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Analysis and Prediction of Pathways in HeLa Cells by Integrating Biological Levels of Organization with Systems-Biology Approaches

Overview of attention for article published in PLOS ONE, June 2013
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Title
Analysis and Prediction of Pathways in HeLa Cells by Integrating Biological Levels of Organization with Systems-Biology Approaches
Published in
PLOS ONE, June 2013
DOI 10.1371/journal.pone.0065433
Pubmed ID
Authors

Juan Carlos Higareda-Almaraz, Ilse A. Valtierra-Gutiérrez, Magdalena Hernandez-Ortiz, Sandra Contreras, Erika Hernandez, Sergio Encarnacion

Abstract

It has recently begun to be considered that cancer is a systemic disease and that it must be studied at every level of complexity using many of the currently available approaches, including high-throughput technologies and bioinformatics. To achieve such understanding in cervical cancer, we collected information on gene, protein and phosphoprotein expression of the HeLa cell line and performed a comprehensive analysis of the different signaling pathways, transcription networks and metabolic events in which they participate. A total expression analysis by RNA-Seq of the HeLa cell line showed that 19,974 genes were transcribed. Of these, 3,360 were over-expressed, and 2,129 under-expressed when compared to the NHEK cell line. A protein-protein interaction network was derived from the over-expressed genes and used to identify central elements and, together with the analysis of over-represented transcription factor motifs, to predict active signaling and regulatory pathways. This was further validated by Metal-Oxide Affinity Chromatography (MOAC) and Tandem Mass Spectrometry (MS/MS) assays which retrieved phosphorylated proteins. The 14-3-3 family members emerge as important regulators in carcinogenesis and as possible clinical targets. We observed that the different over- and under-regulated pathways in cervical cancer could be interrelated through elements that participate in crosstalks, therefore belong to what we term "meta-pathways". Additionally, we highlighted the relations of each one of the differentially represented pathways to one or more of the ten hallmarks of cancer. These features could be maintained in many other types of cancer, regardless of mutations or genomic rearrangements, and favor their robustness, adaptations and the evasion of tissue control. Probably, this could explain why cancer cells are not eliminated by selective pressure and why therapy trials directed against molecular targets are not as effective as expected.

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Geographical breakdown

Country Count As %
Brazil 2 3%
Japan 1 2%
Hungary 1 2%
Mexico 1 2%
Unknown 54 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 27%
Student > Ph. D. Student 8 14%
Student > Master 7 12%
Student > Bachelor 6 10%
Other 5 8%
Other 8 14%
Unknown 9 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 29%
Biochemistry, Genetics and Molecular Biology 14 24%
Computer Science 6 10%
Medicine and Dentistry 4 7%
Chemistry 2 3%
Other 7 12%
Unknown 9 15%