HOXD12 defines an age-related aggressive subtype of oligodendroglioma.

Oligodendroglioma, IDH-mutant and 1p/19q-codeleted has highly variable outcomes that are strongly influenced by patient age. The distribution of oligodendroglioma age is non-Gaussian and reportedly bimodal, which motivated our investigation of age-associated molecular alterations that may drive poorer outcomes. We found that elevated HOXD12 expression was associated with both older patient age and shorter survival in the TCGA (FDR < 0.01, FDR = 1e-5) and the CGGA (p = 0.03, p < 1e-3). HOXD12 gene body hypermethylation was associated with older age, higher WHO grade, and shorter survival in the TCGA (p < 1e-6, p < 0.001, p < 1e-3) and with older age and higher WHO grade in Capper et al. (p < 0.002, p = 0.014). In the TCGA, HOXD12 gene body hypermethylation and elevated expression were independently prognostic of NOTCH1 and PIK3CA mutations, loss of 15q, MYC activation, and standard histopathological features. Single-nucleus RNA and ATAC sequencing data showed that HOXD12 activity was elevated in neoplastic tissue, particularly within cycling and OPC-like cells, and was associated with a stem-like phenotype. A pan-HOX DNA methylation analysis revealed an age and survival-associated HOX-high signature that was tightly associated with HOXD12 gene body methylation. Overall, HOXD12 expression and gene body hypermethylation were associated with an older, atypically aggressive subtype of oligodendroglioma.

Molecular classification to refine surgical and radiotherapeutic decision-making in meningioma.

Treatment of the tumor and dural margin with surgery and sometimes radiation are cornerstones of therapy for meningioma. Molecular classifications have provided insights into the biology of disease; however, response to treatment remains heterogeneous. In this study, we used retrospective data on 2,824 meningiomas, including molecular data on 1,686 tumors and 100 prospective meningiomas, from the RTOG-0539 phase 2 trial to define molecular biomarkers of treatment response. Using propensity score matching, we found that gross tumor resection was associated with longer progression-free survival (PFS) across all molecular groups and longer overall survival in proliferative meningiomas. Dural margin treatment (Simpson grade 1/2) prolonged PFS compared to no treatment (Simpson grade 3). Molecular group classification predicted response to radiotherapy, including in the RTOG-0539 cohort. We subsequently developed a molecular model to predict response to radiotherapy that discriminates outcome better than standard-of-care classification. This study highlights the potential for molecular profiling to refine surgical and radiotherapy decision-making.

Distinct relapse pattern across molecular ependymoma types.

BACKGROUND: Ependymoma (EPN) is not a uniform disease but represents different disease types with biological and clinical heterogeneity. However, the pattern of when and where different types of EPN relapse is not yet comprehensively described. METHODS: We assembled 269 relapsed intracranial EPN from pediatric (n=233) and adult (n=36) patients from European and Northern American cohorts and correlated DNA methylation patterns and copy-number alterations with clinical information. RESULTS: The cohort comprised the following molecular EPN types: PF-EPN-A (n=177), ST-EPN-ZFTA (n=45), PF-EPN-B (n=31), PF-EPN-SE (n=12), and ST-EPN-YAP (n=4). First relapses of PF-EPN-B (PF: posterior-fossa) and PF-EPN-SE (SE: subependymoma) occurred later than of PF-EPN-A, ST-EPN-YAP (ST: supratentorial), or ST-EPN-ZFTA (median time to relapse: 4.3 and 6.0 years vs. 1.9/1.0/2.4 years; p<0.01). Metastatic or combined recurrences in PF-EPN-B and -A more often involved the spinal cord than in ST-EPN-ZFTA (72.7% and 40.0 vs. 12.5%; p<0.01). No distant relapses were observed in ST-EPN-YAP (n=4) or PF-EPN-SE (n=12). Post-relapse survival (PRS) was poor for PF-EPN-A and ST-EPN-ZFTA (5-year PRS: 44.5±4.4/47.8±9.1%), whereas PF-EPN-B and PF-EPN-SE displayed a 5-year PRS of 89.5±7.1/90.0±9.5% (p=0.03). However, 10-year PRS for PF-EPN-B dropped to 45.8±17.3%. Neither between radiation field and relapse pattern nor between radiation field and spinal involvement at relapse an impact was identified. Notably, all patients with relapsed ST-EPN-YAP did not receive upfront radiotherapy, but were successfully salvaged using irradiation at relapse. CONCLUSIONS: Relapse patterns of specific EPN types are different. Future clinical trials, treatment adaptions, duration of surveillance and diagnostics should be planned incorporating entity-specific relapse information.

cIMPACT-NOW Update 8: Clarifications on molecular risk parameters and recommendations for WHO grading of meningiomas.

