Description

Uterine sarcomas are rare mesenchymal neoplasms in the female genital system, accounting for about 1% of female reproductive tract malignancies and 3%~7% of uterine malignancies. Subtypes of uterine sarcoma are leiomyosarcoma, endometrial stromal sarcoma, and adenosarcoma. Uterine leiomyosarcoma is the most common uterine sarcoma, accounting for about 1% to 2% of all uterine malignancies.

Uterine sarcomas differ in histologic appearance and clinical behavior. The incidence of uterine sarcoma is low and the prognosis is poor. Its manifestations mainly include abnormal vaginal bleeding, abdominal pain and abdominal mass, but none of these symptoms are specific.

For uterine sarcoma, there are no diagnostic serum markers and imaging features and the diagnosis of uterine sarcoma still mainly depends on postoperative pathological results. However, with the development of omics technology, immunophenotypes and molecular characterization of uterine sarcomas have increasingly been utilized to improve diagnostic classification and prognostication in uterine sarcomas. Uterine leiomyosarcoma, the most common subtype of uterine sarcoma, does not have a single defining molecular abnormality.

This project intends to use multi-omics technology to screen the key factors for the occurrence, development, and malignant transformation of uterine sarcoma, especially uterine leiomyosarcoma, and to map the interaction network of cell signaling pathways. It provides key molecular markers for the early assessment of recurrence and malignant transformation of uterine myoma after conservative treatment, and provides a molecular mechanism basis for finding solutions to prevent the progression and malignant transformation.