How can we understand the role of genetic variations in cancer development and treatment? This is one of the most challenging and important questions in modern biology and medicine. A new editorial paper, by researchers Jun S. Song and Mohith Manjunath from the University of Illinois at Urbana-Champaign, offers a novel discussion involving computational methods to address this question. On August 30, 2023, their editorial was published in Oncotarget, entitled, "Predicting the molecular functions of regulatory genetic variants associated with cancer."
In this editorial, the authors review recent advances and challenges in identifying and characterizing the functional effects of genetic variants that affect gene regulation, such as enhancers, promoters, and transcription factors. These variants, also known as expression quantitative trait loci (eQTLs), can modulate the expression levels of genes and influence various cellular processes and phenotypes, including cancer susceptibility and response to therapy.
The authors propose a framework for predicting the molecular functions of eQTLs based on their genomic context, epigenetic marks, chromatin accessibility, and three-dimensional interactions. They also discuss how to integrate multiple types of data and methods to improve the accuracy and interpretability of the predictions. Furthermore, they highlight the potential applications and implications of their approach for cancer research and precision medicine.
“A promising approach to address these challenges is to integrate genomic, epigenomic, transcriptomic and machine learning methods to identify functional genetic variants and characterize their mode of action in regulating target genes.”
Full blog - https://www.oncotarget.org/2023/09/07/predicting-functions-of-cancer-associated-genetic-variants/
Editorial DOI - https://doi.org/10.18632/oncotarget.28451
Correspondence to - Jun S. Song - songj@illinois.edu
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Keywords - cancer, genome-wide association studies, cancer risk, regulatory variants, functional genomics
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