Epithelial ovarian cancer (EOC) is challenging to detect early due to the lack of specific symptoms and a limited list of biomarkers. As a result, the majority (>80%) of cases are diagnosed at advanced stages, with a 5-year survival of only 30-50%. Although many EOC patients initially respond to treatment, 85% relapse due to chemoresistance. The highlights the urgent need for better diagnostic tools and therapeutic platforms. In order to predict and prevent EOC emergence and recurrence, it is critical to identify the underlying driver genes. Most discovery studies are limited to protein-coding genes, but clinical success has been limited. Our research is focused on identifying and characterising long noncoding RNAs (lncRNAs), a class of genes known to include biomarkers and druggable genes. Using our established bioinformatics protocols and the transcriptome data from EOC tumour samples sequenced by our group, we identified tens of thousands of novel EOC lncRNAs. By comparing expression profiles between healthy individuals and EOC patients, we shortlisted ten candidate biomarkers. Research by us and others shows that lncRNA expression better defines cell subpopulations in complex tissue environments like tumours. Furthermore, single-cell transcriptomics can help identify rare pre-existing chemoresistant cell subpopulations in EOC, along with their marker gene signatures. Using single-cell expression patterns from the novel EOC lncRNAs in key cell populations across longitudinal patient samples, we prioritised two chemoresistance-related lncRNAs for functional analyses. These lncRNAs regulate the protein-coding genes JUND and FRMD3, both implicated in EOC prognosis. Altering the expression of these lncRNAs using antisense oligonucleotides (ASOs) promoted carboplatin resistance in susceptible cell lines, presenting potential new drug targets. Our findings support the significance of lncRNAs in EOC research and paves the way for novel therapeutic strategies.