Silent mutations may predict cancer development – study



Groundbreaking Tel Aviv University research is able to predict both a patient’s cancer type and likelihood of survival based on silent mutations in cancer genomes – a proof of concept that is likely to save lives. lives in the future.

Silent mutations are defined as those which do not alter the sequence of amino acids in proteins. According to TAU, in recent years, they have been shown to affect the expression of genes both in and outside the cell’s genetic coding region and may be linked to the development and spread of cancer cells. However, the question of whether silent mutations can help identify types of cancer or predict patients’ chances of survival has never been studied before with quantitative tools.

In the new study, which examined around three million mutations in the cancer genomes of 9,915 patients, researchers attempted to identify the type of cancer and predict the likelihood of survival 10 years after initial diagnosis based on only silent mutations. They found that the predictive power of silent mutations is often similar to that of “ordinary”, non-silent mutations.

In addition, they found that by combining the information from the classification of silent and non-silent mutations, 68% of cancer types could be improved and that the best estimates of survival could be obtained for up to nine years after diagnosis. In some types of cancer, the classification was improved by up to 17%, while the prognosis was improved by up to 5%.

To test their hypothesis and quantify the effect of silent mutations, the researchers used public genetic information on cancer genomes from the National Institute of Health in Bethesda, Maryland. By analyzing the data with machine learning techniques, they obtained predictions of the type of cancer and prognoses for patient survival based on silent mutations, then they compared their results with real data from the database. data.

The results of the study, led by TAU’s Department of Biomedical Engineering and the Zimin Institute for Engineering Solutions Advancing Better Lives, were published in NPJ genomic medicine. The implications of the study will be used in various areas of oncology research.
Cancer cells forming a mass in pancreatic tissue (Credit: WIKIMEDIA COMMONS / SCIENTIFIC ANIMATIONS INC.)

Professor Tamir Tuller, who led the study, noted that the genetic material of cells contains two types of information: the sequence of amino acids to be produced, as well as when and how much of each protein to be produced. namely the regulation of production. to treat.

“Even if they don’t change the structure of the protein, silent mutations can influence the process of protein production (gene expression), which is just as important,” Tuller said. “If a cell produces much smaller amounts of a certain protein, it’s almost as if the protein has been completely removed.

Another important aspect, which can also be affected by silent mutations, is the 3D folding of the protein, which has an impact on its functions, ”he said. “Proteins are long molecules usually made up of several hundred amino acids, and their folding process begins when they are produced in the ribosome. Folding can be affected by the rate at which the protein is produced, which in turn can be affected by silent mutations.

“Plus, in some cases, silent mutations can impact a process called splicing, in which pieces of genetic material are cut and rearranged to create the final sequence in the protein,” Tuller said. “In short, it appears that silent mutations can actually make a lot of noise, and in this study we were able to quantify their impact for the first time.”

The professor explained that our genome, like the genome of all other living things, contains mutations that can alter the sequence of amino acids in encoded proteins. “Since these proteins are responsible for various cellular mechanisms, such mutations are involved in the transformation of healthy cells into cancer cells. Other mutations, which do not affect amino acids, have been called “silent” and ignored for many years.

“In our study, approximately 10,000 cancer genomes of each type were analyzed, demonstrating for the first time that silent mutations have diagnostic value in identifying the type of cancer, as well as prognostic value in predicting how long the patient is likely to survive. “


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