title: 'Desperate house genes': the dramatic example of hypoxia.
abstract: BACKGROUND
  Microenvironmental conditions in normal or tumour tissues and cell lines may interfere on further biological analysis. To evaluate transcript variations carefully, it is common to use stable housekeeping genes (HKG) to normalise quantitative microarrays or real-time polymerase chain reaction results. However, recent studies argue that HKG fluctuate according to tissues and treatments. So, as an example of HKG variation under an array of conditions that are common in the cancer field, we evaluate whether hypoxia could have an impact on HKG expression.
  
  
  METHODS
  Expression of 10 commonly used HKG was measured on four cell lines treated with four oxygen concentrations (from 1 to 20%).
  
  
  RESULTS
  Large variations of HKG transcripts were observed in hypoxic conditions and differ along with the cell line and the oxygen concentration. To elect the most stable HKG, we compared the three statistical means based either on PCR cycle threshold coefficient of variation calculation or two specifically dedicated software. Nevertheless, the best HKG dramatically differs according to the statistical method used. Moreover, using, as a reference, absolute quantification of a target gene (here the proteinase activating receptor gene 1 (PAR1) gene), we show that the conclusions raised about PAR1 variation in hypoxia can totally diverge according to the selected HKG used for normalisation.
  
  
  CONCLUSIONS
  The choice of a valid HKG will determine the relevance of the results that will be further interpreted, and so it should be seriously considered. The results of our study confirm unambiguously that HKG variations must be precisely and systematically determined before any experiment for each situation, to obtain reliable normalised results in the experimental setting that has been designed. Indeed, such assay design, functional for all in vitro systems, should be carefully evaluated before any extension to other experimental models including in vivo ones.
authors.affiliation: INSERM, U955 EQ07, Paris Est University, Créteil, France.
authors.forename: J
authors.initials: J
authors.lastname: Caradec
authors.forename: N
authors.initials: N
authors.lastname: Sirab
authors.forename: C
authors.initials: C
authors.lastname: Keumeugni
authors.forename: S
authors.initials: S
authors.lastname: Moutereau
authors.forename: M
authors.initials: M
authors.lastname: Chimingqi
authors.forename: C
authors.initials: C
authors.lastname: Matar
authors.forename: D
authors.initials: D
authors.lastname: Revaud
authors.forename: M
authors.initials: M
authors.lastname: Bah
authors.forename: P
authors.initials: P
authors.lastname: Manivet
authors.forename: M
authors.initials: M
authors.lastname: Conti
authors.forename: S
authors.initials: S
authors.lastname: Loric
mesh_terms: D015687:Cell Hypoxia / Q000235:genetics; D002478:Cells, Cultured; D020869:Gene Expression Profiling / Q000592:standards; D005786:Gene Expression Regulation; D005796:Genes / Q000502:physiology*; D006801:Humans; D000860:Hypoxia / Q000235:genetics* / Q000473:pathology; D020411:Oligonucleotide Array Sequence Analysis / Q000592:standards; D012016:Reference Values; D012107:Research Design / Q000592:standards; D054928:Validation Studies as Topic