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Serum microRNA profile enables preoperative diagnosis of uterine leiomyosarcoma
Akira Yokoi1,2, Juntaro Matsuzaki1, Yusuke Yamamoto1
1Division of Molecular and Cellular Medicine, National Cancer Center Research Institute, Tokyo, Japan.
Abstract:
Uterine leiomyosarcoma (ULMS) is the major subtype of uterine sarcoma (US) and contributes to uterine cancer deaths. Although preoperative diagnosis of US remains challenging, frequent application of laparoscopic surgery for benign uterine leiomyomas (ULM) requires precise exclusion of US. MicroRNAs are stably present in the bloodstream, and the application of circulating miRNAs as disease biomarkers has been recognized. In the present study, we aimed to identify diagnostic biomarkers for distinguishing US from ULM by focusing on circulating miRNAs. All serum samples were collected preoperatively between 2009 and 2017, and all cases were histopathologically diagnosed. Whole miRNA profiles were obtained using a miRNA microarray. By analyzing expression levels of the miRNAs, candidate miRNAs were selected based on diagnostic performance in discriminating US from ULM, and a diagnostic model was then constructed. A total of 90 serum samples were analyzed, and clustering analyses revealed that the profiles of ULMS were distinct from those of controls. Based on leave-one-out cross-validation, seven miRNAs were selected as biomarker candidates. Based on model construction, the optimal model consisted of two miRNAs (miR-1246 and miR-191-5p), with an area under the receiver operating characteristic curve (AUC) for identifying ULMS of 0.97 (95% confidence interval [CI], 0.91-1.00). In contrast, serum lactate dehydrogenase had an AUC of only 0.64 (95% CI, 0.34-0.94). Seven serum miRNAs with high diagnostic performance for preoperative US screening were detected, and a promising diagnostic model for ULMS was generated.
Insights
Circulating microRNAs in blood show promise for diagnosing uterine leiomyosarcoma (ULMS). A diagnostic model using two specific microRNAs achieved high accuracy, aiding in distinguishing ULMS from benign conditions.
Area of Science:
- Gynecologic Oncology
- Molecular Diagnostics
- Biomarker Discovery
Background:
- Uterine sarcoma (US), particularly uterine leiomyosarcoma (ULMS), poses a diagnostic challenge preoperatively.
- Accurate differentiation between ULMS and benign uterine leiomyomas (ULM) is crucial, especially with the rise of minimally invasive surgeries like laparoscopy.
- Circulating microRNAs (miRNAs) are emerging as stable and reliable biomarkers in blood for various diseases.
Purpose of the Study:
- To identify circulating microRNAs as diagnostic biomarkers for distinguishing ULMS from ULM.
- To develop a predictive model for preoperative diagnosis of ULMS using serum miRNA profiles.
Main Methods:
- Serum samples from 90 patients (ULMS and controls) collected between 2009-2017 were analyzed using miRNA microarrays.
- Expression levels of circulating miRNAs were assessed to identify candidate biomarkers.
- A diagnostic model was constructed and validated using leave-one-out cross-validation.
Main Results:
- Clustering analysis revealed distinct miRNA expression profiles between ULMS and control groups.
- Seven candidate miRNAs were identified with high diagnostic performance.
- An optimal diagnostic model incorporating miR-1246 and miR-191-5p demonstrated a high area under the receiver operating characteristic curve (AUC) of 0.97 for ULMS detection.
Conclusions:
- A panel of seven serum miRNAs exhibits significant diagnostic potential for preoperative screening of uterine sarcoma.
- The developed two-miRNA model (miR-1246 and miR-191-5p) offers a promising, accurate, and non-invasive method for differentiating ULMS from ULM.
- This miRNA-based approach surpasses the diagnostic utility of serum lactate dehydrogenase for ULMS detection.
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