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RESCUER

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RESISTANCE UNDER COMBINATORIAL TREATMENT IN ER AND ER BREAST CANCER.

Breast Cancer (BC) is the first cause of cancer-related death in women worldwide. Breast cancer is classified into well-recognized molecular subtypes. Despite solid pre-clinical evidence, only some patients benefit from administer... ver más

31/12/2025

Innovasjon Norge

6M€

Presupuesto del proyecto: 6M€

Líder del proyecto

Innovasjon Norge No se ha especificado una descripción o un objeto social para esta compañía.

Fecha límite participación Sin fecha límite de participación.

Ver 17 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2019-11-22

SC1-BHC-02-2019: Systems approaches for the discover...

I+D

Cerrada hace 6 años

0% 95% 100%

Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

17 Participantes

Innovasjon Norge

933.54K€ | Lider

BIOTECHNOLOGY INSTITUTE

449.55K€ | Participante

IFG GmbH

141.29K€ | Participante

HOSPITAL CLINIC DE BARCELONA

N.D. | Participante

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Duración del proyecto: 73 meses Fecha Inicio: 2019-11-22
Fecha Fin: 2025-12-31

Líder del proyecto

Innovasjon Norge No se ha especificado una descripción o un objeto social para esta compañía.

Presupuesto del proyecto 6M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Breast Cancer (BC) is the first cause of cancer-related death in women worldwide. Breast cancer is classified into well-recognized molecular subtypes. Despite solid pre-clinical evidence, only some patients benefit from administering drug combinations, an indication that patient and tumor heterogeneity is still present in the current stratification. Out of the numerous possible combinations of approved drugs, only a few have been actually tried, and the choice of tested combinations has been to some degree arbitrary. This proposal seeks to develop new approaches and identify mechanisms of treatment resistance at systems level, exploring how the effectiveness of specific targeted therapies applied in different clinical trials is affected by patient- and tumor-specific conditions. For this purpose, the project will gather and integrate longitudinal multidimensional data from ongoing clinical trials and newly generated --omics using systems approaches, which combine sub-cellular/cellular and/or organ level in-silico models and network analysis to build computational frameworks able to discover molecular signatures of resistance and predict patient response to combinatorial therapies. We aim to identify the physiological characteristics of non-responders vs. responders from existing and newly generated multi-omic data and biological samples from in-vivo and ex-vivo clinical studies of specific subtypes of BC patients treated with combination therapy. This new knowledge will be used to investigate the curative potential of new personalized drugs combinations. The overreaching goal is to develop computer xenograft model as a cost-efficient and better alternative in terms of ethics, availability to everyone, and animal use. The framework will include optimization algorithms to identify combinations of approved drugs with a high probability to work on individual or thin strata of patients. The project is endowed with a legal framework addressing ethical aspects

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