Disease allele-dependent small-molecule sensitivities in blood cells from monogenic diabetes

Closing the 'phenotype gap' in precision medicine: improving what we measure to understand complex disease mechanisms

The central concept underlying precision medicine is a mechanistic understanding of each disease and its response to therapy sufficient to direct a specific intervention. To execute on this vision requires parsing incompletely defined disease syndromes into discrete mechanistic subsets and developing interventions to precisely address each of these etiologically distinct entities. This will require substantial adjustment of traditional paradigms which have tended to aggregate high-level phenotypes with very different etiologies. In the current environment, where diagnoses are not mechanistic, drug development has become so expensive that it is now impractical to imagine the cost-effective creation of new interventions for many prevalent chronic conditions. The vision of precision medicine also argues for a much more seamless integration of research and development with clinical care, where shared taxonomies will enable every clinical interaction to inform our collective understanding of disease mechanisms and drug responses. Ideally, this would be executed in ways that drive real-time and real-world discovery, innovation, translation, and implementation. Only in oncology, where at least some of the biology is accessible through surgical excision of the diseased tissue or liquid biopsy, has "co-clinical" modeling proven feasible. In most common germline disorders, while genetics often reveal the causal mutations, there still remain substantial barriers to efficient disease modeling. Aggregation of similar disorders under single diagnostic labels has directly contributed to the paucity of etiologic and mechanistic understanding by directly reducing the resolution of any subsequent studies. Existing clinical phenotypes are typically anatomic, physiologic, or histologic, and result in a substantial mismatch in information content between the phenomes in humans or in animal 'models' and the variation in the genome. This lack of one-to-one mapping of discrete mechanisms between disease and animal models causes a failure of translation and is one form of 'phenotype gap.' In this review, we will focus on the origins of the phenotyping deficit and approaches that may be considered to bridge the gap, creating shared taxonomies between human diseases and relevant models, using cardiovascular examples.

Systematic Quantification of Population Cell Death Kinetics in Mammalian Cells

Cytotoxic compounds are important drugs and research tools. Here, we introduce a method, scalable time-lapse analysis of cell death kinetics (STACK), to quantify the kinetics of compound-induced cell death in mammalian cells at the population level. STACK uses live and dead cell markers, high-throughput time-lapse imaging, and mathematical modeling to determine the kinetics of population cell death over time. We used STACK to profile the effects of over 1,800 bioactive compounds on cell death in two human cancer cell lines, resulting in a large and freely available dataset. 79 potent lethal compounds common to both cell lines caused cell death with widely divergent kinetics. 13 compounds triggered cell death within hours, including the metallophore zinc pyrithione. Mechanistic studies demonstrated that this rapid onset lethal phenotype was caused in human cancer cells by metabolic disruption and ATP depletion. These results provide the first comprehensive survey of cell death kinetics and analysis of rapid-onset lethal compounds.

Applying the logic of genetic interaction to discover small molecules that functionally interact with human disease alleles

Despite rapid advances in the genetics of complex human diseases, understanding the significance of human disease alleles remains a critical roadblock to clinical translation. Here, we present a chemical biology approach that uses perturbation with small molecules of known mechanism to reveal mechanistic and therapeutic consequences of human disease alleles. To maximize human applicability, we perform chemical screening on multiple cell lines isolated from individual patients, allowing the effects of disease alleles to be studied in their native genetic context. Chemical screen analysis combines the logic of traditional genetic interaction screens with analytic methods from high-dimensionality gene expression analyses. We rank compounds according to their ability to discriminate between cell lines that are mutant versus wild type at a disease gene (i.e., the compounds induce phenotypes that differ the most across the two classes). A technique called compound set enrichment analysis (CSEA), modeled after a widely used method to identify pathways from gene expression data, identifies sets of functionally or structurally related compounds that are statistically enriched among the most discriminating compounds. This chemical:genetic interaction approach was applied to patient-derived cells in a monogenic form of diabetes and identified several classes of compounds (including FDA-approved drugs) that show functional interactions with the causative disease gene, and also modulate insulin secretion, a critical disease phenotype. In summary, perturbation of patient-derived cells with small molecules of known mechanism, together with compound-set-based pathway analysis, can identify small molecules and pathways that functionally interact with disease alleles, and that can modulate disease networks for therapeutic effect.

