This review discusses the role of genetic variations in microRNA (miRNA) networks in cancer research. It highlights how single nucleotide polymorphisms (SNPs) in miRNA genes, their processing machinery, and target binding sites can affect cancer risk, treatment efficacy, and patient prognosis. The authors describe methodological approaches used in studies and recommend strategies for future research. They emphasize the importance of understanding miRNA biogenesis, including the seed region and flanking regions, and their impact on target mRNA regulation. The review also covers the functional consequences of SNPs in miRNA coding genes, pre-miRNAs, and 3' UTRs, and their association with cancer risk. Additionally, it discusses the role of miRNA processing machinery, alternative miRNA structural variations (isomiRs), and epigenetic factors in cancer. The authors conclude by emphasizing the need for large-scale studies, functional validation, and a polygenic, network-based approach to fully understand the implications of miRNA genetic variations in cancer.This review discusses the role of genetic variations in microRNA (miRNA) networks in cancer research. It highlights how single nucleotide polymorphisms (SNPs) in miRNA genes, their processing machinery, and target binding sites can affect cancer risk, treatment efficacy, and patient prognosis. The authors describe methodological approaches used in studies and recommend strategies for future research. They emphasize the importance of understanding miRNA biogenesis, including the seed region and flanking regions, and their impact on target mRNA regulation. The review also covers the functional consequences of SNPs in miRNA coding genes, pre-miRNAs, and 3' UTRs, and their association with cancer risk. Additionally, it discusses the role of miRNA processing machinery, alternative miRNA structural variations (isomiRs), and epigenetic factors in cancer. The authors conclude by emphasizing the need for large-scale studies, functional validation, and a polygenic, network-based approach to fully understand the implications of miRNA genetic variations in cancer.