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

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Christopher Yogodzinski ◽  
Abolfazl Arab ◽  
Justin R. Pritchard ◽  
Hani Goodarzi ◽  
Luke A. Gilbert
Keyword(s):  
Cancer Cell ◽  
Cell Biology ◽  
Cancer Biology ◽  
Large Scale ◽  
Synthetic Lethality ◽  
Data Retrieval ◽  
Lethal Gene ◽  
Cancer Data ◽  
Rapid Generation ◽  
Sex Disparity

Abstract Background 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. Results 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. Our approach, which we have named the cancer data integrator (CanDI), is straightforward to implement, is well documented, and is continuously updated which should enable individual users to take full advantage of efforts to map cancer cell biology. We show that CanDI empowered testable hypotheses of new synthetic lethal gene pairs, genes associated with sex disparity, and immunotherapy targets in cancer. Conclusions CanDI provides a flexible approach for large-scale data integration in cancer research enabling rapid generation of hypotheses. The CanDI data integrator is available at https://github.com/GilbertLabUCSF/CanDI.

Synthetic Lethality: From Research to Precision Cancer Nanomedicine

2018 ◽  
Vol 18 (4) ◽  
pp. 337-346 ◽  
Author(s):  
Anuradha Gupta ◽  
Anas Ahmad ◽  
Aqib Iqbal Dar ◽  
Rehan Khan
Keyword(s):  
Cancer Cell ◽  
Mutational Analysis ◽  
Synthetic Lethality ◽  
Therapeutic Index ◽  
Genetic Alterations ◽  
Cancer Drug ◽  
Lethal Gene ◽  
Synthetic Lethal ◽  
Therapeutic Molecules ◽  
Drug Resistant Phenotype

Cancer is an evolutionary disease with multiple genetic alterations, accumulated due to chromosomal instability and/or aneuploidy and it sometimes acquires drug-resistant phenotype also. Whole genome sequencing and mutational analysis helped in understanding the differences among persons for predisposition of a disease and its treatment non-responsiveness. Thus, molecular targeted therapies came into existence. Among them, the concept of synthetic lethality have enthralled great attention as it is a pragmatic approach towards exploiting cancer cell specific mutations to specifically kill cancer cells without affecting normal cells and thus enhancing anti-cancer drug therapeutic index. Thus, this approach helped in discovering new therapeutic molecules for development of precision medicine. Nanotechnology helped in delivering these molecules to the target site in an effective concentration thus reducing off target effects of drugs, dose and dosage frequency drugs. Researchers have tried to deliver siRNA targeting synthetic lethal partner for target cancer cell killing by incorporating it in nanoparticles and it has shown efficacy by preventing tumor progression. This review summarizes the brief introduction of synthetic lethality, and synthetic lethal gene interactions, with a major focus on its therapeutic anticancer potential with the application of nanotechnology for development of personalized medicine.

scholarly journals SL-BioDP: Multi-Cancer Interactive Tool for Prediction of Synthetic Lethality and Response to Cancer Treatment

Cancers ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1682 ◽  
Author(s):  
Xiang Deng ◽  
Shaoli Das ◽  
Kristin Valdez ◽  
Kevin Camphausen ◽  
Uma Shankavaram
Keyword(s):  
Clinical Relevance ◽  
Synthetic Lethality ◽  
Drug Efficacy ◽  
Synthetic Lethal ◽  
Cancer Data ◽  
Cancer Pathways ◽  
Kaplan Meier ◽  
Survival Pathways ◽  
Synthetic Lethal Interactions ◽  
Cancer Genome Atlas

Synthetic lethality exploits the phenomenon that a mutation in a cancer gene is often associated with new vulnerability which can be uniquely targeted therapeutically, leading to a significant increase in favorable outcome. DNA damage and survival pathways are among the most commonly mutated networks in human cancers. Recent data suggest that synthetic lethal interactions between a tumor defect and a DNA repair pathway can be used to preferentially kill tumor cells. We recently published a method, DiscoverSL, using multi-omic cancer data, that can predict synthetic lethal interactions of potential clinical relevance. Here, we apply the generality of our models in a comprehensive web tool called Synthetic Lethality Bio Discovery Portal (SL-BioDP) and extend the cancer types to 18 cancer genome atlas cohorts. SL-BioDP enables a data-driven computational approach to predict synthetic lethal interactions from hallmark cancer pathways by mining cancer’s genomic and chemical interactions. Our tool provides queries and visualizations for exploring potentially targetable synthetic lethal interactions, shows Kaplan–Meier plots of clinical relevance, and provides in silico validation using short hairpin RNA (shRNA) and drug efficacy data. Our method would thus shed light on mechanisms of synthetic lethal interactions and lead to the discovery of novel anticancer drugs.

scholarly journals Does the Logic Underlying Micro and Macrostate Statistics Reflect Different Aspects of Cancer Cell Biology?

