Literature DB >> 34376624

Age influences the distribution of diffuse gliomas.

Alexandre Roux1,2,3, Pascale Varlet1,2,4, Johan Pallud1,2,3.   

Abstract

Entities:  

Keywords:  age; alioblastomas; diffuse gliomas; epigenetic; histo-molecular

Mesh:

Year:  2021        PMID: 34376624      PMCID: PMC8386541          DOI: 10.18632/aging.203414

Source DB:  PubMed          Journal:  Aging (Albany NY)        ISSN: 1945-4589            Impact factor:   5.682


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Diffuse gliomas are the one of the most common malignant primary brain tumours in paediatric, adolescent and young adult (AYA), and adult patients [1]. Age is a main factor influencing the occurrence of cerebral gliomas and, particularly, the histo-molecular profile varies with age [2]. Interestingly, when we analyze the histo-molecular subtypes of diffuse gliomas in children <15 years, AYAs (i.e. between 15 and 25 years), adults between 25 and 55 years, and adults >55 years, we observe a variation of the distribution of the histo-molecular subtypes according to the age group analyzed (Figure 1). H3K27-mutant diffuse gliomas represent the most frequent subgroup in the paediatric population (33%), H3G34-mutant diffuse gliomas have a higher frequency in AYAs (13%), IDH-mutant diffuse gliomas have a higher frequency in adults between 25 and 55 years (60%), and IDH-wildtype diffuse gliomas represent the most frequent molecular subgroup in adults >55 years (58%) [1, 2].
Figure 1

Age distribution of histo-molecular subtypes of diffuse gliomas. Green: Diffuse midline gliomas, H3K27-mutant; Yellow: Diffuse gliomas, H3G34-mutant; Red: Diffuse gliomas, IDH-mutant (with and without 1p/19q-codeletion); Grey: Diffuse gliomas, IDH-wildtype.

Age distribution of histo-molecular subtypes of diffuse gliomas. Green: Diffuse midline gliomas, H3K27-mutant; Yellow: Diffuse gliomas, H3G34-mutant; Red: Diffuse gliomas, IDH-mutant (with and without 1p/19q-codeletion); Grey: Diffuse gliomas, IDH-wildtype. Age also influences the spatial distribution of IDH-wildtype glioblastomas. In patients ≥60 years, they more likely involve the cerebral hemispheres (frontal, temporal, parietal, and insular lobes more than occipital and limbic lobes) [3]. Contrarily, in younger patients, they more likely involve the midline (diencephalo-mesencephalon and thalamic regions) [3]. Age is a main prognostic factor for survival of diffuse gliomas, whatever the histo-molecular subtypes, together with the overall condition of the treatment, the extent of the surgical resection, and the adjuvant neuro-oncological treatments. Moreover, age influences the neurosurgical treatment, including the decision as to whether to perform a large surgical resection [4]. Indeed, although the extent of surgical resection is associated with a significant improvement in progression-free and overall survivals whatever the age of the patient, the rates of postoperative complications and the impact of surgery on functional independence possibly increases with age and is particularly a concern in the elderly population [4]. Similarly, the feasibility of adjuvant neuro-oncological treatments are influenced by age [5, 6]. For instance, the standard radiochemotherapy protocol for IDH-wildtype glioblastomas (i.e. 60Gy in 30 fractions with concurrent chemotherapy with Temozolomide followed by 6 cycles of adjuvant Temozolomide) is validated for patients <70 years. For older patients with functional independence (i.e. Karnofsky performance status >70%), a concentrated radiochemotherapy protocol (40Gy in 15 fractions) is proposed [6]. In the other cases, a chemotherapy alone or supportive care are proposed. In the same way, many radiotherapy and chemotherapy protocols for diffuse gliomas have been tried in paediatric patients [5], with very different patterns from those used in adults. Recently, epigenetic ages [7] and aging-related genes [8] have provided promising results, including their use as prognostic factors for diffuse glioma patients. Liao et al. have demonstrated that epigenetic ages analyzes yield insights into coherent modifications of the epigenome related to different subtypes of gliomas, and have shown correlations with survival and recurrence [7]. Xiao et al. have analyzed the expression profiles, the prognostic value, and the potential mechanisms of action of aging-related genes in diffuse gliomas [8]. They designed risk scores and cluster models based on aging-related genes and glioma cases. This scoring system was correlated with malignant clinical features, poor prognosis, and genomic aberrations of aging-related oncogenes [8]. Altogether, all available data in literature highlight the impact of age on clinical presentation, location, histo-molecular subtype, neurosurgical and neuro-oncological treatments, epigenetic ages, and aging-related genes for diffuse gliomas. It appears essential to merge all these data to better define the role of age in the occurrence and evolution of diffuse gliomas. Age by itself should not be the sole criterion to guide the neuro-oncological treatment and such merge analyzes will allow to choose, on an individual basis, the best therapeutic options for a particular patient. It will contribute to improve patients’ survival and to reduce the under-treatment we observe in elderly patients.
  8 in total

1.  High-grade gliomas in adolescents and young adults highlight histomolecular differences from their adult and pediatric counterparts.

