Building a collaborative cloud platform to accelerate heart, lung, blood, and sleep research.

Research increasingly relies on interrogating large-scale data resources. The NIH National Heart, Lung, and Blood Institute developed the NHLBI BioData CatalystⓇ (BDC), a community-driven ecosystem where researchers, including bench and clinical scientists, statisticians, and algorithm developers, find, access, share, store, and compute on large-scale datasets. This ecosystem provides secure, cloud-based workspaces, user authentication and authorization, search, tools and workflows, applications, and new innovative features to address community needs, including exploratory data analysis, genomic and imaging tools, tools for reproducibility, and improved interoperability with other NIH data science platforms. BDC offers straightforward access to large-scale datasets and computational resources that support precision medicine for heart, lung, blood, and sleep conditions, leveraging separately developed and managed platforms to maximize flexibility based on researcher needs, expertise, and backgrounds. Through the NHLBI BioData Catalyst Fellows Program, BDC facilitates scientific discoveries and technological advances. BDC also facilitated accelerated research on the coronavirus disease-2019 (COVID-19) pandemic.

Li-Fraumeni Exploration Consortium Data Coordinating Center: Building an Interactive Web-Based Resource for Collaborative International Cancer Epidemiology Research for a Rare Condition.

BACKGROUND: The success of multisite collaborative research relies on effective data collection, harmonization, and aggregation strategies. Data Coordination Centers (DCC) serve to facilitate the implementation of these strategies. The utility of a DCC can be particularly relevant for research on rare diseases where collaboration from multiple sites to amass large aggregate datasets is essential. However, approaches to building a DCC have been scarcely documented. METHODS: The Li-Fraumeni Exploration (LiFE) Consortium's DCC was created using multiple open source packages, including LAM/G Application (Linux, Apache, MySQL, Grails), Extraction-Transformation-Loading (ETL) Pentaho Data Integration Tool, and the Saiku-Mondrian client. This document serves as a resource for building a rare disease DCC for multi-institutional collaborative research. RESULTS: The primary scientific and technological objective to create an online central repository into which data from all participating sites could be deposited, harmonized, aggregated, disseminated, and analyzed was completed. The cohort now include 2,193 participants from six contributing sites, including 1,354 individuals from families with a pathogenic or likely variant in TP53. Data on cancer diagnoses are also available. Challenges and lessons learned are summarized. CONCLUSIONS: The methods leveraged mitigate challenges associated with successfully developing a DCC's technical infrastructure, data harmonization efforts, communications, and software development and applications. IMPACT: These methods can serve as a framework in establishing other collaborative research efforts. Data from the consortium will serve as a great resource for collaborative research to improve knowledge on, and the ability to care for, individuals and families with Li-Fraumeni syndrome.

Simvastatin Sodium Salt and Fluvastatin Interact with Human Gap Junction Gamma-3 Protein.

Finding pleiomorphic targets for drugs allows new indications or warnings for treatment to be identified. As test of concept, we applied a new chemical genomics approach to uncover additional targets for the widely prescribed lipid-lowering pro-drug simvastatin. We used mRNA extracted from internal mammary artery from patients undergoing coronary artery surgery to prepare a viral cardiovascular protein library, using T7 bacteriophage. We then studied interactions of clones of the bacteriophage, each expressing a different cardiovascular polypeptide, with surface-bound simvastatin in 96-well plates. To maximise likelihood of identifying meaningful interactions between simvastatin and vascular peptides, we used a validated photo-immobilisation method to apply a series of different chemical linkers to bind simvastatin so as to present multiple orientations of its constituent components to potential targets. Three rounds of biopanning identified consistent interaction with the clone expressing part of the gene GJC3, which maps to Homo sapiens chromosome 7, and codes for gap junction gamma-3 protein, also known as connexin 30.2/31.3 (mouse connexin Cx29). Further analysis indicated the binding site to be for the N-terminal domain putatively 'regulating' connexin hemichannel and gap junction pores. Using immunohistochemistry we found connexin 30.2/31.3 to be present in samples of artery similar to those used to prepare the bacteriophage library. Surface plasmon resonance revealed that a 25 amino acid synthetic peptide representing the discovered N-terminus did not interact with simvastatin lactone, but did bind to the hydrolysed HMG CoA inhibitor, simvastatin acid. This interaction was also seen for fluvastatin. The gap junction blockers carbenoxolone and flufenamic acid also interacted with the same peptide providing insight into potential site of binding. These findings raise key questions about the functional significance of GJC3 transcripts in the vasculature and other tissues, and this connexin's role in therapeutic and adverse effects of statins in a range of disease states.

