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Genome editing, specifically CRISPR/Cas9 technology, has revolutionized biomedical research and offers potential cures for genetic diseases. Despite rapid progress, low efficiency of targeted DNA integration and generation of unintended mutations represent major limitations for genome editing applications caused by the interplay with DNA double-strand break repair pathways. To address this, we conduct a large-scale compound library screen to identify targets for enhancing targeted genome insertions. Our study reveals DNA-dependent protein kinase (DNA-PK) as the most effective target to improve CRISPR/Cas9-mediated insertions, confirming previous findings. We extensively characterize AZD7648, a selective DNA-PK inhibitor, and find it to significantly enhance precise gene editing. We further improve integration efficiency and precision by inhibiting DNA polymerase theta (Polϴ). The combined treatment, named 2iHDR, boosts templated insertions to 80% efficiency with minimal unintended insertions and deletions. Notably, 2iHDR also reduces off-target effects of Cas9, greatly enhancing the fidelity and performance of CRISPR/Cas9 gene editing. Low efficiency of target DNA integration remains a challenge in genome engineering. Here the authors perform large-scale compound library and genetic screens to identify targets that enhance gene editing: they see that combined DNA-PK and Polϴ inhibition with potent compounds increases editing efficiency and precision. [ABSTRACT FROM AUTHOR]

Prime editing recently emerged as a next-generation approach for precise genome editing. Here we exploit DNA double-strand break (DSB) repair to develop two strategies that install precise genomic insertions using an SpCas9 nuclease-based prime editor (PEn). We first demonstrate that PEn coupled to a regular prime editing guide RNA (pegRNA) efficiently promotes short genomic insertions through a homology-dependent DSB repair mechanism. While PEn editing leads to increased levels of by-products, it can rescue pegRNAs that perform poorly with a nickase-based prime editor. We also present a small molecule approach that yields increased product purity of PEn editing. Next, we develop a homology-independent PEn editing strategy, which installs genomic insertions at DSBs through the non-homologous end joining pathway (NHEJ). Lastly, we show that PEn-mediated insertions at DSBs prevent Cas9-induced large chromosomal deletions and provide evidence that continuous Cas9-mediated cutting is one of the mechanisms by which Cas9-induced large deletions arise. Altogether, this work expands the current prime editing toolbox by leveraging distinct DNA repair mechanisms including NHEJ, which represents the primary pathway of DSB repair in mammalian cells. Prime editing is a next-generation approach for precision genome engineering. Here the authors design a nuclease-based prime editor that leverages DNA repair pathways for targeted genomic insertions. [ABSTRACT FROM AUTHOR]

Prokaryotic restriction enzymes, recombinases and Cas proteins are powerful DNA engineering and genome editing tools. However, in many primary cell types, the efficiency of genome editing remains low, impeding the development of gene- and cell-based therapeutic applications. A safe strategy for robust and efficient enrichment of precisely genetically engineered cells is urgently required. Here, we screen for mutations in the receptor for Diphtheria Toxin (DT) which protect human cells from DT. Selection for cells with an edited DT receptor variant enriches for simultaneously introduced, precisely targeted gene modifications at a second independent locus, such as nucleotide substitutions and DNA insertions. Our method enables the rapid generation of a homogenous cell population with bi-allelic integration of a DNA cassette at the selection locus, without clonal isolation. Toxin-based selection works in both cancer-transformed and non-transformed cells, including human induced pluripotent stem cells and human primary T-lymphocytes, as well as it is applicable also in vivo, in mice with humanized liver. This work represents a flexible, precise, and efficient selection strategy to engineer cells using CRISPR-Cas and base editing systems. Genome engineering in cell lines or human stem cells often has poor efficiency, limiting the development of research and therapeutic applications. Here, the authors use a toxin-based selection system for precise bi-allelic engineering in cells and in vivo. [ABSTRACT FROM AUTHOR]

