Comprehensive characterization of differentially expressed genes in thyroid cancer

Mechanism of immune escape mediated by receptor tyrosine kinase KIT in thyroid cancer

OBJECTIVE

Thyroid cancer (TC) is one of the fastest-growing malignant tumors. This study sought to explore the mechanism of immune escape mediated by receptor tyrosine kinase (KIT) in TC.

METHODS

The expression microarray of TC was acquired through the GEO database, and the difference analysis and Kyoto encyclopedia of genes and genomes pathway enrichment analysis were carried out. KIT levels in TC cell lines (K1/SW579/BCPAP) and human normal thyroid cells were detected using reverse transcription quantitative polymerase chain reaction and western blot analysis. TC cells were transfected with overexpressed (oe)-KIT and CD8+ T cells were cocultured with SW579 cells. Subsequently, cell proliferation, migration, and invasion abilities, CD8+ T cell proliferation, cytokine levels (interferon-γ [IFN-γ]/tumor necrosis factor-α [TNF-α]) were determined using colony formation assay, Transwell assays, flow cytometry, and enzyme-linked immunosorbent assay. The phosphorylation of MAPK pathway-related protein (ERK) was measured by western blot analysis. After transfection with oe-KIT, cells were treated with anisomycin (an activator of the MAPK pathway), and the protein levels of p-ERK/ERK and programmed death-ligand 1 (PD-L1) were detected.

RESULTS

Differentially expressed genes (N = 2472) were obtained from the GEO database. KIT was reduced in TC samples and lower in tumor cells than those in normal cells. Overexpression of KIT inhibited immune escape of TC cells. Specifically, the proliferation, migration, and invasion abilities of TC cells were lowered, the proliferation level of CD8+ T cells was elevated, and IFN-γ and TNF-α levels were increased. KIT inhibited the activation of the MAPK pathway in TC cells and downregulated PD-L1.

CONCLUSION

KIT suppressed immune escape of TC by blocking the activation of the MAPK pathway and downregulating PD-L1.

GABRB2, a key player in neuropsychiatric disorders and beyond

The GABA receptors represent the main inhibitory system in the central nervous system that ensure synaptogenesis, neurogenesis, and the regulation of neuronal plasticity and learning. GABAA receptors are pentameric in structure and belong to the Cys-loop superfamily. The GABRB2 gene, located on chromosome 5q34, encodes the β2 subunit that combines with the α and γ subunits to form the major subtype of GABAA receptors, which account for 43% of all GABAA receptors in the mammalian brain. Each subunit probably consists of an extracellular N-terminal domain, four membrane-spanning segments, a large intracellular loop between TM3 and TM4, and an extracellular C-terminal domain. Alternative splicing of the RNA transcript of the GABRB2 gene gives rise at least to four long and short isoforms with dissimilar electrophysiological properties. Furthermore, GABRB2 is imprinted and subjected to epigenetic regulation and positive selection. It has been associated with schizophrenia first in Han Chinese, and subsequently validated in other populations. Gabrb2 knockout mice also exhibited schizophrenia-like behavior and neuroinflammation that were ameliorated by the antipsychotic drug risperidone. GABRB2 was also associated with other neuropsychiatric disorders including bipolar disorder, epilepsy, autism spectrum disorder, Alzheimer's disease, frontotemporal dementia, substance dependence, depression, internet gaming disorder, and premenstrual dysphoric disorder. Recently, it has been postulated that GABRB2 might be a potential marker for different cancer types. As GABRB2 has a pivotal role in the central nervous system and is increasingly recognized to contribute to human diseases, further understanding of its structure and function may expedite the generation of new therapeutic approaches.

Low expression of TFF3 in papillary thyroid carcinoma may correlate with poor prognosis but high immune cell infiltration

Background: Papillary thyroid carcinoma (PTC) is one of the most common endocrine malignancies and has a favorable prognosis. However, optimal treatments and prognostic markers have not been clearly identified. Methods: Gene expression data from primary PTC were downloaded from the Gene Expression Omnibus database and subjected to two analyses of differentially expressed genes (DEGs), followed by intersecting individual and integrated DEGs analyses as well as gene set enrichment analysis. Analysis of data from Sequence Read Archive and The Cancer Genome Atlas, immunohistochemistry and qRT-PCR of TFF3 were performed to validate the results. Finally, the relationship between gene expression and disease-free survival as well as immune cell infiltration were investigated. Results: Six critical DEGs and several tumor-enriched signaling pathways were identified. Immunohistochemistry and qRT-PCR validated the low expression of TFF3 in PTC. TFF3 and FCGBP are coexpressed in PTC, and patients with lower gene expression had worse disease-free survival but higher immune cell infiltration. Conclusion: TFF3 was significantly underexpressed and may function with FCGBP synergistically in PTC.

Development and validation of a novel 14-gene signature for predicting lymph node metastasis in papillary thyroid carcinoma

Background

There is still no reasonably accurate method of preoperatively predicting central lymph node metastasis (LNM), and it is essential to develop an effective evaluation model for predicting LNM in papillary thyroid carcinoma (PTC) patients.

Methods

PTC samples were collected from The Cancer Genome Atlas database. Candidate genes were identified as continuously upregulated or downregulated genes in the process of N0 to N1a and N1a to N1b. The least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct the predictive model for LNM. Multivariate logistic regression analysis was performed to screen the potential factors related to LNM, and a nomogram was established. The risk score of the gene signature model for predicting disease-free survival (DFS) was evaluated by Kaplan-Meier analysis.