Integrating phenotypic small-molecule profiling and human genetics: the next phase in drug discovery

Over the past decade, tremendous progress in high-throughput small molecule-screening methods has facilitated the rapid expansion of phenotype-based data. Parallel advances in genomic characterization methods have complemented these efforts by providing a growing list of annotated cell line features. Together, these developments have paved the way for feature-based identification of novel, exploitable cellular dependencies, subsequently expanding our therapeutic toolkit in cancer and other diseases. Here, we provide an overview of the evolution of phenotypic small-molecule profiling and discuss the most significant and recent profiling and analytical efforts, their impact on the field, and their clinical ramifications. We additionally provide a perspective for future developments in phenotypic profiling efforts guided by genomic science.

Selective modulation of autophagy, innate immunity, and adaptive immunity by small molecules

Autophagy is an evolutionarily conserved catabolic process that directs cytoplasmic proteins, organelles and microbes to lysosomes for degradation. Autophagy acts at the intersection of pathways involved in cellular stress, host defense, and modulation of inflammatory and immune responses; however, the details of how the autophagy network intersects with these processes remain largely undefined. Given the role of autophagy in several human diseases, it is important to determine the extent to which modulators of autophagy also modify inflammatory or immune pathways and whether it is possible to modulate a subset of these pathways selectively. Here, we identify small-molecule inducers of basal autophagy (including several FDA-approved drugs) and characterize their effects on IL-1β production, autophagic engulfment and killing of intracellular bacteria, and development of Treg, TH17, and TH1 subsets from naïve T cells. Autophagy inducers with distinct, selective activity profiles were identified that reveal the functional architecture of connections between autophagy, and innate and adaptive immunity. In macrophages from mice bearing a conditional deletion of the essential autophagy gene Atg16L1, the small molecules inhibit IL-1β production to varying degrees suggesting that individual compounds may possess both autophagy-dependent and autophagy-independent activity on immune pathways. The small molecule autophagy inducers constitute useful probes to test the contributions of autophagy-related pathways in diseases marked by impaired autophagy or elevated IL-1β and to test novel therapeutic hypotheses.

Autosis is a Na+,K+-ATPase-regulated form of cell death triggered by autophagy-inducing peptides, starvation, and hypoxia-ischemia

A long-standing controversy is whether autophagy is a bona fide cause of mammalian cell death. We used a cell-penetrating autophagy-inducing peptide, Tat-Beclin 1, derived from the autophagy protein Beclin 1, to investigate whether high levels of autophagy result in cell death by autophagy. Here we show that Tat-Beclin 1 induces dose-dependent death that is blocked by pharmacological or genetic inhibition of autophagy, but not of apoptosis or necroptosis. This death, termed "autosis," has unique morphological features, including increased autophagosomes/autolysosomes and nuclear convolution at early stages, and focal swelling of the perinuclear space at late stages. We also observed autotic death in cells during stress conditions, including in a subpopulation of nutrient-starved cells in vitro and in hippocampal neurons of neonatal rats subjected to cerebral hypoxia-ischemia in vivo. A chemical screen of ~5,000 known bioactive compounds revealed that cardiac glycosides, antagonists of Na(+),K(+)-ATPase, inhibit autotic cell death in vitro and in vivo. Furthermore, genetic knockdown of the Na(+),K(+)-ATPase α1 subunit blocks peptide and starvation-induced autosis in vitro. Thus, we have identified a unique form of autophagy-dependent cell death, a Food and Drug Administration-approved class of compounds that inhibit such death, and a crucial role for Na(+),K(+)-ATPase in its regulation. These findings have implications for understanding how cells die during certain stress conditions and how such cell death might be prevented.

