{"database":"GEO","file_versions":[{"headers":{"Content-Type":["application/json"]},"body":{"files":{"Other":["ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE325nnn/GSE325548/"]},"type":"primary"},"statusCode":"OK","statusCodeValue":200}],"scores":null,"additional":{"omics_type":["Transcriptomics"],"species":["Mus musculus"],"gds_type":["Expression profiling by high throughput sequencing"],"full_dataset_link":["https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE325548"],"repository":["GEO"],"entry_type":["GSE"],"additional_accession":[]},"is_claimable":false,"name":"Time-resolved transcriptomic profiling of surgical wounds identifies stage-specific therapeutic targets for residual ovarian cancer","description":"Background: The optimal timing of adjuvant chemotherapy after cytoreductive surgery in epithelial ovarian cancer remains uncertain, and perioperative wound-healing responses may transiently create a pro-tumorigenic and drug-resistant microenvironment. This study aimed to characterize time-dependent wound-induced transcriptomic alterations and to identify pharmacologic agents capable of reversing these responses. Methods: An ID8 murine ovarian cancer model was used to compare no treatment, anesthesia alone, and anesthesia plus surgical wounding mimicking futile laparotomy. Tumors were collected at baseline, 1 day (T1), 1 week (T2), and 2 weeks (T3) after intervention. RNA sequencing was performed, and wound-specific differentially expressed genes (WsDEGs) were defined by excluding anesthesia- and progression-related signatures. Functional enrichment analyses were conducted, followed by transcriptome-based drug repurposing using the REMEDY platform to identify compounds predicted to reverse wound-induced gene expression profiles. Results: Surgical wounding significantly increased tumor burden at T1. Transcriptomic analyses revealed distinct, time-dependent wound-associated programs. At T1, WsDEGs were enriched in inflammatory signaling, coagulation, angiogenesis, and immune cell migration, with Vorinostat and Homohar-ringtonine identified as top candidates to counteract these signatures. At T2, pathways related to cell survival, adhesion, and morphogenesis predominated, with LY-2090314, Artesunate, and Birinapant emerging as potential modulators. At T3, cell-cycle regulation and lipid metabolic pathways were dominant, and Fulvestrant, Atorvastatin, Imatinib, and ABT-737 were predicted to inhibit these processes. Conclusions: Perioperative sur-gical wounding induces dynamic, stage-specific transcriptomic programs that may promote ovarian cancer progression and alter drug responsiveness. These findings support time-adapted perioperative pharmacologic strategies to optimize postoperative cancer therapy.","dates":{"publication":"2026/03/27"},"accession":"GSE325548","cross_references":{"GSM":["GSM9608249","GSM9608280","GSM9608281","GSM9608260","GSM9608282","GSM9608283","GSM9608261","GSM9608262","GSM9608284","GSM9608285","GSM9608263","GSM9608286","GSM9608264","GSM9608265","GSM9608287","GSM9608288","GSM9608266","GSM9608289","GSM9608267","GSM9608268","GSM9608269","GSM9608259","GSM9608290","GSM9608291","GSM9608292","GSM9608270","GSM9608271","GSM9608293","GSM9608294","GSM9608272","GSM9608250","GSM9608251","GSM9608295","GSM9608273","GSM9608274","GSM9608252","GSM9608296","GSM9608275","GSM9608253","GSM9608254","GSM9608276","GSM9608277","GSM9608255","GSM9608278","GSM9608256","GSM9608257","GSM9608279","GSM9608258"],"GPL":["9185"],"GSE":["325548"],"taxon":["Mus musculus"]}}