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Prognostic significance of genome-wide DNA methylation profiles within the randomized, phase 3, EORTC CATNON trial on non-1p/19q deleted anaplastic glioma

Abstract Background Survival in patients with IDH1/2-mutant (mt) anaplastic astrocytomas is highly variable. We have used the prospective phase 3 CATNON trial to identify molecular factors related to outcome in IDH1/2mt anaplastic astrocytoma patients. Methods The CATNON trial randomized 751 adult patients with newly diagnosed 1p/19q non-codeleted anaplastic glioma to 59.4 Gy radiotherapy +/− concurrent and/or adjuvant temozolomide. The presence of necrosis and/or microvascular proliferation was scored at central pathology review. Infinium MethylationEPIC BeadChip arrays were used for genome-wide DNA methylation analysis and the determination of copy number variations (CNV). Two DNA methylation-based tumor classifiers were used for risk stratification. Next-generation sequencing (NGS) was performed using 1 of the 2 glioma-tailored NGS panels. The primary endpoint was overall survival measured from the date of randomization. Results Full analysis (genome-wide DNA methylation and NGS) was successfully performed on 654 tumors. Of these, 432 tumors were IDH1/2mt anaplastic astrocytomas. Both epigenetic classifiers identified poor prognosis patients that partially overlapped. A predictive prognostic Cox proportional hazard model identified that independent prognostic factors for IDH1/2mt anaplastic astrocytoma patients included; age, mini-mental state examination score, treatment with concurrent and/or adjuvant temozolomide, the epigenetic classifiers, PDGFRA amplification, CDKN2A/B homozygous deletion, PI3K mutations, and total CNV load. Independent recursive partitioning analysis highlights the importance of these factors for patient prognostication. Conclusion Both clinical and molecular factors identify IDH1/2mt anaplastic astrocytoma patients with worse outcome. These results will further refine the current WHO criteria for glioma classification.

2. Integration of clinical data, DNA methylation profiles, and genetic data is needed for accurate prognostication of IDH1/2mt anaplastic astrocytoma patients.
The diagnosis of gliomas has shifted from histology alone toward the incorporation of molecular data in the revised World Health Organization (WHO) 2016 classification of brain tumors, initially with isocitrate dehydrogenase 1 and 2 (IDH1/2) mutational status and the presence or absence of combined loss of the 1p and 19q chromosomal arms (1p/19q codeletion). This classification was found to be more objective, reproducible, and correlated better with outcome compared to classical histology. [1][2][3] Still, even within the welldefined molecular subsets of glioma, significant and clinically relevant differences in outcome exist. Homozygous deletion (HD) of cyclin-dependent kinase inhibitor 2 A and B (CDKN2A/B) has recently been identified in IDH1/2-mutant (mt) astrocytoma as a first molecular marker of grade 4 clinical behavior. [4][5][6] Numerous other genetic markers have been proposed to further prognosticate IDH1/2mt astrocytoma patients, in particular retinoblastoma 1 (RB1) pathway alterations, tyrosine-protein kinase Met (MET) amplification (amp), N-myc proto-oncogene (MYCN) amplification, platelet-derived growth factor receptor alpha (PDGFRA) amplification, phosphatidylinositol 3-kinase (PI3K) mutations, and total copy number variation (CNV) load. [4][5][6][7][8][9][10] At the epigenetic level, tumor-specific genome-wide cytosinephosphate-guanine (CpG) methylation patterns have been identified in diffuse glioma. Two classification systems have been reported that make use of the epigenetic profile to diagnose brain tumor subtypes: (1)

Importance of the Study
Grading of diffuse IDH1/2mt glioma is still done by classical morphology, apart from homozygous deletion (HD) of CDKN2A/B that is correlated with a poor outcome and which is proposed by the cIMPACT-NOW committee as a criterion for IDH1/2mt astrocytoma, grade 4. Identifying other molecular factors associated with outcome within tumor entities potentially allows for more precise prognostication of histologically similar tumors. We used the randomized CATNON trial to test the prognostic significance of several alterations within a homogeneously treated group of patients diagnosed with IDH1/2mt anaplastic astrocytoma. Tumor-related factors associated with an inferior outcome were identified by 2 different DNA methylation classifiers, as well as HD of CDKN2A/B, PDGFRA amplification, PI3K mutations, and total CNV load. In contrast to histological indicators of high grade, these molecular markers were significant in multivariable analysis and therefore can be used to identify patients with poor prognosis.
Tesileanu et al. CATNON: prognostic DNA methylation in anaplastic astrocytoma Neuro-Oncology phenotype (G-CIMP)-high to G-CIMP-low as reported by de Souza et al. (combined, named here: "the glioma classifier"). [11][12][13][14] The accuracy of these molecular characteristics in relation to outcome has thus far not been clinically validated in homogeneously treated cohorts of patients. We therefore aimed to test and evaluate the importance of reported prognostic genetic and epigenetic molecular markers within the CATNON trial, the largest prospective study conducted on anaplastic astrocytoma patients. 15 These validated subtypes can be used for prognostication and results can be considered for the grading of tumors of the CNS.

