Ovarian cancer is one of the deadliest gynaecological malignancies. Platinum-based chemotherapy remains a standard first-line therapy; however, 80% of patients initially responsive to the treatment eventually develop chemoresistance.
We have performed long-read RNA sequencing of six ovarian cancer cell lines, A2780(parental and chemosensitive), OVAHO, Kuramochi, TYK-NU (parental and chemosesnitive). The data was combined in one filed and it produced 13,303,403 circular consensus (CCS) reads. Upon generation of a sample specific FASTA file, we analysed our DIA data from ovarian cancer cell lines as well as patient samples.
The analysis of six ovarian cancer cell lines, A2780(parental and chemosesnitive), OVAHO, Kuramochi, TYK-NU (parental and chemosensitive) revealed significant differences in proteomic coverage between conventional (UniProt) and sample-specific (SS FASTA) databases. With the sample-specific approach, protein detection increased from 4,200-5,025 to 7,500 to 8,969 across all cell lines, and increased the number of peptides identified from 21,141- 39,558 to 22,118–46,847. SQANTI3 quality control analysis identified 17 novel genes and 52,822 unique isoforms, demonstrating the complexity of the transcriptomic landscape.
We used GenomeProt, a proteogenomics tool for long-read RNA-seq developed by Hitesh Kore and the Clark Laboratory at the University of Melbourne. GenomeProt helped us visualize novel isoforms identified in our dataset. Our approach provides comprehensive isoform characterization Our approach provides a comprehensive perspective of protein isoforms associated with chemoresistance. These findings highlight the importance of isoform-level resolution in cancer proteomics and its potential for advancing biomarker discovery.