A cyclin D1 (CCND1) gene polymorphism contributes to susceptibility to papillary thyroid cancer in the Turkish population

AMBRA1 attenuates the proliferation of uveal melanoma cells

Uveal melanoma (UVM) is the most common primary intraocular malignancy in adults with high metastasis rates. D-type cyclins (CCNDs) are central regulators of the cell division cycle and are among the most frequently deregulated therapeutic targets in human cancer. Recently, the E3 ligase adaptor, autophagy and beclin 1 regulator 1 (AMBRA1), was reported to regulate the stability of CCNDs, including CCND1, but its role in UVM has not been demonstrated. AMBRA1 is lowly expressed in UVM cells, and the ablation of AMBRA1 promotes the proliferation of 92.1 and OMM1 cells, whereas ectopically expressing AMBRA1 attenuates the proliferation of UVM cells. Further studies found that AMBRA1 promotes the ubiquitination and degradation of CCND1, and AMBRA1 regulates the proliferation of UVM cells in a CCND1-dependent manner. Thus, this study suggests that AMBRA1 serves as an important tumor suppressor by limiting UVM cell growth.

Identification of Prognosis-Associated Biomarkers in Thyroid Carcinoma by a Bioinformatics Analysis

Background

This study aimed to identify the key genes associated with prognosis in thyroid cancer (TC), and to explore potential pathways.

Methods

GSE66783, GSE58545, and GSE129562 datasets were used to identify differentially expressed genes (DEGs) between tumor and normal tissues, followed by KEGG analyses on DEGs. The protein-protein interaction (PPI) network of DEGs was subsequently constructed to find the top 10 hub genes and seed genes in the whole network. Furthermore, the mRNA expressions of hub genes and prognostic values were explored. Regarding the seed gene, pathway activity score and GSEA analyses were conducted as well.

Results

1) A total of 183 DEGs were consistently expressed in three datasets comprising 76 up-regulated and 107 down-regulated genes. DEGs were mainly enriched in the p53 signaling pathway, complement and coagulation cascades, and hedgehog signaling pathway. 2) The top 10 hub genes, including CCND1, TIMP1, ICAM1, MET, PLAU, LDLR, PLAUR, ITGA2, ITGA3, and LGALS3, were identified. All hub genes were highly expressed in TC compared with normal samples. 3) High expression of CCND1, TIMP1, MET, and LGALS3 statistically correlated with a favorable prognosis of patients. Poor survival was observed in patients with ITGA2 and ITGA3 high expression. There was no association between ICAM1, PLAU, and PLAUR expression and survival of patients. LGALS3 and TIMP1 were further identified as independent prognostic factors in TC. 4) Among 10 hub genes, TIMP1 was determined as the seed gene, indicating its significance in the whole network. We further found that in most of the famous cancer-related pathways, TIMP1 higher expression caused a lower pathway activity, suggesting its inhibitory effect to these pathways in TC. In addition, TIMP1 positively correlated with the p53 signaling pathway, complement, and coagulation cascades involved in TC.

Conclusion

The present study provided seven prognosis-associated genes in TC and revealed several significant pathways, which contributed to elucidate the pathogenesis of TC.

BCL2 and hsa-miR-181a-5p are potential biomarkers associated with papillary thyroid cancer based on bioinformatics analysis

Background

The morbidity of thyroid carcinoma has been rising worldwide and increasing faster than any other cancer type. The most common subtype with the best prognosis is papillary thyroid cancer (PTC); however, the exact molecular pathogenesis of PTC is still not completely understood.

Methods

In the current study, 3 gene expression datasets (GSE3678, GSE3467, and GSE33630) and 2 miRNA expression datasets (GSE113629 and GSE73182) of PTC were selected from the Gene Expression Omnibus (GEO) database and were further used to identify differentially expressed genes (DEGs) and deregulated miRNAs between normal thyroid tissue samples and PTC samples. Then, Gene Ontology (GO) and pathway enrichment analyses were conducted, and a protein-protein interaction (PPI) network was constructed to explore the potential mechanism of PTC carcinogenesis. The hub gene detection was performed using the CentiScaPe v2.0 plugin, and significant modules were discovered using the MCODE plugin for Cytoscape. In addition, a miRNA-gene regulatory network in PTC was constructed using common deregulated miRNAs and DEGs.

Results

A total of 263 common DEGs and 12 common deregulated miRNAs were identified. Then, 6 significant KEGG pathways (P < 0.05) and 82 significant GO terms were found to be enriched, indicating that PTC was closely related to amino acid metabolism, development, immune system, and endocrine system. In addition, by constructing a PPI network and miRNA-gene regulatory network, we found that hsa-miR-181a-5p regulated the most DEGs, while BCL2 was targeted by the most miRNAs.

