BackgroundA growing body of evidence suggests that immune cell infiltration in cancer is closely related to clinical outcomes. However, there is still a lack of research on papillary thyroid cancer (PTC).MethodsBased on single-sample gene set enrichment analysis (SSGSEA) algorithm and weighted gene co-expression network analysis (WGCNA) tool, the infiltration level of immune cell and key modules and genes associated with the level of immune cell infiltration were identified using PTC gene expression data from The Cancer Genome Atlas (TCGA) database. In addition, the co-expression network and protein-protein interactions network analysis were used to identify the hub genes. Moreover, the immunological and clinical characteristics of these hub genes were verified in TCGA and GSE35570 datasets and quantitative real-time polymerase chain reaction (PCR). Finally, receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic value of hub genes.ResultsActivated B cell, activated dendritic cell, CD56bright natural killer cell, CD56dim natural killer cell, Eosinophil, Gamma delta T cell, Immature dendritic cell, Macrophage, Mast cell, Monocyte, Natural killer cell, Neutrophil and Type 17 T helper cell were significantly changed between PTC and adjacent normal groups. WGCNA results showed that the black model had the highest correlation with the infiltration level of activated dendritic cells. We found 14 hub genes whose expression correlated to the infiltration level of activated dendritic cells in both TCGA and GSE35570 datasets. After validation in the TCGA dataset, the expression level of only 5 genes (C1QA, HCK, HLA-DRA, ITGB2 and TYROBP) in 14 hub genes were differentially expressed between PTC and adjacent normal groups. Meanwhile, the expression levels of these 5 hub genes were successfully validated in GSE35570 dataset. Quantitative real-time PCR results showed the expression of these 4 hub genes (except C1QA) was consistent with the results in TCGA and GSE35570 dataset. Finally, these 4 hub genes had diagnostic value to distinguish PTC and adjacent normal controls.ConclusionsHCK, HLA-DRA, ITGB2 and TYROBP may be key diagnostic biomarkers and immunotherapy targets in PTC.

Resistance to thyroid hormone (RTH) is a rare autosomal hereditary disorder characterized by increased serum thyroid hormone (TH) levels with unsuppressed or increased thyrotropin concentration. It remains unknown whether the coexistence of RTH with papillary thyroid carcinoma (PTC) and Hashimoto thyroiditis (HT) is incidental or whether it possesses a genetic or pathophysiological association. In the present study, a case of RTH with PTC and HT in an 11-year-old Chinese patient was examined and the clinical presentation of RTH with PTC was discussed. In addition, the possible associations between RTH, PTC and HT were determined. HT was confirmed in the patient using an autoimmune assay and thyroid ultrasound. RTH was diagnosed on the basis of clinical manifestations, laboratory information and gene analysis, and PTC was diagnosed according to histological results. Results of BRAFV600E mutation analysis were positive. A literature review of 14 cases of RTH with PTC was included for comparison. The present case report indicates an association of RTH with PTC and HT coexistence in the patient. Close follow-up, histological evaluation and BRAFV600E mutation detection should be performed in each RTH case with HT, since a persistent increase in TSH may be a risk factor for the development of thyroid neoplasm.

Background Understanding the molecule mechanism is a key step in the development of diagnostic and therapeutic measures of follicular variant of papillary thyroid carcinoma. The objective of this study is to identify differentially expressed miRNAs and mRNAs, shedding light on the molecule mechanism of follicular variant of papillary thyroid carcinoma. Methods The data of miRNA, mRNA and DNA methylation were downloaded from The Cancer Genome Atlas (TCGA) database. Differential analysis between the follicular variant of papillary thyroid carcinoma and controls was performed in terms of miRNA expression, mRNA expression and DNA methylation. The regulatory network between miRNAs and mRNAs was constructed followed by the functional analysis of these target mRNAs. Real-time fluorescence quantitative polymerase chain reaction (QRT-PCR) was used to validate the expression of identified miRNAs and mRNAs. Results Totally, up to 8 differentially expressed miRNAs, 973 differentially expressed mRNAs and 146 differentially methylated mRNAs were identified. Hsa-mir-222 (degree =33), hsa-mir-221 (degree =29), hsa-mir-214 (degree =13), hsa-mir-138-2 (degree =11) and hsa-mir-34a (degree =4) were miRNAs that regulated the most target mRNAs (such as BCL2, BCL2L11 and PEG3, ALDH1A1, PLA2R1, TFCP2L1, RAB23, TK1 and CTSB). Focal adhesion, MAPK signaling pathway and p53 signaling pathway were three significantly enriched signaling pathways of target differentially expressed mRNAs in the functional analysis. The in vitro validation of hsa-mir-222 and hsa-mir-221, CTSB, TFCP2L1 and BCL2 was consistent with the bioinformatics analysis. Conclusions The identified altered miRNAs (hsa-mir-222, hsa-mir-221, hsa-mir-214, hsa-mir-138-2 and hsa-mir-34a) and their target mRNAs (BCL2, BCL2L11 and PEG3, ALDH1A1, PLA2R1, TFCP2L1, RAB23, TK1 and CTSB) may be helpful in understanding the molecule mechanism of follicular variant of papillary thyroid carcinoma.

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