Clinical decision support systems for improving diagnostic accuracy and achieving precision medicine.

As research laboratories and clinics collaborate to achieve precision medicine, both communities are required to understand mandated electronic health/medical record (EHR/EMR) initiatives that will be fully implemented in all clinics in the United States by 2015. Stakeholders will need to evaluate current record keeping practices and optimize and standardize methodologies to capture nearly all information in digital format. Collaborative efforts from academic and industry sectors are crucial to achieving higher efficacy in patient care while minimizing costs. Currently existing digitized data and information are present in multiple formats and are largely unstructured. In the absence of a universally accepted management system, departments and institutions continue to generate silos of information. As a result, invaluable and newly discovered knowledge is difficult to access. To accelerate biomedical research and reduce healthcare costs, clinical and bioinformatics systems must employ common data elements to create structured annotation forms enabling laboratories and clinics to capture sharable data in real time. Conversion of these datasets to knowable information should be a routine institutionalized process. New scientific knowledge and clinical discoveries can be shared via integrated knowledge environments defined by flexible data models and extensive use of standards, ontologies, vocabularies, and thesauri. In the clinical setting, aggregated knowledge must be displayed in user-friendly formats so that physicians, non-technical laboratory personnel, nurses, data/research coordinators, and end-users can enter data, access information, and understand the output. The effort to connect astronomical numbers of data points, including '-omics'-based molecular data, individual genome sequences, experimental data, patient clinical phenotypes, and follow-up data is a monumental task. Roadblocks to this vision of integration and interoperability include ethical, legal, and logistical concerns. Ensuring data security and protection of patient rights while simultaneously facilitating standardization is paramount to maintaining public support. The capabilities of supercomputing need to be applied strategically. A standardized, methodological implementation must be applied to developed artificial intelligence systems with the ability to integrate data and information into clinically relevant knowledge. Ultimately, the integration of bioinformatics and clinical data in a clinical decision support system promises precision medicine and cost effective and personalized patient care.

Fibroblast growth factor-2 (FGF2) and syndecan-1 (SDC1) are potential biomarkers for putative circulating CD15+/CD30+ cells in poor outcome Hodgkin lymphoma patients.

BACKGROUND: High risk, unfavorable classical Hodgkin lymphoma (cHL) includes those patients with primary refractory or early relapse, and progressive disease. To improve the availability of biomarkers for this group of patients, we investigated both tumor biopsies and peripheral blood leukocytes (PBL) of untreated (chemo-naïve, CN) Nodular Sclerosis Classic Hodgkin Lymphoma (NS-cHL) patients for consistent biomarkers that can predict the outcome prior to frontline treatment. METHODS AND MATERIALS: Bioinformatics data mining was used to generate 151 candidate biomarkers, which were screened against a library of 10 HL cell lines. Expression of FGF2 and SDC1 by CD30+ cells from HL patient samples representing good and poor outcomes were analyzed by qRT-PCR, immunohistochemical (IHC), and immunofluorescence analyses. RESULTS: To identify predictive HL-specific biomarkers, potential marker genes selected using bioinformatics approaches were screened against HL cell lines and HL patient samples. Fibroblast Growth Factor-2 (FGF2) and Syndecan-1 (SDC1) were overexpressed in all HL cell lines, and the overexpression was HL-specific when compared to 116 non-Hodgkin lymphoma tissues. In the analysis of stratified NS-cHL patient samples, expression of FGF2 and SDC1 were 245 fold and 91 fold higher, respectively, in the poor outcome (PO) group than in the good outcome (GO) group. The PO group exhibited higher expression of the HL marker CD30, the macrophage marker CD68, and metastatic markers TGFß1 and MMP9 compared to the GO group. This expression signature was confirmed by qualitative immunohistochemical and immunofluorescent data. A Kaplan-Meier analysis indicated that samples in which the CD30+ cells carried an FGF2+/SDC1+ immunophenotype showed shortened survival. Analysis of chemo-naive HL blood samples suggested that in the PO group a subset of CD30+ HL cells had entered the circulation. These cells significantly overexpressed FGF2 and SDC1 compared to the GO group. The PO group showed significant down-regulation of markers for monocytes, T-cells, and B-cells. These expression signatures were eliminated in heavily pretreated patients. CONCLUSION: The results suggest that small subsets of circulating CD30+/CD15+ cells expressing FGF2 and SDC1 represent biomarkers that identify NS-cHL patients who will experience a poor outcome (primary refractory and early relapsing).

