BACKGROUND The two most common types of uterine endometrial carcinoma, endometrioid (UEC) and serous (USC), differ in their histopathologic appearance and biologic behavior. Recent studies suggest that these differences may be associated with distinct molecular genetic alterations. METHODS In the current study, the authors compared the frequencies of K‐ras and p53 mutations and microsatellite instability (MI) between UEC and USC by analyzing all 3 molecular genetic changes in one set of tumors. Furthermore, the distribution of these molecular genetic alterations was determined among UECs of different histopathologic grade. The authors analyzed 58 UECs with known MI status for K‐ras and p53 mutations. The K‐ras and p53 genes were analyzed in 45 and 6 cases of USC, respectively. These results were combined with previous data on p53 mutations (21 cases) and MI (34 cases) in USC. RESULTS MI was present in 16 of 57 UECs (28%) but in none of 34 USCs. p53 mutations were found in 7 of 42 UECs (17%) and 25 of 27 USCs (93%) by direct sequencing of exons 5–8. UECs and USCs with p53 mutations showed strong immunoreactivity for p53 in about 85% of the cases, whereas about 15% of the cases were immunonegative. K‐ras mutations at codon 12 were found in 15 of 58 UECs (26%) and in only 1 of 45 USC (2%) by dot blot oligohybridization after polymerase chain reaction amplification of exon 1. Notably, the frequency of both K‐ras and p53 mutations and MI was significantly different between UEC and USC (P < 0.001). In UECs, MI and K‐ras mutations occurred in low grade as well as in high grade tumors, whereas p53 mutations were present almost exclusively in high grade tumors. CONCLUSIONS The results of this study suggest that different molecular genetic pathways are involved in the pathogenesis of UEC and USC and that low grade UEC may progress to high grade UEC. These findings support the hypothesis that UEC and USC are separate entities and suggest that different molecular genetic alterations may be responsible for their distinct morphology and biologic behavior. Cancer 2000;88:814–24. © 2000 American Cancer Society.

Ascites macrophages in advanced epithelial ovarian cancer (AdEOC) are involved in cancer metastasis and progression by modifying the tumor microenvironment. However, the precise mechanisms of cell-to-cell interaction between macrophages and tumor cells are still unclear. This study focused on the activation of signal transducer and activator of transcription 3 (Stat3) which is a critical signal transduction molecule at a point of convergence for numerous oncogenic signaling pathways as well as controlling the M2-poralization of macrophages. AdEOC ascites, in which high concentration of interleukin (IL)-6, IL-10, growth-related oncogene-alpha and vascular endothelial growth factor were detected, stimulated the proliferation of SKOV3 cells, a human ovarian cancer cell line. The simultaneous blocking of IL-6 and IL-10 by neutralizing antibodies suppressed ascites-induced tumor cell proliferation. Stat3 activation in SKOV3 cells was induced by co-culture with macrophages especially with macrophage colony stimulating factor-primed M2 macrophages but lesser extent with granulocyte-macrophage colony stimulating factor-primed immature macrophages. Cyclin-D1 expression in SKOV3 cells was also significantly induced by co-culture with macrophages. Blocking of Stat3 in macrophages by small interfering RNA inhibited the production of IL-6 and IL-10 by macrophages, and suppressed Stat3 activation and cyclin-D1 induction in co-cultured SKOV3 cells. Stat3 activation in SKOV3 cells was abrogated by simultaneous neutralization of IL-6 and IL-10. These results indicate that Stat3 activation by IL-6 and IL-10 plays an important role in cell-to-cell interaction between tumor cells and macrophages in the ascites of AdEOC.

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BackgroundAdvanced-stage ovarian cancer patients are generally treated with platinum/taxane-based chemotherapy after primary debulking surgery. However, there is a wide range of outcomes for individual patients. Therefore, the clinicopathological factors alone are insufficient for predicting prognosis. Our aim is to identify a progression-free survival (PFS)-related molecular profile for predicting survival of patients with advanced-stage serous ovarian cancer.Methodology/Principal FindingsAdvanced-stage serous ovarian cancer tissues from 110 Japanese patients who underwent primary surgery and platinum/taxane-based chemotherapy were profiled using oligonucleotide microarrays. We selected 88 PFS-related genes by a univariate Cox model (p<0.01) and generated the prognostic index based on 88 PFS-related genes after adjustment of regression coefficients of the respective genes by ridge regression Cox model using 10-fold cross-validation. The prognostic index was independently associated with PFS time compared to other clinical factors in multivariate analysis [hazard ratio (HR), 3.72; 95% confidence interval (CI), 2.66–5.43; p<0.0001]. In an external dataset, multivariate analysis revealed that this prognostic index was significantly correlated with PFS time (HR, 1.54; 95% CI, 1.20–1.98; p = 0.0008). Furthermore, the correlation between the prognostic index and overall survival time was confirmed in the two independent external datasets (log rank test, p = 0.0010 and 0.0008).Conclusions/SignificanceThe prognostic ability of our index based on the 88-gene expression profile in ridge regression Cox hazard model was shown to be independent of other clinical factors in predicting cancer prognosis across two distinct datasets. Further study will be necessary to improve predictive accuracy of the prognostic index toward clinical application for evaluation of the risk of recurrence in patients with advanced-stage serous ovarian cancer.