Researchers have developed imaging technology to create an individualised 'fingerprint’ that can be used to assess the prognosis and treatment response to head and neck cancers.

Head and neck cancers have increased considerably in the last 30 years. In the UK, around 12,200 people are diagnosed with head and neck cancer annually, according to Macmillan.

The researchers from the University of Helsinki, in collaboration with the University of Turku and the Max Planck Institute for Molecular Biomedicine in Germany, used a method based on machine learning and analysed hundreds of biobank patient samples at the level of accuracy of individual cells.

The study's most significant finding was the development of an imaging analysis technique that combined analyses of biomarkers of cell behaviour with morphological analyses of single-cell shape and the structure of the entire tumour tissues.

Sara Wickström, research director, said, “These results are a breakthrough in understanding cancer development and diagnostics. For the first time, we have shown that specific combinations of malignant cells and tissue cell types in what is considered healthy tissue have a strong prognostic effect on cancer progression.

“In addition, we identified a key signalling pathway that explains this compound effect and which can be pharmacologically targeted, consequently significantly affecting the progression of the cancer.”

The study

The method enabled the identification of two previously undetected groups of patients. The prognosis for the first group was exceptionally good, while for the second, it was exceptionally bad. The difference was explained by combining a specific cancer cell state and the tissue composition surrounding the cancer cells. In the latter group, the aggressiveness of the disease was associated with signalling between cancer tissue and surrounding healthy connective tissue mediated by the epidermal growth factor (EGF).

Karolina Punovuori, a postdoctoral researcher for Wickström’s research group, said, “In addition, our method was able to identify patients with a particularly poor prognosis who would benefit from an aggressive treatment strategy. On the other hand, we also identified a group of patients whose prognosis was good and for whom a less aggressive treatment, such as a surgical procedure alone, could be sufficient. This would help preserve patient quality of life.”

Diagnostic test under development

The imaging method opens the door for precision diagnoses of cancers in the head and neck area. The researchers are developing a diagnostic test for a more accurate diagnosis of this type of cancer. In addition, they are also studying the use of the method in the diagnostics of other types of cancer and have received funding.

Sara said, “Our research utilises the latest analysis methods in machine learning and spatial biology. We analyse hundreds of patient samples and millions of cells, which is only possible with the help of high-performance computers and artificial intelligence. This study is part of a new revolution in cancer diagnostics. We believe that the technology will significantly improve cancer diagnostics and the accuracy of treatment strategies.

She concluded, “Imaging of cancer biomarkers using antibody stainings is already in clinical use. Therefore, the method will not be particularly expensive, since it only requires the algorithm developed by us and a special combination of antibodies. Considering the cost of cancer treatment, this is quite affordable.”

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