Application of Large-Scale Genome Data in Identifying Clinically Actionable Targets in Cancer

Dear Colleagues,

Large-scale data analysis has contributed tremendously to precision oncology. Genome data analysis has enabled the identification of signature tumor profiles in selective cancers. Many of these targets (e.g., tumor burden or MSI) have therapeutic or diagnostic applications. Separately, large-scale data analysis in constitutional cancer has enabled the identification of alterations related to cancer risk and familial cancer.

This Special Issue provides a platform for studies that utilize large-scale genome data to investigate clinically actionable targets in tumors (i.e., somatic) or germline (i.e., constitutional) cancer. We welcome manuscripts that include large data analysis to present novel methods to identify validated clinical targets in the genome, novel actional variants in selected cancer types (somatic or inherited cancer), functional analysis of genomics and genome targets, analysis of multi-omics data, cancer cohort analysis, variant pattern recognition analysis, and applications of machine learning and AI in identifying actional clinical targets.

Dr. Arezou A. Ghazani
Guest Editor

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