基于TCGA数据库筛选乳腺癌不良预后相关mi RNAs及风险评估
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摘要
目的基于公用数据库,寻找可作为乳腺癌生物标记物的miRNAs。方法利用人类肿瘤基因组(TCGA)数据库下载乳腺癌相关数据集,分析肿瘤组织与正常组织之间miRNAs的差异表达。Cox单因素回归分析与不良预后相关的miRNAs;对差异表达中上调的有意义的miRNAs进行Cox多因素回归分析,建立风险评估模型。结果与正常组织比较,乳腺癌组织中有370个差异表达miRNAs,其中108个miRNAs表达下调,262个miRNAs表达上调。20个miRNAs的高表达与预后不良相关。进一步建立Cox回归模型筛选出10个miRNAs组合(包括hsa-mir-148b、hsa-mir-449c、hsa-mir-106a、hsa-mir-181d、hsa-mir-9-3、hsa-mir-549a、hsa-mir-556、hsa-mir-618、hsa-mir-466、hsa-mir-135a-1)预测乳腺癌不良预后。结论筛选的10个miRNAs组合(ten-miRNAs)的高评分可成为预测乳腺癌不良预后的生物标记物。
Objective To search for miRNAs as biomarkers for breast cancer based on public databases.Methods Breast cancer datasets were downloaded from the Cancer Genome Atlas(TCGA) database and analyzed for differential expression of miRNAs between tumor tissues and normal tissues. Cox univariate regression was used to analyze the miRNAs associated with poor prognosis. Cox multivariate regression was used to analyze the meaningful miRNAs upregulated in differential expression and a risk assessment model was established. Results Compared with normal tissues,there were 370 differentially expressed miRNAs in breast cancer tissues, of which 108 miRNAs were down-regulated and262 miRNAs were up-regulated. The high expression of 20 miRNAs was associated with poor prognosis. Further, a Cox regression model was established to screen out 10 miRNA combinations(including hsa-mir-148 b, hsa-mir-449 c, hsa-mir-106 a, hsa-mir-181 d, hsa-mir-9-3, hsa-mir-549 a, hsa-mir-556, hsa-mir-618, hsa-mir-466, hsa-mir-135 a-1) to predict the poor prognosis of breast cancer. Conclusion The high score of the screened ten-miRNAs could be biomarkers for predicting poor prognosis of breast cancer.
Objective To search for miRNAs as biomarkers for breast cancer based on public databases.Methods Breast cancer datasets were downloaded from the Cancer Genome Atlas(TCGA) database and analyzed for differential expression of miRNAs between tumor tissues and normal tissues. Cox univariate regression was used to analyze the miRNAs associated with poor prognosis. Cox multivariate regression was used to analyze the meaningful miRNAs upregulated in differential expression and a risk assessment model was established. Results Compared with normal tissues,there were 370 differentially expressed miRNAs in breast cancer tissues, of which 108 miRNAs were down-regulated and262 miRNAs were up-regulated. The high expression of 20 miRNAs was associated with poor prognosis. Further, a Cox regression model was established to screen out 10 miRNA combinations(including hsa-mir-148 b, hsa-mir-449 c, hsa-mir-106 a, hsa-mir-181 d, hsa-mir-9-3, hsa-mir-549 a, hsa-mir-556, hsa-mir-618, hsa-mir-466, hsa-mir-135 a-1) to predict the poor prognosis of breast cancer. Conclusion The high score of the screened ten-miRNAs could be biomarkers for predicting poor prognosis of breast cancer.
引文
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[2]罗年安,屈亚琦,董瑞.乳腺癌的治疗进展[J].现代生物医学进展,2015,1:160-162.
[3]Mulrane L,Klinger R,Mcgee SF,et al.microRNAs:a new class of breast cancer biomarkers[J].Expert Rev Mol Diagn,2014,14(3):347-363.
[4]Kloosterman WP,Plasterk RH.The diverse functions of microRNAs in animal development and disease[J].Dev Cell,2006,11(4):441-450.
[5]Di Leva G,Garofalo M,Croce CM.MicroRNAs in Cancer[J].Annual Review of Pathology:Mechanisms of Disease,2014,9(1):287-314.
[6]Caldas C,Brenton JD.Sizing up miRNAs as cancer genes[J].Nat Med,2005,11(7):712-714.
[7]Chen X,Wang YW,Zhu WJ,et al.A 4-microRNA signature predicts lymph node metastasis and prognosis in breast cancer[J].Hum Pathol,2018,76:122-132.
[8]Teng Y,Su X,Zhang X,et al.miRNA-200a/c as potential biomarker in epithelial ovarian cancer(EOC):evidence based on miRNAmeta-signature and clinical investigations[J].Oncotarget,2016,7(49):81621-81633.
[9]Ding Q,Wang Y,Zuo Z,et al.Decreased expression of microRNA-26b in locally advanced and inflammatory breast cancer[J].Hum Pathol,2018,77:121-129.
[10]Zhu QN,Renaud H,Guo Y.Bioinformatics-based identification of miR-542-5p as a predictive biomarker in breast cancer therapy[J].Hereditas,2018,155:17.
[11]Wu Z,Wang H,Fang S,et al.MiR-449c inhibits gastric carcinoma growth[J].Life Sci,2015,137:14-19.
[12]Bertoli G,Cava C,Castiglioni I.MicroRNAs:new biomarkers for diagnosis,prognosis,therapy prediction and therapeutic tools for breast cancer[J].Theranostics,2015,5(10):1122-1143.