Lung cancer remains one of the leading causes of cancer-related deaths in Europe and worldwide. The introduction of immunotherapies for Non-Small Cell Lung Cancer (NSCLC) (treatments that help the body’s own immune system attack cancer cells more effectively) has marked a major advance in cancer care and offered new hope to patients. However, only a minority of patients experience long-term benefits from these immunotherapies, as many develop resistance or do not respond at all. This challenge highlights a critical need: we currently lack reliable tests (known as biomarkers) that can show in advance which patients are likely to benefit from immunotherapy. As a result, many individuals receive treatments that may not help them, leading to unnecessary side effects and costs.
To address this, we need to better understand the complex biological processes that drive resistance to immunotherapy in NSCLC. In particular, it is essential to study the tumour microenvironment (the dynamic community of cancer cells, immune cells, and other surrounding cells) which plays a key role in how tumours evade the immune system.
Traditional research often focuses on single cell types or molecular pathways, missing the bigger picture of how different cells interact within the tumour. SPACETIME takes a new approach by studying these cells both through space and time. “Space” refers to mapping where different types of cells are located within the tumour and how they are organized in relation to each other. “Time” means examining how these cellular neighborhoods change as the cancer develops and progresses. By bringing together international experts in spatial biology, computational science, and clinical research, SPACETIME aims to map the spatial organization and evolution of tumours and their immune environments. The project focuses on KRAS-mutant and driver-negative lung adenocarcinoma, two subtypes of NSCLC with poor prognosis and limited treatment options.
Specifically, the SPACETIME consortium will 1) Map the spatial and molecular landscape of lung tumours and their microenvironment, and how they change over time, 2) Study how the tumor environment interacts with the whole body and lifestyle factors to find risks, 3) Discover how these patterns affect the immune system and treatment options, 4) Make all data and tools openly available for others to use and build on, 5) Develop clear, practical guidelines for a future test to help doctors predict and treat lung cancer better.
To achieve these goals, SPACETIME will employ state-of-the-art techniques—including high-resolution spatial imaging, multi-omics molecular profiling, and advanced computational analysis—on both patient tumour samples and carefully designed laboratory models that closely mimic human lung cancer. By combining data from real patient tissues and innovative mouse models, the project will capture the full complexity of tumour and immune cell interactions as they occur in the body.
SPACETIME is expected to generate significant impact across multiple domains. SPACETIME will deliver new predictive markers and spatial models validated in patient samples. By actively involving patients, clinicians, policymakers, and the public, the project ensures that its results are relevant, ethically sound, and ready for real-world application. In doing so, SPACETIME paves the way for more precise and effective lung cancer care, enabling better patient selection for immunotherapy, reducing unnecessary treatments, and supporting truly personalized medicine, while bridging the gap between molecular discovery, clinical practice, and societal benefit.
