Personalized Medicine: Next Generation Sequencing in the Clinic


Now that we’ve established the basics behind next generation sequencing (NGS), we can more fully delve into its implications.  If you missed the last post, check it out here.  In the current post we’ll uncover if and how NGS can be used in the clinic.

The need to sequence DNA faster and cheaper stems partly from our desire to impact patient diseases.  The future of cancer therapy lies in our ability to target pathways (and the proteins involved) that are altered in cancer cells.  But as we’ve shown, each cancer is unique and the genes involved in that process can vary between patients and even within that same patient.  In a recent publication, using next generation sequencing techniques, the authors analyzed a series of patients with pancreatic cancer and assessed whether looking at them as a group versus looking at their mutations as individuals was more advantageous when deciding treatment options.  They compared pathways altered in individuals to those that were significantly altered across the group and found little overlap suggesting that grouping patients may not provide the most valuable information when deciding treatment options1. Therefore, personalized medicine, or individual gene expression profiling is critical to the acquisition of clinically significant information.  And the ability to do this lies in next-generation sequencing.

Considerations for sequencing cancer genomes: 

This answer, however, may not be as easy as simply sequencing every patient that comes into the clinic.  There are several factors to consider2: 

  1.  DNA quality: poor quality samples and limited DNA impede our ability to obtain accurate genetic information.   Ensuring we have tumor sample without contamination from normal tissue is critical.    Additionally, using fresh instead of preserved tissue improves accuracy.  Accuracy can also be improved with deeper read-depths (number of times a sequence is read).  This of course, takes additional time and additional resources
  2.  Paired normal:tumor comparisions.  Instead of comparing to the common human genome, a personalized “normal” control would be ideal.  This will control for any germline mutations or single nucleotide polymorphisms that an individual carries.  Again, the additional patient samples require additional time and resources.
  3.  Intratumor heterogeneity: As we previously discussed, intratumor heterogeneity poses a real problem when taking single biopsies.  How many samples do we need to take to get an accurate picture of the tumor?  The answer is not clear, and as before, additional biopsies require additional resources.
  4.  Mapping cancer genomes: cancer genomes are highly rearranged with multiple large-scale mutations such as translocations, inversions, fusions and copy number changes.  These types of changes make mapping sequences to normal sequences quite difficult, although not impossible.
  5.  Data acquisition: NGS generates large data files requiring storage space as well as the personnel to understand and interpret the data.   The current clinical laboratories are not equipped for this kind of data acquisition and interpretation.  An additional area of concern is the security of this information, particularly if it is stored in the internet cloud.
  6.  Ethical implications:  Most of sequencing in the clinic involves targeted analysis.  This involves looking within a specific chromosomal region for specific mutations we know are critical for tumor progression.  However, even within this small-scale analysis, the potential exists for discovering additional mutations unrelated to the disease in question.  What are the guidelines for informing the patient? Do you, as a patient, even want to know? 


Where do we go from here?

The expectation is that next generation sequencing technology can change the face of medicine.  Although, still in its infancy, the speed and accuracy with which the current technology allows us to analyze genomes means faster and more precise results for patients.  For cancer patients, NGS has the potential to personalize treatment, tailoring medications for tumor-specific alterations.  With the increasing realization that each patient, each tumor is unique, the ability to decipher the genetic makeup of patient tumors has the potential to improve patient outcomes.  However, apart from the financial constraints places on most clinical facilities, evaluating the success of personalized medicine is worth considering.  For example, if a patient has a mutation and we treat that patient with a specific therapeutic that targets that mutation instead of the canonical, untargeted treatment, how do we know that the targeted therapy improved the outcome in that patient? The National Cancer Institute based in the United States initiated a trial over a year ago with the aim to assess the impact of sequencing tumors and tailoring treatments on patient outcome3.  With an expected completion of 2017, we are still several years away from fully appreciating the value of personalized medicine. 

Lastly, we must not underappreciate the role of basic science research in personalized medicine.  Using next generation sequencing to identify mutations means very little if we do not understand what that a mutation in gene A, for example, means for tumor development.  Furthermore, without the appropriate therapy to target that mutation, the observation that gene A is altered serves no benefit to the patient.  Therefore, cancer scientists play a pivotal role: to understand cancer biology, the role of genetic alterations and how to target these defects in tumor settings.  In fact, we cannot have effective personalized medicine without cancer scientists. 

We are at the edge of a new era in cancer medicine thanks in part to the development of next generation sequencing technologies.  It will be interesting to see where this takes us in 5 or 10 years.  Stay tuned!

References:
       1.     Lili LN, Matyuninia LV, Walker LD et al. Evidence for the importance of personalized molecular profiling in pancreatic cancer.  Pancreas Journal. 2014. 43(2):198-211.
       2.     Ulahanna D. Kovac MB, Mulholland PJ, Cazier JB, Tomlinson I.  Technical and implementation issues in using next-generation sequencing of cancers in clinical practice.  BJC. 2013. 109: 827-835.
       3.     www.nih.gov.new/health/jan2014/nci-30.htm NCI launches trial to assess the utility of genetic sequencing to improve patient outcomes. 

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