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Query: UMLS:C0476089 (endometrial cancer)
 11,379 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

The current medical examinations for detecting endometrial cancer can sometimes be stressful and inconvenient for examinees and examiners. Therefore, we attempted to develop an autoscan-virtual cytology system for detecting endometrial cancer without relying on judgment by the human eye. Exfoliated cells from the uterus were retrieved using a tampon inserted for 3 h. More than 100 monoclonal antibodies (mAb) developed by us were screened in three steps of immunohistochemistry to find mAb sets that would enable the cancer and normal endometrium to be perfectly distinguished. The exfoliated cells provided by 30 endometrial cancer patients and a total of 37 samples of 14 non-malignant volunteers including the menstrual cycle were analyzed using imaging cytometry. All samples contained epithelial cells and dysplasia cells, but the pathologist could not definitively diagnose all of them as endometrial cancer cells because most cells had degenerated. Twenty-two of 28 endometrial cancer tissues (79%) were positive with four mAb sets, CRELD1, GRK5, SLC25A27 and STC2, and 22 of 22 normal endometriums (100%) were negative. Our newly developed autoscan-virtual cytology for exfoliated endometrial cells showed overall sensitivity for endometrial cancer patients and overall specificity for volunteers of 50% (15/30) and 95% (35/37), respectively. Our autoscan-virtual cytology combined with cancer-specific mAb and imaging cytometry could be useful for endometrial cancer detection. Autoscan-virtual cytology for endometrial cancer deserves further evaluation for future endometrial cancer screening.
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PMID:Novel virtual cytological analysis for the detection of endometrial cancer cells using autoscan fluoromicroscopy. 2129 18