title: Identification of novel breast cancer-associated transcripts by UniGene database mining and gene expression analysis in normal and malignant cells.
abstract: Breast cancer is a heterogeneous and complex disease. Although the use of tumor biomarkers has improved individualized breast cancer care, i.e., assessment of risk, diagnosis, prognosis, and prediction of treatment outcome, new markers are required to further improve patient clinical management. In the present study, a search for novel breast cancer-associated genes was performed by mining the UniGene database for expressed sequence tags (ESTs) originating from human normal breast, breast cancer tissue, or breast cancer cell lines. Two hundred and twenty-eight distinct breast-associated UniGene Clusters (BUC1-228) matched the search criteria. Four BUC ESTs (BUC6, BUC9, BUC10, and BUC11) were subsequently selected for extensive in silico database searches, and in vitro analyses through sequencing and RT-PCR based assays on well-characterized cell lines and tissues of normal and cancerous origin. BUC6, BUC9, BUC10, and BUC11 are clustered on 10p11.21-12.1 and showed no homology to any known RNAs. Overall, expression of the four BUC transcripts was high in normal breast and testis tissue, and in some breast cancers; in contrast, BUC was low in other normal tissues, peripheral blood mononuclear cells (PBMCs), and other cancer cell lines. Results to-date suggest that BUC11 and BUC9 translate to protein and BUC11 cytoplasmic and nuclear protein expression was detected in a large cohort of breast cancer samples using immunohistochemistry. This study demonstrates the discovery and expression analysis of a tissue-restricted novel transcript set which is strongly expressed in breast tissue and their application as clinical cancer biomarkers clearly warrants further investigation.
authors.affiliation: The John van Geest Cancer Research Center, School of Science and Technology, Nottingham Trent University, Clifton campus, Nottingham, UK.
authors.forename: Stéphanie A-S
authors.initials: SA
authors.lastname: Laversin
authors.forename: Vinaya M
authors.initials: VM
authors.lastname: Phatak
authors.forename: Des G
authors.initials: DG
authors.lastname: Powe
authors.forename: Geng
authors.initials: G
authors.lastname: Li
authors.forename: Amanda K
authors.initials: AK
authors.lastname: Miles
authors.forename: David C
authors.initials: DC
authors.lastname: Hughes
authors.forename: Graham R
authors.initials: GR
authors.lastname: Ball
authors.forename: Ian O
authors.initials: IO
authors.lastname: Ellis
authors.forename: Angelos D
authors.initials: AD
authors.lastname: Gritzapis
authors.forename: Ioannis
authors.initials: I
authors.lastname: Missitzis
authors.forename: Stéphanie E B
authors.initials: SE
authors.lastname: McArdle
authors.forename: Robert C
authors.initials: RC
authors.lastname: Rees
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D017398:Alternative Splicing; D001374:Azacitidine / Q000494:pharmacology; D014408:Biomarkers, Tumor; D001940:Breast / Q000378:metabolism*; D001943:Breast Neoplasms / Q000235:genetics* / Q000473:pathology; D045744:Cell Line, Tumor; D019295:Computational Biology; D057225:Data Mining; D030561:Databases, Nucleic Acid; D020224:Expressed Sequence Tags; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic / Q000187:drug effects; D006801:Humans; D008875:Middle Aged; D060787:Neoplasm Grading; D009367:Neoplasm Staging; D014158:Transcription, Genetic; D059467:Transcriptome
chemical_list: D014408:Biomarkers, Tumor; D001374:Azacitidine