The Merkin Institute is supporting early-stage ideas aimed at advancing powerful technological approaches for improving how we understand and treat disease. These studies have been limited in the number, diversity, or level of molecular characterization of cancer cell lines or small molecules used. we have generated a dataset that can be used to identify For CTRP v2 data, we evaluated whether small-molecule sensitivity could be correlated with basal gene-expression levels or copy-number variation to identify new biomarkers of sensitivity, candidate protein targets, or other biological determinants of small-molecule sensitivity. CINDy uses a more sophisticated algorithm: while both try to assess the effects of a modulator over a transcriptional network, CINDy uses the entire expression range of the modulator. We developed a growing resource, the Cancer Therapeutics Response Portal (CTRP), to provide analysis results and visualizations of statistically significant connections and to serve as a hypothesis-generating resource for the cancer biology community. CTRP hosts data that are generated by measuring cellular responses to an 'Informer Set' of small-molecule probes and drugs. for computational details. Pearson correlation coefficients were normalized between analyses using Fishers Z transformation to account for different numbers of CCLs participating in different analyses. DepMap is a comprehensive preclinical reference portal that connects tumor features with genetic and small molecule dependencies. We have generated a novel Informer Set of small-molecule Please cite our cancer cell-line profiling Resource by referencing: Small molecules were selected to perturb potential targets and processes on whichcancer cells may become dependent, including but not limited to oncogenes/tumor suppressors, DNA-damage response, reactive-oxygen species metabolism, electrophile-stress response, protein degradation, hypoxic-stress response, mitotic-stress response, survival/apoptosis, nutrient metabolism, nutrient-stress response, chromatin modification, and other major signaling pathways (e.g., PI3K/mTOR; NFkB; others). This critical new resource may aid in advancing discovery of potential cancer drugs matched to the patient populations most likely to benefit from them. Please cite our cancer cell-line profiling Resource by referencing: Access experiments and data generated from the CTD2Center at The Broad Institute. Analysis of subset of theCancer Therapeutic Response Portal(CTRP) transcriptome and drug screening data from810 cancer cell lineswas performed using theEvaluation of Differential DependencY(EDDY) algorithm.This analysis identified pathways enriched for differential dependencies between sensitive and non-sensitive cell-lines to each compound as well as potential novel targets, termed mediators. Through programs spanning genetics, biology, and therapeutic development, Broad researchers are making discoveries that drive biomedical science forward. To negate this problem, MARINa computes the effect that enrichment of each regulon (i.e its activated and repressed targets) has on the differentially expressed genes between two phenotypic states. This resource could be used to mine for lineages or mutations, enriched among cell lines, that are sensitive to small-molecules and identify new therapeutic vulnerabilities. Mice were . Our researchers use their expertise in creating, adapting, and applying a variety of technologies to enable science here and beyond. Furthermore, Cancer Therapeutics Response Portal (CTRP) 13, and Genomics of Drug Sensitivity in Cancer (GDSC) 14 provided pharmacogenomics data from ~ 500 anticancer compounds across > 1000 cancer . features of human cancer cell lines and small-molecule Where multiple probes existed for a target, we prioritized those in clinical development, with stronger selectivity data, or with pharmacokinetic metadata that should enable more rapid drug development. This tool could be used by researchers to determine novel driver genes and drug mechanisms of action. The Cancer Target Discovery and Development (CTD) Network develops new approaches to identify novel targets and functionally validate discoveries made from large-scale genomic initiatives, such as The Cancer Genome Atlas (TCGA), Therapeutically Applicable Research to Generate Effective Treatments (TARGET), and the Cancer Genome