| Literature DB >> 35668402 |
Marcos Yébenes Mayordomo1, Sofian Al Shboul2, Maria Gómez-Herranz3,4, Asim Azfer4, Alison Meynert5, Donald Salter4, Larry Hayward4, Anca Oniscu6, James T Patton7, Ted Hupp4, Mark J Arends4, Javier Antonio Alfaro8.
Abstract
BACKGROUND: Gorham-Stout disease is a rare condition characterized by vascular proliferation and the massive destruction of bone tissue. With less than 400 cases in the literature of Gorham-Stout syndrome, we performed a unique study combining whole-genome sequencing and RNA-Seq to probe the genomic features and differentially expressed pathways of a presented case, revealing new possible drivers and biomarkers of the disease. CASEEntities:
Keywords: AKT; Autophagy; Case report; Fusions; Genomics; Gorham-Stout; Mutations; PI3K; Transcriptomics; mTOR
Mesh:
Substances:
Year: 2022 PMID: 35668402 PMCID: PMC9169400 DOI: 10.1186/s12920-022-01277-x
Source DB: PubMed Journal: BMC Med Genomics ISSN: 1755-8794 Impact factor: 3.622
Fig. 1Gorham stout whole-genome sequencing mutation exploration. a 643 single nucleotide variants and small mutations were detected in 233 genes in the GS tissue, b Top 20 genes containing the most number of mutations in the GS tissue. c Circos plot comparing the number of small mutations (red) and structural variants (blue)
Fig. 2In silico study and validation of gene fusions detected in the GS tissue. a Circos plot of the gene fusions reveals a high number of interchromosomal fusions (red) especially affecting chromosomes 7, 12, and 20. b PCR Validation of the gene fusion candidates. Each fusion contains 3 columns showing the normal adjacent tissue DNA, the GS tissue DNA and a negative control from left to right respectively
Fig. 3RNA expression analysis between Gorham-Stout tissue and adjacent normal. a Volcano plot of the RNA-seq differential expression analysis showing a large number of genes up and down-regulated in GS tissue. b Results of the gene set enrichment analysis (GSEA) selecting the lymph-angiogenesis (VEGF) and osteolysis (NOTCH) pathways. A heavily weighted distribution in multiple genes was found in both pathways, with a high number of genes overexpressed in either GS tissue or the attached normal
Fig. 4Alterations in the PI3K/AKT signaling pathway in GS tissue. a Brief representation of gene members in the PI3K/AKT pathway. Most genes showed changes in expression when comparing adjacent normal to GS tissue affecting other metabolic pathways. b Heatmap representation of the gene members affected by RNA-seq expression changes between normal and GS tissue. PTEN and MDM2 showed over-expression in GS tissue while most of the other affected genes appear down-regulated when compared to adjacent normal
Fig. 5Representative IHC stained images showing the distribution of CD3, CD4, CD8, CD20, and CD163 cell markers. The representative images exhibit the immunohistochemical features of infiltrating immune cells: a CD3+ T cells, b CD4+ T cells, c CD8+ T cells, d CD20+ B cells, e CD163+ M2 macrophages, and f H&E staining. Scale bars show 50 μm. g RNA comparison of a variety of immune cell types between Gorham-Stout disease and normal specimens. The analysis was conducted with 4 technical replicates
Summary of the percentage of cells stained for CD3, CD4, CD8, CD20, and CD163 cell markers within the Gorham-Stout disease sample
| Sample | Positive (%) | Rho | P value |
|---|---|---|---|
| CD3 | 8.22 | 0.997 | < 0.0001 |
| CD4 | 0.06 | 0.986 | < 0.0001 |
| CD8 | 5.93 | 0.991 | < 0.0001 |
| CD20 | 4.86 | 0.995 | < 0.0001 |
| CD163 | 20.01 | 0.996 | < 0.0001 |
The biopsy sections were stained with the following cell markers: CD3, CD4, CD8, CD20, and CD163. Positively stained cells (expressed as a percentage of total cells) were automatically counted using QuPath (version 0.2.0-m7). The methodology was verified by comparing manual counting with QuPath counting in 0.2 mm. [44–46] areas selected randomly across the different sections. Pearson’s correlation (Rho) and P values were calculated