Keywords
smoking, IDH1 mutation, MGMT methylation, glioma, grading
This article is included in the Genomics and Genetics gateway.
smoking, IDH1 mutation, MGMT methylation, glioma, grading
Glioma is one of the most common central nervous system (CNS) tumors in adults, accounting for about 60% of primary brain tumors (Huang et al., 2019). The annual incidence for Caucasians and Asians is about 6 cases per 100,000 people (Hofer et al., 2014). Currently, gliomas are classified by the World Health Organization (WHO) based on histological and molecular characteristics. Histologically, gliomas can be classified into astrocytomas, oligodendrogliomas, and ependymomas. However, the WHO Classification of Tumors of the Central Nervous System in 2016, and then in 2021, combined the molecular characteristics into this classification, with one of the most important molecular characteristics used being IDH gene mutations (Louis et al., 2016, 2021). Another important marker is MGMT promoter methylation which determines patients’ response to alkylating agents such as temozolomide (Hegi et al., 2005).
IDH mutations are quite common in malignancies. In glioblastoma (GBM) itself, the role of IDH mutations was first shown by Parsons et al. (2008). Since then, many studies have shown the significance of IDH mutations in the management of gliomas due to their diagnostic, prognostic, and predictive implications (Picca et al., 2018). In fact, IDH1 mutations have been shown to be an early event in the development of glioma (Watanabe et al., 2009). The most commonly found IDH1 mutation was IDH1 R132 mutation, a missense heterozygous mutation at codon 132 of the IDH1 gene. This mutation has mostly been found in grade II and III astrocytomas and oligodendrogliomas (55–80%). IDH1 mutations are more common in secondary GBM (>80%) and much rarer in primary GBM (<10%). IDH1 mutations are associated with significantly better outcomes, with patients with IDH-mutated glioma having a longer overall survival than wild-type patients (Uno et al., 2011).
Association between smoking and glioma is not clear. Several studies showed a significant association between smoking and glioma formation, while other studies failed to show this association. A large meta-analysis involving seven cohorts and 17 case-control studies with more than 2.3 million subjects found no significant association between cigarette smoking and glioma. The metanalysis, however, showed a statistically significant increase of glioma cases in past smokers in females (RR: 1.13, p=0.046) but not in males (Li et al., 2016). Another study in Korea showed that cigarette smoking might be associated with developing malignant glioma in a dose-dependent manner (Ahn et al., 2020). This study, however, only involved malignant glioma. The association of smoking with glioma grades, in general, remains unknown.
One possible mechanism by which smoking can cause gliomas is through its effect on IDH gene mutations. An association between smoking and IDH1 mutation has been shown in several cancers. For example, smoking history is associated with IDH1 mutations in chronic myelomonocytic leukemia (CMML), myelodysplastic syndromes (MDS), and lung adenocarcinoma (Madanat et al., 2017; Toth et al., 2018). IDH1 mutations play a significant role in gliomagenesis, so knowing the association between smoking and IDH1 mutations in gliomas is crucial. Unfortunately, this association is still unclear.
Previous studies also showed the association of smoking with MGMT methylation. Studies in head and neck squamous cell carcinoma and colorectal cancer showed that methylation of MGMT was suppressed by heavy smoking (Matsuda et al., 2020). This is thought to be part of a biological defense mechanism to suppress various genetic mutations caused by smoking (Matsuda et al., 2020).
As mentioned above, smoking is associated with IDH mutations and MGMT promoter methylation in various cancers. However, these associations have never been proven in glioma. Therefore, this study aimed to examine the association between smoking, IDH mutations, and MGMT promoter methylation in patients with glioma. In addition, because IDH mutations are known to be associated with glioma grade, we also assessed the association of smoking with glioma grade.
This study used a cross-sectional design. All patients diagnosed with glioma based on pathology examination who were treated at Dr. Sardjito General Hospital (a referral hospital in Yogyakarta and Central Java region) and its network hospitals in 2010-2020 were included in this study. Only patients with complete data regarding smoking status and IDH mutations were recruited (See Underlying Data) (Dwianingsih et al., 2022). Written and verbal informed consents were obtained from all patients or family members. Glioma tissue in the form of fresh tissue and formalin-fixed paraffin-embedded (FFPE) samples were taken from the anatomical pathology laboratory and tissue bank at the Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada.
An experienced neuropathologist performed the histopathology examinations. Gliomas were classified according to the 2016 WHO classification of CNS tumors. Smoking status was obtained by history taken from the patients or their family members at the time of consent. To avoid potential bias, neither the neuropathologist analyzing the patient sample nor the physician interviewing the patient and family members were made aware of the IDH1 mutation status. Demographic and clinical data were obtained from medical records. This study was approved by the Medical and Health Research Ethics Committee, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia (KE/FK/0115/EC).
