Summary
Our genome contains 20 000 genes, which are transcribed into mRNAs. These mRNAs are then in turn translated into proteins that exert the cellular functions. In the past decade, researchers have analysed the genetic sequence of all protein coding genes in thousands of tumor samples, with the aim to identify gene defects (‘mutations’) that cause cancer. In most of these studies, only gene mutations that cause amino acid changes in the proteins for which they encode were analysed, and it was assumed that mutations that do not cause amino acid changes (=synonymous or silent mutations) are innocent and meaningless events in cancer pathogenesis.
Despite the fact that synonymous mutations have thus largely been ignored by cancer researchers, there are a couple of synonymous mutations that have been shown to promote cancer. This happens via highly novel and poorly understood mechanisms of gene expression dysregulation that occur at the level of gene transcription to mRNA or at the level of translation of the mRNA into protein. Since the role of synonymous mutations in cancer has not been systematically explored so far, and since there is thus evidence that these mutations are not as ‘silent’ and innocent as many people think, we hypothesized that the pathogenic role of synonymous mutations in cancer is largely underestimated. First, we will delineate the landscape of synonymous driver mutations in cancer. For this purpose, we will develop bioinformatics and statistics approaches to identify relevant synonymous mutations in previously generated sequence data from 11 400 tumor samples. Furthermore, we will apply in silico methods to rank identified mutations and filter out the mutations that are predicted to most efficiently promoting cancer. For 50 of the mutations that are predicted to be pathogenic, we will perform wet lab experimental testing of their capacity to alter gene expression level and to promote cancer cell behavior. Special attention will go to mutations that affect poorly characterized mechanisms to regulate the efficiency of protein translation of the mutated gene, because our lab has a strong expertise in this field. Results from this project may also be relevant for more classical non-synonymous mutations, because the novel modes of gene expression regulation we will discover might also be relevant for such mutations, and the project may thus have broad very implications in the cancer field.
Synonymous mutations are currently difficult to find for researchers. We will make these mutations visible via a public website and we will make the methodology we develop in this project available to the research community. This project will thus give silent synonymous mutations a voice through their first comprehensive characterization in cancer.
Despite the fact that synonymous mutations have thus largely been ignored by cancer researchers, there are a couple of synonymous mutations that have been shown to promote cancer. This happens via highly novel and poorly understood mechanisms of gene expression dysregulation that occur at the level of gene transcription to mRNA or at the level of translation of the mRNA into protein. Since the role of synonymous mutations in cancer has not been systematically explored so far, and since there is thus evidence that these mutations are not as ‘silent’ and innocent as many people think, we hypothesized that the pathogenic role of synonymous mutations in cancer is largely underestimated. First, we will delineate the landscape of synonymous driver mutations in cancer. For this purpose, we will develop bioinformatics and statistics approaches to identify relevant synonymous mutations in previously generated sequence data from 11 400 tumor samples. Furthermore, we will apply in silico methods to rank identified mutations and filter out the mutations that are predicted to most efficiently promoting cancer. For 50 of the mutations that are predicted to be pathogenic, we will perform wet lab experimental testing of their capacity to alter gene expression level and to promote cancer cell behavior. Special attention will go to mutations that affect poorly characterized mechanisms to regulate the efficiency of protein translation of the mutated gene, because our lab has a strong expertise in this field. Results from this project may also be relevant for more classical non-synonymous mutations, because the novel modes of gene expression regulation we will discover might also be relevant for such mutations, and the project may thus have broad very implications in the cancer field.
Synonymous mutations are currently difficult to find for researchers. We will make these mutations visible via a public website and we will make the methodology we develop in this project available to the research community. This project will thus give silent synonymous mutations a voice through their first comprehensive characterization in cancer.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/862246 |
| Start date: | 01-05-2020 |
| End date: | 31-01-2026 |
| Total budget - Public funding: | 1 999 977,00 Euro - 1 999 977,00 Euro |
Cordis data
Original description
Our genome contains 20 000 genes, which are transcribed into mRNAs. These mRNAs are then in turn translated into proteins that exert the cellular functions. In the past decade, researchers have analysed the genetic sequence of all protein coding genes in thousands of tumor samples, with the aim to identify gene defects (‘mutations’) that cause cancer. In most of these studies, only gene mutations that cause amino acid changes in the proteins for which they encode were analysed, and it was assumed that mutations that do not cause amino acid changes (=synonymous or silent mutations) are innocent and meaningless events in cancer pathogenesis.Despite the fact that synonymous mutations have thus largely been ignored by cancer researchers, there are a couple of synonymous mutations that have been shown to promote cancer. This happens via highly novel and poorly understood mechanisms of gene expression dysregulation that occur at the level of gene transcription to mRNA or at the level of translation of the mRNA into protein. Since the role of synonymous mutations in cancer has not been systematically explored so far, and since there is thus evidence that these mutations are not as ‘silent’ and innocent as many people think, we hypothesized that the pathogenic role of synonymous mutations in cancer is largely underestimated. First, we will delineate the landscape of synonymous driver mutations in cancer. For this purpose, we will develop bioinformatics and statistics approaches to identify relevant synonymous mutations in previously generated sequence data from 11 400 tumor samples. Furthermore, we will apply in silico methods to rank identified mutations and filter out the mutations that are predicted to most efficiently promoting cancer. For 50 of the mutations that are predicted to be pathogenic, we will perform wet lab experimental testing of their capacity to alter gene expression level and to promote cancer cell behavior. Special attention will go to mutations that affect poorly characterized mechanisms to regulate the efficiency of protein translation of the mutated gene, because our lab has a strong expertise in this field. Results from this project may also be relevant for more classical non-synonymous mutations, because the novel modes of gene expression regulation we will discover might also be relevant for such mutations, and the project may thus have broad very implications in the cancer field.
Synonymous mutations are currently difficult to find for researchers. We will make these mutations visible via a public website and we will make the methodology we develop in this project available to the research community. This project will thus give silent synonymous mutations a voice through their first comprehensive characterization in cancer.
Status
SIGNEDCall topic
ERC-2019-COGUpdate Date
27-04-2024
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