A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles.
TL;DR: The expanded CMap is reported, made possible by a new, low-cost, high-throughput reduced representation expression profiling method that is shown to be highly reproducible, comparable to RNA sequencing, and suitable for computational inference of the expression levels of 81% of non-measured transcripts.
About: This article is published in Cell.The article was published on 2017-11-30 and is currently open access. It has received 1943 citations till now.
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Henry Ford Health System1, Harvard University2, Stanford University3, University of Hasselt4, University of Texas MD Anderson Cancer Center5, Nencki Institute of Experimental Biology6, École Polytechnique Fédérale de Lausanne7, Sage Bionetworks8, Université libre de Bruxelles9, Poznan University of Medical Sciences10, George Washington University11, Cold Spring Harbor Laboratory12, University of Kansas13, University of California, Santa Cruz14, University of North Carolina at Chapel Hill15, Van Andel Institute16
TL;DR: Novel stemness indices for assessing the degree of oncogenic dedifferentiation are provided and it is found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors.
1,099 citations
Cites methods from "A Next Generation Connectivity Map:..."
...To further investigate about mechanism of actions (MoA) and drug-target we performed specific analysis within Connectivity Map tools (https://clue.io/) (Subramanian et al., 2017)....
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...Connectivity Map (CMap) was recently updated (September 2017) (Subramanian et al., 2017), providing the end-users new functionalities and new graphical interface as web-server, previous registration (https://clue.io/) allowing easily the extraction of druginteraction knowledge using as input a…...
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TL;DR: A resistance program expressed by malignant cells that is associated with T cell exclusion and immune evasion is identified, and this study provides a high-resolution landscape of ICI-resistant cell states, identifies clinically predictive signatures, and suggests new therapeutic strategies to overcome immunotherapy resistance.
794 citations
Cites background or methods from "A Next Generation Connectivity Map:..."
...Moreover, there is a significant overlap between the perturbations that reverse the expression of the program’s repressed and induced components (p = 4.353 10 6, hypergeometric test), including the overexpression of IFN-g and IFN-b and the knockdown of MYC and CDK7 (Subramanian et al., 2017)....
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...Three genes (CDKN2C/ p18, CDKN1B/p27, andCDKN1A/p21) that inhibit CDK4 repress the program when overexpressed (Subramanian et al., 2017) (STARMethods), and the program ismore pronounced in cycling cells (Figures 1E, 2C, and S2E), where CDK4/6 are active....
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...The latter mirrors the significantly large number of Myc and CDK7 (direct) targets (Oki et al., 2018; Subramanian et al., 2005) in the program (p < 1 3 10 17, hypergeometric test)....
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...Indeed, the programs are enriched for Myc targets, even after removing RP genes (p 7.18 3 10 10) and are predicted to be repressed byMYC knockdown according to the Connectivity Map (Subramanian et al., 2017)....
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...353 10 (6), hypergeometric test), including the overexpression of IFN-g and IFN-b and the knockdown of MYC and CDK7 (Subramanian et al., 2017)....
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TL;DR: The extent, origins and consequences of genetic variation within human cell lines are studied, providing a framework for researchers to measure such variation in efforts to support maximally reproducible cancer research.
Abstract: Human cancer cell lines are the workhorse of cancer research. Although cell lines are known to evolve in culture, the extent of the resultant genetic and transcriptional heterogeneity and its functional consequences remain understudied. Here we use genomic analyses of 106 human cell lines grown in two laboratories to show extensive clonal diversity. Further comprehensive genomic characterization of 27 strains of the common breast cancer cell line MCF7 uncovered rapid genetic diversification. Similar results were obtained with multiple strains of 13 additional cell lines. Notably, genetic changes were associated with differential activation of gene expression programs and marked differences in cell morphology and proliferation. Barcoding experiments showed that cell line evolution occurs as a result of positive clonal selection that is highly sensitive to culture conditions. Analyses of single-cell-derived clones demonstrated that continuous instability quickly translates into heterogeneity of the cell line. When the 27 MCF7 strains were tested against 321 anti-cancer compounds, we uncovered considerably different drug responses: at least 75% of compounds that strongly inhibited some strains were completely inactive in others. This study documents the extent, origins and consequences of genetic variation within cell lines, and provides a framework for researchers to measure such variation in efforts to support maximally reproducible cancer research.
601 citations
01 Dec 2016
TL;DR: Perturb-seq accurately identifies individual gene targets, gene signatures, and cell states affected by individual perturbations and their genetic interactions, and posit new functions for regulators of differentiation, the anti-viral response, and mitochondrial function during immune activation.
Abstract: Genetic screens help infer gene function in mammalian cells, but it has remained difficult to assay complex phenotypes-such as transcriptional profiles-at scale. Here, we develop Perturb-seq, combining single-cell RNA sequencing (RNA-seq) and clustered regularly interspaced short palindromic repeats (CRISPR)-based perturbations to perform many such assays in a pool. We demonstrate Perturb-seq by analyzing 200,000 cells in immune cells and cell lines, focusing on transcription factors regulating the response of dendritic cells to lipopolysaccharide (LPS). Perturb-seq accurately identifies individual gene targets, gene signatures, and cell states affected by individual perturbations and their genetic interactions. We posit new functions for regulators of differentiation, the anti-viral response, and mitochondrial function during immune activation. By decomposing many high content measurements into the effects of perturbations, their interactions, and diverse cell metadata, Perturb-seq dramatically increases the scope of pooled genomic assays.
