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DNA Sequencing: The Backbone of Personalized Medicine

Concept of Personalized Medical Care

As a society, we have been accustomed to the concept of a “one-size-fits-all” approach to healthcare. However, this has not been ideal for many people and limits the success of medical management. There are instances where there is some level of tailoring to the individual, but not to the extent needed to address the numerous nuisances that can affect the optimal results of a person’s medical plan. The concept of personalized medicine is not a new one and has been desired for many years. However, achieving that goal is now becoming a reality.

Personalized medicine involves the use of individualized information so that medical treatment for a condition or disease can be tailored to the specific characteristics of the patient. This approach to health care also entails the use of specific data (primarily molecular in nature) to determine the likelihood of a risk for a particular disease well before symptoms are apparent. This allows a new level of preventive medicine consisting of intervention at the pre-disease stage.


Genomics and Diagnostics

Molecular diagnostic approaches are used in genetic screening clinical medicine. There are a variety of molecular diagnostic technologies including PCR-based tests, Gene chip and microfluidic microarrays, and gene expression-based tests. For this article, we will focus on DNA sequencing because of the recent and significant medical advances that are made with the newest DNA sequencing technologies.

Many diseases have been found to be strongly associated with genetic variations in the genome. Discoveries have revealed that although several people can have the same disease, the presence or manifestation of the disease can vary based on differences in the types of genetic variants in these individuals. Having the individual genome sequence information can allow clinicians to better determine the optimal treatment in the person´s particular case. Furthermore, having knowledge of the different genetic variants for a disease would provide a means to address preventive efforts by assessing  if a person may be susceptible to a given disease or condition.


Risk Assessment

The discovery of molecular markers associated with disease risk has bolstered the area of preventive medicine. Testing can be implemented to determine an individual’s risk of developing a particular disease. Early intervention can occur to help prevent the onset or manifestation of the disease. This is preferable to the need to treat a disease after signs and symptoms have begun, especially since it is much more difficult to treat a disease once it is in the advanced stages. In addition to survival and quality of life issues, health care costs are reduced when prevention is the focus.


Tailored Therapeutics

Tailoring a therapeutic regimen to the individual patient can significantly reduce the suffering and time lost due to initiating sub-optimal or ineffective treatments. Also, treatments that are likely to cause idiosyncratic adverse reactions can potentially be avoided. Using genomic sequencing data can reveal information regarding genetic variants that affect drug metabolism. It can also reveal the underlying mechanism of a disease state so that the correct compound targeting that mechanism can be initiated early in the treatment phase of medical management. This approach can positively affect survival rates, increase quality of life, and reduce medical costs.


DNA Sequencing and Disease Management

Role of DNA Sequence Data in Disease Prevention

Due to DNA sequencing technologies, it is known that women with certain BRCA1 or BRCA2 gene mutations can have a higher chance of developing breast cancer by age 70 (65% chance for those with BRCA1 mutations, and 45% chance for those with BRACA2). This is compared to a 12% chance for women of the general population (1).  The ability to test for these variations before symptoms occur can direct screening protocols and preventive actions.  In addition to the breast cancer risk, approximately 1.3% of women in the general population will develop ovarian cancer by age 70. However, this risk increases to 39% and 11% for women with BRCA1 and BRCA2 mutations respectively (1).

The ability to determine risk at the personal level will allow better decision-making regarding preventive steps to take. Those found to have the higher risk factors can choose to undergo enhanced screening measures. Some may consider prophylactic surgery. Chemoprevention has also been undertaken to reduce breast and ovarian cancer in individuals with higher risk levels.


Personalized Diagnostics

An example regarding the identification of a disease-related genetic variant is that discovered by Alsters et al (2). The group performed whole-exome sequencing on a patient with obesity and metabolic disorders and on members of her family. They were able to discover a rare mutation in the carboxypeptidase E gene of the woman. This mutation is associated with loss of expression of the gene and is believed to be associated with the obesity syndrome as supported by mouse knockout studies.  

