<HashMap><database>GEO</database><file_versions><headers><Content-Type>application/xml</Content-Type></headers><body><files><Other>ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE325nnn/GSE325548/</Other></files><type>primary</type></body><statusCode>OK</statusCode><statusCodeValue>200</statusCodeValue></file_versions><scores/><additional><omics_type>Transcriptomics</omics_type><species>Mus musculus</species><gds_type>Expression profiling by high throughput sequencing</gds_type><full_dataset_link>https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE325548</full_dataset_link><repository>GEO</repository><entry_type>GSE</entry_type></additional><is_claimable>false</is_claimable><name>Time-resolved transcriptomic profiling of surgical wounds identifies stage-specific therapeutic targets for residual ovarian cancer</name><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.</description><dates><publication>2026/03/27</publication></dates><accession>GSE325548</accession><cross_references><GSM>GSM9608249</GSM><GSM>GSM9608280</GSM><GSM>GSM9608281</GSM><GSM>GSM9608260</GSM><GSM>GSM9608282</GSM><GSM>GSM9608283</GSM><GSM>GSM9608261</GSM><GSM>GSM9608262</GSM><GSM>GSM9608284</GSM><GSM>GSM9608285</GSM><GSM>GSM9608263</GSM><GSM>GSM9608286</GSM><GSM>GSM9608264</GSM><GSM>GSM9608265</GSM><GSM>GSM9608287</GSM><GSM>GSM9608288</GSM><GSM>GSM9608266</GSM><GSM>GSM9608289</GSM><GSM>GSM9608267</GSM><GSM>GSM9608268</GSM><GSM>GSM9608269</GSM><GSM>GSM9608259</GSM><GSM>GSM9608290</GSM><GSM>GSM9608291</GSM><GSM>GSM9608292</GSM><GSM>GSM9608270</GSM><GSM>GSM9608271</GSM><GSM>GSM9608293</GSM><GSM>GSM9608294</GSM><GSM>GSM9608272</GSM><GSM>GSM9608250</GSM><GSM>GSM9608251</GSM><GSM>GSM9608295</GSM><GSM>GSM9608273</GSM><GSM>GSM9608274</GSM><GSM>GSM9608252</GSM><GSM>GSM9608296</GSM><GSM>GSM9608275</GSM><GSM>GSM9608253</GSM><GSM>GSM9608254</GSM><GSM>GSM9608276</GSM><GSM>GSM9608277</GSM><GSM>GSM9608255</GSM><GSM>GSM9608278</GSM><GSM>GSM9608256</GSM><GSM>GSM9608257</GSM><GSM>GSM9608279</GSM><GSM>GSM9608258</GSM><GPL>9185</GPL><GSE>325548</GSE><taxon>Mus musculus</taxon></cross_references></HashMap>