title: Analysis of gene expression using gene sets discriminates cancer patients with and without late radiation toxicity.
abstract: BACKGROUND
  Radiation is an effective anti-cancer therapy but leads to severe late radiation toxicity in 5%-10% of patients. Assuming that genetic susceptibility impacts this risk, we hypothesized that the cellular response of normal tissue to X-rays could discriminate patients with and without late radiation toxicity.
  
  
  RESULTS
  Prostate carcinoma patients without evidence of cancer 2 y after curative radiotherapy were recruited in the study. Blood samples of 21 patients with severe late complications from radiation and 17 patients without symptoms were collected. Stimulated peripheral lymphocytes were mock-irradiated or irradiated with 2-Gy X-rays. The 24-h radiation response was analyzed by gene expression profiling and used for classification. Classification was performed either on the expression of separate genes or, to augment the classification power, on gene sets consisting of genes grouped together based on function or cellular colocalization.X-ray irradiation altered the expression of radio-responsive genes in both groups. This response was variable across individuals, and the expression of the most significant radio-responsive genes was unlinked to radiation toxicity. The classifier based on the radiation response of separate genes correctly classified 63% of the patients. The classifier based on affected gene sets improved correct classification to 86%, although on the individual level only 21/38 (55%) patients were classified with high certainty. The majority of the discriminative genes and gene sets belonged to the ubiquitin, apoptosis, and stress signaling networks. The apoptotic response appeared more pronounced in patients that did not develop toxicity. In an independent set of 12 patients, the toxicity status of eight was predicted correctly by the gene set classifier.
  
  
  CONCLUSIONS
  Gene expression profiling succeeded to some extent in discriminating groups of patients with and without severe late radiotherapy toxicity. Moreover, the discriminative power was enhanced by assessment of functionally or structurally related gene sets. While prediction of individual response requires improvement, this study is a step forward in predicting susceptibility to late radiation toxicity.
authors.affiliation: Department of Toxicogenetics, Leiden University Medical Center, Leiden, Netherlands.
authors.forename: J Peter
authors.initials: JP
authors.lastname: Svensson
authors.forename: Lukas J A
authors.initials: LJ
authors.lastname: Stalpers
authors.forename: Rebecca E E
authors.initials: RE
authors.lastname: Esveldt-van Lange
authors.forename: Nicolaas A P
authors.initials: NA
authors.lastname: Franken
authors.forename: Jaap
authors.initials: J
authors.lastname: Haveman
authors.forename: Binie
authors.initials: B
authors.lastname: Klein
authors.forename: Ingela
authors.initials: I
authors.lastname: Turesson
authors.forename: Harry
authors.initials: H
authors.lastname: Vrieling
authors.forename: Micheline
authors.initials: M
authors.lastname: Giphart-Gassler
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000032:analysis; D002277:Carcinoma / Q000378:metabolism* / Q000532:radiotherapy*; D016000:Cluster Analysis; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D008214:Lymphocytes / Q000378:metabolism / Q000528:radiation effects; D008297:Male; D046228:Microarray Analysis; D008875:Middle Aged; D008954:Models, Biological; D011471:Prostatic Neoplasms / Q000378:metabolism* / Q000532:radiotherapy*; D011829:Radiation Dosage; D011832:Radiation Injuries / Q000145:classification / Q000175:diagnosis* / Q000378:metabolism; D011839:Radiation, Ionizing
chemical_list: D014408:Biomarkers, Tumor