Specific gene predicts higher chance of surviving prostate cancer

23/04/2020 cancer, chance, gene, higher, of, predicts, prostate, Specific, surviving

According to Statistics Austria about 5,600 men are diagnosed with prostate cancer in Austria every year, meaning it accounts for roughly a quarter of all cancers in men. For some the cancer develops slowly and requires minimal treatment, but others have aggressive forms of the disease which progress very quickly. In order to be able to treat prostate cancer more effectively, better understanding of the complex mechanisms that occur at the molecular level within the tumor is needed. In 2015, a team led by molecular pathologist Lukas Kenner of MedUni Vienna made the unexpected discovery that the protein STAT3 plays a tumor-suppressing role in prostate cancer using a mouse model. They showed that the progression of the disease was significantly worse in patients with low STAT3 levels in cancer cells, compared to patients with high levels.

These findings served as the starting point for a recent study conducted by Monika Oberhuber, a doctoral candidate in Kenner’s team at MedUni Vienna’s Department of Pathology, together with the Center for Biomarker Research in Medicine, a COMET Competence Center with funding from the Austrian Research Promotion Agency (FFG). The study analyzed numerous large patient data sets and compared patients with high and low expression of STAT3 in tissue.

This led to the identification of correlations between the expression characteristics of different gene clusters. The researchers discovered that patients with low STAT3 have a highly active metabolism. Metabolism—especially cellular respiration—is much more active in prostate tumors than in healthy prostate tissue. This gives the tumor additional energy to grow. Patients with low STAT3 exhibit higher cellular respiration and more active tumors, in which many new proteins form.

Oberhuber also investigated the relationship between low STAT3 and an active metabolism using paraffin-embedded tissue sections. The tumor tissue was separated from the healthy tissue with a laser microscope and then analyzed using mass spectrometry.

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