Characterization. Stuart L. Schreiber, Ph.D.ContactPaul Clemons, Principal Investigator Access Cytoscape:https://js.cytoscape.org/, Deconvolution Analysis of RNAi Screening Data (DecoRNAi)(University of Texas Southwestern Medical Center). This method creates an accurate, context-rich map of the datasets and enables biological interpretation of the data. The Cancer Therapeutics Response Portal was developed by researchers at theCenter for the Science of Therapeuticsat the Broad Institute and is sponsored in part by the NCI's Cancer Target Discovery and Development Network. For example, a user might enter through the Compounds link then search for a molecule of interest, like navitoclax. Recently, the Genomics of Drug Sensitivity in Cancer (GDSC; refs. Project Achilles uses genome-wide pooled shRNA screens to identify and catalog genetic vulnerabilities associated with genetic or epigenetic changes across hundreds of cancer cell lines. GENE-E is a tool that allows users to visual matrix-based data, for example, cell lines in columns and cell line features in rows. TheCancer Cell Line Encyclopediaprovides public access to genomic data, analysis and visualization for about 1000 cell lines. cancer cells may become dependent, including but not limited to oncogenes/tumor suppressors, DNA-damage response, reactive-oxygen species metabolism, electrophile-stress response, protein degradation, hypoxic-stress response, mitotic-stress response, survival/apoptosis, nutrient metabolism, nutrient-stress response, chromatin modification, and other major signaling pathways (e.g., PI3K/mTOR; NFkB; others). at the National Cancer Institute, An official website of the United States government, https://califano.c2b2.columbia.edu/aracne, https://www.broadinstitute.org/cancer/ataris, https://califano.c2b2.columbia.edu/demand, https://www.bioconductor.org/packages/release/bioc/html/diggit.html, http://biocomputing.tgen.org/software/EDDY/, http://biocomputing.tgen.org/software/EDDY/CTRP/home.html, https://software.broadinstitute.org/GENE-E/, http://wiki.c2b2.columbia.edu/workbench/index.php/Home, https://califano.c2b2.columbia.edu/marina, https://bioconductor.org/packages/3.1/bioc/html/MethylMix.html, https://github.com/BandyopadhyayLab/MAGNETIC, https://califano.c2b2.columbia.edu/mindy2-cindy, https://bioinformatics.mdanderson.org/main/RDriver, http://genomeportal.stanford.edu/pan-tcga, Systems Biology Lab from Columbia University Medical Center, Data Portal from Memorial Sloan Kettering Cancer Center, U.S. Department of Health and Human Services, mines data to find alterations that potentially influence tumor biology, characterizes the functional roles of candidate alterations in cancers, identifies novel approaches that target causative alterations either directly or indirectly. These results can be accessed using the following URL. We hope that the Portal can be used to develop novel therapeutic hypotheses and to accelerate future discovery of drugs matched to patients based on their cancer genotype and lineage. Access MINDy2/CINDy:https://califano.c2b2.columbia.edu/mindy2-cindy. ATARiS is a computational method designed to analyze the off-target effects in the data generated fromRNAi screens. TheGenomics of Drug Sensitivity in Cancerprovides public access to data on the sensitivity of genomically characterized cancer cell lines to select compounds. This method uses nonnegative matrix factorization to decompose datasets into latent biological factors and embeds these factors, cells, and genes in a two-dimensional visualization. This method uses microarray expression profiles to reconstruct tissue-specific gene regulatory transcriptional interactions in cellular networks. MARINa is an algorithm that could be used to identfy transcription factors (TFs) that control the transition between two cellular phenotypes. We generated concentration-response curves that determined each compounds potency and efficacy for each cell line. Using cancer cell-line profiling, we established an ongoing resource to identify, as comprehensively as possible, the drug-targetable dependencies that specific genomic alterations impart on human cancers. Call 859-309-1700 or 877-597-4655 or submit a form to be contacted. Access DACRE-scan:https://github.com/KChen-lab/DACRE, For questions, please contact Ken Chen: (kchen3@mdanderson.org), Driver-gene Inference by Genetical-Genomics and