RESUMO
Synchronous endometrial and ovarian malignancies occur in 5% of women presenting with endometrial cancer and 10% of patients presenting with ovarian malignancy. When a high-grade serous carcinoma concurrently involves both ovary and endometrium, pathological determination of whether they are synchronous primaries or metastatic tumors from one primary site can be challenging. MicroRNAs (miRNA) are 22-nucleotide noncoding RNAs that are aberrantly expressed in cancer cells and may inherit their cellular lineage characteristics. We explored possible differential miRNA signatures that may separate high-grade ovarian serous carcinoma from primary endometrial serous carcinoma. Forty-seven samples of histologically pure high-grade serous carcinoma of both uterine (16 case) and ovarian primaries (31 cases) were included. Expression of 384 mature miRNAs was analyzed using ABI TaqMan Low-Density Arrays technology. A random forest model was used to identify miRNAs that together could differentiate between uterine and ovarian serous carcinomas. Among 150 miRNAs detectable at various levels in the study cases, a panel of 11-miRNA signatures was identified to significantly discriminate between ovarian and uterine serous carcinoma (P < .05). A nested cross-validated convergent forest plot using 6 of the 11 miRNA signature was eventually established to classify the tumors with 91.5% accuracy. In conclusion, we have characterized a miRNA signature panel in this exploratory study that shows significant discriminatory power in separating primary ovarian high-grade serous carcinoma from its endometrial counterpart.
