The Efficacy and Limitations of Proteomics in Precision Medicine

The Importance of Incorporating Cellular Physiology, Environment, and Medical History in Custom Treatment Plans

Genetics is a powerful tool that has allowed us significant advancements in the medical field. Unfortunately, a person's genetics cannot predict the wide diversity of protein expression patterns, post-translational modifications (PTMs), or protein-protein interactions that an individual will experience.

 

These factors are important to conduced as they will control an individual’s response to a disease or treatment. Precision Medicine is one company striving to overcome this exact limitation. Their research seeks to incorporate an individual’s cellular physiology, environment, and medical history to create a custom treatment plan for each condition they experience.

 

The most holistic view is achieved by using mass spectrometers (MS). The analytical tool can analyze proteins, peptide fragments, small molecules, antibodies, metabolites, and lipids to generate the total of a patient’s physiological state.

 

While there are great benefits that will come with using proteomics in the medical industry, I do not believe they will be successfully applied in the near future. My reasoning behind this belief is the static growth of new diagnostic protein assays.

 

These assays are responsible for providing us with biomarkers to identify various diseases/complications in the body. With no new biomarkers, clinical validation is challenging and limits the proteomics ability to provide an accurate diagnosis or treatment plan for the patient..

 

Even as databases for biomarkers grow, there will still be other difficulties surrounding the effective diagnosis of a disease. Specifically, MS analysis has three prominent inaccuracies. First, not all proteins ionize well and are not detected. This creates an inconclusive or incorrect reading of the individuals' proteome.

 

Second, large molecules do not have a sufficiently unique mass for identification. Being unable to definitively identify proteins can lead to key biomarkers being missed.

 

Finally, while there are many different proteins in a proteome, it is theoretically possible for different proteins to have the same amino acid composition. As a result, they will have the same mass and can not be definitively identified.

 

While there are general limitations to MS analysis, there are several advantages as well. There is not just one type of MS available for scientists to use. Rather, there are several different analysis methods each with its own advantages and disadvantages.

 

The type of MS you pick is greatly influenced by what type of sample you are analyzing and what exactly you are looking for. One specific type of MS that has been very successful in both the diagnosis and prognosis of medical conditions is MALDI-MS.

 

This tool has been applied to diseases including, but not limited to, lung, breast, and ovarian cancers to correlate treatment outcomes or disease progression with changing molecular events in tissue.

 

This technique allows researchers to visualize the distribution of drugs and associate metabolites in the system. Drug developers greatly benefit from this as they can identify the biotransformation pathway of a drug, whether it reaches its intended target location, and where the drug or metabolites might accumulate to cause adverse effects

 

Understanding these pathways is a key step toward creating future custom treatment plans. Overall, valuable analytic techniques have been developed to provide scientists with very important infuriation about how a proteome is a function. This allows for a tailored understanding of a specific human or organism.

 

Unfortunately, we are still a long way away from developing patient-specific treatments. A much more accurate reading of proteins will be needed along with a much larger database of biomarkers. This will allow for an accurate diagnosis and prognosis required for such a tailored treatment plan.