Facilitating the use of large-scale biological data and tools in the era of translational bioinformatics

As both the amount of generated biological data and the processing compute power increase, computational experimentation is no longer the exclusivity of bioinformaticians, but it is moving across all biomedical domains. For bioinformatics to realize its translational potential, domain experts need access to user-friendly solutions to navigate, integrate and extract information out of biological databases, as well as to combine tools and data resources in bioinformatics workflows. In this review, we present services that assist biomedical scientists in incorporating bioinformatics tools into their research. We review recent applications of Cytoscape, BioGPS and DAVID for data visualization, integration and functional enrichment. Moreover, we illustrate the use of Taverna, Kepler, GenePattern, and Galaxy as open-access workbenches for bioinformatics workflows. Finally, we mention services that facilitate the integration of biomedical ontologies and bioinformatics tools in computational workflows.

Human genetics in rheumatoid arthritis guides a high-throughput drug screen of the CD40 signaling pathway

Although genetic and non-genetic studies in mouse and human implicate the CD40 pathway in rheumatoid arthritis (RA), there are no approved drugs that inhibit CD40 signaling for clinical care in RA or any other disease. Here, we sought to understand the biological consequences of a CD40 risk variant in RA discovered by a previous genome-wide association study (GWAS) and to perform a high-throughput drug screen for modulators of CD40 signaling based on human genetic findings. First, we fine-map the CD40 risk locus in 7,222 seropositive RA patients and 15,870 controls, together with deep sequencing of CD40 coding exons in 500 RA cases and 650 controls, to identify a single SNP that explains the entire signal of association (rs4810485, P = 1.4×10⁻⁹). Second, we demonstrate that subjects homozygous for the RA risk allele have ∼33% more CD40 on the surface of primary human CD19+ B lymphocytes than subjects homozygous for the non-risk allele (P = 10⁻⁹), a finding corroborated by expression quantitative trait loci (eQTL) analysis in peripheral blood mononuclear cells from 1,469 healthy control individuals. Third, we use retroviral shRNA infection to perturb the amount of CD40 on the surface of a human B lymphocyte cell line (BL2) and observe a direct correlation between amount of CD40 protein and phosphorylation of RelA (p65), a subunit of the NF-κB transcription factor. Finally, we develop a high-throughput NF-κB luciferase reporter assay in BL2 cells activated with trimerized CD40 ligand (tCD40L) and conduct an HTS of 1,982 chemical compounds and FDA–approved drugs. After a series of counter-screens and testing in primary human CD19+ B cells, we identify 2 novel chemical inhibitors not previously implicated in inflammation or CD40-mediated NF-κB signaling. Our study demonstrates proof-of-concept that human genetics can be used to guide the development of phenotype-based, high-throughput small-molecule screens to identify potential novel therapies in complex traits such as RA.

A current challenge in human genetics is to follow-up “hits” from genome-wide association studies (GWAS) to guide drug discovery for complex traits. Previously, we identified a common variant in the CD40 locus as associated with risk of rheumatoid arthritis (RA). Here, we fine-map the CD40 signal of association through a combination of dense genotyping and exonic sequencing in large patient collections. Further, we demonstrate that the RA risk allele is a gain-of-function allele that increases the amount of CD40 on the surface of primary human B lymphocyte cells from healthy control individuals. Based on these observations, we develop a high-throughput assay to recapitulate the biology of the RA risk allele in a system suitable for a small molecule drug screen. After a series of primary screens and counter screens, we identify small molecules that inhibit CD40-mediated NF-kB signaling in human B cells. While this is only the first step towards a more comprehensive effort to identify CD40-specific inhibitors that may be used to treat RA, our study demonstrates a successful strategy to progress from a GWAS to a drug screen for complex traits such as RA.

Organic synthesis toward small-molecule probes and drugs

"Organic synthesis" is a compound-creating activity often focused on biologically active small molecules. This special issue of PNAS explores innovations and trends in the field that are enabling the synthesis of new types of small-molecule probes and drugs. This perspective article frames the research described in the special issue but also explores how these modern capabilities can both foster a new and more extensive view of basic research in the academy and promote the linkage of life-science research to the discovery of novel types of small-molecule therapeutics [Schreiber SL (2009) Chem Bio Chem 10:26-29]. This new view of basic research aims to bridge the chasm between basic scientific discoveries in life sciences and new drugs that treat the root cause of human disease--recently referred to as the "valley of death" for drug discovery. This perspective article describes new roles that modern organic chemistry will need to play in overcoming this challenge.