Characterizing dedifferentiation of thyroid cancer by integrated analysis.
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ABSTRACT:
SUBMITTER: Luo H
PROVIDER: S-EPMC8318367 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background and objectivesTargeting cancer-associated fibroblast (CAF) is being explored as an approach to improve cancer therapies. The roles of CAF remain unclarified in malignant transformation of papillary thyroid cancer (PTC) into dedifferentiated thyroid cancer (DDTC). This study aimed to investigate correlations of CAF with dedifferentiation and clinicopathological characteristics of thyroid cancer.Materials and methodsWe applied three different mRNA-based CAF gene signatures to quantify CAF in our cohort, the Gene Expression Omnibus (GEO) cohort and The Cancer Genome Atlas (TCGA) cohort, and analyzed expression of ?-SMA by immunohistochemistry in thyroid cancer. The CAF score was analyzed for its associations with clinicopathological characteristics, genetic mutations, tumor-associated signaling pathways and immune landscape.ResultsThe CAF score increased significantly in DDTCs compared with normal thyroid tissues and PTCs, and the ?-SMA-positive CAFs were found enriched in DDTCs. The high CAF score showed a significant correlation with the anaplastic phenotype in DDTC and low thyroid differentiation score in PTC. Patients with a high CAF score remarkably increased the risk of aggressive outcomes in both DDTC and PTC. Furthermore, the CAF score was positively correlated with genetic mutations, oncogenic signaling pathways, the immune score and increased expression of tumor microenvironment (TME) target markers.ConclusionOur findings suggest CAFs positively correlate with dedifferentiation and aggressive outcomes of thyroid cancer, and targeting CAFs as a therapeutic approach may benefit DDTC patients.
| S-EPMC7910116 | biostudies-literature
Project description:Background: Differentiated thyroid cancer (DTC) is the most common type of thyroid cancer. Many of them can relapse to dedifferentiated thyroid cancer (DDTC) and exhibit different gene expression profiles. The underlying mechanism of dedifferentiation and the involved genes or pathways remained to be investigated. Methods: A discovery cohort obtained from patients who received surgical resection in the Fudan University Shanghai Cancer Center (FUSCC) and two validation cohorts derived from Gene Expression Omnibus (GEO) database were used to screen out differentially expressed genes in the dedifferentiation process. Weighted gene co-expression network analysis (WGCNA) was constructed to identify modules highly related to differentiation. Gene Set Enrichment Analysis (GSEA) was used to identify pathways related to differentiation, and all differentially expressed genes were grouped by function based on the GSEA and literature reviewing data. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to control the number of variables in each group. Next, we used logistic regression to build a gene signature in each group to indicate differentiation status, and we computed receiver operating characteristic (ROC) curve to evaluate the indicative performance of each signature. Results: A total of 307 upregulated and 313 downregulated genes in poorly differentiated thyroid cancer (PDTC) compared with papillary thyroid cancer (PTC) and normal thyroid (NT) were screened out in FUSCC cohort and validated in two GEO cohorts. WGCNA of 620 differential genes yielded the seven core genes with the highest correlation with thyroid differentiation score (TDS). Furthermore, 395 genes significantly correlated with TDS in univariate logistic regression analysis were divided into 11 groups. The areas under the ROC curve (AUCs) of the gene signature of group transcription and epigenetic modification, signal and substance transport, extracellular matrix (ECM), and metabolism in the training set [The Cancer Genome Atlas (TCGA) cohort] and validation set (combined GEO cohort) were both >0.75. The gene signature based on group transcription and epigenetic modification, cilia formation and movement, and proliferation can reflect the patient's disease recurrence state. Conclusion: The dedifferentiation of DTC is affected by a variety of mechanisms including many genes. The gene signature of group transcription and epigenetic modification, signal and substance transport, ECM, and metabolism can be used as biomarkers for DDTC.
