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PLoS Genet. 2016;12(8):e1006239.

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

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제1저자 유승근, 이승복, 김수진 · 교신저자 박영주, 이규언, 서정선

소속 (10)
  1. Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Republic of Korea.
  2. Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.
  3. Department of Surgery, Seoul National University College of Medicine, Seoul, Republic of Korea.
  4. Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea.
  5. Research Institute, National Medical Center, Seoul, Republic of Korea.
  6. Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, Republic of Korea.
  7. Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.
  8. Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea.
  9. Macrogen Inc., Seoul, Republic of Korea.
  10. Department of Biochemistry and Molecular Biology, Seoul National University College of Medicine, Seoul, Republic of Korea.

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.

Figures

Fig 1
Fig 1 The mutational landscape of thyroid tumors. Each column represents an individual sample. (A) Age, gender, the presence of lymphocytic thyroiditis, tumor size, TNM Classification of Malignant Tumors stage, American Thyroid Association risk stratification, availability of matched normal tissue, and histological subtype. (B) Frequency of small size mutation by gene (right) and distribution of mutation across the 180 tumors (middle). (C) Frequency of fusion mutation by gene (right) and distribution of mutation across the 180 tumors (middle).
Fig 2
Fig 2 Gene expression analysis on thyroid tumors. (A) The result of K-means clustering via PCA. Three distinct molecular subtypes were found: BRAF–like, RAS–like, and NBNR. Each cluster was represented by a 95.00% confidence ellipse. (B) Driver gene of three molecular subtypes. (C) Histological subtype, molecular subtype, the presence of extrathyroidal extension, the presence of lymph node metastasis, ERK score, TDS, and driver gene in individual samples. 180 tumors were sorted by molecular subtype, driver gene, and high to low TDS. (D) The heat maps represent expression level of 16 thyroid metabolism and function genes and (E) the MAPK signaling pathway genes in tumor (middle) and normal (right) specimens. Genes were clustered by K-means clustering algorithm (K = 3).
Fig 3
Fig 3 Gene expression analysis on follicular-patterned thyroid tumors. (A) The result of PCA on FVPTC. (B) The result of PCA on miFTC and FA. (C) The volcano plots represent identical gene expression among three subtypes: miFTC and FA (upper), FA and EFVPTC (middle), and miFTC and EFVPTC (lower). All analysis was restricted to RAS–like tumors. (D) ESRRA expression level of miFTC and FA. (E) The characteristic gene expression of oncocytic FTN. ESRRA, PPARGC1A, genes in TCA cycle were represented by Log2 (fold change). The illustration was generated based on a figure from Davis et al and KEGG pathway [34,54].
Fig 4
Fig 4 The CNV landscape of thyroid tumors. (A) The examples of arm-level duplication and deletion were pointed by arrow. Enlarged images of chromosome 11q deletion (upper right) and chromosome 17 with deletion and duplication in p and q arm (lower right) were provided. (B) The distribution of CNVs across 180 tumors. The chromosome arms without CNV across all tumors were excluded. Specimens were sorted in the same manner as Fig 2. (C) The percentage of CNV in each histological subtype. (D) The percentage of CNV in each molecular subtype. (E) The percentage of chromosome 22q deletion in each molecular subtype. (F) The volcano plot shows massive number of moderately downregulated genes in RAS–like tumors with chromosome 22q deletion. Positional gene set enrichment result of these genes is provided in S4 Table.
Fig 5
Fig 5 The overview of the present study. (A) The driver mutations in thyroid tumors. Each pie chart represents the distribution of driver mutations identified in FTN, FVPTC, and cPTC, respectively. (B) A schematic model of thyroid cancer progression integrating clinical risk factors, mutational, transcriptional profile, and clinical presentation. Tumor aggressiveness was determined by the presence of invasive pathologic characteristics of ETE or LNM.

그림 출처: PubMed Central 공개 논문 (PMC4975456)

Conflict of interest statement

JSS and JYS are affiliated with Macrogen Inc. The affiliations to this company, along with any other relevant declarations relating to employment, consultancy, patents, products in development or marketed products etc, do not alter the authors' adherence to PLOS GENETICS policies on sharing data and materials.

그 밖의 정보
출판 형태
Journal Article
저널
PLoS genetics · eISSN 1553-7404
전자 출판
2016-08-05
MeSH
Adenoma / diagnosis / genetics / pathology · Adult · Aged · Carcinoma / diagnosis / genetics · Carcinoma, Papillary · Female · Gene Expression Regulation, Neoplastic / genetics · High-Throughput Nucleotide Sequencing · Humans · Male · Middle Aged · Mutation · Neoplasm Proteins / biosynthesis / genetics · Thyroid Cancer, Papillary · Thyroid Neoplasms / diagnosis / genetics · Transcriptome / genetics
Substances
Neoplasm Proteins
참고문헌
68편