Systematic chromatin immunoprecipitation (chIP-chip) experiments have become a central technique for mapping transcriptional interactions in model organisms and humans. However, measurement of chromatin binding does not necessarily imply regulation, and binding may be difficult to detect if it is condition or cofactor dependent. To address these challenges, we present an approach for reliably assigning transcription factors (TFs) to target genes that integrates many lines of direct and indirect evidence into a single probabilistic model. Using this approach, we analyze publicly available chIP-chip binding profiles measured for yeast TFs in standard conditions, showing that our model interprets these data with significantly higher accuracy than previous methods. Pooling the high-confidence interactions reveals a large network containing 363 significant sets of factors (TF modules) that cooperate to regulate common target genes. In addition, the method predicts 980 novel binding interactions with high confidence that are likely to occur in so-far untested conditions. Indeed, using new chIP-chip experiments we show that predicted interactions for the factors Rpn4p and Pdr1p are observed only after treatment of cells with methyl-methanesulfonate, a DNA-damaging agent. We outline the first approach for consistently integrating all available evidences for TF–target interactions and we comprehensively identify the resulting TF module hierarchy. Prioritizing experimental conditions for each factor will be especially important as increasing numbers of chIP-chip assays are performed in complex organisms such as humans, for which “standard conditions” are ill defined.
Head and neck cancer is a frequent malignancy with a complex, and up to now not clear etiology. Therefore, despite of improvements in diagnosis and therapy, the survival rate with head and neck squamous-cell carcinomas is poor. For a better understanding of the molecular mechanisms behind the process of tumorigenesis and tumor progression, we have analyzed changes of protein expression between microdissected normal pharyngeal epithelium and tumor tissue by ProteinChip® technology. For this, cryostat sections from head and neck tumors (n ؍ 57) and adjacent mucosa (n ؍ 44) were laser-microdissected and analyzed on ProteinChip arrays. The derived mass spectrometry profiles exhibited numerous statistical differences. One peak significantly higher expressed in the tumor (p ؍ 0.000029) was isolated by twodimensional gel electrophoresis and identified as annexin V by in-gel proteolytic digestion, peptide mapping, tandem mass spectrometry analysis, and immuno-deplete assay. The relevance of this single marker protein was further evaluated by immunohistochemistry. Annexinpositive tissue areas were re-analyzed on ProteinChip arrays to confirm the identity of this protein. In this study, we could show that biomarker in head and neck cancer can be found, identified, and assessed by combination of ProteinChip technology, two-dimensional gel electrophoresis, and immunohistochemistry. In our experience, however, such studies only make sense if a relatively pure microdissected tumor tissue is used. Only then minute changes in protein expression between normal
Biomarkers are needed to elucidate the biological background and to improve the detection of cancer. Therefore, we have analyzed lasermicrodissected cryostat sections from head and neck tumors and adjacent mucosa on ProteinChip arrays. Two differentially expressed proteins (P ؍ 3.34 ؋ 10 ؊5 and 4.6 ؋ 10
؊5) were isolated by two-dimensional gel electrophoresis and identified as S100A8 (calgranulin A) and S100A9 (calgranulin B) by in-gel proteolytic digestion, peptide mapping, tandem mass spectrometry analysis, and immunodepletion assay. The relevance of these single marker proteins was evaluated by immunohistochemistry. Positive tissue areas were reanalyzed on ProteinChip arrays to confirm the identity of these proteins. As a control, a peak with low P was identified as calgizzarin (S100A11) and characterized in the same way. This technical triade of tissue microdissection, ProteinChip technology, and immunohistochemistry opens up the possibility to find, identify, and characterize tumor relevant biomarkers, which will allow the movement toward the clonal heterogeneity of malignant tumors. Taking this approach, proteins were identified that might be responsible for invasion and metastasis.
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