Mohammadreza Nassiri; Azadeh Safarchi; Masoume Vakili-Azghandi; Vinod Gopalan; Mohammad Doosti; Shahrokh Ghovvati; Ahmad Reza Movassaghi
Abstract
p53 is a tumor suppressor protein that plays an essential role in controlling the cell and vascular endothelial growth factor (VEGF) is one of the most strong and specific angiogenic factors. The main objective of this study was to evaluate the impact of p53 and VEGF-C gene expression in the neoplastic ...
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p53 is a tumor suppressor protein that plays an essential role in controlling the cell and vascular endothelial growth factor (VEGF) is one of the most strong and specific angiogenic factors. The main objective of this study was to evaluate the impact of p53 and VEGF-C gene expression in the neoplastic and normal mammary gland of canine as an animal model. Elleven benign and malignant specimens and 5 normal specimens were collected. After RNA extraction and cDNA synthesis, relative quantification of p53 and VEGF-C genes were accomplished by Real-time quantitative PCR (RT-qPCR) based on use of β-actin as a reference gene. The relative mRNA expression of the p53 and VEGF-C genes were analyzed by GLM procedure of SAS software v9.2. The results indicated that the VEGF-C and p53 mRNA expression in neoplastic specimens was over-and down-expressed respectively as compared with normal specimens and p53 mRNA expression was significantly negatively associated with VEGF-C (~4 fold) in neoplastic specimens (P <0.01). The findings emphasized that simultaneous evaluation of p53 and VEGF-C expression can be used as tumor biomarker for early diagnosis of malignancy in canine. Furthermore, RT-qPCR is a rapid and sensitive method to for monitoring and investigating of suspicious canine at the beginning stage of malignancy and may provide an alternative explanation for deregulated p53 signalling in breast cancer.
Vida Nadafi Sichani; Seyed Alireza Emami; Morteza Bitaraf Sani; Mohammadreza Nassiri; Vinod Gopalan
Abstract
Previous studies have found several distinct alleles at both levels of transcriptional activity and protein-DNA binding manners in breast cancer patients vs. healthy individuals through multi-step experimental approaches. This study presents a computational-based model to investigate ...
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Previous studies have found several distinct alleles at both levels of transcriptional activity and protein-DNA binding manners in breast cancer patients vs. healthy individuals through multi-step experimental approaches. This study presents a computational-based model to investigate the regulatory potential and functional properties of disease-related non-coding single nucleotide polymorphisms (SNPs) variants through several online in silico tools in the Iranian population. The association between the risk of breast cancer and its putative single nucleotide polymorphisms in the Iranian population was investigated through SNPedia database and genome-wide association studies (GWAS). Furthermore, a meta-analysis was performed by Comprehensive Meta-Analysis (CMA) software. Functional analyses were carried out through LDlink, HaploReg, and RegulomeDB. The impact of each single nucleotide polymorphism on gene expression profiles and transcription factor binding sites were predicted by the RegulomeDB. "5", "6", and "1d" scores were assigned to rs3746444, rs1062577, and rs1049174 by this scoring system, respectively. RegulomeDB scores of rs3746444-MYH7B/MIR499A and rs1062577-ESR1 suggested that they are not putative functional single nucleotide polymorphisms; and may not associate with significant eQTL signals. The “1d” score for rs1049174-RP11-277P12.20 confirmed an association with the expression of the target gene. Proxy variants rs6088678 and rs2617160 have been identified using LDlink in non-coding segments. They were in strong linkage disequilibrium (LD) with single nucleotide polymorphisms rs3746444 and rs1049174, respectively. Also, non-coding variants rs6088678-TRPC4AP and rs2617160- RP11-277P12.20 with high-ranked scores showed the strongest related-expression. This work provides a rapid and direct in silico-based approach for the identification of functional genetic variants in the breast cancer. These analyses were conducted to evaluate the association of intended SNPs with the regulatory elements of histones, DNases, motif changes, and selected eQTL signals. It can be extended to some other complex single nucleotide polymorphism-related diseases.
