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Gingival fibromatosis GF is a rare condition gene expression profiling von brustkrebs gingival overgrowth, characterized by a slowly progressive, benign, localized or generalized fibrous enlargement of maxillary and mandibular keratinized gingiva 1 — 3.

GF may co-exist with various genetic syndromes, such as Rutherfurd syndrome, Cowden syndrome, Zimmerman-Laband syndrome, Murray-Puretic syndrome and hyaline fibromatosis syndrome, or occurs as an apparent isolated trait as non-syndromic hereditary GF HGF 1 gene expression profiling von brustkrebs, 4 — 6.

HGF, also known as hereditary gingival hyperplasia or idiopathic gingival fibromatosis, is the most common genetic form of GF that is typically transmitted as an autosomal-dominant trait 78. HGF affects males and females equally at an estimated incidence of 1 perof the population 19. As HGF is rare and benign, and due to an increase in the number of non-surgical treatments, it is difficult to collect large samples of HGF. To date, four loci, namely 2p HGF exhibits an autosomal dominant inheritance pattern, although its penetrance and expressivity are variable 8.

Diagnosis of HGF mainly depends on medical history, clinical examination, blood tests and histopathological evaluation of affected gingival tissue 1. However, owing to high genetic heterogeneity, genetic testing to confirm the diagnosis is not justified It is therefore important to identify key signature genes and to understand the molecular mechanisms underlying HGF.

The raw gene expression gene expression profiling von brustkrebs was preprocessed with R v3. All gene expression values were obtained from the data of GSE using the affy package As some probes correspond to the same gene symbol, the average of the expression values of these probes was defined as the expression value of the gene. A total of 20, gene symbols were identified following preprocessing.

The pheatmap package in R was used to generate a heatmap for the visualization of these DEGs. The minimum required interaction score was set to 0. Subsequently, Cytoscape software v3. The degree of a node was defined as the number of direct interactions between the corresponding gene and others in the network. There were 65 upregulated genes and downregulated genes among these DEGs Fig.

Heatmap of differentially expressed genes in GSE Rows represent genes and columns represent samples. The heatmap is color-coded based on Z-score; red represents high expression value and green represents low expression value.

Protein-protein interaction network of differentially expressed genes in GSE The color of each node represents the logFC value of the corresponding gene; the size of each node represents the degrees connections of the corresponding gene with others in the network.

FC, fold-change. Differentially expressed genes in the protein-protein interaction network and their corresponding degree. In the current periodontal diseases and conditions classification, which was developed by Armitage in 21HGF is defined a benign, non-hemorrhagic and fibrous gingival overgrowth that may cover all or part of the teeth.

HGF is also one of the subtypes of gingival lesions of genetic origin among gingival diseases 622 HGF gingiva is typically pink in color and has a fibrous appearance and marked stippling without signs of inflammation, and covers the teeth partially or totally with a variable degree of severity, without affecting the bone 623 — Gene expression profiling von brustkrebs generally interferes with speech, lip closure and chewing, and may also become a psychological burden by affecting the self-esteem of patients 6.

HGF presents an autosomal dominant inheritance pattern, although its penetrance and expressivity are variable. However, owing to high genetic heterogeneity, genetic testing to confirm the diagnosis is not justified. Thus, it is important to identify the key signature genes and to understand the molecular mechanisms of HGF. As an important discipline of biological science, bioinformatics analysis employs scientific resources for research purposes 27and is considered an efficient method for predicting disease-related genes.

Gene expression profiling von brustkrebs the present study, DEGs were identified, consisting of 65 upregulated and downregulated genes, in the GSE dataset.

Notably, among the top 10 upregulated genes of the DEGs, the gene encoding bone morphogenetic protein and activin membrane bound inhibitor has previously been associated with fibromatosis These results indicated that HGF-related enriched GO terms are gene expression profiling von brustkrebs associated with cell growth and tissue hyperplasia. Histologically, HGF is characterized by the growth and hyperplasia of gingival epithelial cells Straka et al 29 observed in HGF that some collagen fibrils exhibited loops in the gingival lamina propria and identified the presence of empty perinuclear space in the cytoplasm of epithelial cells.

These findings may relate to the enriched GO terms. The method of DEG screening or the algorithms of the tools used may have lead to this result. Furthermore, while it has not been reported that CALB2, is directly associated with HGF, Barak et al 30 documented that calretinin encoded by the CALB2 gene may be an important immunohistochemical marker in other benign and malignant fibromatosis.

The FGF family also serve an important role in fibroblast growth Meanwhile, Lee et al 32 reported that LOR was important in keratinocyte differentiation in a study on the cell envelope of normal human oral keratinocytes. C3 has also been associated with fibrous papule development Although reports on the functions of these core genes are limited, they may serve important roles in HGF.

This may have been due to the tools employed and the restricted screening parameters, as well as the limited scope of research on HGF. A crucial limitation gene expression profiling von brustkrebs the present study was the small number of samples with and without HGF. Therefore, larger datasets and further experiments, for instance using reverse transcription-quantitative polymerase chain reaction, are required to validate the present results.

Bioinformatics analysis is an efficient method for predicting potential diagnostic and therapeutic targets. However, the increased number of data mining and analytical tools and algorithms poses a challenge 34as results for the same data using gene expression profiling von brustkrebs bioinformatics tools may vary.

Furthermore, the predictions require verification through experimental and clinical methods. In summary, the prediction of potential diagnostic and therapeutic targets in diseases using bioinformatics methods is an efficient strategy in clinical research, though also poses a number of challenges. In the gene expression profiling von brustkrebs study, a public dataset of Gene expression profiling von brustkrebs was used to analyze the potential diagnostic and therapeutic targets of HGF.

The current predictions of potential diagnostic and therapeutic targets now require verification through experimental methods in cell and animal models prior to clinical trials. Orphanet J Rare Dis. View Article : Google Scholar. Case Rep Dent. BMJ Case Rep. J Indian Soc Periodontol. Chin J Dent Res. J Dent Res. Ann Plast Surg. Am J Hum Genet. J Clin Periodontol. Methods Mol Biol. Hum Genet. Nucleic Acids Res.

Nat Protoc. Curr Protoc Bioinformatics. Armitage GC: Development of a classification system for periodontal diseases and conditions. Ann Periodontol. J Periodontol. Journal of the American Dental Association. J Periodontal Res. J Bone Gene expression profiling von brustkrebs Res.

Neuro Endocrinol Lett. Gene expression profiling von brustkrebs S, Wang Z and Miettinen M: Immunoreactivity for calretinin and keratins in desmoid fibromatosis and other myofibroblastic tumors: A diagnostic pitfall. Am J Gene expression profiling von brustkrebs Pathol. Wiley Interdiscip Rev Dev Biol. FEBS Lett. J Cutan Pathol. Cancer Immunol Immunother. February Volume 8 Issue 2. Sign up for eToc alerts.

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I agree. Home Submit Manuscript My Account. Advanced Search. Register Login. Biomedical Reports. Cited By CrossRef : 0 citations. This article is mentioned in:. Introduction Gingival fibromatosis GF is a rare condition of gingival overgrowth, characterized by a slowly progressive, benign, localized or generalized fibrous enlargement of maxillary and mandibular keratinized gingiva 1 — 3.

Materials and methods Gene expression microarray datasets The gene expression microarray data of the GSE dataset 14 were downloaded from the GEO database. Preprocessing of raw datasets The raw gene expression data was preprocessed with R v3. Top 10 up- and downregulated differentially expressed genes in GSE Related Articles.


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