539 citations
TL;DR: The current state-of-the art of AI-assisted pharmaceutical discovery is discussed, including applications in structure- and ligand-based virtual screening, de novo drug design, physicochemical and pharmacokinetic property prediction, drug repurposing, and related aspects.
Abstract: Artificial intelligence (AI), and, in particular, deep learning as a subcategory of AI, provides opportunities for the discovery and development of innovative drugs. Various machine learning approaches have recently (re)emerged, some of which may be considered instances of domain-specific AI which have been successfully employed for drug discovery and design. This review provides a comprehensive portrayal of these machine learning techniques and of their applications in medicinal chemistry. After introducing the basic principles, alongside some application notes, of the various machine learning algorithms, the current state-of-the art of AI-assisted pharmaceutical discovery is discussed, including applications in structure- and ligand-based virtual screening, de novo drug design, physicochemical and pharmacokinetic property prediction, drug repurposing, and related aspects. Finally, several challenges and limitations of the current methods are summarized, with a view to potential future directions for AI-assisted drug discovery and design.
425 citations
References
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TL;DR: The findings indicated that ‘omics’ data mining based drug repositioning is a potentially powerful tool to discover novel anti-diabetic indications from marketed drugs and clinical candidates.
Abstract: Drug repositioning has shorter developmental time, lower cost and less safety risk than traditional drug development process. The current study aims to repurpose marketed drugs and clinical candidates for new indications in diabetes treatment by mining clinical ‘omics’ data. We analyzed data from genome wide association studies (GWAS), proteomics and metabolomics studies and revealed a total of 992 proteins as potential anti-diabetic targets in human. Information on the drugs that target these 992 proteins was retrieved from the Therapeutic Target Database (TTD) and 108 of these proteins are drug targets with drug projects information. Research and preclinical drug targets were excluded and 35 of the 108 proteins were selected as druggable proteins. Among them, five proteins were known targets for treating diabetes. Based on the pathogenesis knowledge gathered from the OMIM and PubMed databases, 12 protein targets of 58 drugs were found to have a new indication for treating diabetes. CMap (connectivity map) was used to compare the gene expression patterns of cells treated by these 58 drugs and that of cells treated by known anti-diabetic drugs or diabetes risk causing compounds. As a result, 9 drugs were found to have the potential to treat diabetes. Among the 9 drugs, 4 drugs (diflunisal, nabumetone, niflumic acid and valdecoxib) targeting COX2 (prostaglandin G/H synthase 2) were repurposed for treating type 1 diabetes, and 2 drugs (phenoxybenzamine and idazoxan) targeting ADRA2A (Alpha-2A adrenergic receptor) had a new indication for treating type 2 diabetes. These findings indicated that ‘omics’ data mining based drug repositioning is a potentially powerful tool to discover novel anti-diabetic indications from marketed drugs and clinical candidates. Furthermore, the results of our study could be related to other disorders, such as Alzheimer’s disease.
75 citations
"A Next Generation Connectivity Map:..." refers background in this paper
..., 2015), compounds targeting COX2 and ADRA2A as potential diabetes treatments (Zhang et al., 2015), small molecules that mitigate skeletal muscular atrophy (Dyle et al....
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TL;DR: This work identifies CCT020312 as a novel small molecule chemical tool for the selective activation of EIF2A-mediated translation control with utility for proof-of-concept applications in EIF 2A-centered therapeutic approaches, and as a chemical starting point for pathway selective agent development.
Abstract: Human cancers often contain genetic alterations that disable G1/S checkpoint control and loss of this checkpoint is thought to critically contribute to cancer generation by permitting inappropriate proliferation and distorting fate-driven cell cycle exit. The identification of cell permeable small molecules that activate the G1/S checkpoint may therefore represent a broadly applicable and clinically effective strategy for the treatment of cancer. Here we describe the identification of several novel small molecules that trigger G1/S checkpoint activation and characterise the mechanism of action for one, CCT020312, in detail. Transcriptional profiling by cDNA microarray combined with reverse genetics revealed phosphorylation of the eukaryotic initiation factor 2-alpha (EIF2A) through the eukaryotic translation initiation factor 2-alpha kinase 3 (EIF2AK3/PERK) as the mechanism of action of this compound. While EIF2AK3/PERK activation classically follows endoplasmic reticulum (ER) stress signalling that sets off a range of different cellular responses, CCT020312 does not trigger these other cellular responses but instead selectively elicits EIF2AK3/PERK signalling. Phosphorylation of EIF2A by EIF2A kinases is a known means to block protein translation and hence restriction point transit in G1, but further supports apoptosis in specific contexts. Significantly, EIF2AK3/PERK signalling has previously been linked to the resistance of cancer cells to multiple anticancer chemotherapeutic agents, including drugs that target the ubiquitin/proteasome pathway and taxanes. Consistent with such findings CCT020312 sensitizes cancer cells with defective taxane-induced EIF2A phosphorylation to paclitaxel treatment. Our work therefore identifies CCT020312 as a novel small molecule chemical tool for the selective activation of EIF2A-mediated translation control with utility for proof-of-concept applications in EIF2A-centered therapeutic approaches, and as a chemical starting point for pathway selective agent development. We demonstrate that consistent with its mode of action CCT020312 is capable of delivering potent, and EIF2AK3 selective, proliferation control and can act as a sensitizer to chemotherapy-associated stresses as elicited by taxanes.
