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Review of "Systems Biology, Proteomics, and the Future of Health Care: Toward Predictive, Preventive, and Personalized Medicine".
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'''Biomarkers''' '''Biomarkers'''
using blood plasma proteome patterns ("proteome signature") to distinguish normal organ function from pathogenic organ function '''Serum Proteome Pattern Diagnostics''' using blood plasma proteome patterns ("proteome signature") to distinguish normal organ function from pathogenic organ function '''Serum Proteome Pattern Diagnostics'''
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Program using Artificial Intelligence pattern recognition was used to "learn" the healthy proteome Mass Spec distribution, and was able to accurately predict unhealthy distributions, thus diagnosing patients with ovarian cancer Program using Artificial Intelligence pattern recognition was used to "learn" the healthy proteome Mass Spec distribution, and was able to accurately predict unhealthy distributions, thus diagnosing patients with ovarian cancer
signature has also been developed to distinguish patients with prostrate cancer from healthy patients signature has also been developed to distinguish patients with prostrate cancer from healthy patients

Revision as of 06:19, 20 October 2005

Contents

Mark Kaganovich

Background

I'm a senior concentrating in Biochemistry and Computer Science.

Biophysics 101 Assignments

Week 4

- Review and comments concerning Systems Biology, Proteomics, and the Future of Health Care: Toward Predictive, Preventative, and Personalized Medicine and ideas relating to it

also reviewed by Chiki

Week 3

Introduction to Personalized Medicine

Review of "Systems Biology, Proteomics, and the Future of Health Care: Toward Predictive, Preventive, and Personalized Medicine".

link to paper

This article has a good introductory discussion of Systems Biology and the technologies that it utilizes and its applications to personalized medicine. The authors make a good point that is relevant to our potential project idea of thinking about software that can help people effect their lifestyles based on genomic data. They mention that environmental factors can also be monitored with developing technologies - just like we assume individual genome sequencing will be accessible to most people in the near future, technologies that will be able to tell people what kind of chemicals they are exposed to, what their diet is, etc. will be soon available. This can be integrated into our model.

The authors argue that systems biology will be crucial to elucidating the mechanism of disease, which is essential for prediction and prevention. They also argue that a systems approach can prove very useful in treatment as well since while current treatments are focused on single molecules (like inhibitors, etc.) "the behaviors of most biological systems, including those affected in cancer, cannot be attributed to a single molecule or pathway, rather they emerge as a result of interactions at multiple levels, and among many cellular components."

Biomarkers using blood plasma proteome patterns ("proteome signature") to distinguish normal organ function from pathogenic organ function Serum Proteome Pattern Diagnostics

 Program using Artificial Intelligence pattern recognition was used to "learn" the healthy proteome Mass Spec distribution, and was able to accurately predict unhealthy distributions, thus diagnosing patients with ovarian cancer
 signature has also been developed to distinguish patients with prostrate cancer from healthy patients



Protein chips.

Intro to Personalized Medicine

Intro to Personalized Medicine Good article summarizing the companies exploring this area: http://www.bio-itworld.com/archive/100902/path.html

A goal of Personalized Medicine is to figure out which variations in the human genome are responsible for various diseases/conditions. Figuring this out will enable the administration of drugs that are more appropriate for an individual genotype, diagnose diseases more accurately and efficiently, and screen patients for clinical trials, etc.

The problem is currently being explored by several companies (Millenium Pharmaceuticals, Inc., Cambridge, MA; DeCODE Genetics, Iceland; Sequenom, San Diego, CA; Genome Therapeutics, Waltham, MA; Variagenics Inc., Cambridge, MA; Compugen, Israel to name the few that are mentioned in the above article). The companies are comparing genomes of individuals and isolating genetic markers that distinguish diseased genomes from healthy ones. The most common markers are Single Nucleotide Polymorphisms (SNPs) and microsatelites. For example, genomes from young patients are compred to healthy, old patients and SNPs that distinguish the two are investigated for their relevance in disease. They use statistics and bioinformatics to isolate the genes that seem to correlate to specific diseases/conditions. The result is that genes involved in asthma, hypertension, schizophrenia, allergies, diabetes, osteoporosis, breast cancer, melanoma, etc. have been mapped.

It becomes clear that an important challenge is to categorize people/genomes into geneologic groups so that doing genetics and statistics is possible.

Also, to make sequencing more economically viable and efficient, it is important to be able to identify and sequence specific genes in patients, once we know which genes we are looking for.


The review Meyer, J.M. and Ginsburg, G.S. (2002).The path to personalized medicine. Curr Opin Chem Biol 6:434-438 talks about this in a little bit more detail.

Image:Fig1.gif This figure illustrates the major areas where personal genomics research is applicable: screening for patient predisposition to a disease/condition, screening for disease onset, diagnosing a disease, and treating and monitoring a disease by applying therapeutics catered more specifically to the individual.

The article also talks about recent research in Single Nucleotide Polymorphisms (SNPs) and the identification of haplotype blocks, which are linkages between SNPs the knowledge of which helps minimize the number of SNPs that need to be searched to establish effective biomarkers.

Some questions/comments: -How is a sufficiently representative sample of the healthy human population obtained? -A useful tool would be a way of measuring dynamic gene expression during disease progression in humans.