Identification of Key Regulator Genes Linked to Radioresistance in Head and Neck Squamous Cell Carcinoma by Bioinformatic Processing of Transcript Data
(English)Manuscript (preprint) (Other academic)
Purpose: We analyzed basal expression patterns of cell lines with different intrinsic radiosensitivity to discover predictive markers of radiotherapy response.
Experimental Design: Five head and neck squamous cell carcinoma (HNSCC) cell lines were selected for microarray analysis. Two cell lines showed high resistance to radiation, two cell lines showed an intermediate resistance and one cell line was sensitive and therefore used as reference to other cell lines. Three gene lists were generated from this analysis; one list with commonly deregulated genes in all cell lines compared to the reference and two lists with deregulated genes for the intermediate and highly resistant cell lines compared to the reference, respectively. Gene Ontology enrichment profiling and Ingenuity Pathway Analysis was applied on all gene lists. Key transcript findings were verified at the protein level by Western blot.
Results: Expression analysis of the high and intermediate resistant cell lines compared to the reference resulted in approximately 1300 significantly altered transcripts, respectively; 552 transcripts were found commonly differently expressed. The deregulated transcripts enriched several GO-categories under biological process, cellular component and molecular function as well as multiple molecular networks in Ingenuity Pathway Analysis. A transcriptional profile of 28 key-regulator genes from the molecular networks was generated from the four resistant lines compared to the reference. Finally, immunoblot analysis supported deregulation at the protein level of markers implicated from the transcriptional-profile.
Conclusions: Novel markers for prediction of radiation sensitivity could be proposed from bioinformatic processing of gene-expression profiles in HNSCC carcinoma cells.
Microarray, Radiotherapy, Predictive biomarkers, Gene Ontology, Pathway analysis
Medical and Health Sciences
IdentifiersURN: urn:nbn:se:liu:diva-19570OAI: oai:DiVA.org:liu-19570DiVA: diva2:225482