Clin Exp Otorhinolaryngol.  2022 May;15(2):183-193. 10.21053/ceo.2021.02215.

Transcriptomic Analysis of Papillary Thyroid Cancer: A Focus on Immune-Subtyping, Oncogenic Fusion, and Recurrence

• Park SJ
• Kang YE
• Kim JH
• Park JL
• Kim SK
• Baek SW
• Chu IS
• Yi S
• Lee SE
• Park YJ
• Chung EJ
• Kim JM
• Ko HM
• Kim JR
• Jung SN
• Won HR
• Chang JW
• Koo BS
• Kim SY

• KMID: 2530165
• DOI: http://doi.org/10.21053/ceo.2021.02215

Abstract

Objectives
. Thyroid cancer is the most common endocrine tumor, with rapidly increasing incidence worldwide. However, its transcriptomic characteristics associated with immunological signatures, driver fusions, and recurrence markers remain unclear. We aimed to investigate the transcriptomic characteristics of advanced papillary thyroid cancer.
Methods
. This study included 282 papillary thyroid cancer tumor samples and 155 normal samples from Chungnam National University Hospital and Seoul National University Hospital. Transcriptomic quantification was determined by high-throughput RNA sequencing. We investigated the associations of clinical parameters and molecular signatures using RNA sequencing. We validated predictive biomarkers using the Cancer Genome Atlas database.
Results
. Through a comparison of differentially expressed genes, gene sets, and pathways in papillary thyroid cancer compared to normal tumor-adjacent tissue, we found increased immune signaling associated with cytokines or T cells and decreased thyroid hormone synthetic pathways. In addition, patients with recurrence presented increased CD8+ T-cell and Th1-cell signatures. Interestingly, we found differentially overexpressed genes related to immune-escape signaling such as CTLA4, IDO1, LAG3, and PDCD1 in advanced papillary thyroid cancer with a low thyroid differentiation score. Fusion analysis showed that the PI3K and mitogen-activated protein kinase (MAPK) signaling pathways were regulated differently according to the RET fusion partner genes (CCDC6 or NCOA4). Finally, we identified HOXD9 as a novel molecular biomarker that predicts the recurrence of thyroid cancer in addition to known risk factors (tumor size, lymph node metastasis, and extrathyroidal extension).
Conclusion
. We identified a high association with immune-escape signaling in the immune-hot group with aggressive clinical characteristics among Korean thyroid cancer patients. Moreover, RET fusion differentially regulated PI3K and MAPK signaling depending on the partner gene of RET, and HOXD9 was found to be a recurrence marker for advanced papillary thyroid cancer.

Keyword

Thyroid Cancer; Korean Thyroid Cancer; Advanced Papillary Thyroid Cancer; RNA Sequencing; Immune Subtyping; Immune-Escape Signaling; Fusion Outlier; Predictive Biomarker

Figure

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  Fig. 1. Transcriptomic overview and immuno-clinical associations in Korean papillary thyroid cancer patients. (A) Volcano plots showing differentially expressed genes across groups. Red and gray dots represent significance (Fisher exact test; P<0.01 and fold change >1.5) and nonsignificance, respectively. (B) Results of gene-set enrichment analysis using the KEGG and Hallmark database from Enrichr. Light red and light blue indicate upregulated and downregulated terms in tumors compared to normal tissues. (C) Increased immune-related signaling was exclusively observed when lymph node metastasis (LNM) and recurrence occurred. Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) and tumor necrosis factor-alpha (TNF-α) were only enriched when LNM occurred and CD8+ T cells and Th1 cells were only enriched when recurrence occurred. EMT, epithelial-mesenchymal transition; UV, ultraviolet.

• 

  Fig. 2. Association of immune signatures with the thyroid differentiation score (TDS) in advanced papillary thyroid cancer (PTC). (A) The immune landscape of PTC using the immune signature of xCell. The immune subtype based on the immune score was represented as immunehot (n=35), immune-intermediate (n=107), and immune-cold (n=140). (B) The TDS across three immune subtypes. (C) Heatmap sorted by TDS and expression of the top 20 genes that showed high correlations with the TDS. (D) Boxplots showing the major immune-checkpoint inhibitors, including CTLA4, IDO1, LAG3, and PDCD1. (E) Hub gene discovery through network module analysis for each immune subtype. ECI, extracapsular invasion; ETE, extrathyroidal extension; C_LNM, central lymph node metastasis; L_LNM, lateral lymph node metastasis; LVI, lymphovascular invasion; EMT, epithelial-mesenchymal transition.

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  Fig. 3. Different regulation patterns of the PI3K and mitogen-activated protein kinase (MAPK) signaling pathways according to the partner genes of RET fusion. (A) Bar plot showing the fusion count across papillary thyroid cancer (PTC) tumors. (B) Outlier analysis of RET fusion. Blue and red dots indicate the expression of the RET gene in samples without and with fusions, respectively. (C) Impacts of the two partner genes of RET fusion on the MAPK and PI3K pathways. “Common” indicates overlapping genes in both pathways. Circles and squares indicate cis- and trans-acting genes, but there is no cis-interaction, and their sizes indicate the significance of the P-value. (D, E) The genes regulated by RET fusion of CCDC6 and NCOA4 may bridge the MAPK signaling pathway. (D) PTC in the Korean Thyroid Cancer (KTC) cohort. (E) The Thyroid Carcinoma cohort from the Cancer Genome Atlas (TCGA-THCA). (F) Two ways that RET fusion regulates MAPK signaling with different partner genes. WT, wildtype.

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  Fig. 4. HOXD9 is a candidate gene associated with the recurrence of papillary thyroid cancer (PTC). (A) Discovery of recurrence-related factors in PTC samples. The Fisher exact test was performed with a threshold of P<0.01. (B) Barplots showing the spectrum of samples in the PTC group for well-known risk factors such as tumor size, extrathyroidal extension (ETE), and lateral lymph node metastasis (L_LNM). (C) Workflow for selecting HOXD9. (D) Kaplan-Meier plot of thyroid cancer patients based on the expression of HODX9 (high or low based on the median value from the GEPIA database. (E) Barplots showing the recurrence rate based on the expression of HOXD9. (F) Enriched signaling pathways in the HOXD9-high group. (G) Correlation of gene expression between HOXD9 and transcription factors such as transcription factor 3 (TCF3) and enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2) that regulate HOXD9 in the Korean Thyroid Cancer (KTC) cohort and the Thyroid Carcinoma cohort from the Cancer Genome Atlas (TCGA-THCA cohort). (H) Summary of the two routes to recurrence from Korean PTC samples. ECI, extracapsular invasion; C_LNM, central lymph node metastasis; L_LVI, lateral-lymphovascular invasion; NS, not significant; RF, risk factor; DFS, disease free survival; NF-κB, nuclear factor kappa-light-chain-enhancer of activated B cells; TNF-α, tumor necrosis factoralpha; TF, transcription factor.

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