Abstract
Precision medicine based on cancer genomics is being applied in clinical practice. However, patients do not always derive benefits from genomic testing. Here, we performed targeted amplicon exome sequencing-based panel tests, including 160 cancer-related genes (PleSSision-160), on 88 malignant ovarian tumors (high-grade serous carcinoma, 27; endometrioid carcinoma, 15; clear cell carcinoma, 30; mucinous carcinoma, 6; undifferentiated carcinoma, 4; and others, 6 (immature teratoma, 1; carcinosarcoma, 3; squamous cell carcinoma, 1; and mixed, 1)), to assess treatment strategies and useful biomarkers for malignant ovarian tumors. Overall, actionable gene variants were found in 90.9%, and druggable gene variants were found in 40.9% of the cases. Actionable BRCA1 and BRCA2 variants were found in 4.5% of each of the cases. ERBB2 amplification was found in 33.3% of mucinous carcinoma cases. Druggable hypermutation/ultramutation (tumor mutation burden ≥ 10 SNVs/Mbp) was found in 7.4% of high-grade serous carcinoma, 46.7% of endometrioid carcinoma, 10% of clear cell carcinoma, 0% of mucinous carcinoma, 25% of undifferentiated carcinoma, and 33.3% of the other cancer cases. Copy number alterations were significantly higher in high-grade serous carcinoma (P <.005) than in other histologic subtypes; some clear cell carcinoma showed high copy number alterations that were correlated with advanced stage (P <.05) and worse survival (P <.01). A high count of copy number alteration was associated with worse survival in all malignant ovarian tumors (P <.05). Our study shows that targeted agents can be detected in approximately 40% of malignant ovarian tumors via multigene panel testing, and copy number alteration count can be a useful marker to help assess risks in malignant ovarian tumor patients.
| Original language | English |
|---|---|
| Pages (from-to) | 7407-7417 |
| Number of pages | 11 |
| Journal | Cancer Medicine |
| Volume | 9 |
| Issue number | 20 |
| DOIs | |
| Publication status | Published - 01-10-2020 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Oncology
- Radiology Nuclear Medicine and imaging
- Cancer Research
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