To address this gap, we first performed bioinformatics analyses using transcriptomic datasets from ovarian cancer patients and normal controls obtained from public databases, including The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO), with a focus on the differential expression of FTO.20, 21, 22. The gene discussed is FTO; the disease is ovarian cancer.