Understanding cancer through the lens of dynamic Spatial Hallmark Ecosystems

Researchers at the Instituto de Investigación contra la Leucemia Josep Carreras have proposed a new conceptual framework that views cancer as a dynamic ecosystem of tumor characteristics.

This new perspective, developed by researchers Mustafa Sibai and Eduard Porta together with international teams, combines advanced technologies such as spatial single-cell analysis with classical approaches like genomics and proteomics. The goal is to move beyond the traditional view of cancer as a static process and toward a more complex, dynamic, and phenotype-based model.

For decades, cancer has been studied mainly from a genetic perspective, focused on identifying mutations responsible for the disease. While this approach has led to major advances, it has also generated vast amounts of data that are difficult to integrate. In this context, the concept of “Hallmarks of Cancer” has gained prominence, describing the functional capabilities that tumor cells must acquire to become malignant.

However, this model still relies on a static view of the disease. The new proposal introduces the concept of Spatial Hallmark Ecosystems, which allows cancer to be understood as a system in constant evolution, where cells interact with each other and with their environment over time.

“Cancer cells are not static representations of malignancy, but dynamically interact with their surrounding microenvironment,” explains Mustafa Sibai. From this perspective, it is not only important to understand what the tumor is doing, but also where and when these changes occur.

This approach helps answer questions that the traditional view could not fully explain. For example, why premalignant states can show cells with critical mutations without the presence of a visible tumor. According to this model, this may be because the tumor ecosystem has not yet reached a critical threshold in its functional properties.

Understanding how different cell populations interact within a tumor opens new possibilities for clinical practice. This knowledge could enable clinicians to anticipate disease progression and intervene earlier, before cancer fully develops, thereby expanding treatment opportunities.

In the coming months, this model will be validated using real-world data from large patient cohorts. As it evolves, it may help clinicians better understand tumors and guide treatment decisions more precisely, focusing not only on specific genes but on tumor ecosystems and their changes.

In addition, integrating these approaches with large-scale data analysis and artificial intelligence will enable the development of more sophisticated biomarkers, capable of capturing the true complexity of tumors and helping identify the most appropriate treatment for each patient.

At the Josep Carreras Foundation, we continue to support research that opens new avenues of knowledge and brings us closer to more precise, personalized, and effective cancer care.