Biomarkers Associated with Lymph Nodal Metastasis in Endometrioid Endometrial Carcinoma

Simple Summary In endometrial cancer, lymph node invasion assessed through surgical lymphadenectomy or sentinel lymph node biopsy is a determinant factor for the prognosis and planification of adjuvant treatment. Those surgical procedures are associated with short- and long-term complications. Recent advances in molecular characterization of endometrial cancer have provided important insights into the biological nature of tumors but have not improved the pre-operative prediction of LND. This study is a description of the transcriptomic landscape associated with lymph node metastases in endometroid endometrial carcinomas. A 54-genes expression signature was generated at analysis of the primary tumor. Differential gene expression was found between patients with and without lymph node metastasis, with an 87% accuracy. Our findings provide a basis for the development of a gene expression-based signature that can be used to pre-operatively select patients for whom surgical assessment of lymph node status is of little value, and, consequently, an unfavorable risk-benefit balance. Introduction. Lymph node metastasis is determinant in the prognosis and treatment of endometrioid endometrial cancer (EEC) but the risk-benefit balance of surgical lymph node staging remains controversial. Objective. Describe the pathways associated with lymph node metastases in EEC detected by whole RNA sequencing. Methods. RNA-sequencing was performed on a retrospective series of 30 non-metastatic EEC. N+ and N- patients were matched for tumoral size, tumoral grade and myometrial invasion. Results. Twenty-eight EECs were analyzable (16 N+ and 12 N-). Bioinformatics Unsupervised analysis revealed three patterns of expression, enriched in N+, mix of N+/N- and enriched in N-, respectively. The cluster with only N+ patient overexpressed extra cellular matrix, epithelial to mesenchymal and smooth muscle contraction pathways with respect to the N- profile. Differential expression analysis between N+ and N- was used to generate a 54-genes signature with an 87% accuracy. Conclusion. RNA-expression analysis provides a basis to develop a gene expression-based signature that could pre-operatively predict lymph node invasion.