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Proteogenomics reveals two distinct biological pilocytic astrocytoma subgroups

ABSTRACT: Pilocytic astrocytoma (PA) is the most common pediatric brain tumor and driven by aberrant MAPK signaling, typically mediated by BRAF alterations. While five-year overall survival rates exceed 95%, tumor recurrence constitutes a major clinical challenge in incompletely resected tumors despite chemotherapeutic or radiation based therapies. Therefore, we used proteogenomics to discern the biological heterogeneity of PA to improve classification of this tumor entity and identify novel therapeutic targets. Our proteogenomics approach integrates RNA sequencing and LC/MS-based proteomic profiling data from a cohort of 58 confirmed, primary PA samples. An integrative genomics approach was conducted to discern the biological heterogeneity of PA and to identify aberrant pathway activation in these biological subgroups. In summary, Pilocytic astrocytomas segregate into two groups where younger patients are significantly associated with Group 1. Importantly, we validate the two distinct biological subgroups in two non-overlapping cohorts. The biological heterogeneity seen here may improve biological classification and reveal novel therapeutic targets specifically useful for non-resectable tumors with high risk of recurrent or progressive disease.

PROVIDER: EGAS00001006402 | EGA |

REPOSITORIES: EGA

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Proteogenomics reveals two distinct biological pilocytic astrocytoma subgroups

Project description:Pilocytic astrocytoma (PA) is the most common pediatric brain tumor and driven by aberrant MAPK signaling, typically mediated by BRAF alterations. While five-year overall survival rates exceed 95%, tumor recurrence constitutes a major clinical challenge in incompletely resected tumors despite chemotherapeutic or radiation based therapies. Therefore, we used proteogenomics to discern the biological heterogeneity of PA to improve classification of this tumor entity and identify novel therapeutic targets. Our proteogenomics approach integrates RNA sequencing and LC/MS-based proteomic profiling data from a cohort of 58 confirmed, primary PA samples. An integrative genomics approach was conducted to discern the biological heterogeneity of PA and to identify aberrant pathway activation in these biological subgroups. In summary, pilocytic astrocytomas segregate into two groups where younger patients are significantly associated with Group 1. Importantly, we validate the two distinct biological subgroups in two non-overlapping cohorts. The biological heterogeneity seen here may improve biological classification and reveal novel therapeutic targets specifically useful for non-resectable tumors with high risk of recurrent or progressive disease.

2023-09-20 | GSE210353 | GEO

Proteogenomics reveals two distinct biological pilocytic astrocytoma subgroups

Project description:Pilocytic astrocytoma (PA) is the most common pediatric brain tumor and driven by aberrant MAPK signaling, typically mediated by BRAF alterations. While five-year overall survival rates exceed 95%, tumor recurrence constitutes a major clinical challenge in incompletely resected tumors despite chemotherapeutic or radiation based therapies. Therefore, we used proteogenomics to discern the biological heterogeneity of PA to improve classification of this tumor entity and identify novel therapeutic targets. Our proteogenomics approach integrates RNA sequencing and LC/MS-based proteomic profiling data from a cohort of 58 confirmed, primary PA samples. An integrative genomics approach was conducted to discern the biological heterogeneity of PA and to identify aberrant pathway activation in these biological subgroups. In summary, Pilocytic astrocytomas segregate into two groups where younger patients are significantly associated with Group 1. Importantly, we validate the two distinct biological subgroups in two non-overlapping cohorts. The biological heterogeneity seen here may improve biological classification and reveal novel therapeutic targets specifically useful for non-resectable tumors with high risk of recurrent or progressive disease.

2023-10-24 | PXD035773 | Pride

Proteogenomics reveals two distinct biological pilocytic astrocytoma subgroups

Project description:Proteogenomics reveals two distinct biological pilocytic astrocytoma subgroups

| PRJNA865354 | ENA

Molecular refinement of pilocytic astrocytoma in adult patients

Project description:Genome wide DNA methylation profiling of 79 histologically diagnosed pilocytic astrocytoma (PA) in adults, of which we were able to upload 71 samples. The methylation profiling indicates that many of the histologically diagnosed PA do not show a concordant methylation classification.

2024-01-01 | GSE244566 | GEO

Illumina Infinium HumanMethylation EPIC beadchip profiling of 31 pediatric histologically defined anaplastic pilocytic astrocytoma

Project description:We used the Illumina Infinium HumanMethylation EPIC beadchip array to profile 31 pediatric tumors with the histological diagnosis of anaplastic pilocytic astrocyoma (PA). PA with anaplasia has been defined in the 2016 WHO classification as a tumor with PA morphology and >4 mitoses per 10 HPF, with or without necrosis with a potential worse outcome. DNA Methylation based studies performed mainly in adults have put forward this subtype as a distinct entity. After performing the same techniques on pediatric samples, our findings argue that the diagnostic histomolecular criteria established for anaplasia in adult PA are not of diagnostic or prognostic value in a pediatric setting.

