis of these changes.

show abstract

“…Extensive efforts have focused instead on the regulatory machinery of enhancers with an anticipation that tumours (including brain tumours) are sensitive to modulation of the transcriptional output of specific oncogenic programmes [59]. Inhibition of chromatin ‘readers’ of H3K27ac, termed BET bromodomain inhibitors, is one example of this strategy [60,61]. Furthermore, there are other emerging efforts (in other solid tumours) that have focused on inhibition of H3K27ac acetyltransferases (‘writers’) or transcriptional elongation machinery to inhibit oncogene transcription in brain tumours.…”

Section: Therapeutic Interventions Against Enhancersmentioning

confidence: 99%

Invited Review: The role and contribution of transcriptional enhancers in brain cancer

Arabzade

Stuckert

Bertrand

et al. 2020

Neuropathology Appl Neurobio

View full text Add to dashboard Cite

2020) Neuropathology and Applied Neurobiology 46, 48-56 The role and contribution of transcriptional enhancers in brain cancer Genetic alterations identified across several paediatric and adult brain tumours reveal recurrent disruption of active chromatin landscapes and dysregulation of transcriptional programmes. Noncoding elements, specifically enhancers, are central to these mechanisms, and are influenced by developmental and neural gene regulatory signatures. Epigenomic and transcriptomic methods and techniques have facilitated detection of active enhancers, and characterization of brain tumours integrated with genomic structural information. These datasets have provided new insights into the mechanisms of transcriptional control that are profoundly altered in childhood and adult brain cancer; offering new ideas and molecular targets for therapeutic intervention. This review summarizes recent advances in our understanding of active transcriptional programmes of brain cancer, their impact on tumour development, and research areas for further exploration.

show abstract

Neuronal differentiation and cell-cycle programs mediate response to BET-bromodomain inhibition in MYC-driven medulloblastoma

Cited by 42 publications

References 60 publications

CloneRetriever: retrieval of rare clones from heterogeneous cell populations

CloneRetriever: retrieval of rare clones from heterogeneous cell populations

CloneSifter: enrichment of rare clones from heterogeneous cell populations

Invited Review: The role and contribution of transcriptional enhancers in brain cancer

Contact Info

Product

Resources

About