{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Zirem Y"],"funding":["INSERM","NIA NIH HHS","Region Hauts-de-France","NIMH NIH HHS","NCI NIH HHS","National Institutes of Health"],"pagination":["101482"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11031375"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["5(4)"],"pubmed_abstract":["Glioblastoma is a highly heterogeneous and infiltrative form of brain cancer associated with a poor outcome and limited therapeutic effectiveness. The extent of the surgery is related to survival. Reaching an accurate diagnosis and prognosis assessment by the time of the initial surgery is therefore paramount in the management of glioblastoma. To this end, we are studying the performance of SpiderMass, an ambient ionization mass spectrometry technology that can be used in vivo without invasiveness, coupled to our recently established artificial intelligence pipeline. We demonstrate that we can both stratify isocitrate dehydrogenase (IDH)-wild-type glioblastoma patients into molecular sub-groups and achieve an accurate diagnosis with over 90% accuracy after cross-validation. Interestingly, "],"journal":["Cell reports. Medicine"],"pubmed_title":["Real-time glioblastoma tumor microenvironment assessment by SpiderMass for improved patient management."],"pmcid":["PMC11031375"],"funding_grant_id":["R44 MH132196","R44 AG078097","R44 CA236097"],"pubmed_authors":["Roussel L","Duhamel M","Maurage CA","Lim MJ","Salzet M","Meresse B","Fournier I","Ledoux L","Zirem Y","Le Rhun E","Rothschild KJ","Tirilly P","Yagnik G"],"additional_accession":[]},"is_claimable":false,"name":"Real-time glioblastoma tumor microenvironment assessment by SpiderMass for improved patient management.","description":"Glioblastoma is a highly heterogeneous and infiltrative form of brain cancer associated with a poor outcome and limited therapeutic effectiveness. The extent of the surgery is related to survival. Reaching an accurate diagnosis and prognosis assessment by the time of the initial surgery is therefore paramount in the management of glioblastoma. To this end, we are studying the performance of SpiderMass, an ambient ionization mass spectrometry technology that can be used in vivo without invasiveness, coupled to our recently established artificial intelligence pipeline. We demonstrate that we can both stratify isocitrate dehydrogenase (IDH)-wild-type glioblastoma patients into molecular sub-groups and achieve an accurate diagnosis with over 90% accuracy after cross-validation. Interestingly, ","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Apr","modification":"2026-06-01T21:20:33.795Z","creation":"2026-05-21T03:08:16.971Z"},"accession":"S-EPMC11031375","cross_references":{"pubmed":["38552622"],"doi":["10.1016/j.xcrm.2024.101482"]}}