A new method to identify genes responsible for "quality control" of DNA can help in the diagnosis and treatment of various cancers.
BRAZIL/USA – The research work, which combined bioinformatics techniques with functional analyses, found 182 S. cerevisiae GIS genes, 50 of which suppress genome instability in at least 3 of the 4 GCR assays. While 98 had never been described before.
“This has the potential to lead to new therapies, as well as tests that can predict how aggressive a particular tumor of a patient,” says Sandro de Souza, a researcher at the Institute of Brain UFRN (Federal University of Rio Grande do Norte) and one of the authors of the study published in the Nature Communications.
The research helps illustrate how what is usually called cancer is actually a complex series of different diseases, where the only thing they have in common is uncontrolled growth of cells that have undergone mutation.
The researchers focused on a phenomenon that is observed frequently in some cancers, such as colorectal and ovarian but not in others, such as leukemia. It is a strong shuffling of the genome of the cell, the gross chromosomal rearrangement.
It happens when some genes responsible for maintaining organization in all DNA fail in this function and induces the appearance of mutations, which in turn increase the chances of emergence of a malignant tumor. But what exactly are these genes such as GIS? Finding such explanation was the main objective of the study.
Under the leadership of Richard Kolodner, a researcher at the Ludwig Institute for Cancer Research in La Jolla, California, the group focused at first in the genome of Saccharomyces cerevisiae.
The hunt for such genes would not be trivial as it is not easy to come up with laboratory schemes able to reveal them in cell cultures. Here then is the innovation that allowed success: work began on a “virtual hunt” in the computer. Part of this work was carried out in the Digital Metropolis Institute also at UFRN.
Using bioinformatics techniques developed over the past few years with increasing computing power to process genomic data, the researchers “fished” in the genome yeast, a number of possible candidates.
So, with these genes in the crosshairs, they left for practice tests with cell cultures in order to confirm its function as suppressors of genomic instability. Sometimes they came to test them two by two. And the effort paid off.
182 GIS genes were discovered, and other 438 are not exactly from the same category, but they act in preservation of system integrity of the genome.
Looking at the GIS genes identified with those contained in the Cancer Genome Atlas data (TCGA), the researchers noted that there is a strong correlation between defect in the gene sequences and the emergence of cancers such as ovarian and colorectal.
In ovarian case, the correlation between problems with the GIS, and the disease incidence is at least 93%. In colorectal, the number drops to 66%, but still is an important indicator.
On a more basic level, the study offers more glimpses on how to operate certain types of cancer, probably induced by mutations that lead to the collapse of the DNA quality control system and the emergence of gross chromosomal rearrangements.
According to the authors, however, it goes beyond that, it would also open doors for the development of new treatments and techniques for diagnosis and prognosis.
“There is the possibility that these genes are targets for potential therapies,” says Sandro de Souza. “If we have to restore the function of these genes, it brings a therapeutic potential.”
The researcher also highlights how they can provide clues to help assess the expected level of tumor aggressiveness.
“When these genes are mutated, their tumors have higher mutation rate. Thus, there is greater likelihood of the emergence of a more aggressive variation.”
It is still early to expect a practical test, however. “We need studies to confirm and define the exact predictive signature,” avers Souza.
The work is an important starting point, but there is still much to be done. “We are now working on an approach using data for about 15 different tumor types and we are also working in pairs of genes that appear to act in a collaborative way,” says the Brazilian researcher.
“We want to understand how these mutations in these pairs may reflect clinical characteristics in patients.”