Developing predictive molecular maps of human disease through community-based modeling

Derry, Jonathan M.J.; Mangravite, Lara M.; Suver, Christine; Furia, Matthew D.; Henderson, David C.; Schildwachter, Xavier; Bot, Brian M.; Izant, Jonathan G.; Sieberts, Solveig K.; Kellen, Michael R.; Friend, Stephen H.

doi:10.1038/ng.1089

Cited by 54 publications

(43 citation statements)

References 21 publications

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“…In addition, the networks and supplementary data have been deposited on an external repository for biomedical data (Synapse 84 ) and code has been deposited on GitHub. Links to these resources are available on our website and in Supplementary Table 6.…”

Section: Methodsmentioning

confidence: 99%

Tissue-specific regulatory circuits reveal variable modular perturbations across complex diseases

et al. 2016

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Mapping the molecular circuits that are perturbed by genetic variants underlying complex traits and diseases remains a great challenge. We present a comprehensive resource of 394 cell type and tissue-specific gene regulatory networks for human, each specifying the genome-wide connectivity between transcription factors, enhancers, promoters and genes. Integration with 37 genome-wide association studies (GWASs) shows that disease-associated genetic variants — including variants that do not reach genome-wide significance — often perturb regulatory modules that are highly specific to disease-relevant cell types or tissues. Our resource opens the door to systematic analysis of regulatory programs across hundreds of human cell types and tissues.

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Section: Methodsmentioning

confidence: 99%

Tissue-specific regulatory circuits reveal variable modular perturbations across complex diseases

et al. 2016

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“…The Synapse platform from Sage specifically provides a secure, Health Insurance Portability and Accountability Act (HIPAA)–compliant infrastructure that enables data versioning and provenance (12), and the cBioPortal provides visualization and analysis features for exploring large-scale, deidentified cancer genomic datasets (13, 14). …”

Section: Introductionmentioning

confidence: 99%

AACR Project GENIE: Powering Precision Medicine through an International Consortium

André¹,

Arnedos²,

Baras³

et al. 2017

Cancer Discovery

1,377

758

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The AACR Project GENIE is an international data-sharing consortium focused on generating an evidence base for precision cancer medicine by integrating clinical-grade cancer genomic data with clinical outcome data for tens of thousands of cancer patients treated at multiple institutions worldwide. In conjunction with the first public data release from approximately 19,000 samples, we describe the goals, structure, and data standards of the consortium and report conclusions from high-level analysis of the initial phase of genomic data. We also provide examples of the clinical utility of GENIE data, such as an estimate of clinical actionability across multiple cancer types (>30%) and prediction of accrual rates to the NCI-MATCH trial that accurately reflect recently reported actual match rates. The GENIE database is expected to grow to >100,000 samples within 5 years and should serve as a powerful tool for precision cancer medicine. Significance The AACR Project GENIE aims to catalyze sharing of integrated genomic and clinical datasets across multiple institutions worldwide, and thereby enable precision cancer medicine research, including the identification of novel therapeutic targets, design of biomarker-driven clinical trials, and identification of genomic determinants of response to therapy.

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“…Moreover, adapting new efforts, such as ‘crowd sourcing’ to large data analysis, have already provided an exciting and novel way to analyse large system-level biological data. 38,39 Projects such as the Dialogue for Reverse Engineering Assessments and Methods (DREAM challenge), have made ‘big data’, collected through efforts such as the ICBP, available to the international community of computational biologists and mathematicians (Table 1). …”

Section: Cancer Systems Biology Resourcesmentioning

confidence: 99%

“…A different crowdsourcing research study focused on developing prognostic models for breast cancer using genome-scale data (gene expression, copy number analysis, and clinical variables), and showed the approach to be capable of generating prognostic models of at least equal quality to previously reported studies, 110 and consistent across multiple independent evaluations. 38,39 Much as there have been different experimental approaches to understand cancer there have also been many different modeling approaches that have been developed. The modeling approaches utilise different algorithms and these are largely dependent on the type of data that has been available and the questions that are being answered…”

Section: Data Sharingmentioning

confidence: 99%

Cancer Systems Biology: a peek into the future of patient care?

2014

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Traditionally, scientific research has focused on studying individual events, such as single mutations, gene function or the effect of the manipulation of one protein on a biological phenotype. A range of technologies, combined with the ability to develop robust and predictive mathematical models, is beginning to provide information that will enable a holistic view of how the genomic and epigenetic aberrations in cancer cells can alter the homeostasis of signalling networks within these cells, between cancer cells and the local microenvironment, at the organ and organism level. This systems biology process needs to be integrated with an iterative approach wherein hypotheses and predictions that arise from modelling are refined and constrained by experimental evaluation. Systems biology approaches will be vital for developing and implementing effective strategies to deliver personalized cancer therapy. Specifically, these approaches will be important to select those patients most likely to benefit from targeted therapies as well as for the development and implementation of rational combinatorial therapies. Systems biology can help to increase therapy efficacy or bypass the emergence of resistance, thus converting the current (often short term) effects of targeted therapies into durable responses, ultimately to improve quality of life and provide a cure.

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Developing predictive molecular maps of human disease through community-based modeling

Cited by 54 publications

References 21 publications

Tissue-specific regulatory circuits reveal variable modular perturbations across complex diseases

Tissue-specific regulatory circuits reveal variable modular perturbations across complex diseases

AACR Project GENIE: Powering Precision Medicine through an International Consortium

Cancer Systems Biology: a peek into the future of patient care?

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