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Researchers Identify Genes Linked to Increased Ovarian Cancer Risk

Nalley, Catlin

doi: 10.1097/01.COT.0000569316.81071.c9
Opinion
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ovarian cancer; genomics

ovarian cancer; genomics

A team of researchers have identified 34 genes that are associated with an increased risk for developing the earliest stages of ovarian cancer (Nat Genet 2019;51:815-823). These findings have the potential to not only help identify women who are at highest risk of developing ovarian cancer, but also lay the foundation for the development of therapies targeting these specific genes.

“Ovarian cancer cases are commonly diagnosed at a late clinical stage when prognosis is poor. Furthermore, family history (inherited genetic variation) plays an important role in risk of developing ovarian cancer, with a woman with a first-degree relative with ovarian cancer being at a nearly three-fold increased risk of developing disease as compared to women with no family history,” noted Bogdan Pasaniuc, PhD, Associate Professor of Pathology and Laboratory Medicine at the David Geffen School of Medicine at UCLA.

“This motivates research in first mapping regions in the genome that contribute to risk of ovarian cancer; and second, to understand mechanistically what genes at these regions are causing increased risk.”

With this in mind, Pasaniuc co-led the study along with Simon Gayther, PhD, Director of the Center for Bioinformatics and Functional Genomics at Cedars-Sinai; Alexander Gusev, PhD, Assistant Professor of Medical Oncology at Dana-Farber; and Kate Lawrenson, PhD, Assistant Professor of Obstetrics and Gynecology at Cedars-Sinai.

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Study Details

This study builds upon large-scale genetic data gathered by the Ovarian Cancer Association Consortium over the course of more than a decade. Genetic profiles of approximately 25,000 women with ovarian cancer and 45,000 women without the disease were compared. Findings showed more than 30 regions in the genome associated with the disease.

In the current study, the researchers “sought to identify susceptibility genes for high-grade serous ovarian cancer (HGSOC) by performing a transcriptome-wide association study of gene expression and splice junction usage in HGSOC-relevant tissue types (N=2,169) and the largest genome-wide association study available for HGSOC (N=13,037 cases and 40,941 controls).”

“We identified 25 transcriptome-wide association study significant genes, seven at the junction level only, including LRRC46 at 19q21.32, (P=1 × 10−9), CHMP4C at 8q21 (P=2 × 10−11), and a PRC1 junction at 15q26 (p=7 × 10−9),” the researchers reported. “In vitro assays for CHMP4C showed that the associated variant induces allele-specific exon inclusion (P=0.0024).

“Functional screens in HGSOC cell lines found evidence of essentiality for three of the new genes we identified: HAUS6, KANSL1, and PRC1, with the latter comparable to MYC. Our study implicates at least one target gene for six out of 13 distinct genome-wide association study regions, identifying 23 new candidate susceptibility genes for HGSOC.”

“One novelty of this work is that we looked at risk 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,” explained Gusev, in a statement. “Beyond a better understanding, if these risk mechanisms really operate through splicing, that also opens up new drug-target opportunities.”

“Now that we've identified all these regions in the genome that increase the risk for ovarian cancer, we're at the stage where we are mapping the genes of these risk regions,” Pasaniuc noted. “Ultimately, that will lead to better prediction, and that will lead to better stratification of women of different risk categories.”

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Implications, Next Steps

This research has the potential to help improve the early diagnosis of ovarian cancer as well as lead to new targeted therapies.

“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,” 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.”

Looking to the future, Pasaniuc noted, “Next steps include better and more functional screens for these genes, generating a larger panel of expression/genetics to identify new risk regions for ovarian cancer as a large component of the genetic risk remains unaccounted for.

“A promising direction is to integrate other molecular mechanisms (e.g., protein regulation) to understand the genetic risk at the remaining risk regions,” he added.

Catlin Nalley is associate editor.

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