Cancer of unknown primary (CUP) is a heterogeneous disease that comprises approximately 2-8% of all cancer cases in the world. It is defined by the presence of metastatic disease with no identified primary tumor at presentation using established diagnostic tools, based on imaging and immunohistochemistry. The outcome is extremely poor, in part due to lack of knowledge of which is the most suitable treatment. This scenario makes clear the need to make progress in the development of effective prediction tools and therapies. In the scenario of a previous ERC PoC project, our group developed EPICUP, an epigenetic-based tool capable of predicting CUP tissues of origin, which was licensed and commercialized by the pharmacology company Ferrer Advanced Biotherapeutics and is currently used in CUP diagnostics.
Personalized oncology is one of the major goals of the current approaches based on high-throughput techniques for molecular characterization. Using existing molecular platforms, CUP diagnostic accuracy has increased, leading to the identification of the tumor of origin in more than 80% of metastases initially diagnosed as CUP. Despite the need to demonstrate its effectiveness in prospective randomized studies, the benefit to patient survival of determining the origin of these orphan metastases has been reported. Moreover, the identification of the best antineoplasic treatment and the status of actionable targets for existing drugs will be crucial to open new therapeutic options for these patients. In this sense, the identification of more effective tailored therapies would represent a greater milestone for management of this type of neoplasm.
The innovative idea behind the EPIPHARM (EPIgenetics of PHARMacogenetics) project is to develop a package demonstrating the feasibility of a high-throughput tool for epigenotyping Cancer of Unknown Primary (CUP) to identify a chemosensitive profile based in the DNA methylation profile. We have developed an affordable technology that permits the prediction of chemoprofiles in CUP cases, taking the prediction of the tissue of origin into account. We have involved the use of the DNA methylation profiles of human cancer cell lines of 8 different tumor types, and tested for more than 100 drugs. The classification of cell lines, as sensitive and resistant for each drug in the panel (based on the IC50 values) was followed by of the identification of CpGs that distinguish both groups by using bioinformatic algorithms. Once the EPIPHARM algorithm described herein has been successfully validated in independent in vitro models, its real value to predict chemosensitivity in CUP patients is being assessed using CUP-derived tumours implanted in an orthotopic manner in nude mice. To date, we have included 9 CUP cases in the study whose tumours were implanted in mice. From them, 3 have been grown, are available and drug testing are in process. In these cases, EPIPHARM algorithm is based in site of origin predicted by EPICUP and drugs available into the clinics for this tumor type. In this line and with the aim to detect actionable targets for the administration of targeted therapies, a bioinformatic tool has been developed, allowing us to identify relevant mutation profiles using NGS. The presence of actionable targets could allow the inclusion of CUP cases in "basket trials, an important chance of treatment for these patients for which clinical studies are not available.
In the context of immunotherapy, in a study recently published in Lancet Respiratory Medicine, we identified an epigenetic signature (EPIMMUNE), which is capable to predict which patients are most likely to benefit from anti-PD-1 agents. This signature was identified in non-small cell lung cancer, neoplasia that represents the origin of 27% of CUP cases finally diagnosed, leading to important treatment opportunity for these patients.
The EPIPHARM project aims to optimize the tailored treatment in CUP cases, especially for which the origin has been identified using molecular platforms. The existing therapeutic options are unspecific and this explains why, to date, this group of patients has an extremely poor overall survival. In this sense, it will provide oncologist with a unique tool that can be used to achieve a match-up between the epigenomic profile and the most suitable drug, allowing a more accurate treatment and a personalized medicine.
Regarding socioeconomic impact, EPIPHARM is a new potential tool that, together with molecular diagnostic platforms used, supposes to be advancement in the clinical outcome of cases firstly diagnosed as CUP. In this sense, the physician could optimize managing of disease administering the most suitable therapy and leading to better longevity and quality of life for patients. Moreover, the administration of suitable treatment would reduce unnecessary toxicities and associated hospitalization costs, optimizing the economic impact in Health System.