Tissue banking, bioinformatics, and electronic medical records: the front-end requirements for personalized medicine.

Personalized medicine promises patient-tailored treatments that enhance patient care and decrease overall treatment costs by focusing on genetics and "-omics" data obtained from patient biospecimens and records to guide therapy choices that generate good clinical outcomes. The approach relies on diagnostic and prognostic use of novel biomarkers discovered through combinations of tissue banking, bioinformatics, and electronic medical records (EMRs). The analytical power of bioinformatic platforms combined with patient clinical data from EMRs can reveal potential biomarkers and clinical phenotypes that allow researchers to develop experimental strategies using selected patient biospecimens stored in tissue banks. For cancer, high-quality biospecimens collected at diagnosis, first relapse, and various treatment stages provide crucial resources for study designs. To enlarge biospecimen collections, patient education regarding the value of specimen donation is vital. One approach for increasing consent is to offer publically available illustrations and game-like engagements demonstrating how wider sample availability facilitates development of novel therapies. The critical value of tissue bank samples, bioinformatics, and EMR in the early stages of the biomarker discovery process for personalized medicine is often overlooked. The data obtained also require cross-disciplinary collaborations to translate experimental results into clinical practice and diagnostic and prognostic use in personalized medicine.

Phosphorylation of the Gal4 DNA-binding domain is essential for activator mono-ubiquitylation and efficient promoter occupancy.

Recent analysis of a Gal4 mutant (Gap71) carrying three point mutations (S22D, K23Q and K25F) in its DNA-binding domain (DBD), has demonstrated that it cannot occupy GAL promoters efficiently in cells and that it is not mono-ubiquitylated, suggesting a functional link between this modification and stable DNA binding in cells. The mechanistic underpinning of this phenotype is that this protein is hypersensitive to a newly discovered activity of the proteasomal ATPases--their ability to actively dissociate transcription factor-DNA complexes after direct interaction with the activation domain. In this paper, we examine the roles of each of the three point mutations contained in Gap71 individually. These experiments have revealed that serine 22 is a site of phosphorylation in the Gal4 DBD and that lysine 23 is essential for S22 phosphorylation, possibly acting as part of the kinase recognition site. Mutation of either residue blocks Gal4 DBD phosphorylation, its subsequent ubiquitylation and compromises the ability of the activator to bind promoter DNA in vivo. These data represent the first report of an essential phosphorylation event that is critical for the activity of this paradigmatic transcription factor.

Concurrent fast and slow cycling of a transcriptional activator at an endogenous promoter.

For gene regulation, some transcriptional activators bind periodically to promoters with either a fast (approximately 1 minute) or a slow (approximately 15 to 90 minutes) cycle. It is uncertain whether the fast cycle occurs on natural promoters, and the function of either cycle in transcription remains unclear. We report that fast and slow cycling can occur simultaneously on an endogenous yeast promoter and that slow cycling in this system reflects an oscillation in the fraction of accessible promoters rather than the recruitment and release of stably bound transcriptional activators. This observation, combined with single-cell measurements of messenger RNA (mRNA) production, argues that fast cycling initiates transcription and that slow cycling regulates the quantity of mRNA produced. These findings counter the prevailing view that slow cycling initiates transcription.

The role of the proteasomal ATPases and activator monoubiquitylation in regulating Gal4 binding to promoters.

