The LINCS project currently consists of 10 centers: two data production/analysis centers, that generate data for the LINCS matrix, four centers dedicated to developing technology to complement and facilitate the collection of cellular signatures, and four centers that are developing computational tools for analyzing the data produced by the data production centers. In addition, two external supplements, as well as a number of internal collaborations, support and augment the work done by the LINCS centers.

Data Production and Analysis Centers (U54)

The LINCS Data Production and Analysis program has two research centers, one at Harvard Medical School and the other at the Broad Institute. These centers are focused on high-throughput experiments that examine the changes that occur when a variety of different cell lines are exposed to perturbations.

  • At Harvard Medical School, LINCS researchers aim to create signatures that measure the responses to therapeutic drugs of cells derived from different human tissues. The perturbing agents they focus on are small molecule kinase inhibitors, which are a leading class of therapeutic agents for treatment of cancer, autoimmune and other diseases.
  • At the Broad Institute, LINCS researchers concentrate on cataloging the cellular consequences of diverse small-molecule and genetic perturbations in a breadth of human cell lines.
  • There is also a joint Broad-HMS collaboration project, in which the two data production centers work together to ensure that the data they generate is consistent and will be able to be meaningfully integrated. Through this collaboration, the Broad Institute carries out expression profiling on a subset of the HMS perturbation studies.

Technology Development (U01)

The Technology Development program is developing and substantially adapting technologies and methodologies to significantly improve the functionality, quality, scope, and/or throughput of perturbation-induced cellular signature data generation. These technologies should accelerate the rate of data generation and the range of signatures that can be identified and characterized by large scale high-throughput perturbation-induced signature collection efforts like LINCS. There are four LINCS technology awards: Arizona State University, the Broad Institute, Columbia University, and Yale University.

  • At Arizona State, LINCS researchers are developing a platform for dynamic, multi-parameter sensing of single-cell metabolic phenotypes in a high throughput live-cell microarray format. A sandwich microarray, called the Cellarium, will be developed and used to analyze individual live cells.
  • At the Broad Institute, the focus is on developing a high information content multiplex mass spectrometry-based assay to query serine and threonine signaling pathways.
  • At Columbia, LINCS researchers are establishing a platform for the quantitative study of synergistic drug activity, not just for cell viability but rather for an entire range of disease-relevant cellular phenotypes. Columbia also plans to generate the molecular profile data necessary to transform combination therapy from a trial and error exercise to a rational discipline, by allowing identification of synergistic drug combinations on a predictive basis.
  • At Yale, LINCS researchers will enable high-content and high-throughput analysis of single cell protein signatures.

Computational Tools (U01)

The Computational Tools program is focused on developing ways to integrate, analyze, and utilize the data generated by the Data Production Centers. The four LINCS computational awardees are the University of Cincinnati, Columbia University, Methodist Hospital Research Institute, and the University of Miami.

  • At the University of Cincinnati, the statistical methods being developed by the iLINCS Genomics project will address two levels of data integration: integration of the same type readouts into meta-signatures and integration of various types of readouts and meta-signatures into regulatory network activity signatures.
  • Columbia University uses LINCS in vitro signatures to predict compound-related properties (mechanism of action, activity, sensitivity, synergy, etc.) in vivo.
  • At Methodist Hospital Research Institute, LINCS researchers are developing a signature-oriented software platform called the Integrative and Translational Network-based Cellular Signature Analyzer.
  • At the University of Miami, LINCS researchers are working on seamless “on-the fly” data integration and analysis via a semantic “Linked Data” approach that is scalable with respect to information volume and complexity. This LINCS Information FramEwork (LIFE) Knowledge Base will incorporate biomedical domain-level ontologies, including the recently developed BioAssay Ontology (BAO), to semantically associate related data types and to provide a knowledge context of the underlying experiments and screening outcomes.

External Collaborations

There are two external collaborations that support the LINCS program, one between Dr. Vamsi Mootha and the HMS LINCS Centerand one between Dr. Evan Snyder and the HMS LINCS Center. The Mootha project is working to apply cell and protein-based profiling methods to characterize the changes in cell signaling networks that result from mutations in components of the oxidative phosphorylation (OXPHOS) pathway. The Snyder project is working on patient-derived induced pluripotent stem (iPS) cells to study signaling pathways that might be relevant to neuropsychopathology.

Internal Collaborations

LINCS internal collaborations facilitate cooperation and partnerships between LINCS centers that advance the overall goals of the LINCS project.

  • HMS-Broad: Interactive Web Content for Integrated Analysis of LINCS Joint Project
    Creation of non-expert dynamic web tools for analysis of combined LINCS data (biochemical and cell-based data from HMS Center and gene expression data from the Broad Center)
  • HMS-Miami: Development of a Unified LINCS Data Portal
    Pilot project to develop an easy-to-use user interface (UI) to directly query and explore a small slice of LINCS data; this project will inform best practices for curation of LINCS data and set the stage for development of a distributed data management system (portal).
  • Columbia-Columbia: A Systems Approach to Elucidate Mechanisms of Drug Activity and Sensitivity
    Develop software to allow expert users to query the Columbia LINCS Center data, and probe for synergistic effects of drug-pairs in a number of different cancer cell lines; this will aid in the elucidation of mechanisms of drug activity and sensitivity.
  • Broad-HMS: Prototyping a cloud-based solution to enhance access to LINCS datasets
    Making raw and analyzed LINCS data freely accessible to the broader scientific community via hosting on the Amazon Web Services (cloud).
  • Methodist-Miami: A Pan-LINCS Data Warehouse-based Supply Chain Landscape Model
    Enable more comprehensive data integration and novel types of queries to interrogate LINCS data.