In France, there are about 7,000 such patients, or 2% to 3% of cancer cases. The results of this new work on the subject are published in the Journal of Molecular Diagnostics.

In order to find the primary tissue of a case of cancer, and thus propose the best possible treatment, doctors have to perform a battery of tests.

The Insitut Curie explains that specialised doctors “would run comprehensive medical imaging of the entire body using a scanner and PET scan,” then “conduct detailed analysis via microscope (anatomic-pathology) of samples of these metastases on the lookout for clues as to their origin.

“More recently,” doctors “would draw on molecular biology to spot mutations, particular genetic features that would point to a given organ,” but despite all these approaches lack of identification often led to patients being “treated via non-specific broad-spectrum chemotherapy.”

The deep-learning approach

Researchers at the Institut Curie have now developed a deep-learning artificial intelligence tool to “sequence all genes expressed in a tumour,” outlined Sarah Watson.

Subsequently, the AI “draws up a diagnostic classifier based on expression profiles of over 20,000 tumours and normal tissues.”

Early results are promising. The scientists submitted 48 tumours of unknown origin, and in 79% of the cases, the tissue of origin was discovered. Of the 11 patients diagnosed, 8 have already received treatment.