Cell-cycle gene expression analysis using real time PCR in locally advanced squamous-cell head and neck cancer.

PURPOSE: The analysis of gene expression, especially those involved in cell cycle control, can help to discover mechanisms determining the outcome of radiation treatment. The main purpose of this study was to examine the expression level of genes responsible for cell cycle regulation in samples of the head and neck cancer, obtained during surgery. METHODS: Postsurgical samples of SCC of head and neck region were collected. Over 80 genes were analysed using cell cycle quantitative real-time RT-PCR Array method. Presence of 14 high-risk HPV types DNA in frozen or paraffin-embedded tumour pathological samples was also assessed. To correlate gene expression with selected pathological features and clinical outcome we used different hierarchical clustering method. RESULTS: Hierarchical clustering demonstrated the association between gene expression within certain clusters and gender, tumour site, T stage, N stage, grade, pathological subtype or tumour recurrence. CONCLUSIONS: Despite some limitations we were able to identify gene clusters that allowed to classify patients according to selected clinical features and occurrence of tumour recurrence. The results of the analysis also confirm that the incidence of HPV infection among the patients from Upper Silesia is relatively low, whereas HPV negative tumours, likely associated with smoking, appeared dominant.

Bystander effects induced by medium from irradiated cells: similar transcriptome responses in irradiated and bystander K562 cells.

PURPOSE: Cells exposed to ionizing radiation release factors that induce deoxyribonucleic acid damage, chromosomal instability, apoptosis, and changes in the proliferation rate of neighboring unexposed cells, phenomena known as bystander effects. This work analyzes and compares changes in global transcript levels induced by direct irradiation and by bystander effects in K562 (human erythroleukemia) cells. METHODS AND MATERIALS: Cells were X-irradiated with 4 Gy or transferred into culture medium collected from cells 1 h after irradiation (irradiation-conditioned medium). Global transcript profiles were assessed after 36 h of growth by use of Affymetrix microarrays (Affymetrix, Santa Clara, CA) and the kinetics of change of selected transcripts by quantitative reverse transcriptase-polymerase chain reaction. RESULTS: The level of the majority (72%) of transcripts changed similarly (increase, decrease, or no change) in cells grown in irradiation-conditioned medium or irradiated, whereas only 0.6% showed an opposite response. Transcript level changes in bystander and irradiated cells were significantly different from those in untreated cells grown for the same amount of time and were confirmed by quantitative reverse transcriptase-polymerase chain reaction for selected genes. Signaling pathways in which the highest number of transcripts changed in both conditions were found in the following groups: neuroactive ligand-receptor, cytokine-cytokine receptor interaction, Janus Kinase-Signal Transducers and Activators of Transcription (JAK-STAT) and Mitogen-Activated Protein Kinase (MAPK) In control cells more transcripts were downregulated than in irradiated and bystander cells with transcription factors YBX1 and STAT5B, heat shock protein HSPA1A, and ribonucleic acid helicase DDX3X as examples. CONCLUSIONS: The transcriptomes of cells grown in medium from X-irradiated cells or directly irradiated show very similar changes. Signals released by irradiated cells may cause changes in the transcriptome of neighboring cells that sustain their survival.

Calculation of reliable transcript levels of annotated genes on the basis of multiple probe-sets in Affymetrix microarrays.

Microarray methods have become a basic tool in studies of global gene expression and changes in transcript levels. Affymetrix microarrays from the HGU133 series contain multiple probe-sets complementary to the same gene (4742 genes are represented by more than one probe-set in a microarray HGU133A). Individual probe-sets annotated to the same gene often show different hybridization signals and even opposite trends, which may result from some of them matching transcripts of more than one gene and from the existence of different splice-variant transcripts. Existing methods that redefine probe-sets and develop custom probe-set definitions use mathematical tools such as Matlab or the R statistical environment with the Bioconductor package (Gentleman et al., 2004, Genome Biol. 5: 280) and thus are directed to researchers with a good knowledge of bioinformatics. We propose here a new approach based on the principle that a probe-set which hybridizes to more than one transcript can be recognized because it produces a signal significantly different from others assigned to the particular gene, allowing it to be detected as an outlier in the group and eliminated from subsequent analyses. A simple freeware application has been developed (available at www.bioinformatics.aei.polsl.pl) that detects and removes outlying probe-sets and calculates average signal values for individual genes using the latest annotation database provided by Affymetrix. We illustrate this procedure using microarray data from our experiments aiming to study changes of transcription profile induced by ionizing radiation in human cells.

X-irradiation and bystander effects induce similar changes of transcript profiles in most functional pathways in human melanoma cells.

Unirradiated cells which neighbor cells exposed to ionizing radiation (IR) show responses termed bystander effects, including DNA damage, chromosomal instability, mutation, and apoptosis. We used genome-wide microarrays to compare the change in transcript profiles in Me45 (human melanoma) cells grown in culture medium from irradiated cells (irradiation conditioned medium, ICM) with those which occurred after IR, sampling after more than one division cycle to detect long-term changes which could be relevant in radiotherapy. Transcripts of >10,000 genes showed an increased or decreased level in both conditions using the criterion of a >+/-10% change, and >85% of these were common to growth in ICM and after IR. When these genes were grouped into metabolic pathways according to the Kyoto Encyclopedia of Genes and Genomes (KEGG), significant differences (p<0.01) were seen between the numbers of up- and down-regulated transcripts in certain groups after both ICM and IR, particularly in the groups neuroactive ligand-receptor interactions, oxidative phosphorylation, cytokine-cytokine receptor interactions, proteasomes, and ribosomes. Quantitative RT-PCR assays of transcripts of selected genes in these pathways confirmed the similar effects of growth in ICM and IR. We conclude that factors transmitted from irradiated cells can influence transcript levels in bystander cells, and that these changes persist for more than one cell cycle consistent with the long-term transmissible effects seen in progeny cells, revealing new facets of the IR-induced bystander effect.