Meningiomas are the most frequent primary intracranial tumors. Hence, they constitute a major share of diagnostic specimens in neuropathology practice. The 2021 WHO Classification of Central Nervous System Tumors ("CNS5") has introduced the first molecular grading parameters for meningioma with oncogenic variants in the TERT promoter and homozygous deletion of CDKN2A/B as markers for CNS WHO grade 3. However, after publication of the new classification volume, clarifications were requested, not only on novel but also on long-standing questions in meningioma grading that were beyond the scope of the WHO "blue book". In addition, more recent research into possible new molecular grading parameters could not yet be implemented in the 2021 classification but constitute a compelling body of literature. Hence, the cIMPACT-NOW Steering Committee convened a working group to provide such clarification and assess the evidence of possible novel molecular criteria. As a result, this cIMPACT-NOW update provides guidance for more standardized morphological evaluation and interpretation, most prominently pertaining to brain invasion, identifies scenarios in which advanced molecular testing is recommended, proposes to assign CNS WHO grade 2 for cases with CNS WHO grade 1 morphology but chromosomal arm 1p deletion in combination with 22q deletion and/or NF2 oncogenic variants, and discusses areas in which the current evidence is not yet sufficient to result in new recommendations.

The Open Pediatric Cancer Project.

Background: In 2019, the Open Pediatric Brain Tumor Atlas (OpenPBTA) was created as a global, collaborative open-science initiative to genomically characterize 1,074 pediatric brain tumors and 22 patient-derived cell lines. Here, we extend the OpenPBTA to create the Open Pediatric Cancer (OpenPedCan) Project, a harmonized open-source multi-omic dataset from 6,112 pediatric cancer patients with 7,096 tumor events across more than 100 histologies. Combined with RNA-Seq from the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA), OpenPedCan contains nearly 48,000 total biospecimens (24,002 tumor and 23,893 normal specimens). Findings: We utilized Gabriella Miller Kids First (GMKF) workflows to harmonize WGS, WXS, RNA-seq, and Targeted Sequencing datasets to include somatic SNVs, InDels, CNVs, SVs, RNA expression, fusions, and splice variants. We integrated summarized CPTAC whole cell proteomics and phospho-proteomics data, miRNA-Seq data, and have developed a methylation array harmonization workflow to include m-values, beta-vales, and copy number calls. OpenPedCan contains reproducible, dockerized workflows in GitHub, CAVATICA, and Amazon Web Services (AWS) to deliver harmonized and processed data from over 60 scalable modules which can be leveraged both locally and on AWS. The processed data are released in a versioned manner and accessible through CAVATICA or AWS S3 download (from GitHub), and queryable through PedcBioPortal and the NCI's pediatric Molecular Targets Platform. Notably, we have expanded PBTA molecular subtyping to include methylation information to align with the WHO 2021 Central Nervous System Tumor classifications, allowing us to create research- grade integrated diagnoses for these tumors. Conclusions: OpenPedCan data and its reproducible analysis module framework are openly available and can be utilized and/or adapted by researchers to accelerate discovery, validation, and clinical translation.

Clinical utility of DNA methylation profiling for choroid plexus tumors.

