Print“We found that one in 10 cancers analyzed in this study would be classified differently using this new approach,” says Chuck Perou. “That means that 10 percent of the patients might be better off getting a different therapy—that’s huge.”
Cancers are traditionally classified depending on the organ of the body where the tumor originates. But a just published study by researchers in the Cancer Genome Atlas Research Network, detailing the largest and most diverse tumor genetic analysis ever conducted, reveals a new approach to classifying cancers that could upend that tradition, revamping traditional ideas of how cancers are diagnosed and treated. It could also have a profound impact on the future landscape of drug development, say the researchers.
“We found that one in 10 cancers analyzed in this study would be classified differently using this new approach,” says Chuck Perou, professor of genetics and pathology at the University of North Carolina Lineberger Comprehensive Cancer Center and senior author of the paper, which was published in the journal Cell. “That means that 10 percent of the patients might be better off getting a different therapy—that’s huge.”
In their study, researchers from multiple institutions analyzed more than 3,500 tumors across 12 different tissue types to see how they compared to one another. Each tumor type was characterized using six different methods of molecular analysis that included DNA and RNA sequencing and protein expression analysis. The analysis showed that cancers are more likely to be genetically similar based on the type of cell in which the cancer originated, compared to the type of tissue in which it originated.
“In some cases, the cells in the tissue from which the tumor originates are the same,” says Katherine Hoadley, UNC research assistant professor in genetics and lead author. “But in other cases, the tissue in which the cancer originates is made up of multiple types of cells that can each give rise to tumors. Understanding the cell in which the cancer originates appears to be very important in determining the subtype of a tumor and, in turn, how that tumor behaves and how it should be treated.”
The new approach may also shift how cancer drugs are developed, Perou and Hoadley say, focusing more on the development of drugs targeting larger groups of cancers with genomic similarities, as opposed to a single tumor type as they are currently developed.
Breast cancer is a striking example of the genetic differences within a single tissue type. The breast, a highly complex organ with multiple types of cells, gives rise to multiple types of breast cancer: luminal A, luminal B, HER2-enriched and basal-like, which was previously known. In this analysis, the basal-like breast cancers looked more like ovarian cancer and cancers of a squamous-cell type origin, a type of cell that composes the lower-layer of a tissue, rather than other cancers that arise in the breast.
“This latest research further solidifies that basal-like breast cancer is an entirely unique disease and is completely distinct from other types of breast cancer,” Perou says. In addition, researchers found that bladder cancers were also quite diverse and might represent at least three different disease types that also showed differences in patient survival.
“We can now say what the telltale signatures of the subtypes are, so you can classify a patient’s tumor just based on the gene expression data, or just based on mutation data, if that's what you have,” says Joshua Stuart, senior author and professor of biomolecular engineering at UC Santa Cruz. “Having a molecular map like this could help get a patient into the right clinical trial.”
Although follow-up studies are needed to validate the findings, this new analysis lays the groundwork for classifying tumors into molecularly defined subtypes. The new classification scheme could be used to enroll patients in clinical trials and could lead to different treatment options based on molecular subtypes.
According to Stuart, the percentage of tumors that are reclassified based on molecular signatures is likely to grow as more samples and tumor types are included in the analysis. Coauthor Christopher Benz, an oncologist at the Buck Institute for Research on Aging and UC San Francisco, noted that the 10 percent reclassification rate in the current study is likely an underestimate due to the unequal representation of different tumors. “If our study had included as many bladder cancers as breast cancers, for example, we would have reclassified 30 percent,” Benz says.
The researchers reported that each molecular subtype may reflect tumors arising from distinct cell types. For example, the data showed a marked difference between cancers of epithelial and non-epithelial origins. “We think the subtypes reflect primarily the cell of origin. Another factor is the nature of the genomic lesion, and third is the microenvironment of the cell and how surrounding cells influence it,” Stuart says. “We are disentangling the signals from these different factors so we can gauge each one for its prognostic power.”
August 10, 2014
http://www.burrillreport.com/article-new_system_for_classifying_cancer_could_change_the_way_drugs_are_developed.html
