膀胱癌预后的mRNA分子标记和预测模型开发

李文省; 张彦丽; 周志敏; 庞永冰; 张雁

doi:10.13201/j.issn.1001-1420.2020.05.009

膀胱癌预后的mRNA分子标记和预测模型开发

- 1. 菏泽医学专科学校诊断教研室(山东菏泽, 274000);
- 2. 菏泽医学专科学校附属医院泌尿外科;
- 3. 清华大学蛋白质研究技术中心;
- 4. 华中农业大学动物科学动物医学学院;
- 5. 曹县人民医院泌尿外科

详细信息

通讯作者: 张彦丽,E-mail:yanlizhang12@mail.tsinghua.edu.cn

中图分类号: R737.14

收稿日期: 2019-02-02

Development of mRNA molecular marker and prediction model for prognosis of bladder cancer

- 1. Department of Diagnosis, Heze Medical College, Heze, Shandong, 274000, China;
- 2. Department of Urology, Affiliated Hospital of Heze Medical College;
- 3. Center of Beijing Biomedical Analysis, Tsinghua University;
- 4. School of Veterinary Medicine, Huazhong Agricultural University;
- 5. Department of Urology, Caoxian People's Hospital

More Information

Corresponding author: ZHANG Yanli, E-mail: yanlizhang12@mail.tsinghua.edu.cn

Received Date: 02 February 2019

摘要

摘要: 目的:通过TCGA数据库挖掘膀胱癌预后相关的mRNA分子标记,和构建膀胱癌患者预后的预测模型。方法:从TCGA数据库中下载膀胱癌患者的mRNA表达谱数据,进行预处理和分组后,先在训练数据中通过单因素Cox回归分析和基于似然的生存分析等方法鉴定与膀胱癌预后生存率显著相关的mRNA分子,然后通过多变量Cox回归分析建立基于mRNA分子表达谱的膀胱癌预后风险评分模型,最后通过ROC分析确定患者分类风险水平的最佳分界点,并通过Kaplan-Meier估计法和log-rank检验在验证数据集和全部数据集中分别验证预后风险评分模型。结果:开发了首个基于mRNA分子标记的膀胱癌预后风险评分模型,发现将基于7个mRNA分子标记的膀胱癌风险评分模型应用于训练集或验证数据时,高风险评分患者与低风险评分患者的生存曲线均存在显著差异,进一步的功能研究这发现这7个mRNA分子在肿瘤发生、进展和预后中可能发挥着重要作用。结论:7个mRNA分子标记包括ZNF432、TNFRSF14、POLR3G、ZNF574、LIPT1、AGER和ZRSR2,基于这7个mRNA表达谱构建的风险评分模型可作为新型生物标记用于膀胱癌患者预后生存期预测。
- 膀胱癌 /
- 分子标记 /
- 预后模型 /
- mRNA
Abstract: Objective: To explore mRNA molecular markers related to bladder cancer prognosis through the TCGA database, and construct a model for prognostic prediction of bladder cancer patients. Method: The mRNA expression data of bladder cancer patients were downloaded from the TCGA database. After data preprocessing and grouping, single factor Cox regression analysis and the likelihood-based survival analysis were used to identify mRNA molecules significantly associated with bladder cancer survival in the training data. Then, through multivariate Cox regression analysis, a bladder cancer prognosis risk score model was built based on mRNA expression profile. In addition, an optimal cut-off point of the classification of risk level in bladder cancer patients was calculated using ROC curve. Finally, Kaplan-Meier estimation method and log-rank test were used to verify the prognostic risk score model in the validated data set and the whole data sets respectively. Result: We developed the first mRNA-based prognosis risk score model for bladder cancer.When this model was applied either to the training set or to the validation sets, the patients with high risk of survival and patients with low risk were distinguished significantly.A further functional study found that these seven mRNA molecules may play an important role in tumorigenesis, development and prognosis.Conclusion: The seven mRNA molecular markers including ZNF432, TNFRSF14, POLR3 G, ZNF574, LIPT1, AGER, and ZRSR2 can be used as novel biomarkers to predict the prognosis and survival of bladder cancer patients.
- bladder cancer /
- molecular marker /
- prognostic model /
- mRNA

HTML全文

参考文献(30)

