No abstract

Cyclin A, a cell cycle regulatory protein, promotes cell proliferation and has been observed to be highly expressed in cancer and to promote tumor growth; however, its value as a marker for endometrial carcinoma has not yet been established. Accordingly, the aim of the present study was to clarify whether cyclin A can be used as a cell proliferation marker using the endometrial carcinoma cell lines Ishikawa and HEC-50B, derived from patients with low-grade and high-grade cancer, respectively. The expression of cyclin A was determined by flow cytometry using double staining with FITC and 7-AAD, and immunocytochemical staining. The results were compared to those of Ki-67, the widely used cell proliferation marker that is considered to be a prognostic marker in endometrial cancer. The flow cytometry results revealed that cyclin A expression was significantly higher in HEC-50B than in Ishikawa cells during the logarithmic growth phase. In addition, cyclin A expression was consistently higher than Ki-67 expression in the examined cell lines. Immunocytochemical staining confirmed cyclin A expression in HEC-50B and Ishikawa cells, demonstrating significantly higher expression during the logarithmic growth phase than during the stationary phase. By contrast, Ki-67 was expressed in almost 90% of the cells, irrespective of their growth state. These results indicate that cyclin A expression is significantly increased in cells with higher proliferative ability and is specifically expressed in cells that have passed the G1-S checkpoint. Therefore, cyclin A may be a reliable proliferation biomarker for endometrioid carcinoma.

Introduction: Direct smearing preparation (conventional preparation [CP]) has been widely used for endometrial cytology in Japan. In CP, sampling and screening errors are problematic. In liquid-based cytology preparation (LBC), the problems of CP can be solved. But there is a problem that cytological findings of LBC are different from those of CP. The purpose of this study was to evaluate the differences of morphological findings of endometrial cytology between LBC and CP, and the usefulness of the endometrial LBC to differentiate endometrioid carcinoma grade 1 (G1) from grade 3 (G3). Methods: Thirteen cases of endometrioid carcinoma G1, and 5 cases of G3 collected by the Softcyte device and prepared by LBC and CP (split specimen) were used. We focused on the following items: (1) the number of clusters per cm2, (2) the number of layers of clusters, (3) area of clusters, (4) perimeter of clusters, (5) roundness of clusters, (6) complexity of clusters, (7) area of nucleus, (8) perimeter of nucleus, (9) roundness of nucleus, (10) complexity of nucleus, (11) area of nucleolus, and (12) nucleolus-nucleus ratio (N/N). Results: Compared with CP, the number of clusters and layers of the clusters in LBC were significantly larger in G1. The area and perimeters of the clusters and the nucleus were significant smaller, and the N/N ratio was greater in LBC than that in CP in both G1 and G3. Regarding morphological differences between G1 and G3 in LBC and CP, the number of layers was significantly larger in G1 than in G3 in LBC and CP. The area of the clusters in LBC was significantly larger in G1 than in G3. The area and perimeters of the nucleus in CP and the area of the nucleolus and N/N ratio in LBC and CP were significantly smaller in G1 than in G3. Conclusion: In the endometrial cytology, it became clear that the cell image was different between LBC and CP and between G1 and G3. By microscopic examination understanding the characteristics of the cell image in LBC, endometrial LBC could be useful to diagnose endometrial carcinoma.

Ovarian cancer is the most common cause of gynecological malignancy-related mortality since early-stage disease is difficult to diagnose. Advanced clear cell carcinoma of the ovary (CCCO) has dismal prognosis, and its incidence has been increasing in Japan, emphasizing the need for highly sensitive diagnostic and prognostic CCCO biomarkers. Exosomal microRNAs (miRNAs) secreted by tumor cells are known to play a role in carcinogenesis; however, their involvement in ovarian cancer is unclear. In this study, we performed expression profiling of miRNAs from exosomes released by five cell lines representing different histological types of ovarian cancer. Exosomes isolated from culture media of cancer and normal cells were compared for miRNA composition using human miRNA microarray. We detected 143 exosomal miRNAs, whose expression was ≥1.5-fold higher in ovarian cancer cells than in the control. Among them, 28 miRNAs were upregulated in cells of all histological ovarian cancer types compared to control, and three were upregulated in CCCO cells compared to other types. Functional analyses indicated that miR-21 overexpressed in CCCO cells targeted tumor suppressor genes PTEN, TPM1, PDCD4, and MASP1. The identified miRNAs could represent novel candidate biomarkers to diagnose or monitor progression of ovarian cancer, particularly CCCO.

Objective: The cytological diagnosis of coelomic fluid is essential for examining malignant mesothelioma (MM). However, reactive mesothelium (RM), caused by various factors, is morphologically similar to MM and thus often complicates the differential diagnosis. Here, nuclear luminance and steric alterations were assessed for the discriminant analysis of MM and RM. Study Design: Thirteen epithelial MM and 11 RM cases were included. One hundred alterations in the numbers of nuclear pixels and focus layers and the coefficient of variation of nuclear luminance among layers were determined for each case to conduct discriminant analysis using the Mahalanobis distance. Results: A cutoff value of 0.072 allowed highly accurate discrimination of MM (89.5%) and RM (89.6%). Fifteen cells appeared in 6 agglomerates of indiscriminable MM cases. The 6 agglomerates were individually examined. Malignant cells were dominant in 3 agglomerates (50%), allowing the discrimination of malignant cases. Conclusion: Discrimination using nuclear luminance and steric alterations is useful for morphologically indiscriminable MM cases. Three-dimensional analysis of agglomerates will be further investigated to improve the diagnostic accuracy.