Conclusions

The results of this study suggested that hsa-miR-181a-5p and BCL2 and their regulatory networks may play important roles in the pathogenesis of PTC.

Genetic Variants Related to Cell Cycle and Stability of Telomere in Patients with Glioma

Background:

Glioma, most common primary malignant brain tumor in adults, is highly aggressive and associated with a poor prognosis. Evaluate the association of polymorphisms related of to the cell cycle, integrity and DNA repair with gliomas, as well as lifestyle habits, comorbidities, survival and response to treatment.

Methods:

Were studied 303 individuals distributed into: Study Group - 100 patients with gliomas, regardless of the degree of malignancy, and Control Group - 203 individuals without clinical signs of the disease. These polymorphisms were genotyped by TaqMan^® SNP Genotyping Assay. Significance level was set at 5%.

Results:

Smoking, alcohol consumption, systemic arterial hypertension (SAH) and diabetes mellitus (DM) prevailed in patients, compared to controls (P=0.0088, P=0.0001, P=0.0001, P=0.0011, respectively). In the logistic regression analysis, alcohol consumption and SAH were identified as independent risk factors for gliomas (P=0.0001, P=0.0027, respectively). Patients with low-grade gliomas showed survival in one year (92.0±6.8%), compared to patients with high-grade gliomas (24.0±5.3; P=0.011).

Conclusion:

Polymorphisms involved in cell cycle, telomere protection and stability and DNA repair are not associated with gliomas. On the other hand, alcohol consumption and SAH stand out as independent risk factors for the disease. Low-grade gliomas, response to treatment and the combination of chemotherapy with Temozolomide and radiation therapy show increased survival of patients.

CCND1 Splice Variant as A Novel Diagnostic and Predictive Biomarker for Thyroid Cancer

Cyclin D1 protein is aberrantly overexpressed in thyroid cancers, but mutations of the CCND1 gene are rare in these tumors. We investigated the CCND1 rs9344 (G870A) polymorphism and the expression profiles of wild-type CCND1a and shortened oncogenic isoform CCND1b at the mRNA and protein levels in 286 thyroid tumors. Genotype AA of rs9344 was associated with high expression of CCND1b mRNA and was more frequently found in thyroid cancer than in benign tumors. The mRNA expression levels of CCND1b were higher in papillary thyroid carcinoma (PTC) than in benign or other malignant tumors. However, the expression of CCND1a mRNA showed no association with the parameters. Noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) was distinguished from PTC by low expression of CCND1b at mRNA and protein levels. We further observed that cyclin D1b immunostaining helped to avoid the misdiagnosis of classic PTC with predominant follicular pattern as NIFTP in a separate cohort. Nuclear cyclin D1b expression was associated with aggressive clinicopathologic features in PTC. These findings suggest that cyclin D1b overexpression can be used as a diagnostic and predictive biomarker in thyroid tumors and may be functionally involved in the development and progression of the disease.

Identification of key genes of papillary thyroid cancer using integrated bioinformatics analysis

OBJECTIVE

To identify novel clinically relevant genes in papillary thyroid carcinoma from public databases.

METHODS

Four original microarray datasets, GSE3678, GSE3467, GSE33630 and GSE58545, were downloaded. Differentially expressed genes (DEGs) were filtered from integrated data. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, followed by protein-protein interaction (PPI) network construction. The CentiScape pug-in was performed to scale degree. The genes at the top of the degree distribution (≥ 95% percentile) in the significantly perturbed networks were defined as central genes. UALCAN and The Cancer Genome Atlas Clinical Explorer were used to verify clinically relevant genes and perform survival analysis.

RESULT

225 commonly changed DEGs (111 up-regulated and 114 down-regulated) were identified. The DEGs were classified into three groups by GO terms. KEGG pathway enrichment analysis showed DEGs mainly enriched in the PI3K-Akt signaling pathway, pathways in cancer, focal adhesion and proteoglycans in cancer. DEGs' protein-protein interaction (PPI) network complex was developed; six central genes (BCL2, CCND1, FN1, IRS1, COL1A1, CXCL12) were identified. Among them, BCL2, CCND1 and COL1A1 were identified as clinically relevant genes.

CONCLUSION

BCL2, CCND1 and COL1A1 may be key genes for papillary thyroid carcinoma. Further molecular biological experiments are required to confirm the function of the identified genes.