Periodic Reporting for period 2 - SILENT (Silent mutations in cancer)
Période du rapport: 2021-11-01 au 2023-04-30
Our genome contains 20 000 genes, which are transcribed into mRNAs. These mRNAs are then in turn translated into proteins that exert 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 the 77% of gene mutations that cause amino acid changes in the proteins for which they encode were analysed, and it was assumed that the 23% of 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 36 059 tumor samples. Furthermore, we will apply bioinformatic methods to rank identified mutations and filter out the mutations that are predicted to most efficiently promoting cancer. For mutations that are predicted to be highly pathogenic, we will perform wet lab experimental testing of their capacity to alter gene expression level and to promote cancer cell behaviour. 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 very broad 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 36 059 tumor samples. Furthermore, we will apply bioinformatic methods to rank identified mutations and filter out the mutations that are predicted to most efficiently promoting cancer. For mutations that are predicted to be highly pathogenic, we will perform wet lab experimental testing of their capacity to alter gene expression level and to promote cancer cell behaviour. 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 very broad 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.
The first project objective aims to analyze publically available cancer genomics datasets in order to identify synonymous mutations with a high potential to be involved in cancer pathogenesis. Sequencing data from 36 059 tumor samples, corresponding to 19 different tumor types, have been screened for synonymous mutations that may be of interest using an in house developed bioinformatics pipeline that identifies the mutations and allows to predict the likeliness that these mutations will be pathogenic. This part of the project has almost been completed and has resulted in a shortlist of mutations that we would like to experimentally test in our wet lab.
In the second objective, a website will be built where the results from the first objective will be made available to the research community and a bioinformatic package will be developed that allows other researchers to apply the methodology that we developed on other datasets. This objective will be initiated once the first objective has been completely finalized.
In the third objective, mutations of interest identified in the first objective will be tested in the laboratory experiments for their effects on gene expression and cancer cell behavior. Testing for 7 mutations has been initiated, and clear effects of synonymous mutations on gene expression have been documented now for 2 mutations. Analysis of effects on cell behavior are ongoing.
In the final project objective, we aimed to explore how a well-known non-synonymous mutation in a major leukemia oncogene affects secondary RNA structure and in this way may promote gene expression and leukemia development. When starting this project, we had obtained very promising results for this part of the project, which needed further validation. These validation experiments have been performed but unfortunately did not results in confirmation of the initial results. We have decided to stop this objective for now and invest more in the very promising results that we have obtained so far for the first and third project objectives.
In the second objective, a website will be built where the results from the first objective will be made available to the research community and a bioinformatic package will be developed that allows other researchers to apply the methodology that we developed on other datasets. This objective will be initiated once the first objective has been completely finalized.
In the third objective, mutations of interest identified in the first objective will be tested in the laboratory experiments for their effects on gene expression and cancer cell behavior. Testing for 7 mutations has been initiated, and clear effects of synonymous mutations on gene expression have been documented now for 2 mutations. Analysis of effects on cell behavior are ongoing.
In the final project objective, we aimed to explore how a well-known non-synonymous mutation in a major leukemia oncogene affects secondary RNA structure and in this way may promote gene expression and leukemia development. When starting this project, we had obtained very promising results for this part of the project, which needed further validation. These validation experiments have been performed but unfortunately did not results in confirmation of the initial results. We have decided to stop this objective for now and invest more in the very promising results that we have obtained so far for the first and third project objectives.
Whereas the recognition of the pathogenic role of synonymous mutations in cancer is starting, we hypothesize that the role of synonymous mutations in cancer is still underestimated. The previous studies that have been performed in this field suffer from a number of limitations, which we will try to resolve in this project in order to generate a more complete picture of pathogenic synonymous mutations in cancer. Most of the previous studies are based on bioinformatic computer analyses and in such studies very little or no mutations have been experimentally tested in a laboratory. In this project, we will use a combination of bioinformatic tools to identify the best candidate synonymous mutations that may be pathogenic in cancer and we will move on to wet lab testing of their role in cancer pathogenesis. Such a multi-disciplinary approach combining bioinformatic tools and wet lab experimental strategies is novel and the gain of it will be enormous as it will contribute to a better mapping of biologically relevant synonymous mutations, which represents a high clinical need. Indeed, next generation sequencing mutation analysis of tumor samples has become part of standard diagnostic workflows in the clinic, but synonymous mutations that are detected are typically discarded in these analyses as their relevance has not been extensively characterized. In this way, mutations that may be relevant for cancer pathogenesis and drug sensitivity are currently disregarded in clinic. With our work, we aim to convince clinicians and researchers that synonymous mutations should not be standardly discarded and we want to provide tools to identify clinically relevant synonymous mutations.