In most cancer cases, doctors can quickly identify the source of the disease, such as cancer of the liver or lungs. However, in approximately 1 in 20 cases, the doctor can confirm that the patient has cancer but cannot find the source. These patients then face the prospect of a long wait with numerous diagnostic tests and attempts to locate the origin of the cancer before starting any treatment.

Now, researchers at DTU Systems Biology in Lyngby, Denmark, have combined genetics with computer science and created a new diagnostic technology based on advanced self-learning computer algorithms. On the basis of a biopsy from a metastasis, these algorithms can identify the source of the disease with 85% certainty, and thus target treatment and, ultimately, improve the prognosis for the patient. Their research was reported in BMC Medical Genomics (2015; doi:10.1186/s12920-015-0130-0).

Many people with cancer face the prospect of a long wait until their cancer has been diagnosed and its source located. However, even after very extensive tests, the origin of the cancer still cannot be found in 2% to 3% of patients. In such cases, the patient is treated with a cocktail of chemotherapy instead of a targeted treatment that could be more effective and gentler on the patient.

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The newly developed method, which researchers are calling TumorTracer, are based on analyses of DNA mutations in cancer tissue samples from patients with metastasized cancer.

The pattern of mutations is analyzed in a computer program that has been trained to find possible primary tumor localizations. The method was tested on many thousands of samples where the primary tumor was already identified, and it has proven extremely precise. The next step will be to test the method on patients with unknown primary tumors. In recent years, researchers have discovered several ways of using genome sequencing of tumors to predict whether an individual patient with cancer will benefit from a specific type of medicine.

“We are very pleased that we can now use the same sequencing data together with our new algorithms to provide a much faster diagnosis for cancer cases that are difficult to diagnose, and to provide a useful diagnosis in cases which are currently impossible to diagnose,” said Associate Professor Aron Eklund, PhD, of DTU Systems Biology. “At the moment, it takes researchers 2 days to obtain a biopsy result, but we expect this time to be reduced as it becomes possible to do the sequencing increasingly faster. And it will be straightforward to integrate the method with the methods already being used by doctors.”

Researchers expect that, in the long term, the method can also be used to identify the source of free cancer cells from a blood sample, and thus also as an effective and easy way of monitoring people who are at risk of developing cancer.