SUMMARY Tumor-specific genomic information has the potential to guide therapeutic strategies and revolutionize patient treatment. Currently, this approach is limited by an abundance of disease-associated mutants whose biological functions and impacts on therapeutic response are uncharacterized. To begin to address this limitation, we functionally characterized nearly all (99.84%) missense mutants of MAPK1/ERK2, an essential effector of oncogenic RAS and RAF. Using this approach, we discovered rare gain- and loss-of-function ERK2 mutants found in human tumors, revealing that, in the context of this assay, mutational frequency alone cannot identify all functionally impactful mutants. Gain-of-function ERK2 mutants induced variable responses to RAF-, MEK- and ERK-directed therapies, providing a reference for future treatment decisions. Tumor-associated mutations spatially clustered in two ERK2 effector-recruitment domains, yet produced mutants with opposite phenotypes. This approach articulates an allele-characterization framework that can be scaled to meet the goals of genome-guided oncology.

BET-bromodomain inhibition (BETi) has shown pre-clinical promise for MYC-amplified medulloblastoma. However, the mechanisms for its action, and ultimately for resistance, have not been fully defined. Here, using a combination of expression profiling, genome-scale CRISPR/Cas9-mediated loss of function and ORF/cDNA driven rescue screens, and cell-based models of spontaneous resistance, we identify bHLH/homeobox transcription factors and cell-cycle regulators as key genes mediating BETi’s response and resistance. Cells that acquire drug tolerance exhibit a more neuronally differentiated cell-state and expression of lineage-specific bHLH/homeobox transcription factors. However, they do not terminally differentiate, maintain expression of CCND2, and continue to cycle through S-phase. Moreover, CDK4/CDK6 inhibition delays acquisition of resistance. Therefore, our data provide insights about the mechanisms underlying BETi effects and the appearance of resistance and support the therapeutic use of combined cell-cycle inhibitors with BETi in MYC-amplified medulloblastoma.

No abstract

No abstract

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