An Overview of the Polymorphisms of Circadian Genes Associated With Endocrine Cancer

Morales-Santana, Sonia; Morell, Santiago; León, Josefa; Carazo-Gallego, Angel; Jiménez-López, José Carlos; Morell, María

doi:10.3389/fendo.2019.00104

Cited by 60 publications

(45 citation statements)

References 71 publications

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“…Studies have shown the BRIP1 gene variant rs4986764 associated with breast cancer in Chinese population [32], however no significant association was found in the studied population. The variant rs3792152 in REV1 gene, not associated with population under study, has been previously reported to be associated with the development of epithelial ovarian cancer in European population [33].…”

Section: Genetic Variants Not Associated With Bc In the Population Unmentioning

confidence: 88%

MassARRAY-based single nucleotide polymorphism analysis in breast cancer of north Indian population

Bakshi

Nagpal

Sharma³

et al. 2020

BMC Cancer

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Background Breast Cancer (BC) is associated with inherited gene mutations. High throughput genotyping of BC samples has led to the identification and characterization of biomarkers for the diagnosis of BC. The most common genetic variants studied are SNPs (Single Nucleotide Polymorphisms) that determine susceptibility to an array of diseases thus serving as a potential tool for identifying the underlying causes of breast carcinogenesis. Methods SNP genotyping employing the Agena MassARRAY offers a robust, sensitive, cost-effective method to assess multiple SNPs and samples simultaneously. In this present study, we analyzed 15 SNPs of 14 genes in 550 samples (150 cases and 400 controls). We identified four SNPs of genes TCF21, SLC19A1, DCC, and ERCC1 showing significant association with BC in the population under study. Results The SNPs were rs12190287 (TCF21) having OR 1.713 (1.08–2.716 at 95% CI) p-value 0.022 (dominant), rs1051266 (SLC19A1) having OR 3.461 (2.136–5.609 at 95% CI) p-value 0.000000466 (dominant), rs2229080 (DCC) having OR 0.6867 (0.5123–0.9205 at 95% CI) p-value 0.0116 (allelic) and rs2298881 (ERCC1) having OR 0.669 (0.46–0.973 at 95% CI), p-value 0.035 (additive) respectively. The in-silico analysis was further used to fortify the above findings. Conclusion It is further anticipated that the variants should be evaluated in other population groups that may aid in understanding the genetic complexity and bridge the missing heritability.

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Section: Genetic Variants Not Associated With Bc In the Population Unmentioning

confidence: 88%

MassARRAY-based single nucleotide polymorphism analysis in breast cancer of north Indian population

Bakshi

Nagpal

Sharma³

et al. 2020

BMC Cancer

View full text Add to dashboard Cite

show abstract

“…Studies have shown the BRIP1 gene variant rs4986764 associated with breast cancer in Chinese population (32), however no signi cant association was found in the studied population. The variant rs3792152 in REV1 gene, not associated with population under study, has been previously reported to be associated with the development of epithelial ovarian cancer in European population (33).…”

Section: Genetic Variants Associated With the Increased Risk Of Bc Inmentioning

confidence: 88%

MassARRAY-based single nucleotide polymorphism analysis in breast cancer of North Indian Population.

Bakshi

Nagpal

Sharma³

et al. 2020

Preprint

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Background Breast Cancer (BC) is associated with inherited gene mutations. High throughput genotyping of BC samples has led to the identification and characterization of biomarkers for the diagnosis of BC. The most common genetic variants studied are SNPs (Single Nucleotide Polymorphisms) that determine susceptibility to an array of diseases thus serving as a potential tool for identifying the underlying causes of breast carcinogenesis. Methods SNP genotyping employing the Agena MassARRAY offers a robust, sensitive, cost-effective method to assess multiple SNPs and samples simultaneously. In this present study, we analyzed 15 SNPs of 14 genes in 550 samples (150 cases and 400 controls). We identified four SNPs of genes TCF21, SLC19A1, DCC, and ERCC1 showing significant association with BC in the population under study. Results The SNPs were rs12190287 (TCF21) having OR 1.713 (1.08-2.716 at 95% CI) p-value 0.022 (dominant), rs1051266 (SLC19A1) having OR 3.461 (2.136-5.609 at 95% CI) p-value 0.000000466 (dominant), rs2229080 (DCC) having OR 0.6867 (0.5123 -0.9205 at 95% CI) p-value 0.0116 (allelic) and rs2298881 (ERCC1) having OR 0.669 (0.46-0.973 at 95% CI), p-value 0.035 (additive) respectively. The in-silico analysis was further used to fortify the above findings. Conclusion It is further anticipated that the variants should be evaluated in other population groups that may aid in understanding the genetic complexity and bridge the missing heritability.

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“…Maglic et al demonstrated that overexpression of DMTF1β was associated with poor clinical outcomes, by examining the expression of DMTF1β in the cancer and adjacent tissue from twenty breast cancer patients, which suggested that DMTF1β could be considered a potential diagnostic index for patients with breast cancer [47]. When it comes to RORA, viewed as a member of the circadian genes, it could disrupt endogenous homeostasis and thereby promote endocrine tumor development and accelerate progression resulting from the dysfunction of this gene [48]. Taheri et al found that one functional polymorphism (rs4774388) of RORA was associated with breast cancer risk after performing a comparative analysis between the breast cancer patients and the healthy persons in Iran [49].…”

Section: Discussionmentioning

confidence: 99%

Identification of Potential Prognostic Biomarkers for Breast Cancer Based on lncRNA-TF-Associated ceRNA Network and Functional Module

Zhu

Qiu

2020

BioMed Research International

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Breast cancer leads to most of cancer deaths among women worldwide. Systematically analyzing the competing endogenous RNA (ceRNA) network and their functional modules may provide valuable insight into the pathogenesis of breast cancer. In this study, we constructed a lncRNA-TF-associated ceRNA network via combining all the significant lncRNA-TF ceRNA pairs and TF-TF PPI pairs. We computed important topological features of the network, such as degree and average path length. Hub nodes in the lncRNA-TF-associated ceRNA network were extracted to detect differential expression in different subtypes and tumor stages of breast cancer. MCODE was used for identifying the closely connected modules from the ceRNA network. Survival analysis was further used for evaluating whether the modules had prognosis effects on breast cancer. TF motif searching analysis was performed for investigating the binding potentials between lncRNAs and TFs. As a result, a lncRNA-TF-associated ceRNA network in breast cancer was constructed, which had a scale-free property. Hub nodes such as MDM4, ZNF410, AC0842-19, and CTB-89H12 were differentially expressed between cancer and normal sample in different subtypes and tumor stages. Two closely connected modules were identified to significantly classify patients into a low-risk group and high-risk group with different clinical outcomes. TF motif searching analysis suggested that TFs, such as NFAT5, might bind to the promoter and enhancer regions of hub lncRNAs and function in breast cancer biology. The results demonstrated that the synergistic, competitive lncRNA-TF ceRNA network and their functional modules played important roles in the biological processes and molecular functions of breast cancer.

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An Overview of the Polymorphisms of Circadian Genes Associated With Endocrine Cancer

Cited by 60 publications

References 71 publications

MassARRAY-based single nucleotide polymorphism analysis in breast cancer of north Indian population

MassARRAY-based single nucleotide polymorphism analysis in breast cancer of north Indian population

MassARRAY-based single nucleotide polymorphism analysis in breast cancer of North Indian Population.

Identification of Potential Prognostic Biomarkers for Breast Cancer Based on lncRNA-TF-Associated ceRNA Network and Functional Module

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