Biology subjects

Walbert, T.

Publications and source records attributed to Walbert, T..

3 recordsLinked to original sources

bioRxiv2026

Single-nucleus multiomics unveils malignant cellular states, regulatory architectures and microenvironmental reorganization across the G-CIMP epigenomic transition in IDH-mutant glioma

IDH-mutant gliomas stratified by glioma CpG island methylator phenotype (G-CIMP) into High (GCH) and Low (GCL) exhibit markedly divergent clinical outcomes, yet cellular and regulatory determinants of this distinction remain incompletely defined. Integrating single-nucleus RNA-and ATAC-sequencing across 18 tumor specimens from 10 patients, we resolved six malignant cellular states whose differential enrichment across G-CIMP strata delineates the GCL epigenomic transition. GCL tumors were enriched for independently prognostic Mesenchymal and Mitotic Proliferative states, driven by convergent E2F, MYC, MEF2, and NFI-family regulatory networks confirmed across chromatin, histone, and transcriptomic modalities. Pseudotime trajectory inference revealed a multifurcating developmental model from an Astrocytic-like origin, with GCL tumors gaining preferential access to proliferative and mesenchymal endpoints. A reorganized immune microenvironment and candidate therapeutic axes including CDK4/6-E2F, MYC/BET, KIF11, and NOTCH, potentially combinable with vorasidenib as an epigenomic backbone provide a translationally actionable framework for intercepting GCL progression in IDH-mutant glioma.

cancer biology↗

bioRxiv2020

DNA Methylation-based Signatures Classify Sporadic Pituitary Tumors According to Clinicopathological Features.

BackgroundDistinct genome-wide methylation patterns have consistently clustered pituitary neuroendocrine tumors (PT) into molecular groups associated with specific clinicopathological features. Here we aim to identify, characterize and validate the methylation signatures that objectively classify PT into those molecular groups. MethodsCombining in-house and publicly available data, we conducted an analysis of the methylome profile of a comprehensive cohort of 177 tumor and 20 non-tumor specimens from the pituitary gland. We also retrieved methylome data from an independent pituitary tumor (PT) cohort (N=86) to validate our findings. ResultsWe identified three methylation clusters associated with functional status and adenohypophyseal cell lineages using an unsupervised approach. We also identified signatures based on differentially methylated CpG probes (DMP), some of which overlapped with pituitary-specific transcription factors genes (SF1 and Tpit), that significantly distinguished pairs of clusters related to functional status and adenohypophyseal cell lineage. These findings were reproduced in an independent cohort, validating these methylation signatures. The DMPs were mainly annotated in enhancer regions associated with pathways and genes involved in cell identity and tumorigenesis. ConclusionsWe identified and validated methylation signatures that distinguished PT by distinct functional status and adenohypophyseal cell lineages. These signatures, annotated in enhancer regions, indicate the importance of these elements in pituitary tumorigenesis. They also provide an unbiased approach to classify pituitary tumors according to the most recent classification recommended by the WHO 2017 using methylation profiling. Key-pointsO_LIDistinct methylation landscapes define PT groups with specific functional status/subtypes and adenohypophyseal lineages subtypes. C_LIO_LIMethylation abnormalities in each cluster mainly occur in CpG annotated in distal regions overlapping predicted enhancers regions associated with pathways and genes involved in cell identity and tumorigenesis. C_LIO_LIDNA methylation signatures provide an unbiased approach to classify PT. C_LI Importance of the studyThis study harnessed the largest methylome data to date from a comprehensive cohort of pituitary specimens obtained from four different institutions. We identified and validated methylation signatures that distinguished pituitary tumors into molecular groups that reflect the functionality and adenohypophyseal cell lineages of these tumors. These signatures, mainly located in enhancers, are associated with pathways and genes involved in cell identity and tumorigenesis. Our results show that methylome profiling provides an objective approach to classify PT according to the most recent classification of PT recommended by the 2017 WHO.

cancer biology↗

bioRxiv2019

Detection of glioma and prognostic subtypes by non-invasive circulating cell-free DNA methylation markers

Genome-wide DNA methylation profiling has shown that epigenetic abnormalities are biologically important in glioma and can be used to classify these tumors into distinct prognostic groups. Thus far, DNA profiling has required surgically resected glioma tissue; however, gliomas release tumoral material into biofluids, such as blood and cerebrospinal fluid, providing an opportunity for a minimally invasive testing. While prior studies have shown that genetic and epigenetic markers can be detected in blood or cerebrospinal fluid (e.g., liquid biopsy [LB]), there has been low sensitivity for tumor-specific markers. We hypothesize that the low sensitivity is due to the targeted assay methods. Therefore, we profiled the genome-wide CpG methylation levels in DNA of tumor tissue and cell-free DNA in serum of glioma patients, to identify non-invasive epigenetic LB (eLB) markers in the serum that reflect the characteristics of the tumor tissue. From the epigenetic profiles of serum from patients diagnosed with glioma (N=15 IDH mutant and N=7 IDH wildtype) and with epilepsy (N=3), we defined glioma-specific and IDH-specific eLB signatures (Glioma-eLB and IDH-eLB, respectively). The epigenetic profiles of the matched tissue demonstrate that these eLB signatures reflected the signature of the tumor. Through cross-validation we show that Glioma-eLB can accurately predict a patients glioma from those with other neoplasias (N=6 Colon; N=14 Pituitary; N=3 Breast; N=4 Lung), non-neoplastic immunological conditions (N=22 sepsis; N=9 pancreatic islet transplantation), and from healthy individuals (sensitivity: 98%; specificity: 99%). Finally, IDH-eLB includes promoter methylated markers associated with genes known to be involved in glioma tumorigenesis (PVT1 and CXCR6). The application of the non-invasive eLB signature discovered in this study has the potential to complement the standard of care for patients harboring glioma.

cancer biology↗