Reclassification of TCGA Diffuse Glioma Profiles Linked to Transcriptomic, Epigenetic, Genomic and Clinical Data, According to the 2021 WHO CNS Tumor Classification

Abstract

In 2021, the fifth edition of the WHO classification of tumors of the central nervous system (WHO CNS5) was published. Molecular features of tumors were directly incorporated into the diagnostic decision tree, thus affecting both the typing and staging of the tumor. It has changed the traditional approach, based solely on histopathological classification. The Cancer Genome Atlas project (TCGA) is one of the main sources of molecular information about gliomas, including clinically annotated transcriptomic and genomic profiles. Although TCGA itself has played a pivotal role in developing the WHO CNS5 classification, its proprietary databases still retain outdated diagnoses which frequently appear incorrect and misleading according to the WHO CNS5 standards. We aimed to define the up-to-date annotations for gliomas from TCGA’s database that other scientists can use in their research. Based on WHO CNS5 guidelines, we developed an algorithm for the reclassification of TCGA glioma samples by molecular features. We updated tumor type and diagnosis for 828 out of a total of 1122 TCGA glioma cases, after which available transcriptomic and methylation data showed clustering features more consistent with the updated grouping. We also observed better stratification by overall survival for the updated diagnoses, yet WHO grade 3 IDH-mutant oligodendrogliomas and astrocytomas are still indistinguishable. We also detected altered performance in the previous diagnostic transcriptomic molecular biomarkers (expression of SPRY1, CRNDE and FREM2 genes and FREM2 molecular pathway) and prognostic gene signature (FN1, ITGA5, OSMR, and NGFR) after reclassification. Thus, we conclude that further efforts are needed to reconsider glioma molecular biomarkers.

An atlas of causal and mechanistic drivers of interpatient heterogeneity in glioma

“… A) Distribution of patients with different disease subtypes according to 2021 WHO classification 17 across each state. B) Boxplots of GuanRank risk scores for patients within transcriptional states, rank ordered from low to high median risk (from L to R, respectively).…”

“…For sake of consistency with prior work especially the TCGA nomenclature, we have decided to use “GBM” with the caveat that some of the tumors in this cohort may not meet the criteria of how GBM is currently defined. To help the reader relate the findings we have provided a mapping of the new classification across all relevant results throughout the paper by using previous annotations 17 ( Supplementary Table 9 ). Analysis of gene expression and copy number alterations of GBM cataloged in The Cancer Genome Atlas (TCGA) has revealed several molecular subtypes: mesenchymal, proneural, and classical.…”

RNA splicing analysis deciphers developmental hierarchies and reveals therapeutic targets in adult glioma

“…The neural lineage markers list is obtained from the neural marker booklet available on the Abcam website: https:// www.abcam.com/neuroscience/neural-markers-guide. TCGA Samples have been reclassified according to the 2021 WHO CNS5 guidelines (62). Genetic information, including TERT promoter mutation, EGFR amplification, and chromosome +7/−10, is required to establish the molecular diagnosis of GBM.…”

Molecular landscapes of glioblastoma cell lines revealed a group of patients that do not benefit from WWOX tumor suppressor expression

“…Subsequently, patients with desired WWOX / POLE4 / HSF2BP expression were selected via which() function in the R environment and further subjected to survival analysis using the surfvit(), of which results were visualized using ggsurvplot(). For each patient from the designated groups, the supplementary clinical information and data on molecular subtypes were acquired from the literature ( Brennan et al, 2013 ; Wang et al, 2017 ; Zakharova et al, 2022 ), whereas the drug sensitivity prediction for Temozolomide (TMZ) measured by Half-maximal inhibitory concentration (IC50) was obtained from the CancerRxTissue repository ( Li et al, 2021 ). These additional data were visualized using pROC and ggplot2 R-packages ( Robin et al, 2011 ).…”