Informatics and data quality at collaborative multicenter Breast and Colon Cancer Family Registries.

Quality control and harmonization of data is a vital and challenging undertaking for any successful data coordination center and a responsibility shared between the multiple sites that produce, integrate, and utilize the data. Here we describe a coordinated effort between scientists and data managers in the Cancer Family Registries to implement a data governance infrastructure consisting of both organizational and technical solutions. The technical solution uses a rule-based validation system that facilitates error detection and correction for data centers submitting data to a central informatics database. Validation rules comprise both standard checks on allowable values and a crosscheck of related database elements for logical and scientific consistency. Evaluation over a 2-year timeframe showed a significant decrease in the number of errors in the database and a concurrent increase in data consistency and accuracy.

Mapping DNA adducts of mitomycin C and decarbamoyl mitomycin C in cell lines using liquid chromatography/ electrospray tandem mass spectrometry.

The antitumor antibiotic and cancer chemotherapeutic agent mitomycin C (MC) alkylates and crosslinks DNA, forming six major MC-deoxyguanosine adducts of known structures in vitro and in vivo. Two of these adducts are derived from 2,7-diaminomitosene (2,7-DAM), a nontoxic reductive metabolite of MC formed in cells in situ. Several methods have been used for the analysis of MC-DNA adducts in the past; however, a need exists for a safer, more comprehensive and direct assay of the six-adduct complex. Development of an assay, based on mass spectrometry, is described. DNA from EMT6 mouse mammary tumor cells, Fanconi Anemia-A fibroblasts, normal human fibroblasts, and MCF-7 human breast cancer cells was isolated after MC or 10-decarbamoyl mitomycin C (DMC) treatment of the cells, digested to nucleosides, and submitted to liquid chromatography electrospray-tandem mass spectrometry. Two fragments of each parent ion were monitored ("multiple reaction monitoring"). Identification and quantitative analysis were based on a standard mixture of six adducts, the preparation of which is described here in detail. The lower limit of detection of adducts is estimated as 0.25 pmol. Three initial applications of this method are reported as follows: (i) differential kinetics of adduct repair in EMT6 cells, (ii) analysis of adducts in MC- or DMC-treated Fanconi Anemia cells, and (iii) comparison of the adducts generated by treatment of MCF-7 breast cancer cells with MC and DMC. Notable results are the following: Repair removal of the DNA interstrand cross-link and of the two adducts of 2,7-DAM is relatively slow; both MC and DMC generate DNA interstrand cross-links in human fibroblasts, Fanconi Anemia-A fibroblasts, and MCF-7 cells as well as EMT6 cells; and DMC shows a stereochemical preference of linkage to the guanine-2-amino group opposite from that of MC.

Synthesis of an oligodeoxyribonucleotide adduct of mitomycin C by the postoligomerization method via a triamino mitosene.

The cancer chemotherapeutic agent mitomycin C (MC) alkylates and cross-links DNA monofunctionally and bifunctionally in vivo and in vitro, forming six major MC-deoxyguanosine adducts of known structures. The synthesis of one of the monoadducts (8) by the postoligomerization method was accomplished both on the nucleoside and oligonucleotide levels, the latter resulting in the site-specific placement of 8 in a 12-mer oligodeoxyribonucleotide 26. This is the first application of this method to the synthesis of a DNA adduct of a complex natural product. Preparation of the requisite selectively protected triaminomitosenes 14 and 24 commenced with removal of the 10-carbamoyl group from MC, followed by reductive conversion to 10-decarbamoyl-2,7-diaminomitosene 10. This substance was transformed to 14 or 24 in several steps. Both were successfully coupled to the 2-fluoro-O(6)-(2-trimethylsilylethyl)deoxyinosine residue of the 12-mer oligonucleotide. The N(2)-phenylacetyl protecting group of 14 after its coupling to the 12-mer oligonucleotide could not be removed by penicillinamidase as expected. Nevertheless, the Teoc protecting group of 24 after coupling to the 12-mer oligonucleotide was removed by treatment with ZnBr2 to give the adducted oligonucleotide 26. However, phenylacetyl group removal was successful on the nucleoside-level synthesis of adduct 8. Proof of the structure of the synthetic nucleoside adduct included HPLC coelution and identical spectral properties with a natural sample, and (1)H NMR. Structure proof of the adducted oligonucleotide 26 was provided by enzymatic digestion to nucleosides and authentic adduct 8, as well as MS and MS/MS analysis.