Human ECM-based platform for anti-cancer drug testing - CARES (CAncer dRug tESting)

Información del proyecto

CARES

Identificador del acuerdo de subvención: 101130985

DOI

10.3030/101130985

Fecha de la firma de la CE 3 Julio 2023

Fecha de inicio 1 Noviembre 2023

Fecha de finalización 31 Octubre 2027

Financiado con arreglo a

• Marie Skłodowska-Curie Actions (MSCA)

Coste total

Sin datos

Aportación de la UE

€ 276 000,00

Coordinado por

ASOCIACION CENTRO DE INVESTIGACION COOPERATIVA EN BIOCIENCIAS
Spain

Periodic Reporting for period 1 - CARES (Human ECM-based platform for anti-cancer drug testing - CARES (CAncer dRug tESting))

Período documentado: 2023-11-01 hasta 2025-10-31

Resumen del contexto y de los objetivos generales del proyecto

Cancer remains one of Europe’s greatest health challenges, causing 2 million deaths annually and imposing an economic burden of €100 billion. Despite significant progress in cancer treatments over recent decades, the success rate of new anti-cancer drugs in clinical trials remains disappointingly low. This limits the rapid and accurate development of innovative targeted therapies.

Our vision is to create a bold, cutting-edge technology that replicates the active role of the human tumour microenvironment, a key regulator of tumour initiation, growth, and progression through dynamic interactions between tumour cells and the extracellular matrix.

CARES brings together leading academic and industry experts in matrix biology, biomaterials, microfluidics, and cancer research to develop a precise tool for assessing cancer cell responses to diverse anti-cancer drugs. As a proof of concept, we will use breast cancer cells as a model system, with plans to expand to other cancer types in the future.

Our ultimate goal is to deliver a novel, user-friendly platform that mimics the tumour microenvironment at both early and advanced stages of cancer. This platform will predict, with unprecedented accuracy, how tumour cells respond to therapies in vivo. By doing so, it will accelerate drug development, improve testing, and bridge the gap between translational research and targeted treatment, thus creating a significant impact on society and the economy.

Beyond its scientific ambition, CARES will provide a foundation for intensive interdisciplinary and cross-sector training of young scientists. Participants will gain an exceptional translational research portfolio, equipping them to thrive in both academia and industry.

Trabajo realizado desde el comienzo del proyecto hasta el final del período abarcado por el informe y los principales resultados hasta la fecha

Project Progress and Implementation:

CARES is advancing according to the scientific programme, and all planned deliverables and milestones have been successfully achieved. Dissemination activities are progressing well, with a strong output in communication. This includes a broad range of actions, numerous presentations at international conferences, and several events and initiatives aimed at engaging the general public.


Scientific and Technical Achievements:

CARES focuses on defining and characterizing novel bioscaffolds to enhance the impact of drug testing in breast cancer research. The first work package employed a computational approach, resulting in the development of a shared tool for all consortium partners. This tool maps the main interactome between molecules in the extracellular matrix, with specific emphasis on the tumour matrix in the human breast. Furthermore, this information has been translated into the development of novel matrices that are being tested and characterised at different levels for the analysis of breast cancer cell activities.


Implementation Challenges and Mitigation Measures:

The implementation of secondments has been slower than initially planned, primarily due to the prioritization of developing fully functional AI tools and platforms. This has been identified as the main challenge. Mitigation measures have been implemented, and secondments are now fully underway. The consortium is confident that the progress achieved in the first work package provides a solid foundation for the next phases, ensuring the continuation and successful completion of productive secondments.

Avances que van más allá del estado de la técnica e impacto potencial esperado (incluida la repercusión socioeconómica y las implicaciones sociales más amplias del proyecto hasta la fecha)

One of the most distinctive aspects of CARES is its bottom-up approach. The most likely structure of the extracellular matrix (ECM) network in breast cancer was inferred by integrating validated ECM interactions from MatrixDB with protein staining profiles from The Human Protein Atlas (THPA), gene expression data from The Cancer Genome Atlas (TCGA), and proteomics data from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and MatrisomeDB. Progress during this reporting period has led to the publication of several articles presenting the developed tools.

To achieve this, we developed an artificial intelligence (AI)-based algorithm building on the previous MatriNet publication. This new algorithm incorporates analyses of single-cell and spatial transcriptomics datasets and introduces MatriCom—a novel cell-ECM and ECM-ECM communication algorithm. The AI model will form the next MatriNet release. To address the limitations of existing cell-cell communication algorithms in capturing ECM biology, MatriCom was developed as a dedicated tool for studying ECM-dependent communication routes in high-dimensional datasets. MatriCom has been successfully deployed and demonstrated its ability to identify ECM-specific patterns across multiple human organs and tissues.

Consortium members have leveraged this innovative approach to select potential interactors for the design and testing of new matrices. This process is ongoing and, crucially, it benefits from its iterative nature. Therefore, CARES continues to evolve through the integration of improved datasets and consortium-generated results obtained through the various analyses of breast cancer cell behaviour in the context of the newly designed matrices.

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