scholarly journals mslp: a comprehensive pipeline in predicting cancer mutations specific synthetic lethal partners

2021 ◽  
Author(s):  
Chunxuan Shao
Keyword(s):  
Cell Viability ◽  
Cell Lines ◽  
Large Scale ◽  
Signal To Noise Ratio ◽  
Model Organisms ◽  
Lethal Gene ◽  
Synthetic Lethal ◽  
Cancer Mutations ◽  
Set Up ◽  
Context Specific

Background: Mutation specific synthetic lethal partners (SLPs) offer significant insights in identifying novel targets and designing personalized treatments in cancer studies. Large scale genetic screens in cell lines and model organisms provide crucial resources for mining SLPs, yet those experiments are expensive and might be difficult to set up. Various computational methods have been proposed to predict the potential SLPs from different perspectives. However, those efforts are hampered by the low signal-to-noise ratio in simple correlation based approaches, or incomplete reliable training sets in supervised approaches. Results: Here we present mslp, a comprehensive pipeline to identify potential SLPs via integrating genomic and transcriptomic datasets from both patient tumours and cancer cell lines. Leveraging cutting-edges algorithms, we identify a broad spectrum of primary SLPs for mutations presented in patient tumours. Further, for mutations detected in cell lines, we develop the idea of consensus SLPs which are also identified as screen hits, and show consistency impact on cell viability. Applied in real datasets, we successfully identified known synthetic lethal gene pairs. Remarkably, genetic screen results suggested that consensus SLPs have a significant impact on cell viability compared to common hits. Conclusions: Mslp is a powerful and flexible pipeline to identify potential SLPs in a cancer context-specific manner, which might aid in drug developments and precise medicines in cancer treatments. The pipeline is implemented in R and freely available in github.

P04.20 The role of YAP in Glioblastoma cell lines

2021 ◽  
Vol 23 (Supplement_2) ◽  
pp. ii22-ii23
Author(s):  
G Casati ◽  
L Giunti ◽  
A Iorio ◽  
A Marturano ◽  
I Sardi
Keyword(s):  
Cell Viability ◽  
Cell Lines ◽  
Western Blotting ◽  
Cytotoxic Effect ◽  
Target Genes ◽  
Hippo Pathway ◽  
Combined Treatment ◽  
Set Up ◽  
The Hippo Pathway

Abstract BACKGROUND Glioblastoma (GBM) is a primary human malignant brain tumor, the most common in adults. Several studies have highlighted the Hippo-pathway as a cancer signalling network. The Hippo pathway is an evolutionarily conserved signal cascade, which is involved in the control of organ growth. Dysregulations among this pathway have been found in lung, ovarian, liver and colorectal cancer. The key downstream effector of the Hippo-pathway is the Yes-associated protein (YAP); in the nucleus, its function as transcription co-activator is to interact with transcription factors, resulting in the expression of target genes involved in pro-proliferating and anti-apoptotic programs. MATERIAL AND METHODS Using western blotting analysis, we determined the nuclear expression of YAP on three GBM cell lines (U87MG, T98G and A172). To investigate which inhibitors against the Hippo-pathway were the most efficient, we performed a cytotoxic assay: we treated all the three cell lines with different inhibitors such as Verteporfin (VP), Cytochalasin D (CIT), Latrunculin A (LAT), Dobutamine (DOB) and Y27632. Afterwards, we performed a treatment using Doxorubicin (DOX) combined with the inhibitors, evaluating its cytotoxic effect on our cell lines, through cell viability experiments. More western blotting experiments were performed to investigate the oncogenic role of YAP at nucleus level. Furthermore, preliminary experiments have been conducted in order to investigate the apoptosis, senescence and autophagy modulation due to the Hippo-pathway. RESULTS We showed our cell lines express nuclear YAP. We assessed the efficiency of the main inhibitors against Hippo-pathway, proving that VP, LAT A and CIT show a strong cytostatic effect, linked to time increase; plus we saw a cytotoxic effect on T98G. The association of DOX with selected inhibitors is able to reduce cell viability and nuclear YAP expression rate in all three GBM lines. Finally, preliminary experiments were set up to assess how and if the mechanisms of apoptosis, autophagy and senescence were affected by the Hippo-pathway. The combination of DOX with inhibitors promotes resistance to apoptosis. CONCLUSION Our results show that nuclear YAP is present in all tumor lines, thus confirming that this molecular pathway is functioning in GBM lines. Nuclear YAP is more highly expressed after DOX administration. Moreover, the combined treatment (DOX with Hippo-pathway inhibitors) reduces both cell proliferation and viability, and increases the rate of apoptosis. Preliminary experiments on senescence and autophagy were used to determine the best Hippo-pathway inhibitor. These data demonstrate that the Hippo-pathway plays a crucial role in GBM proliferation and resistance to apoptosis. Inhibiting this pathway and in particular the transcription factor YAP, in association with DOX, might be an excellent therapeutic target.

