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: It is discovered that TCS substantially accelerates hepatocellular carcinoma (HCC) development, acting as a liver tumor promoter, and that the mechanism of TCS-induced mouse liver pathology may be relevant to humans.
Abstract: Triclosan [5-chloro-2-(2,4-dichlorophenoxy)phenol; TCS] is a synthetic, broad-spectrum antibacterial chemical used in a wide range of consumer products including soaps, cosmetics, therapeutics, and plastics. The general population is exposed to TCS because of its prevalence in a variety of daily care products as well as through waterborne contamination. TCS is linked to a multitude of health and environmental effects, ranging from endocrine disruption and impaired muscle contraction to effects on aquatic ecosystems. We discovered that TCS was capable of stimulating liver cell proliferation and fibrotic responses, accompanied by signs of oxidative stress. Through a reporter screening assay with an array of nuclear xenobiotic receptors (XenoRs), we found that TCS activates the nuclear receptor constitutive androstane receptor (CAR) and, contrary to previous reports, has no significant effect on mouse peroxisome proliferation activating receptor α (PPARα). Using the procarcinogen diethylnitrosamine (DEN) to initiate tumorigenesis in mice, we discovered that TCS substantially accelerates hepatocellular carcinoma (HCC) development, acting as a liver tumor promoter. TCS-treated mice exhibited a large increase in tumor multiplicity, size, and incidence compared with control mice. TCS-mediated liver regeneration and fibrosis preceded HCC development and may constitute the primary tumor-promoting mechanism through which TCS acts. These findings strongly suggest there are adverse health effects in mice with long-term TCS exposure, especially on enhancing liver fibrogenesis and tumorigenesis, and the relevance of TCS liver toxicity to humans should be evaluated.
184 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: Among these impactful variants are rare somatic, clinically actionable variants including EGFR S645C, ARAF S214C and S214F, ERBB2 S418T, and multiple BRAF variants, demonstrating that rare mutations can be functionally important in cancer.
179 citations
TL;DR: This study explores a cost-effective way of rapidly assessing the biological performance diversity of a screening collection in a single assay by simultaneously measuring a large number of cellular features, unbiased profiling assays can distinguish compound effects with high resolution and thus measure performance diversity.
Abstract: High-throughput screening has become a mainstay of small-molecule probe and early drug discovery. The question of how to build and evolve efficient screening collections systematically for cell-based and biochemical screening is still unresolved. It is often assumed that chemical structure diversity leads to diverse biological performance of a library. Here, we confirm earlier results showing that this inference is not always valid and suggest instead using biological measurement diversity derived from multiplexed profiling in the construction of libraries with diverse assay performance patterns for cell-based screens. Rather than using results from tens or hundreds of completed assays, which is resource intensive and not easily extensible, we use high-dimensional image-based cell morphology and gene expression profiles. We piloted this approach using over 30,000 compounds. We show that small-molecule profiling can be used to select compound sets with high rates of activity and diverse biological performance.
171 citations
"A Next Generation Connectivity Map:..." refers result in this paper
...Consistent with our earlier studies (Wawer et al., 2014), we found that whereas 2,232/2,429 (92%) established drugs yielded a strong L1000 transcriptional response (transcriptional activity score [TAS] > 0....
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TL;DR: The results suggest that by acting on ErbB ligand shedding, an excess of TGF-β may result in conditioning of the tumor microenvironment with growth factors that can engage adjacent stromal and endothelial cells and poor clinical outcomes in women with breast cancer.
Abstract: In HER2-overexpressing mammary epithelial cells, transforming growth factor β (TGF-β) activated phosphatidylinositol-3 kinase (PI3K)/Akt and enhanced survival and migration. Treatment with TGF-β or expression of an activated TGF-β type I receptor (Alk5 with the mutation T204D [Alk5T204D]) induced phosphorylation of TACE/ADAM17 and its translocation to the cell surface, resulting in increased secretion of TGF-α, amphiregulin, and heregulin. In turn, these ligands enhanced the association of p85 with ErbB3 and activated PI3K/Akt. RNA interference of TACE or ErbB3 prevented TGF-β-induced activation of Akt and cell invasiveness. Treatment with TGF-β or expression of Alk5T204D in HER2-overexpressing cells reduced their sensitivity to the HER2 antibody trastuzumab. Inhibition of Alk5, PI3K, TACE, or ErbB3 restored sensitivity to trastuzumab. A gene signature induced by Alk5T204D expression correlated with poor clinical outcomes in patients with invasive breast cancer. These results suggest that by acting on ErbB ligand shedding, an excess of TGF-β may result in (i) conditioning of the tumor microenvironment with growth factors that can engage adjacent stromal and endothelial cells; (ii) potentiation of signaling downstream ErbB receptors, thus contributing to tumor progression and resistance to anti-HER2 therapies; and (iii) poor clinical outcomes in women with breast cancer.
168 citations
TL;DR: The findings show that disrupting the UPR during glucose deprivation could be an attractive approach for selective cancer cell killing and could provide a chemical genomic basis for developing UPR-targeting drugs against solid tumors.
Abstract: Glucose deprivation, a cell condition that occurs in solid tumors, activates the unfolded protein response (UPR). A key feature of the UPR is the transcription program activation, which allows the cell to survive under stress conditions. Here, we show that the UPR transcription program is disrupted by the antidiabetic biguanides metformin, buformin, and phenformin depending on cellular glucose availability. These drugs inhibit production of the UPR transcription activators XBP1 and ATF4 and induce massive cell death during glucose deprivation as did the antitumor macrocyclic compound versipelostatin. Gene expression profiling shows remarkable similarity in the modes of action of biguanides and versipelostatin determined by the broad range of glucose deprivation-inducible genes. Importantly, during glucose deprivation, most of the biguanide suppression genes overlap with the genes induced by tunicamycin, a chemical UPR inducer. Gene expression profiling also identifies drug-driven signatures as a tool for discovering pharmacologic UPR modulators. Our findings show that disrupting the UPR during glucose deprivation could be an attractive approach for selective cancer cell killing and could provide a chemical genomic basis for developing UPR-targeting drugs against solid tumors.
157 citations