Invitae Unveils New Research for Breast Cancer Patients with Variants of Uncertain Significance

Rhea-AI Summary

Invitae (NVTA) announces new studies to be presented at the American Society of Breast Surgeons Annual Meeting, highlighting the role of machine learning in reducing variants of uncertain significance (VUS) in genetic testing for breast cancer patients. The research shows machine learning models can benefit underrepresented populations, resulting in more definitive genetic testing outcomes.

Positive

• Invitae presents new studies at the ASBrS Annual Meeting showcasing the impact of machine learning in reducing VUS in genetic testing for breast cancer patients.
• Machine learning algorithms help classify uncertain variants more definitively, particularly benefiting underrepresented populations like Black, Asian, and Hispanic individuals.
• Results indicate that VUS in genetic testing do not lead to overuse of mastectomies for breast cancer patients, offering reassurance on clinical management.
• The research emphasizes the importance of accurate genetic testing results in improving patient outcomes and reducing healthcare disparities.

Negative

• None.

– Study findings to be presented at the 2024 American Society of Breast Surgeons Annual Meeting –

SAN FRANCISCO, April 11, 2024 /PRNewswire/ -- Invitae (OTC: NVTA), a leading medical genetics company, today announced new studies to be presented at the American Society of Breast Surgeons Annual Meeting (ASBrS) held in Orlando from April 10-14, 2024. The featured research will highlight how machine learning can reduce variants of uncertain significance (VUS) in patients who have received genetic testing for breast cancer, in addition to results from real world data showing that uncertain results do not lead to an overuse of mastectomies for breast cancer patients.

New findings show machine learning models can help reduce the burden on clinicians and patients in the process of resolving uncertain genetic test results for hereditary breast cancer, particularly for underrepresented populations.

Due to limited evidence, classifying uncertain variants can be challenging. Individuals from certain racial, ethnic and ancestral (REA) populations are often underrepresented in large genomic databases and medical literature, leading to less definitive results, resulting in VUS which are at the center of healthcare disparities. To generate more definitive genetic testing results for these groups, the study sought to develop gene-specific machine learning models and evaluate their usefulness in genetic testing for patients with breast cancer.

After validating gene-specific machine learning algorithms, the impact on variant classification was analyzed in patients with breast cancer who underwent hereditary cancer genetic testing from January 2022 - May 2023. The study found that among breast cancer patients who had at least one variant with machine learning evidence applied, more than 15% resulted in a definitive (non-VUS) variant classification. However, when stratifying the analysis by REA populations, a higher percentage of Black (22%), Asian (28%), and Hispanic (19%) individuals with breast cancer had a definitive classification that was determined by machine learning evidence compared to White (12%) individuals, suggesting that machine learning evidence is particularly useful for patients from historically underrepresented populations with breast cancer who undergo hereditary cancer testing. By reclassifying these VUS into definitive results, laboratories can help clinicians better manage the care of their patients and help reduce gaps in healthcare disparities across racial, ethnic, and socio-economic groups.

"We're excited to demonstrate that machine learning algorithms are able to provide more accurate and equitable results for breast cancer patients with VUS," said Dr. Ed Esplin M.D., Ph.D., FACMG, Clinical Geneticist at Invitae and co-author of the study. "These definitive results can help improve outcomes for these patients and is just one example of the incredible power of coupling AI with Invitae's vast, unparalleled genetic data to further increase and accelerate the patient benefits of genetic testing."

Results offer reassurance that variants of uncertain significance in genetic testing results among breast cancer patients do not lead to overuse of breast surgeries, like mastectomies.

Genetic testing for hereditary disease, which looks at genes that can directly inform surgical, medical and surveillance strategies for breast cancer risk-reduction and treatment, has become the standard of care for assessing hereditary cancer predisposition. Although this testing can lead to high rates of uncertain results, it has been unclear if these results impact clinical management.

