This is one of the most discussed topics especially in Clinical Genomics! Affordability, accuracy, feasibility and of course time consumption - based on these factor mostly, which sequencing technology is more suitable for clinics? Whole Exome Sequencing or Whole Genome Sequencing? (WGS or WES, WGS vs WES) So here's my 2 cents on this discussion! When it comes to DNA sequencing there has always been a raging debate over the choice of Whole Genome Sequencing (WGS) or Whole Exome Sequencing (WXS) for routine use. Whole genome sequencing (WGS), as the name suggests is the process of obtaining the entire genome. In most cases however, this is far from practical and only 95-97% of the genome is covered because it is technically difficult to sequence certain regions of the genome (high GC content, large repeat regions, centromeres, telomeres, etc.) with existing technology. “It’s very fair to say the human genome was never fully sequenced,” - Craig Venter “The human genome ha
What is Clinical Genomics? What's the difference between precision medicine and personalised medicine?
Genomics is the study of an organism's entire genome (all the DNA for the discussion lets say)!
– the correlation between diseases and human genome
– the interaction of medication and human genome
– developing disease diagnostic methods from human genome
- Finally - coming up with ways to treat that disease based on all this knowledge built with the help of genomics.
When we think about genomics in treating a disease like cancer, we consider two aspects. First is the patient’s own genome, which is in every cell in their body. In their genome, they may have mutations that make them more susceptible to a particular type of cancer than someone who doesn’t have that particular type of mutation. For example, we know that individuals with specific inherited mutations in BRCA1 and BRCA2 genes are at a greater risk for breast and ovarian cancers.
The second side of genomics is the specific genetics of the tumor. Doctors look at the genetic profile of a tumor to determine if it has one or more mutations that would affect its behavior, including mutations that make it more likely to respond to a specific treatment. The appearance of a specific mutation does not mean the cancer will definitely respond to that targeted therapy, but it does mean it is more likely to. This is precision medicine - targeting a particular condition based on the data we have about it.
In addition to a patient’s biology and the biology of their tumor, doctors also consider the patient’s personal value system to ensure the treatment strategy fits their goals and preferences. This is called personalized care.
Personalized treatment plans take into account all of these moving parts – the patient’s genomic profile, the tumor’s genomic profile and patient values – and merge that information with the known data from clinical trials to determine what combination of therapy and supportive care is likely to provide the best outcome for the patient.
Personalized treatment plans have always been a part of oncology. The difference between 10 years ago and now is the amount of information we have available, which enables us to make more refined decisions with the patient’s individual needs in mind. Historically, patients were treated based on the original tumor site, the cancer stage and the patient’s overall health and preferences.
Today, we know there is variation based on genetics in tumors arising from a single organ and that certain targeted drugs are helpful to patients with particular sub-types of cancer. For instance, a patient with HER2 overexpressed breast cancer may benefit from treatments that would not benefit a person with a breast cancer that does not overexpress HER2.
Personalized medicine allows us to get away from the “one size fits all” cancer treatment strategy, refining the diagnosis within a disease type and individualizing treatment plans.
Personalized medicine will continue to expand with further innovation and discoveries in genomics. For example, there are ongoing clinical trials to determine whether a genetic mutation that is responsive to a treatment in one disease type is also responsive in another. As we understand more about the biology of these diseases, patient subsets are going to shrink and our treatment plans are going to become increasingly precise.
Thanks,
Venkatesh Chellappa
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