DNA mutations driving cancer development are caused by different mechanisms, each of them leaving behind specific patterns, or “scars” in the genome. Using CRISPR-Cas9 technology, researchers at CeMM and the Wellcome Trust Sanger Institute at Cambridge, UK were able to show for the first time in cell culture that specific genetic alterations indeed lead to the predicted pattern of mutational signatures observed in human cancers. The results were published in Nature Communications (DOI: 10.1038/s41467-018-04052-8).
When a cell develops into a tumor, something has gone terribly wrong: the uncontrolled growth, invasion of nearby tissues and finally metastasis are the result of many consecutive DNA mutations. Such an accumulation of demolished genetic material often derives from initial environmental exposures, enzymatic activities or defects in DNA replication or DNA repair mechanisms. Each of those initial mutagenic conditions creates their own pattern of DNA damage called mutational signature. Deciphering them could theoretically allow us to trace back the initial cause of a tumor, profile its properties and help find a therapeutic strategy.
However, reading those mutational signatures in tumor samples is a difficult task, as the large amount of mutations that a patient acquires during its lifetime create a noisy and uncontrolled system – even the best clinical data will, at most, provide only associations. Therefore, the group of Joanna Loizou, Principal Investigator at CeMM in collaboration with researchers from the Wellcome Trust Sanger Institute, developed an experimental setup to validate the concept of mutational signatures in cell culture.
The findings of this study not only confirm an analytical principle that describes mutational processes and cancer development, mutational signatures are a direct mechanistic read-out of specific dysfunctions of a cell. Thus, even if the underlying gene defect is unknown, mutational signatures could be used as biomarkers for the molecular characterization of tumors – a new diagnostic tool to improve the precise and personalized treatment of cancer.
Xueqing Zou*, Michel Owusu*, Rebecca Harris, Stephen P. Jackson, Joanna I. Loizou#, Serena Nik-Zainal# (*These authors contributed equally to this work # Corresponding authors). Validating the concept of mutational signatures with isogenic cell models. Nature Communications 9, 2018. DOI: 10.1038/s41467-018-04052-8.
The study was funded by the Austrian Academy of Sciences, the European Commission (Marie-Curie Career Integration Grant), the Austrian Science Fund FWF and the Wellcome Trust.