Gene signature associated with benign neurofibroma transformation to malignant peripheral nerve sheath tumors.
Marta MartínezCarlos O S SorzanoAlberto Pascual-MontanoJose M CarazoPublished in: PloS one (2017)
Benign neurofibromas, the main phenotypic manifestations of the rare neurological disorder neurofibromatosis type 1, degenerate to malignant tumors associated to poor prognosis in about 10% of patients. Despite efforts in the field of (epi)genomics, the lack of prognostic biomarkers with which to predict disease evolution frustrates the adoption of appropriate early therapeutic measures. To identify potential biomarkers of malignant neurofibroma transformation, we integrated four human experimental studies and one for mouse, using a gene score-based meta-analysis method, from which we obtained a score-ranked signature of 579 genes. Genes with the highest absolute scores were classified as promising disease biomarkers. By grouping genes with similar neurofibromatosis-related profiles, we derived panels of potential biomarkers. The addition of promoter methylation data to gene profiles indicated a panel of genes probably silenced by hypermethylation. To identify possible therapeutic treatments, we used the gene signature to query drug expression databases. Trichostatin A and other histone deacetylase inhibitors, as well as cantharidin and tamoxifen, were retrieved as putative therapeutic means to reverse the aberrant regulation that drives to malignant cell proliferation and metastasis. This in silico prediction corroborated reported experimental results that suggested the inclusion of these compounds in clinical trials. This experimental validation supported the suitability of the meta-analysis method used to integrate several sources of public genomic information, and the reliability of the gene signature associated to the malignant evolution of neurofibromas to generate working hypotheses for prognostic and drug-responsive biomarkers or therapeutic measures, thus showing the potential of this in silico approach for biomarker discovery.
Keyphrases
- genome wide
- genome wide identification
- poor prognosis
- copy number
- systematic review
- dna methylation
- genome wide analysis
- transcription factor
- histone deacetylase
- cell proliferation
- clinical trial
- long non coding rna
- peripheral nerve
- gene expression
- healthcare
- bioinformatics analysis
- end stage renal disease
- endothelial cells
- electronic health record
- randomized controlled trial
- mental health
- small molecule
- chronic kidney disease
- quality improvement
- single cell
- ejection fraction
- pi k akt
- signaling pathway
- cancer therapy
- adverse drug
- machine learning
- drug induced
- molecular dynamics simulations
- human health
- breast cancer cells
- risk assessment
- cerebral ischemia
- binding protein
- subarachnoid hemorrhage
- data analysis