Smoking status was classified as previously reported (Ahn et al., 2020). Current smokers were patients who had smoked more than five packs (100 cigarettes) in their lifetime and were still smoking when diagnosed with glioma. Former smokers were patients who smoked more than five packs (100 cigarettes) in their lifetime but had stopped smoking when diagnosed with glioma. Never smokers were patients who had never smoked at all or had smoked but less than five packs (100 cigarettes) in their lifetime. In addition, data on total smoking duration in years and the average number of daily cigarettes consumption were collected. Total cigarette smoke was classified as < 10 cigarettes per day, 10–19 cigarettes per day, and ≥ 20 cigarettes per day (Ahn et al., 2020).
Isolation of genomic DNA from FFPE samples or fresh glioma tissue was performed. Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) was then performed to determine IDH1 mutation status. Finally, samples that did not show conclusive results on PCR-RFLP were subjected to DNA sequencing. Our previous publication described all methods (Malueka et al., 2020a).
Methylation-specific qRT-PCR was performed to identify MGMT promoter methylation (See Underlying Data) (Dwianingsih et al., 2022). First, bisulfite conversions of genomic DNA were performed, followed by quantitative real-time PCRs as previously described (Malueka et al., 2020b; Rivera et al., 2010).
Statistical tests were performed to identify the association between smoking with IDH1 gene mutation, MGMT promoter methylation, and grading in glioma. T-test or Mann-Whitney test was used to analyze numerical data using IBM SPSS Statistics version 22 (SPSS, RRID:SCR_002865). Meanwhile, for categorical variables, Chi-square or Fisher’s exact test was used. The subjects who had incomplete or missing data were not included in the analysis, as mentioned before in the inclusion criteria.
This study recruited a total of 122 patients. Detailed patients’ characteristics are shown in Table 1. According to gender groups, most patients were male (69, 56.6%). The average age at glioma diagnosis was 38.61±18.6 years old. The smoking patients were significantly older (49.09±11.5 vs. 34.4±19.3 years old, p<0.001). As many as 35 patients (28.7%) had a smoking history. Of these, only two patients were former smokers, while the rest were current smokers. For further analysis, these two groups were combined in one group (ever smokers). Most smokers were male (male vs. female smokers, 88.6% vs. 11.4%, p<0.001). In terms of intensity, most smokers (57.1%) smoke less than ten cigarettes per day (Table 2). However, most of them (68.8%) have been smoking for more than 20 years.
Variable | Total | Smoking | Not smoking | p-value |
---|---|---|---|---|
Number of patients, n (%) | 122 | 35(28.7) | 87(71.3) | |
Mean age, years (SD) | 38.61(18.6) | 49.09(11.5) | 34.40(19.3) | <0.001* |
Sex, n (%) | ||||
69(56.6) | 31(88.6) | 38(43.7) | <0.001 | |
53(43.4) | 4(11.4) | 49(56.3) | ||
Histological type, n (%) | ||||
97(79.5) | 29(82.9) | 68(78.2) | 0.239** | |
6(4.9) | 1(2.9) | 5(5.7) | ||
12(9.8) | 5(14.3) | 7(8.05) | ||
7(5.7) | 0(0) | 7(8.05) | ||
Grade, n (%) | ||||
10(8.2) | 0(0) | 10(11.5) | 0.033** | |
40(32.8) | 8(22.9) | 32(36.8) | ||
21(17.2) | 8(22.9) | 13(14.9) | ||
51(41.8) | 19(54.3) | 32(36.8) | ||
Combined grade, n (%) | ||||
46(37.7) | 7(20) | 39(44.8) | 0.01 | |
76(62.3) | 28(80) | 48(55.2) | ||
MGMT methylation | ||||
24(29.6) | 11(39.3) | 13(24.5) | 0.167 | |
57(70.4) | 17(60.7) | 40((75.5) |
Variable | Total | IDH1 mutant | IDH1 wild type | p-value |
---|---|---|---|---|
Smoking status, n(%) | ||||
35(100) | 11(31.4) | 24(65.6) | 0.038* | |
87(100) | 13(14.9) | 74(85.1) | ||
Amount of cigarettes smoked per day, n(%) | ||||
20(100) | 7(35) | 13(65) | 1** | |
14(100) | 4(28.6) | 10(71.4) | ||
1(100) | 0(0) | 1(100) | ||
Duration of smoking in years, n(%) | ||||
4(100) | 1(25) | 3(75) | 0.226** | |
6(100) | 0(0) | 6(100) | ||
22(100) | 8(36.4) | 14(63.6) |
MGMT methylation analysis using methylation-specific real-time PCR was performed in 81 patients. Methylation of MGMT promoters was found in 24 patients (29.6%). No significant difference was found in the proportion of patients with MGMT methylation between the smoking and non-smoking group (39.3 vs. 24.5%, p=0.167).
