Georgetown Lombardi Comprehensive Cancer Center researchers and the Innovation Center for Biomedical Informatics published a study Feb. 3 indicating a relationship between the Ly6 family of genes, which allow cancers cells to grow and divide indefinitely, and more aggressive forms of cancer.
According to the study, the expression of four different genes within the Ly6 family in multiple different cancers is strongly related to more severe prognoses for patients. This discovery could potentially open up avenues for more in-depth cancer research.
“The remarkable findings of increased expression of Ly6 family members and its positive correlation with poor outcome on patient survival in multiple cancer type indicate that Ly6 family members Ly6D, Ly6E, Ly6K and Ly6H will be an important targets in clinical practice as marker of poor prognosis and for developing novel therapeutics in multiple cancer type,” the abstract reads.
Senior Researcher and Assistant Professor of Oncology Geeta Upadhyay sought to determine whether or not there was a trend regarding Ly6 gene expression and cancer growth.
“We wanted to see if the gene-family of a specific system plays a role in cancer formation and progression or if it affects the clinical outcome,” Upadyay said.
According to Upadhyay, this family of genes can affect the clinical outcomes of patients’ years after treatment has been administered and remission has occurred. After analyzing data from several studies, researchers found that the Ly6 gene may be the culprit behind more aggressive cancers.
“The high expression of these genes associated with overall survival outcomes means that the more aggressive cancers which were not responding well were having these genes expressed,” Upadhyay said.
Upadhyay said that when a cancer is more aggressive, it spreads faster, is less responsive to therapeutic interventions and is consequently more lethal.
“So the most aggressive cancer after five years or after three years, these patients may not be alive. So, that what’s aggressive is, failing to respond to therapy,” she said.
The study’s analysis utilized bioinformatics, the use of different mathematical methods to process data obtained from other biological studies, to examine data from 130 other studies.
Innovation Center for Biomedical Informatics researcher and co-author of the paper Yuriy Gusev said that although the sheer volume of data available on gene expression and cancer aggressiveness makes conducting an overarching study difficult, bioinformatics enables scientists to make sense of the results of several experiments within a single given context.
“It is basically a multidisciplinary field where people apply different kinds of computational methods — computers to analyze and interpret data which are generated modern biotechnologies,” Gusev said. “Instead of doing one experiment, it is equivalent to doing 130 different projects at the same time in three months.
Upadhyay added that while the research results point to a correlation between the Ly6 family of genes and cancer prognosis, the exact mechanism of how these genes work is still not known to researchers.
“As of now, we can say that this paper gives important information about the gene expression and survival outcome of cancer stem cell genes but we don’t know the real mechanism,” Upadhyay said.
According to Gusev, the study was the summer project of graduate student Linlin Luo (GRD ’15). Under Gusev’s and Upadhyay’s mentorship, Luo was able to process data over the summer and successfully have her results published in a magazine.
“Together we supervised this bright young student and she was able to, in three months, generate so much data that we sent out a paper and it was very quickly accepted and made the news!” Gusev said.
Luo has already graduated and is not currently doing research at the Georgetown University Medical Center. She did not respond to requests for comment.
Upadhyay expressed hope that, in the future, drugs can be developed specially to target cancers in which Ly6 genes have been expressed, while excluding normal cells from the effects of treatment.
“The idea is that it will be that these molecules will be expressed on the cell surface so they are exposed to an incoming drug which can specifically bind to these proteins and leave the normal cells alone,” Upadhyay said.
Gusev predicted that new discoveries could potentially be made from existing data using bioinformatics.
“We are basically talking about a treasure trove – a gold mine of really well-developed information that just needs to be analyzed to find new relationships, basically new biological knowledge,” Gusev said.