A gene called SETD2 is frequently mutated in various cancer types. Cancers in which SETD2 function is lost are more aggressive and lead to a worse prognosis for patients. To understand more about how SETD2 loss impacts cancer development, DPhil candidate Hira Javaid (Department of Oncology) and colleagues analysed 24 different cancer types. They observed that SETD2 loss was linked to altered patterns of DNA methylation in 21 of these cancer types.
To exemplify the effect of the dysregulated DNA methylation, in renal cancer, DNA methylation alterations were correlated with changes in the expression of vital genes such as TP53, FOXO1, and CDK4. These genes are pivotal to cancer initiation, tumour suppression, and invasiveness. Such findings have the potential to reshape our understanding of the mechanisms driving cancer development and progression. This work suggests a broader role for SETD2 loss in not only cancer development but also cancer aggressiveness through DNA methylation disturbances.
The study, published in BMC Cancer, also used a new machine learning approach for biomarker selection developed by Alessandro Barberis (Nuffield Department of Surgical Sciences). This method identified a DNA methylation signature that accurately predicts SETD2 mutation status. This approach will help scientists develop biomarkers that are more readily translatable into the clinic.
This DNA methylation signature not only holds promise for earlier and more accurate diagnosis of SETD2-mutated cancers but also demonstrates a strong correlation with patient prognosis. It is hoped that this could enable oncologists to tailor treatments based on the individual molecular profile of each patient, leading to more personalised and effective therapies.
Read the full news story on the Department of Oncology website