Periostin expression and its supposed roles in benign and malignant thyroid nodules: an immunohistochemical study of 105 cases

Spatial Transcriptomics in a Case of Follicular Thyroid Carcinoma Reveals Clone-Specific Dysregulation of Genes Regulating Extracellular Matrix in the Invading Front

Follicular thyroid carcinoma (FTC) is recognized by its ability to invade the tumor capsule and blood vessels, although the exact molecular signals orchestrating this phenotype remain elusive. In this study, the spatial transcriptional landscape of an FTC is detailed with comparisons between the invasive front and histologically indolent central core tumor areas. The Visium spatial gene expression platform allowed us to interrogate and visualize the whole transcriptome in 2D across formalin-fixated paraffin-embedded (FFPE) tissue sections. Four different 6 × 6 mm areas of an FTC were scrutinized, including regions with capsular and vascular invasion, capsule-near area without invasion, and a central core area of the tumor. Following successful capturing and sequencing, several expressional clusters were identified with regional variation. Most notably, invasive tumor cell clusters were significantly over-expressing genes associated with pathways interacting with the extracellular matrix (ECM) remodeling and epithelial-to-mesenchymal transition (EMT). Subsets of these genes (POSTN and DPYSL3) were additionally validated using immunohistochemistry in an independent cohort of follicular thyroid tumors showing a clear gradient pattern from the core to the periphery of the tumor. Moreover, the reconstruction of the evolutionary tree identified the invasive clones as late events in follicular thyroid tumorigenesis. To our knowledge, this is one of the first 2D global transcriptional mappings of FTC using this platform to date. Invasive FTC clones develop in a stepwise fashion and display significant dysregulation of genes associated with the ECM and EMT - thus highlighting important molecular crosstalk for further investigations.

A novel exosome-related prognostic risk model for thyroid cancer

AIM

The aim was to build an exosome-related gene (ERG) risk model for thyroid cancer (TC) patients.

METHODS

Note that, 510 TC samples from The Cancer Genome Atlas database and 121 ERGs from the ExoBCD database were obtained. Differential gene expression analysis was performed to get ERGs in TC (TERGs). Functional enrichment analyses including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were conducted on the TERGs. Then we constructed a model based on LASSO Cox regression analysis. Kaplan-Meier survival analysis was applied and a Nomogram model was also built. The immune landscape was evaluated by CIBERSORT.

RESULTS

Thirty-eight TERGs were identified and their functions were enriched on 591 GO terms and 30 KEGG pathways. We built a Risk Score model based on FGFR3, ADRA1B, and POSTN. Risk Scores were significantly higher in T4 than in other stages, meanwhile, it didn't significantly differ in genders and TNM N or M classifications. The nomogram model could reliably predict the overall survival of TC patients. The mutation rate of BRAF and expression of cytotoxic T-lymphocyte-associated protein 4 were significantly higher in the high-risk group than in the low-risk group. The risk score was significantly correlated to the immune landscape.

CONCLUSION

We built a Risk Score model using FGFR3, ADRA1B, and POSTN which could reliably predict the prognosis of TC patients.

Effect of hypoxia‑HIF‑1α‑periostin axis in thyroid cancer

The incidence of thyroid carcinoma (TC) has exhibited a rapid increase in recent years. A proportion of TCs exhibit aggressive behavior. The present study aimed to investigate the potential role of hypoxia‑hypoxia inducible factor 1 subunit α (HIF‑1α)‑periostin axis in the progression of TC. The upregulation of periostin and HIF‑1α expression levels was detected in 95 clinical TC tissues as compared with normal thyroid tissues. Hypoxia promoted the viability and invasion of TC cells and this effect was inhibited by the downregulation of periostin. Hypoxia also induced the Warburg effect in TC and this effect was inhibited by the silencing of periostin. Further investigations revealed that hypoxia activated HIF‑1α, which in turn regulated the expression of periostin. Immunoprecipitation and dual luciferase reporter assays demonstrated that HIF‑1α upregulated the expression of periostin by binding to the promoter of periostin. On the whole, these findings suggest the existence of a hypoxia‑HIF‑1α‑periostin axis in TC and indicate the role of this axis in the progression of TC.

Identifying key genes of classic papillary thyroid cancer in women aged more than 55 years old using bioinformatics analysis

BACKGROUND

The incidence rate of thyroid carcinoma (THCA) markedly increased in the recent few decades and has been likely over-diagnosed, especially papillary thyroid cancer (PTC) in women. However, the incidence of advanced-stage papillary thyroid cancer is also rising. According to earlier studies, tumors with identical pathology might have different clinical outcomes, which implies some variances in papillary thyroid cancer. Although the mortality of thyroid cancer has remained stable or declined, there is still an important problem in estimating whether it is benign or needs surgery for patients with papillary thyroid cancer.

METHODS

After obtaining data from The Cancer Genome Atlas (TCGA) Project-THCA database by R package TCGA bio links, 18 samples (11 at stage IV as high-risk group and 7 at stage I as low-risk group) were obtained using survival package and edgeR to ensure differential expression; ClusterProfiler package was used to carry on gene set enrichment analysis and searched the possible pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. STRING and Cytoscape were used to construct and modify the protein-protein interaction (PPI) network to get hub genes of differentially expressed genes. Next, the pROC package was used to get the receiver operating characteristic (ROC) curves of hub genes' disease-free survival (DFS). Then, transcription factors (TFs) and miRNAs of key genes were predicted by ENCORI and AnimalTFDB. In the end, TF-target genes-miRNA regulatory network was also constructed by Cytoscape.

RESULTS

Our research obtained the top 9 candidate genes from the whole network (IFNA1, MRC1, LGALS3, LOX, POSTN, TIMP1, CD276, SDC4, and TLR2). According to the ROC results, TIMP1, LOX, CD276, IFNA1, TLR2, and POSTN were considered to play a more critical role in malignant papillary thyroid cancer or immature cancer of papillary thyroid cancer. Our analysis concludes that TIMP1, LOX, CD276, IFNA1, TLR2, and POSTN are identified as thyroid cancer biomarkers, which lead to the different clinical courses of a woman older than 55 years old with papillary thyroid cancer. Especially CD276, POSTN, and IFNA1 may be considered as new biomarkers associated with the prognosis of thyroid cancer.

CONCLUSIONS

TIMP1, LOX, CD276, IFNA1, TLR2, and POSTN have different expressions in PTCs, which lead to the various clinical courses of a woman older than 55 years old with papillary thyroid cancer. Especially CD276, POSTN, and IFNA1 may be considered as new potential biomarkers associated with the prognosis of thyroid cancer. In addition, TF-miRNA-target gene regulatory network may help further reach for PTC.