Study Design and Participants
The CATNON trial is a 2 × 2 factorial design, nonblinded, multicenter (n = 137), randomized clinical trial in adult patients (n = 751) with primary 1p/19q non-codeleted anaplastic gliomas conducted by the European Organisation for Research and Treatment of Cancer (EORTC). 15 After local diagnosis of an anaplastic glioma, tumor samples were submitted prior to randomization for central pathology review of the tumor grade, and for central testing of O 6 -methylguanine DNA methyltransferase (MGMT) promoter methylation status. The absence of combined 1p/19q loss was either determined by local testing or at central review. Patients were computer-generated randomized (1:1:1:1) to radiotherapy alone (59.4 Gy in 33 fractions of 1.8 Gy), radiotherapy with concurrent temozolomide (75 mg/ m 2 daily, max 7 weeks), radiotherapy with adjuvant temozolomide (12 4-week cycles: 150-200 mg/m 2 on days 1-5), or radiotherapy with both concurrent and adjuvant temozolomide.

Compliance With Ethical Standards
All institutions obtained ethics approval from their institutional review boards or ethics review committees before enrollment started. All patients gave written informed consent according to local, national, and international guidelines.
Procedures DNA was isolated from formalin-fixed paraffin-embedded (FFPE) tumor samples as described previously. 16 IDH1/2, B-Raf proto-oncogene serine/threonine-protein kinase (BRAF), H3.3 histone A (H3F3A), CDKN2A/B, RB1, PI3K subunit alpha (PIK3CA), and PI3K regulatory subunit 1 (PIK3R1) mutation status were determined from either 1 of the 2 glioma-tailored next-generation sequencing (NGS) panels as described previously. 17,18 DNA methylation profiling was performed with the Infinium MethylationEPIC BeadChip according to the manufacturer's instructions after using the Infinium FFPE DNA Restoration Kit. CNV data (CDKN2A/B HD, RB1 HD, cyclin-dependent kinase 4 (CDK4) amp, cyclin-dependent kinase 6 (CDK6) amp, METamp, MYCNamp, PDGFRAamp) were derived from the DNA methylation data. MGMT promoter status was assessed with the MGMT-STP27 algorithm. 19 Samples that did not pass quality control, ie, the signal detection P value was <.01 in more than 5% of the probes were excluded from further analysis. HDs and amplifications were defined as ±0.60 log2 intensity differences. CNV differences between ±0.60 and ±0.30 log2 intensity were visually inspected for CNV calling, blinded to all other molecular or clinical data. DNA methylation-based epigenetic subtyping was established using random forest modeling using a classifier described by Capper et al., and one classifier described by Ceccarelli et al. 11,12 The latter classifier was supplemented with the risk of progression from G-CIMP-high to G-CIMPlow based on beta values of 7 specific CpGs as described previously (named here: "risk tumors" and "no-risk tumors"). 13 Total CNV load was calculated as described previously with a threshold for loss and gain of ±0.10 log2 intensity on the CNV plot and a cutoff of 350 Mb. 20 Two dedicated neuropathologists scored the presence or absence of necrosis and microvascular proliferation at the central pathology review (J.M.K.: European and Australian samples, K.A.: North American samples). Clinical data such as survival, sex, age at enrollment, use of corticosteroids at enrollment (no use vs stable/decreasing dose), type of surgery (biopsy vs resection), mini-mental state examination (MMSE) score at enrollment (<27 vs 27-30), and treatment regimen were collected from the study entry forms.

