{"doi":"10.1093/noajnl/vdae031","title":"Sex differences in glioblastoma response to treatment: Impact of MGMT methylation","abstract":"It has been established that glioblastoma (GBM) survival differs by sex, with females having a significant survival advantage.1 Another prognostic factor associated with GBM survival is O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation, associated with sensitivity to alkylating chemotherapy, such as temozolomide (TMZ), and improved survival.2,3MGMT methylation status impacts treatment patterns for GBM. Studies suggest that patients with unmethylated tumors should receive only radiotherapy.4 Here, we investigate, utilizing a large real-world data set, the impact of MGMT methylation status on sex-specific survival for different GBM treatment patterns. Despite aggressive multimodal treatments, GBM remains uniformly lethal. Survival is largely dictated by the extent of surgical resection and response to standard-of-care radiation and TMZ. MGMT promoter methylation status has been shown to have prognostic and predictive value.2,4 It has been postulated that enhanced MGMT methylation may predispose an individual to better responses to alkylating treatments and radiotherapy. To analyze the impact of sex, MGMT promoter methylation, and treatment modality on survival, we analyzed 2108 adult (>25 years old) individuals with GBM as determined by a combination of annotated histology and IDH wild-type status from the CARIS Lifesciences data set from 2013 to 2021 (61.5% male, 38.5% female). MGMT promoter methylation analysis was performed by pyrosequencing.5 Samples with ≥7% and <9% methylation were considered to be equivocal or gray zone results.5 Real-world overall survival and treatment information was obtained from insurance claims data from payers and calculated from start of any type of GBM treatment to last contact6; uninsured patients were not included. Individuals were categorized by MGMT promoter methylation status, TMZ treatment at any dosage/time period, and radiation treatment at any dosage. Treatment information was obtained from the insurance claims data. Date of first treatment was determined by the first insurance treatment of interest claims, independent of the tissue collection date.6 Kaplan–Meier survival curves were evaluated to assess survival differences by sex, stratified by 3 different treatment regimens (TMZ alone, radiation alone, and TMZ plus radiation). Corresponding log-rank test P-values are reported (P < 0.05 as significant). All analyses were performed using the Caris CODEai data platform. Limitations with the analytical tools within the platform prevented multivariate analyses, and therefore all results are presented stratified by MGMT promoter methylation and treatment status. Additional stratifications, including age at diagnosis, were out of this analysis scope. Within each treatment modality, median survival estimates were generally higher among individuals with MGMT promoter methylation compared to unmethylated individuals (Figure 1). This is consistent with other studies that have demonstrated that overall survival is better in individuals with MGMT promoter methylation compared to individuals that are unmethylated.7 Similar results were observed here in individuals treated with standard of care. Previous studies also demonstrated that there is no difference in survival, by sex, in individuals receiving standard of care who have unmethylated MGMT. This was observed here, as there were no significant survival differences observed by sex within any treatment group among unmethylated individuals (Figure 1A, C, and E). This larger study does show a direction of lower survival in male survival among the TMZ-only (Figure 1C) and radiation-only (Figure 1E) treatment groups; while this did not reach significance, it may be worth examining in a larger study group. There were no observed sex differences in survival within GBM individuals with MGMT promoter methylation receiving either TMZ and radiation (Figure 1B) or TMZ alone (Figure 1D). A notable survival difference was observed among MGMT-m","journal":"Neuro-Oncology Advances","year":2024,"id":442009,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":8,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9531,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":760813,"name":"Kristin Waite","orcid":"0000-0002-3186-8510","position":1,"is_corresponding":false},{"id":1255514,"name":"Mantas Dmukauskas","orcid":"0000-0002-1716-9772","position":2,"is_corresponding":false},{"id":228899,"name":"Michael Glantz","orcid":"0000-0003-4877-5094","position":3,"is_corresponding":false},{"id":1186993,"name":"Sonikpreet Aulakh","orcid":"0000-0001-7150-5805","position":4,"is_corresponding":false},{"id":289880,"name":"Theodore Nicolaides","orcid":"0000-0002-0637-1086","position":5,"is_corresponding":false},{"id":458977,"name":"Soma Sengupta","orcid":"0000-0003-4577-1397","position":6,"is_corresponding":false},{"id":254337,"name":"Joanne Xiu","orcid":"0000-0001-8744-5827","position":7,"is_corresponding":false},{"id":14321,"name":"Jill S. Barnholtz‐Sloan","orcid":"0000-0001-6190-9304","position":8,"is_corresponding":false},{"id":262238,"name":"Gino Cioffi","orcid":"0000-0002-3296-8652","position":0,"is_corresponding":true}],"reference_count":10,"raw_metadata":null,"created_at":"2026-07-19T02:01:15.932178Z","pmid":"38476929","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}