Validation of Whole Genome Methylation Profiling Classifier for Central Nervous System Tumors

Santana-Santos, Lucas; Kam, Kwok Ling; Dittmann, David; Vito, Stephanie De; McCord, Matthew; Jamshidi, Pouya; Fowler, Hailie; Wang, Xinkun; Aalsburg, Alan M.; Brat, Daniel J.; Horbinski, Craig; Jennings, Lawrence J.

doi:10.1016/j.jmoldx.2022.04.009

Cited by 13 publications

(12 citation statements)

References 18 publications

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“…The development of the DKFZ/Heidelberg CNS tumor methylation classifier significantly contributes to our comprehension of methylation patterns and their interplay with clinical variables. This advancement greatly enhances the precision of molecular pathological classification in the realm of brain tumors [ 42 , 44 ].…”

Section: Resultsmentioning

confidence: 99%

Epidemiology, Diagnostic Strategies, and Therapeutic Advances in Diffuse Midline Glioma

Miguel Llordes,

Medina Pérez,

Curto Simón

et al. 2023

JCM

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Object: Diffuse midline glioma (DMG) is a highly aggressive and lethal brain tumor predominantly affecting children and young adults. Previously known as diffuse intrinsic pontine glioma (DIPG) or grade IV brain stem glioma, DMG has recently been reclassified as “diffuse midline glioma” according to the WHO CNS5 nomenclature, expanding the DMG demographic. Limited therapeutic options result in a poor prognosis, despite advances in diagnosis and treatment. Radiotherapy has historically been the primary treatment modality to improve patient survival. Methods: This systematic literature review aims to comprehensively compile information on the diagnosis and treatment of DMG from 1 January 2012 to 31 July 2023. The review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement and utilized databases such as PubMed, Cochrane Library, and SciELO. Results: Currently, molecular classification of DMG plays an increasingly vital role in determining prognosis and treatment options. Emerging therapeutic avenues, including immunomodulatory agents, anti-GD2 CAR T-cell and anti-GD2 CAR-NK therapies, techniques to increase blood–brain barrier permeability, isocitrate dehydrogenase inhibitors, oncolytic and peptide vaccines, are being explored based on the tumor’s molecular composition. However, more clinical trials are required to establish solid guidelines for toxicity, dosage, and efficacy. Conclusions: The identification of the H3K27 genetic mutation has led to the reclassification of certain midline tumors, expanding the DMG demographic. The field of DMG research continues to evolve, with encouraging findings that underscore the importance of highly specific and tailored therapeutic strategies to achieve therapeutic success.

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Section: Resultsmentioning

confidence: 99%

Epidemiology, Diagnostic Strategies, and Therapeutic Advances in Diffuse Midline Glioma

Miguel Llordes,

Medina Pérez,

Curto Simón

et al. 2023

JCM

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“…Previous studies of methylation classifiers have indicated that sample tumor purities affect classifier performance 17,27,28 . Tumor purities in the present study were similar to those used for sarcoma classification 28 , but much lower than purities seen in central nervous system tumor classification 17,27 . While low tumor purities resulted in lower TUO classifier scores, they did not have a substantial effect on classification accuracy when not including classifier scores, similar to the patterns seen in previous sarcoma and TUO classifiers 28,29 .…”

Section: Discussionmentioning

confidence: 99%

“…A lack of class annotation has limited the value of investigations in many cases. Unsupervised clustering methods coupled with highly annotated clinical samples leads to improved model prediction and has been harnessed to successfully create novel classifiers for CNS tumors and sarcomas 17,27,28 . While most TUO classifiers to date have used data from TCGA and Gene Expression Omnibus (GEO), few approaches have been clinically validated using institutional TUO samples to assess real-world utility.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, methylation has been implicated as an important factor in both the transition of a tumor to a higher cancer stage 11 and from non-metastatic to metastatic 11,15 . Several studies have demonstrated the remarkable utility of methylation profiling for cancer classification, subtyping, and prognosis [16][17][18] . Given that methylation changes can be tissue-specific, this method holds great potential for examining TUO tumors 13,19,20 .…”

Section: Introductionmentioning

confidence: 99%

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Accurate Identification of Primary Site in Tumors of Unknown Origin (TUO) Using DNA Methylation

Santana-Santos,

Duckett,

Vormittag-Nocito

et al. 2024

Preprint

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Tumors of unknown origin (TUO) generally result in poor patient survival and are clinically difficult to address. Identification of the site of origin in TUO patients is paramount to their improved treatment and survival but is difficult to obtain with current methods. Here, we develop a random forest machine learning TUO methylation classifier using a large number of primary and metastatic tumor samples. Our classifier achieves high accuracy in primary site identification when applied to both publicly available and internal validation samples, with 97% of samples classified correctly and 85% receiving high probability scores (≥ 0.9). Moreover, by employing pathologist expertise and unsupervised clustering, the TUO classifier can assign samples to 46 different site of origin/disease classes. This strategy also revealed multiple classes of yet unknown significance for future exploration. Overall, the presented TUO classifier represents a significant step forward in the diagnosis of TUO tumors.

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“…Retrospective analyses of large CNS cancer cohorts have demonstrated the robustness of methylation-based classifier approaches [ 2 , 3 ] and their ability to provide more precise diagnostic information in the setting of indeterminant diagnoses, to the extent that the 2021 WHO Guidelines for diagnosis of CNS malignancies included methylation-based classification within the standard of diagnosis [ 4 ]. Recently, a large prospective trial of methylation array-based classification was reported for pediatric patients with CNS malignancies, further demonstrating improved precision in sub-group classification (e.g., higher granularity among similarly subtyped classes of CNS cancers) and linking new sub-group classifications to outcomes [ 5 ▪▪ ].…”

Section: Overview Of Genomic Toolsmentioning

confidence: 99%

Overview of modern genomic tools for diagnosis and precision therapy of childhood solid cancers

Mardis

2023

Current Opinion in Pediatrics

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Purpose of review The application of technology and computational analyses to generate new data types from pediatric solid cancers is transforming diagnostic accuracy. This review provides an overview of such new capabilities in the pursuit of improved treatment for essentially rare and underserved diseases that are the highest cause of mortality in children over one year of age. Sophisticated ways of identifying therapeutic vulnerabilities for highly personalized treatment are presented alongside cutting-edge disease response monitoring by liquid biopsy. Recent findings Precision molecular profiling data are now being combined with conventional pathology-based evaluation of pediatric cancer tissues. The resulting diagnostic information can be used to guide therapeutic decision-making, including the use of small molecule inhibitors and of immunotherapies. Integrating somatic and germline variant profiles constitutes a critical component of this emerging paradigm, as is tissue-of-origin derivation from methylation profiling, and rapid screening of potential therapies. These new approaches are poised for use in disease response and therapy resistance monitoring. Summary The integration of clinical molecular profiling data with pathology can provide a highly precise diagnosis, identify therapeutic vulnerabilities, and monitor patient responses, providing next steps toward precision oncology for improved outcomes, including reducing lifelong treatment-related sequelae.

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Validation of Whole Genome Methylation Profiling Classifier for Central Nervous System Tumors

Cited by 13 publications

References 18 publications

Epidemiology, Diagnostic Strategies, and Therapeutic Advances in Diffuse Midline Glioma

Epidemiology, Diagnostic Strategies, and Therapeutic Advances in Diffuse Midline Glioma

Accurate Identification of Primary Site in Tumors of Unknown Origin (TUO) Using DNA Methylation

Overview of modern genomic tools for diagnosis and precision therapy of childhood solid cancers

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