Dataset Information

Comprehensive Analysis of the Transcriptional and Mutational Landscape of Follicular and Papillary Thyroid Cancers.

ABSTRACT: Follicular thyroid carcinoma (FTC) and benign follicular adenoma (FA) are indistinguishable by preoperative diagnosis due to their similar histological features. Here we report the first RNA sequencing study of these tumors, with data for 30 minimally invasive FTCs (miFTCs) and 25 FAs. We also compared 77 classical papillary thyroid carcinomas (cPTCs) and 48 follicular variant of PTCs (FVPTCs) to observe the differences in their molecular properties. Mutations in H/K/NRAS, DICER1, EIF1AX, IDH1, PTEN, SOS1, and SPOP were identified in miFTC or FA. We identified a low frequency of fusion genes in miFTC (only one, PAX8-PPARG), but a high frequency of that in PTC (17.60%). The frequencies of BRAFV600E and H/K/NRAS mutations were substantially different in miFTC and cPTC, and those of FVPTC were intermediate between miFTC and cPTC. Gene expression analysis demonstrated three molecular subtypes regardless of their histological features, including Non-BRAF-Non-RAS (NBNR), as well as BRAF-like and RAS-like. The novel molecular subtype, NBNR, was associated with DICER1, EIF1AX, IDH1, PTEN, SOS1, SPOP, and PAX8-PPARG. The transcriptome of miFTC or encapsulated FVPTC was indistinguishable from that of FA, providing a molecular explanation for the similarly indolent behavior of these tumors. We identified upregulation of genes that are related to mitochondrial biogenesis including ESRRA and PPARGC1A in oncocytic follicular thyroid neoplasm. Arm-level copy number variations were correlated to histological and molecular characteristics. These results expanded the current molecular understanding of thyroid cancer and may lead to new diagnostic and therapeutic approaches to the disease.

SUBMITTER: Yoo SK

PROVIDER: S-EPMC4975456 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Comprehensive Analysis of the Transcriptional and Mutational Landscape of Follicular and Papillary Thyroid Cancers.

Yoo Seong-Keun SK Lee Seungbok S Kim Su-Jin SJ Jee Hyeon-Gun HG Kim Byoung-Ae BA Cho Hyesun H Song Young Shin YS Cho Sun Wook SW Won Jae-Kyung JK Shin Jong-Yeon JY Park Do Joon do J Kim Jong-Il JI Lee Kyu Eun KE Park Young Joo YJ Seo Jeong-Sun JS

PLoS genetics 20160805 8

Follicular thyroid carcinoma (FTC) and benign follicular adenoma (FA) are indistinguishable by preoperative diagnosis due to their similar histological features. Here we report the first RNA sequencing study of these tumors, with data for 30 minimally invasive FTCs (miFTCs) and 25 FAs. We also compared 77 classical papillary thyroid carcinomas (cPTCs) and 48 follicular variant of PTCs (FVPTCs) to observe the differences in their molecular properties. Mutations in H/K/NRAS, DICER1, EIF1AX, IDH1, ...[more]

