Phenopacket-tools: Building and validating GA4GH Phenopackets.

The Global Alliance for Genomics and Health (GA4GH) is a standards-setting organization that is developing a suite of coordinated standards for genomics. The GA4GH Phenopacket Schema is a standard for sharing disease and phenotype information that characterizes an individual person or biosample. The Phenopacket Schema is flexible and can represent clinical data for any kind of human disease including rare disease, complex disease, and cancer. It also allows consortia or databases to apply additional constraints to ensure uniform data collection for specific goals. We present phenopacket-tools, an open-source Java library and command-line application for construction, conversion, and validation of phenopackets. Phenopacket-tools simplifies construction of phenopackets by providing concise builders, programmatic shortcuts, and predefined building blocks (ontology classes) for concepts such as anatomical organs, age of onset, biospecimen type, and clinical modifiers. Phenopacket-tools can be used to validate the syntax and semantics of phenopackets as well as to assess adherence to additional user-defined requirements. The documentation includes examples showing how to use the Java library and the command-line tool to create and validate phenopackets. We demonstrate how to create, convert, and validate phenopackets using the library or the command-line application. Source code, API documentation, comprehensive user guide and a tutorial can be found at https://github.com/phenopackets/phenopacket-tools. The library can be installed from the public Maven Central artifact repository and the application is available as a standalone archive. The phenopacket-tools library helps developers implement and standardize the collection and exchange of phenotypic and other clinical data for use in phenotype-driven genomic diagnostics, translational research, and precision medicine applications.

Standards for the classification of pathogenicity of somatic variants in cancer (oncogenicity): Joint recommendations of Clinical Genome Resource (ClinGen), Cancer Genomics Consortium (CGC), and Variant Interpretation for Cancer Consortium (VICC).

PURPOSE: Several professional societies have published guidelines for the clinical interpretation of somatic variants, which specifically address diagnostic, prognostic, and therapeutic implications. Although these guidelines for the clinical interpretation of variants include data types that may be used to determine the oncogenicity of a variant (eg, population frequency, functional, and in silico data or somatic frequency), they do not provide a direct, systematic, and comprehensive set of standards and rules to classify the oncogenicity of a somatic variant. This insufficient guidance leads to inconsistent classification of rare somatic variants in cancer, generates variability in their clinical interpretation, and, importantly, affects patient care. Therefore, it is essential to address this unmet need. METHODS: Clinical Genome Resource (ClinGen) Somatic Cancer Clinical Domain Working Group and ClinGen Germline/Somatic Variant Subcommittee, the Cancer Genomics Consortium, and the Variant Interpretation for Cancer Consortium used a consensus approach to develop a standard operating procedure (SOP) for the classification of oncogenicity of somatic variants. RESULTS: This comprehensive SOP has been developed to improve consistency in somatic variant classification and has been validated on 94 somatic variants in 10 common cancer-related genes. CONCLUSION: The comprehensive SOP is now available for classification of oncogenicity of somatic variants.

Supervised learning with word embeddings derived from PubMed captures latent knowledge about protein kinases and cancer.

Inhibiting protein kinases (PKs) that cause cancers has been an important topic in cancer therapy for years. So far, almost 8% of >530 PKs have been targeted by FDA-approved medications, and around 150 protein kinase inhibitors (PKIs) have been tested in clinical trials. We present an approach based on natural language processing and machine learning to investigate the relations between PKs and cancers, predicting PKs whose inhibition would be efficacious to treat a certain cancer. Our approach represents PKs and cancers as semantically meaningful 100-dimensional vectors based on word and concept neighborhoods in PubMed abstracts. We use information about phase I-IV trials in ClinicalTrials.gov to construct a training set for random forest classification. Our results with historical data show that associations between PKs and specific cancers can be predicted years in advance with good accuracy. Our tool can be used to predict the relevance of inhibiting PKs for specific cancers and to support the design of well-focused clinical trials to discover novel PKIs for cancer therapy.

Niche-Based Screening in Multiple Myeloma Identifies a Kinesin-5 Inhibitor with Improved Selectivity over Hematopoietic Progenitors.

