five

Table 1_Identification of endogenous reference genes for RT-qPCR analysis in breast cancer and matched adjacent tissues.docx

收藏
NIAID Data Ecosystem2026-05-10 收录
下载链接:
https://figshare.com/articles/dataset/Table_1_Identification_of_endogenous_reference_genes_for_RT-qPCR_analysis_in_breast_cancer_and_matched_adjacent_tissues_docx/31178899
下载链接
链接失效反馈
官方服务:
资源简介:
BackgroundReal-time quantitative PCR (RT-qPCR), essential for gene expression and biomarker studies, requires stable endogenous reference genes (RGs) for normalization. This study aimed to identify consistently expressed RGs in breast cancer and adjacent tissues to facilitate comparative analyses of breast cancer-related gene expression. Material and methodsFive candidate RGs (β-actin, 18S rRNA, PUM1, RPLP0, TFRC) were analyzed by RT-qPCR from 30 breast cancer patients. Threshold cycle (Ct) values were evaluated using descriptive statistics, and stability of RGs was assessed using RefFinder, integrating GeNorm, NormFinder, ΔCt, and BestKeeper algorithms. ResultsIn cancer tissues, descriptive statistics showed that 18S rRNA was a suitable RG (Ct Range = 3.96; Mean Ct=8.43; SD = 0.84). RefFinder identified TFRC as the most stable RG (GM = 1.19), followed by 18S rRNA (GM = 1.41). In adjacent tissues, TFRC was find with its narrowest Ct range (Ct range = 6.29) and highest stability (GM = 1.00) by RefFinder. However, GeNorm and BestKeeper indicated instability for TFRC (M = 2.364, SD = 4.30), exceeding the stability threshold values of 1.5 and 1, respectively. Adjacent tissues displayed significantly higher Ct values than cancer tissues. TFRC may serve as the suitable RG for detecting gene expression when concerning both breast cancer and adjacent tissues (GM = 1.19), though, GeNorm and BestKeeper indicated its instability (M = 2.364, SD = 4.30). ConclusionTFRC and 18S rRNA may be suitable RGs in breast cancer tissues, while all five candidates were not stable in adjacent tissues. Larger studies are needed to confirm these findings.
创建时间:
2026-01-29
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作