CDK7 inhibition suppresses super-enhancer-linked oncogenic transcription in MYCN-driven cancer.

The MYC oncoproteins are thought to stimulate tumor cell growth and proliferation through amplification of gene transcription, a mechanism that has thwarted most efforts to inhibit MYC function as potential cancer therapy. Using a covalent inhibitor of cyclin-dependent kinase 7 (CDK7) to disrupt the transcription of amplified MYCN in neuroblastoma cells, we demonstrate downregulation of the oncoprotein with consequent massive suppression of MYCN-driven global transcriptional amplification. This response translated to significant tumor regression in a mouse model of high-risk neuroblastoma, without the introduction of systemic toxicity. The striking treatment selectivity of MYCN-overexpressing cells correlated with preferential downregulation of super-enhancer-associated genes, including MYCN and other known oncogenic drivers in neuroblastoma. These results indicate that CDK7 inhibition, by selectively targeting the mechanisms that promote global transcriptional amplification in tumor cells, may be useful therapy for cancers that are driven by MYC family oncoproteins.

S. cerevisiae chromosomes biorient via gradual resolution of syntely between S phase and anaphase.

Following DNA replication, eukaryotic cells must biorient all sister chromatids prior to cohesion cleavage at anaphase. In animal cells, sister chromatids gradually biorient during prometaphase, but current models of mitosis in S. cerevisiae assume that biorientation is established shortly after S phase. This assumption is based on the observation of a bilobed distribution of yeast kinetochores early in mitosis and suggests fundamental differences between yeast mitosis and mitosis in animal cells. By applying super-resolution imaging methods, we show that yeast and animal cells share the key property of gradual and stochastic chromosome biorientation. The characteristic bilobed distribution of yeast kinetochores, hitherto considered synonymous for biorientation, arises from kinetochores in mixed attachment states to microtubules, the length of which discriminates bioriented from syntelic attachments. Our results offer a revised view of mitotic progression in S. cerevisiae that augments the relevance of mechanistic information obtained in this powerful genetic system for mammalian mitosis.

BORIS promotes chromatin regulatory interactions in treatment-resistant cancer cells.

The CCCTC-binding factor (CTCF), which anchors DNA loops that organize the genome into structural domains, has a central role in gene control by facilitating or constraining interactions between genes and their regulatory elements1,2. In cancer cells, the disruption of CTCF binding at specific loci by somatic mutation3,4 or DNA hypermethylation5 results in the loss of loop anchors and consequent activation of oncogenes. By contrast, the germ-cell-specific paralogue of CTCF, BORIS (brother of the regulator of imprinted sites, also known as CTCFL)6, is overexpressed in several cancers7-9, but its contributions to the malignant phenotype remain unclear. Here we show that aberrant upregulation of BORIS promotes chromatin interactions in ALK-mutated, MYCN-amplified neuroblastoma10 cells that develop resistance to ALK inhibition. These cells are reprogrammed to a distinct phenotypic state during the acquisition of resistance, a process defined by the initial loss of MYCN expression followed by subsequent overexpression of BORIS and a concomitant switch in cellular dependence from MYCN to BORIS. The resultant BORIS-regulated alterations in chromatin looping lead to the formation of super-enhancers that drive the ectopic expression of a subset of proneural transcription factors that ultimately define the resistance phenotype. These results identify a previously unrecognized role of BORIS-to promote regulatory chromatin interactions that support specific cancer phenotypes.

Methylation-Sensitive Restriction Enzyme Quantitative Polymerase Chain Reaction Enables Rapid, Accurate, and Precise Detection of Methylation Status of the Regulatory T Cell (Treg)-Specific Demethylation Region in Primary Human Tregs.

Human regulatory T cells (Tregs) have been implicated in cancer immunotherapy and are also an emerging cellular therapeutic for the treatment of multiple indications. Although Treg stability during ex vivo culture has improved, methods to assess Treg stability such as bisulfite Sanger sequencing to determine the methylation status of the Treg-specific demethylated region (TSDR) have remained unchanged. Bisulfite Sanger sequencing is not only costly and cumbersome to perform, it is inaccurate because of relatively low read counts. Bisulfite next-generation sequencing, although more accurate, is a less accessible method. In this study, we describe the application of methylation-sensitive restriction enzymes (MSRE) and quantitative PCR (qPCR) to determine the methylation status of the TSDR. Using known ratios of Tregs and non-Tregs, we show that MSRE-qPCR can distinguish the methylation status of the TSDR in populations of cells containing increasing proportions of Tregs from 0 to 100%. In a comparison with values obtained from an established bisulfite next-generation sequencing approach for determining the methylation status of the TSDR, our MSRE-qPCR results were within 5% on average for all samples with a high percentage (>70%) of Tregs, reinforcing that MSRE-qPCR can be completed in less time than other methods with the same level of accuracy. The value of this assay was further demonstrated by quantifying differences in TSDR methylation status of Tregs treated with and without rapamycin during an ex vivo expansion culture. Together, we show that our novel application of the MSRE-qPCR to the TSDR is an optimal assay for accurate assessment of Treg purity.

Proteomic Landscape of Tissue-Specific Cyclin E Functions in Vivo.

