Methylation subgroup and molecular heterogeneity is a hallmark of glioblastoma: implications for biopsy targeting, classification and therapy

Resolving spatial response heterogeneity in glioblastoma

PURPOSE

Spatial intratumoral heterogeneity poses a significant challenge for accurate response assessment in glioblastoma. Multimodal imaging coupled with advanced image analysis has the potential to unravel this response heterogeneity.

METHODS

Based on automated tumor segmentation and longitudinal registration with follow-up imaging, we categorized contrast-enhancing voxels of 61 patients with suspected recurrence of glioblastoma into either true tumor progression (TP) or pseudoprogression (PsP). To allow the unbiased analysis of semantically related image regions, adjacent voxels with similar values of cerebral blood volume (CBV), FET-PET, and contrast-enhanced T1w were automatically grouped into supervoxels. We then extracted first-order statistics as well as texture features from each supervoxel. With these features, a Random Forest classifier was trained and validated employing a 10-fold cross-validation scheme. For model evaluation, the area under the receiver operating curve, as well as classification performance metrics were calculated.

RESULTS

Our image analysis pipeline enabled reliable spatial assessment of tumor response. The predictive model reached an accuracy of 80.0% and a macro-weighted AUC of 0.875, which takes class imbalance into account, in the hold-out samples from cross-validation on supervoxel level. Analysis of feature importances confirmed the significant role of FET-PET-derived features. Accordingly, TP- and PsP-labeled supervoxels differed significantly in their 10th and 90th percentile, as well as the median of tumor-to-background normalized FET-PET. However, CBV- and T1c-related features also relevantly contributed to the model's performance.

CONCLUSION

Disentangling the intratumoral heterogeneity in glioblastoma holds immense promise for advancing precise local response evaluation and thereby also informing more personalized and localized treatment strategies in the future.

Analysis of gliomas DNA methylation: Assessment of pre-analytical variables

Precision oncology is driven by molecular biomarkers. For glioblastoma multiforme (GBM), the most common malignant adult primary brain tumor, O6-methylguanine-DNA methyltransferase ( MGMT ) gene DNA promoter methylation is an important prognostic and treatment clinical biomarker. Time consuming pre-analytical steps such as biospecimen storage before fixing, sampling, and processing are major sources of errors and batch effects, that are further confounded by intra-tumor heterogeneity of MGMT promoter methylation. To assess the effect of pre-analytical variables on GBM DNA methylation, tissue storage/sampling (CryoGrid), sample preparation multi-sonicator (PIXUL) and 5-methylcytosine (5mC) DNA immunoprecipitation (Matrix MeDIP-qPCR/seq) platforms were used. MGMT promoter CpG methylation was examined in 173 surgical samples from 90 individuals, 50 of these were used for intra-tumor heterogeneity studies. MGMT promoter methylation levels in paired frozen and formalin fixed paraffin embedded (FFPE) samples were very close, confirming suitability of FFPE for MGMT promoter methylation analysis in clinical settings. Matrix MeDIP-qPCR yielded similar results to methylation specific PCR (MS-PCR). Warm ex-vivo ischemia (37°C up to 4hrs) and 3 cycles of repeated sample thawing and freezing did not alter 5mC levels at MGMT promoter, exon and upstream enhancer regions, demonstrating the resistance of DNA methylation to the most common variations in sample processing conditions that might be encountered in research and clinical settings. 20-30% of specimens exhibited intratumor heterogeneity in the MGMT DNA promoter methylation. Collectively these data demonstrate that variations in sample fixation, ischemia duration and temperature, and DNA methylation assay technique do not have significant impact on assessment of MGMT promoter methylation status. However, intratumor methylation heterogeneity underscores the need for histologic verification and value of multiple biopsies at different GBM geographic tumor sites in assessment of MGMT promoter methylation. Matrix-MeDIP-seq analysis revealed that MGMT promoter methylation status clustered with other differentially methylated genomic loci (e.g. HOXA and lncRNAs), that are likewise resilient to variation in above post-resection pre-analytical conditions. These MGMT -associated global DNA methylation patterns offer new opportunities to validate more granular data-based epigenetic GBM clinical biomarkers where the CryoGrid-PIXUL-Matrix toolbox could prove to be useful.

Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results

MGMT promoter methylation testing is required for prognosis and predicting temozolomide response in gliomas. Accurate results depend on sufficient tumor cellularity, but histologic estimates of cellularity are subjective. We sought to determine whether driver mutation variant allelic frequency (VAF) could serve as a more objective metric for cellularity and identify possible false-negative MGMT samples. Among 691 adult-type diffuse gliomas, MGMT promoter methylation was assessed by pyrosequencing (N = 445) or DNA methylation array (N = 246); VAFs of TERT and IDH driver mutations were assessed by next generation sequencing. MGMT results were analyzed in relation to VAF. By pyrosequencing, 56% of all gliomas with driver mutation VAF ≥ 0.325 had MGMT promoter methylation, versus only 37% with VAF < 0.325 (p < 0.0001). The mean MGMT promoter pyrosequencing score was 19.3% for samples with VAF VAF ≥ 0.325, versus 12.7% for samples with VAF < 0.325 (p < 0.0001). Optimal VAF cutoffs differed among glioma subtypes (IDH wildtype glioblastoma: 0.12-0.18, IDH mutant astrocytoma: ~0.33, IDH mutant and 1p/19q co-deleted oligodendroglioma: 0.3-0.4). Methylation array was more sensitive for MGMT promoter methylation at lower VAFs than pyrosequencing. Microscopic examination tended to overestimate tumor cellularity when VAF was low. Re-testing low-VAF cases with methylation array and droplet digital PCR (ddPCR) confirmed that a subset of them had originally been false-negative. We conclude that driver mutation VAF is a useful quality assurance metric when evaluating MGMT promoter methylation tests, as it can help identify possible false-negative cases.

Multiscale quantification of morphological heterogeneity with creation of a predictor of longer survival in glioblastoma

Intratumor heterogeneity is a main cause of the dismal prognosis of glioblastoma (GBM). Yet, there remains a lack of a uniform assessment of the degree of heterogeneity. With a multiscale approach, we addressed the hypothesis that intratumor heterogeneity exists on different levels comprising traditional regional analyses, but also innovative methods including computer-assisted analysis of tumor morphology combined with epigenomic data. With this aim, 157 biopsies of 37 patients with therapy-naive IDH-wildtype GBM were analyzed regarding the intratumor variance of protein expression of glial marker GFAP, microglia marker Iba1 and proliferation marker Mib1. Hematoxylin and eosin stained slides were evaluated for tumor vascularization. For the estimation of pixel intensity and nuclear profiling, automated analysis was used. Additionally, DNA methylation profiling was conducted separately for the single biopsies. Scoring systems were established to integrate several parameters into one score for the four examined modalities of heterogeneity (regional, cellular, pixel-level and epigenomic). As a result, we could show that heterogeneity was detected in all four modalities. Furthermore, for the regional, cellular and epigenomic level, we confirmed the results of earlier studies stating that a higher degree of heterogeneity is associated with poorer overall survival. To integrate all modalities into one score, we designed a predictor of longer survival, which showed a highly significant separation regarding the OS. In conclusion, multiscale intratumor heterogeneity exists in glioblastoma and its degree has an impact on overall survival. In future studies, the implementation of a broadly feasible heterogeneity index should be considered.

Development of a tumor microenvironment-related prognostic signature in glioma to predict immune landscape and potential therapeutic drugs

The involvement of the tumor microenvironment (TME) in the biology of gliomas has expanded, while it is yet uncertain its potential of supporting diagnosis and therapy choices. According to immunological characteristics and overall survival, cohorts of glioma patients from public databases were separated into two TME-relevant clusters in this analysis. Based on differentially expressed genes between TME clusters and correlative regression analysis, a 21-gene molecular classifier of TME-related prognostic signature (TPS) was constructed. Afterward, the prognostic efficacy and effectiveness of TPS were assessed in the training and validation groups. The outcome demonstrated that TPS might be utilized alone or in conjunction with other clinical criteria to act as a superior prognostic predictor for glioma. Also, high-risk glioma patients classified by TPS were considered to associate with enhanced immune infiltration, greater tumor mutation, and worse general prognosis. Finally, possible treatment medicines specialized for different risk subgroups of TPS were evaluated in drug databases.