PMID: 27494611

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Project description:Extrathyroidal extension (ETE) affects papillary thyroid cancer (PTC) prognosis. The objective of this study was to identify biomarkers for ETE and explore the mechanisms controlling its development in PTC. We performed a comprehensive bioinformatics analysis using several datasets. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) on 58 paired PTC samples from The Cancer Genome Atlas (TCGA) were used to detect ETE-related mRNA and long noncoding (lnc) RNA modules and construct an lncRNA/mRNA network. An independent TCGA dataset containing 438 samples was utilized to validate and characterize the WGCNA results. Functional annotation was used to identify the biological functions and related pathways of ETE modules. Two independent RNA sequencing datasets were combined to crossvalidate relationships between lncRNAs and mRNAs by Pearson correlation analysis. Transcription factors (TFs) for affected genes were predicted using the binding motif data from Ensembl Biomart to construct a TF/lncRNA/mRNA network. Other two independent datasets were used to crossvalidate TF-mRNA associations. Finally, receiver operating characteristic, survival analyses, and Cox proportional hazard regression model were performed to explore the significance of hub genes in ETE diagnosis and PTC prognosis. Three mRNA modules and two lncRNA modules were significantly associated with ETE. Enrichment analysis showed extracellular matrix changes was closely related to the development of ETE. A TF/lncRNA/mRNA regulatory network was constructed containing 33 validated hub genes, 64 lncRNAs, and 64 TFs, all differentially expressed between ETE and non-ETE samples. Unc-5 family C-terminal like [area under the curve (AUC): 0.711], sushi repeat containing protein X-linked 2 (AUC: 0.706), lysyl oxidase (AUC: 0.704), collagen type I alpha 1 chain (AUC: 0.704), and collagen type X alpha 1 chain (AUC: 0.704) were the most highly significant hub genes for ETE diagnosis. The Cox proportional hazard regression model constructed with hub genes showed significant survival differences between low- and high-risk groups (p = 0.00025) and performed good prediction for PTC prognosis(AUC = 0.794; C-index = 0.895). The identification of 33 biomarkers and TF/lncRNA/mRNA regulatory network would provide new insights into the molecular mechanisms of ETE besides the prognosis model may have important clinical implications in the improvement of PTC risk stratification, therapeutic decision-making, and prognosis prediction.

Project description:BACKGROUND:Follicular variant of papillary thyroid carcinoma (FVPTC) and follicular adenoma (FA) are histologically closely related tumors and differential diagnosis remains challenging. RNA expression profiling is an established method to unravel molecular mechanisms underlying the histopathology of diseases. METHODS:BRAF mutational status was established by direct sequencing the hotspot region of exon 15 in six FVPTCs and seven FAs. Whole-transcript arrays were employed to generate expression profiles in six FVPTCs, seven FAs and seven normal thyroid tissue samples. The threshold of significance for differential expression on the gene and exon level was a p-value with a false discovery rate (FDR) < 0.05 and a fold change cutoff > 2. Two dimensional average linkage hierarchical clustering was generated using differentially expressed genes. Network, pathway, and alternative splicing utilities were employed to interpret significance of expression data on the gene and exon level. RESULTS:Expression profiling in FVPTCs and FAs, all of which were negative for a BRAF mutation, revealed 55 transcripts that were significantly differentially expressed, 40 of which were upregulated and 15 downregulated in FVPTCs vs. FAs. Amongst the most significantly upregulated genes in FVPTCs were GABA B receptor, 2 (GABBR2), neuronal cell adhesion molecule (NRCAM), extracellular matrix protein 1 (ECM1), heparan sulfate 6-O-sulfotransferase 2 (HS6ST2), and retinoid X receptor, gamma (RXRG). The most significantly downregulated genes in FVPTCs included interaction protein for cytohesin exchange factors 1 (IPCEF1), G protein-coupled receptor 155 (GPR155), Purkinje cell protein 4 (PCP4), chondroitin sulfate N-acetylgalactosaminyltransferase 1 (CSGALNACT1), and glutamate receptor interacting protein 1 (GRIP1). Alternative splicing analysis detected 87 genes, 52 of which were also included in the list of 55 differentially expressed genes. Network analysis demonstrated multiple interactions for a number of differentially expressed molecules including vitamin D (1,25- dihydroxyvitamin D3) receptor (VDR), SMAD family member 9 (SMAD9), v-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homolog (KIT), and RXRG. CONCLUSIONS:This is one of the first studies using whole-transcript expression arrays to compare expression profiles between FVPTCs and FAs. A set of differentially expressed genes has been identified that contains valuable candidate genes to differentiate both histopathologically related tumor types on the molecular level.

Dataset Information

Comprehensive Analysis of the Transcriptional and Mutational Landscape of Follicular and Papillary Thyroid Cancers.

Publications

Comprehensive Analysis of the Transcriptional and Mutational Landscape of Follicular and Papillary Thyroid Cancers.

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