Recent studies have shown that the intersection between transcription and proteins involved in the ubiquitin-proteasome pathway encompasses both proteolytic and nonproteolytic functions. Examples of the latter type include evidence that monoubiquitylation of some transcriptional activators stimulates their activity. In addition, the proteasomal ATPases are recruited to many active promoters through binding to activators and play an important, nonproteolytic role in promoter escape and elongation. In this study, we report the discovery of a new nonproteolytic activity of the proteasome (specifically the proteasomal ATPases): the active destabilization of activator-promoter complexes. This reaction depends on the presence of an activation domain and ATP. Destabilization is inhibited in vitro and in vivo if the protein is monoubiquitylated or if ubiquitin is genetically fused to the activator. The fact that monoubiquitylated activator is resistant to the "stripping" activity of the proteasomal ATPases may explain, in part, why some activators require this modification in order to function efficiently.

Keeping transcriptional activators under control.

Transcriptional activators need to be modulated and eventually switched off after the initial event that triggers their activation. Here, we discuss how ubiquitination of activators and their proteasome-mediated turnover are crucial steps in this process.

Proteolytic turnover of the Gal4 transcription factor is not required for function in vivo.

Transactivator-promoter complexes are essential intermediates in the activation of eukaryotic gene expression. Recent studies of these complexes have shown that some are quite dynamic in living cells owing to rapid and reversible disruption of activator-promoter complexes by molecular chaperones, or a slower, ubiquitin-proteasome-pathway-mediated turnover of DNA-bound activator. These mechanisms may act to ensure continued responsiveness of activators to signalling cascades by limiting the lifetime of the active protein-DNA complex. Furthermore, the potency of some activators is compromised by proteasome inhibition, leading to the suggestion that periodic clearance of activators from a promoter is essential for high-level expression. Here we describe a variant of the chromatin immunoprecipitation assay that has allowed direct observation of the kinetic stability of native Gal4-promoter complexes in yeast. Under non-inducing conditions, the complex is dynamic, but on induction the Gal4-promoter complexes 'lock in' and exhibit long half-lives. Inhibition of proteasome-mediated proteolysis had little or no effect on Gal4-mediated gene expression. These studies, combined with earlier data, show that the lifetimes of different transactivator-promoter complexes in vivo can vary widely and that proteasome-mediated turnover is not a general requirement for transactivator function.

First-in-class pan caspase inhibitor developed for the treatment of liver disease.

A series of oxamyl dipeptides were optimized for pan caspase inhibition, anti-apoptotic cellular activity and in vivo efficacy. This structure-activity relationship study focused on the P4 oxamides and warhead moieties. Primarily on the basis of in vitro data, inhibitors were selected for study in a murine model of alpha-Fas-induced liver injury. IDN-6556 (1) was further profiled in additional in vivo models and pharmacokinetic studies. This first-in-class caspase inhibitor is now the subject of two Phase II clinical trials, evaluating its safety and efficacy for use in liver disease.

Structure-activity relationships within a series of caspase inhibitors. Part 2: Heterocyclic warheads.

Various heterocyclic hetero-methyl ketones of the 1-naphthyloxyacetyl-Val-Asp backbone have been prepared. A study of their structure-activity relationship (SAR) related to caspase-1, -3, -6, and -8 is reported. Their efficacy in a cellular model of cell death is also discussed. Potent broad-spectrum caspase inhibitors have been identified.

Oxamyl dipeptide caspase inhibitors developed for the treatment of stroke.

Structural modifications were made to a previously described acyl dipeptide caspase inhibitor, leading to the oxamyl dipeptide series. Subsequent SAR studies directed toward the warhead, P2, and P4 regions of this novel peptidomimetic are described herein.

Structure-activity relationships within a series of caspase inhibitors: effect of leaving group modifications.

Various aryloxy methyl ketones of the 1-naphthyloxyacetyl-Val-Asp backbone have been prepared. A systematic study of their structure-activity relationship (SAR) related to caspases 1, 3, 6, and 8 is reported. Highly potent irreversible broad-spectrum caspase inhibitors have been identified. Their efficacy in cellular models of cell death and inflammation are also discussed.