2019-11-08 | E-MTAB-8390 | biostudies-arrayexpress

Four subgroups by gene expression profile correlate with biological and clinical features in colorectal cancer.

Project description:(Purpose) Biological classification of colorectal cancer (CRC) can help to understand its heterogeneous background. The purpose of this study is to classify CRC based on gene expression profiles using formalin-fixed paraffin-embedded (FFPE) samples and to correlate subgroups of CRC with biological features and clinical outcomes. (Results) CRC was clustered into four subgroups by unsupervised hierarchical clustering method. These subgroups show different biological and clinical features. (Conclusion) Gene expression profiles of CRC using FFPE samples distinguish four subgroups that had different biological features and clinical outcomes. These subgroups may explain heterogeneity of CRC and be useful biomarker for clinical.

2014-01-01 | GSE33193 | GEO

Transcription profiling of human core binding factor acute myeloid leukemias to identify molecular subclasses within the group

Project description:Core binding factor (CBF) leukemias, characterized by either inv(16)/t(16;16) or t(8;21), constitute acute myeloid leukemia (AML) subgroups with favorable prognosis. However, there exists substantial biological and clinical heterogeneity within these cytogenetic groups, which is not fully reflected by the current classification system. To improve the molecular characterization we profiled gene expression in a large series (n=93) of AML patients with CBF leukemia [inv(16) n=55, t(8;21) n=38]. By unsupervised hierarchical clustering we were able to define a subgroup of CBF cases (n=35) characterized by shorter overall survival times (P=0.03). While there was no obvious correlation with fusion gene transcript levels, FLT3 tyrosine kinase domain, KIT, and NRAS mutations, the newly defined inv(16)/t(8;21)-subgroup was associated with elevated white blood cell counts and FLT3 internal tandem duplications (P=0.011 and P=0.026, respectively). Supervised analyses of gene expression suggested alternative cooperating pathways leading to transformation. In the ?favorable? CBF leukemias anti-apoptotic mechanisms and deregulated mTOR-signaling, and in the newly defined ?unfavorable? subgroup aberrant MAPKinase-signaling and chemotherapy-resistance mechanisms might play a role. While the leukemogenic relevance of these signatures remains to be validated, their existence nevertheless supports a prognostically relevant biological basis for the heterogeneity observed in CBF leukemia.

2007-06-10 | E-SMDB-4056 | biostudies-arrayexpress

Gene expression data from pilocytic astrocytoma tumour samples and normal cerebellum controls

Project description:Pilocytic astrocytomas (PA) are the most common brain tumor in pediatric patients and can cause significant morbidity, including chronic neurological deficiencies. They are characterized by activating alterations in the mitogen-activated protein kinase (MAPK) pathway, but little else is known about their development. To further define their molecular development, we analysed the global DNA methylation profiles of 61 PAs and 6 normal cerebellum samples and integrated this data with transcriptome profiling. These data revealed two subgroups of PA that separate according to tumor location (infratentorial versus supratentorial), and identified key neural developmental genes that are differentially methylated between the two groups. Significant expression differences were identified for the majority of differentially methylated genes, and these were unexpectedly associated with a strong positive correlation between methylation and expression. We also identified a large number of differentially methylated/expressed genes between cerebellar PAs and normal cerebellum, which included additional developmental genes.

2013-06-12 | GSE44971 | GEO

Gene expression data from pilocytic astrocytoma tumour samples and normal cerebellum controls

2013-06-12 | E-GEOD-44971 | biostudies-arrayexpress

DNA methylation data from pilocytic astrocytoma tumor samples and normal cerebellum controls

Project description:Pilocytic astrocytomas (PA) are the most common brain tumor in pediatric patients and can cause significant morbidity, including chronic neurological deficiencies. They are characterized by activating alterations in the mitogen-activated protein kinase (MAPK) pathway, but little else is known about their development. To map the global DNA methylation profiles of these tumors, we analysed 61 PAs and 6 normal cerebellum samples using Illumina's Infinium HumanMethylation450 BeadChips. These data revealed two subgroups of PA that separate according to tumor location (infratentorial versus supratentorial), and identified key neural developmental genes that are differentially methylated between the two groups. Integration with transcriptome microarray data highlighted significant expression differences, which were unexpectedly associated with a strong positive correlation between methylation and expression. Differentially methylated probes were often identified within the gene body and/or regions up- or downstream of the gene, rather than at the transcription start site. We also identified a large number of differentially methylated genes between cerebellar PAs and normal cerebellum, which included additional developmental genes.

2013-06-12 | GSE44684 | GEO

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