Statistical Analysis
The primary endpoint for all correlations of the epigenetic subtypes, DNA mutations and CNV was overall survival (OS), measured from the date of randomization until the date of death or censored at the date of last follow-up. Survival curves were created using the Kaplan-Meier technique and compared with the log-rank test. The Cox regression model was used for univariable and multivariable analysis to determine hazard ratios (HR) with 95% confidence intervals (CI), and significance was assessed with the likelihood ratio test. Factors with likelihood ratio test P values ≤.10 and at least 2 subgroups with n > 5 were taken into consideration for multivariable analysis. Principal component analysis (PCA) was performed on the 20 000 most variable probes between samples. The t-distributed stochastic neighbor embedding (t-SNE) plot was created with all significant probes at detection P value <.01 except those with lower overall reliability as previously described by Zhou et al. 21 The prognostic prediction models were made using stepwise backward elimination. Schoenfeld's test was utilized to assess proportional hazard (PH) assumptions of Cox PH models. Harrell's concordance index (C-index) was calculated and bootstrapped by 1000 iterations for the final models. Recursive partitioning analysis was performed on the significant factors from univariable analysis with 10 cross-validations in which every leaf had n > 20 patients. For all non-specified analyses, P values below .05 were considered significant. Statistical analysis was performed using R version 3.6.3 and packages minfi, stats, rms, survival, Rtsne, and rpart. This trial is registered with ClinicalTrials.gov, number NCT00626990. Upon completion of all ongoing analyses, all data will be made available upon request at EORTC headquarters.

Cohort Description
Comparison of the patient cohorts with and without molecular data identified that those able to be analyzed were younger (median age: 41 years vs 47 years, P = .006) and more likely to have had debulking surgery (82.6% vs 58.8%, P < .0001), but all other factors were similar (Supplementary Table 1). Genome-wide DNA methylation analysis was successfully performed on 654 samples of the 751 patients (19 samples were of low quality, and for 78 patients, there was insufficient tumor tissue available, Supplementary Figures 1 and 2). Of these, 440 (67.3%) were IDH1/2mt, 204 (31.2%) were IDH1/2 wild type (wt), and for 10, the IDH1/2 status could not be determined ( Figure  1A, B and Supplementary Figure 1). Copy number assessment identified 8 (1.2%) IDH1/2mt anaplastic oligodendroglioma leaving 432 IDH1/2mt anaplastic astrocytomas. Ten IDH1/2wt tumors had an H3F3A K27M mutation and 4 had an H3F3A G34R mutation. Three IDH1/2wt tumors had a BRAF mutation (2 V600E and 1 R509Q) and 1 IDH1/2mt tumor had a BRAF mutation (K601E). Central histology review identified necrosis and/or microvascular proliferation, consistent with grade 4 tumors, in 95 (14.5%) samples (38 IDH1/2wt, 57 IDH1/2mt; in 40 necrosis, and in 79 microvascular proliferation; Figure 2F and Supplementary Figure  3A). PCA of the DNA methylation data primarily showed division between IDH1/2wt and IDH1/2mt gliomas in the first primary component accounting for 51% of variance in all samples ( Figure 1B). Clinical characteristics of the cohort are listed in Table 1.