Information Theory (DIGGIT)(Columbia University). Thus, we anticipate the ability to match patients with potentially effective drugs and that improved patient outcomes will dramatically increase. Access MethylMix:https://bioconductor.org/packages/3.1/bioc/html/MethylMix.html, For questions, please contact Olivier Gevaert: (olivier.gevaert@stanford.edu), Mining Essentiality Data to Identify Critical Interactions for Cancer Drug Target Discovery and Development(MEDICI)(Emory University). Researchers anywhere can explore more than 6,000 drugs in the hub and search for possible new uses for them to jump-start new drug discovery. Vizome, Beat AML data viewer allows easy access to clinical, genomic, transcriptomic and functional analyses of AML samples. Pharmacologic area under the dose-response curve test AUC is used to describe the drug response reaction. Learn about breakthroughs from Broad scientists. Access DepMap:https://depmap.org/portal/depmap/, For questions, please contact this email: (depmap@broadinstitute.org), Detecting Mechanism of Action based Network Dysregulation (DeMAND)(Columbia University). In addition to these genetic changes, normal functioning proteins that play roles in innocuous cellular processes may become essential to cancer cell survival when they get co-opted into partnerships with oncogene proteins. Results The IGS was constructed based on 8 immune-related hub genes with individual coefficients. These cell lines were established from many different types of tumors. CellMinerCDB is an openaccess tool for integrating genomics and pharmacogenomics analyses of cancer cell lines. The Cancer Therapeutics Response Portal v1 provides open access to the results obtained through quantitatively measuring the sensitivity of 242 genetically characterized cancer-cell lines to a 354-member Informer Set of small-molecule probes and drugs. Pathway Commons is a network biology resource that serves as a convenient access point to biological pathway information collected from public pathway databases, which users can search, visualize, and download. Connections and visualizations based on these approaches are available via theCTRP website. Our Certified Patient Navigators can work one-on-one with you to help with your needs. node in cell circuitry and that collectively modulate a broad Under the General tab, the navitoclax entry shows the chemical structure of the compound and provides other general information (top right). We anticipate continuing to expand the dataset in the portal, providing a living resource for the cancer-research community. Raw data were merged with assay metadata, and percent-viability scores were calculated relative to DMSO controls, after which concentration-response curves were fit for percent viability. Once inside the portal, users can mine this resource for novel and therapeutically exploitable vulnerabilities in different cancer types across ~185 small molecules. There are currently 83 datasets available from 12 centers. 5Cancer Therapeutics Response Portal (CTRP) Genomics of Drug Sensitivity in Cancer ( GDSC) Cancer Genome Project (CGP)138 anticancer drugs against 727 cell lines pRRophetic pRRophetic_0.5.tar.gz500M Multiple Contacts, Principal Investigator Additionally, we made available all primary data such that it can be re-analyzed to yield further hypotheses as additional computational approaches and deeper genetic and epigenetic characterization of the cancer cell lines become available. MethylMix is an algorithm to identify hyper and hypomethylated genes for a disease. Despite the incredible progress in mapping cancer genomes and annotating cancer gene function, a number of challenges (in technology, biology, chemistry, and financial incentive structure) currently impede the rapid translation of cancer genome science into cancer genome-inspired medicine. Dependencies can be represented and assessed graphically for the expression of a gene set within a particular cellular context. geWorkbench is an open source bioinformatics application that provides access to an integrated suite of tools for the analysis and visualization of data from a wide range of genomic domains (gene expression, sequence, protein structure and systems biology). We profiled human CCLs in parallel in 384-well (CTRP v1) or 1536-well (CTRP v2) plates, with each cell line propagated and carefully expanded in its preferred