Posted on by Dr. Francis Collins
Cancer is a disease of the genome. It can be driven by many different types of DNA misspellings and rearrangements, which can cause cells to grow uncontrollably. While the first oncogenes with the potential to cause cancer were discovered more than 35 years ago, it’s been a long slog to catalog the universe of these potential DNA contributors to malignancy, let alone explore how they might inform diagnosis and treatment. So, I’m thrilled that an international team has completed the most comprehensive study to date of the entire genomes—the complete sets of DNA—of 38 different types of cancer.
Among the team’s most important discoveries is that the vast majority of tumors—about 95 percent—contained at least one identifiable spelling change in their genomes that appeared to drive the cancer . That’s significantly higher than the level of “driver mutations” found in past studies that analyzed only a tumor’s exome, the small fraction of the genome that codes for proteins. Because many cancer drugs are designed to target specific proteins affected by driver mutations, the new findings indicate it may be worthwhile, perhaps even life-saving in many cases, to sequence the entire tumor genomes of a great many more people with cancer.
The latest findings, detailed in an impressive collection of 23 papers published in Nature and its affiliated journals, come from the international Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. Also known as the Pan-Cancer Project for short, it builds on earlier efforts to characterize the genomes of many cancer types, including NIH’s The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC).
In these latest studies, a team including more than 1,300 researchers from around the world analyzed the complete genomes of more than 2,600 cancer samples. Those samples included tumors of the brain, skin, esophagus, liver, and more, along with matched healthy cells taken from the same individuals.
In each of the resulting new studies, teams of researchers dug deep into various aspects of the cancer DNA findings to make a series of important inferences and discoveries. Here are a few intriguing highlights:
• The average cancer genome was found to contain not just one driver mutation, but four or five.
• About 13 percent of those driver mutations were found in so-called non-coding DNA, portions of the genome that don’t code for proteins .
• The mutations arose within about 100 different molecular processes, as indicated by their unique patterns or “mutational signatures.” [3,4].
• Some of those signatures are associated with known cancer causes, including aberrant DNA repair and exposure to known carcinogens, such as tobacco smoke or UV light. Interestingly, many others are as-yet unexplained, suggesting there’s more to learn with potentially important implications for cancer prevention and drug development.
• A comprehensive analysis of 47 million genetic changes pieced together the chronology of cancer-causing mutations. This work revealed that many driver mutations occur years, if not decades, prior to a cancer’s diagnosis, a discovery with potentially important implications for early cancer detection .
The findings represent a big step toward cataloging all the major cancer-causing mutations with important implications for the future of precision cancer care. And yet, the fact that the drivers in 5 percent of cancers continue to remain mysterious (though they do have RNA abnormalities) comes as a reminder that there’s still a lot more work to do. The challenging next steps include connecting the cancer genome data to treatments and building meaningful predictors of patient outcomes.
To help in these endeavors, the Pan-Cancer Project has made all of its data and analytic tools available to the research community. As researchers at NIH and around the world continue to detail the diverse genetic drivers of cancer and the molecular processes that contribute to them, there is hope that these findings and others will ultimately vanquish, or at least rein in, this Emperor of All Maladies.
 Pan-Cancer analysis of whole genomes. ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium. Nature. 2020 Feb;578(7793):82-93.
 Analyses of non-coding somatic drivers in 2,658 cancer whole genomes. Rheinbay E et al; PCAWG Consortium. Nature. 2020 Feb;578(7793):102-111.
 The repertoire of mutational signatures in human cancer. Alexandrov LB et al; PCAWG Consortium. Nature. 2020 Feb;578(7793):94-101.
 Patterns of somatic structural variation in human cancer genomes. Li Y et al; PCAWG Consortium. Nature. 2020 Feb;578(7793):112-121.
 The evolutionary history of 2,658 cancers. Gerstung M, Jolly C, Leshchiner I, Dentro SC et al; PCAWG Consortium. Nature. 2020 Feb;578(7793):122-128.
The Genetics of Cancer (National Cancer Institute/NIH)
NIH Support: National Cancer Institute, National Human Genome Research Institute
Posted on by Dr. Francis Collins
Each year, more than 15,000 American children and teenagers will be diagnosed with cancer. While great progress has been made in treating many types of childhood cancer, it remains the leading cause of disease-related death among kids who make it past infancy in the United States . One reason for that sobering reality is our relatively limited knowledge about the precise biological mechanisms responsible for childhood cancers—information vital for designing targeted therapies to fight the disease in all its varied forms.
Now, two complementary studies have brought into clearer focus the genomic landscapes of many types of childhood cancer [2, 3]. The studies, which analyzed DNA data representing tumor and normal tissue from more than 2,600 young people with cancer, uncovered thousands of genomic alterations in about 200 different genes that appear to drive childhood cancers. These so-called “driver genes” included many that were different than those found in similar studies of adult cancers, as well as a considerable number of mutations that appear amenable to targeting with precision therapies already available or under development.