Novel therapeutic approaches are urgently required for multiple myeloma (MM). We used a phenotypic screening approach using co-cultures of MM cells with bone marrow stromal cells to identify compounds that overcome stromal resistance. One such compound, BRD9876, displayed selectivity over normal hematopoietic progenitors and was discovered to be an unusual ATP non-competitive kinesin-5 (Eg5) inhibitor. A novel mutation caused resistance, suggesting a binding site distinct from known Eg5 inhibitors, and BRD9876 inhibited only microtubule-bound Eg5. Eg5 phosphorylation, which increases microtubule binding, uniquely enhanced BRD9876 activity. MM cells have greater phosphorylated Eg5 than hematopoietic cells, consistent with increased vulnerability specifically to BRD9876's mode of action. Thus, differences in Eg5-microtubule binding between malignant and normal blood cells may be exploited to treat multiple myeloma. Additional steps are required for further therapeutic development, but our results indicate that unbiased chemical biology approaches can identify therapeutic strategies unanticipated by prior knowledge of protein targets.

Cinnamides as selective small-molecule inhibitors of a cellular model of breast cancer stem cells.

A high-throughput screen (HTS) was conducted against stably propagated cancer stem cell (CSC)-enriched populations using a library of 300,718 compounds from the National Institutes of Health (NIH) Molecular Libraries Small Molecule Repository (MLSMR). A cinnamide analog displayed greater than 20-fold selective inhibition of the breast CSC-like cell line (HMLE_sh_Ecad) over the isogenic control cell line (HMLE_sh_eGFP). Herein, we report structure-activity relationships of this class of cinnamides for selective lethality towards CSC-enriched populations.

Phenotypic high-throughput screening elucidates target pathway in breast cancer stem cell-like cells.

Cancer stem cells (CSCs) are resistant to standard cancer treatments and are likely responsible for cancer recurrence, but few therapies target this subpopulation. Due to the difficulty in propagating CSCs outside of the tumor environment, previous work identified CSC-like cells by inducing human breast epithelial cells into an epithelial-to-mesenchymal transdifferentiated state (HMLE_sh_ECad). A phenotypic screen was conducted against HMLE_sh_ECad with 300 718 compounds from the Molecular Libraries Small Molecule Repository to identify selective inhibitors of CSC growth. The screen yielded 2244 hits that were evaluated for toxicity and selectivity toward an isogenic control cell line. An acyl hydrazone scaffold emerged as a potent and selective scaffold targeting HMLE_sh_ECad. Fifty-three analogues were acquired and tested; compounds ranged in potency from 790 nM to inactive against HMLE_sh_ECad. Of the analogues, ML239 was best-in-class with an IC(50)= 1.18 µM against HMLE_sh_ECad, demonstrated a >23-fold selectivity over the control line, and was toxic to another CSC-like line, HMLE_shTwist, and a breast carcinoma cell line, MDA-MB-231. Gene expression studies conducted with ML239-treated cells showed altered gene expression in the NF-κB pathway in the HMLE_sh_ECad line but not in the isogenic control line. Future studies will be directed toward the identification of ML239 target(s).

Screening for inhibitors of an essential chromatin remodeler in mouse embryonic stem cells by monitoring transcriptional regulation.

The SWI/SNF-like adenosine triphosphate (ATP)-dependent chromatin remodeling complex, esBAF, is both necessary and, in some contexts, sufficient to induce the pluripotent state. Furthermore, mutations in various BAF subunits are associated with cancer. Little is known regarding the precise mechanism(s) by which this complex exerts its activities. Thus, it is unclear which protein interactions would be important to disrupt to isolate a relevant readout of mechanism. To address this, we developed a gene expression-based assay to identify inhibitors of the native esBAF complex. Specifically, a quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) assay was developed in mouse embryonic stem (ES) cells to monitor expression of Bmi1, a developmentally important gene repressed by the esBAF complex. The assay was miniaturized to a 384-well format and used to screen a diverse collection of compounds, including novel products of diversity-oriented synthesis (DOS). Confirmed hits were validated using a knock-in ES cell reporter line in which luciferase is inserted into the Bmi1 locus. Several of the validated hits regulate a panel of target genes in a manner similar to the BAF chromatin-remodeling complex. Together these data indicate that expression-based screening using qRT-PCR is a successful approach to identify compounds targeting the regulation of key developmental genes in ES cells.

Identification of a selective small molecule inhibitor of breast cancer stem cells.