2020 ◽  
Vol 5 (4) ◽  
Keyword(s):  
Quantum Logic ◽  
Cancer Cell ◽  
Cell Biology ◽  
Cancer Biology ◽  
Popular Literature ◽  
Random Events

Do elements of microstate logic apply to microstate events? What is the relation between macrostate two-valued logic and microstate quantum logic as they reflect deterministic or random events in biology and medicine or even in other fields. The relations between different classifications of probability and logic are not often discussed in the popular literature. It could be especially interesting if random and “chaotic” events in these two realms exhibited identifiable differences affecting outcomes which if more fully understood could have implications for biologic, medical or other fields. Do the two forms of logic reflect identifiable differences in cancer biology?

scholarly journals Chromosomal arrangement of synthetic lethal gene pairs: repulsion or attraction?

2020 ◽  
Author(s):  
Sayed-Rzgar Hosseini ◽  
Bishoy Wadie ◽  
Evangelia Petsalaki
Keyword(s):  
Synthetic Lethality ◽  
Yeast Genome ◽  
Lethal Gene ◽  
Bacterial Genomes ◽  
Synthetic Lethal ◽  
Evolutionary Forces ◽  
Gene Pairs ◽  
Chromosomal Arrangement ◽  
Synthetic Lethal Interactions ◽  
2D And 3D

AbstractSynthetic lethal interactions are of paramount importance both in biology and in medicine, and hence increasing efforts have been devoted to their systematic identification. Our previous computational analysis revealed that in prokaryotic species, synthetic lethal genes tend to be further away in chromosomes than random (i.e. repulsion), which was shown to provide bacterial genomes with greater robustness to large-scale DNA deletions. To test the generalizability of this observation in eukaryotic genomes, we leveraged the wealth of experimentally determined synthetic lethal genetic interactions of yeast that are curated in the BioGRID (Biological General Repository for Interaction Datasets) database. We observed an opposite trend that is the genomic proximity of synthetic lethal gene pairs both on the 2D and 3D chromosomal space of the yeast genome (i.e. 2D and 3D attraction). To gain mechanistic insights into the origin of the attraction of synthetic lethal gene pairs in S. cerevisiae, we characterized four classes of genes, in which synthetic lethal interactions are enriched and partly explain the observed patterns of genomic attraction: i) gene pairs operating on the same pathways, 2) co-expressed genes, 3) gene pairs whose protein products physically interact and 4) the paralogs. However, our analysis revealed that the contribution of these four types of genes is not sufficient to fully explain the observed 2D and 3D attraction of synthetic lethal gene pairs and hence its evolutionary origin still remains as an open question.Significance statementUnravelling the organizing principles underlying gene arrangements is one of the fundamental questions of research in evolutionary biology. One understudied aspect of this organization is the relative chromosomal arrangement of synthetic lethal gene pairs. In this study, by analyzing a wealth of synthetic lethality data in yeast, we provide evidence that synthetic lethal gene pairs tend to be attracted to each other both on 2D and 3D chromosomal space of the yeast genome. This observation is in sharp contrast with the repulsion of synthetic lethal (metabolic) gene pairs that we observed previously in bacterial genomes. Characterizing the evolutionary forces underlying this genomic pattern in yeast can open the door towards an evolutionary theory of genome organization in eukaryotes.

scholarly journals How Cancer Genomics Drives Cancer Biology: Does Synthetic Lethality Explain Mutually Exclusive Oncogenic Mutations?

