Rarely Observed Histopathological Subtypes of Endometrial Malignant Tumors in a Tertiary Care Center: A Case Series.

Introduction Endometrial cancer, one of the most prevalent gynecological malignancies, represents a significant contributor to global mortality and morbidity. The histological subtype of this cancer is pivotal in treatment planning and patient risk stratification. This case series, comprising seven cases, underscores the significance of rare endometrial cancer variants and the importance of ancillary studies, specifically immunohistochemistry, in comprehending and diagnosing the condition. Materials and methods The data of all the rare histological subtypes of malignant endometrial tumors encountered from April 2021 to April 2024 were collected. The data collected included age; risk factor; histological type; tumor, node, metastasis (TNM) stage; the International Federation of Gynecology and Obstetrics (FIGO) grade; P53; and mismatch repair (MMR) status. The histopathology specimens were reviewed using a Labomed microscope (LX500) manufactured in India. Images were taken and added wherever necessary, and the results were studied, analyzed, clinically correlated, and are shown in tables. Results Seven rare histopathological subtypes of malignant endometrial tumors were encountered in this period in this tertiary care center. This included mesonephric like adenocarcinoma, high-grade carcinosarcoma, carcinosarcoma with the serous and chondrosarcomatous components, clear cell carcinoma of endometrium, endometrial stromal sarcoma with smooth muscle differentiation, endometrial stromal sarcoma, and undifferentiated sarcoma with focal myxoid degeneration.  Conclusion Diagnosis of uncommon endometrial carcinomas proves to be challenging due to their various histological subtypes, most often with overlapping features. The cornerstone of effective care lies in collaboration with clinicians, radiologists, and pathologists to identify these lesions as early as possible using a multidisciplinary approach for optimal patient outcome management.