Proteome analysis enables separate clustering of normal breast, benign breast and breast cancer tissues

We have used proteomics with cluster analysis for the classification of breast tumour tissues. In our approach, we can distinguish between normal breast, benign breast and breast cancer tissues on the basis of the protein expression profiles. We propose an objective method for the classification of breast tumour specimens

Proteomic analysis of morphologically changed tissues after prolonged dexamethasone treatment

Prolonged dexamethasone (Dex) administration leads to serious adverse and decrease brain and heart size, muscular atrophy, hemorrhagic liver, and presence of kidney cysts. Herein, we used an untargeted proteomic approach using liquid chromatography-tandem mass spectrometry (LC-MS/MS) for simultaneous identification of changes in proteomes of the major organs in Sprague-Dawley (SD rats post Dex treatment. The comparative and quantitative proteomic analysis of the brain, heart, muscle, liver, and kidney tissues revealed differential expression of proteins (n = 190, 193, 39, 230, and 53, respectively) between Dex-treated and control rats. Functional network analysis using ingenuity pathway analysis (IPA revealed significant differences in regulation of metabolic pathways within the morphologically changed organs that related to: (i) brain-cell morphology, nervous system development, and function and neurological disease; (ii) heart-cellular development, cellular function and maintenance, connective tissue development and function; (iii) skeletal muscle-nucleic acid metabolism, and small molecule biochemical pathways; (iv) liver-lipid metabolism, small molecular biochemistry, and nucleic acid metabolism; and (v) kidney-drug metabolism, organism injury and abnormalities, and renal damage. Our study provides a comprehensive description of the organ-specific proteomic profilesand differentially altered biochemical pathways, after prolonged Dex treatement to understand the molecular basis for development of side effects

Behavior of the density current in a semi-closed water body and tidal river

研究科: 千葉大学大学院自然科学研究科博士(学術)報告番号:甲第学287

Errors in CGAP xProfiler and cDNA DGED: the importance of library parsing and gene selection algorithms

<p>Abstract</p> <p>Background</p> <p>The Cancer Genome Anatomy Project (CGAP) xProfiler and cDNA Digital Gene Expression Displayer (DGED) have been made available to the scientific community over a decade ago and since then were used widely to find genes which are differentially expressed between cancer and normal tissues. The tissue types are usually chosen according to the ontology hierarchy developed by NCBI. The xProfiler uses an internally available flat file database to determine the presence or absence of genes in the chosen libraries, while cDNA DGED uses the publicly available UniGene Expression and Gene relational databases to count the sequences found for each gene in the presented libraries.</p> <p>Results</p> <p>We discovered that the CGAP approach often includes libraries from dependent or irrelevant tissues (one third of libraries were incorrect on average, with some tissue searches no correct libraries being selected at all). We also discovered that the CGAP approach reported genes from outside the selected libraries and may omit genes found within the libraries. Other errors include the incorrect estimation of the significance values and inaccurate settings for the library size cut-off values. We advocated a revised approach to finding libraries associated with tissues. In doing so, libraries from dependent or irrelevant tissues do not get included in the final library pool. We also revised the method for determining the presence or absence of a gene by searching the UniGene relational database, revised calculation of statistical significance and sorted the library cut-off filter.</p> <p>Conclusion</p> <p>Our results justify re-evaluation of all previously reported results where NCBI CGAP expression data and tools were used.</p

Deciphering a subgroup of breast carcinomas with putative progression of grade during carcinogenesis revealed by comparative genomic hybridisation (CGH) and immunohistochemistry

Distinct parallel cytogenetic pathways in breast carcinogenesis could be identified in recent years. Nevertheless, it remained unclear as to which tumours may have progressed in grade or which patterns of cytogenetic alteration may define the switch from an in situ towards an invasive lesion. In order to gain more detailed insights into cytogenetic mechanisms of the pathogenesis of breast cancer, the chromosomal imbalances of 206 invasive breast cancer cases were characterised by means of comparative genomic hybridisation (CGH). CGH data were subjected to hierarchical cluster analysis and the results were further compared with immunohistochemical findings on tissue arrays from the same breast cancer cases. The combined analysis of immunohistochemical and cytogenetic data provided evidence that carcinomas with gains of 7p, and to a lesser extent losses of 9q and gains of 5p, are a distinct subgroup within the spectrum of ductal invasive grade 3 breast carcinomas. These aberrations were associated with a high degree of cytogenetic instability (16.6 alterations per case on average), 16q-losses in over 70% of these cases, strong oestrogen receptor expression and absence of strong expression of p53, c-erbB2 and Ck 5. These characteristics provide strong support for the hypothesis that these tumours may develop through stages of well- and perhaps intermediately differentiated breast cancers. Our results therefore underline the existence of several parallel and also stepwise progression pathways towards breast cancer