DORGE: A New Prediction Algorithm Can Identify Previously Undetected Cancer Driver Genes
With the advent of technology, experts learn new things that can be considered breakthroughs in the medical field. University of California, Irvine (UCI) researchers conduct a study that can deepen the understanding of tumorigenesis's epigenesis and reveals a previous undetected reserve of cancer driver genes.
Epigenetic changes are important for tumor initiation and progression
ALSO READ: Johnson & Johnson Collaboration for Lung Cancer Diagnosis to Proceed With Pilot Stage
According to the Center for Genomic Regulation, cancer driver genes give cells a growth advantage when they are mutated, aiding tumors multiply. They added that identifying these genes are vital steps in personalizing cancer treatment. However, the complexity and diversity of cancer cells make it difficult to find.
In the release by the University of California, Irvine, using the discovery of Oncogenes and tumor suppressor genes using Genetic and Epigenetic features (DORGE), the researchers were able to identify novel tumor suppressoR genes (TSGs) and Oncogenes (OGs), predominantly the ones with rare mutations, through the integration of the most comprehensive collection of genetic and epigenetic data.
According to UCI School of Medicine Department of Biological Chemistry professor of bioinformatics, and senior author of the study, Wei Li, Ph.D., existing bioinformatics algorithms do not satisfactorily leverage epigenetic feature in predicting cancer driver genes, even though epigenetic modifications are known to be connected with cancer driver genes. He added that their computational algorithm integrates public data on epigenetic and genetic alterations in improving the prediction of cancer driver genes.
READ ALSO: Research Finds HDA6 That Can Control Growth of Tumor and Stop It From Metastasizing
The release further said that cancer results from an accumulation of key genetic alterations that interrupt the equilibrium between cell division and apoptosis. They further that genes with driver mutations that affect cancer development are acknowledged as cancer driver genes, which can be classified as tumor suppressor genes and oncogenes basing on their roles in cancer growth.
Methods and results
According to the release, the research shows how cancer driver genes are predicted by the DORGE, including known cancer driver genes and novel cancer driver genes, which is not mentioned in current literature. They added that DORGE's novel dual-functional genes were able to predict as both TSGs and OGs are highly supplemented at hubs in protein-protein interaction (PPI) and compound-gene connections.
Dr. Li explained that the DORGE algorithm successfully leveraged public data in discovering the epigenetic and genetic changes that have a significant role in cancer driver gene dysregulation. He added that the findings could help improve cancer prevention and diagnosis and treatment efforts in the future.
DORGE
According to the researcher's data discovery of cancer driver genes, including tumor suppressor genes (TSGs) and oncogenes (OGs), is important for cancer prevention, treatment, and of course, diagnosis. Epigenetic changes are important for tumor initiation and progression. However, the researchers added that most known driver genes re-identified through genetic changes alone. The researchers highlighted that the newly developed algorithm, DORGE (Discovery of Oncogenes and tumor suppressoR genes using Genetic and Epigenetic features), can identify TSGs and OGs by assimilating complete genetic and epigenetic data. The researchers emphasized that their study has deepened the understanding of epigenetic mechanisms in tumorigenesis and revealed previously undetected cancer driver genes.
Check out more news and information on Cancer on MD News Daily.
© MD News Daily.