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Cancer patients with tumors of similar grading, staging and histogenesis can have markedly different treatment responses to different chemotherapy agents. So far, individual markers have failed to correctly predict resistance against anticancer agents. We tested 30 cancer cell lines for sensitivity to 5-fluorouracil, cisplatin, cyclophosphamide, doxorubicin, etoposide, methotrexate, mitomycin C, mitoxantrone, paclitaxel, topotecan and vinblastine at drug concentrations that can be systemically achieved in patients. The resistance index was determined to designate the cell lines as sensitive or resistant, and then, the subset of resistant vs. sensitive cell lines for each drug was compared. Gene expression signatures for all cell lines were obtained by interrogating Affymetrix U133A arrays. Prediction Analysis of Microarrays was applied for feature selection. An individual prediction profile for the resistance against each chemotherapy agent was constructed, containing 42-297 genes. The overall accuracy of the predictions in a leave-one-out cross validation was 86%. A list of the top 67 multidrug resistance candidate genes that were associated with the resistance against at least 4 anticancer agents was identified. Moreover, the differential expressions of 46 selected genes were also measured by quantitative RT-PCR using a TaqMan micro fluidic card system. As a single gene can be correlated with resistance against several agents, associations with resistance were detected all together for 76 genes and resistance phenotypes, respectively. This study focuses on the resistance at the in vivo concentrations, making future clinical cancer response prediction feasible. The TaqMan-validated gene expression patterns provide new gene candidates for multidrug resistance.

Summary: The Helmholtz Network for Bioinformatics (HNB) is a joint venture of eleven German bioinformatics research groups that offers convenient access to numerous bioinformatics resources through a single web portal. The 'Guided Solution Finder' which is available through the HNB portal helps users to locate the appropriate resources to answer their queries by employing a detailed, tree-like questionnaire. Furthermore, automated complex tool cascades ('tasks'), involving resources located on different servers, have been implemented, allowing users to perform comprehensive data analyses without the requirement of further manual intervention for data transfer and re-formatting. Currently, automated cascades for the analysis of regulatory DNA segments as well as for the prediction of protein functional properties are provided., Availability: The HNB portal is available at http://www.hnbioinfo.de

Velocity profiles of human blood flowing through vertical and horizontal glass tubes (25-100 microns ID) were measured as a function of time following a sudden reduction of wall shear stress (tau w) from a high value to values ranging from 2 to 100 mPa. Cell velocities at various radial positions were determined off-line from video recordings by digital image analysis. In vertical tubes, symmetric velocity profiles were obtained that developed increasing bluntness with time, particularly at lower tau w and in smaller tubes. In horizontal tubes, velocity profiles developed strong asymmetry as a function of time. Red blood cell (RBC) sedimentation was associated with uniform low flow velocities in the concentrating cell sediment, whereas faster flow and almost parabolic profiles were observed in the supernatant plasma region. Calculations of effective blood viscosity showed a decrease with time at low tau w in vertical tubes but an increase in horizontal tubes. The differences between profile shape and effective viscosity in vertical and horizontal tubes disappeared at tau w > 50 mPa. These findings are related to the cross-sectional distribution of RBC, which depends on RBC aggregation and sedimentation.