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The biomolecular era for thoracic surgeons: the example of the ESTS Biology Club.

ABSTRACT: Understanding basic mechanisms of lung disease may help to move forward the management of our patients. Molecular biology has affected our diagnostic and therapeutic pathways in the direction of personalized medicine not only for thoracic malignancies. Accordingly, thoracic surgeons are becoming increasingly aware that specific knowledge of genetic and epigenetic alterations may influence their clinical behavior-from the ward to the operating room (OR). In this continuously evolving scenario, surgical societies have perceived the increasing relevance of biomolecular medicine in the practice of modern thoracic surgery. More recently, in the spirit of mutual collaboration between sister societies, the European Society of Thoracic Surgeons (ESTS) has adopted the concept of the American Association for Thoracic Surgery (AATS) incorporating one session dedicated to the Biology Club within the Annual Meeting Program. The aim of the ESTS Biology Club is to outline and sponsor the new profile of the surgeon scientist during the only world meeting exclusively focused on general thoracic surgery. The following article will summarize the significance of this and give an update on molecular biology tools for thoracic malignancies.

SUBMITTER: Opitz I

PROVIDER: S-EPMC4032959 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

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The biomolecular era for thoracic surgeons: the example of the ESTS Biology Club.

Opitz Isabelle I D'Amico Thomas A TA Rocco Gaetano G

Journal of thoracic disease 20140501

Understanding basic mechanisms of lung disease may help to move forward the management of our patients. Molecular biology has affected our diagnostic and therapeutic pathways in the direction of personalized medicine not only for thoracic malignancies. Accordingly, thoracic surgeons are becoming increasingly aware that specific knowledge of genetic and epigenetic alterations may influence their clinical behavior-from the ward to the operating room (OR). In this continuously evolving scenario, su ...[more]

PMID: 24868444

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Project description:Background and contributionIn network biology, molecular functions can be characterized by network-based inference, or "guilt-by-associations." PageRank-like tools have been applied in the study of biomolecular interaction networks to obtain further the relative significance of all molecules in the network. However, there is a great deal of inherent noise in widely accessible data sets for gene-to-gene associations or protein-protein interactions. How to develop robust tests to expand, filter, and rank molecular entities in disease-specific networks remains an ad hoc data analysis process.ResultsWe describe a new biomolecular characterization and prioritization tool called Weighted In-Network Node Expansion and Ranking (WINNER). It takes the input of any molecular interaction network data and generates an optionally expanded network with all the nodes ranked according to their relevance to one another in the network. To help users assess the robustness of results, WINNER provides two different types of statistics. The first type is a node-expansion p-value, which helps evaluate the statistical significance of adding "non-seed" molecules to the original biomolecular interaction network consisting of "seed" molecules and molecular interactions. The second type is a node-ranking p-value, which helps evaluate the relative statistical significance of the contribution of each node to the overall network architecture. We validated the robustness of WINNER in ranking top molecules by spiking noises in several network permutation experiments. We have found that node degree-preservation randomization of the gene network produced normally distributed ranking scores, which outperform those made with other gene network randomization techniques. Furthermore, we validated that a more significant proportion of the WINNER-ranked genes was associated with disease biology than existing methods such as PageRank. We demonstrated the performance of WINNER with a few case studies, including Alzheimer's disease, breast cancer, myocardial infarctions, and Triple negative breast cancer (TNBC). In all these case studies, the expanded and top-ranked genes identified by WINNER reveal disease biology more significantly than those identified by other gene prioritizing software tools, including Ingenuity Pathway Analysis (IPA) and DiAMOND.ConclusionWINNER ranking strongly correlates to other ranking methods when the network covers sufficient node and edge information, indicating a high network quality. WINNER users can use this new tool to robustly evaluate a list of candidate genes, proteins, or metabolites produced from high-throughput biology experiments, as long as there is available gene/protein/metabolic network information.

Dataset Information

The biomolecular era for thoracic surgeons: the example of the ESTS Biology Club.

Publications

The biomolecular era for thoracic surgeons: the example of the ESTS Biology Club.

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