Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: EC:2.7.10.1 (ERK)
 95,504 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

Each breast cancer has its unique spatial shape, but the clinical importance and the underlying mechanism for the three-dimensional tumor shapes are mostly unknown. We collected the data on the three-dimensional tumor size and tumor volume data of invasive breast cancers from 2,250 patients who underwent surgery between Jan 2000 and Jul 2007. The degree of tumor eccentricity was estimated by using the difference between the spheroid tumor volume and ellipsoid tumor volume (spheroid-ellipsoid discrepancy, SED). In 41 patients, transcriptome and exome sequencing data obtained. Estimation of more accurate tumor burden by calculating ellipsoid tumor volumes did not improve the outcome prediction when compared to the traditional longest diameter measurement. However, the spatial tumor eccentricity, which was measured by SED, showed significant variation between the molecular subtypes of breast cancer. Additionally, the degree of tumor eccentricity was associated with well-known prognostic factors of breast cancer such as tumor size and lymph node metastasis. Transcriptome data from 41 patients showed significant association between MMP13 and spatial tumor shapes. Network analysis and analysis of TCGA gene expression data suggest that MMP13 is regulated by ERBB2 and S100A7A. The present study validates the usefulness of the current tumor size method in determining tumor stages. Furthermore, we show that the tumors with high eccentricity are more likely to have aggressive tumor characteristics. Genes involved in the extracellular matrix remodeling can be candidate regulators of the spatial tumor shapes in breast cancer.
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PMID:The Clinical Significance and Molecular Features of the Spatial Tumor Shapes in Breast Cancers. 2666 40

FLT3-ITD+ acute myeloid leukemia (AML) is an important subtype of AML, accounting for approximately 25 % of all AML cases in the world. Recently, increasing evidence has shown that circular RNAs (circRNAs) can act as effective biomarkers of various human cancers. However, the roles of circRNAs in AML remain largely unclear. In the present study, circ_0000370 was found to be significantly increased in FLT3-ITD+ AML and was demonstrated to act as an oncogenic circRNA of AML in vitro. TargetScan results showed that miR-1299, miR-370-3p, miR-502-5p, miR-1281 and miR-640 were potential targets of circ_0000370, and miR-1299 had the broadest range of interactome compared with other microRNAs of interest. Moreover, we demonstrated that S100A7A was a target gene of miR-1299, and circ_0000370 could regulate S100A7A expression by sponging miR-1299 in AML cell lines. Therefore, we suggest that the promoting effects of circ_0000370 on the progression of FLT3-ITD+ AML might be relevant to the inhibition of miR-1299 and the upregulation of S100A7A.
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PMID:A novel circular RNA (hsa_circ_0000370) increases cell viability and inhibits apoptosis of FLT3-ITD-positive acute myeloid leukemia cells by regulating miR-1299 and S100A7A. 3191 40

Immunotherapies targeting interleukin (IL)-17 greatly improve plaque psoriasis. Most previous studies on IL-17 focused on the T-helper (Th)17 immune response, but investigation of the effects of IL-17A on psoriatic epidermal structure are limited. Using an in vitro 3-D human epidermis model, we investigated the effects of IL-17A and IL-17C on morphological changes and gene expression. IL-17A directly suppressed the formation of the granular layer, whereas IL-17C did not. IL-17A significantly downregulated the gene expression of profilaggrin (FLG), which is a major component of keratohyalin granules in the granular layer. Global gene expression analysis of this 3-D epidermis model showed that both IL-17A and IL-17C upregulated S100A7A and type 1 interferon-related genes including MX1, IFI44L, XAF1 and IFIT1. However, only IL-17A directly downregulated keratinocyte differentiation-related and cornified envelope-related genes including FLG, LOR, C1ORF68, LCE1E, LCE1B, KRT10, CST6 and RPTN. In conclusion, IL-17A, a systemic inflammatory cytokine, affected keratinization in our 3-D epidermis model. In contrast, IL-17C, a locally produced cytokine, did not have strong effects on keratinization. Targeting IL-17A does not only reduce inflammation but it may also directly affect epidermal differentiation in psoriasis.
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PMID:Interleukin-17A suppresses granular layer formation in a 3-D human epidermis model through regulation of terminal differentiation genes. 3202 Jun 72