Center Driven Project

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G. Center-Driven Research Project: Genomic signature-based screening in robust HTS formats G.1. Introduction We propose to develop general and robust HTS methods that enable the discovery of small molecules that switch, for example, disease states to healthy states without requiring knowledge of the relevant cellular target(s) in advance of the screen. These methods require the ability to perform multiple measurements per well that together define signatures of the relevant states. Small-molecule, high-throughput screens often entail a single measurement per well, for example, the activity of a singular, purified enzyme. In principle and in practice, the ability to perform multiple measurements per well provides novel scientific insights, as demonstrated through high-content expression- and image-based screening. To illustrate: 1) cells treated with small molecules have been probed with Luminex beads to determine the relative amounts of RNAs (mRNA, miRNA)13'43, 2) multiple cellular features have been measured and selected as state classifiers using image-analysis software developed by researchers at the Broad Institute38'39, and 3) protein microarray and Luminex bead-based methods have been adapted to the analyses of phosphoproteins in cells65'66. Such capabilities underlie signature-based state-switching screens, which permit the probing of biological and disease circuitries in order to discover small molecules able to switch one state to the other. (Methods for making multiple measurements can also permit extremely efficient screens where each of the individual measurements is of particular, but not necessarily related, importance, e.g., where the many RNAs being measured each represent a singular biological or therapeutic probe.) Important understandings in biology have already been gained from the two most advanced and informative methods for multiplexed measurements in screens at the Broad Institute: gene expression-based screening and automatic scoring of complex cellular phenotypes by machine learning from multiple features of cells. In the former case, for example, one clinical trial was initiated based on the discovery that sirolimus converts a dexamethasone-resistant state of leukemia (ALL) - HRG-bl +HRG-D1 ce||Sj jdentjfjec| by its gene-expression signature, to a dexamethasone-sensitive state, and a second clinical trial involving patients with relapsed or refractory AMI was initiated based on the discovery that gefitinib and erlotonib induced differentiation of acute myeloid leukemia cells13. In the case of imaged features of cells, for example, the discovery of modulators of heregulin (HRG)-mediated, ErbB2- dependent filopodia extension, an example of a complex phenotype, was achieved based on supervised selection of imaged cellular features of the non and heregulin-teated cell states (Figure 13). While the capability to make two such multiplexed measurements already exists at the Broad Institute, it is not yet possible to do so in a fully automated high-throughput format. Until that challenge is met, the full potential to exploit the novel technologies and to share them with the MLPCN and other labs cannot be realized. In addition, the continuing evolution of technologies like single molecule-based measurements provide the opportunity for continued process improvement through greater sensitivity and resolution. Finally, other methods are being developed that have not yet reached a stage of throughput sufficient for use in smallmolecule screens, but that offer considerable promise in terms of the unique insights they provide into cell circuitry and the relationship of small-molecule structure to protein binding. Two examples of such technologies under development currently at the Broad Institute are: 1) chromatin immunoprecipitation followed by exhaustive (Solexa-based) DNA sequencing, and 2) the use of stable isotope labeling of cells (SILAC) and MS-based proteomics to determine rank-ordered small-molecule/protein interactions in cells treated with small molecules (unpublished results, Steve Carr, Stuart Schreiber and colleagues). While we propose here initially to undertake two specific signature-based screening techniques and to convert them to robust HTS formats, we will also explore other promising new areas and develop a process, in consultation with MLPCN leadership, for determining whether they merit effort as future Center-driven research projects. Two biological systems illustrate how signature-based screening might be used in the future. As described earlier (Section B), we have developed a 384-well format for culturing human primary pancreatic islets having functional endocrine cells. We have also cultured individual cell types from these islets. If signatures of the individual endocrine cell types could be identified, small molecules, including ones targeted to chromatinmodifying enzymes, would be screened for their ability to convert non-beta cells to beta cells. Earlier (Section B), we also described our ability to co-culture primary hematopoietic or leukemic stem cells with stromal (e.g., osteoblast) cells. Signature-based screens would be of great value for discovering small molecules that selectively alter the developmental states of these individual cell types. The objective of the Broad Center-Driven Research Project is to convert promising or existing (pilot stage) methods into robust, fully automated HTS methods. The specific aims are: ¿ To advance benchmark systems in gene expression- and image-based signature screening from their current pilot stage to a mature, HTS stage defined by the ability to screen the complete MLPCN smallmolecule collection. ¿ To develop tools for the comparative analysis of signature-based, multidimensional HTS datasets. To incubate nascent yet promising methods for multiplexed measurements yielding signatures of cell states that are well suited for HTS and complementary to the first two systems. ¿ To make these capabilities available to the MLPCN community, initially by advancing them to the Production Facility of the BCSC. We envision that this Center-Driven Research Project will impact several facets of the MLPCN. Used in primary screens, these methods offer powerful new discovery capabilities, giving researchers the opportunity to probe expression and image-based biological outcomes, neither of which can be used routinely in HTS. The ability to compare directly the information obtained from such methods will enable evaluation of multiplex assay methods and help determine priorities for future development. They can also facilitate probe development by permitting richer and more informative structure/activity relationships to be obtained (mechanism-associated signatures), ones based on multiple measurements that provide greater assurance that structural variants are staying "on mechanism" while showing improved cell-based-selectivity and potency. Potential off-target effects that would otherwise be "silent" in single-measurement short-term cell-based systems could then be identified at the earliest stages of probe development. On-mechanism signatures provide a systematic means to identify and to validate biomarkers of value in small-molecule experiments involving organ cultures and even animals. Looking ahead, the capacity and capability to perform multi-dimensional data analysis will help elucidate complex pathway inter-relationships, provide a means for comprehensively probing the basis for clinically observed drug resistance, and enable the design of screens for generating disease-relevant cell states that can be used in an HTS mode to systematically discover novel, multiple-drug therapies.