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Author Spotlight: Advancing Cancer Associated Thrombosis Research in Rodent Models
Published on: January 5, 2024
Potential utility of comprehensive genomic profiling to predict venous thromboembolism in patients with solid cancer
Kanna Nakamura1, Kazuhisa Kaneda1, Shinya Ikeda2
1Department of Cardiovascular Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Background:
It has become increasingly important to accurately identify cancer patients at high risk for venous thromboembolism (VTE) who could have greater benefit with anticoagulants. Cancer-associated genomic variants could have a potential clinical utility for prediction of VTE.
Methods:
This study was a single-center observational study using the C-CAT database, the national datacenter for cancer genomic medicine in Japan, and evaluated 412 cancer patients who underwent comprehensive genome profiling with FoundationOne CDx at Kyoto University Hospital. We comprehensively investigated the association between cancer-associated genomic variants and VTE development.
Results:
In the entire cohort, 77% had distant metastasis, and 90% were under chemotherapy. During a median follow-up period of 693 days, 59 patients (14.3%) developed VTE events. The cumulative incidence of VTE events after specimen collection was 26.0% at 5 years. In the multivariable Fine-Gray sub-distribution hazard models adjusted for age, sex, cancer type, metastasis, and chemotherapy at baseline, several genomic variants showed a trend toward an increased risk of VTE, including ERBB2 (HR 2.43, 95% CI 1.21-4.87), APC (HR 1.94, 95% CI 0.84-4.50), KRAS (HR 1.67, 95% CI 0.79-3.53), ATM (HR 1.64, 95% CI 0.74-3.65), and NOTCH1 (HR 1.51, 95% CI 0.73-3.11). However, no variants remained statistically significant after correction for multiple testing.
Conclusion:
The current exploratory study identified several genomic variants potentially associated with a high risk of cancer-associated VTE, which may indicate potential clinical utility of comprehensive genomic profiling for accurate prediction of VTE events in cancer patients.
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