Background: Choroid plexus tumors (CPTs) are rare, potentially aggressive CNS tumors with defined histologic criteria for grading. In recent years, several patients within our practice have demonstrated discordance between the histologic diagnosis and clinical behavior. DNA methylation profiling has emerged as a potential diagnostic adjunct for aiding the clinical approach. Methods: We reviewed the clinical and pathologic data of all CPTs diagnosed at Boston Children's Hospital from 1995 to 2023. All cases with available material (38/48) underwent DNA methylation profiling at NIH/NCI, and the classifier results were correlated with the WHO histologic grade and patient outcomes. Survival information was analyzed using Kaplan-Meier curves. Results: There was good correlation (11/12, 92%) between methylation class and WHO histologic grade for choroid plexus carcinomas (CPC); one histologic CPC grouped with choroid plexus papilloma (CPP) group pediatric (P). Five CPPs grouped with methylation class CPC (5/17, 29%). In the group of atypical CPPs (n = 9), there were two that grouped with methylation class CPC. Survival analysis showed utility of methylation classes in the prediction of biologic behavior. Conclusions: Results indicated that methylation profiling may serve as a valuable tool in the clinical decision-making process for patients with CPTs, providing additional prognostic information compared to WHO histologic grade alone. The value of methylation array analysis is particularly important given the lack of consensus on treatment regimens for CPTs.

Papillary tumor of the pineal region: analysis of DNA methylation profiles and clinical outcomes in 76 cases.

Papillary tumor of the pineal region (PTPR) is an uncommon tumor of the pineal region with distinctive histopathologic and molecular characteristics. Experience is limited with respect to its molecular heterogeneity and clinical characteristics. Here, we describe 39 new cases and combine these with 37 previously published cases for a cohort of 76 PTPR's, all confirmed by methylation profiling. As previously reported, two main methylation groups were identified (PTPR-A and PTPR-B). In our analysis we extended the subtyping into three subtypes: PTPR-A, PTPR-B1 and PTPR-B2 supported by DNA methylation profile and genomic copy number variations. Frequent loss of chromosome 3 or 14 was found in PTPR-B1 tumors but not in PTPR-B2. Examination of clinical outcome showed that nearly half (14/30, 47%) of examined patients experienced tumor progression with significant difference among the subtypes (p value = 0.046). Our analysis extends the understanding of this uncommon but distinct neuroepithelial tumor by describing its molecular heterogeneity and clinical outcomes, including its tendency towards tumor recurrence.

Chromosome 7 gain compensates for chromosome 10 loss in glioma.

The co-occurrence of chromosome 10 loss and chromosome 7 gain in gliomas is the most frequent loss-gain co-aneuploidy pair in human cancers. This phenomenon has been investigated since the late 1980s without resolution. Expanding beyond previous gene-centric studies, we investigated the co-occurrence in a genome-wide manner taking an evolutionary perspective. Mining of large-scale tumor aneuploidy data confirmed the previous finding of a small-scale longitudinal study that the most likely order is chromosome 10 loss followed by chromosome 7 gain. Extensive analysis of genomic and transcriptomic data from both patients and cell lines revealed that this co-occurrence can be explained by functional rescue interactions that are highly enriched on chromosome 7, which could potentially compensate for any detrimental consequences arising from the loss of chromosome 10. Transcriptomic data from various normal, non-cancerous human brain tissues were analyzed to assess which tissues may be most predisposed to tolerate compensation of chromosome 10 loss by chromosome 7 gain. The analysis indicated that the pre-existing transcriptomic states in the cortex and frontal cortex, where gliomas arise, are more favorable than other brain regions for compensation by rescuer genes that are active on chromosome 7. Collectively, these findings suggest that the phenomenon of chromosome 10 loss and chromosome 7 gain in gliomas is orchestrated by a complex interaction of many genes residing within these two chromosomes and provide a plausible reason why this co-occurrence happens preferentially in cancers originating in certain regions of the brain.

A deep-learning framework to predict cancer treatment response from histopathology images through imputed transcriptomics.

Advances in artificial intelligence have paved the way for leveraging hematoxylin and eosin-stained tumor slides for precision oncology. We present ENLIGHT-DeepPT, an indirect two-step approach consisting of (1) DeepPT, a deep-learning framework that predicts genome-wide tumor mRNA expression from slides, and (2) ENLIGHT, which predicts response to targeted and immune therapies from the inferred expression values. We show that DeepPT successfully predicts transcriptomics in all 16 The Cancer Genome Atlas cohorts tested and generalizes well to two independent datasets. ENLIGHT-DeepPT successfully predicts true responders in five independent patient cohorts involving four different treatments spanning six cancer types, with an overall odds ratio of 2.28 and a 39.5% increased response rate among predicted responders versus the baseline rate. Notably, its prediction accuracy, obtained without any training on the treatment data, is comparable to that achieved by directly predicting the response from the images, which requires specific training on the treatment evaluation cohorts.