Utility of genome-wide DNA methylation profiling for pediatric-type diffuse gliomas

Despite the current progress of treatment, pediatric-type diffuse glioma is one of the most lethal primary malignant tumors in the central nervous system (CNS). Since pediatric-type CNS tumors are rare disease entities and highly heterogeneous, the diagnosis is challenging. An accurate diagnosis is essential for the choice of optimal treatment, which leads to precision oncology and improvement of the patient's outcome. Genome-wide DNA methylation profiling recently emerged as one of the most important tools for the diagnosis of CNS tumors, and the utility of this novel assay has been reported in both pediatric and adult patients. In the current World Health Organization classification published in 2021, several new entities are recognized in pediatric-type diffuse gliomas, some of which require methylation profiling. In this review, we investigated the utility of genome-wide DNA methylation profiling in pediatric-type diffuse glioma, as well as issues in the clinical application of this assay. Furthermore, the combination of genome-wide DNA methylation profiling and other comprehensive genomic assays, which may improve diagnostic accuracy and detection of the actionable target, will be discussed.

[Total DNA methylation profile in assessing the MGMT gene promoter status in malignant gliomas]

Methylation of the O-6-methylguanine-DNA methyltransferase (MGMT) gene promoter is currently the most important prognostic biomarker in therapy of IDH-wild-type glioblastoma. One can obtain information about this methylation from total DNA methylation profile.

OBJECTIVE

To analyze the DNA methylation signal intensity in the MGMT gene in samples of malignant gliomas and identify the most significant genomic positions for calculating the MGMT gene promoter status for further improvement of diagnostics and prediction of therapeutic options in patients with malignant gliomas.

MATERIAL AND METHODS

The study is based on 43 samples (frozen tissue or paraffin blocks) from patients with malignant gliomas. Tumor DNA samples were prepared using the Illumina Infinium MethylationEPIC BeadChip Kit and the Illumina Next-Seq 550 Sequencing System platform. DNA methylation profiles were analyzed using computational algorithms in the R language, specialized libraries minfi and mgmtstp27, as well as basic statistical functions in the Rstudio environment.

RESULTS

We established the MGMT gene promoter status in 43 samples of malignant gliomas considering total DNA methylation profile. In 24 samples (55%), the MGMT gene promoter was methylated. We compared methylation signal in certain CpG islands in groups with methylated and unmethylated MGMT gene promoters and identified the most significant positions for further improvement of data analysis algorithm.

CONCLUSION

These data demonstrate the possibilities and prospects for further improvement of algorithm for analysis of the MGMT gene promoter status based on total DNA methylation profile in patients with malignant gliomas as an alternative to methyl-specific PCR. Our results are consistent with data of other neuro-oncology researchers. Indeed, computational methods like MGMT-STP27 are quite powerful and can be used in scientific and clinical practice to assess prognosis and make decisions about chemotherapy with alkylating agents.

Methylation Profiling in Diffuse Gliomas: Diagnostic Value and Considerations

Diffuse gliomas cause significant morbidity across all age groups, despite decades of intensive research efforts. Here, we review the differences in diffuse gliomas in adults and children, as well as the World Health Organisation (WHO) 2021 classification of these tumours. We explain how DNA methylation-based classification works and list the methylation-based tumour types and subclasses for adult and paediatric diffuse gliomas. The benefits and utility of methylation-based classification in diffuse gliomas demonstrated to date are described. This entails the identification of novel tumour types/subclasses, patient stratification and targeted treatment/clinical management, and alterations in the clinical diagnosis in favour of the methylation-based over the histopathological diagnosis. Finally, we address several considerations regarding the use of DNA methylation profiling as a diagnostic tool, e.g., the threshold of the classifier, the calibrated score, tumour cell content and intratumour heterogeneity.