Faculty Bibliography

Renal neoplasms are morphologically and molecularly heterogeneous, with their diagnosis often hindered by interobserver variability and overlapping microscopic features. A subset of cases is unclassifiable despite immunohistochemical, mutation, and cytogenetic-based diagnostic workup. Through examination of the genome-wide DNA methylation signatures of over 2000 renal neoplasms, we identified 23 coherent groups that correlate with known neoplasm types and identified novel clinically relevant subtypes of existing neoplasm types. We used machine learning models to develop and validate a classifier trained on DNA methylation profiles of 1284 samples. The classifier was tested on an external data set of 287 renal neoplasms with >90% concordance between expected neoplasm type and high-score DNA methylation-based classification. Discordance between the original histologic label and methylation class led to potential reclassification of some cases. This work demonstrates proof of principle for the feasibility of a DNA methylation classifier as a clinically useful tool to assist in the diagnosis of renal neoplasms.

PURPOSE/OBJECTIVE:Histopathological grading of IDH-mutant astrocytomas demonstrates limited prognostic accuracy. However, DNA methylation subclassification has demonstrated improved prognostication beyond histological grading. This study aimed to investigate the associations between imaging features, tumor volumetric data, and DNA methylation grade in IDH-mutant astrocytomas. METHODS:We analyzed imaging features and volumetric data for 72 patients diagnosed with IDH-mutant astrocytomas, who underwent preoperative MRI and DNA methylation profiling. VASARI features and multicompartmental volumetrics were evaluated. Logistic regression was used to identify imaging predictors of methylation subclass, WHO histologic grade, copy number variation (CNV), and CDKN2A/B homozygous deletion. Univariable and multivariable Cox proportional hazard models were also developed to assess these variables' influence on overall survival and progression-free survival. RESULTS:Patients were classified into 27 methylation high-grade (A_IDH_HG) and 45 methylation low-grade (A_IDH_LG) tumors. Tumor volumes and proportions varied by methylation grade, CNV status, and WHO histologic grade, but not by CDKN2A/B status. Imaging features distinguished methylation subclasses with 75% accuracy (AUC = 0.77). Methylation high-grade subclass was associated with imaging features such as midline crossing, ependymal extension, and poorly defined enhancing margins. Predictive performance for WHO histologic grade, CNV status, and CDKN2A/B deletion was moderate (AUC = 0.67, 0.69, and 0.65, respectively). Methylation grade, CDKN2A/B status, VASARI features, and proportions of edema and non-contrast enhancing tumor were significantly associated with survival. CONCLUSION/CONCLUSIONS:MRI-derived imaging features facilitate noninvasive prediction of DNA methylation subclass in IDH-mutant astrocytomas.

BACKGROUND:Molecular aberrations have been incorporated into tumour classification guidelines of meningioma. TERT-promoter (TERTp) mutation is associated with worse prognosis and is designated a WHO grade 3 biomarker. However, it remains unclear whether TERTp mutation is context-dependent, with other co-occurring genetic alterations potentially driving its association with prognosis. We sought to characterise the role of TERTp mutation in meningioma and guide TERTp sequencing. METHODS:We identified 1492 patients of all ages who had previously received surgery for meningioma across 14 medical centres in the USA, Canada, and Germany. Patients were eligible if they had post-surgical clinical or radiographical assessment of the resection site, and TERTp status evaluated by Nov 1, 2024. Multi-modal profiling was used to assess TERTp mutation, focal gene alterations-including CDKN2A/B loss-and copy number alterations. An adjusted WHO grade was calculated for TERTp-mutant meningiomas, incorporating all WHO criteria except TERTp status. Kaplan-Meier curves and multivariable Cox proportional hazards models were used to quantify the effect of TERTp mutation on the endpoints of overall survival and recurrence-free survival across adjusted WHO grade and co-occurring molecular alterations. FINDINGS/RESULTS:64 (4·3%) of 1492 meningiomas were TERTp-mutant and 1428 (95·7%) were TERTp-wildtype. Of the TERTp-mutant meningiomas, 33 (51·6%) were from female patients and 31 (48·4%) were from male patients, and the overall median age was 67 years (IQR 60-75). Of the wildtype meningiomas, 965 (67·6%) were from female patients and 463 (32·4%) were from male patients, and the overall median age of the patients was 59 years (IQR 48-70). Data on race was inconsistently reported and thus excluded. The TERTp-mutant patients had a 5-year overall survival (49·4% [95% CI 33·7-72·4]) and 5-year recurrence-free survival (27·6% [95% CI 16·8-45·5]) resembling that of patients with WHO grade 3 TERTp-wildtype tumours (5-year overall survival 32·3% [95% CI 17·2-60·5], p=0·28, 5-year recurrence-free survival 14·3% [5·8-35·2], p=0·28). However, the TERTp-mutant group had heterogenous histological grading and was enriched for aggressive molecular features, with 1p loss present in 44 (77·2%) of 57 profiled tumours and CDKN2A/B loss in 24 (41·4%) of the 58 profiled tumours. Adjusting tumour grade revealed a subset of TERTp-mutant meningiomas that were more molecularly and clinically benign. Among TERTp-mutant tumours, CDKN2A/B loss played a defining role in stratifying tumour behaviour. Multivariable analysis confirmed this, with CDKN2A/B loss being significantly associated with shorter overall survival (HR 3·04 [95% CI 1·67-5·52], p=0·00026) and faster time to recurrence (HR 5·22 [95% CI 3·10-8·79], p<0·0001), while TERTp-mutation did not independently affect overall survival (HR 1·00 [95% CI 0·53-1·87], p=0·99) or recurrence-free survival (1·17 [95% CI 0·75-1·83], p=0·49). Sequencing for TERTp-mutation demonstrated clinical impact only among histologically WHO grade 2 meningiomas. INTERPRETATION/CONCLUSIONS:The indolent behaviour of certain TERTp-mutant meningiomas suggests that TERTp mutation is not sufficient to assign the most aggressive meningioma grade. Instead, TERT sequencing might offer prognostic utility in identifying high-risk cases among WHO grade 2 meningiomas. FUNDING/BACKGROUND:National Institutes of Health, National Institute of Neurological Disorders and Stroke, Friedberg Charitable Foundation, Courtney Meningioma Research Fund, Fleming Meningioma Research Fund, and the Gray Family Foundation.

