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:: Posted by American Biotechnologist on 04-13-2011
Lisa Grauer from BioTechniques recently discussed an elegant study by Dr. Benjamin Natelson of the University of Medicine and Dentistry of New Jersey, that highlights the utility of proteome-wide association studies in disease diagnosis.
Her article focused on a study that compared the protein profile in the cerebral spinal fluid (CSF) of “normal” individuals and those suffering from Chronic Fatigue Syndrome (CFS…talk about getting confused by acronyms) or neurologic post-treatment Lyme syndrome (nPTLS). The results showed 738 proteins that were uniquely expressed in the CFS group and 692 in the nPTLS group. These findings are a significant step in the study of CFS and nPTLS which until now have been classified as “medically unexplained illnesses” often resulting in patient complaints not being taken seriously by their primary care provider.
While more detailed downstream analysis remain to be done, this study provides a wonderful example of how population-scale proteomic studies help in the advancement of disease diagnosis.
Less than a year ago, NCBI released FLink (frequency weighted links) which is a tool that enables users to traverse from a group of records in a source database to a ranked list of associated records in a destination database. I found FLink useful for cross-referencing my favorite gene (ETAR) against the BioSystems in which it appears. FLink’s is extremely easy to navigate and in combination with NCBI BioSystems helps to simplify complex processes.
Although FLink is pretty easy to use and self-explanatory, the OpenHelix blog has posted a video tutorial of FLink on SciVee which is a good place to start for anybody wishing to learn more about the tool before actually diving in.
How often have you used FLink? What is your favorite NCBI tool and how are you using it in your research?
In this TED presentation, scientist Danny Hill explains a fundamental difference between infectious diseases and cancer and why physicians need to change their method of treating both of them in a similar manner. According to Hill, infectious disease is an external attack on one’s body which can be defended against by a wide array of treatments (such as antibiotics). Cancer, on the other hand, is something that occurs naturally in every individual but spins out of control when naturally-occurring protection mechanisms fail. Hill proposes that we begin thinking of cancer as a verb and recognize that while everyone is “cancering” certain individuals have aberrant defense mechanisms which results in “cancer” related symptoms.
While the presentation was intended for a lay audience, seasoned scientists will appreciate Hill’s demonstration of how 2D Gel Electrophoresis can be used to identify differences in protein expression between healthy and diseased individuals. Automated analysis of serum protein is the most efficient way to diagnose patients and is what Hill’s company Applied Proteomics focuses on.
Grrl Scientist commented that she is skeptical that proteomic analysis of blood proteins can be used to track solid tumor progression. However, a quick pubmed search reveals thousands of articles written on tumor biomarkers found in serum, indicating that certain tumors either directly or indirectly secrete biomarkers into the blood which may eventually be used to detect tumor progression.
:: Posted by American Biotechnologist on 02-01-2011
Genome Medicine’s editors recently published an article outlining what they felt were the most exciting breakthroughs in research in the past 2 years and what (in their opinion) the future of genomic medicine might hold. Below is a brief summary of their recommended steps for improvement over the next two years.
improved analytical power to keep pace with falling costs and exponential increase in DNA sequencing capabilities of whole-genome sequencing
a plan for dealing with the “public’s” perception of genomic research and their need for “control” over their own genetic samples
a plan for closing the gap between discovery and clinical validity of personalized medicine
the need to develop a multidisciplinary translation research agenda
to be able to characterize all forms of genetic variation in an individual patient’s genome including single or simple nucleotide variation (SNV) and copy number variation (CNV)
more complete tools for the physician including information on individual genetic make-up of the patient which can be used to guide the selection of drugs or treatment processes
increased sensitivity of proteomics-based analytical techniques that will enable identification of disease-specific biomarkers and enhanced quantitative measurement of specific proteins in clinical samples
The editorial represents the opinions of editors in the USA, Canada, Germany and France and can therefore be assumed to be universally relevant.