Machine learning improves the diagnosis of patients with head and neck cancers

ScienceDaily | 9/12/2019 | Staff
smnth28 (Posted by) Level 3
Every year, more than 17,000 people in Germany are diagnosed with head and neck cancers. These include cancers of the oral cavity, larynx and nose, but can also affect other areas of the head and neck. Some head and neck cancer patients will also develop lung cancer. "In the large majority of cases, it is impossible to determine whether these represent pulmonary metastases of the patient's head and neck cancer or a second primary cancer, i.e. primary lung cancer," explains Prof. Dr. Frederick Klauschen of Charité's Institute of Pathology, who co-led the study alongside Prof. Dr. David Capper of Charité's Department of Neuropathology. "This distinction is hugely important in the treatment of people affected by these cancers," emphasizes Prof. Klauschen, adding: "While surgery may provide a cure in patients with localized lung cancers, patients with metastatic head and neck cancers fare significantly worse in terms of survival and will require treatments such as chemoradiotherapy."

When trying to distinguish between metastases and a second primary tumor, pathologists will usually use established techniques such as analyzing the cancer's microstructure and detecting characteristic proteins in the tissue. However, due to the marked similarities between head and neck cancers and lung cancers in this regard, these tests are usually inconclusive. "In order to solve this problem, we tested tissue samples for a specific chemical alteration known as DNA methylation," explains Prof. Capper who, like Prof. Klauschen, is a Scientific Member of the DKTK in Berlin. He adds: "We know from earlier studies that DNA methylation patterns...
(Excerpt) Read more at: ScienceDaily
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