medium. Differentially expressed genes between pancreatic cancers with high and low stemness index (mRNAsi) scores were compared to screen out inhibitory immune checkpoints. This approach uses the transcripts most directly affected by the activity of the proteinand ranks relative protein activity on a sample-by-sample basis by transforming a gene expression matrix into a protein activity matrix. Many have already started using this hypothesis-generating tool1. The Cancer Therapeutics Response Portal (CTRP; http://portals.broadinstitute.org/ctrp/ ) homepage (top left) allows users to access data through three entry points: small molecules, enriched features, or targets. MAGNETIC is a bioinformatic approach that integrates multi-omic cancer patient data (e.g., somatic mutations, copy-number alterations, gene methylation, transcriptomes, proteomes, etc.) EDDY is a statistical test for estimating differential dependencies for a set of genes between two conditions. By leveraging work from previous projects and recent advances in high-throughput technologies, we addressed previous shortcomings of high-throughput cancer profiling studies. In March of 2020, Broad Institute converted a clinical genetics processing lab into a large-scale COVID-19 testing facility in less than two weeks. Access DecoRNAi:https://qbrc.swmed.edu/softwares.php, For questions, please contact Yang Xie: (Yang.Xie@UTsouthwestern.edu). Access MEDICI:https://github.com/cooperlab/MEDICI, For questions, please contact Lee Cooper: (lee.cooper@emory.edu), Modular Analysis of Gene Networks In Cancer (MAGNETIC)(University of California San Francisco (1)). Chemical biology and therapeutics science, Genome regulation, cellular circuitry, and epigenomics, Merkin Institute for Transformative Technologies in Healthcare, Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, https://www.ncbi.nlm.nih.gov/pubmed/23993102, https://www.ncbi.nlm.nih.gov/pubmed/25058389, https://www.ncbi.nlm.nih.gov/pubmed/26482930, https://www.ncbi.nlm.nih.gov/pubmed/26656090, https://www.ncbi.nlm.nih.gov/pubmed/28678785, Cancer Therapeutics Response Portal (CTRP), Chemical Biology and Therapeutics Science. at the National Cancer Institute, An official website of the United States government, Cancer Therapeutics Response Portal (CTRP v1, 2013) Dataset, Cancer Therapeutics Response Portal (CTRP v2, 2015) Dataset, Annotated Cluster Multidimensional Enrichment (ACME) Analysis, Basal Gene-expression and Copy-number Correlation Analysis, Computational Human High-grade Glioblastoma Multiform (GBM) Interactome - miRNA (Post-transcriptional) Layer, Direct Reversal of Glucocorticoid Resistance by AKT Inhibition in Acute Lymphoblastic Leukemia (T-ALL), Expression Profile of Neuroendocrine Tumor Cell-line Perturbed with Small Molecules, PLATE-seq for Genome-wide Regulatory Network Analysis of High-throughput Screens, Pharmacological Targeting of Mechanistic Dependencies in Neuroendocrine Tumors, Core Regulatory Elements of High-risk Neuroblastoma, Proteome-wide Signaling-network Analysis in Lung Adenocarcinoma, Mapping the Function of Rare Oncogenic Variants, Discovery of Resistance Mechanisms: Breast Cancer, Discovery of Resistance Mechanisms: Colon Cancer, Discovery of Novel Oncogenes: Ovarian Cancer, Discovery of Novel Oncogenes: Across Cancer Types, Discovery of Novel Oncogenes: High-grade Serous Ovarian Cancer, Identification of Therapeutic Targets: Adult and Pediatric Cancer Types, Identification of Therapeutic Targets Across Cancer Types: ATARiS, Identification of Therapeutic Targets Across Cancer Types: Project Achilles, Identification of Therapeutic Targets in KRAS Driven Lung Cancer, Identification of Therapeutic Targets in Ovarian Cancer, Genome-wide shRNA Screens with DEMETER Inferred Gene Effects, Computational Correction of Copy-number Effect in CRISPR-Cas9 Screens of Cancer Cells, SMAD4 Represses FOSL1 Expression and Pancreatic Cancer Metastatic Colonization, High-throughput Protein-protein Interaction Analysis for Hippo Pathway Profiling, LC-MS Analysis of PRAS40 Protein-protein Interactions, High-throughput Protein-protein Interaction Dataset for Lung Cancer-associated Genes, MEDICI (Mining Essentiality Data to Identify Critical Interactions) for Cancer Drug Target Discovery and Development, Discovery of Novel MYC Protein Interactors with NanoPCA High-throughput Protein-protein Interaction