Scientists in four continents worked for over a decade on a massive project that has resulted in the most detailed picture of cancer ever produced. Researchers now have a huge database of DNA and can draw from thousands of tumors.
According to a recent article in the BBC News, it took twenty-two scientific journal papers to present details of the project.
Their efforts brought results. Scientists are now able to view genetic changes that contribute to cancer. They are in a position to locate the knowledge gaps that have existed for years.
The project, the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, will further their understanding of the ‘driver mutations’ underpinning the development of cancer.
It was determined that on average, patients’ cancers contain four or five mutations that drive their growth. These driver mutations present a target for future treatments.
Initially, driver mutations were found in about two-thirds of patients. Now, working on a larger scale, the researchers found driver mutations in ninety-one percent of samples.
Many scientists agree that ninety-nine percent of the mystery of cancer’s origin has been missing until now.
The studies, which approach an almost complete view of cancer, have been published in the journal NATURE.
The Complexities of Cancer
After years of cancer research, doctors were still unable to determine why two cancers may look similar under the microscope but would have a completely opposite response to the same treatment.
One geneticist commented that he felt the most striking finding of the project was how different one person’s cancer genome is from another person’s cancer genome.
An over-simplification for the complexity of cancer is that there are thousands of mutation combinations that can cause cancer. Cancer is a corruption of our healthy cells. It is a mutation to our DNA that changes our cells which eventually divide uncontrollably.
Therefore it was a massive undertaking for scientists to analyze the whole genetic code of over 2600 whole cancer genomes together with their matching normal tissues. The project involved thirty-eight types of cancers.
The researchers were comparing diverse types of tumors. Therefore uniform computational formulas were used to compare the tumors and their matching normal genomes. They were then put through stringent quality control tests.
The effort also involved coordinated data processing and validation of the computational pipeline that is used in detecting mutations.
Implications Now and For the Future
As a result of the PCAWG project, timelines of genetic mutations were developed across a broad array of cancer types.
Researchers developed a method to ‘carbon date’ mutations. They were able to show that over one-fifth of mutations were present many years before the cancer was diagnosed.
The ultimate goal is to use technology drawn from the project to find treatments designed specifically for each patient’s unique tumor.
Just as important is detecting cancer much earlier. Special consideration will be given to developing new diagnostic tests that recognize signs of cancer at very early stages.
The challenge still exists in being able to identify which mutation will become cancer and which one will not.
There is still much more work to do and it is expensive to sequence a cancer genome. The good news is that the cost of sequencing is falling.
The PCAWG project opens new avenues to the development of drugs that prevent and treat resistance to treatment once it occurs.
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