NRG-BN002: Phase I study of ipilimumab, nivolumab, and the combination in patients with newly diagnosed glioblastoma.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have efficacy in several solid tumors but limited efficacy in glioblastoma (GBM). This study evaluated the safety of anti-CTLA-4 and anti-PD-1 ICIs alone or in combination in newly diagnosed GBM after completion of standard radiochemotherapy with the subsequent intent to test combinatorial ICIs in this setting. METHODS: The primary endpoint was dose-limiting toxicity (DLT) for adults with unifocal, supratentorial newly diagnosed GBM after resection and chemoradiation. Ipilimumab and nivolumab were tested separately and in combination with a planned expansion cohort dependent upon DLT results. RESULTS: Thirty-two patients were enrolled at 9 institutions: 6 to each DLT assessment cohort and 14 to the expansion cohort. Median age: 55 years, 67.7% male, 83.9% White. Treatment was well tolerated with 16% Grade 4 events; the combination did not have unexpectedly increased toxicity, with no Grade 5 events. One DLT was seen in each single-agent treatment; none were observed in the combination, leading to expanded accrual of the combined treatment. The median follow-up was 19.6 months. For all patients receiving combination treatment, median overall survival (OS) and progression-free survival (PFS) were 20.7 and 16.1 months, respectively. CONCLUSIONS: IPI and NIVO are safe and tolerable with toxicities similar to those noted with other cancers when given in combination with adjuvant temozolomide for newly diagnosed GBM. Combination IPI + NIVO is not substantially more toxic than single agents. These results support a subsequent efficacy trial to test the combination of ICIs in Phase II/III for patients with newly diagnosed GBM. CLINICALTRIALS.GOV REGISTRATION: NCT02311920.

The biological significance of tumor grade, age, enhancement and extent of resection in IDH mutant gliomas: how should they inform treatment decision in the era of IDH inhibitors? Invited review.

The 2016 and 2021 World Health Organization (WHO) 2021 Classification of Central Nervous System (CNS) tumors have resulted in a major improvement of the classification of IDH-mutant gliomas. With more effective treatments many patients experience prolonged survival . However, treatment guidelines are often still based on information from historical series comprising both patients with IDHwt and IDH mutant tumors. They provide recommendations for radiotherapy and chemotherapy for so-called high-risk patients, usually based on residual tumor after surgery and age over 40. More up-to-date studies give a better insight into clinical, radiological and molecular factors associated with outcome of patients with IDH-mutant glioma. These insights should be used today for risk stratification and for treatment decisions. In many patients with an IDH-mutant grade 2 and grade 3 glioma, if carefully monitored postponing radiotherapy and chemotherapy is safe, and will not jeopardize overall outcome of patients. With the INDIGO trial showing patient benefit from the IDH inhibitor vorasidenib, there is a sizable population in which it seems reasonable to try this class of agents before recommending radio-chemotherapy with its delayed adverse event profile affecting quality of survival. Ongoing trials should help to further identify the patients that are benefiting from this treatment.

Radiotherapy Plan Quality Assurance in NRG Oncology Trials for Brain and Head/Neck Cancers: An AI-Enhanced Knowledge-Based Approach.