Screening, mRNA-seq Analysis of FFPE Prostate Cancer Tissues, Identification of Protein-protein Interaction Inhibitors as Potential Anti-tumor Immunity Enhancers, Discovering Protein-protein Interaction (PPI) Inducers to Restore the Lost Function of a Tumor Suppressor, Discovery of the First Chemical Tools to Regulate MKK3-mediated MYC Activation in Cancer, Genetic Disruption of CTCF Destabilizes DNA Methylation, Functional Landscape of the Human Kinome in MYCN Amplified and Non-amplified Neuroblastoma, Identification of Drug Targets for Combination Therapy with Retinoic Acid in Neuroblastoma, Functional Exploration of the Druggable Genome in MYCN Amplified and Non-amplified Neuroblastoma, Identification of Candidate Therapeutic Targets in Head and Neck Cancer Using Functional Kinomics, Kinome-wide siRNA Screens (screen 1) to Discover Novel Vulnerabilities in Ras/Tp53 Mutant Murine Squamous Cell Carcinomas, Functional Exploration of the Druggable Genome in Cisplatin Resistant Ovarian Cancer, Functional Exploration of the Kinome in MYC Driven Ovarian Cancer, Functional Exploration of the Kinome in Pancreatic Ductal Adenocarcinoma, Functional Exploration of the Druggable Genome in Pancreatic Ductal Adenocarcinoma, Functional Exploration of the Druggable Genome in Head and Neck Squamous Cell Carcinoma, Kinome-wide siRNA Screens (screen 2) to Discover Novel Vulnerabilities in Ras/Tp53 Mutant Murine Squamous Cell Carcinomas, Identification of Novel Targets and Sensitizers to the PARP Inhibitor Rucaparib in Ovarian Cancer, Transcript Splicing in Ovarian Cancer and in Diverse Normal Tissues, NanoString Profiling of MUC16 in Serous Ovarian Cancer, Benign Ovarian Tumor and Normal Tissues, Spectral Nature of Fusion Transcripts in Serous Ovarian Cancer, E-cadherin Promotes Metastasis in Invasive Ductal Breast Cancer, Organoid Spectral Invasion and Population Genetics, Functional Genomic Landscape of Acute Myeloid Leukaemia, Secondary Fusion Proteins as a Mechanism of BCR::ABL1 Kinase-independent Resistance in Chronic Myeloid Leukaemia, Large-scale Characterization of Drug Responses for Clinically Relevant Proteins in Cancer Cell Lines, In Vivo Functional Characterization of EGFR Variants Identifies Novel Drivers of Glioblastoma, Tumor-intrinsic SIRPA Promotes Sensitivity to Checkpoint Inhibition Immunotherapy in Melanoma, Identifying Methylation-driven Genes in Colorectal Cancer, Organoid Modeling of the Tumor Immune Microenvironment, Quantifying the Timing of Metastatic Progression from Patient Genomic Data, Single-cell Genomic Characterization of the Tumor Microenvironment of Gastric Cancer, Predicting DNA Methylation Patterns using Histopathology Images, A CRISPR/Cas9-engineered ARID1A-deficient Human Gastric Cancer Organoid Model Reveals Essential and Non-essential Modes of Oncogenic Transformation, Tumor Microenvironment of Metastatic Colorectal Cancer, Glioblastoma Multiforme Orthotopic Xenograft Transcriptome, Identification of Pathways Enriched with Condition-specific Statistical Dependencies Across Four Subtypes of Glioblastoma Multiforme (GBM), Quantified Cancer Cell Line Encyclopedia RNA-seq Data, Chemical-genetic Interaction Mapping Strategy, Construction of Directional Regulatory Networks Using Orthogonal CRISPR/Cas Screens, A Quantitative Chemical-genetic Interaction Map of Cancer Chemotherapy, Characterization of PIK3R1 Neomorphic Mutations, High-throughput Screening Identifying Driving Mutations in Endometrial Cancer, Phenotypic Examination of PIK3CA Allelic Series Using MCF10A Cell Sensor Platform, Systematic Functional Annotation of Somatic Mutations in Cancer, Lung Cancer Oncogenotype-selective Drug Target Discovery (Natural Products Focus), Functional Signature Ontology Tool: Triplicate Measurements of Reporter Gene Expression in Response to Individual Genetic and Chemical Perturbations in HCT116 Cells (Colon Cancer), High-throughput siRNA Screening of a Non-small Cell Lung Cancer (NSCLC) Cell Line Panel, Identification of ASCL1 as a Therapeutic Target for High-grade Neuroendocrine Lung Cancers, SW04428 is a Novel Topoisomerase 1 Inhibitor, NSCLC Cell Lines with Loss of SMARCA4 Expression are Hypersensitive to Inhibitors of Aurora Kinase A, DRC Study of Natural Products against Non-small Cell Lung Cancer (NSCLC) Cell Lines, U.S. Department of Health and Human Services.
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