title: Gene expression pattern associated with radiotherapy sensitivity in cervical cancer.
abstract: The objective of the present preliminary study was to determine if a difference in the pattern of gene expression exists between tumors that were subsequently found to be sensitive to radiotherapy and tumors found to be resistant to radiotherapy.
  
  
  METHODS
  A total of 16 patients with invasive squamous cell carcinoma of the uterine cervix were included in this study. All patients were treated with standardized radiotherapy alone. Ten of the tumors were clinically radiosensitive and six were radioresistant. Total RNA, extracted from tumor specimens obtained prior to treatment, was hybridized onto an oligonucleotide microarray with probe sets complementary to over 20,000 transcripts. The genes were first subjected to a statistical filter to identify genes with statistically significant differential expression levels between those that were radiosensitive and those that were radioresistant. A back-propagation neural network was then constructed to model the differences so that patterns could be easily identified.
  
  
  RESULTS
  Although a number of genes were found to express differentially between radiosensitive and radioresistant tumors; the 10 most discriminating genes were used to construct the model. Using the expressions from these 10 genes, we found that neural networks constructed from random subsets of the whole data were capable of predicting radiotherapy responses in the remaining subset, which appears stable within the dataset.
  
  
  CONCLUSIONS
  This study shows that such an approach has the potential to differentiate tumor radiosensitivity, although confirmation of such a pattern using other larger independent datasets is necessary before firm conclusions can be drawn.
authors.affiliation: Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, NT, Hong Kong. yickfuwong@cuhk.edu.hk
authors.forename: Y F
authors.initials: YF
authors.lastname: Wong
authors.forename: D S
authors.initials: DS
authors.lastname: Sahota
authors.forename: T H
authors.initials: TH
authors.lastname: Cheung
authors.forename: K W K
authors.initials: KW
authors.lastname: Lo
authors.forename: S F
authors.initials: SF
authors.lastname: Yim
authors.forename: T K H
authors.initials: TK
authors.lastname: Chung
authors.forename: A M Z
authors.initials: AM
authors.lastname: Chang
authors.forename: D I
authors.initials: DI
authors.lastname: Smith
mesh_terms: D000328:Adult; D000368:Aged; D002294:Carcinoma, Squamous Cell / Q000235:genetics* / Q000532:radiotherapy; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008875:Middle Aged; D009361:Neoplasm Invasiveness / Q000473:pathology; D009363:Neoplasm Proteins / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis; D012334:RNA, Neoplasm; D011836:Radiation Tolerance / Q000235:genetics*; D014407:Tumor Cells, Cultured; D002583:Uterine Cervical Neoplasms / Q000235:genetics* / Q000532:radiotherapy
chemical_list: D009363:Neoplasm Proteins; D012334:RNA, Neoplasm