New single nucleotide polymorphisms (SNPs) in homologous recombination repair genes detected by microarray analysis in Polish breast cancer patients

Bioinformatics Analysis Reveals the Related Role of miR-511-5p in the Progression of Breast Cancer

Breast cancer remains a dangerous disease, and delving the molecular mechanism of breast cancer is still necessary. To illustrate the role of miR-511-5p, TCGA database was used to excavate the abundance of miR-511-5p, and the miR-511-5p level was measured in the pathological tissues and tumor cell lines. Moreover, the targets of miR-511-5p were identified with miRDIP and GEPIA and then were used for functional enrichment analysis. Besides, the targets of miR-511-5p were analyzed with the protein-protein interaction (PPI) network for the hub nodes, and then the expression levels of the hub nodes were visualized with the GEPIA database. The results showed that miR-511-5p was significantly downregulated in multiple types of tumor samples in the online database, and the downregulated miR-511-5p was also found in pathological tissues and tumor cell lines. Moreover, 48 genes were identified as the potential targets of miR-511-5p by miRDIP and GEPIA databases and enriched in cell cycle, PI3K/AKT, and P53 pathways. Besides, seven genes including BRCA1, FN1, CCNE1, CCND1, CHEK1, BUB3, and CDC25A were identified as the hub nodes by the PPI network, and CCNE1 and CHEK1 were confirmed to be related with the prognostic survival of the patients with breast cancer. In conclusion, the proofs in this study suggest that reduced miR-511-5p was a biomarker event for breast cancer, and CCNE1 and CHEK1 served as potential targets of miR-511-5p to involve the progression of breast cancer.

Characterization and in silico analyses of the BRCA1/2 variants identified in individuals with personal and/or family history of BRCA-related cancers

Pathogenic variants in the coding regions of the BRCA1/2 lead dysfunctional or nonfunctional BRCA proteins however the contribution of non-coding BRCA1/2 variants to BRCA-related disease risk has not been fully elucidated. Thus, we characterized the functional impact of both coding and non-coding BRCA1/2 variants identified in individuals with personal and/or family history of BRCA-related cancers. The data were produced by resequencing the exons and exon-intron junctions of the BRCA1/2 in 125 individuals and were comprehensively analyzed by using bioinformatics tools and databases. A total of 96 variants (59 coding and 37 non-coding) including 7 novel variants were identified and analyzed for their functional importance. We identified 11 missense variants that potentially affect protein function; 22 variants were likely to alter different types of posttranslational modifications. Also, multiple non-coding BRCA1/2 variants were found to reside in the critical regulatory regions that have the potential to act as eQTLs and affect alternative splicing. The results of our study shed light on the possible contributions of not only coding variants but also non-coding BRCA1/2 variants in BRCRA-related cancers. Further investigation is required to fully understand their potential associations with phenotypes which may ultimately lead their utilization on cancer management as a biomarker.

XPC as breast cancer susceptibility gene: evidence from genetic profiling, statistical inferences and protein structural analysis

BACKGROUND

Gene polymorphisms that affect nucleotide excision repair (NER) pathway may link with higher susceptibility of breast cancer (BC); however, the significance of these associations may vary conferring to the individual ethnicity. Xeroderma pigmentosum complementation gene (XPC) plays a substantial role in recognizing damaged DNA during NER process.

OBJECTIVE AND METHODS

To estimate the relationship among XPC polymorphisms and breast cancer (BC) risk, we carried out a case-control-association study with 493 BC cases and 387 controls using TETRA-ARMS-PCR. Distributional differences of clinical features, demographic factors and XPC polymorphisms among BC cases and controls were examined by conditional logistic regression model. Kaplan-Meier test was applied to predict survival distributions and protein structure was predicted using computational tools.

RESULTS

Obesity, consanguinity, positive marital status and BC family history were associated (P ≤ 0.01) with higher BC risk. Genotyping revealed significant involvement (P ≤ 0.01) of two XPC polymorphisms rs2228001-A > C (OR = 3.8; CI 1.9-7.6) and rs2733532-C > T (OR = 2.6; CI 1.4-5.03) in BC development, asserting them potential risk factors for increased BC incidence. However, no association (P > 0.05) was detected for overall or progression free survival for both XPC polymorphisms possibly due to shorter follow-up time (45 months). As compared to normal XPC structure, pronounced conformational changes have been observed in the C-terminus of XPC^Q939K, bearing rs2228001-A > C substitution. In XPC^Q939K, two additional α-helices were observed at A292-E297 and Y252-R286, while L623-M630 and L649-L653 helices were converted into loop conformation.

