Transcriptomic datasets of melittin- and un-treated murine cervical carcinoma U14 cells

Zhang, R.; Zhang, Y.; Wang, M.; Jiang, J.; Li, Y.; Chen, D.; Yan, T.; Guo, R.

doi:10.64898/2026.07.25.739748

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bioRxiv · 10.64898/2026.07.25.739748

Transcriptomic datasets of melittin- and un-treated murine cervical carcinoma U14 cells

Zhang, R.·Zhang, Y.·Wang, M.·Jiang, J.·Li, Y.·Chen, D.·Yan, T.·Guo, R.

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Abstract

Melittin, a potent amphipathic cationic peptide derived from bee venom, exhibits broad-spectrum antineoplastic efficacy, notably against cervical carcinoma. Despite its established therapeutic potential, the global transcriptional reprogramming orchestrating its acute multi-pathway cytotoxicity remains incompletely understood. To bridge this knowledge gap, we generated the first comprehensive, untargeted RNA-seq dataset profiling the acute phase of melittin-induced cell death in murine cervical carcinoma U14 cells (exposed to 4 g/mL melittin for 20 minutes) alongside untreated controls. Utilizing deep sequencing and rigorous bioinformatics workflows, we quantified genome-wide mRNA abundances and mapped a distinct transcriptomic shift, identifying 254 significantly differentially expressed genes, comprising 158 up- and 96 down-regulated transcripts. Validated by stringent quality control metrics, exceptional genomic mapping rates, and comprehensive functional annotations via the GO and KEGG databases, this high-resolution transcriptomic resource provides a systems-level map of early molecular alterations. All raw and processed sequencing data are publicly available. This transcriptomic resource provides a valuable foundation for elucidating the acute regulatory networks underlying melittin-induced anti-cervical cancer effects. DatasetThe dataset can be accessed through the NGDC website by searching with the BioProject accession number PRJCA068439. Reviewers may use this link for anonymous access during the review process. Direct URL to data: Genome Sequence Archive-CNCB-NGDC

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Zhang, R., Zhang, Y., Wang, M., Jiang, J., Li, Y., Chen, D., Yan, T., Guo, R.. 2026-07-28. Transcriptomic datasets of melittin- and un-treated murine cervical carcinoma U14 cells. https://doi.org/10.64898/2026.07.25.739748

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