کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5888002 1152300 2015 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Tissue-specific selection of optimal reference genes for expression analysis of anti-cancer drug-related genes in tumor samples using quantitative real-time RT-PCR
موضوعات مرتبط
علوم زیستی و بیوفناوری بیوشیمی، ژنتیک و زیست شناسی مولکولی بیوشیمی بالینی
پیش نمایش صفحه اول مقاله
Tissue-specific selection of optimal reference genes for expression analysis of anti-cancer drug-related genes in tumor samples using quantitative real-time RT-PCR
چکیده انگلیسی
Gene transcription analysis in clinical tumor samples can help with diagnosis, prognosis, and treatment of cancers. We aimed to identify the optimal reference genes for reliable expression analysis in various tumor samples by quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR). Using a one-step TaqMan-based qRT-PCR, 5 commonly used reference genes (ACTB, GAPDH, RPLPO, GUSB, and TFRC) and 10 anticancer drug-related genes (TYMS, RRM1, TUBB3, STMN1, TOP2A, EGFR, VEGFR2, HER2, ERCC1, and BRCA1) were analyzed in 327 tissue samples from lung, rectal, colon, gastric, esophageal, and breast tumors. According to the expression stability assessments obtained by using three programs (geNorm, NormFinder, and BestKeeper) and a comprehensive ranking method, the optimal reference genes for lung, gastric, esophageal, and breast tumors were RPLPO, GAPDH, ACTB, and ACTB, respectively. For rectal tumors, a combination of the 3 most stable genes (GUSB, ACTB, and RPLPO) was suitable for qRT-PCR, whereas for colon tumors, a combination of the 4 most stable genes (GAPDH, ACTB, GUSB, and RPLPO) was optimal for qRT-PCR. Based on the expression data of target genes normalized against selected reference genes, the principal component analysis revealed 4 expression patterns in 6 different tissues. One pattern was observed in gastric, rectal, and colon tumor tissues, which are gastrointestinal tumors. Expressions in the breast, lung, and esophageal tissues were separately represented as one pattern. Our results could facilitate the practice of personalized cancer medicine based on the gene expression profile of the patients.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Experimental and Molecular Pathology - Volume 98, Issue 3, June 2015, Pages 375-381
نویسندگان
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