scholarly journals Core Transcriptional Regulatory Circuitries in AML

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 280-280
Author(s):  
Maxim Pimkin ◽  
Juliana Xavier Ferrucio ◽  
Neekesh Vijay Dharia ◽  
Taku Harada ◽  
Andrew Kossenkov ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Cell Lines ◽  
Large Scale ◽  
Cell Function ◽  
Functional Dependency ◽  
Drop Out ◽  
Feed Forward ◽  
Knock Out ◽  
Transcriptional Regulatory ◽  
Context Specific

Core transcriptional regulatory circuitries (CRCs) are tightly integrated networks of master transcription factors (TFs) that establish and maintain lineage-specific programs of gene expression. We hypothesized that divergent CRCs establish distinct subtypes of acute myeloid leukemia (AML). CRCs are defined as sets of master TFs that are marked by superenhancers (SEs) and bind to their own genes and those of the other core TFs, forming feed-forward auto-regulatory loops. We have performed large-scale H3K27ac ChIP-seq experiments to map the SE landscape in 20 AML cell lines, 3 normal hematopoietic tissues and 50 patient-derived xenograft (PDX) models of human AML. These experiments highlighted a core set of SE-marked, highly expressed TF genes shared by all the examined AML subtypes, corresponding to a putative pan-AML CRC. Importantly, a significant majority (>70%) of these transcription factors correspond to AML-specific genetic dependencies in the Project Achilles genome-scale RNAi and CRISPR-Cas9 screening efforts undertaken by colleagues at the Broad Institute, confirming the specific reliance of AML on these TFs for survival. We reasoned that CRCs can be predicted by integrating the epigenomic and functional dependency datasets. Indeed, intersecting SE-marked TF genes with preferential AML dependencies resulted in 32 candidate TFs. We have validated these TFs as AML dependencies in a low-throughput system with lentiviral delivery of Cas9 and specific gRNAs. ChiP-seq experiments with antibodies against 23 of these candidates (GATA2, PU1, IRF8, GSE1, GFI1, MEIS1, LYL1, CEBPA, MEF2D, MEF2C, IKZF1, ZEB2, FLI1, ETV6, ELF2, MAX, RUNX1, MYB, IRF2BP2, LMO2, SP1, ZMYND8, MYC) resulted in nearly 100% validation rate. They demonstrated that CRC TFs tend to co-occupy DNA and bind their own and each other's promoters and SEs, suggesting that CRC members function in higher-order chromatin complexes and establish reciprocal feed-forward regulatory loops. Analysis of TF co-binding revealed 237,636 unique binding sites, with most occupied by at least two CRC TFs. Specific combinatorial patterns of TF binding appear to be associated with promoters, enhancers and super-enhancers. Importantly, in addition to the pan-AML CRCs, highly specific dependencies restricted only to a subset of AML cell lines can be accurately predicted from examination of divergent (subtype-specific) AML CRCs, lending support to our hypothesis that context-specific vulnerabilities can be robustly inferred from a systematic study of TF circuits. Specifically, we identified MEF2D and IRF8 as TFs that are selectively marked by SEs in a subset of AML cell lines and PDXs, most notably in samples carrying an MLL rearrangement. At the same time, these genes are strong preferential dependencies in a subset of AML cell lines, most of which also carry an MLL fusion. This suggests specific roles of IRF8 and MEF2D in MLL-induced leukemogenesis. Interestingly, functional dependency scores for these two TFs show an extremely high degree of correlation, indicating tightly integrated functions. While IRF8 is a known regulator of macrophage/dendritic cell function, MEF2D has no recognized roles in hematopoiesis. We have validated MEF2D as a dependency in a low-throughput CRISPR-Cas9 drop out experiment in an MLL-rearranged cell line. At the same time, we observed no functional effect of MEF2D knock out in a human CD34+ cell colony forming assay. This confirms context-specific transcriptional addiction to MEF2D induced by an MLL fusion and suggests a potential "Achilles heel" for leukemia-specific therapy with little or no detrimental effects on normal hematopoiesis. In summary, our data allow us to draw the following conclusions: 1) Intersection of lineage-restricted gene dependencies with SE profiling permits highly specific discovery of CRCs. 2) Transcriptional control in AML is orchestrated by a large CRC of >30 essential TFs. 3) Divergent CRCs are diagnostic of cancer- and context-specific transcriptional addiction. 4) AML CRC is a highly integrated network of co-binding TFs that orchestrate both promoter- and enhancer-centric regulation. Figure Disclosures Lin: Syros Pharmaceuticals: Equity Ownership, Patents & Royalties. Stegmaier:Novartis: Research Funding; Rigel Pharmaceuticals: Consultancy. Orkin:Syros: Consultancy; Novartis: Consultancy.

