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Nat Commun. 2019;10(1):2764.

Integrative analysis of genomic and transcriptomic characteristics associated with progression of aggressive thyroid cancer.

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제1저자 유승근, 송영신 · 교신저자 박영주, 서정선

PMID 31235699 PMC6591357 DOI 10.1038/s41467-019-10680-5 IF 18.1 내분비대사내과
소속 (18)
  1. Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, 03080, Republic of Korea.
  2. Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 08826, Republic of Korea.
  3. Macrogen Inc., Seoul, 08511, Republic of Korea.
  4. Department of Internal Medicine, Seoul National University College of Medicine, Seoul, 03080, Republic of Korea.
  5. Department of Internal Medicine, CHA Bundang Medical Center, CHA University, Seongnam, 13496, Republic of Korea.
  6. Center for Thyroid Cancer, National Cancer Center, Goyang, 10408, Republic of Korea.
  7. Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, 03080, Republic of Korea.
  8. Department of Pathology, Seoul National University Boramae Medical Center, Seoul, 07061, Republic of Korea.
  9. Department of Surgery, Seoul National University College of Medicine, Seoul, 03080, Republic of Korea.
  10. Department of Pathology, Seoul National University College of Medicine, Seoul, 03080, Republic of Korea.
  11. Department of Otorhinolaryngology-Head and Neck Surgery, Seoul National University College of Medicine, Seoul, 03080, Republic of Korea.
  12. Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, 03080, Republic of Korea. yjparkmd@snu.ac.kr.
  13. Department of Internal Medicine, Seoul National University College of Medicine, Seoul, 03080, Republic of Korea. yjparkmd@snu.ac.kr.
  14. Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, 03080, Republic of Korea. jeongsunseo@gmail.com.
  15. Macrogen Inc., Seoul, 08511, Republic of Korea. jeongsunseo@gmail.com.
  16. Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, 03080, Republic of Korea. jeongsunseo@gmail.com.
  17. Precision Medicine Center, Seoul National University Bundang Hospital, Seongnam, Bundang-gu, Gyeonggi-do, 13605, Republic of Korea. jeongsunseo@gmail.com.
  18. Gong-Wu Genomic Medicine Institute, Seoul National University Bundang Hospital, Seongnam, 13605, Republic of Korea. jeongsunseo@gmail.com.

Abstract

Anaplastic thyroid cancer (ATC) and advanced differentiated thyroid cancers (DTCs) show fatal outcomes, unlike DTCs. Here, we demonstrate mutational landscape of 27 ATCs and 86 advanced DTCs by massively-parallel DNA sequencing, and transcriptome of 13 ATCs and 12 advanced DTCs were profiled by RNA sequencing. TERT, AKT1, PIK3CA, and EIF1AX were frequently co-mutated with driver genes (BRAFV600E and RAS) in advanced DTCs as well as ATC, but tumor suppressors (e.g., TP53 and CDKN2A) were predominantly altered in ATC. CDKN2A loss was significantly associated with poor disease-specific survival in patients with ATC or advanced DTCs, and up-regulation of CD274 (PD-L1) and PDCD1LG2 (PD-L2). Transcriptome analysis revealed a fourth molecular subtype of thyroid cancer (TC), ATC-like, which hardly reflects the molecular signatures in DTC. Furthermore, the activation of JAK-STAT signaling pathway could be a potential druggable target in RAS-positive ATC. Our findings provide insights for precision medicine in patients with advanced TCs.