[1]	Ferlay J,Soerjomataram I,Dikshit R,etal.Cancer incidence and mortality worldwide:Sources,methods and major patterns in GLOBOCAN 2012[J].Int J Cancer,2015,136(5):E359-E386.
[2]	龙武林,程帆.长链非编码RNA HNF1A-AS1在膀胱癌中的表达水平及其临床意义[J].临床泌尿外科杂志,2019,34(3):210-214.
[3]	刘正升,陈磊,邢金春.膀胱癌新型基因和生物标记物研究进展[J].临床泌尿外科杂志,2017,32(2):80-83.
[4]	郭园园,刘贝贝,汪盛,等.分子标记物预测肌层浸润性膀胱癌疗效的研究进展[J].临床泌尿外科杂志,2019,34(5):75-79.
[5]	Mercer TR,Dinger ME,Mattick JS.Long non-coding RNAs:insights into functions[J].Nat Rev Genet,2009,10(3):155-159.
[6]	Maruyama R,Suzuki H.Long noncoding RNA involvement in cancer[J].Bmb Rep,2012,45(11):604.
[7]	Zhu X,Tian X,Yu C,et al.A long non-coding RNA signature to improve prognosis prediction of gastric cancer[J].Mol Cancer,2016,15(1):60.
[8]	Meng J,Li P,Zhang Q,et al.A four-long non-coding RNA signature in predicting breast cancer survival[J].J Exp Clin Canc Res,2014,33(1):84.
[9]	Sun J,Cheng L,Shi H,et al.A potential panel of six-long non-coding RNA signature to improve survival prediction of diffuse large-B-cell lymphoma[J].Sci Rep-UK,2016,6:27842.
[10]	Cao W,Liu JN,Liu Z,et al.A three-lncRNA signature derived from the Atlas of ncRNA in cancer(TANRIC)database predicts the survival of patients with head and neck squamous cell carcinoma[J].Oral Oncol,2017,65:94-101.
[11]	Sun Y,Hu B,Wang Q,et al.Long non-coding RNA HOTTIP promotes BCL-2 expression and induces chemoresistance in small cell lung cancer by sponging miR-216a[J].Cell Death Dis,2018,9(2):85.
[12]	Mao X,Qin X,Li L,et al.A 15-long non-coding RNA signature to improve prognosis prediction of cervical squamous cell carcinoma[J].Gynecol Oncol,2018,149(1):181-187.
[13]	Sidaway P.Bladder cancer:TCGA cohort is representative of invasive disease[J].Nat Rev Urol,2017,14(6):327.
[14]	王庆伟,张涛,文建国,等.上尿路尿路上皮癌预后多因素分析及术后再发膀胱癌危险因素分析[J].临床泌尿外科杂志,2018,33(5):385-389.
[15]	Therneau T M,Lumley T.Package'survival'[J].R Top Doc,2015,128:112.
[16]	Renaud G,Stenzel U,Maricic T,et al.deML:robust demultiplexing of Illumina sequences using a likelihood-based approach[J].Bioinformatics,2015,31(5):770-772.
[17]	Heagerty PJ,Lumley T,Pepe MS.Time-dependent ROC curves for censored survival data and a diagnostic marker[J].Biometrics,2000,56(2):337-344.
[18]	Wu AC,Himes BE,Laskysu J,et al.Inhaled corticosteroid treatment modulates ZNF432 gene variant'seffect on bronchodilator response in asthmatics[J].J Allergy Clin Immun,2014,133(3):723-728.
[19]	Cao L,Wang S,Zhang Y,et al.Zinc-finger protein 471 suppresses gastric cancer through transcriptionally repressing downstream oncogenic PLS3 and TFAP2A[J].Oncogene,2018,37(26):3601-3616.
[20]	Pei L,He X,Li S,et al.KRAB zinc-finger protein 382 regulates epithelial-mesenchymal transition and functions as a tumor suppressor,but is silenced by CpG methylation in gastric cancer[J].Int J Oncol,2018,53(3):961-972.
[21]	王一,刘晓强,郭战军,等.膀胱癌中锌指结构转录因子1和E钙黏蛋白的表达及其相关性研究[J].中华泌尿外科杂志,2015,36(5):337-341.
[22]	马俊红,宋志强,李胜文.斑点型锌指结构蛋白在膀胱癌中的表达[J].中国医药,2015,10(7):1074-1077.
[23]	Wang S,Peng Z,Wang S,et al.KRAB-type zinc-finger proteins PITA and PISA specifically regulate p53-dependent glycolysis and mitochondrial respiration[J].Cell Res,2018,28(5):572-592.
[24]	Berg M,Agesen TH,Thiis-Evensen E,et al.Distinct high resolution genome profiles of early onset and late onset colorectal cancer integrated with gene expression data identify candidate susceptibility loci[J].Mol Cancer,2010,9:100.
[25]	Zhu YD,Lu MY.Increased expression of TNFRSF14 indicates good prognosis and inhibits bladder cancer proliferation by promoting apoptosis[J].Mol Med Rep,2018,18(3):3403-3410.
[26]	Pan Z,Liu L,Nie W,et al.Long non-coding RNA AGER-1 functionally upregulates the innate immunity gene AGER and approximates its anti-tumor effect in lung cancer[J].Mol Carcinogen,2018,57(3):305-318.
[27]	Lund RJ,Rahkonen N,Malonzo M,et al.RNA Polymerase Ⅲ Subunit POLR3G Regulates Specific Subsets of PolyA +,and SmallRNA Transcriptomes and Splicing in Human Pluripotent Stem Cells[J].Stem Cell Rep,2017,8(5):1442-1454.
[28]	Kim SS,Stevenson KE,Yoda A,et al.Loss-Of-Function Mutations In The Splicing Factor ZRSR2 Are Common In Blastic Plasmacytoid Dendritic Cell Neoplasm and Have Male Predominance[J].Blood,2013,122(21):741.
[29]	Hong JY,Seo JY,Kim SH,et al.Mutations in the Spliceosomal Machinery Genes SRSF2,U2AF1,and ZRSR2 and Response to Decitabine in Myelodysplastic Syndrome[J].Anticancer Res,2015,35(5):3081-3089.
[30]	Vargas T,Moreno-Rubio J,Herranz J,et al.ColoLipid Gene:signature of lipid metabolism-related genes to predict prognosis in stage-Ⅱ colon cancer patients[J].Oncotarget,2015,6(9):7348-7363.