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)

Gene identification by nonsense-mediated mRNA decay inhibition (GINI) has proven to be a strategy for genome-wide discovery of genes containing inactivating mutations in colon and prostate cancers. Here, we present the first study of inhibition of the nonsense-mediated mRNA decay (NMD) pathway in melanoma. We used a combination of emetine and actinomycin D treatment to stabilize mRNAs containing premature termination codons (PTCs), followed by microarray analysis and sequencing to identify novel tumor suppressor genes (TSGs) in a panel of 12 melanoma cell lines. Stringent analysis of the array data was used to select 35 candidate genes for sequencing. Of these, 4 (11%) were found to carry PTCs, including ARHGEF17, DENND2D, FGFR3, and RB1. While RB1 mutations have previously been described in melanoma, the other three genes represent potentially novel melanoma; TSGs. ARHGEF17 showed a G1865A mutation leading to W622X in a cell line derived from a mucosal melanoma; in RB1 a C1411T base change resulting in Q471X was discovered in a cell line derived from an acral melanoma; and the FGFR3 and DENND2D genes had intronic insertions leading to PTCs in cell lines derived from superficially spreading melanomas. We conclude that although the false positive rate is high, most likely due to the lack of DNA mismatch repair gene defects, the GINI protocol is one approach to discover novel TSGs in melanoma.
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PMID:Identification of ARHGEF17, DENND2D, FGFR3, and RB1 mutations in melanoma by inhibition of nonsense-mediated mRNA decay. 1867 70

The interplay between copy number variation (CNV) and differential gene expression may be able to shed light on molecular process underlying breast cancer and lead to the discovery of cancer-related genes. In the current study, genes concurrently identified in array comparative genomic hybridization (CGH) and gene expression microarrays were used to derive gene signatures for Han Chinese breast cancers. We performed 23 array CGHs and 81 gene expression microarrays in breast cancer samples from Taiwanese women. Genes with coherent patterns of both CNV and differential gene expression were identified from the 21 samples assayed using both platforms. We used these genes to derive signatures associated with clinical ER and HER2 status and disease-free survival. DISTRIBUTIONS OF SIGNATURE GENES WERE STRONGLY ASSOCIATED WITH CHROMOSOMAL LOCATION: chromosome 16 for ER and 17 for HER2. A breast cancer risk predictive model was built based on the first supervised principal component from 16 genes (RCAN3, MCOLN2, DENND2D, RWDD3, ZMYM6, CAPZA1, GPR18, WARS2, TRIM45, SCRN1, CSNK1E, HBXIP, CSDE1, MRPL20, IKZF1, and COL20A1), and distinct survival patterns were observed between the high- and low-risk groups from the combined dataset of 408 microarrays. The risk score was significantly higher in breast cancer patients with recurrence, metastasis, or mortality than in relapse-free individuals (0.241 versus 0, P<0.001). The concurrent gene risk predictive model remained discriminative across distinct clinical ER and HER2 statuses in subgroup analysis. Prognostic comparisons with published gene expression signatures showed a better discerning ability of concurrent genes, many of which were rarely identifiable if expression data were pre-selected by phenotype correlations or variability of individual genes. We conclude that parallel analysis of CGH and microarray data, in conjunction with known gene expression patterns, can be used to identify biomarkers with prognostic values in breast cancer.
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PMID:Concurrent gene signatures for han chinese breast cancers. 2409 97