2016 ◽  
Author(s):  
Harold Varmus ◽  
Arun M. Unni ◽  
William W. Lockwood
Keyword(s):  
Cancer Biology ◽  
Large Scale ◽  
Cancer Genomics ◽  
Synthetic Lethality ◽  
Mutual Exclusivity ◽  
Physiological Basis ◽  
Oncogenic Mutations ◽  
Mutational Pattern ◽  
Cancer Multiple ◽  
Lung Adenocarcinomas

AbstractLarge-scale analyses of cancer genomes are revealing patterns of mutations that suggest biologically significant ideas about many aspects of cancer, including carcinogenesis, classification, and preventive and therapeutic strategies. Among those patterns is “mutual exclusivity”, a phenomenon observed when two or more mutations that are commonly observed in samples of a type of cancer are not found combined in individual tumors. We have been studying a striking example of mutual exclusivity: the absence of co-existing mutations in theKRASandEGFRproto-oncogenes in human lung adenocarcinomas, despite the high individual frequencies of such mutations in this common type of cancer. Multiple lines of evidence suggest that toxic effects of the joint expression ofKRASandEGFRmutant oncogenes, rather than loss of any selective advantages conferred by a second oncogene that operates through the same signaling pathway, are responsible for the observed mutational pattern. We discuss the potential for understanding the physiological basis of such toxicity, for exploiting it therapeutically, and for extending the studies to other examples of mutual exclusivity.

scholarly journals Identification of a novel synthetic lethal vulnerability in non-small cell lung cancer by co-targeting TMPRSS4 and DDR1

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Maria Villalba ◽  
Esther Redin ◽  
Francisco Exposito ◽  
Maria Jose Pajares ◽  
Cristina Sainz ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Large Scale ◽  
Tumor Regression ◽  
Synthetic Lethality ◽  
Disease Free Survival ◽  
Small Cell ◽  
Small Cell Lung ◽  
Synthetic Lethal

Abstract Finding novel targets in non-small cell lung cancer (NSCLC) is highly needed and identification of synthetic lethality between two genes is a new approach to target NSCLC. We previously found that TMPRSS4 promotes NSCLC growth and constitutes a prognostic biomarker. Here, through large-scale analyses across 5 public databases we identified consistent co-expression between TMPRSS4 and DDR1. Similar to TMPRSS4, DDR1 promoter was hypomethylated in NSCLC in 3 independent cohorts and hypomethylation was an independent prognostic factor of disease-free survival. Treatment with 5-azacitidine increased DDR1 levels in cell lines, suggesting an epigenetic regulation. Cells lacking TMPRSS4 were highly sensitive to the cytotoxic effect of the DDR1 inhibitor dasatinib. TMPRSS4/DDR1 double knock-down (KD) cells, but not single KD cells suffered a G0/G1 cell cycle arrest with loss of E2F1 and cyclins A and B, increased p21 levels and a larger number of cells in apoptosis. Moreover, double KD cells were highly sensitized to cisplatin, which caused massive apoptosis (~40%). In vivo studies demonstrated tumor regression in double KD-injected mice. In conclusion, we have identified a novel vulnerability in NSCLC resulting from a synthetic lethal interaction between DDR1 and TMPRSS4.

scholarly journals N-myristoyltransferase inhibition is synthetic lethal in MYC-deregulated cancers

2021 ◽  
Author(s):  
Gregor A. Lueg ◽  
Monica Faronato ◽  
Andrii Gorelik ◽  
Andrea Goya Grocin ◽  
Eva Caamano-Gutierrez ◽  
...  
Keyword(s):  
Membrane Trafficking ◽  
Complex I ◽  
Protein Modification ◽  
Large Scale ◽  
Synthetic Lethality ◽  
Cancer Cell Line ◽  
New Paradigm ◽  
Synthetic Lethal ◽  
Synthetically Lethal

Human N-myristoyltransferases (NMTs) catalyze N-terminal protein myristoylation, a modification regulating membrane trafficking and interactions of >100 proteins. NMT is a promising target in cancer, but a mechanistic rationale for targeted therapy remains poorly defined. Here, large-scale cancer cell line screens against a panel of NMT inhibitors (NMTi) were combined with systems-level analyses to reveal that NMTi is synthetic lethal with deregulated MYC. Synthetic lethality is mediated by post-transcriptional failure in mitochondrial respiratory complex I protein synthesis concurrent with loss of myristoylation and degradation of complex I assembly factor NDUFAF4, followed by mitochondrial dysfunction specifically in MYC-deregulated cancer cells. NMTi eliminated MYC-deregulated tumors in vivo without overt toxicity, providing a new paradigm in which targeting a constitutive co-translational protein modification is synthetically lethal in MYC-deregulated cancers.

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.

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