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New Gene-Testing Tools May Personalize Ovarian Cancer Care
Researchers say using next-generation sequencing technology as a diagnostic tool may increase precision treatment plans for people with ovarian cancer.
The Challenge
Improvements in genetic testing have allowed for significant advances in the development and use of targeted therapies to treat people with certain types of cancers, including some types of ovarian cancer.
Targeted therapy is a type of cancer treatment that ideally uses drugs or other substances to attack a specific aspect of cancer cells (such as defective proteins due to gene mutations) and kill them while doing little damage to normal cells. This focused action means targeted therapy kills cancer cells more specifically than chemotherapy and radiation do, both of which kill rapidly dividing cells like cancer cells—and normal cells too.
While there are some FDA-approved targeted therapies for ovarian cancer, there remains an urgent need for novel therapies to improve clinical outcomes.
Most ovarian cancers originate from epithelial cells (those that line glands and ducts) called carcinomas, and most epithelial ovarian carcinomas are high-grade serous tumors. These high-grade tumors tend to have the fewest established risk factors and the worst prognosis. They grow and spread faster than lower-grade tumors and cause nearly 90% of ovarian cancer deaths.
High-grade serous ovarian carcinomas have a highly variable genetic makeup. People with the same subtype of ovarian cancer can have different genetic variations, and there can even be genetic variations within the same person. This lack of a consistent target increases the challenge of developing new treatments.
Without targeted therapies, the only available treatments for the most common type of ovarian cancer are the traditional ones—chemotherapy before or after surgery. A large percentage of people with high-grade epithelial ovarian cancers respond well to chemotherapy before surgery; however, the cancer often recurs within a couple of years.
To improve outcomes after treatment and decrease deaths from ovarian cancer, it’s essential to find new treatment plans for people with these genetically varied subtypes. Developing such treatments will require a thorough and nuanced understanding of the genetic differences in ovarian cancer.
The Research
American Cancer Society (ACS) grantee Anil Sood, MD, focuses his research on developing new biologically targeted therapies for ovarian cancer at the University of Texas MD Anderson Cancer Center in Houston.
Sood is a recipient of the ACS Research Professor Award, the most prestigious grant we give to recognize pioneering, influential work, and mentoring that is continuing to change the direction of cancer research.
He’s also co-leader of MD Anderson’s Ovarian Cancer Moon Shot research. These Moon Shot investigators focus on increasing genetic testing rates for women diagnosed with ovarian cancer and developing innovative methods for more personalized surgical care.
Sood recently published a study in Cancer that analyzed how helpful the technique of tumor-based next-generation sequencing (tbNGS) is for people with ovarian cancer. tbNGS enables simultaneous analysis of thousands of genes from tumors at a feasible cost and turnaround time.
Featured Term:
Next-generation Sequencing (NGS)
Technology that allows for simultaneous sequencing of DNA and RNA in multiple people at the same time. Compared to traditional sequencing, which determines the genetic sequence one section at a time, next-generation sequencing is much faster, less expensive, and delivers a much larger magnitude of information. Making sense of these huge datasets requires bioinformatics and computational biology.
NGS has revolutionized the field of personalized medicine (precision medicine).
tbNGS (tumor-based next-generation sequencing) is the use of NGS to evaluate the genetic sequence of tumors from multiple people at the same time.
More and more patients with ovarian cancer are getting tbNGS to identify genetic mutations in their tumors even though the benefits of finding those errors have not been well established. My team aimed to learn if this tool could be more broadly helpful for assessing treatment options for patients with ovarian tumors, particularly high-grade epithelial ovarian carcinomas.”
This was a retrospective study, meaning Sood's team collected and analyzed stored data without being able to alter the course of a person’s cancer treatment. The research team examined the results of tbNGS from 409 people diagnosed with high-grade epithelial ovarian carcinoma enrolled in the MD Anderson Ovarian Cancer Moot Shot program between 2013 and 2021. They collected data on multiple types of genetic mutations.
They found that almost 96% of the tumors had a least one genetic mutation, and almost 75% of those tumors had a mutation that was considered “useful for clinical decision-making.” Their findings show what could have been offered to these patients if oncologists knew how to adjust treatment based on cancer’s genetic details—and what might be offered for future patients.
A “useful mutation” qualifies the person with ovarian cancer to receive an existing targeted therapy or enroll in a clinical trial. Specifically, they found that:
- 1 in 4 patients in the study was a potential candidate for an available targeted therapy.
- 3 of 4 patients were potential candidates for a clinical trial of a targeted therapy or biomarker
“Our findings support the clinical relevance of tbNGS in the management of the most common type of ovarian cancer. With it, we discovered many more possible treatment plans for high-grade epithelial ovarian cancers than the standard chemotherapy and surgery that we’ve thought were our only choices," says Sood.
The authors say that they advocate for guideline committees to consider adding the use of tbNGS as an additional diagnostic tool in women with primary or recurrent ovarian cancer.
Why It Matters
The number of sequencing tests Sood’s team had access to provides a detailed description of ovarian cancer genomics at the population level. Sood’s findings show that tbNGS is helpful in identifying genetic mutations in most patients with high-grade epithelial ovarian cancers.
Having information about a patient’s specific genetic mutations and a tumor’s molecular makeup may help oncologists recommend personalized treatments or clinical trials to patients. Such information also helps researchers learn which genetic variations to study as potential new drug targets.
The authors say the information they’ve gathered and that other scientists will gather in the future can help with two key next steps:
- Guide the development of clinical decision-support tools so that oncologists know how to effectively apply the big data from tbNGS into a patient’s treatment plan to improve their outcomes.
- Identify new targets to study for potential new targeted therapies for patients with high-grade epithelial ovarian cancers.
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