Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: EC:2.7.10.1 (ERK)
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Humoral response in cancer patients appears early in cancer progression and can be used for diagnosis, including early detection. By using human recombinant protein and T7 phage microarrays displaying colorectal cancer (CRC)-specific peptides, we previously selected 6 phages and 6 human recombinant proteins as tumor-associated antigens (TAAs) with high diagnostic value. After completing validation in biological samples, TAAs were classified according to their correlation, redundancy in reactivity patterns and multiplex diagnostic capabilities. For predictor model optimization, TAAs were reanalyzed with a new set of samples. A combination of three phages displaying peptides homologous to GRN, NHSL1 and SREBF2 and four proteins PIM1, MAPKAPK3, FGFR4 and ACVR2B, achieved an area under the curve (AUC) of 94%, with a sensitivity of 89.1% and specificity of 90.0%, to correctly predict the presence of cancer. For early colorectal cancer stages, the AUC was 90%, with a sensitivity of 88.2% and specificity of 82.6%. In summary, we have defined an optimized predictor panel, combining TAAs from different sources, with highly improved accuracy and diagnostic value for colorectal cancer. This article is part of a Special Issue entitled: Translational Proteomics.
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PMID:An optimized predictor panel for colorectal cancer diagnosis based on the combination of tumor-associated antigens obtained from protein and phage microarrays. 2246 12

The aim of this study was to identify potential microRNAs and genes associated with drug resistance in ovarian cancer through web-available microarrays. The drug resistant-related microRNA microarray dataset GS54665 and mRNA dataset GSE33482, GSE28646, and GSE15372 were downloaded from the Gene Expression Omnibus database. Dysregulated microRNAs/genes were screened with GEO2R and were further identified in SKOV3 (SKOV3/DDP) and A2780 (A2780/DDP) cells by real-time quantitative PCR (qRT-PCR), and then their associations with drug resistance was analyzed by comprehensive bioinformatic analyses. Nine microRNAs (microRNA-199a-5p, microRNA-199a-3p, microRNA-199b-3p, microRNA-215, microRNA-335, microRNA-18b, microRNA-363, microRNA-645 and microRNA-141) and 38 genes were identified to be differentially expressed in drug-resistant ovarian cancer cells, with seven genes (NHSL1, EPHA3, USP51, ZSCAN4, EPHA7, SNCA and PI15) exhibited exactly the same expression trends in all three microarrays. Biological process annotation and pathway enrichment analysis of the 9 microRNAs and 38 genes identified several drug resistant-related signaling pathways, and the microRNA-mRNA interaction revealed the existence of a targeted regulatory relationship between the 9 microRNAs and most of the 38 genes. The expression of 9 microRNAs and the 7 genes by qRT-PCR in SKOV3/DDP and A2780/DDP cells indicating a consistent expression profile with the microarrays. Among those, the expression of EPHA7 and PI15 were negatively correlated with that of microRNA-141, and they were also identified as potential targets of this microRNA via microRNA-mRNA interaction. We thus concluded that microRNA-141, EPHA7, and PI15 might jointly participate in the regulation of drug resistance in ovarian cancer and serve as potential targets in targeted therapies.
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PMID:Analysis of microarray-identified genes and microRNAs associated with drug resistance in ovarian cancer. 2626 72