Kimiya Sato

MicroRNA-21 expression in cancer cells is an independent biomarker of progression-free survival of endometrioid endometrial carcinoma

Endometrial carcinoma is one of the most common gynecological cancers. MicroRNA-21 (miR-21) is the most consistently overexpressed miRNA in almost all human cancer types, and it might be a useful clinical biomarker and therapeutic target. However, its precise localization and significance in endometrial carcinoma have not been clarified. This study aimed to examine miR-21 expression in endometrial carcinoma and reveal its clinicopathological importance. We investigated miR-21 expression by in situ hybridization (ISH) using locked nucleic acid (LNA)-modified probes in 230 endometrial carcinoma patients. We evaluated miR-21 expression in cancer cells and stroma separately. High miR-21 expression in cancer cells was significantly associated with higher histological grade and lymph node metastasis. In Kaplan-Meier analysis, high miR-21 expression in cancer cells was significantly associated with poor progression-free survival. In particular, in endometrioid carcinoma, high miR-21 expression in cancer cells was an independent prognostic factor associated with poor progression-free survival, as well as older age and higher International Federation of Gynecology and Obstetrics (FIGO) stage.

Correlation of high LAT1 expression with the prognosis of endometrioid carcinoma of the uterine corpus

The expression of L-type amino acid transporter 1 (LAT1) has been described to play essential roles in cancer cell growth and survival. To determine the significance of LAT1 in the prognosis of endometrial endometrioid carcinoma, we investigated LAT1 expression in 353 endometrioid carcinoma patients by immunohistochemical analysis using tissue microarray. The tumors in which stained tumor cells made up more than 25% of the tumor were graded as high expression. High expression of LAT1 was detected in 29 (8.2%) of patients. The ratio of high LAT1 expression did not significantly differ by age (< 60 vs. ≥ 60), FIGO stage (stage I/II vs. III/IV), histological grade (grade 1 vs. grade 2/3), or lymph node metastasis (positive vs. negative). However, high LAT1 expression in endometrioid carcinoma was associated with a poorer progression-free survival and overall survival, as per the results of the log-rank test (P = 0.0263 and 0.0404, respectively). Cox univariate and multivariate analyses revealed that high LAT1 expression is an independent marker of poor progression-free survival (hazard ratio = 2.598, P = 0.0137), in addition to a higher age (≥ 60 years vs. < 60 years), FIGO stage (stage III/IV vs. I/II), and histological grade (grade 2/3 vs. grade 1). In conclusion, we demonstrate that LAT1 is associated with a poor prognosis of endometrioid carcinoma of the uterine corpus.

Different Prognostic Implications of Aquaporin-1 and Aquaporin-5 Expression among Different Histological Types of Ovarian Carcinoma

The aquaporins (AQPs) are a family of transmembrane water channel proteins that are distributed in various human tissues. Recent studies have suggested that AQP expression correlates with various aspects of cancer biology that determine the aggressiveness of different cancers. Ovarian carcinoma is one of the most lethal gynecological cancers. Some studies have suggested that AQPs are expressed in ovarian carcinoma, and are associated with cancer cell growth and migration. In this study, we immunohistochemically evaluated the expression of AQP1, 3, 5, and 9 in a total of 300 ovarian carcinomas using tissue microarrays. In our analyses of correlations between aquaporin expression and overall survival, high AQP5 expression was significantly associated with poorer prognosis (P = 0.029). For AQP1, the low expression group trended towards poorer prognosis than the high expression group, but the difference was not statistically significant. When ovarian carcinomas were divided by histological types, high AQP5 expression correlated with poorer prognosis in serous carcinoma (P = 0.015), and low AQP1 expression correlated with poorer prognosis in clear cell carcinomas (P = 0.0055). By contrast, high AQP1 expression correlated with poorer prognosis in mucinous carcinoma (P = 0.0001) and endometrioid carcinoma (P = 0.021). Our studies suggest that AQPs can be useful prognostic markers in ovarian carcinoma, but their correlation with prognosis depends on the histological type of ovarian carcinoma.

Establishment of a Model to Predict the Prognosis of Endometrial Carcinoma Using Tumor‐Infiltrating Lymphocytes Evaluated With Artificial Intelligence: A Retrospective Analysis

ABSTRACT Background The objective of this study was to establish a new model for predicting the prognosis of endometrial carcinoma (EC) using tumor‐infiltrating lymphocytes (TILs) based on artificial intelligence (AI). Methods Patients with EC who were treated between 1989 and 2022 were included in this study. For each patient, one hematoxylin and eosin‐stained slide containing the most invasive frontline of the tumor was selected and digitized. The area within a 500 μm width span, extending 250 μm toward the stroma and tumor from the manually annotated invasive frontline, was automatically annotated. The average number of lymphocytes per area (μm 2 ) in the annotated area was calculated using AI. Patients were classified into the High‐TIL and Low‐TIL groups, and survival analysis was conducted. Four mismatch repair (MMR)‐related proteins were evaluated using immunohistochemical staining. Results A total of 659 patients were included: 346 (52.5%) in the High‐TIL group and 313 (47.5%) in the Low‐TIL group. MMR deficiency was observed more frequently in the High‐TIL group than in the Low‐TIL group ( p  &lt; 0.01). Progression‐free survival (PFS) and overall survival (OS) were better in the High‐TIL group than in the Low‐TIL group (both p  &lt; 0.01). Multivariate analysis revealed that TIL status was a prognostic factor for PFS (hazard ratio [HR] (95% confidence interval [CI]) 0.61 (0.43–0.87); p  &lt; 0.01) and OS (HR (95% CI) 0.54 (0.33–0.86); p  = 0.01). Conclusion TILs evaluated using AI could accurately and significantly predict the prognosis of EC. Further studies are needed to establish new methods for evaluating TILs in ECs.