The quality of radiation therapy (RT) treatment plans directly affects the outcomes of clinical trials. KBP solutions have been utilized in RT plan quality assurance (QA). In this study, we evaluated the quality of RT plans for brain and head/neck cancers enrolled in multi-institutional clinical trials utilizing a KBP approach. The evaluation was conducted on 203 glioblastoma (GBM) patients enrolled in NRG-BN001 and 70 nasopharyngeal carcinoma (NPC) patients enrolled in NRG-HN001. For each trial, fifty high-quality photon plans were utilized to build a KBP photon model. A KBP proton model was generated using intensity-modulated proton therapy (IMPT) plans generated on 50 patients originally treated with photon RT. These models were then applied to generate KBP plans for the remaining patients, which were compared against the submitted plans for quality evaluation, including in terms of protocol compliance, target coverage, and organ-at-risk (OAR) doses. RT plans generated by the KBP models were demonstrated to have superior quality compared to the submitted plans. KBP IMPT plans can decrease the variation of proton plan quality and could possibly be used as a tool for developing improved plans in the future. Additionally, the KBP tool proved to be an effective instrument for RT plan QA in multi-center clinical trials.

Prediction of DNA methylation-based tumor types from histopathology in central nervous system tumors with deep learning.

Precision in the diagnosis of diverse central nervous system (CNS) tumor types is crucial for optimal treatment. DNA methylation profiles, which capture the methylation status of thousands of individual CpG sites, are state-of-the-art data-driven means to enhance diagnostic accuracy but are also time consuming and not widely available. Here, to address these limitations, we developed Deep lEarning from histoPathoLOgy and methYlation (DEPLOY), a deep learning model that classifies CNS tumors to ten major categories from histopathology. DEPLOY integrates three distinct components: the first classifies CNS tumors directly from slide images ('direct model'), the second initially generates predictions for DNA methylation beta values, which are subsequently used for tumor classification ('indirect model'), and the third classifies tumor types directly from routinely available patient demographics. First, we find that DEPLOY accurately predicts beta values from histopathology images. Second, using a ten-class model trained on an internal dataset of 1,796 patients, we predict the tumor categories in three independent external test datasets including 2,156 patients, achieving an overall accuracy of 95% and balanced accuracy of 91% on samples that are predicted with high confidence. These results showcase the potential future use of DEPLOY to assist pathologists in diagnosing CNS tumors within a clinically relevant short time frame.

Meningioma transcriptomic landscape demonstrates novel subtypes with regional associated biology and patient outcome.

Meningiomas, although mostly benign, can be recurrent and fatal. World Health Organization (WHO) grading of the tumor does not always identify high-risk meningioma, and better characterizations of their aggressive biology are needed. To approach this problem, we combined 13 bulk RNA sequencing (RNA-seq) datasets to create a dimension-reduced reference landscape of 1,298 meningiomas. The clinical and genomic metadata effectively correlated with landscape regions, which led to the identification of meningioma subtypes with specific biological signatures. The time to recurrence also correlated with the map location. Further, we developed an algorithm that maps new patients onto this landscape, where the nearest neighbors predict outcome. This study highlights the utility of combining bulk transcriptomic datasets to visualize the complexity of tumor populations. Further, we provide an interactive tool for understanding the disease and predicting patient outcomes. This resource is accessible via the online tool Oncoscape, where the scientific community can explore the meningioma landscape.

Meningioma: International Consortium on Meningiomas (ICOM) consensus review on scientific advances & treatment paradigms for clinicians, researchers, and patients.

Meningiomas are the most common primary intracranial tumors in adults and are increasing in incidence due to the aging population and the rising availability of neuroimaging. While most exhibit non-malignant behaviour, a subset of meningiomas are biologically aggressive and lead to significant neurological morbidity and mortality. In recent years, meaningful advances in our understanding of the biology of these tumors have led to the incorporation of molecular biomarkers into their grading and prognostication. However, unlike other central nervous system tumors, a unified molecular taxonomy for meningiomas has not yet been established and remains an overarching goal of the Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy-Not Official WHO (cIMPACT-NOW) working group. There also remains clinical equipoise on how specific meningioma cases and patient populations should be optimally managed. To address these existing gaps, members of the International Consortium on Meningiomas (ICOM) including field-leading experts, have prepared a comprehensive consensus narrative review directed towards clinicians, researchers, and patients. Included in this manuscript are detailed overviews of proposed molecular classifications, novel biomarkers, contemporary treatment strategies, trials on systemic therapies, health-related quality of life studies, and management strategies for unique meningioma patient populations. In each section we discuss the current state of knowledge as well as ongoing clinical and research challenges to road map future directions for further investigation.