| S-EPMC8113627 | biostudies-literature
Project description:Papillary thyroid cancer (PTC) is one of the malignancies with an excellent prognosis. However, in PTC, progression or dedifferentiation into poorly differentiated thyroid cancer (PDTC) or anaplastic thyroid cancer (ATC) extremely jeopardizes patients' prognosis. MMP1 is a zinc-dependent endopeptidase, and its role in PTC progression and dedifferentiation is unclear. In this study, transcriptome data of PDTC/ATC and PTC from the Gene Expression Omnibus and The Cancer Genome Atlas databases were utilized to perform an integrated analysis of MMP1 as a potential regulator of tumor progression and dedifferentiation in PTC. Both bulk and single-cell RNA-sequencing data confirmed the high expression of MMP1 in ATC tissues and cells, and further study verified that MMP1 possessed good diagnostic and prognostic value in PTC and PDTC/ATC. Up-regulated MMP1 was found to be positively related to more aggressive clinical characteristics, worse survival, extracellular matrix-related pathways, oncogenic immune microenvironment, more mutations, higher stemness, and more dedifferentiation of PTC. Meanwhile, in vitro experiments verified the high level of MMP1 in PDTC/ATC cell lines, and MMP1 knockdown and its inhibitor triolein could both inhibit the cell viability of PTC and PDTC/ATC. In conclusion, our findings suggest that MMP1 is a potential regulator of tumor progression and dedifferentiation in PTC, and might become a novel therapeutic target for PTC, especially for more aggressive PDTC and ATC.
| S-EPMC9720150 | biostudies-literature
Project description:Cyclin-dependent kinase 1 (CDK1) has a unique role in cell cycle regulation, as it is crucial for cell cycle progression and cell division. The aim of the present study was to use a combination of various detection methods to examine the expression and clinical significance of CDK1 in thyroid cancer (THCA). We used in-house tissue microarrays, immunohistochemistry, public RNA-sequencing, gene microarrays, and meta-analyses to conduct a comprehensive analysis of the role of CDK1 in the occurrence and development of THCA. CDK1 protein expression was notably higher in THCA tissues than in non-cancer tissues as evidenced by the in-house tissue microarrays. The expression of CDK1 protein was also significantly higher in pathologic T3-T4 than in T1-T2 samples. The pooled standardized mean difference (SMD) for CDK1 was 0.71 (95% CI, 0.46-0.95) including a total of 931 THCA and 585 non-cancerous thyroid tissue samples. An aggregation of the immunohistochemistry results and the RNA-sequencing/microarray findings gave a pooled SMD for CDK1 expression of 2.13 (95% CI, 1.30-2.96). The final area under curve (AUC) for the summarized receiver operating characteristic (sROC) was 0.7941 using all 1102 cases of THCA and 672 cases of controls. KEGG analysis with the co-expressed genes of CDK1 in THCA demonstrated the top enriched pathways to be the cell cycle, thyroid hormone synthesis, autoimmune thyroid disease, etc. In summary, we reveal the overexpression of CDK1 in THCA based on multiple detection methods that combine independent cohorts. However, further studies are required to elucidate the molecular mechanisms of CDK1 that promotes the biological aggressiveness of THCA cells.
| S-EPMC6943461 | biostudies-literature
Project description:Iodide uptake and the metabolism of thyroid cells are regulated by thyrotropin (TSH)-TSH receptor (TSHR) signaling. Thus, it is necessary to elevate serum TSH levels by T4 withdraw or rTSH administration to facilitate radioiodide (131I) therapy for differentiated thyroid cancer (DTC). However, non-iodide-avid metastases of DTC which is dedifferentiated do not respond to stimulation by high levels of TSH, suggesting abnormal TSH-TSHR signal transduction in cancer cells. In addition, PI3K/AKT/mTOR signaling activation has been shown to be associated with the dedifferentiated phenotype of thyroid cancer, but the mechanism remains elusive. Therefore, in this study, we aimed to explore the role of abnormal TSH-TSHR signaling activation in regulating iodide uptake and cell mobility in thyroid cancer and its relationship with PI3K/AKT/mTOR signaling. We found that in thyroid cancer cells, TSH binds TSHR coupled to the Gα12/13 protein and then activates RhoA through interacting with leukemia associated RhoA guanine exchange factor (LARG). This results in a promigration tumorigenic phenotype independent of canonical TSHR-GαS signaling that regulates the expression of molecules involved in iodine uptake and metabolism. We observed that signaling pathways downstream of Gα12/13 signaling were increased, while that of Gαs signaling was decreased in thyroid cancer cells undergoing dedifferentiation compared to control cells following stimulation with different levels of TSH. PI3K/AKT/mTOR signaling activation enhanced Gα12/13 signaling through increasing LARG levels but also inhibited the expression of molecules downstream of Gαs signaling, including thyroid-specific molecules, and iodide uptake. In summary, our results demonstrate the noncanonical activation of TSH-TSHR signaling and its role in increasing the cell mobility and dedifferentiation of thyroid cancer through crosstalk with PI3K/AKT/mTOR signaling.
