Cancer treatment is one of the major areas where sequencers are expected to have the largest impact in the near future. This is due to the many types of genetic aberrations involved, and the variations between cancers, which can affect treatment and outcome. There is a large network of consortia and cancer genome projects, with varying degrees of coordination taking place. Along with the tumor itself, the circulating DNA in the blood may allow the determination of response to drugs, disease burden, and likelihood of recurrence.
The latest sequencer technologies permit analysis at the level of DNA sequencing, RNA sequencing, microRNA sequencing, methylation, transcription factor, and other regulatory protein binding; all of these are being explored as potentially valuable approaches. New technologies allowing single-cell sequencing may also be particularly useful for cancer-related applications.
Today, there are standard treatments used for tumors with similar pathology, but tumors are not routinely genetically sequenced. There has been a remarkable increase in the use of sequencing in cancer. Tumor sequencing can provide clues to the genetic composition of a tumor that is not available by other technologies.
Further, it is anticipated that sequencing studies will identify new genes that we had not previously known to be involved in cancer. This could give rise to new test panels. In February 2010, Johns Hopkins Kimmel Cancer Center reported that a personalized, blood-based cancer test could be available in five years. The test identifies tumor DNA “rearrangements” that are specific to the individual patient and so could track whether cancer treatment is working or if the disease has recurred.
There are challenges as DNA sequencing expands beyond research. The rapid changes in medicine are likely to bring about many new questions and challenges. Individual disease areas can each have their own intricacies, and the advances have been gradual. Data analysis and data management can be difficult tasks.
For example, the storage of an individual’s sequence data, and how to ethically approach situations where a disease can be predicted but not treated, are examples of the difficult issues. Furthermore, sequence data can be used to uniquely identify an individual.
The information also crosses into areas unrelated to medical treatment, such as ancestry, abilities, and other traits. Combined with the ongoing innovations permitted by the internet, it is hard to predict exactly how these things will progress over the longer term.
Without a doubt, many of the clinical applications will continue moving into mainstream use as they become proven and the economics gets worked out. Due to lower regulatory hurdles, these developments will most likely occur more rapidly in Europe than in the U.S.