Page 86 - Helicobacter pylori and Gastric Cancer: From Tumor microenvironment to Immunotherapy

μl [γ-33P] ATP (approx. 1000 kBq (Amersham AH9968). Next, the peptide array mix was added onto the chip, and the chip was kept at 37°C in a humidified stove for 90 min. Subsequently the peptide array was washed twice with Tris-buffered saline with Tween 20, twice in 2 M NaCl, and twice in demineralised H2O and then air-dried. The chips were exposed to a phosphor screen for 72 hours, and the density of the spots was measured and analyzed with array software (ScanAnalyze ). ScanAlyze software was used. Using grid tools, spot density and individual background were corrected and spot intensities and background intensities were analyzed. Data from at least 9 independent data points were exported to an excel sheet for further analysis. Control spots on the array were analyzed for validation of spot intensities between the different samples. Inconsistent data (i.e., SD between the different data points >1.96 of the mean value) were excluded from further analysis. For each peptide the average and standard deviation of phosphorylation was determined and plotted in an amplitude‐based hierarchical fashion. For data analysis, first every peptide was given an “on” call or “off” call (Markov state analysis). To this end, first an average signal was calculated for each peptide using the three biological replicates (each consisting of two technical replicates) yielding an aggregate dataset for each the hematopoietic subsets. Subsequently, for each of the aggregate datasets, either “on” calls or “off” calls were given to each peptide substrate (Markov state analysis). In order to do this, we assumed that the subset of signals representing the 1-1-e fraction of peptides having the lowest phosphorylation of all peptides contained pure noise and did represent meaningful phosphorylation. The distribution of this noise was fitted as a single exponent, using the amplitude-sorted row number of these substrates as the X domain of the distribution and this single exponent was assumed to describe noise for the entire dataset. Now for all data points within the subset, when the actual amplitude observed minus 1,96 the standard deviation was in excess of the value expected from distribution describing the noise, a substrate was given an “on” cal (p < 0.05) in this Markov analysis. Subsequently results were collapsed on elective signal transduction categories and subjected to dichotomal significance analysis, contrasting Shh-stimulated cultures to parallel vehicle cultures or Purmorphamine- stimualted cultures to parallel unstimulated cultures. If a significant result (p < 0.05) was detected, we considered the result as robust evidence of differential activation of signal transduction between Hedgehog-stimulated and unstimulated cultures and in the depiction of results the corresponding signal transduction categories have been highlighted with a red border. For those signal transduction categories in which
Chapter 4
Chapter 4
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