According to the WHO grading, the most commonly found glioma was grade IV (41.8%), followed by grade II (32.8%), grade III (17.2%), and grade I (8.2%). Smoking history was significantly associated with glioma grading. Smoking patients have a significantly higher proportion of high-grade glioma than non-smokers (80% vs. 55.2%, p=0.01).
Among 122 patients, 24 (19.7%) of them carried IDH1 mutation. Smoking patients have a significantly higher proportion of IDH1 mutation compared with non-smokers (31.4 vs. 14.9 %, p<0.001). However, no significant association was found between intensity and duration of smoking with IDH1 mutation and glioma grade (Tables 2 and 3).
Variable | Total | Low grade glioma | High grade glioma | p-value |
---|---|---|---|---|
Amount of cigarettes smoked per day | ||||
20(100) | 6(30) | 14(70) | 0.358* | |
14(100) | 1(7.1) | 13(92.9) | ||
1(100) | 0(0) | 1(100) | ||
Duration of smoking, years | ||||
4(100) | 1(25) | 3(75) | 1* | |
6(100) | 1(16.7) | 5(83.3) | ||
22(100) | 5(22.7) | 17(77.3) |
This study showed a significant association between smoking and IDH1 mutation in glioma. A higher proportion of IDH1 mutation was found in smokers compared to non-smokers. The association of smoking with IDH1 mutation in gliomas was previously unclear. Several studies have reported a possible association between smoking and IDH mutations in other types of cancers. For example, smoking has been associated with IDH1 mutations in patients with lung adenocarcinoma, MDS, and CMML (Madanat et al., 2017; Rodriguez et al., 2020; Toth et al., 2018). In these studies, smoking intensity seemed to play an important role. In the case of MDS and CMML, an association of smoking with IDH1 mutations was identified in smokers who smoke more than two packs per day or more than 40 pack-years (Madanat et al., 2017). Our study, however, did not find this association between smoking intensity and IDH1 mutation (Table 2).
The association between smoking and glioma grade is unclear. A study from Korea reported a higher risk of malignant glioma formation in smokers (Hazard ratio (HR) 1.22) compared to never smokers. This risk was greater for those who smoked ≥20 cigarettes a day (HR = 1.50) (Ahn et al., 2020). These results suggest that cigarette smoking may be associated with the development of malignant glioma in a dose-dependent manner (Ahn et al., 2020). Our study also showed a significant association of smoking with a higher glioma grade. Smoking patients in our study have a significantly higher proportion of high-grade glioma than non-smokers (80% vs. 55.2%, p= 0.01). However, we did not find a significant association between smoking intensity and glioma grading (Table 3).
Several mechanisms have been proposed to explain the association between smoking and glioma. Smoking can induce several mutational signatures, including the IDH mutation. The mutations can occur in tissues exposed to smoking directly or indirectly (Ahn et al., 2020; Madanat et al., 2017). Because the IDH mutations are early events in gliomagenesis, the finding of an association between smoking and IDH mutations suggests a possible role for smoking in glioma formation (Turkalp et al., 2014). Recent studies showed that smoking could breach the blood-brain barrier by damaging endothelial tight junctions. This may facilitate the penetration of carcinogens into the brain (Ahn et al., 2020). Tobacco products have been shown in an animal experiment to produce exogenous N-nitroso compounds, which have been shown to induce glioma. More than 60 known carcinogens have been found in cigarette smoke, including polycyclic aromatic hydrocarbons (PAHs), aromatic amines, and nitrosamines; all play a key role in tumorigenesis. Nicotine has also been shown to increase the proliferation and migration of human glioma cells (Grando, 2014). Indeed, a recent experimental study has shown that nicotine-induced stimulation of malignancy in glioma cells (Kalita et al., 2021). Therefore, nicotine is not only the main addictive compound that keeps smokers in their habits but also makes a genotoxic contribution to cancer pathogenesis (Grando, 2014).
Previous studies have shown an association between smoking and methylation of MGMT promoters. A study by Pulling et al. in lung adenocarcinoma showed that smokers had decreased frequency of having a methylated MGMT than non-smokers (Pulling et al., 2003). Another study in head and neck squamous cell carcinoma showed that methylation of MGMT was suppressed by heavy smoking (Matsuda et al., 2020). A similar study in colorectal cancer showed that smoking is associated with a lower level of MGMT hypermethylation (Matsuda et al., 2020). These studies indicated that methylation of MGMT was suppressed by smoking. This is thought to be part of a biological defense mechanism. Several mutagens in tobacco, namely, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone, N′-nitrosonornicotine, and N-dimethylnitrosamine attack DNA at the O6-position of guanine. As a defense mechanism, the resulting O6-alkylguanine adducts will be repaired by the MGMT enzyme (Christmann & Kaina, 2012). Therefore, upregulation of MGMT through suppression of methylation occurred to facilitate this repair mechanism (Matsuda et al., 2020). However, our study did not show an association between smoking and MGMT methylation status. Another study in patients with squamous cell carcinoma of head and neck showed a similar result with our study, namely no association between smoking and MGMT promoter methylation was found (Puri et al., 2005). Further research is needed to determine the cause of this difference in results.
This study has several limitations. The first limitation is the small number of former smokers (2 patients) which required us to analyze current and former smokers in the same group, namely ever smokers. The second limitation is that because the patients included in this study were only patients who had undergone surgery, the available data may not represent the general glioma population. Finally, the third limitation is the possibility of recall bias when the patient or family was asked about smoking behavior.
In conclusion, this study showed that smoking is associated with IDH1 mutations and higher grades in glioma patients. This finding underlined the importance of smoking as a possible risk factor for glioma.
Figshare: Underlying data for ‘Associations among smoking, IDH mutations, MGMT promoter methylation, and grading in glioma a cross-sectional study’, https://www.doi.org/10.6084/m9.figshare.19337141 (Dwianingsih et al., 2022).
This project contains the following underlying data:
• Demographic, clinical and IDH mutation and MGMT methylation of Glioma patient in Dr. Sardjito General Hospital
Data are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).
Conceptualization: RGM, RAH, EKD. Data Curation: RAH, ASW, EB. Formal Analysis: MA, CMS. Funding Acquisition: RGM, EKD. Investigation: MA, CMS. Methodology: KD, AA, MA, CMS. Project Administration: EKD, RGM. Resources: KD, AA, RAH, ASW, EB. Software: ASW, EB. Supervision: RGM, RAH, EKD. Validation: EKD, RGM. Visualization: KD, AA. Writing – Original Draft Preparation: RGM, MA, CMS. Writing – Review & Editing: RGM, EKD.
We would like to thank Klinik Bahasa of Faculty of Medicine, Public Health and Nursing, UGM for assistance in language editing of this manuscript.
Views | Downloads | |
---|---|---|
F1000Research | - | - |
PubMed Central
Data from PMC are received and updated monthly.
|
- | - |
Is the work clearly and accurately presented and does it cite the current literature?
Partly
Is the study design appropriate and is the work technically sound?
Partly
Are sufficient details of methods and analysis provided to allow replication by others?
Partly
If applicable, is the statistical analysis and its interpretation appropriate?
No
Are all the source data underlying the results available to ensure full reproducibility?
Yes
Are the conclusions drawn adequately supported by the results?
Partly
References
1. Braganza M, Rajaraman P, Park Y, Inskip P, et al.: Cigarette smoking, alcohol intake, and risk of glioma in the NIH-AARP Diet and Health Study. British Journal of Cancer. 2014; 110 (1): 242-248 Publisher Full TextCompeting Interests: No competing interests were disclosed.
Reviewer Expertise: Neuro-oncology
Is the work clearly and accurately presented and does it cite the current literature?
Partly
Is the study design appropriate and is the work technically sound?
Yes
Are sufficient details of methods and analysis provided to allow replication by others?
Yes
If applicable, is the statistical analysis and its interpretation appropriate?
Yes
Are all the source data underlying the results available to ensure full reproducibility?
Partly
Are the conclusions drawn adequately supported by the results?
Partly
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Pain management
Alongside their report, reviewers assign a status to the article:
Invited Reviewers | ||
---|---|---|
1 | 2 | |
Version 1 29 Apr 22 |
read | read |
Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list:
Sign up for content alerts and receive a weekly or monthly email with all newly published articles
Already registered? Sign in
The email address should be the one you originally registered with F1000.
You registered with F1000 via Google, so we cannot reset your password.
To sign in, please click here.
If you still need help with your Google account password, please click here.
You registered with F1000 via Facebook, so we cannot reset your password.
To sign in, please click here.
If you still need help with your Facebook account password, please click here.
If your email address is registered with us, we will email you instructions to reset your password.
If you think you should have received this email but it has not arrived, please check your spam filters and/or contact for further assistance.
Comments on this article Comments (0)