Sequencing an entire genome currently costs in the neighborhood of
$5,000 to $10,000, not including the interpretation of the information.
It is usually not reimbursed by insurance, which is more likely to cover
tests for genetic mutations that are known to be responsive to drugs.
The treatments themselves, which are sometimes covered, typically cost
several times that.
Even optimists warn that medicine is a long way from deriving useful
information from routine sequencing, raising questions about the social
worth of all this investment at a time of intense fiscal pressure on the
health care system.
“What’s the real health benefit?” said Dr. Robert C. Green, a Harvard
professor and a medical geneticist at Brigham and Women’s Hospital in
Boston. “If you’re a little bit cynical, you say, well, none, it’s
foolish.”
The real question is "what gene?". Namely are we sequencing the genes of the person which made them what they are, or are we sequencing the genes of the cancer. And even worse, what cancer cells since they have the nasty habit of mutating at a rather rapid rate.
The germ line genes may or may not tell us a great deal, unless we understand what went wrong and when. Very few cancers are germ line related, most are somatic. Stuff happens, and then it happens again and again.
As we have argued in our recent work on cancer cell dynamics there is a highly complex but measurable and modelable process to examine this complex somatic process. Furthermore we have explicitly demonstrated that for prostate cancer and melanoma.
Specifically any such program should:
1. Catalog the germ-line genes. It is always good to know where you are starting from.
2. Monitor the somatic genes of a cancer as it progresses.
3. Understand the "expression" not just the genes since expression is modulated by epigenetic factors such as methylation and miRNAs as examples.
4. Perform the analysis using a fact based model which is spatially and temporally based along with recognizable mutation paths.
5. Validate the models and use them for prognostic purposes.
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