scholarly journals Learning epistatic gene interactions from perturbation screens

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254491
Author(s):  
Kieran Elmes ◽  
Fabian Schmich ◽  
Ewa Szczurek ◽  
Jeremy Jenkins ◽  
Niko Beerenwinkel ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Gene Interactions ◽  
Data Sets ◽  
Lethal Gene ◽  
Interaction Coefficients ◽  
Epistatic Interactions ◽  
Synthetic Lethal ◽  
Rnai Screening ◽  
Wide Range ◽  
Perturbation Data

The treatment of complex diseases often relies on combinatorial therapy, a strategy where drugs are used to target multiple genes simultaneously. Promising candidate genes for combinatorial perturbation often constitute epistatic genes, i.e., genes which contribute to a phenotype in a non-linear fashion. Experimental identification of the full landscape of genetic interactions by perturbing all gene combinations is prohibitive due to the exponential growth of testable hypotheses. Here we present a model for the inference of pairwise epistatic, including synthetic lethal, gene interactions from siRNA-based perturbation screens. The model exploits the combinatorial nature of siRNA-based screens resulting from the high numbers of sequence-dependent off-target effects, where each siRNA apart from its intended target knocks down hundreds of additional genes. We show that conditional and marginal epistasis can be estimated as interaction coefficients of regression models on perturbation data. We compare two methods, namely glinternet and xyz, for selecting non-zero effects in high dimensions as components of the model, and make recommendations for the appropriate use of each. For data simulated from real RNAi screening libraries, we show that glinternet successfully identifies epistatic gene pairs with high accuracy across a wide range of relevant parameters for the signal-to-noise ratio of observed phenotypes, the effect size of epistasis and the number of observations per double knockdown. xyz is also able to identify interactions from lower dimensional data sets (fewer genes), but is less accurate for many dimensions. Higher accuracy of glinternet, however, comes at the cost of longer running time compared to xyz. The general model is widely applicable and allows mining the wealth of publicly available RNAi screening data for the estimation of epistatic interactions between genes. As a proof of concept, we apply the model to search for interactions, and potential targets for treatment, among previously published sets of siRNA perturbation screens on various pathogens. The identified interactions include both known epistatic interactions as well as novel findings.

scholarly journals Synthetic lethal screening identifies existing drugs with selective viability effects on Neurofibromatosis type-1 model systems

2021 ◽  
Author(s):  
Yuanli Wang ◽  
Megan Stevens ◽  
Torrey R Mandigo ◽  
Stephanie J Bouley ◽  
Aditi Sharma ◽  
...  
Keyword(s):  
Cell Viability ◽  
Cell Lines ◽  
Neurofibromatosis Type 1 ◽  
Mutant Cell ◽  
Neurofibromatosis Type ◽  
Model Systems ◽  
Synthetic Lethal ◽  
Mutant Cells