| S-EPMC8506026 | biostudies-literature
Project description:BackgroundThyroid adenoma associated (THADA) has been identified as the target gene affected by chromosome 2p21 translocations in thyroid adenomas, but the role of THADA in the thyroid is still elusive. The aim of this study was to quantify THADA gene expression in normal tissues and in thyroid hyper- and neoplasias, using real-time PCR.MethodsFor the analysis THADA and 18S rRNA gene expression assays were performed on 34 normal tissue samples, including thyroid, salivary gland, heart, endometrium, myometrium, lung, blood, and adipose tissue as well as on 85 thyroid hyper- and neoplasias, including three adenomas with a 2p21 translocation. In addition, NIS (sodium-iodide symporter) gene expression was measured on 34 of the pathological thyroid samples.ResultsResults illustrated that THADA expression in normal thyroid tissue was significantly higher (p < 0.0001, exact Wilcoxon test) than in the other tissues. Significant differences were also found between non-malignant pathological thyroid samples (goiters and adenomas) and malignant tumors (p < 0.001, Wilcoxon test, t approximation), anaplastic carcinomas (ATCs) and all other samples and also between ATCs and all other malignant tumors (p < 0.05, Wilcoxon test, t approximation). Furthermore, in thyroid tumors THADA mRNA expression was found to be inversely correlated with HMGA2 mRNA. HMGA2 expression was recently identified as a marker revealing malignant transformation of thyroid follicular tumors. A correlation between THADA and NIS has also been found in thyroid normal tissue and malignant tumors.ConclusionsThe results suggest THADA being a marker of dedifferentiation of thyroid tissue.
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Project description:Thyroid cancer (TC) is one of the most common types of malignancy of the endocrine-system. At present, there is a lack of effective methods to predict neck lymph node metastasis (LNM) in TC. The present study compared the expression profiles from The Cancer Genome Atlas between N1M0 and N0M0 subgroups in each T1-4 stages TC in order to identify the four groups of TC LNM-associated differentially expressed genes (DEGs). Subsequently, DEGs were combined to obtain a total of 493 integrated DEGs by using the method of Robust Rank Aggregation. Furthermore, the underlying mechanisms of LNM were investigated. The results from Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses demonstrated that the identified DEGs may promote LNM via numerous pathways, including extracellular matrix-receptor interaction, PI3K-AKT signaling pathway and focal adhesion. Following construction of a protein-protein interaction network, the significance score for each gene was calculated and seven hub genes were screened, including interleukin 6, actinin ?2, collagen type I ? 1 chain, actin ?1, calbindin 2, thrombospondin 1 and parathyroid hormone. These genes were predicted to serve crucial roles in TC with LNM. The results from the present study could therefore improve the understanding of LNM in TC. In addition, the seven DEGs identified may be considered as potential novel targets for the development of biomarkers that could be used in the diagnosis and therapy of TC.
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Project description:BackgroundThe advent of genotype data from large-scale efforts that catalog the genetic variants of different populations have given rise to new avenues for multifactorial disease association studies. Recent work shows that genotype data from the International HapMap Project have a high degree of transferability to the wider population. This implies that the design of genotyping studies on local populations may be facilitated through inferences drawn from information contained in HapMap populations.ResultsTo facilitate analysis of HapMap data for characterizing the haplotype structure of genes or any chromosomal regions, we have developed an integrated web-based resource, iHAP. In addition to incorporating genotype and haplotype data from the International HapMap Project and gene information from the UCSC Genome Browser Database, iHAP also provides capabilities for inferring haplotype blocks and selecting tag SNPs that are representative of haplotype patterns. These include block partitioning algorithms, block definitions, tag SNP definitions, as well as SNPs to be "force included" as tags. Based on the parameters defined at the input stage, iHAP performs on-the-fly analysis and displays the result graphically as a webpage. To facilitate analysis, intermediate and final result files can be downloaded.ConclusionThe iHAP resource, available at http://ihap.bii.a-star.edu.sg, provides a convenient yet flexible approach for the user community to analyze HapMap data and identify candidate targets for genotyping studies.