DNA Methylation Analysis of All Samples
The majority of samples were assigned by "the CNS tumor classifier" to lower-grade (WHO 2 or 3) IDH1/2mt astrocytomas (A_IDH, n = 317) or high-grade (WHO 3 or 4) IDH1/2mt astrocytomas (A_IDH_HG, n = 113). Other diagnoses according to "the CNS tumor classifier" were methylation class family IDH1/2wt glioblastomas (MTCF_ GBM, n = 161), H3F3Amt G34R gliomas (GBM_G34, n = 5), H3F3Amt K27M gliomas (DMG_K27, n = 11), 1p/19q codeleted gliomas (O_IDH, n = 12), and 35 tumors with other, more rare diagnoses. Of note, not all classifications were considered equally reliable: in 74 samples the main class calibrated score was below 0.836, which has been described as the lower bound for an optimal sensitivity and specificity. 12 When only samples meeting this calibration score were taken into account, the classifications correlated even better with molecular features. For example, all 4 DMG_K27 tumors with a reliability score below 0.836 did not show an H3F3A K27M mutation in the NGS analysis, whereas the mutation was confirmed in all 7 tumors with a calibrated score ≥0.836 ( Figure 1D).
We next assigned the 654 tumors into subgroups based on "the glioma classifier, " to 409 G-CIMP-high tumors, 19 G-CIMP-low tumors, 18 codel tumors, 107 mesenchymallike tumors, 48 classic-like tumors, and 53 pilocytic astrocytoma (PA)-like/glioblastoma-like glioma methylation group 6 ("LGm6-GBM") tumors. The latter subdiagnosis is combined as it requires additional histology review to determine the presence or absence of necrosis and/or microvascular proliferation for further separation. After this central histology review, the subgroup is further separated into 41 PA-like tumors and 12 LGm6-GBM tumors. The PA-like tumors were not a single nosological entity; in this set, we identified 9 tumors with H3F3A mutations (7 K27M, 2 G34R) and 1 BRAF-mutated tumor (R509Q). The LGm6-GBM tumors also contained 2 tumors with H3F3A mutations (K27M) and 1 tumor with a BRAF mutation (V600E).
To explore potential prognostic differences between "the CNS tumor classifier" and "the glioma classifier, " we stratified "the CNS tumor classifier" classes by "the glioma classifier" subtypes and vice versa (Supplementary Figure 5). Within the A_IDH_HG tumors, those assigned to G-CIMPlow had a significantly worse OS compared to those assigned to G-CIMP-high regardless of progression risk. There were, however, no differences in OS when either A_IDH or A_IDH_HG tumors were stratified by risk to G-CIMP-low progression (log-rank test between G-CIMP-high: No-risk and G-CIMP-high: Risk of Supplementary Figure 5A, B: P = .33 and P = .42, respectively). Stratifying "risk tumors" and "no-risk tumors" into "the CNS tumor classifier" subgroups showed a significant OS difference in both A_IDH and A_IDH_HG tumors (HR 1.80 95% CI 1.01-3.21, P = .06; and HR 2.00 95% CI 1.06-3.77, P = .03, respectively).

Analysis of the IDH1/2mt Anaplastic Astrocytoma Cohort
We set out to build a prognostic model specifically for IDH1/2mt anaplastic astrocytoma patients. Although a t-SNE plot of only the 432 IDH1/2mt anaplastic astrocytomas does not separate these epigenetic subtypes, they do have a distinct spatial distribution within this plot ( Figure 3A and Supplementary Figure 6). We further performed NGS and CNV analysis and identified 43 IDH1/2mt anaplastic astrocytomas with CDKN2A/B HD, 6 with RB1 HD, 25 with CDK4amp, 22 with PDGFRAamp, 7 with METamp, 7 with MYCNamp, 4 with CDK6amp, and 20 with PI3K mutations (14 PIK3R1, 6 PIK3CA). The total CNV load was classified as high in 185 (42.8%) IDH1/2mt anaplastic astrocytomas based on an algorithm by Shirahata et al. 20 Univariable analysis of the IDH1/2mt anaplastic astrocytomas showed that most of the clinical, molecular, and histological factors were associated with OS, ie, age groups, WHO performance score, MMSE, type of surgery, use of corticosteroids, treatment with adjuvant temozolomide, treatment with concurrent temozolomide, the presence of necrosis and/or microvascular proliferation, "the CNS tumor classifier, " "the glioma classifier, " CDK4amp, METamp, PDGFRAamp, CDKN2A/B HD, PI3K mutations, and total CNV load (Supplementary Table 2, Figure 2F, Supplementary Figures 7 and 8). Only patient sex, MGMT promoter methylation, MYCNamp, and RB1 HD were not associated with OS at univariable analysis (with the latter 2 factors present in only a few cases). The presence of the prognostic molecular and histological markers correlated with DNA methylation classes A_IDH_ HG tumors, G-CIMP-low tumors, and G-CIMP-low progression risk ( Figure 3B). Moreover, several of the prognostic molecular and histological markers showed significant co-occurrence.
Cox PH models made by stepwise backward elimination of significant factors from univariable analysis resulted in 3 multivariable models with independent significant factors: (1) the clinical/histological model (using the clinical and histological factors), (2) the tissue-based model (using the molecular and histological factors), and (3) the combined model (using clinical, molecular, and histological factors). The final clinical/histological model included age groups, WHO performance score, treatment with adjuvant temozolomide, the presence of necrosis and/or microvascular proliferation, and type of primary surgery and had a bootstrap corrected C-index of 0.626, while the final tissue-based model included "the CNS tumor classifier, " "the glioma classifier, " PDGFRAamp, CDKN2A/B HD, PI3Kmt, and total CNV load with a bootstrap corrected C-index of 0.665. However, the predictive final combined model performed markedly better than both the clinical/histological and the tissue-based model  Figure 9). The final tissue-based model is illustrated in Supplementary Figure 10. Finally, we performed recursive partitioning analysis on the significant factors from univariable analysis to create a prognostic decision tree for IDH1/2mt anaplastic astrocytoma patients. The first split of the tree is made Overall survival of IDH1/2mt anaplastic astrocytoma patients: necrosis and/or microvascular proliferation vs no necrosis or microvascular proliferation. CNS, central nervous system; A_IDH, IDH1/2mt-like astrocytomas lower-grade; A_IDH_HG, IDH1/2mt-like astrocytomas high-grade; O_IDH, IDH1/2mt-like oligodendrogliomas; IDH1/2mt, isocitrate dehydrogenase 1 and 2 mutant; DMG_K27, H3F3Amt K27M-like tumor; GBM_G34, H3F3Amt G34R-like tumor; H3F3Amt, H3.3 histone A mutant; MTCF_GBM, glioblastoma; Codel, 1p/19q codeleted; G-CIMP, glioma-CpG island methylator phenotype; PA-like/LGm6-GBM, pilocytic astrocytoma-like/glioblastoma-like glioma methylation group 6; No-risk, no-risk of progression to G-CIMP-low; Risk, risk of progression to G-CIMP-low.