Background: Resistance to endocrine treatment in metastatic breast cancer is a major clinical challenge. Clinical tools to predict both drug resistance and possible treatment combination approaches to overcome it are lacking. This unmet need is mainly due to the heterogeneity underlying both the mechanisms involved in resistance development and breast cancer itself.Methods: To study the complexity of the mechanisms involved in the resistance to the selective estrogen receptor degrader (SERD) fulvestrant, we performed comprehensive biomarker analyses using several in vitro models that recapitulate the heterogeneity of developed resistance. We further corroborated our findings in tissue samples from patients treated with fulvestrant.Results: We found that different in vitro models of fulvestrant resistance show variable stability in their phenotypes, which corresponded with distinct genomic alterations. Notably, the studied models presented adaptation at different cell cycle nodes to facilitate progression through the cell cycle and responded differently to CDK inhibitors. Cyclin E2 overexpression was identified as a biomarker of a persistent fulvestrant-resistant phenotype. Comparison of pre- and post-treatment paired tumor biopsies from patients treated with fulvestrant revealed an upregulation of cyclin E2 upon development of resistance. Moreover, overexpression of this cyclin was found to be a prognostic factor determining resistance to fulvestrant and shorter progression-free survival.Conclusions: These data highlight the complexity of estrogen receptor positive breast cancer and suggest that the development of diverse resistance mechanisms dictate levels of ER independence and potentially cross-resistance to CDK inhibitors. [ABSTRACT FROM AUTHOR]

Prokaryotic restriction enzymes, recombinases and Cas proteins are powerful DNA engineering and genome editing tools. However, in many primary cell types, the efficiency of genome editing remains low, impeding the development of gene- and cell-based therapeutic applications. A safe strategy for robust and efficient enrichment of precisely genetically engineered cells is urgently required. Here, we screen for mutations in the receptor for Diphtheria Toxin (DT) which protect human cells from DT. Selection for cells with an edited DT receptor variant enriches for simultaneously introduced, precisely targeted gene modifications at a second independent locus, such as nucleotide substitutions and DNA insertions. Our method enables the rapid generation of a homogenous cell population with bi-allelic integration of a DNA cassette at the selection locus, without clonal isolation. Toxin-based selection works in both cancer-transformed and non-transformed cells, including human induced pluripotent stem cells and human primary T-lymphocytes, as well as it is applicable also in vivo, in mice with humanized liver. This work represents a flexible, precise, and efficient selection strategy to engineer cells using CRISPR-Cas and base editing systems. Genome engineering in cell lines or human stem cells often has poor efficiency, limiting the development of research and therapeutic applications. Here, the authors use a toxin-based selection system for precise bi-allelic engineering in cells and in vivo. [ABSTRACT FROM AUTHOR]

The definitive characterization of common cancer stem cell (CSCs) subpopulations in breast cancer subtypes with distinct genotypic and phenotypic features remains an ongoing challenge. In this study, we have used a non-biased genome wide screening approach to identify transcriptional networks that may be specific to the CSC subpopulations in both luminal and basal breast cancer subtypes. In depth studies of three CSC-enriched breast cancer cell lines representing various subtypes of breast cancer revealed a striking hyperactivation of the mevalonate metabolic pathway in comparison to control cells. The upregulation of metabolic networks is a key feature of tumour cells securing growth and proliferative capabilities and dysregulated mevalonate metabolism has been associated with tumour malignancy and cellular transformation in breast cancer. Furthermore, accumulating evidence suggests that Simvastatin therapy, a mevalonate pathway inhibitor, could affect breast cancer progression and reduce breast cancer recurrence. When detailing the mevalonate pathway in breast cancer using a single-cell qPCR, we identified the mevalonate precursor enzyme, HMGCS1, as a specific marker of CSC-enriched subpopulations within both luminal and basal tumour subtypes. Down-regulation of HMGCS1 also decreased the CSC fraction and function in various model systems, suggesting that HMGCS1 is essential for CSC-activities in breast cancer in general. These data was supported by strong associations between HMGCS1 expression and aggressive features, such as high tumour grade, p53 mutations as well as ER-negativity in lymph node positive breast cancer. Importantly, loss of HMGCS1 also had a much more pronounced effect on CSC-activities compared to treatment with standard doses of Simvastatin. Taken together, this study highlights HMGCS1 as a potential gatekeeper for dysregulated mevalonate metabolism important for CSC-features in both luminal and basal breast cancer subtypes. Pharmacological inhibition of HMGCS1 could therefore be a superior novel treatment approach for breast cancer patients via additional CSC blocking functions. [ABSTRACT FROM AUTHOR]

