Research on cancers of unknown primary

Clinical Research

Few clinical trials are dedicated specifically to cancers of unknown primary, due to the heterogeneity of these tumors and the difficulty of identifying treatments applicable to all patients. However, two international clinical trials have demonstrated the value of in-depth molecular characterization to guide CUP treatment. These trials are now closed.

CUPISCO: This trial evaluated the benefit of targeted therapy based on the identification of actionable molecular alterations in CUP. The CUPISCO trial showed that, for patients whose tumors harbor targetable alterations, personalized targeted therapy is more effective than chemotherapy. These results highlight the importance of systematically searching for actionable molecular alterations in CUP. 

Fudan CUP-001 trial: This trial assessed the benefit of chemotherapy guided by the likely tissue of origin, as determined by a molecular test. It demonstrated that, when the tissue of origin could be identified, tissue-guided chemotherapy was more effective than broad-spectrum chemotherapy. Fudan CUP-001 trial supports the value of molecular approaches used within the national CUP MCM.  

To date, no clinical trials specifically dedicated to CUP are currently open in France. However, some trials designed for other cancer types may be suitable for CUP patients and may be recommended by the MCM.

Scientific Research

The NET-CaPI group is involved in several research projects aimed at improving understanding of the disease and optimizing diagnostic and therapeutic strategies for cancers of unknown primary.

The group recently developed an artificial intelligence tool, TransCUPtomics, designed to identify the tissue of origin of CUP based on molecular profiles. This tool was trained on more than 20,000 tumor and normal tissue samples and can distinguish the molecular “identity cards” of several hundred cancer subtypes.

When applied to CUP molecular profiles, TransCUPtomics can predict the tissue of origin in 70–80% of cases. The tool is available within the national CUP MCM, where AI-generated predictions are integrated with clinical, pathological, and molecular data to achieve the most accurate diagnosis possible.

New AI tools combining multiple data types (imaging and molecular data) are currently under development to further improve diagnostic performance.

Other NET-CaPI research projects focus on specific CUP subtypes. As with all rare diseases, collecting and analyzing patient data is essential to improve knowledge and care. The national MCM has enabled the creation of a multimodal database to support research projects. Using this resource, the group provided the first in-depth characterization of a cohort of CUP cases of presumed renal origin and demonstrated the benefit of treatment tailored to this origin. Additional projects are underway, including collaborations with the IHU Institute of Women’s Cancers.