Conflicting results have been reported regarding whether patients with VUS are more likely to undergo breast surgeries, compared to those with negative results. This study titled, "Real-World Breast Surgery Utilization among Breast Cancer Patients with Germline Variants of Uncertain Significance," examines breast surgery uptake in a large, recent sample of breast cancer patients undergoing genetic testing.

The study found, through a sample of more than 9,000 breast cancer patients, those with VUS results did not undergo surgical procedures more frequently than patients with negative results. These results offer reassurance that VUS results do not lead to overuse of mastectomies for breast cancer patients.

"Over the years there have been many discussions around preventative mastectomies and whether or not these measures have been overused in practice due to genetic testing results," said Dr. Kevin Hughes, Director of Cancer Genetics in the Medical University of South Carolina Department of Surgery and an author of the study. "When we found that the uptake of breast surgeries, particularly bilateral mastectomies, was comparable between patients with negative and VUS results in this large national cohort of patients with breast cancer, it confirmed our hypothesis that receipt of a VUS does not impact clinical management."

For more information about genetic testing, visit Invitae.

About Invitae
Invitae (OTC: NVTA) is a leading medical genetics company trusted by millions of patients and their providers to deliver timely genetic information using digital technology. We aim to provide accurate and actionable answers to strengthen medical decision-making for individuals and their families. Invitae's genetics experts apply a rigorous approach to data and research, serving as the foundation of their mission to bring comprehensive genetic information into mainstream medicine to improve healthcare for billions of people.

To learn more, visit invitae.com and follow for updates on LinkedIn, X, Instagram, and Facebook @Invitae.

Safe Harbor Statement
This press release contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995, including statements relating to the company's research and study findings and the company's beliefs regarding the impact of such findings.  Forward-looking statements are subject to risks and uncertainties that could cause actual results to differ materially, and reported results should not be considered as an indication of future performance. These risks and uncertainties include, but are not limited to: risks and uncertainties regarding the company's ability to successfully consummate and complete a plan of reorganization under Chapter 11; the company's ability to continue operating in the ordinary course while the Chapter 11 cases are pending; potential adverse effects of the Chapter 11 cases on the company's business, financial condition, liquidity and results of operations; the company's ability to use rapidly changing genetic data to interpret test results accurately and consistently; risks associated with litigation; security breaches, loss of data and other disruptions; laws and regulations applicable to the company's business; and the other risks set forth in the company's filings with the Securities and Exchange Commission, including the risks set forth in the company's Quarterly Report on Form 10-Q for the quarter ended September 30, 2023. These forward-looking statements speak only as of the date hereof, and Invitae Corporation disclaims any obligation to update these forward-looking statements.

Contact:
Renee Kelley
pr@invitae.com 

View original content to download multimedia:https://www.prnewswire.com/news-releases/invitae-unveils-new-research-for-breast-cancer-patients-with-variants-of-uncertain-significance-302114308.html

SOURCE Invitae Corporation

FAQ

How can machine learning reduce variants of uncertain significance (VUS) in genetic testing for breast cancer patients?

Machine learning models can help reduce the burden on clinicians and patients in resolving uncertain genetic test results, leading to more definitive classifications.

What impact did gene-specific machine learning models have on variant classification in breast cancer patients?

The study found that among breast cancer patients with machine learning evidence applied, over 15% resulted in definitive variant classifications, particularly benefiting underrepresented populations.

Do variants of uncertain significance (VUS) in genetic testing lead to overuse of mastectomies for breast cancer patients?

Results show that VUS in genetic testing do not lead to overuse of mastectomies, offering reassurance on clinical management.

Who is Dr. Ed Esplin and what role does he play in the study?

Dr. Ed Esplin is a Clinical Geneticist at Invitae and a co-author of the study. He highlights the benefits of machine learning algorithms in providing accurate results for breast cancer patients.

What did the study find regarding breast surgery utilization among breast cancer patients with variants of uncertain significance (VUS)?

The study found that patients with VUS results did not undergo surgical procedures more frequently than those with negative results, indicating that VUS does not lead to overuse of mastectomies.