biostudies-arrayexpressKate MeesonHomo sapienshttps://www.ebi.ac.uk/biostudies/studies/E-MTAB-16770OV56 ovarian cancer cell line treated with siTPI1 (siRNA targeted against triose phosphate isomerase 1) and the following negative controls: NTsiRNA (non-targeting siRNA), transfection reagent only and untreated. Experiment designed to assess the effect of TPI1 gene knockdown on OV56 gene expression.biostudies-arrayexpressGrowth Protocol - OV56 cells (1,300 cell/well) in a 96-well plate. Cultured in 1:1 ratio of DMEM:F12 with 5% FBS, 2mM glutamine, 0.5ug/mL hydrocortisone, 10ug/mL insulin and 50ug/mL penicillin/streptomycin.Nucleic Acid Extraction - RNA was isolated from harvested cells using the RNeasy mini kit.Sample Treatment - Transfection with ON-TARGETplus SMARTpool Human TPI1 siRNA or NTsiRNA. Negative controls treated with transfection reagent only or untreated. Final concentration of 66nM siRNA in a seeding density of 1300 cells/well. Incubation for 48 hours.Sequencing - Libraries were multiplexed and pooled prior to loading onto the appropriate flow-cell. The flow-cell was paired-end sequenced (59 + 59 cycles, plus indices) on an Illumina NovaSeq6000 instrument. Output was demultiplexed and BCL-to-FastQ conversion was performed using Illumina’s bcl2fastq software (2.20.0.422).Library Construction - Poly-adenylated mRNA extracted from total RNA using poly-T, oligo-attached magnetic beads. mRNA fragmented under elevated temperature and reverse transcribed into first strand cDNA using random hexamer primers and Actinomycin D. Second strand cDNA synthesised to yield blunt-ended, double-stranded cDNA fragments. Strand specificity maintained by dUTP-incorporation. Following a single adenine base addition, adapters with a corresponding, complementary thymine overhang were ligated to the cDNA fragments to prepare for dual indexing. PCR amplification used to add the index adaptor sequences to create final cDNA library.Sample Collection - OV56 were cells harvested from 96-well plates, after 48-hour incubation with siRNA for test conditions.OrganizationMINSEQE ScoreAssays and DataMAGE-TAB FilesUnknownTranscriptomicsGenomicsProteomicsIllumina NovaSeq 6000<h4>ABSTRACT</h4> Constraint-based modelling (CBM) is a powerful computational approach that reconstructs cellular metabolism by integrating ‘omics data with genome-scale metabolic models (GEMs), enabling in silico hypothesis generation and genetic engineering studies. Advances in high-throughput ‘omics technologies and the complete mapping of the human genome have expanded the application of CBM to human systems. Given that altered metabolism is a hallmark of cancer, this disease represents an ideal context for developing and applying CBM workflows. Despite the presence of well-characterised metabolic signatures and vulnerabilities in ovarian cancer, this tumour type remains under-explored within the CBM field. Meanwhile, the limited efficacy of current therapies and the frequent emergence of chemoresistance underscore the need for novel, mechanism-based approaches to therapeutic discovery. In this study, we constructed ovarian cancer-specific metabolic models using an ‘omics integration algorithm that incorporates transcriptomic data in a way that is directed by experimental growth measurements. Simulations identified multiple candidate molecules predicted to influence cancer cell proliferation. Among these, triosephosphate isomerase 1 (TPI1) was selected for experimental validation based on qualitative prioritisation criteria. Notably, model predictions were supported by RNA sequencing and proliferation assays, implicating TPI1 in ovarian cancer cell growth. Our results provide novel insights into the metabolic dependencies of ovarian cancer and demonstrate a multi-omics CBM workflow that may be broadly applicable for uncovering therapeutic vulnerabilities in other malignancies.RNA-seq of total RNAHomo sapiensTranscriptome-driven constraint-based modelling reveals metabolic targets for ovarian cancerKate MeesonKate E. Meeson, Joanne C. McGrail, Jean-Marc Schwartz, Stephen S. TaylorfalseTranscriptome-driven constraint-based modelling reveals metabolic targets for ovarian cancerOV56 ovarian cancer cell line treated with siTPI1 (siRNA targeted against triose phosphate isomerase 1) and the following negative controls: NTsiRNA (non-targeting siRNA), transfection reagent only and untreated. Experiment designed to assess the effect of TPI1 gene knockdown on OV56 gene expression.2026-04-09T00:00:00Z2026-04-09T01:02:06.935Z2026-03-17T14:37:12.921ZE-MTAB-16770ERP190899EFO_0002944EFO_0004170EFO_0009653EFO_0003789EFO_0005518EFO_0004184EFO_000396910.1101/2025.06.24.661329