70 citations
TL;DR: The aims here are to review studies of human exposure levels, to evaluate the results of studies examining the effects of triclosan on cancer development, and to suggest possible directions for future research.
Abstract: Triclosan is a broad-spectrum antibacterial commonly used in cosmetics, dentifrices, and other consumer products. The compound's widespread use in consumer products and its detection in breast milk, urine, and serum have raised concerns regarding its potential association with various human health outcomes. Recent evidence suggests that triclosan may play a role in cancer development, perhaps through its estrogenicity or ability to inhibit fatty acid synthesis. Our aims here are to review studies of human exposure levels, to evaluate the results of studies examining the effects of triclosan on cancer development, and to suggest possible directions for future research.
69 citations
"A Next Generation Connectivity Map:..." refers background in this paper
...The safety of triclosan has recently been questioned (Dinwiddie et al., 2014; Yueh et al., 2014)....
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TL;DR: Treatment with MAPK inhibitors beyond disease progression can provide significant clinical benefit, and the withdrawal of these inhibitors led to a marked increase in the rate of disease progression in two patients, providing a rationale for the continuation of BRAF and MEK inhibitors after disease progression.
Abstract: Inhibitors of the mitogen-activated protein kinases (MAPK), BRAF, and MAP-ERK kinase (MEK) induce tumor regression in the majority of patients with BRAF-mutant metastatic melanoma. The clinical benefit of MAPK inhibitors is restricted by the development of acquired resistance with half of those who benefit having progressed by 6 to 7 months and long-term responders uncommon. There remains no agreed treatment strategy on disease progression in these patients. Without published evidence, fears of accelerated disease progression on inhibitor withdrawal have led to the continuation of drugs beyond formal disease progression. We now show that treatment with MAPK inhibitors beyond disease progression can provide significant clinical benefit, and the withdrawal of these inhibitors led to a marked increase in the rate of disease progression in two patients. We also show that MAPK inhibitors retain partial activity in acquired resistant melanoma by examining drug-resistant clones generated to dabrafenib, trametinib, or the combination of these drugs. All resistant sublines displayed a markedly slower rate of proliferation when exposed to MAPK inhibitors, and this coincided with a reduction in MAPK signaling, decrease in bromodeoxyuridine incorporation, and S-phase inhibition. This cytostatic effect was also associated with diminished levels of cyclin D1 and p-pRb. Two short-term melanoma cultures generated from resistant tumor biopsies also responded to MAPK inhibition, with comparable inhibitory changes in proliferation and MAPK signaling. These data provide a rationale for the continuation of BRAF and MEK inhibitors after disease progression and support the development of clinical trials to examine this strategy.
67 citations
"A Next Generation Connectivity Map:..." refers methods in this paper
...In the first study, 21 patients with melanoma were treated with the RAF inhibitors dabrafenib or vemurafenib and 9 patients were treated with dabrafenib plus theMEK inhibitor trametinib (Carlino et al., 2013; Long et al., 2014)....
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TL;DR: A systematic library resource of proteomic signatures that measure changes in the reduced-representation phosphoproteome (P100) and changes in epigenetic marks on histones (GCP) is presented and consistent connectivity among cell types revealed cellular responses that transcended lineage and unexpected associations between drugs.
Abstract: Although the value of proteomics has been demonstrated, cost and scale are typically prohibitive, and gene expression profiling remains dominant for characterizing cellular responses to perturbations. However, high-throughput sentinel assays provide an opportunity for proteomics to contribute at a meaningful scale. We present a systematic library resource (90 drugs × 6 cell lines) of proteomic signatures that measure changes in the reduced-representation phosphoproteome (P100) and changes in epigenetic marks on histones (GCP). A majority of these drugs elicited reproducible signatures, but notable cell line- and assay-specific differences were observed. Using the "connectivity" framework, we compared signatures across cell types and integrated data across assays, including a transcriptional assay (L1000). Consistent connectivity among cell types revealed cellular responses that transcended lineage, and consistent connectivity among assays revealed unexpected associations between drugs. We further leveraged the resource against public data to formulate hypotheses for treatment of multiple myeloma and acute lymphocytic leukemia. This resource is publicly available at https://clue.io/proteomics.
65 citations
"A Next Generation Connectivity Map:..." refers background in this paper
...Other groups are generating proteomic or high-content imaging readouts following perturbation (Litichevskiy et al., 2017; Rohban et al., 2017) consistent with early reports of feasibility of annotating compounds based on cellular consequences (Seiler et al....
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