A high-throughput screen (HTS) with the National Institute of Health-Molecular Libraries Small Molecule Repository (NIH-MLSMR) compound collection identified a class of acyl hydrazones to be selectively lethal to breast cancer stem cell (CSC) enriched populations. Medicinal chemistry efforts were undertaken to optimize potency and selectivity of this class of compounds. The optimized compound was declared as a probe (ML239) with the NIH Molecular Libraries Program and displayed greater than 20-fold selective inhibition of the breast CSC-like cell line (HMLE_sh_Ecad) over the isogenic control line (HMLE_sh_GFP).

Identification and validation of novel spinophilin-associated proteins in rodent striatum using an enhanced ex vivo shotgun proteomics approach.

Spinophilin regulates excitatory postsynaptic function and morphology during development by virtue of its interactions with filamentous actin, protein phosphatase 1, and a plethora of additional signaling proteins. To provide insight into the roles of spinophilin in mature brain, we characterized the spinophilin interactome in subcellular fractions solubilized from adult rodent striatum by using a shotgun proteomics approach to identify proteins in spinophilin immune complexes. Initial analyses of samples generated using a mouse spinophilin antibody detected 23 proteins that were not present in an IgG control sample; however, 12 of these proteins were detected in complexes isolated from spinophilin knock-out tissue. A second screen using two different spinophilin antibodies and either knock-out or IgG controls identified a total of 125 proteins. The probability of each protein being specifically associated with spinophilin in each sample was calculated, and proteins were ranked according to a chi(2) analysis of the probabilities from analyses of multiple samples. Spinophilin and the known associated proteins neurabin and multiple isoforms of protein phosphatase 1 were specifically detected. Multiple, novel, spinophilin-associated proteins (myosin Va, calcium/calmodulin-dependent protein kinase II, neurofilament light polypeptide, postsynaptic density 95, alpha-actinin, and densin) were then shown to interact with GST fusion proteins containing fragments of spinophilin. Additional biochemical and transfected cell imaging studies showed that alpha-actinin and densin directly interact with residues 151-300 and 446-817, respectively, of spinophilin. Taken together, we have developed a multi-antibody, shotgun proteomics approach to characterize protein interactomes in native tissues, delineating the importance of knock-out tissue controls and providing novel insights into the nature and function of the spinophilin interactome in mature striatum.

Multivalent interactions of calcium/calmodulin-dependent protein kinase II with the postsynaptic density proteins NR2B, densin-180, and alpha-actinin-2.

Dendritic calcium/calmodulin-dependent protein kinase II (CaMKII) is dynamically targeted to the synapse. We show that CaMKIIalpha is associated with the CaMKII-binding proteins densin-180, the N-methyl-D-aspartate receptor NR2B subunit, and alpha-actinin in postsynaptic density-enriched rat brain fractions. Residues 819-894 within the C-terminal domain of alpha-actinin-2 constitute the minimal CaMKII-binding domain. Similar amounts of Thr286-autophosphorylated CaMKIIalpha holoenzyme [P-T286]CaMKII bind to alpha-actinin-2 as bind to NR2B (residues 1260-1339) or to densin-180 (residues 1247-1495) in glutathione-agarose cosedimentation assays, even though the CaMKII-binding domains share no amino acid sequence similarity. Like NR2B, alpha-actinin-2 binds to representative splice variants of each CaMKII gene (alpha, beta, gamma, and delta), whereas densin-180 binds selectively to CaMKIIalpha. In addition, C-terminal truncated CaMKIIalpha monomers can interact with NR2B and alpha-actinin-2, but not with densin-180. Soluble alpha-actinin-2 does not compete for [P-T286]CaMKII binding to immobilized densin-180 or NR2B. However, soluble densin-180, but not soluble NR2B, increases CaMKII binding to immobilized alpha-actinin-2 by approximately 10-fold in a PDZ domain-dependent manner. A His6-tagged NR2B fragment associates with GST-densin or GST-actinin but only in the presence of [P-T286]CaMKII. Similarly, His6-tagged densin-180 or alpha-actinin fragments associate with GST-NR2B in a [P-T286]CaMKII-dependent manner. In addition, GST-NR2B and His6-tagged alpha-actinin can bind simultaneously to monomeric CaMKII subunits. In combination, these data support a model in which [P-T286]CaMKIIalpha can simultaneously interact with multiple dendritic spine proteins, possibly stabilizing the synaptic localization of CaMKII and/or nucleating a multiprotein synaptic signaling complex.