Study Finds New Candidate Susceptibility Genes for High-Grade Serous Ovarian Cancer
A team of researchers have identified 34 genes that are associated with an increased risk for developing the earliest stages of ovarian cancer. The findings, published by Gusev et al in Nature Genetics, may help identify women who are at highest risk of developing ovarian cancer and pave the way for identifying new therapies that can target these specific genes.
“If you detect ovarian cancer really early, then the survival rate is very high, nearly 90%,” said study coauthor Bogdan Pasaniuc, PhD, Associate Professor of Pathology and Laboratory Medicine at the David Geffen School of Medicine at the University of California Los Angeles (UCLA) and a member of the UCLA Jonsson Comprehensive Cancer Center. “But that doesn't happen often. Most cases are found at a later stage and survival drops dramatically. That's why we want to understand the genetics behind it—so we can do a better job at predicting who is at a higher risk of developing this cancer.”
The study revealed that when we look at the relationship between women's risk of ovarian cancer, as defined by their genetic blueprint, “there is an interplay between their genetics and specific genes that drives the very earliest stages of cancer development," said study coauthor Simon Gayther, PhD, Director of the Center for Bioinformatics and Functional Genomics and Codirector of the Applied Genomics, Computation, and Translational Core at Cedars-Sinai.
Study Methods
The current study builds on previous research of large-scale genetic data gathered over more than a decade by the Ovarian Cancer Association Consortium. Those researchers compared the genetic profiles of about 25,000 women with ovarian cancer and 45,000 women without the disease. The investigators found more than 30 regions in the genome that are associated with ovarian cancer.
“One novelty of this work is that we looked at genetic variants that operate through alternative splicing rather than just the total abundance of a gene, which led us to genes we would not have otherwise identified, including one validated experimentally. Beyond a better understanding, if these risk mechanisms really operate through splicing, that also opens up new drug-target opportunities,” said study coauthor Alexander Gusev, PhD, Assistant Professor of Medical Oncology at Dana-Farber Cancer Institute.
To pinpoint the genes, the researchers analyzed patient data to try to find genetic variants in the DNA blueprint that explain the patient disease status.
“This study also shows how critical it is to study the specific cells from which ovarian cancers arise,” said study coauthor Kate Lawrenson, PhD, Assistant Professor of Obstetrics and Gynecology at Cedars-Sinai. “Collecting normal ovaries and fallopian tubes enabled us to map the molecular fingerprints of these specific cell types in a large cohort of women. This has enabled us to identify the features that relate to cancer risk in the correct tissue type.”
The great challenge the researchers faced was dealing with the number of genes that are in one region of the genome, Dr. Pasaniuc said. To help identify the genes in these particular regions, the team compared the large-scale genetic data from the Ovarian Cancer Association Consortium with a different data type that describes the expression of genes in ovarian and other tissues. By putting these two pieces of information together, the researchers were able to distinguish which genes in the genomes are actually the risk genes.
Genes Identified
Through this computational technique, the team identified 34 genes that are associated with an increased risk for developing ovarian cancer.
They identified 25 transcriptome-wide association study significant genes, 7 at the junction level only, including LRRC46 at 19q21.32, CHMP4C at 8q21, and a PRC1 junction at 15q26. In vitro assays for CHMP4C showed that the associated variant induces allele-specific exon inclusion (P = .0024). Functional screens in ovarian cancer cell lines found evidence of essentiality for three of the new genes identified: HAUS6, KANSL1, and PRC1, with the latter comparable to MYC.
“With the identification of these genes, we now have a narrow list of genes that can help us better predict ovarian cancer risks in women who may have never known that they were at a higher risk for developing the disease,” Dr. Pasaniuc said. “While we're not there yet, we're hoping this study will lead to better outcomes because we will be able to monitor women earlier, when the cancer is easier to treat.”
Disclosure: The study was funded by the National Institutes of Health and the Ovarian Cancer Research Fund Alliance. For full disclosures of the study authors, visit nature.com.
The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.