| S-EPMC1698582 | biostudies-literature
Project description:BackgroundImmune cells account for a large proportion of the tumour microenvironment in anaplastic thyroid carcinomas (ATCs). However, the expression pattern of immune-related genes (IRGs) in ATCs is unclear. Our study aimed to identify an immune-related signature indicating the dedifferentiation of thyroid cells.MethodsWe compared the differences in thyroid differentiation score (TDS), infiltration of immune cells and enriched pathways between ATCs and papillary thyroid carcinomas (PTCs) or normal thyroid tissues in the Gene Expression Omnibus database. Univariate and multivariable Cox analyses were used to screen prognosis-associated IRGs in The Cancer Genome Atlas database. After constructing a risk score, we investigated its predictive value for differentiation and survival by applying receiver operating characteristic and Kaplan-Meier curves. We further explored its associations with important immune checkpoint molecules, infiltrating immune cells and response to immunotherapy.ResultsCompared with PTCs or normal thyroid tissues, ATCs exhibited lower TDS values and higher enrichment of immune cells and activation of the inflammatory response. The quantitative analyses and immunohistochemical staining validated that most ATC cell lines and ATC tissues had higher expression of MMP9 and lower expression of SDC2 than normal thyroid samples and PTC. Higher risk scores indicates dedifferentiation and a worse prognosis. Additionally, the risk score was positively correlated with the immune checkpoint molecules PDL1, CTLA4, IDO1, and HAVCR2 and infiltration of multiple immune cells. Importantly, we found that the samples with higher risk scores tended to have a better response to immunotherapy than those with lower scores.ConclusionOur findings indicate that the risk score may not only contribute to the determination of differentiation and prognosis of thyroid carcinomas but also help the prediction of immune cells infiltration and immunotherapy response.
| S-EPMC8067302 | biostudies-literature
Project description:Anaplastic thyroid carcinoma (ATC) is one of the most aggressive and rapidly lethal tumors. However, limited advances have been made to prolong the survival and to reduce the mortality over the last decades. Therefore, identifying the master regulators underlying ATC progression is desperately needed. In our present study, three datasets including GSE33630, GSE29265, and GSE65144 were retrieved from Gene Expression Omnibus with a total of 32 ATC samples and 78 normal thyroid tissues. A total of 1804 consistently changed differentially expressed genes (DEGs) were identified from three datasets. KEGG pathways enrichment suggested that upregulated DEGs were mainly enriched in ECM-receptor interaction, cell cycle, PI3K-Akt signaling pathway, focal adhesion, and p53 signaling pathway. Furthermore, key gene modules in PPI network were identified by Cytoscape plugin MCODE and they were mainly associated with DNA replication, cell cycle process, collagen fibril organization, and regulation of leukocyte migration. Additionally, TOP2A, CDK1, CCNB1, VEGFA, BIRC5, MAPK1, CCNA2, MAD2L1, CDC20, and BUB1 were identified as hub genes of the PPI network. Interestingly, module analysis showed that 8 out of 10 hub genes participated in Module 1 network and more than 70% genes of Module 2 consisted of collagen family members. Notably, transcription factors (TFs) regulatory network analysis indicated that E2F7, FOXM1, and NFYB were master regulators of Module 1, while CREB3L1 was the master regulator of Module 2. Experimental validation showed that CREB3L1, E2F7, and FOXM1 were significantly upregulated in ATC tissue and cell line when compared with normal thyroid group. In conclusion, the TFs regulatory network provided a more detail molecular mechanism underlying ATC occurrence and progression. TFs including E2F7, FOXM1, CREB3L1, and NFYB were likely to be master regulators of ATC progression, suggesting their potential role as molecular therapeutic targets in ATC treatment.
| S-EPMC6512074 | biostudies-literature