The use of genomic sequence testing has been more widely used in the area of cancer diagnostics. Whole-genome and RNA sequencing is a powerful tool to characterize tumors. This knowledge is harnessed to ultimately determine the treatment that will best halt tumor growth with the least toxicity to the patient. An example is the case of a person with acute lymphoblastic leukemia that did not respond to chemotherapy and a bone marrow transplant. Sequencing data uncovered overexpression of the FLT3 gene. Treatments with sunitinib (an FLT3 inhibitor) led to treatment success (3).


Choosing Optimal Therapies

As we have seen in the case of the sunitinib-responsive leukemia case, knowing specific sequence information of an individual can greatly improve and sometimes define treatment success. The molecular basis of various diseases is being revealed continuously via DNA sequencing technologies. This information is paramount when making decisions concerning the best therapeutic approaches. Using a “one-size-fits-all” approach can lead to failed treatments, trial and error efforts, and lost time for the patient. Chances of survival can increase drastically by making available better targeted and tailored courses of therapy.

DNA sequencing data can also help detect variations in genes coding for metabolizing enzymes and drug targets in general. This information can be used to predict and avoid adverse drug reactions and hypersensitivities. Armed with this type of information, medical personnel can select the optimal therapeutic compounds and doses as early as possible without the disadvantages of a trial and error approach.


Next-Generation Sequencing Transforms Medical Science

Massively parallel DNA sequencing technology such as next-generation sequencing (NGS) has begun to significantly benefit the genomic diagnostic arena. A major benefit is the accessibility to the clinical medical field due to the speed of obtaining actionable results and the markedly reduced cost of sequencing an individual’s genome. The use of NGS for clinical use is quite promising and is already providing an overwhelming collection of data that is being used to characterize many diseases, the factors that increases an individual’s susceptibility to disease and conditions, and the mechanisms related to drug metabolism, resistance, and more.  

In a study of lung cancer, Hageman et al (4) performed NGS assays of genes known to be mutated in different forms of lung cancer. It took less than a month to obtain the genomic data that revealed that 46% of the samples tested had KRAS mutations. With this information, the initiation of personalized therapeutic regimens was possible.  

An important consideration in the ability to rapidly and accurately obtain important sequence information is the instrumentation used to achieve the genomic diagnostic goals. An example of the equipment used to perform NGS is the HiSeq X, which can produce up to 1.8 terabases of data from a 3-day run. This combined with the use of bioinformatics programs provides a powerful tool to obtain a massive amount of valuable information for use at the population and personal medicine levels.  



There are some challenges regarding regulations associated with the clinical management and use of sequencing data. This includes policies governing the approval and use of genetic tests (considered medical devices) and approval of pharmaceuticals that are designed based on interpreted sequencing data. These challenges also dictate the extent and nature of the use of DNA sequencing data in a routine manner for personalized medicine. There are also concerns regarding the impact on insurance coverage decisions based on risk analyses obtained from sequencing data. Nonetheless, the benefits are expected to outweigh these current concerns.

The ability to obtain and use sequence information from the genome of an individual will greatly enhance diagnostic efforts minimizing misdiagnosis and enhancing the earliest possible detection. This can also promote the implementation of tailored treatments that are much more effective with lower toxicity. For society, this translates to higher survival rates and quality of life and lower healthcare costs.  

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  1. Antoniou A, Pharoah PD, Narod S, et al. Average risks of breast and ovarian cancer associated with BRCA1 or BRCA2 mutations detected in case series unselected for family history: A combined analysis of 22 studies. American Journal of Human Genetics 2003; 72(5):1117–1130.
  1. Alsters SI, Goldstone AP, Buxton JL, Zekavati A, Sosinsky A, Yiorkas AM, et al. Truncating Homozygous Mutation of Carboxypeptidase E (CPE) in a Morbidly Obese Female with Type 2 Diabetes Mellitus, Intellectual Disability and Hypogonadotrophic Hypogonadism. PloS one. 2015;10(6):e0131417.
  1. Kolata G. Treatment for leukemia, glimpses of the future. The New York Times, 8th July (2012).
  2. Hagemann IS, Devarakonda S, Lockwood CM, Spencer DH, Guebert K, Bredemeyer AJ, et al. Clinical next-generation sequencing in patients with non-small cell lung cancer. Cancer. 2015;121(4):631-9.