Results

A 14-gene signature was developed by LASSO regression for predicting LNM based on 69 differential expression genes (DEGs) that were continuously upregulated or downregulated in the progress of PTC. The receiver operating characteristic (ROC) curves of the 14-gene signature predicting LNM, central LNM and lateral LNM were generated. The area under the ROC (AUC) values were 0.806 [95% confidence interval (CI): 0.7608-0.8815], 0.755 (95% CI: 0.6839-0.8263) and 0.821 (95% CI: 0.7608-0.8815). The nomogram's C-index value, including the 14-gene signature and other potential risk factors, was 0.786 (95% CI: 0.7296-0.8425), and the calibration exhibited fairly good consistency with the perfect prediction. Based on the 14-gene risk score, high-risk PTC patients had a worse DFS.

Conclusions

A novel 14-gene signature was developed for predicting LNM in PTC patients. The risk score also correlated with DFS in PTC patients.

Generation and Differentiation of Adult Tissue-Derived Human Thyroid Organoids

Total thyroidectomy as part of thyroid cancer treatment results in hypothyroidism requiring lifelong daily thyroid hormone replacement. Unbalanced hormone levels result in persistent complaints such as fatigue, constipation, and weight increase. Therefore, we aimed to investigate a patient-derived thyroid organoid model with the potential to regenerate the thyroid gland. Murine and human thyroid-derived cells were cultured as organoids capable of self-renewal and which expressed proliferation and putative stem cell and thyroid characteristics, without a change in the expression of thyroid tumor-related genes. These organoids formed thyroid-tissue-resembling structures in culture. (Xeno-)transplantation of 600,000 dispersed organoid cells underneath the kidney capsule of a hypothyroid mouse model resulted in the generation of hormone-producing thyroid-resembling follicles. This study provides evidence that thyroid-lineage-specific cells can form organoids that are able to self-renew and differentiate into functional thyroid tissue. Subsequent (xeno-)transplantation of these thyroid organoids demonstrates a proof of principle for functional miniature gland formation.

Progression of Thyroid Carcinoma Is Promoted by the m6A Methyltransferase METTL3 Through Regulating m6A Methylation on TCF1

Objective

This study aims to uncover the progression of thyroid carcinoma influenced by the m6A methyltransferase METTL3 through regulating m⁶A methylation on TCF1 mRNA and the activated Wnt pathway.

Methods

Thyroid carcinoma tissues and paracancerous ones were collected for detecting levels of METTL3 and TCF1. Potential correlation between levels of METTL3 and TCF1 was analyzed by Pearson analysis. Survival of thyroid carcinoma patients influenced by METTL3 level was assessed by Kaplan–Meier method. Regulatory effect of METTL3 on migratory ability in TPC-1 cells was examined by wound healing assay. The interaction between METTL3 with TCF1 and IGF2BP2 was verified by RNA-Binding Protein Immunoprecipitation (RIP) assay. Meanwhile, the activity of the Wnt pathway was reflected by TOP/FOP-Flash. At last, rescue experiments were conducted to clarify the involvement of TCF1 in phenotype changes of thyroid carcinoma cells that were regulated by METTL3.

Results

METTL3 and TCF1 were upregulated in thyroid carcinoma. Similarly, METTL3 was highly expressed in thyroid carcinoma cells as well. Kaplan–Meier method uncovered poor prognosis in thyroid carcinoma patients expressing a high level of METTL3. Silence of METTL3 inhibited migratory ability and Wnt activity in TPC-1 cells. RIP assay confirmed the interaction between TCF1 and METTL3 or IGF2BP2. Moreover, METTL3 positively regulated the enrichment abundance of TCF1 in anti-IGF2BP2. Rescue experiments demonstrated that TCF1 was responsible for METTL3-regulated thyroid carcinoma progression via the m⁶A methylation.

Conclusion

Upregulated m6A methyltransferase METTL3 promotes the progression of thyroid carcinoma through m⁶A methylation on TCF1.

Identification of key genes and pathways of thyroid cancer by integrated bioinformatics analysis

Thyroid cancer is a common endocrine malignancy with a rapidly increasing incidence worldwide. Although its mortality is steady or declining because of earlier diagnoses, its survival rate varies because of different tumour types. Thus, the aim of this study was to identify key biomarkers and novel therapeutic targets in thyroid cancer. The expression profiles of GSE3467, GSE5364, GSE29265 and GSE53157 were downloaded from the Gene Expression Omnibus database, which included a total of 97 thyroid cancer and 48 normal samples. After screening significant differentially expressed genes (DEGs) in each data set, we used the robust rank aggregation method to identify 358 robust DEGs, including 135 upregulated and 224 downregulated genes, in four datasets. Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes pathway enrichment analyses of DEGs were performed by DAVID and the KOBAS online database, respectively. The results showed that these DEGs were significantly enriched in various cancer-related functions and pathways. Then, the STRING database was used to construct the protein-protein interaction network, and modules analysis was performed. Finally, we filtered out five hub genes, including LPAR5, NMU, FN1, NPY1R, and CXCL12, from the whole network. Expression validation and survival analysis of these hub genes based on the The Cancer Genome Atlas database suggested the robustness of the above results. In conclusion, these results provided novel and reliable biomarkers for thyroid cancer, which will be useful for further clinical applications in thyroid cancer diagnosis, prognosis and targeted therapy.