Precision oncology represents a challenge when it comes to Endometrial Cancer (EC). The incidence of this cancer has increased in the last years and the prognostic and therapeutic options for advanced disease stages are still poor. Thus, to improve the treatment of EC patients with poor prognosis, it is necessary to gain more knowledge in the cancer molecular biology and also in the new approaches to capture the innate intra-tumour heterogeneity (ITH), which is highly present in EC. The objective of the ECLAI consortium is to reach personalised EC management by developing new tools that recapitulate the heterogeneous molecular composition of tumors and finally establish new and effective therapeutic regimens. With this aim, our consortium will combine: a) the use of non-invasive biopsies, which capture ITH, and the genomic characterisation of the tumor within the disease evolution, b) the generation of preclinical models to test personalised alternative targeted therapies and c) the use of machine learning strategies to decipher a recurrence and therapeutic response rate algorithm, named ECLAI, with clinical application to improve EC management. This workflow will be applied with the advise and support of patients’ associations and ENITEC, the European research network on EC. Altogether, this pioneering strategy has the final goal to improve the management and life quality of EC patients who currently have limited clinical opportunities.
