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The role of quantitative mass spectrometry in the discovery of pancreatic cancer biomarkers for translational science

Overview of attention for article published in Journal of Translational Medicine, April 2014
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Title
The role of quantitative mass spectrometry in the discovery of pancreatic cancer biomarkers for translational science
Published in
Journal of Translational Medicine, April 2014
DOI 10.1186/1479-5876-12-87
Pubmed ID
Authors

Daniel Ansari, Linus Aronsson, Agata Sasor, Charlotte Welinder, Melinda Rezeli, György Marko-Varga, Roland Andersson

Abstract

In the post-genomic era, it has become evident that genetic changes alone are not sufficient to understand most disease processes including pancreatic cancer. Genome sequencing has revealed a complex set of genetic alterations in pancreatic cancer such as point mutations, chromosomal losses, gene amplifications and telomere shortening that drive cancerous growth through specific signaling pathways. Proteome-based approaches are important complements to genomic data and provide crucial information of the target driver molecules and their post-translational modifications. By applying quantitative mass spectrometry, this is an alternative way to identify biomarkers for early diagnosis and personalized medicine. We review the current quantitative mass spectrometric technologies and analyses that have been developed and applied in the last decade in the context of pancreatic cancer. Examples of candidate biomarkers that have been identified from these pancreas studies include among others, asporin, CD9, CXC chemokine ligand 7, fibronectin 1, galectin-1, gelsolin, intercellular adhesion molecule 1, insulin-like growth factor binding protein 2, metalloproteinase inhibitor 1, stromal cell derived factor 4, and transforming growth factor beta-induced protein. Many of these proteins are involved in various steps in pancreatic tumor progression including cell proliferation, adhesion, migration, invasion, metastasis, immune response and angiogenesis. These new protein candidates may provide essential information for the development of protein diagnostics and targeted therapies. We further argue that new strategies must be advanced and established for the integration of proteomic, transcriptomic and genomic data, in order to enhance biomarker translation. Large scale studies with meta data processing will pave the way for novel and unexpected correlations within pancreatic cancer, that will benefit the patient, with targeted treatment.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 1%
United States 1 1%
Unknown 82 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 23%
Student > Master 14 17%
Student > Bachelor 11 13%
Researcher 11 13%
Student > Doctoral Student 6 7%
Other 13 15%
Unknown 10 12%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 21 25%
Agricultural and Biological Sciences 15 18%
Medicine and Dentistry 13 15%
Chemistry 6 7%
Immunology and Microbiology 3 4%
Other 14 17%
Unknown 12 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 April 2014.
All research outputs
#20,228,193
of 22,753,345 outputs
Outputs from Journal of Translational Medicine
#3,305
of 3,977 outputs
Outputs of similar age
#193,108
of 226,065 outputs
Outputs of similar age from Journal of Translational Medicine
#36
of 63 outputs
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