Elisabetta Marton1, Enrico Giordan2, Francesca Siddi3, Christian Curzi3, Giuseppe Canova1, Bruno Scarpa4, Angela Guerriero5, Sabrina Rossi6, Domenico D' Avella3, Pierluigi Longatti1, Alberto Feletti7. 1. Department of Neurosurgery, Padova University, Treviso Regional Hospital, Treviso, Italy. 2. Department of Neurosurgery, Padova University, Treviso Regional Hospital, Treviso, Italy. Electronic address: enrico.giordan@aulss2.veneto.it. 3. Department of Neuroscience, University of Padova, Padova, Italy. 4. Department of Statistical Sciences, University of Padova, Padova, Italy. 5. Department of Pathology, Treviso Regional Hospital, Treviso, Italy. 6. Department of Pathology, Bambin Gesù Children's Hospital, Rome, Italy. 7. Department of Neurosciences, Biomedicine and Movement Sciences, Neurosurgery Unit, University of Verona, Italy.
Abstract
PURPOSE: The reasons why a specific subset of glioblastoma (GBM) patients survive longer than others is still unclear. This study analyzed a cohort of long-term and very-long-term GBM survivors to determine which genetic alterations or patient's characteristics influence survival time. METHODS: We retrospectively reviewed a cohort of GBM patients treated at our institution over the last 20 years, stratifying patients in three groups: those with a survival time ≥ 36 months and < 120 months (LTS), ≥120 months (VLTS), and < 36 months, respectively. Clinical (age, sex, focality, resection degree, Karnofsky performance status), and immunohistochemical and molecular data (Ki-67 expression and multiple genes alterations) were collected. We then utilized principal component analysis, logistic regression, and Cox proportional hazard models to identify those variables associated with survival. RESULTS: Younger age at presentation (HR = 0.36, 95% CI 0.21-0.67, p = .001), and MGMT promoter [(MGMTp), methylated, HR = 0.57, CI 0.34-0.96, p = .034) were associated with higher odds of VLTS survival. The multivariate analysis showed how the combination of younger age (< 50 years), Ki-67 < 10%, and the coexistence of TERTp not mutated, MGMTp methylated, and IDH1/2 mutated in the same patient are also associated with higher odds of survival (HR = 0.10, CI 0.01-0.74, p = .025). CONCLUSIONS: We confirmed younger age at presentation and MGMTp methylation as the only independent factors associated with VLTS. The exceptional survival of our VLTS patients is probably associated with different, still understudied, gene mutations, or with the coexistence of multiple factors.
PURPOSE: The reasons why a specific subset of glioblastoma (GBM) patients survive longer than others is still unclear. This study analyzed a cohort of long-term and very-long-term GBM survivors to determine which genetic alterations or patient's characteristics influence survival time. METHODS: We retrospectively reviewed a cohort of GBMpatients treated at our institution over the last 20 years, stratifying patients in three groups: those with a survival time ≥ 36 months and < 120 months (LTS), ≥120 months (VLTS), and < 36 months, respectively. Clinical (age, sex, focality, resection degree, Karnofsky performance status), and immunohistochemical and molecular data (Ki-67 expression and multiple genes alterations) were collected. We then utilized principal component analysis, logistic regression, and Cox proportional hazard models to identify those variables associated with survival. RESULTS: Younger age at presentation (HR = 0.36, 95% CI 0.21-0.67, p = .001), and MGMT promoter [(MGMTp), methylated, HR = 0.57, CI 0.34-0.96, p = .034) were associated with higher odds of VLTS survival. The multivariate analysis showed how the combination of younger age (< 50 years), Ki-67 < 10%, and the coexistence of TERTp not mutated, MGMTp methylated, and IDH1/2 mutated in the same patient are also associated with higher odds of survival (HR = 0.10, CI 0.01-0.74, p = .025). CONCLUSIONS: We confirmed younger age at presentation and MGMTp methylation as the only independent factors associated with VLTS. The exceptional survival of our VLTS patients is probably associated with different, still understudied, gene mutations, or with the coexistence of multiple factors.
Authors: Sali Al-Ansari; Rozita Jalali; Antonius L J J Bronckers; Olaf van Tellingen; Judith Raber-Durlacher; Nasser Nadjmi; Alan Henry Brook; Jan de Lange; Frederik R Rozema Journal: Genes (Basel) Date: 2022-07-04 Impact factor: 4.141
Authors: James L Rogers; Elizabeth Vera; Alvina Acquaye; Nicole Briceno; Varna Jammula; Amanda L King; Heather Leeper; Martha M Quezado; Javier Gonzalez Alarcon; Lisa Boris; Eric Burton; Orieta Celiku; Anna Choi; Alexa Christ; Sonja Crandon; Ewa Grajkowska; Nicole Leggiero; Nicole Lollo; Marta Penas-Prado; Jennifer Reyes; Christine Siegel; Brett J Theeler; Michael Timmer; Kathleen Wall; Jing Wu; Kenneth Aldape; Mark R Gilbert; Terri S Armstrong Journal: Neurooncol Pract Date: 2021-04-10