In this project we aim to create a first installment of data generation and analysis for the LINCS program. Specifically, we will use a novel approach to genome-wide expression profiling developed at the Broad Institute (based on a Luminex bead assay) to catalog the cellular consequences of diverse small-molecule and genetic perturbations in a breadth of human cell lines. We will perform these perturbations in 20 cell types chosen for their biological diversity and interest to the broad scientific community. For the genetic perturbations, we will profile the cellular consequences of treatment of each of these cell lines with 4,000 small-molecule compounds of interest to the community (including compounds emerging from the MLPCN network). For the genetic perturbations, we will perform both gain- and loss-of-function studies for 3,000 human genes. The resulting expression data will be made publicly available without restriction, and importantly, will be accompanied by a series of analytical tools that will enable researchers to query the data via a web interface. The project has been configured so that it a) can scale to larger efforts in the future, b) can accommodate technology platform changes in the future, and c) can accommodate the integration with other types of data.

Public Health Relevance

The proposed project is expected to enable the biomedical research community to interact with a rich database of functional perturbational data that can support a) the discovery of function of unknown components of the genome, b) the annotation of function of small molecules, and c) the linking of disease sates with small-molecule or genetic perturbational signatures, thereby providing insight into the biological basis of disease and perhaps even initial insights into new therapeutic opportunities.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54HG006093-03
Application #
8332360
Study Section
Special Emphasis Panel (ZRG1-CB-P (52))
Program Officer
Ajay, Ajay
Project Start
2010-09-27
Project End
2014-07-31
Budget Start
2012-08-01
Budget End
2014-07-31
Support Year
3
Fiscal Year
2012
Total Cost
$2,336,931
Indirect Cost
$872,253
Name
Broad Institute, Inc.
Department
Type
DUNS #
623544785
City
Cambridge
State
MA
Country
United States
Zip Code
02142
Stathias, Vasileios; Jermakowicz, Anna M; Maloof, Marie E et al. (2018) Drug and disease signature integration identifies synergistic combinations in glioblastoma. Nat Commun 9:5315
Niepel, Mario; Hafner, Marc; Duan, Qiaonan et al. (2017) Common and cell-type specific responses to anti-cancer drugs revealed by high throughput transcript profiling. Nat Commun 8:1186
Corsello, Steven M; Bittker, Joshua A; Liu, Zihan et al. (2017) The Drug Repurposing Hub: a next-generation drug library and information resource. Nat Med 23:405-408
Subramanian, Aravind; Narayan, Rajiv; Corsello, Steven M et al. (2017) A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles. Cell 171:1437-1452.e17
Zhu, Xiaodong; Girardo, David; Govek, Eve-Ellen et al. (2016) Role of Tet1/3 Genes and Chromatin Remodeling Genes in Cerebellar Circuit Formation. Neuron 89:100-12
Pikman, Yana; Puissant, Alexandre; Alexe, Gabriela et al. (2016) Targeting MTHFD2 in acute myeloid leukemia. J Exp Med 213:1285-306
Wilson, Frederick H; Johannessen, Cory M; Piccioni, Federica et al. (2015) A functional landscape of resistance to ALK inhibition in lung cancer. Cancer Cell 27:397-408
Vempati, Uma D; Chung, Caty; Mader, Chris et al. (2014) Metadata Standard and Data Exchange Specifications to Describe, Model, and Integrate Complex and Diverse High-Throughput Screening Data from the Library of Integrated Network-based Cellular Signatures (LINCS). J Biomol Screen 19:803-16
Duan, Qiaonan; Flynn, Corey; Niepel, Mario et al. (2014) LINCS Canvas Browser: interactive web app to query, browse and interrogate LINCS L1000 gene expression signatures. Nucleic Acids Res 42:W449-60
Wawer, Mathias J; Li, Kejie; Gustafsdottir, Sigrun M et al. (2014) Toward performance-diverse small-molecule libraries for cell-based phenotypic screening using multiplexed high-dimensional profiling. Proc Natl Acad Sci U S A 111:10911-6

Showing the most recent 10 out of 14 publications