The CCND1 G870A polymorphism and susceptibility to bladder cancer

Genetic Polymorphisms Involved in Bladder Cancer: A Global Review

Bladder cancer (BC) has been associated with genetic susceptibility. Single peptide polymorphisms (SNPs) can modulate BC susceptibility. A literature search was performed covering the period between January 2000 and October 2020. Overall, 334 articles were selected, reporting 455 SNPs located in 244 genes. The selected 455 SNPs were further investigated. All SNPs that were associated with smoking and environmental exposure were excluded from this study. A total of 197 genes and 343 SNPs were found to be associated with BC, among which 177 genes and 291 SNPs had congruent results across all available studies. These genes and SNPs were classified into eight different categories according to their function.

Genetic and expression variations of cell cycle pathway genes in brain tumor patients

The present study was designed to determine the association between the genetic polymorphisms/expression variations of RB1 and CCND1 genes and brain tumor risk. For this purpose, 250 blood samples of brain tumor patients along with 250 controls (cohort I) and 96 brain tumor tissues (cohort II) with adjacent control section were collected. Mutation analysis of RB1 (rs137853294, rs121913300) and CCND1 (rs614367, rs498136) genes was performed using ARMS-PCR followed by sequencing, and expression analysis was performed using real-time PCR and immunohistochemistry. The results showed homozygous mutant genotype of RB1 gene polymorphism, rs121913300 (P=0.003) and CCND1 gene polymorphism rs614367 (P=0.01) were associated significantly with brain tumor risk. Moreover, significant down-regulation of RB1 (P=0.005) and up-regulation of CCND1 (P=0.0001) gene was observed in brain tumor sections vs controls. Spearman correlation showed significant negative correlation between RB1 vs proliferation marker, Ki-67 (r = -0.291*, P<0.05) in brain tumors. Expression levels of selected genes were also assessed at protein level using immunohistochemical analysis (IHC) and signification down-regulation of RB1 (P=0.0001) and up-regulation of CCND1 (P=0.0001) was observed in brain tumor compared with control sections. In conclusion, it is suggested that polymorphisms/expression variations of RB1 and CCND1 genes may be associated with increased risk of brain tumor.

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.

Impact of interaction between the G870A and EFEMP1 gene polymorphism on glioma risk in Chinese Han population

AIMS

To investigate the impact of CCND1 and EFEMP1 gene polymorphism, and additional their gene-gene interactions and haplotype within EFEMP1 gene on glioma risk based on Chinese population.

METHODS

Logistic regression was performed to investigate association between single-nucleotide polymorphisms (SNP) and glioma risk and generalized multifactor dimensionality reduction (GMDR) was used to analyze the gene-gene interaction.

RESULTS

Glioma risks were higher in carriers of homozygous mutant of rs603965 within CCND1 gene, rs1346787 and rs3791679 in EFEMP1 gene than those with wild-type homozygotes, OR (95%CI) were 1.67 (1.23-2.02), 1.59 (1.25-2.01) and 1.42 (1.15-1.82), respectively. GMDR analysis indicated a significant two-locus model (p=0.0010) involving rs603965 within CCND1 gene and rs1346787 within EFEMP1 gene. Overall, the cross-validation consistency of the two- locus models was 10\ 10, and the testing accuracy is 60.17%. Participants with rs603965 - GA or AA and rs1346787- AG or GG genotype have the highest glioma risk, compared to participants with rs603965 - GG and rs1346787- AA genotype, OR (95%CI) was 3.65 (1.81-5.22). We conducted haplotype analysis for rs1346787 and rs3791679, because D' value between rs1346787 and rs3791679 was more than 0.8. The most common haplotype was rs1346787 - A and rs3791679- G haplotype, the frequency of which was 0.4905 and 0.4428 in case and control group.

CONCLUSIONS

Polymorphism in rs603965 within CCND1 gene and rs1346787 within EFEMP1 gene and its gene- gene interaction were associated with increased glioma risk.

Association between the G870A polymorphism of Cyclin D1 gene and glioma risk

Previous studies have shown the association of the Cyclin D1 (CCND1) G870A polymorphism with glioma risk, but the findings are inconsistent and inconclusive. To shed some light on the findings across individual studies and acquire a quantitative assessment of this association, we conducted a meta-analysis of all published case-control studies thus far. Four independent studies with a total of 690 cases and 1,014 controls were identified after a systematic search of the PubMed, Embase, Web of Science, and Wanfang databases. The strength of the association between the CCND1 G870A polymorphism and glioma risk was estimated by the pooled odds ratios (ORs) with 95 % confidence intervals (95 %CIs). Subgroup analysis by ethnicity was also performed. Overall, a statistically significant association was found between the CCND1 G870A polymorphism and glioma risk in three genetic models (ORA vs. G = 1.178, 95 %CI 1.025-1.354, P OR = 0.021; ORAA vs. GG = 1.328, 95 %CI 1.007-1.750, P OR = 0.045; ORAA + AG vs. GG = 1.253, 95 %CI 1.006-1.516, P OR = 0.044). In subgroup analysis, the pooled ORs suggested that the CCND1 G870A polymorphism was associated with an increased risk of glioma in Caucasians under the heterozygote and dominant genetic models (ORAG vs. GG = 1.329, 95 %CI 1.001-1.766, P OR = 0.049; ORAA + AG vs. GG = 1.332, 95 %CI 1.019-1.740, P OR = 0.036). The meta-analysis suggests that the CCND1 G870A polymorphism is a risk factor for the development of glioma.