Neurofibromatosis type 1 (NF1) is a genetic multi-system disorder. Symptoms include near universal benign neurofibromas, as well as malignant tumours, including generally fatal malignant peripheral nerve sheath tumours. There are limited therapies for any NF1-associated tumours; therefore, there is a clear clinical need to discover new drugs that specifically target NF1-deficient tumour cells. Using a Drosophila NF1-KO cell model, we used synthetic lethal screening to identify candidate drug targets for NF1-deficient tumours and performed statistical enrichment analysis to identify further targets. We then assessed the top 72 candidate synthetic lethal partner genes to NF1 using Variable Dose Analysis, resulting in 15 candidate genes that decreased NF1-KO viability by >10% and were novel druggable targets for NF1. Autophagy inhibitors Chloroquine (CQ) and Bafilomycin A1 resulted in a significant reduction in NF1-KO cell viability, which was conserved in a panel of human NF1 mutant cell lines. AZT and Enzalutamide also selectively reduced NF1 mutant cell viability in human cell lines. Furthermore, the effect of CQ was conserved in a Drosophila NF1-mutant in vivo model. This study highlights two key points: 1) The use of Drosophila cells as a model to screen for drugs specifically targeting NF1 mutant cells was highly successful as candidate interactions were conserved across a panel of human NF1 mutant cells and an in vivo fly NF1 mutant model, and 2) NF1-deficient cells have vulnerability to disruption of the autophagy pathway, telomerase activity, and AR activity. These pathways/drugs represent promising targets for the potential treatment of NF1-associated tumours.

scholarly journals Reducing the Cost of Rapid Antigen Tests through Swab Pooling and Extraction in a Device

2021 ◽  
Author(s):  
Tim Berking ◽  
Sabrina G. Lorenz ◽  
Alexander Ulrich ◽  
Joachim Greiner ◽  
Clemens Richert
Keyword(s):  
Large Scale ◽  
Signal To Noise Ratio ◽  
Point Of Care ◽  
Positive Control ◽  
Extraction Buffer ◽  
Large Scale Testing ◽  
Antigen Tests ◽  
Set Up ◽  
Cost Of Materials ◽  
The Cost

AbstractThe COVID-19 pandemic places a significant stress on the viral testing capabilities of many countries. The value of rapid point-of-care (PoC) antigen tests is becoming increasingly clear, but implementing frequent large scale testing is costly. We have developed an inexpensive device for pooling swabs, extracting specimens, and detecting viral antigens with a commercial lateral flow assay detecting the nucleocapsid protein of SARS-CoV-2 as antigen. The holder of the device can be produced locally through 3D printing. The extraction and the elution can be performed with the entire set-up encapsulated in a transparent bag, minimizing the risk of infection for the operator. With 6 swabs holding approx. 0.1 mL specimen each and 0.35 mL extraction buffer, 43±6 % (n= 8) of the signal for an individual extraction of a positive control standard was obtained. Image analysis still showed a signal-to-noise ratio of ≥ 7 upon further eight-fold dilution. Our current total cost of materials is below $ 2 per tested person or 20% of our cost for an individual PoC test. These findings suggest that pooling can make frequent testing more affordable for schools, universities and other institutions, without decreasing sensitivity to an unacceptable level. Further validation of the method is required.

scholarly journals A global cancer data integrator reveals principles of synthetic lethality, sex disparity and immunotherapy.

2021 ◽  
Author(s):  
Christopher H Yogodzinski ◽  
Abolfazl Arab ◽  
Justin R Pritchard ◽  
Hani Goodarzi ◽  
Luke Gilbert
Keyword(s):  
Cancer Cell ◽  
Cell Biology ◽  
Cancer Biology ◽  
Large Scale ◽  
Synthetic Lethality ◽  
Data Retrieval ◽  
Lethal Gene ◽  
Synthetic Lethal ◽  
Cancer Data ◽  
Sex Disparity

Advances in cancer biology are increasingly dependent on integration of heterogeneous datasets. Large scale efforts have systematically mapped many aspects of cancer cell biology; however, it remains challenging for individual scientists to effectively integrate and understand this data. We have developed a new data retrieval and indexing framework that allows us to integrate publicly available data from different sources and to combine publicly available data with new or bespoke datasets. Beyond a database search, our approach empowered testable hypotheses of new synthetic lethal gene pairs, genes associated with sex disparity, and immunotherapy targets in cancer. Our approach is straightforward to implement, well documented and is continuously updated which should enable individual users to take full advantage of efforts to map cancer cell biology.

scholarly journals WRN Helicase is a Synthetic Lethal Target in Microsatellite Unstable Cancers

