Visualizing genomic characteristics across an RNA-Seq based reference landscape of normal and neoplastic brain

Abstract

In order to better understand the relationship between normal and neoplastic brain, we combined five publicly available large-scale datasets, correcting for batch effects and applying Uniform Manifold Approximation and Projection (UMAP) to RNA-Seq data. We assembled a reference Brain-UMAP including 702 adult gliomas, 802 pediatric tumors and 1409 healthy normal brain samples, which can be utilized to investigate the wealth of information obtained from combining several publicly available datasets to study a single organ site. Normal brain regions and tumor types create distinct clusters and because the landscape is generated by RNA-Seq, comparative gene expression profiles and gene ontology patterns are readily evident. To our knowledge, this is the first meta-analysis that allows for comparison of gene expression and pathways of interest across adult gliomas, pediatric brain tumors, and normal brain regions. We provide access to this resource via the open source, interactive online tool Oncoscape, where the scientific community can readily visualize clinical metadata, gene expression patterns, gene fusions, mutations, and copy number patterns for individual genes and pathway over this reference landscape.

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

“…This landscape is made up of multiple clusters of different sizes, all of which are composed of a mix of the 13 datasets with the exception of the HKU/UCSF dataset (GSE212666) for which a minor subset of patients forms two, small unique clusters (11% of HKU/UCSF dataset) (Figure 1B). In addition to UMAP, we explored other dimension reduction techniques (Principal Component Analysis (PCA) and t-distributed Stochastic Neighbor Embedding (tSNE)) and found that UMAP better distinguished clusters that showed differences in clinical and genomic features (Figures S1B, S1C) 27 . The collection of tumor samples included fresh frozen tissue as well as Formalin-Fixed Paraffin-Embedded tissue.…”

“…Gene expression values from combined datasets were normalized and converted to units of log2 transcripts per million (log2(TPM+1)) 26 . Uniform Manifold Approximation and Projection (UMAP), a dimensionality reduction method, was applied on normalized counts from 19979 protein-coding genes to create the meningioma reference landscape 27 . UMAPs were constructed using the R package "umap" (https://cran.r-project.org/web/packages/umap/index.html).…”

Transcriptional profiling of human brain cortex identifies novel lncRNA-mediated networks dysregulated in amyotrophic lateral sclerosis

“…2 g), with the higher expression in brain spinal cord. Among these lncRNAs, only one - LINC01445 – has been previously studied, as it has been found fused to EGFR in 17.7% of adult IDH-wt glioblastoma 62 . Interestingly, the green module resulted unconnected to the rest of the network: as network edges represent co-expression relationships between genes, such a scenario indicates possible features (e.g.…”

Semântica em prontuários eletrônicos para oncologia pediátrica: uma revisão integrativa

“…Table 4 presents the summary of Review 2, including KOS adopted in the EHR and the key contribution. Eleven studies were analyzed in Review 3, of each the studies (12,13,14,15,16) use GO, work (17) used both GO and NCIt, works (18,19) refer to the NCIt, and other three works are undefi ned regarding the use of KOS.…”

“…In reference (18) a modified Delphi approach is used to guide the Pediatric Cancer Data gathering. Work (15) uses GO in the visualization of genomic characteristics and reference (16) uses GO to reveal recurrent genetic and transcriptomic signatures.…”