Molecular profiling of Endometrial Cancer and its impact on designing personalized therapy

Endometrial cancer is one of the most prevalent gynecological malignancies, with a significant increase in both incidence and mortality over the past decade. The estimated number of new cases of endometrial cancer in India in 2022 was 17,420 with an estimated deaths of about 6845 and ranks 3rd in number among female genital tract malignancies. This upward trajectory is largely attributed to increased life expectancy and the rising prevalence of risk factors such as obesity, which has become a major contributor to the growing incidence of the disease. The adoption of sentinel lymph node (SLN) mapping has emerged as a promising technique to overcome the issues associated with traditional lymphadenectomy, providing reliable data on nodal involvement. Furthermore, the use of ultra-staging in SLN mapping allows for the detection of low-volume disease, including isolated tumor cells and micro-metastases, which are often missed by conventional histopathological methods. This advancement has significantly improved the accuracy of staging and treatment planning. One of the most impactful innovations in endometrial cancer management has been the integration of molecular and genomic profiling. The landmark data from The Cancer Genome Atlas (TCGA) published in 2013, followed by updates from the European Society for Medical Oncology (ESMO), European Society of Gynaecological Oncology (ESGO), and the International Federation of Gynecology and Obstetrics (FIGO), have led to a better understanding of the molecular heterogeneity of this disease. Our hypothesis is that there will be differences in sentinel lymph node involvement rates and adjuvant therapy pathways if molecular classification is integrated in conventional management for patients with endometrial cancer. This might provide evidence to escalate or de-escalate therapeutic decisions and personalized management. However, there is currently no prospective evidence supporting the use of molecular classification to guide surgical or adjuvant treatment decisions. This prospective study aims to evaluate the predictive value of molecular features over the conventional histopathological prognostic factors for planning adjuvant therapy and for identifying the risk of sentinel nodal metastases in endometrial cancer.