Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts:   Target Concepts:
Query: EC:2.7.10.2 (focal adhesion kinase)
 44,029 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

In India, oral cancer has consistently ranked among top three causes of cancer-related deaths, and it has emerged as a top cause for the cancer-related deaths among men. Lack of effective therapeutic options is one of the main challenges in clinical management of oral cancer patients. We interrogated large pool of samples from oral cancer gene expression studies to identify potential therapeutic targets that are involved in multiple cancer hallmark events. Therapeutic strategies directed towards such targets can be expected to effectively control cancer cells. Datasets from different gene expression studies were integrated by removing batch-effects and was used for downstream analyses, including differential expression analysis. Dependency network analysis was done to identify genes that undergo marked topological changes in oral cancer samples when compared with control samples. Causal reasoning analysis was carried out to identify significant hypotheses, which can explain gene expression profiles observed in oral cancer samples. Text-mining based approach was used to detect cancer hallmarks associated with genes significantly expressed in oral cancer. In all, 2365 genes were detected to be differentially expressed genes, which includes some of the highly differentially expressed genes like matrix metalloproteinases (MMP-1/3/10/13), chemokine (C-X-C motif) ligands (IL8, CXCL-10/-11), PTHLH, SERPINE1, NELL2, S100A7A, MAL, CRNN, TGM3, CLCA4, keratins (KRT-3/4/13/76/78), SERPINB11 and serine peptidase inhibitors (SPINK-5/7). XIST, TCEAL2, NRAS and FGFR2 are some of the important genes detected by dependency and causal network analysis. Literature mining analysis annotated 1014 genes, out of which 841 genes were statistically significantly annotated. The integration of output of various analyses, resulted in the list of potential therapeutic targets for oral cancer, which included targets such as ADM, TP53, EGFR, LYN, CTLA4, SKIL, CTGF and CD70.
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PMID:Potential therapeutic targets for oral cancer: ADM, TP53, EGFR, LYN, CTLA4, SKIL, CTGF, CD70. 2502 26

Cholesteatoma is the growth of keratinizing squamous epithelium in the middle ear. It is associated with severe complications and has a poorly understood etiopathogenesis. Here, we present the results from extensive bioinformatics analyses of the first large-scale proteomic investigation of cholesteatoma. The purpose of this study was to take an unbiased approach to identifying alterations in protein expression and in biological processes, in order to explain the characteristic phenotype of this skin-derived tumor. Five different human tissue types (cholesteatoma, neck of cholesteatoma, tympanic membrane, external auditory canal skin, and middle ear mucosa) were analyzed. More than 2,400 unique proteins were identified using nanoLC-MS/MS based proteomics (data deposited to the ProteomeXchange), and 295 proteins were found to be differentially regulated in cholesteatoma. Validation analyses were performed by SRM mass spectrometry. Proteins found to be up- or down-regulated in cholesteatoma were analyzed using Ingenuity Pathway Analysis and clustered into functional groups, for which activation state and associations to disease processes were predicted. Cholesteatoma contained high levels of pro-inflammatory S100 proteins, such as S100A7A and S100A7. Several proteases, such as ELANE, were up-regulated, whereas extracellular matrix proteins, such as COL18A1 and NID2, were under-represented. This may lead to alterations in integrity and differentiation of the tissue (as suggested by the up-regulation of KRT4 in the cholesteatoma). The presented data on the differential protein composition in cholesteatoma corroborate previous studies, highlight novel protein functionalities involved in the pathogenesis, and identify new areas for targeted research that hold therapeutic potential for the disease.
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PMID:Large-scale proteomics differentiates cholesteatoma from surrounding tissues and identifies novel proteins related to the pathogenesis. 2509 96