Synonymous Mutations

Not silent at all

The so-called "silent" or "synonymous" genetic alterations do not result in altered proteins. But they can nevertheless influence numerous functions of the cell and thus also disease processes. Scientists from the German Cancer Consortium, German Cancer Research Center, and the University of Freiburg have now created a comprehensive database of all synonymous mutations ever found in cancer. This is a "reference book" that provides cancer researchers with all available information on each of these supposedly "silent" mutations at a glance. Using the example of an important oncogene, the researchers show how synonymous mutations can influence the function of this cancer driver.

Deadline 15th September 2019

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Stomach and colorectal cancer

Identifying patients at an early stage who are suitable for artificial intelligence immunotherapy.

Changes in certain sections of the genetic material of cancer cells, so-called microsatellites, can provide an important indication of whether immunotherapy may be successful in a patient with stomach or colorectal cancer. Scientists from Uniklinik RWTH Aachen, the German Cancer Research Center (DKFZ), and the National Center for Tumor Diseases Heidelberg (NCT) have developed an adaptive algorithm that can predict instability in microsatellites based directly on images of tissue samples. This could help to potentially identify patients at an early stage who could benefit from immunotherapy. The research results were published in the journal Nature Medicine.

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Cancer drugs promote stem cell properties of colorectal cancer

Scientists from the German Cancer Research Center (Deutsches Krebsforschungszentrum, DKFZ) and the Mannheim University Medical Center have now discovered that a certain group of cancer drugs (MEK Inhibitors) activates the cancer-promoting Wnt signalling pathway in colorectal cancer cells. This can lead to the accumulation of tumor cells with stem cell characteristics that are resistant to many therapies and can lead to relapses. The researchers thus provide a possible explanation for why these drugs are not effective in colorectal cancer.

Glioblastoma

Fatty acid metabolism as a possible new therapeutic approach

In order to gain enough energy for their rapid growth, glioblastoma cells reprogram their fatty acid metabolism. How they do this has been unclear until now. Researchers at the German Cancer Research Center in Heidelberg have now discovered that a protein called ACBP (acyl-CoA-binding protein) enhances the transport of fatty acids into the mitochondria. This provides glioblastoma cells with the necessary energy source for their rapid growth. This discovery is not only scientifically relevant, but may also offer new therapeutic approaches for an aggressive tumor with a poor prognosis.

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DKTK

Fighting colon cancer with killer cells

Genetically modified immune cells can successfully destroy colon cancer cells. This has been demonstrated for the first time by scientists from the German Cancer Consortium (DKTK) at Georg Speyer House in Frankfurt using mini-tumors produced in the lab. They are making use of a new approach in cancer immunotherapy: genetically modified natural killer cells. Using patient-specific tumor cultures, scientists can now run tests in the lab to see how effective the killer cells will be in individual patients.

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Targeted approach to therapy for rare type of bone cancer

Chordomas are rare bone tumors for which only few options of treatment exist. Scientists and doctors from the National Center for Tumor Diseases (NCT), the German Cancer Research Center (DKFZ), and Heidelberg University Hospital (UKHD) have discovered a particular genetic trait of chordomas in advanced stages after conducting gene analysis.

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Artificial intelligence helps to better assess treatment response of brain tumors

A team from Heidelberg University Hospital and the German Cancer Research Centre has developed a new method for the automated image analysis of brain tumors. In their recent publication, the authors show that machine learning methods carefully trained on standard magnetic resonance imaging (MRI) are more reliable and precise than established radiological methods in the treatment of brain tumors. Thus, they make a valuable contribution to the individualized treatment of tumors. In addition, the validated method is an important first step towards the automated high-throughput analysis of medical image data of brain tumors.

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