Abstract OT1-20-01: Feasibility of creation of a clinico-biological database: A prospective longitudinal cohort study of metastatic breast cancer patients (epicuresein)
Authors: Colombié Mathilde , Jézéquel Pascal , Rubeaux Mathieu , Frenel Jean-Sebastien , Bigot Frédéric , Seegers Valérie , Campone Mario 
Published: March 2022

Abstract
Background: Each year 5 to 10% of new breast cancers are diagnosed with a metastatic staging. Metastatic breast cancer remains an incurable disease despite significant therapeutic advances in both supportive cares and targeted specific therapies. The disease is in most cases characterized by the disruption of systemic homeostasis (coinciding with multiple interactive and dependent parameters). Decision algorithms rely on a number of objective and subjective parameters which allow the therapeutic decision making process to become the most individualized or adapted. Extrinsic objectives parameters are currently based on EBM (evidence-based-medicine). Intrinsic subjective parameters are taken into account in decision-making: parameters that are linked to the oncologist's assumptions, such asthe sensitivity to the theoretical efficacy of treatments and the definition of sensitivity. Currently, the clinician rationalizes these therapeutic indications according to the prediction of the treatment response from the "phenotypic classification". Cancer is a complex disease relying on numerous elements in dynamic, organized and evolving interactions, and analysis of a complex system requires a global approach. The research hypothesis is to evolve from a reductionist, disjunctive, analytical view of the characterization of cell components (genes, transcripts, proteins, etc.) to a global, systemic, conjunctive and organizational vision: distinct datasets are linked and we need to unravel these underlying links. With this project, we want to demonstrate the ability to exploit complex data in healthcare and in particular in cancer management. We chose a specific metastatic breast cancer model. Methods: Our project is to integrate massive and heterogeneous data concerning the patient’s environment, personal and familial history, clinical and biological data, imaging, histological results, multi-omics data, and microbiota analysis. These characteristics are multiple and in dynamic interaction overtime. The main objective is to prove feasibility of creation of a clinico-biological database prospectively by collecting epidemiological, socio-economic, clinical, biological, pathological, multi-omics data and to identify characteristics related to the disease progression before treatment and within 15 years after treatment start from a cohort of 300 patients with a metastatic breast cancer treated in our institution. Results: The EPICURE trial opened in December 2018. Overall recruitment as of July 2021 was 116 patients; 72% had history of adjuvant therapy and 28% had immediately metastatic disease. We created three groups: HR+/Her2- (75% of enrolment); HER2+ (12%); and triple-negative breast cancer (13%). For 89% of patients, we obtained metastatic biopsy during screening and at date 20 metastatic biopsies for recurrence. For all patients, we collected blood sample following the flow chart and microbiota at the screening. Conclusion: EPICURE is an original and longitudinal prospective biocollection of metastatic breast cancer patients. We expect answering specific scientific questions regarding metastatic disease with heterogeneous data, especially by collecting data without a priori value or links each other. Clinical trial information: NCT03958136. Funding: EPICURE is funded by the FEDER European fundings, Astra Zeneca and Lilly
Citation Format: Mathilde Colombié, Pascal Jézéquel, Mathieu Rubeaux, Jean-Sebastien Frenel, Frédéric Bigot, Valérie Seegers, Mario Campone. Feasibility of creation of a clinico-biological database: A prospective longitudinal cohort study of metastatic breast cancer patients (epicuresein) [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr OT1-20-01.