Neuro-Oncology
on the presence/absence of CDKN2A/B HD highlighting the importance of this molecular marker for prognostication. Additional branches are made by treatment with adjuvant temozolomide, WHO performance score, and "the CNS tumor classifier, " resulting in 3 clinically relevant subgroups with either a fair outcome, intermediate outcome, or poor outcome ( Figure 5). Recursive partitioning analysis of solely the IDH1/2mt anaplastic astrocytoma cohort that was treated with adjuvant temozolomide did not result in a stable model and is therefore not shown here.

Discussion
Our study used tissue samples from the prospective randomized CATNON trial to validate the prognostic relevance of DNA methylation-based epigenetic subtyping by both "the CNS tumor classifier" and "the glioma classifier" in a cohort of homogenously treated anaplastic glioma patients. We demonstrate that, in IDH1/2mt anaplastic astrocytoma patients, both DNA methylation classifiers, alone or in combination with clinical data as well as other molecular markers (PI3K mutation status, and CNV analysis of PDGFRA, CDKN2A/B, and CNV load) exhibit prognostic significance. Our study validates the OS difference of A_IDH and A_IDH_HG tumor patients, the negative prognostic impact of the G-CIMP-low methylation profile, and the negative prognostic impact of the risk to G-CIMP-low progression score.
This validation is important, as both "the CNS tumor classifier" and "the glioma classifier" are available and can be easily used to diagnose and prognosticate new tumor samples with locally assessed DNA methylation data. 12,22 The clear prognostic importance of the DNA methylation-based subgroups in IDH1/2mt anaplastic astrocytoma suggests consideration for implementation in standard glioma diagnostics. Importantly, the added predictive effect of PDGFRAamp, CDKN2A/B HD, total CNV load, and PI3K mutation status can be considered as an integral part of prognosticating ("grading") IDH1/2mt anaplastic astrocytomas. For example, both the G-CIMPlow methylation profile and HD of CDKN2A/B were shown to be negative prognostic markers, yet only in patients harboring tumors with the combination of these markers does the OS resemble the outcome in grade CNV load high (n=185) Necrosis and/or MVP (n=56) 1556 Tesileanu et al. CATNON: prognostic DNA methylation in anaplastic astrocytoma 4 IDH1/2wt glioma patients as described in previous research. 23 Within IDH1/2wt anaplastic astrocytoma, the prognostic PA-like/LGm6-GBM subgroup of "the glioma classifier" was assessed as well. Both BRAF mutations and H3F3A mutations were identified in these tumors showing heterogeneity in this subgroup, since these mutations are indicative of both better and worse outcome patients. 3,24,25 This heterogeneity is further emphasized by the overlap with sporadic diagnoses from "the CNS tumor classifier" with low reliability scores. These findings show that some tumors of this group cannot be classified by epigenetics and they require classification based on NGS and/or CNV data. Further analysis of IDH1/2wt anaplastic gliomas of the CATNON trial and outcome to treatment will be reported separately elsewhere.