Authors:  Alexandre Roux; Johan Pallud; Raphaël Saffroy; Myriam Edjlali-Goujon; Marie-Anne Debily; Nathalie Boddaert; Marc Sanson; Stéphanie Puget; Steven Knafo; Clovis Adam; Thierry Faillot; Dominique Cazals-Hatem; Emmanuel Mandonnet; Marc Polivka; Georges Dorfmüller; Aurélie Dauta; Mathilde Desplanques; Albane Gareton; Mélanie Pages; Arnault Tauziede-Espariat; Jacques Grill; Franck Bourdeaut; François Doz; Frédéric Dhermain; Karima Mokhtari; Fabrice Chretien; Dominique Figarella-Branger; Pascale Varlet
Journal:  Neuro Oncol       Date:  2020-08-17       Impact factor: 12.300

2.  Models of epigenetic age capture patterns of DNA methylation in glioma associated with molecular subtype, survival, and recurrence.

Authors:  Peter Liao; Quinn T Ostrom; Lindsay Stetson; Jill S Barnholtz-Sloan
Journal:  Neuro Oncol       Date:  2018-06-18       Impact factor: 12.300

3.  Short-Course Radiation plus Temozolomide in Elderly Patients with Glioblastoma.

Authors:  James R Perry; Normand Laperriere; Christopher J O'Callaghan; Alba A Brandes; Johan Menten; Claire Phillips; Michael Fay; Ryo Nishikawa; J Gregory Cairncross; Wilson Roa; David Osoba; John P Rossiter; Arjun Sahgal; Hal Hirte; Florence Laigle-Donadey; Enrico Franceschi; Olivier Chinot; Vassilis Golfinopoulos; Laura Fariselli; Antje Wick; Loic Feuvret; Michael Back; Michael Tills; Chad Winch; Brigitta G Baumert; Wolfgang Wick; Keyue Ding; Warren P Mason
Journal:  N Engl J Med       Date:  2017-03-16       Impact factor: 91.245

4.  MRI Atlas of IDH Wild-Type Supratentorial Glioblastoma: Probabilistic Maps of Phenotype, Management, and Outcomes.

Authors:  Alexandre Roux; Pauline Roca; Myriam Edjlali; Kanako Sato; Marc Zanello; Edouard Dezamis; Pietro Gori; Stéphanie Lion; Ariane Fleury; Frédéric Dhermain; Jean-François Meder; Fabrice Chrétien; Emmanuèle Lechapt; Pascale Varlet; Catherine Oppenheim; Johan Pallud
Journal:  Radiology       Date:  2019-10-08       Impact factor: 11.105

5.  Recurrent glioblastomas in the elderly after maximal first-line treatment: does preserved overall condition warrant a maximal second-line treatment?

Authors:  Marc Zanello; Alexandre Roux; Renata Ursu; Sophie Peeters; Luc Bauchet; Georges Noel; Jacques Guyotat; Pierre-Jean Le Reste; Thierry Faillot; Fabien Litre; Nicolas Desse; Evelyne Emery; Antoine Petit; Johann Peltier; Jimmy Voirin; François Caire; Jean-Luc Barat; Jean-Rodolphe Vignes; Philippe Menei; Olivier Langlois; Edouard Dezamis; Antoine Carpentier; Phong Dam Hieu; Philippe Metellus; Johan Pallud
Journal:  J Neurooncol       Date:  2017-07-19       Impact factor: 4.130

Review 6.  Diffuse brainstem glioma in children: critical review of clinical trials.

Authors:  Darren Hargrave; Ute Bartels; Eric Bouffet
Journal:  Lancet Oncol       Date:  2006-03       Impact factor: 41.316

7.  Aging-related genes are potential prognostic biomarkers for patients with gliomas.

Authors:  Gelei Xiao; Xiangyang Zhang; Xun Zhang; Yuanbing Chen; Zhiwei Xia; Hui Cao; Jun Huang; Quan Cheng
Journal:  Aging (Albany NY)       Date:  2021-05-04       Impact factor: 5.682

8.  CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2013-2017.

Authors:  Quinn T Ostrom; Nirav Patil; Gino Cioffi; Kristin Waite; Carol Kruchko; Jill S Barnholtz-Sloan
Journal:  Neuro Oncol       Date:  2020-10-30       Impact factor: 12.300

  8 in total

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