COST Action bridges the gap in cancer immunotherapy research
Cancer is still a leading cause of death worldwide. Globally, there were an estimated 20 million new cases of cancer and 10 million deaths. The burden will continue to grow globally by nearly 60% over the next two decades. The direct consequence will exert physical, emotional, and financial strain on individuals, families, communities, and the health system.
Groundbreaking progress in cancer treatment through immunotherapy is evident in remarkable outcomes, particularly in previously untreatable cancers like metastatic melanoma. Despite these successes, the widespread use of these treatments faces challenges due to their limited effectiveness and associated side effects.
To overcome these hurdles and make immunotherapies safer and more effective, it is crucial to deepen our understanding of the intricate interactions between cancer cells and the immune system. One major roadblock in this research is the shortage of accurate preclinical models that faithfully mimic human immunity. These models are essential for identifying new therapeutic targets, understanding biomarkers for treatment response and side effects, and generating reliable data on how different drugs can work together.
Introducing COST Action IMMUNO-model
Studying and understanding the complexity of the immune response in the context of cancer immunotherapy requires strong communication between immunologists and cancer researchers. This collaboration is essential for crafting and advancing new protocols and strategies that can effectively tackle the lingering questions in the field of cancer immunotherapy.
Therefore, more research in this field is needed, because standardized pre-clinical models are lacking to further investigate these mechanisms and causes of resistance.
To address this challenge, the COST Action Modelling immunotherapy response and toxicity in cancer (IMMUNO-model) established a network of researchers involved in the development and implementation of experimental models. By exploring the cause of resistance, the aim is to increase the quality of life and the survival rate of patients.
We aim to bring together clinical and basic researchers, industry, patients and other key stakeholders to improve and translate preclinical designs quickly and efficiently, helping us to bring immunotherapy to as many patients as possible.“
Dr Eva Martinez-Balibrea, Chair of IMMUNO-model
IMMUNO-model currently brings together more than 250 researchers and scientists representing 28 countries, from diverse backgrounds and disciplines ranging from basic to clinical-oriented research, including academia and industry. This COST Action was launched in November 2022 with the common goal of establishing a network of scientists that endorses immune-oncology research by promoting, sharing, and standardising applications of immunotherapy preclinical models.
IMMUNO-model articulates its work through five working groups, each with its aims and activities. The results will be then shared to provide improved tools for immunotherapy research to reach a stronger impact on cancer patient’s life. “IMMUNO-model is a compound of five Working Groups focusing on a broad range of in vitro, ex vivo and in vivo model for solid and hematologic tumours as well as in the communication of our activities within the Action” adds Dr Laura Belver, Working Group leader.
To better understand the complexity, the IMMUNO-model released a video ‘Discover how preclinical models will boost immunotherapy for cancer.
The network’s collaborative efforts, orchestrated through the Working Groups, are poised to yield impactful results. The focus on a diverse array of experimental models, as encapsulated in IMMUNO-model, underscores our comprehensive approach. The forthcoming sharing of outcomes is anticipated to furnish advanced tools for immunotherapy research.
The ultimate aim of this Action is to contribute to translating novel scientific discoveries into benefits for cancer patients and society. The results will be important benefits in the clinic, as the knowledge generated will provide essential experimental evidence to support the design of new clinical trials. This will in turn increase their probability of success and result in a direct impact on the quality of life and survival of cancer patients.
