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Promoter regions of the human genome play a key role in our understanding of the regulatory mechanisms related to the physiological and disease states. The aim of this study was to investigate the sequence positional properties of experimentally verified human promoters. Consequently, we determined short sequence elements ranging from 4 to 9mers presenting position dominance close to, or away from the transcription start site (TSS). For this purpose rigid statistical criteria were used and whether position dominance was in any way related to transcription control was determined. To achieve this goal we designed and implemented a dedicated filtering method to massively detect position-dominant sequence elements embedded in the promoter set. Additionally, via a high throughput procedure, we gathered data on the majority of the publicly available transcription factor-binding sites (TFBSs) and matched them to our findings, aiming to accomplish a large-scale correlation between position-dominant sequence elements and TFBSs. In this analysis, we present unique compositional and conservational perturbations at the TSS and the core promoter region. Using our filtering method, 7,088 short sequences ranging from 4 to 9mers were found to present strong positional dominance close to or away from the TSS, while the aforementioned short sequences were matched to a large number of known TFBSs. Moreover, using probability theory, evidence is presented showing that TFBSs tend to present strong positional preferences. In addition, we demonstrate that the actual TFBS copy number is related to the transcription regulatory process. On the basis of the last argument, it is suggested that all the detected short sequences which did not match any known TFBS, have a high potential for being novel transcription control elements. Furthermore, using a well-described ;high potential cancer biomarker resource', we attempted to identify position dominant sequence elements associated with cancer, as derived by their presence in the respective promoters of cancer related proteins.

We report the establishment of two novel clear cell sarcoma (CCS) cell lines (soft tissue melanoma) from a patient and the production of the corresponding xenografts after xenotransplantation of those cells to NOD/SCID mice. As no comprehensive study on the relevant proteomes of this type of cancer has been reported to date, proteomics technologies were applied in a first attempt to analyze the proteins of the two cell lines and their corresponding primary xenografts. Total protein extracts were separated by two dimensional gel electrophoresis (2-DE) and analysed by MALDI-MS and MALDI-MS-MS following in-gel digestion with trypsin. Protein identification was carried out by peptide mass fingerprint (PMF) and post source decay (PSD), respectively. Comparative analysis revealed that 124 proteins were common between the cell lines and the xenografts; 249 proteins were found to be expressed only in the proteome of the cell lines, while 178 proteins were expressed only in the proteome of xenografts. Our results demonstrated that both cell lines and xenografts were positive for vimentin and S100 reported as markers for CCS. After functional analysis, 27 different protein groups were identified in the analysed proteomes, including apoptosis-related proteins, oncogenes and several proteins closely related to TP-53 and NF-kappa B pathways. Furthermore, the proteins nestin, stem cell growth factor CLC11 and mdr-1, closely related to malignant-melanoma-initiating cells, were found to be expressed in both the cell lines and their corresponding xenografts. Since there are no data concerning protein expression in CCS, this study may contribute to the understanding of the molecular basis of the disease, while the cell lines as well as the developed xenografts may be used as tools for the development of new therapeutic strategies to tackle this rare but fatal malignancy.

The human osteosarcoma U2OS cell line is one of the first generated cell lines and is used in various areas of biomedical research. Knowledge of its protein expression is limited and no comprehensive study on the proteome of this cell line has been reported to date. Proteomics technology was used in order to analyse the proteins of the U2OS cell line. Total protein extracts were separated by two-dimensional gel electrophoresis (2-DE) and analysed by matrix-assisted laser desorption ionisation-mass spectrometry (MALDI-MS) and MALDI--MS-MS following in-gel digestion with trypsin and, finally, protein identification was carried out by peptide mass fingerprint (PMF) and post source decay (PSD), respectively. Approximately 3,000 spots were excised from two 2-DE gels and were analysed, resulting in the identification of 237 different gene products. The majority of the identified proteins were enzymes, regulatory proteins and RNA-associated proteins, while leukocyte markers and oncogenes were also present. Our findings include 11 protooncogenes (FKBP4, SRC8, PSD10, FUBP1, PARK7, NPM, PDIA1, OXRP, SET, TCTP and GRP75) related to the cancerous state of the U2OS cell line. The U2OS 2-DE database provides the basis for future protein studies.

The human immature T-cell line CCRF-CEM is widely used for all kinds of in vitro studies in biochemistry, biology, toxicology and medicine. Knowledge about protein expression is limited and no comprehensive study on the proteome of this cell type has been reported to date. Proteomics technologies were applied in order to analyse the proteins of the CEM cell line. The proteins were separated by two-dimensional (2-D) gel electrophoresis and analysed by MALDI-MS and MALDI-MS-MS following in-gel digestion with trypsin and, finally, protein identification was carried out by peptide mass fingerprint (PMF) and post source decay (PSD), respectively. Approximately 4,500 spots, excised from four 2-D gels, were analysed. The analysis resulted in the identification of about 1,150 proteins, the products of 451 different genes. The majority of the identified proteins were enzymes, regulatory proteins and transporters, while leukocyte markers and oncogenes were also included. The CCRF-CEM cell database today represents one of the largest 2-D databases for eukaryotic proteomes, forming the basis for future expressional studies at the protein level.