PURPOSE/OBJECTIVE:) disease. NRG Oncology BN002 (phase I) demonstrated safety and suggested efficacy of ipilimumab (ipi) with nivolumab (nivo) in newly diagnosed glioblastoma, leading to this phase II/III trial. METHODS:) of .15, superior PFS with immunotherapy in phase II would lead to phase III overall survival (OS) testing. Corticosteroids were disallowed when starting immunotherapy. Diagnosis, biomarkers, and PFS were centrally assessed. RESULTS:= .36). CONCLUSION/CONCLUSIONS:glioblastoma versus TMZ. Accrual closed permanently; the trial will not proceed to phase III. No new safety signals were identified. Molecular correlative analyses and survival follow-up are ongoing.

BACKGROUND/UNASSIGNED:Methylation class pleomorphic xanthoastrocytoma (mcPXA) comprises tumors with the DNA methylation signature of classical PXA but with a wider histologic spectrum, including overlap with glioblastoma (GBM). METHODS/UNASSIGNED:To clarify the histologic and molecular scope of mcPXA and characterize its clinical behavior, a cohort of 469 tumor samples from 458 patients matching to mcPXA by the DKFZ classifier (v12.6 score ≥0.85) was interrogated. RESULTS/UNASSIGNED:promoter mutations. CONCLUSION/UNASSIGNED:Tumors in mcPXA share molecular characteristics with histologically defined PXA, and high-grade histologic features can help predict their clinical behavior. The use of an epigenetic classification of PXA reveals that this group of tumors is more common than previously appreciated and warrants in-depth study to identify efficacious therapeutic options.

Decreased brain levels of coenzyme Q₁₀ (CoQ₁₀), an endogenously synthesized lipophilic antioxidant^1,2, underpin encephalopathy in primary CoQ₁₀ deficiencies^3,4 and are associated with common neurodegenerative diseases and the ageing process^5,6. CoQ₁₀ supplementation does not increase CoQ₁₀ pools in the brain or in other tissues. The recent discovery of the mammalian CoQ₁₀ headgroup synthesis pathway, in which 4-hydroxyphenylpyruvate dioxygenase-like protein (HPDL) makes 4-hydroxymandelate (4-HMA) to synthesize the CoQ₁₀ headgroup precursor 4-hydroxybenzoate (4-HB)⁷, offers an opportunity to pharmacologically restore CoQ₁₀ synthesis and mechanistically treat CoQ₁₀ deficiencies. To test whether 4-HMA or 4-HB supplementation promotes CoQ₁₀ headgroup synthesis in vivo, here we administered 4-HMA and 4-HB to Hpdl^-/- mice, which model an ultra-rare, lethal mitochondrial encephalopathy in humans. Both 4-HMA and 4-HB were incorporated into CoQ₉ and CoQ₁₀ in the brains of Hpdl^-/- mice. Oral treatment of Hpdl^-/- pups with 4-HMA or 4-HB enabled 90-100% of Hpdl^-/- mice to live to adulthood. Furthermore, 4-HB treatment stabilized and improved the neurological symptoms of a patient with progressive spasticity due to biallelic HPDL variants. Our work shows that 4-HMA and 4-HB can modify the course of mitochondrial encephalopathy driven by HPDL variants and demonstrates that CoQ₁₀ headgroup intermediates can restore CoQ₁₀ synthesis in vivo.

[This corrects the article DOI: 10.3389/fonc.2022.969812.].

BACKGROUND:Pituitary neuroendocrine tumors (PitNETs) are the most common intracranial neuroendocrine tumors. PitNETs can be challenging to classify, and current recommendations include a large immunohistochemical panel to differentiate among 14 WHO-recognized categories. METHODS:In this study, we analyzed clinical, immunohistochemical and DNA methylation data of 118 PitNETs to develop a clinico-molecular approach to classifying PitNETs and identify epigenetic classes. RESULTS:CNS DNA methylation classifier has an excellent performance in recognizing PitNETs and distinguishing the three lineages when the calibrated score is ≥0.3. Unsupervised DNA methylation analysis separated PitNETs into two major clusters. The first was composed of silent gonadotrophs, which form a biologically distinct group of PitNETs characterized by clinical silencing, weak hormonal expression on immunohistochemistry, and simple copy number profile. The second major cluster was composed of corticotrophs and Pit1 lineage PitNETs, which could be further classified using DNA methylation into distinct subclusters that corresponded to clinically functioning and silent tumors and are consistent with transcription factor expression. Analysis of promoter methylation patterns correlated with lineage for corticotrophs and Pit1 lineage subtypes. However, the gonadotrophic genes did not show a distinct promoter methylation pattern in gonadotroph tumors compared to other lineages. Promoter of the NR5A1 gene, which encodes SF1, was hypermethylated across all PitNETs clinical and molecular subtypes including gonadotrophs with strong SF1 protein expression indicating alternative epigenetic regulation. CONCLUSION/CONCLUSIONS:Our findings suggest that classification of PitNETs may benefit from DNA methylation for clinicopathological stratification.