E-type cyclins (cyclins E1 and E2) are components of the cell cycle machinery that has been conserved from yeast to humans. The major function of E-type cyclins is to drive cell division. It is unknown whether in addition to their 'core' cell cycle functions, E-type cyclins also perform unique tissue-specific roles. Here, we applied high-throughput mass spectrometric analyses of mouse organs to define the repertoire of cyclin E protein partners in vivo. We found that cyclin E interacts with distinct sets of proteins in different compartments. These cyclin E interactors are highly enriched for phosphorylation targets of cyclin E and its catalytic partner, the cyclin-dependent kinase 2 (Cdk2). Among cyclin E interactors we identified several novel tissue-specific substrates of cyclin E-Cdk2 kinase. In proliferating compartments, cyclin E-Cdk2 phosphorylates Lin proteins within the DREAM complex. In the testes, cyclin E-Cdk2 phosphorylates Mybl1 and Dmrtc2, two meiotic transcription factors that represent key regulators of spermatogenesis. In embryonic and adult brains cyclin E interacts with proteins involved in neurogenesis, while in adult brains also with proteins regulating microtubule-based processes and microtubule cytoskeleton. We also used quantitative proteomics to demonstrate re-wiring of the cyclin E interactome upon ablation of Cdk2. This approach can be used to study how protein interactome changes during development or in any pathological state such as aging or cancer.

UDiTaS™, a genome editing detection method for indels and genome rearrangements.

BACKGROUND: Understanding the diversity of repair outcomes after introducing a genomic cut is essential for realizing the therapeutic potential of genomic editing technologies. Targeted PCR amplification combined with Next Generation Sequencing (NGS) or enzymatic digestion, while broadly used in the genome editing field, has critical limitations for detecting and quantifying structural variants such as large deletions (greater than approximately 100 base pairs), inversions, and translocations. RESULTS: To overcome these limitations, we have developed a Uni-Directional Targeted Sequencing methodology, UDiTaS, that is quantitative, removes biases associated with variable-length PCR amplification, and can measure structural changes in addition to small insertion and deletion events (indels), all in a single reaction. We have applied UDiTaS to a variety of samples, including those treated with a clinically relevant pair of S. aureus Cas9 single guide RNAs (sgRNAs) targeting CEP290, and a pair of S. pyogenes Cas9 sgRNAs at T-cell relevant loci. In both cases, we have simultaneously measured small and large edits, including inversions and translocations, exemplifying UDiTaS as a valuable tool for the analysis of genome editing outcomes. CONCLUSIONS: UDiTaS is a robust and streamlined sequencing method useful for measuring small indels as well as structural rearrangements, like translocations, in a single reaction. UDiTaS is especially useful for pre-clinical and clinical application of gene editing to measure on- and off-target editing, large and small.

Robust lineage reconstruction from high-dimensional single-cell data.

Single-cell gene expression data provide invaluable resources for systematic characterization of cellular hierarchy in multi-cellular organisms. However, cell lineage reconstruction is still often associated with significant uncertainty due to technological constraints. Such uncertainties have not been taken into account in current methods. We present ECLAIR (Ensemble Cell Lineage Analysis with Improved Robustness), a novel computational method for the statistical inference of cell lineage relationships from single-cell gene expression data. ECLAIR uses an ensemble approach to improve the robustness of lineage predictions, and provides a quantitative estimate of the uncertainty of lineage branchings. We show that the application of ECLAIR to published datasets successfully reconstructs known lineage relationships and significantly improves the robustness of predictions. ECLAIR is a powerful bioinformatics tool for single-cell data analysis. It can be used for robust lineage reconstruction with quantitative estimate of prediction accuracy.

Bifurcation analysis of single-cell gene expression data reveals epigenetic landscape.

We present single-cell clustering using bifurcation analysis (SCUBA), a novel computational method for extracting lineage relationships from single-cell gene expression data and modeling the dynamic changes associated with cell differentiation. SCUBA draws techniques from nonlinear dynamics and stochastic differential equation theories, providing a systematic framework for modeling complex processes involving multilineage specifications. By applying SCUBA to analyze two complementary, publicly available datasets we successfully reconstructed the cellular hierarchy during early development of mouse embryos, modeled the dynamic changes in gene expression patterns, and predicted the effects of perturbing key transcriptional regulators on inducing lineage biases. The results were robust with respect to experimental platform differences between RT-PCR and RNA sequencing. We selectively tested our predictions in Nanog mutants and found good agreement between SCUBA predictions and the experimental data. We further extended the utility of SCUBA by developing a method to reconstruct missing temporal-order information from a typical single-cell dataset. Analysis of a hematopoietic dataset suggests that our method is effective for reconstructing gene expression dynamics during human B-cell development. In summary, SCUBA provides a useful single-cell data analysis tool that is well-suited for the investigation of developmental processes.

A highly efficient transgene knock-in technology in clinically relevant cell types.

Inefficient knock-in of transgene cargos limits the potential of cell-based medicines. In this study, we used a CRISPR nuclease that targets a site within an exon of an essential gene and designed a cargo template so that correct knock-in would retain essential gene function while also integrating the transgene(s) of interest. Cells with non-productive insertions and deletions would undergo negative selection. This technology, called SLEEK (SeLection by Essential-gene Exon Knock-in), achieved knock-in efficiencies of more than 90% in clinically relevant cell types without impacting long-term viability or expansion. SLEEK knock-in rates in T cells are more efficient than state-of-the-art TRAC knock-in with AAV6 and surpass more than 90% efficiency even with non-viral DNA cargos. As a clinical application, natural killer cells generated from induced pluripotent stem cells containing SLEEK knock-in of CD16 and mbIL-15 show substantially improved tumor killing and persistence in vivo.