Algorithm Developed to Identify Hereditary Gynecologic Cancer Patients... 100% Positive Predictive Value

Bundang Seoul National University Hospital Team Develops Algorithm for Germline Genetic Testing
Analysis of 702 Gynecologic Cancer Patients
Hereditary Mutations Confirmed in All Four Patients Selected by the Algorithm and Tested

An algorithm has been developed that can identify patients with hereditary gynecologic cancers. It is expected to help reduce indiscriminate germline genetic testing while ensuring that genuinely high-risk individuals are not overlooked.

Professor Kim Kidong, Department of Obstetrics and Gynecology, Bundang Seoul National University Hospital. Bundang Seoul National University Hospital

Bundang Seoul National University Hospital announced on March 3 that the research team led by Professor Kim Kidong of the Department of Obstetrics and Gynecology has developed a technology that utilizes the 'tumor gene panel test,' which is routinely performed for gynecologic cancer treatment, to further screen patients who genuinely require additional genetic testing.

It is known that approximately 10% of gynecologic cancer patients have hereditary cancer. The issue is that tumor gene panel tests only confirm the presence of mutations, but cannot distinguish whether these mutations are of germline or somatic origin. To determine if a mutation is germline, a separate test is required. However, with testing costs ranging from 500,000 to 1 million won, it is not feasible to perform such tests for all patients.

The research team focused on two indicators already provided in tumor panel tests. One is the 'mutation tier,' which classifies mutations according to cancer relevance. The team used tier 1 and tier 2 mutations, which are highly associated with hereditary cancers, as the standard. The other indicator is the mutation allele frequency. Since germline mutations exist in all cells, their frequency tends to be relatively high, so the threshold was set at 40% or higher.

Additionally, the scope was limited to 11 genetic mutations that are well-established as being linked to hereditary gynecologic cancers such as ovarian and endometrial cancer. This design aims to reduce unnecessary false positives.

To validate the algorithm, it was applied to 702 patients with gynecologic cancers who underwent tumor gene panel testing. As a result, 19 patients, or 2.7%, were classified as requiring additional germline genetic testing. Among them, all four who actually underwent further testing were confirmed to have hereditary gynecologic cancer. The research team reported a positive predictive value of 100%.

This study is significant in that it presents an algorithm-based screening criterion for germline testing, which had previously been performed without clear standards. If future prospective studies provide additional indicators such as sensitivity and specificity, the likelihood of clinical application will increase further.

Professor Kim stated, "This algorithm is a practical tool that bridges the diagnostic gap between tumor gene panel tests and germline testing. By systematically identifying patients who genuinely need genetic counseling and germline testing using tumor test data, our goal is to efficiently utilize medical resources while ensuring that high-risk hereditary cancer patients receive appropriate management." The research results were recently published in the international journal 'Gynecologic Oncology.'

This content was produced with the assistance of AI translation services.