title: Gene expression profile of papillary thyroid cancer: sources of variability and diagnostic implications.
abstract: The study looked for an optimal set of genes differentiating between papillary thyroid cancer (PTC) and normal thyroid tissue and assessed the sources of variability in gene expression profiles. The analysis was done by oligonucleotide microarrays (GeneChip HG-U133A) in 50 tissue samples taken intraoperatively from 33 patients (23 PTC patients and 10 patients with other thyroid disease). In the initial group of 16 PTC and 16 normal samples, we assessed the sources of variability in the gene expression profile by singular value decomposition which specified three major patterns of variability. The first and the most distinct mode grouped transcripts differentiating between tumor and normal tissues. Two consecutive modes contained a large proportion of immunity-related genes. To generate a multigene classifier for tumor-normal difference, we used support vector machines-based technique (recursive feature replacement). It included the following 19 genes: DPP4, GJB3, ST14, SERPINA1, LRP4, MET, EVA1, SPUVE, LGALS3, HBB, MKRN2, MRC2, IGSF1, KIAA0830, RXRG, P4HA2, CDH3, IL13RA1, and MTMR4, and correctly discriminated 17 of 18 additional PTC/normal thyroid samples and all 16 samples published in a previous microarray study. Selected novel genes (LRP4, EVA1, TMPRSS4, QPCT, and SLC34A2) were confirmed by Q-PCR. Our results prove that the gene expression signal of PTC is easily detectable even when cancer cells do not prevail over tumor stroma. We indicate and separate the confounding variability related to the immune response. Finally, we propose a potent molecular classifier able to discriminate between PTC and nonmalignant thyroid in more than 90% of investigated samples.
authors.affiliation: Department of Nuclear Medicine and Endocrine Oncology, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, Poland.
authors.forename: Barbara
authors.initials: B
authors.lastname: Jarzab
authors.forename: Malgorzata
authors.initials: M
authors.lastname: Wiench
authors.forename: Krzysztof
authors.initials: K
authors.lastname: Fujarewicz
authors.forename: Krzysztof
authors.initials: K
authors.lastname: Simek
authors.forename: Michal
authors.initials: M
authors.lastname: Jarzab
authors.forename: Malgorzata
authors.initials: M
authors.lastname: Oczko-Wojciechowska
authors.forename: Jan
authors.initials: J
authors.lastname: Wloch
authors.forename: Agnieszka
authors.initials: A
authors.lastname: Czarniecka
authors.forename: Ewa
authors.initials: E
authors.lastname: Chmielik
authors.forename: Dariusz
authors.initials: D
authors.lastname: Lange
authors.forename: Agnieszka
authors.initials: A
authors.lastname: Pawlaczek
authors.forename: Sylwia
authors.initials: S
authors.lastname: Szpak
authors.forename: Elzbieta
authors.initials: E
authors.lastname: Gubala
authors.forename: Andrzej
authors.initials: A
authors.lastname: Swierniak
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D002291:Carcinoma, Papillary / Q000175:diagnosis / Q000235:genetics* / Q000378:metabolism; D002648:Child; D002675:Child, Preschool; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D008297:Male; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis; D015203:Reproducibility of Results; D013964:Thyroid Neoplasms / Q000175:diagnosis / Q000235:genetics* / Q000378:metabolism