MTMasashi Takano
Papers(3)
Co-Expression of Meso…Rapid decrease in ser…Establishment of a Mo…
Collaborators(10)
Soichiro KakimotoMorikazu MiyamotoTaira HadaHiroaki SoyamaTakahiro SakamotoHideki IwahashiTakahiro EinamaHiroki IshibashiHiroko MatsuuraJin Suminokura
Institutions(1)
National Defense Medi…

Papers

Co-Expression of Mesothelin and CA125 Is Associated with the Poor Prognosis of Endometrial Serous Carcinoma and Mixed Carcinomas Including Serous Carcinoma

The aim of this study was to investigate the association between the clinicopathologic factors and either expression or co-expression of mesothelin and cancer antigen (CA) 125 in endometrial serous carcinoma and mixed carcinomas including serous carcinoma. Between 1990 and 2017, patients with endometrial serous carcinoma and mixed carcinoma including serous carcinoma treated by total hysterectomy and bilateral salpingo-oophorectomy at our hospital were identified. The association between either expression or co-expression of mesothelin and CA125 was evaluated by immunochemical analysis and the clinico-pathological features were retrospectively examined. Among the 40 patients included, 19, 31, and 18 patients exhibited single positive mesothelin, single positive CA125, and positive co-expression, respectively. The expression of mesothelin and CA125 was observed to be positively associated (p = 0.021). There was no significant association of age and FIGO stage with individual mesothelin or CA125 expression or their co-expression. Overall survival (OS), but not progression-free survivals (PFS), of only mesothelin-positive patients was worse (p = 0.024). Hence, OS and PFS of patients with positive co-expression were worse (PFS: p = 0.043, OS: p = 0.012). In multivariate analysis, single mesothelin expression and single CA125 expression did not lead to worse prognosis. However, positive co-expression was the worst prognostic factor for OS (hazard ratio: 3.32, p = 0.039). Co-expression of mesothelin and CA125 may accurately predict OS in endometrial serous carcinoma and mixed carcinomas including serous carcinoma. Further studies should examine this relationship.

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  < 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  < 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  < 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.

13Works
3Papers
21Collaborators
Ovarian NeoplasmsPrognosisBiomarkers, TumorEndometrial NeoplasmsNeoplasm Recurrence, LocalDrug Resistance, NeoplasmCystadenocarcinoma, SerousCell Line, Tumor