2018 ◽  
Author(s):  
Edmond Chan ◽  
Tsukasa Shibue ◽  
James McFarland ◽  
Benjamin Gaeta ◽  
Justine McPartlan ◽  
...  
Keyword(s):  
Dna Repair ◽  
Cell Lines ◽  
Large Scale ◽  
Synthetic Lethality ◽  
Cancer Therapeutics ◽  
Dna Helicase ◽  
Dna Breaks ◽  
Synthetic Lethal ◽  
Dna Mismatch ◽  
Double Strand Dna Breaks

Synthetic lethality, an interaction whereby the co-occurrence of two or more genetic events lead to cell death but one event alone does not, can be exploited to develop novel cancer therapeutics. DNA repair processes represent attractive synthetic lethal targets since many cancers exhibit an impaired DNA repair pathway, which can lead these cells to become dependent on specific repair proteins. The success of poly (ADP-ribose) polymerase 1 (PARP-1) inhibitors in homologous recombination-deficient cancers highlights the potential of this approach in clinical oncology. Hypothesizing that other DNA repair defects would give rise to alternative synthetic lethal relationships, we asked if there are specific dependencies in cancers with microsatellite instability (MSI), which results from impaired DNA mismatch repair (MMR). Here we analyzed data from large-scale CRISPR/Cas9 knockout and RNA interference (RNAi) silencing screens and found that the RecQ DNA helicase was selectively essential in MSI cell lines, yet dispensable in microsatellite stable (MSS) cell lines. WRN depletion induced double-strand DNA breaks and promoted apoptosis and cell cycle arrest selectively in MSI models. MSI cancer models specifically required the helicase activity, but not the exonuclease activity of WRN. These findings expose WRN as a synthetic lethal vulnerability and promising drug target in MSI cancers.

scholarly journals High-throughput microfluidic cell sorting platform (MICS)

2019 ◽  
Author(s):  
David Philpott ◽  
Peter Aldridge ◽  
Barbara Mair ◽  
Randy Atwal ◽  
Sanna Masud ◽  
...  
Keyword(s):  
Protein Expression ◽  
Cell Viability ◽  
High Throughput ◽  
Cell Sorting ◽  
Mammalian Cells ◽  
Large Scale ◽  
Genetic Screens ◽  
Large Numbers ◽  
Conventional Cell ◽  
Set Up

Abstract Genome-scale functional genetic screens can be used to interrogate determinants of protein expression modulation of a target of interest. Such phenotypic screening approaches typically require sorting of large numbers of cells (>108). In conventional cell sorting techniques (i.e. fluorescence-activated cell sorting), sorting time, associated with high instrument and operating costs and loss of cell viability, are limiting to the scalability and throughput of these screens. We recently established a rapid and scalable high-throughput microfluidic cell sorting platform (MICS) using immunomagnetic nanoparticles to sort cells in parallel capable of sorting more than 108 HAP1 cells in under one hour while maintaining high levels of cell viability (Ref. 1). This protocol outlines how to set-up MICS for large-scale phenotypic screens in mammalian cells. We anticipate this platform being used for genome-wide functional genetic screens as well as other applications requiring the sorting of large numbers of cells based on protein expression.

scholarly journals Integrative analysis of large-scale loss-of-function screens identifies robust cancer-associated genetic interactions

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Christopher J Lord ◽  
Niall Quinn ◽  
Colm J Ryan
Keyword(s):  
Protein Interaction ◽  
Large Scale ◽  
Interaction Network ◽  
Genetic Interactions ◽  
Driver Gene ◽  
Loss Of Function ◽  
Lethal Effects ◽  
Synthetic Lethal ◽  
Protein Protein Interaction ◽  
Context Specific

Genetic interactions, including synthetic lethal effects, can now be systematically identified in cancer cell lines using high-throughput genetic perturbation screens. Despite this advance, few genetic interactions have been reproduced across multiple studies and many appear highly context-specific. Here, by developing a new computational approach, we identified 220 robust driver-gene associated genetic interactions that can be reproduced across independent experiments and across non-overlapping cell line panels. Analysis of these interactions demonstrated that: (i) oncogene addiction effects are more robust than oncogene-related synthetic lethal effects; and (ii) robust genetic interactions are enriched among gene pairs whose protein products physically interact. Exploiting the latter observation, we used a protein–protein interaction network to identify robust synthetic lethal effects associated with passenger gene alterations and validated two new synthetic lethal effects. Our results suggest that protein–protein interaction networks can be used to prioritise therapeutic targets that will be more robust to tumour heterogeneity.

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