z-logo
open-access-imgOpen Access
A view of the epidemiologic landscape: how population-based studies can lend novel insights regarding the pathophysiology of glioblastoma
Author(s) -
Ramya Tadipatri,
Kristopher A. Lyon,
Amir Azadi,
Ekokobe Fonkem
Publication year - 2020
Publication title -
chinese clinical oncology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.733
H-Index - 22
eISSN - 2304-3873
pISSN - 2304-3865
DOI - 10.21037/cco.2020.02.07
Subject(s) - medicine , pten , disease , population , oncology , mutation , bioinformatics , cancer research , genetics , biology , gene , apoptosis , pi3k/akt/mtor pathway , environmental health
Glioblastoma is an aggressive disease that is difficult to treat, in large part due to the high level of molecular heterogeneity that limits the utility of targeted therapies. As such, population studies have been essential in characterizing the factors that promote survival. In this review, we summarize the findings in these studies. Demographic trends, molecular markers (IDH mutation, MGMT promoter methylation, TERT promoter mutation, chromosome 1p19q codeletion, PTEN, and p53 among others), radiographic correlates (peritumoral edema, enhancement, cyst formation, necrosis, and invasion among others), nonsteroidal anti-inflammatory drug (NSAID) and statin use, and ketogenic diet have been assessed. Overall, studies have found that IDH mutation and MGMT promoter methylation are positive prognostic markers and TERT is a negative prognostic marker, although subgroup analysis has revealed differential responses. NSAID and statin use have also suggested improved survival reaching significance in some studies. Ketogenic diet has not yet been adequately assessed. Further studies to characterize the interplay of these and other genetic and environmental factors are warranted.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom