H3K27M-mutant Diffuse Midline Gliomas should be Further Molecularly Stratified: An Integrated Analysis of 669 Patients

doi:10.21203/rs.3.rs-949930/v1

Download PDF

Research Article

H3K27M-mutant Diffuse Midline Gliomas should be Further Molecularly Stratified: An Integrated Analysis of 669 Patients

https://doi.org/10.21203/rs.3.rs-949930/v1

This work is licensed under a CC BY 4.0 License

Journal Publication

published 18 Nov, 2021

Read the published version in Journal of Neuro-Oncology →

You are reading this latest preprint version

Introduction: H3K27M-mutated diffuse midline gliomas (H3-DMGs) are aggressive tumors with a fatal outcome. This study integrating individual patient data (IPD) from published studies aimed to investigate the prognostic impact of different genetic alterations on survival of these patients.

Methods: We accessed PubMed and Web of Science to search for relevant articles. Studies were included if they have available data of follow-up and additional molecular investigation of H3-DMGs. For survival analysis, Kaplan-Meier analysis and Cox regression models were utilized, and corresponding hazard ratios (HR) and 95% confidence intervals (CI) were computed to analyze the impact of genetic events on overall survival (OS).

Result: We included 30 studies with 669 H3-DMGs. TP53 mutations were the most common second alteration among these neoplasms. In univariate Cox regression model, TP53 mutation was an indicator of shortened survival (HR = 1.446; 95% CI = 1.143-1.829) whereas ACVR1 (HR = 0.712; 95% CI = 0.518-0.976) and FGFR1 mutations (HR = 0.408; 95% CI = 0.208-0.799) conferred prolonged survival. In addition, ATRX loss was also associated with a better OS (HR = 0.620; 95% CI = 0.386-0.996). Adjusted for age, gender, tumor location, and the extent of resection, the presence of TP53 mutations, the absence of ACVR1 or FGFR1 mutations remained significantly poor prognostic factors.

Conclusions: We outlined the prognostic importance of additional genetic alterations in H3-DMGs and recommended that these neoplasms should be further molecularly segregated. It could help neuro-oncologists better evaluate the risk stratification of patients and consider pertinent treatments.

Neurology

Oncology

Histone

H3 K27M

H3F3A

HIST1H3B

diffuse midline glioma

survival

Diffuse midline gliomas are predominantly seen in children and likely have a lethal prognosis. These tumors typically arise in the pons, thalamus, or spinal cord and have a dismal survival of 12-18 months ¹. About 70-80% of them carry missense mutations in the Histone H3 genes, including the HIST1H3B/C (H3.1), HIST2H3A/C (H3.2), or H3F3A (H3.3) ^{2, 3}. The H3.3 protein share some similarities and differences in functions with its H3.1 and H3.2 counterparts. These proteins maintain the core function of the nucleosome. H3.3 is accumulated into the transcriptionally active regions to replace nucleosomes ⁴ whereas H3.1 and H3.2 are coupled to DNA synthesis ^{5, 6}. The most common H3 mutations are missense mutations of G34R/V and K27M ². These neoplasms are considered World Health Organization (WHO) grade IV, implying their advanced aggressiveness.

Published studies have established an adverse prognosis of midline gliomas harboring H3K27M mutations as compared to wild-type (wt) tumors ^{2, 3, 7, 8}. In addition, the presence of H3K27M mutations is also an indicator of shortened survival among IDH-wt gliomas and GBMs ^9–11. It is still debated as to whether all H3K27M-mutant diffuse midline gliomas (H3-DMG) have a universally poor prognosis, and reports have suggested that these tumors are clinically heterogeneous ⁸. It is of clinical importance to further stratify these neoplasms molecularly to better predict patient outcomes and make appropriate therapeutic decisions. In this study, we integrated individual patient data (IPD) from published studies and examined the prognostic impact of various genetic biomarkers in H3-DMGs.

Search term and literature search

We accessed PubMed and Web of Science to search for relevant articles from inception to June 2021 using the following search term: Glioma AND (H3K27M OR H3-K27M OR H3 K27M OR H3F3A OR HIST1H3B OR HIST1H3C). We followed the recommendations of the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement ¹².

Selection criteria and abstract screening

Duplicates from the two electronic databases were removed after results are merged and imported into EndNote (Clarivate, PA, USA). Two reviewers independently screened the title and abstract of the articles using the designated selection criteria. Studies were included if they fulfill all following criteria: (i) studies providing IPD of H3-DMG with follow-up data available and (ii) studies with data of at least one genetic event of H3-DMGs available. We excluded studies if: (i) not relevant to research aims; (ii) studies without data of K27M mutations; (iii) case reports; (iv) reviews, theses, or books; (v) conference or proceeding papers; or (vi) studies with duplicated populations.

Full-text screening and data extraction

Two reviewers independently reviewed the full-text of potential studies and extracted data into a standardized excel form. The following IPD were extracted from the articles: authors, institution, country, year of publication, study period, patient identification number, H3 genotypes, detection methods, demographic information, tumor location, WHO grades, treatments, overall survival (OS) time, OS status, and genetic alterations of H3-DMGs. We subsequently removed cases in non-midline locations or cases without follow-up data among the extracted datasets.

Statistical analyses

For studies with potentially overlapping populations, we selected the study with the largest sample size for analysis. Kaplan-Meier analysis and Cox proportional hazards model were conducted to assess the impact of various clinical and molecular parameters on survival of H3-DMGs. The deviance residuals and the dfbeta values were used to examine influential observations. Hazard ratios (HR) are presented as mean and 95% confidence interval (CI). A two-sided p-value of < 0.05 was considered statistically significant. The statistical analyses were performed using the R software, version 3.6.1 (The R Foundation, Vienna, Austria).

We identified 714 articles for the title and abstract screening and included 65 studies for full-text reading. Subsequently, 35 studies were further excluded due to missing survival data, without IPD, without genetic event investigation, or duplicated populations. Finally, we included 30 studies with 669 H3-DMGs for integrated analyses ^{3, 7, 8, 11, 13–38} (Fig. 1). The characteristics of 30 included studies are presented in Fig. S1.

Clinical characteristics of H3-DMGs

The median patient age was 11 years (range, 1-82) and there was no gender predilection. Genetically, H3.3 K27M mutation was predominant, followed by H3.1; only 2 H3.2 K27M mutations were found. Stratified by tumor locations, 91.3% of cases were intracranial midline gliomas with pons and thalamus being the most common sites, while a subset of cases (8.7%) located in the spinal cord. More than 50% of patients died within the first year of follow-up and the median OS was 11.6 months. The clinical features of H3-DMGs are shown in Table S1.

Genetic alterations of H3-DMGs

Table S2 lists the prevalence of concurrent genetic alterations in H3-DMGs. Mutations in the TP53 genes were the most common genetic event, accounting for more than 50% of cases. Other common genomic events included ATRX loss/mutations, PDGFRA amplification, ACVR1, PIK3CA, FGFR1, and PPM1D mutations, and MGMT methylation. Other rare somatic mutations with a prevalence of less than 10% were BRAF, NF1, PDGFRA, PIK3R1, PTEN, and TERT mutations. Genetic variations in the EGFR were also uncommon.

Impact of genetic events on the prognosis of H3-DMGs

There was no statistical difference in OS of patients with H3.3 versus H3.1 K27M mutations (HR = 1.083; 95% CI = 0.833-1.408). On the other hand, the presence of TP53 mutations were associated with a shorter OS (median OS of 9.1 versus 12.0 months; HR = 1.446; 95% CI = 1.143-1.829) (Fig. 1) whereas ACVR1 (median OS of 14.7 versus 9.9 months; HR = 0.712; 95% CI = 0.518-0.976) (Fig. 2) and FGFR1 mutations (median OS of 14.2 versus 10.9 months; HR = 0.408; 95% CI = 0.799) (Fig. 3) conferred a prolonged survival. ATRX loss also defined a subgroup of H3K27M-mutant gliomas with a favorable survival (median OS of 10.8 versus 8.7 months; HR = 0.620; 95% CI = 0.386-0.996). Other genetic biomarkers had no significant impact on patient outcome (Table 2).

Table 1

Characteristics of all included studies
Study	Country	No. of H3K27M gliomas	H3 mutation detection methods	Mean age (SD)	Median follow-up (months)
Aihara 2014	Japan	10	Sanger	34.2 (9.76)	10.2
Alvi 2019	USA	6	Sanger	30.5 (9.83)	10.5
Bruzek 2020	USA	9	Sanger	10.0 (4.66)	14.0
Buczkowicz 2014	Canada	23	NGS	6.3 (2.70)	12.0
Castel 2015	France	77	NGS	7.5 (3.41)	10.4
Daoud 2018	USA	6	IHC	38.5 (11.04)	7.8
Dono 2020	USA	3	NGS	31.3 (7.64)	16.7
Dufour 2020	France	35	NGS	N/A	8.0
Eschbacher 2021	USA	6	NGS/IHC	37.2 (17.13)	14.9
Garibotto 2020	Italy	12	NGS	8.7 (3.89)	9.5
Gojo 2020	Austria & Czech	18	IHC	8.3 (4.56)	17.2
Hoffman 2016	USA	7	IHC	8.3 (7.36)	13.4
Karlowee 2019	Japan	12	IHC	27.9 (15.34)	14.6
Korshunov 2015	Russia	68	Sanger	10.1 (4.29)	12.0
Mackay 2017	Multi	10	NGS/Sanger	10.4 (4.04)	9.0
Mackay 2018	Multi	22	Sanger	11.9 (3.44)	12.0
Meyronet 2017	France	21	NGS	35.3 (16.95)	10.0
Mueller 2019	USA	13	Sanger	7.4 (3.25)	13.1
Nomura 2017	Japan	3	Sanger	41.7 (22.81)	11.3
Pan 2019	China	32	Droplet digital PCR	20.2 (17.25)	9.4
Picca 2018	France	37	NGS	36.7 (15.39)	16.2
Ryall 2016	Canada	16	IHC/Pyrosequencing	10.4 (3.23)	12.3
Schwartzentruber 2012	Multi	3	NGS	11.3 (1.53)	7.0
Sturm 2012	Germany & Canada	12	Sanger	10.7 (4.52)	12.5
Taylor 2014	France & Spain	35	Sanger	7.2 (2.39)	13.1
Wang 2018	China	55	WGS/WES	26.8 (17.87)	6.0
Wang 2020	China	43	Sanger	35.4 (19.39)	8.0
Wu 2014	USA	51	WGS/WES	8.0 (4.34)	10.2
Yi 2019	Republic of Korea	20	Sanger	35.5 (13.93)	25.5
Zhou 2021	China	4	Multiplexed PCR	N/A	7.4
Abbreviations: IHC, immunohistochemistry; N/A, not available; NGS, next-generation sequencing; SD, standard deviation; WES, whole-exome sequencing; WGS, whole-genome sequencing;

Table 2

The impact of genetic markers on overall survival of H3K27M-mutant midline gliomas (Univariate Cox proportional hazards)
Genetic markers	Hazard ratio (95% CI)	p-value*
H3.3 vs H3.1	1.083 (0.833-1.408)	0.552
ACVR1 mutations	0.712 (0.518-0.976)	0.035
ATRX loss	0.620 (0.386-0.996)	0.048
ATRX mutations	1.105 (0.757-1.612)	0.606
BRAF mutations	1.154 (0.646-2.059)	0.629
EGFR amplification	1.565 (0.579-4.232)	0.377
EGFR mutations	0.863 (0.317-2.348)	0.773
FGFR1 mutations	0.408 (0.208-0.799)	0.009
MGMT methylation	1.044 (0.638-1.709)	0.864
NF1 mutations	0.619 (0.331-1.159)	0.134
PDGFRA amplification	1.344 (0.980-1.844)	0.066
PDGFRA mutations	1.457 (0.823-2.581)	0.196
PIK3CA mutations	0.778 (0.530-1.143)	0.201
PIK3R1 mutations	1.347 (0.761-2.387)	0.307
PTEN mutations	1.302 (0.524-3.232)	0.571
PPM1D mutations	0.680 (0.408-1.133)	0.568
TERT mutations	0.934 (0.376-2.318)	0.882
TP53 mutations	1.446 (1.143-1.829)	0.002

Adding TP53, ACVR1, FGFR1 mutations, and ATRX loss alternately into a multivariate Cox regression model adjusted for age, gender, tumor sites, and the extent of surgical resection, the presence of TP53 (HR = 1.759; 95% CI = 1.087-2.844; p = 0.021), ACVR1 (HR = 0.646; 95% CI = 0.457-0.914; p = 0.014), or FGFR1 mutations (HR = 0.134; 95% CI = 0.028-0.634; p = 0.011) remained independent prognostic markers for patient survival. However, ATRX loss had no effect on patient outcome in the multivariate analysis (HR = 0.624; 95% CI = 0.344-1.133; p = 0.121).

Diffuse midline gliomas are lethal neoplasms because of their infiltrative nature and difficulty to achieve gross tumor removal as well as resistance to conventional therapy. Over the past few decades, patient survival remains unchanged despite recent advances in understanding their biology and genetic landscape. Based on their aggressiveness, diffuse midline gliomas can range from WHO grade II to IV, but they have always been considered grade IV clinically because of their universally poor prognosis ^{39, 40}. More recently, landmark studies demonstrated that histone mutations are the most common genetic marker of these tumors and are associated with a poor outcome regardless of their primary location ^{2, 41, 42}; there is also increasing evidence that H3K27M-mutant gliomas are clinically and prognostically heterogeneous ^{8, 19, 43}. Therefore, further segregation of H3K27M tumors into subgroups would facilitate a refined assessment of natural history and risk profiling. Our study demonstrated several genetic markers that are of clinical importance.

TP53 mutations, encoding the TP53 protein, have long been known to be the driver mutation of many cancers, including brain tumors ⁴⁴. Notably, TP53 and H3K27M mutations are prevalent among diffuse midline gliomas and GBMs and more than half of H3-DMGs concurrently harbor TP53 mutations ^{2, 36}. TP53 mutations were found to be associated with H3.3 rather than H3.1 K27M mutations ^{8, 36, 45}. Experimental studies of diffuse intrinsic pontine gliomas (DIPG) demonstrated that H3K27M mutations are early recurrent mutations and subsequently accompanied by an obligate partner mutation of either the growth factor signaling (e.g., RAS and PI3K), RB1, or TP53 pathways ⁴⁶. Furthermore, studies reported that mutations in the TP53 tumor suppressor gene could play a role in tumor resistance against radiotherapy in DIPG cell models ⁴⁷. Clinically, TP53 mutations were found to worsen survival of DIPG patients and reduce response to radiation treatment compared to TP53-wt DIPGs ⁴⁷. However, the impact of the parallel occurrence of TP53 and H3K27M mutation in midline gliomas warrants further investigation. Several studies have reported a potential link of TP53 mutations with adverse prognosis in H3K27M-mutated tumors ^{8, 36, 43} whereas other studies failed to establish this association ^{2, 3, 19, 32, 33}. Our study confirmed the association of TP53 mutations with poor survival of H3-DMGs.

In contrast to TP53 aberration, mutations in ACVR1 and FGFR1 are more frequently associated with H3.1 K27M mutations and lower-grade histology ^{25, 30, 33, 43}. ACVR1 and FGFR1 mutations have been proved to be independent predictors of prolonged survival in midline gliomas ^{16, 30}. These two mutations are almost mutually exclusive with TP53 mutations but could co-occur with H3 mutations in a subset of midline gliomas ^{33, 43}. The concomitant occurrence of H3 and FGFR1/ACVR1 may complicate the diagnostic decisions towards an aggressive or favorable tumor, particularly in small biopsies in which the tumor tissue is too small for low- and high-grade discrimination. Therefore, further investigation into the effects of ACVR1/FGFR1 alterations in H3-DMGs is essential. This study integrating 264 and 153 analyzed cases for ACVR1 and FGFR1 alterations demonstrated that these two mutations were correlated with a superior outcome. Because TP53, ACVR1, and FGFR1 mutations mostly do not co-occur with each other, we did not analyze them in a multivariate model. Multivariate analyses further confirm the independent prognostic effects of these mutations regardless of age, gender, tumor locations, and resection methods. These findings would be helpful for further risk stratification of midline gliomas and may open up potential possibilities of targeted therapies. Our results support additional risk stratification of H3-DMGs to accurately refine the prognosis of this entity. The rapid development of next-generation sequencing and other advanced molecular techniques could help improve patient care and finalize the standard treatments for these malignant gliomas.

ATRX deficiency is a common event in IDH-mutated but rarely occurs in IDH-wt cortical gliomas ⁴⁸. Astrocytic tumors with ATRX loss have a significantly better prognosis than patients who express ATRX ⁴⁸. In IDH-wt diffuse midline gliomas, however, ATRX loss is more frequently observed in about 25-40% of cases ^{8, 34}. Our results showed that the presence of ATRX loss alone was also a positive marker of midline glioma survival. However, after adjusting for confounding factors, we could not reproduce the significant association of this biomarker and patient survival. A few studies reported PDGFRA amplification as a marker for unfavorable outcome of diffuse midline glioma ^{19, 25}. Our integrated analysis revealed a similar trend but our result did not reach statistical significance. Other mutations of the MAPK pathway including BRAF mutation have been correlated with favorable survival in glioma patients ^{49, 50}. BRAF mutation is very rare among H3-DMGs and we did not uncover any meaningful association of this mutation with patient survival. Unlike in IDH-wt cortical GBMs ^{51, 52}, EGFR alterations and TERT promoter mutations were uncommon in midline gliomas and had no impact on patient survival. Genetic alterations of the PI3K/AKT pathway such as PIK3CA, PIK3R1, or PTEN mutations showed no effects on patient outcome. Castel et al. reported a prolonged survival of H3.1 K27M-mutant tumors in comparison to H3.3-mutant but this finding was not confirmed in our study ⁸.

This integrated analysis demonstrated the prognostic importance of various genetic biomarkers in a large population of H3-DMGs. In the 2021 WHO classification of central nervous system tumors, the following key biomarkers have been recommended to better stratify the survival of H3-DMGs including TP53, ACVR1, PDGFRA, EGFR, and EZHIP ⁵³. This recommendation is primarily based on published institutional results and our pooled data from 30 studies demonstrated that the prognostic values of PDGFRA and EGFR alterations are not significant. On the other side, we highlighted that FGFR1 mutation and ATRX loss could be used to further stratify the H3-DMGs. However, our study has limitations. Firstly, most of the included studies relied on retrospective patient selection so we could not avoid the risk of selection bias stemming from these studies. Next, important clinical covariates such as radiation and chemotherapy administration, and chemotherapy regimen detail were missing in over 50% of the included studies so we could not include them in the multivariate models. Finally, the prevalence and identification of genetic markers could be affected by the application of different detection methods among the included studies. Prospective multicenter studies with a large sample size are needed to confirm our study findings and refine H3-DMGs into different prognostic subgroups.

In summary, our study demonstrated several important molecular markers that can influence the survival outcome of H3-DMGs including TP53, ACVR1, FGFR1 mutations, and ATRX loss. Our results suggested that these aggressive gliomas do not have a universally dismal survival and should be further routinely molecularly stratified to better predict patient clinical course and consider necessary treatment strategies.

Funding

This study receives no funding support.

Conflicts of interest

The authors declare no conflicts of interest.

Ethics approval and consent to participate

Not applicable

Consent for publication

Not applicable

Data availability statement

Not applicable

Authors’ contributions

HGV: conceptualization, data curation, formal analysis, investigation, methodology, project administration, software, validation, writing-review, and editing.

HTL: data curation, formal analysis, investigation, methodology, writing-review.

TNMN: data curation, formal analysis, investigation, methodology, writing-review.

KMF: data curation, formal analysis, investigation, methodology, project administration, validation, writing-review, and editing.

JDB: data curation, formal analysis, investigation, methodology, project administration, validation, writing-review, and editing.

RMK: data curation, formal analysis, investigation, methodology, project administration, validation, writing-review, and editing.

IFD: data curation, formal analysis, investigation, methodology, project administration, validation, writing-review, editing, and supervision.

All authors have read and approved the manuscript.

Acknowledgments

Not applicable

1. Louis DN, Giannini C, Capper D, et al. cIMPACT-NOW update 2: diagnostic clarifications for diffuse midline glioma, H3 K27M-mutant and diffuse astrocytoma/anaplastic astrocytoma, IDH-mutant. Acta Neuropathol. 2018;135: 639-642.

2. Khuong-Quang DA, Buczkowicz P, Rakopoulos P, et al. K27M mutation in histone H3.3 defines clinically and biologically distinct subgroups of pediatric diffuse intrinsic pontine gliomas. Acta Neuropathol. 2012;124: 439-447.

3. Sturm D, Witt H, Hovestadt V, et al. Hotspot mutations in H3F3A and IDH1 define distinct epigenetic and biological subgroups of glioblastoma. Cancer Cell. 2012;22: 425-437.

4. Ray-Gallet D, Woolfe A, Vassias I, et al. Dynamics of histone H3 deposition in vivo reveal a nucleosome gap-filling mechanism for H3.3 to maintain chromatin integrity. Mol Cell. 2011;44: 928-941.

5. Yuen BT, Knoepfler PS. Histone H3.3 mutations: a variant path to cancer. Cancer Cell. 2013;24: 567-574.

6. Tagami H, Ray-Gallet D, Almouzni G, Nakatani Y. Histone H3.1 and H3.3 complexes mediate nucleosome assembly pathways dependent or independent of DNA synthesis. Cell. 2004;116: 51-61.

7. Mackay A, Burford A, Molinari V, et al. Molecular, Pathological, Radiological, and Immune Profiling of Non-brainstem Pediatric High-Grade Glioma from the HERBY Phase II Randomized Trial. Cancer Cell. 2018;33: 829-842.e825.

8. Castel D, Philippe C, Calmon R, et al. Histone H3F3A and HIST1H3B K27M mutations define two subgroups of diffuse intrinsic pontine gliomas with different prognosis and phenotypes. Acta Neuropathol. 2015;130: 815-827.

9. Vuong HG, Tran TTK, Ngo HTT, et al. Prognostic significance of genetic biomarkers in isocitrate dehydrogenase-wild-type lower-grade glioma: the need to further stratify this tumor entity - a meta-analysis. Eur J Neurol. 2019;26: 379-387.

10. Aibaidula A, Chan AK, Shi Z, et al. Adult IDH wild-type lower-grade gliomas should be further stratified. Neuro Oncol. 2017;19: 1327-1337.

11. Korshunov A, Ryzhova M, Hovestadt V, et al. Integrated analysis of pediatric glioblastoma reveals a subset of biologically favorable tumors with associated molecular prognostic markers. Acta Neuropathol. 2015;129: 669-678.

12. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6: e1000097.

13. Aihara K, Mukasa A, Gotoh K, et al. H3F3A K27M mutations in thalamic gliomas from young adult patients. Neuro Oncol. 2014;16: 140-146.

14. Alvi MA, Ida CM, Paolini MA, et al. Spinal cord high-grade infiltrating gliomas in adults: clinico-pathological and molecular evaluation. Mod Pathol. 2019;32: 1236-1243.

15. Bruzek AK, Ravi K, Muruganand A, et al. Electronic DNA Analysis of CSF Cell-free Tumor DNA to Quantify Multi-gene Molecular Response in Pediatric High-grade Glioma. Clin Cancer Res. 2020;26: 6266-6276.

16. Buczkowicz P, Hoeman C, Rakopoulos P, et al. Genomic analysis of diffuse intrinsic pontine gliomas identifies three molecular subgroups and recurrent activating ACVR1 mutations. Nat Genet. 2014;46: 451-456.

17. Daoud EV, Rajaram V, Cai C, et al. Adult Brainstem Gliomas With H3K27M Mutation: Radiology, Pathology, and Prognosis. J Neuropathol Exp Neurol. 2018;77: 302-311.

18. Dono A, Takayasu T, Ballester LY, Esquenazi Y. Adult diffuse midline gliomas: Clinical, radiological, and genetic characteristics. J Clin Neurosci. 2020;82: 1-8.

19. Dufour C, Perbet R, Leblond P, et al. Identification of prognostic markers in diffuse midline gliomas H3K27M-mutant. Brain Pathol. 2020;30: 179-190.

20. Eschbacher KL, Ida CM, Johnson DR, et al. Diffuse Gliomas of the Brainstem and Cerebellum in Adults Show Molecular Heterogeneity. Am J Surg Pathol. 2021.

21. Garibotto F, Madia F, Milanaccio C, et al. Pediatric Diffuse Midline Gliomas H3 K27M-Mutant and Non-Histone Mutant Midline High-Grade Gliomas in Neurofibromatosis Type 1 in Comparison With Non-Syndromic Children: A Single-Center Pilot Study. Front Oncol. 2020;10: 795.

22. Gojo J, Pavelka Z, Zapletalova D, et al. Personalized Treatment of H3K27M-Mutant Pediatric Diffuse Gliomas Provides Improved Therapeutic Opportunities. Front Oncol. 2019;9: 1436.

23. Hoffman LM, DeWire M, Ryall S, et al. Spatial genomic heterogeneity in diffuse intrinsic pontine and midline high-grade glioma: implications for diagnostic biopsy and targeted therapeutics. Acta Neuropathol Commun. 2016;4.

24. Karlowee V, Amatya VJ, Takayasu T, et al. Immunostaining of Increased Expression of Enhancer of Zeste Homolog 2 (EZH2) in Diffuse Midline Glioma H3K27M-Mutant Patients with Poor Survival. Pathobiology. 2019;86: 152-161.

25. Mackay A, Burford A, Carvalho D, et al. Integrated Molecular Meta-Analysis of 1,000 Pediatric High-Grade and Diffuse Intrinsic Pontine Glioma. Cancer Cell. 2017;32: 520-537.e525.

26. Meyronet D, Esteban-Mader M, Bonnet C, et al. Characteristics of H3 K27M-mutant gliomas in adults. Neuro Oncol. 2017;19: 1127-1134.

27. Mueller S, Jain P, Liang WS, et al. A pilot precision medicine trial for children with diffuse intrinsic pontine glioma-PNOC003: A report from the Pacific Pediatric Neuro-Oncology Consortium. Int J Cancer. 2019;145: 1889-1901.

28. Nomura M, Mukasa A, Nagae G, et al. Distinct molecular profile of diffuse cerebellar gliomas. Acta Neuropathol. 2017;134: 941-956.

29. Pan C, Diplas BH, Chen X, et al. Molecular profiling of tumors of the brainstem by sequencing of CSF-derived circulating tumor DNA. Acta Neuropathol. 2019;137: 297-306.

30. Picca A, Berzero G, Bielle F, et al. FGFR1 actionable mutations, molecular specificities, and outcome of adult midline gliomas. Neurology. 2018;90: e2086-e2094.

31. Ryall S, Krishnatry R, Arnoldo A, et al. Targeted detection of genetic alterations reveal the prognostic impact of H3K27M and MAPK pathway aberrations in paediatric thalamic glioma. Acta Neuropathol Commun. 2016;4: 93.

32. Schwartzentruber J, Korshunov A, Liu XY, et al. Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma. Nature. 2012;482: 226-231.

33. Taylor KR, Mackay A, Truffaux N, et al. Recurrent activating ACVR1 mutations in diffuse intrinsic pontine glioma. Nat Genet. 2014;46: 457-461.

34. Wang L, Li Z, Zhang M, et al. H3 K27M-mutant diffuse midline gliomas in different anatomical locations. Hum Pathol. 2018;78: 89-96.

35. Wang Y, Feng LL, Ji PG, et al. Clinical Features and Molecular Markers on Diffuse Midline Gliomas With H3K27M Mutations: A 43 Cases Retrospective Cohort Study. Front Oncol. 2020;10: 602553.

36. Wu G, Diaz AK, Paugh BS, et al. The genomic landscape of diffuse intrinsic pontine glioma and pediatric non-brainstem high-grade glioma. Nat Genet. 2014;46: 444-450.

37. Yi S, Choi S, Shin DA, et al. Impact of H3.3 K27M Mutation on Prognosis and Survival of Grade IV Spinal Cord Glioma on the Basis of New 2016 World Health Organization Classification of the Central Nervous System. Neurosurgery. 2019;84: 1072-1081.

38. Zhou C, Zhao H, Yang F, et al. Clinical and Genetic Features of Brainstem Glioma in Adults: A Report of 50 Cases in a Single Center. J Clin Neurol. 2021;17: 220-228.

39. Buczkowicz P, Bartels U, Bouffet E, Becher O, Hawkins C. Histopathological spectrum of paediatric diffuse intrinsic pontine glioma: diagnostic and therapeutic implications. Acta Neuropathol. 2014;128: 573-581.

40. Mosaab A, El-Ayadi M, Khorshed EN, et al. Histone H3K27M Mutation Overrides Histological Grading in Pediatric Gliomas. Sci Rep. 2020;10: 8368.

41. Karremann M, Gielen GH, Hoffmann M, et al. Diffuse high-grade gliomas with H3 K27M mutations carry a dismal prognosis independent of tumor location. Neuro Oncol. 2018;20: 123-131.

42. Castel D, Philippe C, Kergrohen T, et al. Transcriptomic and epigenetic profiling of 'diffuse midline gliomas, H3 K27M-mutant' discriminate two subgroups based on the type of histone H3 mutated and not supratentorial or infratentorial location. Acta Neuropathol Commun. 2018;6: 117.

43. Schüller U, Iglauer P, Dorostkar MM, et al. Mutations within FGFR1 are associated with superior outcome in a series of 83 diffuse midline gliomas with H3F3A K27M mutations. Acta Neuropathol. 2021;141: 323-325.

44. Bögler O, Huang HJ, Kleihues P, Cavenee WK. The p53 gene and its role in human brain tumors. Glia. 1995;15: 308-327.

45. Fontebasso AM, Schwartzentruber J, Khuong-Quang DA, et al. Mutations in SETD2 and genes affecting histone H3K36 methylation target hemispheric high-grade gliomas. Acta Neuropathol. 2013;125: 659-669.

46. Nikbakht H, Panditharatna E, Mikael LG, et al. Spatial and temporal homogeneity of driver mutations in diffuse intrinsic pontine glioma. Nat Commun. 2016;7: 11185.

47. Werbrouck C, Evangelista CCS, Lobón-Iglesias MJ, et al. TP53 Pathway Alterations Drive Radioresistance in Diffuse Intrinsic Pontine Gliomas (DIPG). Clin Cancer Res. 2019;25: 6788-6800.

48. Wiestler B, Capper D, Holland-Letz T, et al. ATRX loss refines the classification of anaplastic gliomas and identifies a subgroup of IDH mutant astrocytic tumors with better prognosis. Acta Neuropathol. 2013;126: 443-451.

49. Vuong HG, Altibi AMA, Duong UNP, et al. BRAF Mutation is Associated with an Improved Survival in Glioma-a Systematic Review and Meta-analysis. Mol Neurobiol. 2018;55: 3718-3724.

50. Mistry M, Zhukova N, Merico D, et al. BRAF mutation and CDKN2A deletion define a clinically distinct subgroup of childhood secondary high-grade glioma. J Clin Oncol. 2015;33: 1015-1022.

51. Vuong HG, Altibi AMA, Duong UNP, et al. TERT promoter mutation and its interaction with IDH mutations in glioma: Combined TERT promoter and IDH mutations stratifies lower-grade glioma into distinct survival subgroups-A meta-analysis of aggregate data. Crit Rev Oncol Hematol. 2017;120: 1-9.

52. Smith JS, Tachibana I, Passe SM, et al. PTEN Mutation, EGFR Amplification, and Outcome in Patients With Anaplastic Astrocytoma and Glioblastoma Multiforme. JNCI: Journal of the National Cancer Institute. 2001;93: 1246-1256.

53. Louis DN, Perry A, Wesseling P, et al. The 2021 WHO Classification of Tumors of the Central Nervous System: a summary. Neuro Oncol. 2021;23: 1231-1251.

GeneticeventsofH3K27MgliomaSup.docx

Download PDF

Journal Publication

published 18 Nov, 2021

Read the published version in Journal of Neuro-Oncology →

Reviews received at journal
28 Sep, 2021
Reviewers invited by journal
28 Sep, 2021
Editor assigned by journal
28 Sep, 2021
First submitted to journal
28 Sep, 2021

You are reading this latest preprint version

H3K27M-mutant Diffuse Midline Gliomas should be Further Molecularly Stratified: An Integrated Analysis of 669 Patients

Status:

Journal Publication

Version 1

Abstract

Figures

Introduction

Methods

Search term and literature search

Selection criteria and abstract screening

Full-text screening and data extraction

Statistical analyses

Results

Clinical characteristics of H3-DMGs

Genetic alterations of H3-DMGs

Impact of genetic events on the prognosis of H3-DMGs

Discussion

Declarations

References

Supplementary Files

Status:

Journal Publication

Version 1