Whole genome identification of Mycobacterium tuberculosis vaccine candidates by comprehensive data mining and bioinformatic analyses

<p>Abstract</p> <p>Background</p> <p><it>Mycobacterium tuberculosis</it>, the causative agent of tuberculosis (TB), infects ~8 million annually culminating in ~2 million deaths. Moreover, about one third of the population is latently infected, 10% of which develop disease during lifetime. Current approved prophylactic TB vaccines (BCG and derivatives thereof) are of variable efficiency in adult protection against pulmonary TB (0%–80%), and directed essentially against early phase infection.</p> <p>Methods</p> <p>A genome-scale dataset was constructed by analyzing published data of: (1) global gene expression studies under conditions which simulate intra-macrophage stress, dormancy, persistence and/or reactivation; (2) cellular and humoral immunity, and vaccine potential. This information was compiled along with revised annotation/bioinformatic characterization of selected gene products and <it>in silico </it>mapping of T-cell epitopes. Protocols for scoring, ranking and prioritization of the antigens were developed and applied.</p> <p>Results</p> <p>Cross-matching of literature and <it>in silico</it>-derived data, in conjunction with the prioritization scheme and biological rationale, allowed for selection of 189 putative vaccine candidates from the entire genome. Within the 189 set, the relative distribution of antigens in 3 functional categories differs significantly from their distribution in the whole genome, with reduction in the Conserved hypothetical category (due to improved annotation) and enrichment in Lipid and in Virulence categories. Other prominent representatives in the 189 set are the PE/PPE proteins; iron sequestration, nitroreductases and proteases, all within the Intermediary metabolism and respiration category; ESX secretion systems, resuscitation promoting factors and lipoproteins, all within the Cell wall category. Application of a ranking scheme based on qualitative and quantitative scores, resulted in a list of 45 best-scoring antigens, of which: 74% belong to the dormancy/reactivation/resuscitation classes; 30% belong to the Cell wall category; 13% are classical vaccine candidates; 9% are categorized Conserved hypotheticals, all potentially very potent T-cell antigens.</p> <p>Conclusion</p> <p>The comprehensive literature and <it>in silico</it>-based analyses allowed for the selection of a repertoire of 189 vaccine candidates, out of the whole-genome 3989 ORF products. This repertoire, which was ranked to generate a list of 45 top-hits antigens, is a platform for selection of genes covering all stages of <it>M. tuberculosis </it>infection, to be incorporated in rBCG or subunit-based vaccines.</p

Value analysis of digital breast tomosynthesis for breast cancer screening in a commercially-insured US population

Machaon M Bonafede,1 Vivek B Kalra,2 Jeffrey D Miller,1 Laurie L Fajardo3 1Truven Health Analytics, Cambridge, MA, 2Yale University School of Medicine, New Haven, CT, 3Department of Radiology, University of Iowa College of Medicine, Iowa City, IA, USA Purpose: The objective of this study was to conduct a value analysis of digital breast tomosynthesis (DBT) for breast cancer screening among women enrolled in US commercial health insurance plans to assess the potential budget impact associated with the clinical benefits of DBT. Methods: An economic model was developed to estimate the system-wide financial impact of DBT as a breast cancer screening modality within a hypothetical US managed care plan with one million members. Two scenarios were considered for women in the health plan who undergo annual screening mammography, ie, full field digital mammography (FFDM) and combined FFDM + DBT. The model focused on two main drivers of DBT value, ie, the capacity for DBT to reduce the number of women recalled for additional follow-up imaging and diagnostic services and the capacity of DBT to facilitate earlier diagnosis of cancer at less invasive stages where treatment costs are lower. Model inputs were derived from published sources and from analyses of the Truven Health MarketScan&reg; Research Databases (2010&ndash;2012). Comparative clinical and economic outcomes were simulated for one year following screening and compared on an incremental basis. Results: Base-case analysis results show that 4,523 women in the hypothetical million member health plan who are screened using DBT avoid the use of follow-up services. The overall benefit of DBT was calculated at $78.53 per woman screened. Adjusting for a hypothetical$50 incremental cost of the DBT examination, this translates to $28.53 savings per woman screened, or$0.20 savings per member per month across the plan population and an overall cost savings to the plan of $2.4 million per year. Conclusion: The results of this study demonstrate clinical and economic favorability of DBT for breast cancer screening among commercially-insured US women. Wider adoption of DBT mammography presents an opportunity to deliver value-based care in the US health care system. Keywords: breast cancer screening, mammography, digital breast tomosynthesis, cost analysis, value analysis, economic mode