Figures

Fig. 1
Fig. 1 The mutational landscape of ATC and advanced DTCs. Each column represents an individual tumor. Only genes harboring mutations confirmed to be somatic in at least one tumor were displayed. Genes were sorted by their functions as oncogenes, tumor suppressors, splicing machinery gene, RET fusion, and telomere lengthening genes. The right bar chart represents the frequencies of gene alterations across 113 advanced TCs. FU, LN, NA, PT, LRT, and DMT indicate follow-up, lymph node, not available, primary tumor, locally recurred or residual tumor, and distant metastatic tumor, respectively
Fig. 2
Fig. 2 Recurrently altered genes in ATC and advanced DTCs. The frequencies of recurrent gene alterations among diverse types of TC were represented by radar charts. a TERT, b TSGs, c TP53, and d the frequencies of AKT1/PIK3CA and EIF1AX co-mutations with BRAFV600E or RAS in diverse types of TC (blue). The mutational frequencies without BRAFV600E and RAS were also displayed (orange). e The distribution of recurrent oncogene mutations across 113 TCs. f The functional domains of PDE8B–TERT fusion. g The expression level of TERT at each exon with PDE8B-TERT fusion. h The expression level of TERT by alteration type. P-values from DESeq2 were represented. i A schematic illustration of TERT upstream translocation. The breakpoints were pointed out by arrows
Fig. 3
Fig. 3 CDKN2A loss in ATC and advanced DTCs. a Detection of CDKN2A loss in ATC using WGS. b Detection of CDKN2A loss in ATC using targeted sequencing. c The frequency of CDKN2A loss among diverse types of TC were represented by a radar chart. d The distribution of TP53 and CDKN2A alterations across 113 advanced TCs. e The effect of CDKN2A loss on thyroid differentiation score (TDS) in ATC. P-values from two-tailed Mann–Whitney U-test were represented. f The effect of CDKN2A loss on disease-specific survival in patients with ATC and advanced DTCs. del and 2n indicate CDKN2A copy number loss and neutral, respectively. g The effect of p16 expression on disease-specific survival in patients with ATC and advanced DTCs. P-values from Log-rank test were represented
Fig. 4
Fig. 4 The transcriptome landscape of ATC and advanced DTCs. a The result of K-means clustering via PCA. The types of tumors and driver mutations were represented by shape and color, respectively. b The results of BRAFV600E-RAS score (BRS) analysis were represented by box plots. P-values from two-tailed Mann–Whitney U-test were represented. c TDS and ERK score were displayed on a scatter plot. d The results of TDS analysis and e ERK score analysis were represented by box plots. P-values from two-tailed Mann–Whitney U-test were represented. f The heatmap represents the expression profile of 16 genes associated with thyroid function and metabolism in TCs. The right panel represents gene expression levels in normal thyroid tissues
Fig. 5
Fig. 5 The potential druggable targets of ATC. a The top 15 significantly up-regulated KEGG pathways in BRAFV600E-positive and RAS-positive ATCs. The significance of these pathways were also noted in PTC, FA/miFTC, and wiFTC, as they were also found within the top 15 significantly up-regulated pathways of each tumor. b The increment levels of genes in the JAK-STAT-signaling pathway in RAS-positive ATC compared with FA/miFTC/wiFTC were represented by Log2(fold-change) values. Asterisks indicate the genes that were also up-regulated BRAFV600E-positive ATC. c Quantitative reverse transcription polymerase chain reaction measurement of expression of JAK-STAT-signaling pathway genes and d cell viabilities analyzed by cell counting kit-8 assay, in CAL72 cells following treatment with ruxolitinib (1, 10, 20, and 25 μM). Ctrl denotes control. All data were expressed as mean ± standard deviation. *P < 0.05 from two-tailed Mann–Whitney U-test (compared with controls). e The expression levels of CD274 and PDCD1LG2 in various types of TC. f The relationship between the up-regulation of two immunotherapeutic genes and CDKN2A loss. Samples were sorted by high to low TDS

그림 출처: PubMed Central 공개 논문 (PMC6591357)

Conflict of interest statement

The authors declare no competing interests.

그 밖의 정보
출판 형태
Journal Article, Research Support, Non-U.S. Gov't
저널
Nature communications · eISSN 2041-1723
전자 출판
2019-06-24
MeSH
Adult · Aged · Biomarkers, Tumor / genetics / metabolism · Cell Line, Tumor · Disease Progression · Female · Gene Expression Profiling · Gene Expression Regulation, Neoplastic / genetics · Genomics · High-Throughput Nucleotide Sequencing · Humans · Janus Kinases / metabolism · Male · Middle Aged · Mutation · Precision Medicine / methods · STAT Transcription Factors / metabolism · Signal Transduction / genetics · Survival Analysis · Thyroid Carcinoma, Anaplastic / genetics / mortality / pathology / therapy · Thyroid Gland / pathology · Thyroid Neoplasms / genetics / mortality / pathology / therapy · Transcriptome / genetics · Up-Regulation
Substances
Biomarkers, Tumor · STAT Transcription Factors · Janus Kinases
연구비
Ministry of Science, ICT and Future Planning (MSIP) NRF-2016R1A2B4012417
참고문헌
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