High-density microarray expression profiling in conventional papillary thyroid carcinomas with versus without a BRAF mutation
© Alotibi et al; licensee BioMed Central Ltd. 2014
Published: 2 April 2014
Whereas 40 % to 70 % of papillary thyroid carcinomas (PTCs) are characterized by a BRAF mutation (BRAFmut), unified biomarkers for the genetically heterogeneous group of BRAF wild type (BRAFwt) PTCs are not established yet [1, 2]. Using state-of-the-art technology we compared RNA expression profiles between conventional BRAFwt and BRAFmut PTCs.
Materials and methods
Affymetrix HuGene 1.0 ST microarrays were used to generate whole transcript expression profiles in 11 BRAFwt and 14 BRAFmut PTCs. A p-value with a false discovery rate (FDR) ≤ 0.05 and a fold change > 2 were used as a threshold of significance for differential expression. Spearman’s correlation as a similarity matrix was utilized for unsupervised two dimensional hierarchical clustering. The BRAF mutational status was surveyed by direct sequencing the hotspot region of BRAF exon 15.
Hundred eighty transcripts from annotated genes were significantly differentially expressed between BRAFwt and BRAFmut PTCs and unsupervised cluster analysis was able to separate both groups. The most significantly upregulated genes in BRAFmut compared to BRAFwt PTCs include transmembrane 7 superfamily member 4 (TM7SF4, located on 8q23), glutaminase 2 (GLS2; 12q13), ladinin 1 (LAD1; 1q25.1-q32.3), TBC1 domain family, member 2 (TBC1D2; 9q22.33), chromosome 19 open reading frame 33 (C19orf33; 19q13.2), keratin 19 (KRT19; 17q21.2), and poliovirus receptor-related 4 (PVRL4; 1q22-q23.2). The most downregulated genes in BRAFmut PTCs include inositol 1,4,5-triphosphate receptor, type 1 (ITPR1; 3p26-p25), leucine rich repeat and Ig domain containing 2 (LINGO2; 9p21.2-p21.1), solute carrier family 26, member 4 (SLC26A4: 7q31), deiodinase, iodothyronine, type I (DIO1; 1p33-p32), and hepatic leukemia factor (HLF; 17q22). Among differentially expressed microRNAs, mir492 was highly upregulated in BRAFmut PTCs.
This study provides a detailed overview of differentially expressed genes between BRAFwt vs. BRAFmut conventional PTCs using whole transcript, high-density microarrays. Valuable candidate genes shall be assessed further to identify molecular pathways and molecular biomarkers which distinguish BRAFwt from BRAFmut PTCs.
This study was supported by King Abdulaziz City for Science and Technology (KACST) grants 09-BIO707-03 and 09-BIO820-03.
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