CONCLUSION

In conclusion, both XPC polymorphisms confer significant association with increased BC risk. rs2228001 substitution may change the structural and functional preferences of XPC C-terminus, while rs2733532 may have regulatory role thereby leading to potential BC risk.

Gene expression profiling revealed MCM3 to be a better marker than Ki67 in prognosis of invasive ductal breast carcinoma patients

Invasive ductal carcinoma (IDC) is the most common breast cancer. Our study used gene microarray data to select differentially expressed genes between normal and IDC mammary tissues. From these, we selected genes related to the proliferation of tumor cells and compared their prognostic value with known biomarker Ki67 for IDC. Analysis of publicly available Gene Expression Omnibus (GEO) data revealed 24 differentially expressed genes (DEGs) in normal and 31 DEGS in IDC tissues that were used for further analyses. Gene chip analysis software was used to identify DEGs. DEG profiles were confirmed using quantitative PCR (qPCR). DEG functions where shown to be related to cell proliferation. We confirmed MCM3 expression using immunohistochemical staining in 45 IDC patients. The relationship between MCM3 expression and survival was investigated using Kaplan-Meier survival curves and Cox proportional hazard regression models. A total of 1307 differentially expressed genes were identified between IDC and normal tissues, which were enriched in 32 Gene Ontology (GO) terms and 9 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. qPCR demonstrated that both COL1A1 and MCM3 were significantly up-regulated in IDC tissues, of which only MCM3 was related to cell proliferation. Ki67 is closely associated with the tumor grade, ER status, PR status and HER2 status, while MCM3 was shown to relate to tumor size, lymph node, and PR status. There was significant association between survival and MCM3, but not for Ki67. High MCM3 expression demonstrated statistically significant associations with poor prognosis in IDC patients. Findings from the gene microarray data analysis confirmed that MCM3 is associated with the response to cell proliferation. MCM3 represents a better proliferation marker than Ki67 making it a valuable prognostic tool that is independent of ER and HER2 status.

Novel Associations between BRCA1 Variants C.181 T>G (Rs28897672) and Ovarian Crisk in Saudi Females

BACKGROUND

Mutations in BRCA1 gene have been implicated in ovarian cancers, and BRCA testing may be conducted in high-risk women. This study was designed to determine the frequency of three single nucleotide polymorphisms (SNPs) variants in BRCA1 gene and BRCA1 expression in Saudi females with ovarian cancer.

METHODS

Expression levels of mRNA of BRCA1 gene were studied in 10 ovarian cancer and 10 normal ovarian tissues, by quantitative real time polymerase chain reaction (qPCR). The study also included 28 females who had suffered from ovarian cancer and had been successfully operated upon and 90 healthy females with no history of cancer. Blood was drawn in EDTA tubes and used for extraction of DNA. The genotyping was carried out using Taqman® SNP Genotyping kit by RT-PCR. The variants investigated included c.871 T>C (rs799917), c.1040 G>A (rs4986852), c.181 T>G (rs28897672) in BRCA1 gene.

RESULTS

The c.181 T>G (rs28897672) showed significantly different genotype and allele frequencies between the patients and the control subjects (p value = 0.002 and 0.02, respectively). The genotype TG was significantly protective (OR = 0.36, p value = 0.024). The mRNA expression of BRCA1 gene was found to be low in the ovarian cancer tissues.

CONCLUSIONS

This study showed that c.181 T>G in BRCA1 genes is associated with the development of ovarian cancer in Saudis. More studies are needed to unveil other SNPs that may be associated with ovarian cancer and to understand the mechanism(s) involved in reducing the expression of BRCA1 gene in ovarian cancer tissues.

Characteristic and influencing factors of Taqman genotyping calling error

BACKGROUND

Taqman fluorescent probe was frequently applied in single nucleotide polymorphism (SNP) genotyping. However, the characteristic of calling error and the influencing factors remain unclear.

METHOD

Calling errors of Taqman genotyping was evaluated systematically based on Mendelian inheritance. Twenty-two SNPs were genotyped by Taqman probe for 419 pedigrees. Mendelian genetic errors were counted for every SNP and pedigree. Cluster analysis was applied to investigate the compatibility between Taqman probes and DNA sample.

RESULTS

On one hand, errors were found for all the SNPs. The error number ranged from 4 to 33 with median of 10.5. On the other hand, Mendelian genetic errors showed features of both randomness and cluster. Half of the pedigrees containing errors had only 1 Mendelian genetic error. But there was also a pedigree containing up to 10 Mendelian genetic errors. Furthermore, cluster analysis indicated that errors of different SNPs took place in different pedigree cluster.

CONCLUSION

It could be concluded that calling error is inevitable for Taqman genotyping of large samples. The quality of Taqman probe and DNA sample, as well as their compatibility, may account for the error incidence.