1 2 5 4 VOLUME 18 | NUMBER 8 | AUGUST 2012 nAture medicine Therapeutic cancer vaccines hold the promise of combining meaningful efficacy (prolongation of survival) with very good safety and tolerability, as has been shown in several recent randomized trials 1-3 . However, development of cancer vaccines remains a major challenge, with little knowledge of (i) the optimal tumor antigens to target, (ii) suitable agents to counteract regulatory mechanisms opposing successful immunotherapy and (iii) surrogate and predictive biomarkers that can improve our understanding of these regulatory mechanisms and predict a patient's response to therapy. The first major issue addressed in this work is whether relevant HLArestricted peptides for immunotherapeutic intervention in patients with RCC can be identified and clinically validated. We defined the relevance of the antigens as their natural presence on the tumor in the majority of RCC samples, their immunogenicity (induction of T cell responses in clinical studies) and the association of the vaccine-induced T cell responses with clinical benefit. For the identification, selection and preclinical immunological validation of such antigens, we used the antigen discovery platform XPRESIDENT 4,5 to create a multipeptide vaccine designated IMA901 for immunotherapy of RCC. We tested IMA901 in HLA-A*02 + subjects with advanced RCC in two clinical trials, a phase 1 (n = 28) and a randomized phase 2 (n = 68) trial, both of which assessed the association of T cell responses to IMA901 with clinical benefit.
Purpose: In the setting of a prospective clinical trial, we determined the predictive value of the methylation status of the O-6-methylguanine-DNA methyltransferase (MGMT) promoter for outcome in glioblastoma patients treated with the alkylating agent temozolomide. Expression of this excision repair enzyme has been associated with resistance to alkylating chemotherapy.Experimental Design: The methylation status of MGMT in the tumor biopsies was evaluated in 38 patients undergoing resection for newly diagnosed glioblastoma and enrolled in a Phase II trial testing concomitant and adjuvant temozolomide and radiation. The epigenetic silencing of the MGMT gene was determined using methylation-specific PCR.Results: Inactivation of the MGMT gene by promoter methylation was associated with longer survival (P ؍ 0.0051; Log-rank test). At 18 months, survival was 62% (16 of 26) for patients testing positive for a methylated MGMT promoter but reached only 8% (1 of 12) in absence of methylation (P ؍ 0.002; Fisher's exact test). In the presence of other clinically relevant factors, methylation of the MGMT promoter remains the only significant predictor (P ؍ 0.017; Cox regression).Conclusions: This prospective clinical trial identifies MGMT-methylation status as an independent predictor for glioblastoma patients treated with a methylating agent. The association of the epigenetic inactivation of the DNA repair gene MGMT with better outcome in this homogenous cohort may have important implications for the design of future trials and supports efforts to deplete MGMT by O-6-benzylguanine, a noncytotoxic substrate of this enzyme.
The methylation status of the O 6 -methylguanine-DNA methyltransferase ( MGMT ) gene is an important predictive biomarker for benefit from alkylating agent therapy in glioblastoma. Recent studies in anaplastic glioma suggest a prognostic value for MGMT methylation. Investigation of pathogenetic and epigenetic features of this intriguingly distinct behavior requires accurate MGMT classification to assess high throughput molecular databases. Promoter methylation-mediated gene silencing is strongly dependent on the location of the methylated CpGs, complicating classification. Using the HumanMethylation450 (HM - 450K) BeadChip interrogating 176 CpGs annotated for the MGMT gene, with 14 located in the promoter, two distinct regions in the CpG island of the promoter were identified with high importance for gene silencing and outcome prediction. A logistic regression model (MGMT-STP27) comprising probes cg1243587 and cg12981137 provided good classification properties and prognostic value (kappa = 0.85; log-rank p < 0.001) using a training-set of 63 glioblastomas from homogenously treated patients, for whom MGMT methylation was previously shown to be predictive for outcome based on classification by methylation-specific PCR. MGMT-STP27 was successfully validated in an independent cohort of chemo-radiotherapy-treated glioblastoma patients ( n = 50; kappa = 0.88; outcome, log-rank p < 0.001). Lower prevalence of MGMT methylation among CpG island methylator phenotype (CIMP) positive tumors was found in glioblastomas from The Cancer Genome Atlas than in low grade and anaplastic glioma cohorts, while in CIMP-negative gliomas MGMT was classified as methylated in approximately 50 % regardless of tumor grade. The proposed MGMT-STP27 prediction model allows mining of datasets derived on the HM - 450K or HM-27K BeadChip to explore effects of distinct epigenetic context of MGMT methylation suspected to modulate treatment resistance in different tumor types. Electronic supplementary material The online version of this article (doi:10.1007/s00401-012-1016-2) contains supplementary material, which is available to authorized users.
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