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  • Online Resource  (2)
  • American Association for Cancer Research (AACR)  (2)
  • 2020-2024  (2)
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  • Online Resource  (2)
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  • American Association for Cancer Research (AACR)  (2)
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  • 2020-2024  (2)
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Subjects(RVK)
  • 1
    In: Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 29, No. 19 ( 2023-10-02), p. 3892-3900
    Abstract: The EORTC-26101 study was a randomized phase II and III clinical trial of bevacizumab in combination with lomustine versus lomustine alone in progressive glioblastoma. Other than for progression-free survival (PFS), there was no benefit from addition of bevacizumab for overall survival (OS). However, molecular data allow for the rare opportunity to assess prognostic biomarkers from primary surgery for their impact in progressive glioblastoma. Experimental Design: We analyzed DNA methylation array data and panel sequencing from 170 genes of 380 tumor samples of the EORTC-26101 study. These patients were comparable with the overall study cohort in regard to baseline characteristics, study treatment, and survival. Results: Of patients' samples, 295/380 (78%) were classified into one of the main glioblastoma groups, receptor tyrosine kinase (RTK)1, RTK2 and mesenchymal. There were 10 patients (2.6%) with isocitrate dehydrogenase mutant tumors in the biomarker cohort. Patients with RTK1 and RTK2 classified tumors had lower median OS compared with mesenchymal (7.6 vs. 9.2 vs. 10.5 months). O6-methylguanine DNA-methyltransferase (MGMT) promoter methylation was prognostic for PFS and OS. Neurofibromin (NF)1 mutations were predictive of response to bevacizumab treatment. Conclusions: Thorough molecular classification is important for brain tumor clinical trial inclusion and evaluation. MGMT promoter methylation and RTK1 classifier assignment were prognostic in progressive glioblastoma. NF1 mutation may be a predictive biomarker for bevacizumab treatment.
    Type of Medium: Online Resource
    ISSN: 1078-0432 , 1557-3265
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2023
    detail.hit.zdb_id: 1225457-5
    detail.hit.zdb_id: 2036787-9
    Location Call Number Limitation Availability
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  • 2
    In: Clinical Cancer Research, American Association for Cancer Research (AACR), ( 2024-07-17), p. OF1-OF10
    Abstract: To propose a novel recursive partitioning analysis (RPA) classification model in patients with IDH-wildtype glioblastomas that incorporates the recently expanded conception of the extent of resection (EOR) in terms of both supramaximal and total resections. Experimental Design: This multicenter cohort study included a developmental cohort of 622 patients with IDH-wildtype glioblastomas from a single institution (Severance Hospital) and validation cohorts of 536 patients from three institutions (Seoul National University Hospital, Asan Medical Center, and Heidelberg University Hospital). All patients completed standard treatment including concurrent chemoradiotherapy and underwent testing to determine their IDH mutation and MGMTp methylation status. EORs were categorized into either supramaximal, total, or non-total resections. A novel RPA model was then developed and compared with a previous Radiation Therapy Oncology Group (RTOG) RPA model. Results: In the developmental cohort, the RPA model included age, MGMTp methylation status, Karnofsky performance status, and EOR. Younger patients with MGMTp methylation and supramaximal resections showed a more favorable prognosis [class I: median overall survival (OS) 57.3 months], whereas low-performing patients with non-total resections and without MGMTp methylation showed the worst prognosis (class IV: median OS 14.3 months). The prognostic significance of the RPA was subsequently confirmed in the validation cohorts, which revealed a greater separation between prognostic classes for all cohorts compared with the previous RTOG RPA model. Conclusions: The proposed RPA model highlights the impact of supramaximal versus total resections and incorporates clinical and molecular factors into survival stratification. The RPA model may improve the accuracy of assessing prognostic groups.
    Type of Medium: Online Resource
    ISSN: 1078-0432 , 1557-3265
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2024
    detail.hit.zdb_id: 1225457-5
    detail.hit.zdb_id: 2036787-9
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
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