Cell proliferation includes a series of events that is tightly regulated by several checkpoints and layers of control mechanisms. Most studies have been performed on large cell populations, but detailed understanding of cell dynamics and heterogeneity requires single-cell analysis. Here, we used quantitative real-time PCR, profiling the expression of 93 genes in single-cells from three different cell lines. Individual unsynchronized cells from three different cell lines were collected in different cell cycle phases (G0/G1 - S - G2/M) with variable cell sizes. We found that the total transcript level per cell and the expression of most individual genes correlated with progression through the cell cycle, but not with cell size. By applying the random forests algorithm, a supervised machine learning approach, we show how a multi-gene signature that classifies individual cells into their correct cell cycle phase and cell size can be generated. To identify the most predictive genes we used a variable selection strategy. Detailed analysis of cell cycle predictive genes allowed us to define subpopulations with distinct gene expression profiles and to calculate a cell cycle index that illustrates the transition of cells between cell cycle phases. In conclusion, we provide useful experimental approaches and bioinformatics to identify informative and predictive genes at the single-cell level, which opens up new means to describe and understand cell proliferation and subpopulation dynamics. [ABSTRACT FROM AUTHOR]

Objective: Quantification of small molecule numbers often requires preamplification to generate enough copies for accurate downstream enumerations. Here, we studied experimental parameters in targeted preamplification and their effects on downstream quantitative real-time PCR (qPCR). Methods: To evaluate different strategies, we monitored the preamplification reaction in real-time using SYBR Green detection chemistry followed by melting curve analysis. Furthermore, individual targets were evaluated by qPCR. Result: The preamplification reaction performed best when a large number of primer pairs was included in the primer pool. In addition, preamplification efficiency, reproducibility and specificity were found to depend on the number of template molecules present, primer concentration, annealing time and annealing temperature. The amount of nonspecific PCR products could also be reduced about 1000-fold using bovine serum albumin, glycerol and formamide in the preamplification. Conclusion: On the basis of our findings, we provide recommendations how to perform robust and highly accurate targeted preamplification in combination with qPCR or next-generation sequencing. [ABSTRACT FROM AUTHOR]

In the present work, the objective has been to analyse the compatibility of plant and human transcriptional machinery. The experiments revealed that nuclear import and export are conserved among plants and mammals. Further it has been shown that transactivation of a human promoter occurs by human transcription factor NF-κB in plant cells, demonstrating that the transcriptional machinery is highly conserved in both kingdoms. Functionality was also seen for regulatory elements of NF-κB such as its inhibitor IκB isoform a that negatively regulated the transactivation activity of the p50/RelA heterodimer by interaction with NF-κB in plant cells. Nuclear export of RelA could be demonstrated by FRAP-measurements so that RelA shows nucleo-cytoplasmic shuttling as reported for RelA in mammalian cells. The data reveals the high level of compatibility of human transcriptional elements with the plant transcriptional machinery. Thus, Arabidopsis thaliana mesophyll protoplasts might provide a new heterologous expression system for the investigation of the human NF-κB signaling pathways. The system successfully enabled the controlled manipulation of NF-κB activity. We suggest the plant protoplast system as a tool for reconstitution and analyses of mammalian pathways and for direct observation of responses to e.g. pharmaceuticals. The major advantage of the system is the absence of interference with endogenous factors that affect and crosstalk with the pathway. [ABSTRACT FROM AUTHOR]

These authors contributed equally: Nina Akrap, Silvia Cerboni. In the original version of this Article the Acknowledgements failed to state support from the European Union's Horizon 2020 research and innovation program by grant number 814316. [Extracted from the article]