New hope for treating cancer? Patterns seen in 12 types of tumors
Examining the molecular profiles of tumors from 12 different types of cancers, scientists working with the National Institutes of Health-backed Cancer Genome Atlas said Thursday they had found striking similarities between tumors originating in different organs.
Their discoveries, made possible by improvements in sequencing technologies and computing methods, could herald a day when cancers are treated based on their genetic profiles, rather than on their tissue of origin, said UC Santa Cruz biomolecular engineer Josh Stuart, a participant in the project and coauthor of a commentary discussing its findings released Thursday by the journal Nature Genetics.
Eventually, such a shift in thinking could lead researchers to new treatments for hard-to-treat cancers, Stuart said, in an interview with the Los Angeles Times.
If scientists can find molecular similarities, say, between a rare form of breast cancer and a form of ovarian cancer, they might be able to use a drug known to target the ovarian tumor to treat the unusual subtype of breast cancer.
“Hopefully fewer patients will be left out on their own,” Stuart said.
The Cancer Genome Atlas or TCGA, which has been underway since 2006, seeks to catalog the DNA and other molecular features of thousands of different tumors from a variety of cancer types. (The Los Angeles Times reported on findings from two earlier Cancer Genome Atlas studies in May.) By identifying how genes are scrambled up in tumors and what effects those changes have in cells, the thinking goes, researchers might be able to understand better how different cancers progress, and find the best treatments for particular tumor types and subtypes.
The Pan-Cancer initiative that Stuart is involved with carries the analysis further, comparing cancers of different types to see what patterns emerge. The team looked at TCGA data -- gene mutations, changes in the numbers of copies of genes, and measures of how the genes were behaving -- from tumors sampled from thousands of patients who had 12 different cancers (including tumor types in the brain, head and neck, kidney, lung, breast, ovary, cervix, colon and rectum and one type of leukemia.)
The cross-cancer comparison was a project many researchers had wanted to pursue, Stuart said. Some had already noticed similarities as they studied various tumors as part of TCGA. “We’d say, hey, I recognize that copy number profile in that breast cancer. Didn’t we see it in ovarian cancer last month?” he said.
Comparing different types of tumors is useful because it lets scientists learn more about how cancers behave than looking at one type on its own can. Cancers are a jumble of cells. Looking at just one type of tumor might let a researcher identify the jumble within that certain cancer, but doesn’t necessarily point to the mechanism that triggered the cancer in the first place, Stuart said.
But looking at several cancers at once and finding commonalities can help tease out the cell of origin, he added.
Over the coming months, the collaboration will publish dozens of papers detailing what researchers found in the cancers. Two such papers were published Thursday, also in Nature Genetics. One noted similarities in gene copy-number changes across cancers. The other classified tumors and tumor subtypes according to their molecular profiles, identifying two large classes that had not been identified previously (one set of cancers where genetic mutations predominate, and another where copy number changes predominate.) Nature Genetics also published a second commentary about the Pan-Cancer initiative, delving into the computing strategies scientists have devised to crunch vast stores of tumor-related genetic data.
Stuart said that while the notion tumors of different origins might share genetic signatures wasn’t a new one, the TCGA Pan-Cancer effort finally lets scientists dig in and see whether it’s true.
“We just haven’t had the data to step back and look at it all together and connect the dots,” he said. Over coming months, researchers will add tumors and tumor types to the dataset, and will also analyze whole genome data.
But changes in medical approaches to treating cancers won’t happen overnight, Stuart added.
“There’s a lot to put in place,” he said, noting therapies would be tested in cells and lab animals before there were trials in people.
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