Dataset Information

Multi-level model for the investigation of oncoantigen-driven vaccination effect.

ABSTRACT: BACKGROUND: Cancer stem cell theory suggests that cancers are derived by a population of cells named Cancer Stem Cells (CSCs) that are involved in the growth and in the progression of tumors, and lead to a hierarchical structure characterized by differentiated cell population. This cell heterogeneity affects the choice of cancer therapies, since many current cancer treatments have limited or no impact at all on CSC population, while they reveal a positive effect on the differentiated cell populations. RESULTS: In this paper we investigated the effect of vaccination on a cancer hierarchical structure through a multi-level model representing both population and molecular aspects. The population level is modeled by a system of Ordinary Differential Equations (ODEs) describing the cancer population's dynamics. The molecular level is modeled using the Petri Net (PN) formalism to detail part of the proliferation pathway. Moreover, we propose a new methodology which exploits the temporal behavior derived from the molecular level to parameterize the ODE system modeling populations. Using this multi-level model we studied the ErbB2-driven vaccination effect in breast cancer. CONCLUSIONS: We propose a multi-level model that describes the inter-dependencies between population and genetic levels, and that can be efficiently used to estimate the efficacy of drug and vaccine therapies in cancer models, given the availability of molecular data on the cancer driving force.

SUBMITTER: Cordero F

PROVIDER: S-EPMC3633011 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Multi-level model for the investigation of oncoantigen-driven vaccination effect.

Cordero Francesca F Beccuti Marco M Fornari Chiara C Lanzardo Stefania S Conti Laura L Cavallo Federica F Balbo Gianfranco G Calogero Raffaele R

BMC bioinformatics 20130417

<h4>Background</h4>Cancer stem cell theory suggests that cancers are derived by a population of cells named Cancer Stem Cells (CSCs) that are involved in the growth and in the progression of tumors, and lead to a hierarchical structure characterized by differentiated cell population. This cell heterogeneity affects the choice of cancer therapies, since many current cancer treatments have limited or no impact at all on CSC population, while they reveal a positive effect on the differentiated cell ...[more]

PMID: 23734974

Similar Datasets

Project description:ObjectivesTo determine if living in areas where higher proportions of people of the same ethnicity reside is protective for common mental disorders, and associated with a reduced exposure to discrimination and improved social support. Finally, to determine if any protective ethnic density effects are mediated by reduced exposure to racism and improved social support.DesignMulti-level logistic regression analysis of national survey data, with area-level, own-group ethnic density modelled as the main exposure. Participants and setting 4281 participants of Irish, black Caribbean, Indian, Pakistani, Bangladeshi, and white British ethnicity, aged 16-74 years, randomly sampled from 892 "middle layer super output areas" in England.Main outcome measuresCommon mental disorders (assessed via structured interviews); discrimination (assessed via structured questionnaire); and social support and social networks (assessed via structured questionnaire).ResultsAlthough the most ethnically dense areas were also the poorest, for each 10 percentage point increase in own-group ethnic density, there was evidence of a decreased risk of common mental disorders, for the full ethnic minority sample (odds ratio 0.94 (95% confidence interval 0.89 to 0.99); P=0.02, trend), for the Irish group (odds ratio 0.21 (0.06 to 0.74); P=0.01, trend), and for the Bangladeshi group (odds ratio 0.75 (0.62 to 0.91); P=0.005, trend), after adjusting for a priori confounders. For some groups, living in areas of higher own-group density was associated with a reduction in the reporting of discrimination and with improved social support and improved social networks. However, none of these factors mediated ethnic density effects.ConclusionsA protective effect of living in areas of higher own-group ethnic density was present for common mental disorders for some minority groups. People living in areas of higher own-group density may report improved social support and less discrimination, but these associations did not fully account for density effects.

Project description:This article describes the data, data flows, and spreadsheet implementations for linking multi-level contribution margin accounting as a subsystem in cost accounting with several versions of a multi-level fixed-charge problem (MLFCP), the latter based on the optimization approach in operations research. This linkage can reveal previously hidden optimization potentials within the framework of multi-level contribution margin accounting, thus providing better information for decision making in companies and other organizations. For the data, plausible fictitious values have been assumed taking into consideration the calculation principles in cost accounting where applicable. They include resource-related data, market-related data, and data from cost accounting needed to analyze the profitability of a company´s products and organizational entities in the presence of hierarchically structured fixed costs. The data are processed and analyzed by means of mathematical optimization techniques and sensitivity analysis. The linkage between multi-level contribution margin accounting and MLFCP is implemented in three spreadsheet files, including versions for deterministic optimization, stochastic optimization, and robust optimization. This paper provides specifications for compatible solver add-ins and for executing sensitivity analysis. The data and spreadsheet implementations described in this article were used in a research article entitled "Making better decisions by applying mathematical optimization to cost accounting: An advanced approach to multi-level contribution margin accounting" [1]. The data sets and the spreadsheet implementations may be reused a) by researchers in management and cost accounting as well as in operations research and quantitative methods for verification and for further development of the linkage concept and of the underlying optimization models; b) by practitioners for gaining insight into the data requirements, methods, and benefits of the proposed linkage, thus supporting continuing education; and c) by instructors in academia who may find the data and spreadsheets valuable for classroom use in advanced courses. The complete spreadsheet implementations in the form of three ready-to-use Excel files (deterministic, stochastic, and robust version) are available for download at Mendeley Data. They may serve as customizable templates for various use cases in research, practice, and education.

Dataset Information

Multi-level model for the investigation of oncoantigen-driven vaccination effect.

Publications

Multi-level model for the investigation of oncoantigen-driven vaccination effect.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets