用于膀胱癌预后预测的lncRNA分子标记物开发

Your Location：

Home >

Browse articles >

用于膀胱癌预后预测的lncRNA分子标记物开发

中国医学科学杂志（英文版） 2020年35卷第3期页码：239-247

Original Article | Updated：2024-04-10

|

- 用于膀胱癌预后预测的lncRNA分子标记物开发
- Affiliations：
  
  1. 1Department of Diagnosis, Heze Medical College, Heze, Shandong 274000, China
  2. 2Department of Urology, Affiliated Hospital of Heze Medical College, Heze, Shandong 274000, China
  3. 3School of Life Sciences, Tsinghua University, Beijing 100084, China
  4. 4School of Veterinary Medicine, Huazhong Agricultural University, Wuhan 430072, China
- Author bio：
  
  * E-mail: yanlizhang12@mail.tsinghua.edu.cn
- Funds：
- DOI：10.24920/003662
  中图分类号：
- 收稿日期：2019-10-16，
  
  网络出版日期：2020-09-30，
  
  纸质出版日期：2020-09-30
- Accepted：
Scan QR Code
李文省, 张彦丽. 用于膀胱癌预后预测的lncRNA分子标记物开发[J]. 中国医学科学杂志（英文版）, 2020,35(3):239-247.

Li Wenxing, Zhang Yanli. Novel Long Non-coding RNA Markers for Prognostic Prediction of Patients with Bladder Cancer[J]. Chinese medical sciences journal, 2020, 35(3): 239-247.
李文省, 张彦丽. 用于膀胱癌预后预测的lncRNA分子标记物开发[J]. 中国医学科学杂志（英文版）, 2020,35(3):239-247. DOI： 10.24920/003662.

Li Wenxing, Zhang Yanli. Novel Long Non-coding RNA Markers for Prognostic Prediction of Patients with Bladder Cancer[J]. Chinese medical sciences journal, 2020, 35(3): 239-247. DOI： 10.24920/003662.

摘要

目的

探讨与膀胱癌预后相关的长链非编码RNA (lncRNA)分子标志物

建立膀胱癌患者的预后预测模型。

方法

从TCGA数据库中下载膀胱癌患者lncRNA的表达数据。使用单变量Cox回归和基于似然的生存分析发现预后相关的lncRNA分子标记。通过共表达分析和代谢通路富集分析对预后相关的lncRNA进行功能研究。采用多变量Cox回归分析建立风险评分模型

ROC分析确定模型的最佳分界点。通过Kaplan-Meier估计法和log-rank检验对风险评分模型进行验证。

结果

我们发现7个预后相关的lncRNA标记(OCIAD1-AS1

RP11-111J6.2

AC079354.3

RP11-553A21.3

RP11-598F7.3

CYP4F35P

RP11-113K21.4)可以预测膀胱癌患者的生存期。通过对这些lncRNA的特点、其靶基因的共表达和代谢通路分析进一步揭示了lncRNA在膀胱癌的发生和发展中发挥重要作用。此外

我们建立并验证了基于7个lncRNA分子标记的的膀胱癌患者预后预测风险评分模型。值得注意的是

我们首次发现了两种与肿瘤相关的反义lncRNA (OCIAD1-AS1和RP11-553A21.3)在膀胱癌预后中的潜在意义。

结论

这些lncRNA分子标记可作为治疗膀胱癌的潜在靶点

值得进一步进行功能验证研究。

Abstract

Objective

To explore novel long non-coding RNA (lncRNA) molecular markers related to bladder cancer prognosis and to construct a prognostic prediction model for bladder cancer patients.

Methods

LncRNA expression data of patients with bladder cancer were downloaded from TCGA database. Univariate Cox regression and likelihood-based survival analysis were used to discover prognosis related lncRNAs. Functional studies of prognosis related lncRNAs were conducted by co-expression analysis and pathway enrichment analysis. Multivariate Cox regression analysis was used to establish risk score model

and Receiver Operating Characteristic analysis was used to determine the optimal cut-off point of the model. The risk score model was validated through Kaplan Meier estimation method and log-rank test.

Results

Seven prognosis related lncRNAs (OCIAD1-AS1

RP11-111J6.2

AC079354.3

RP11-553A21.3

RP11-598F7.3

CYP4F35P and RP11-113K21.4) which can predict survival of bladder cancer patient were discovered. Co-expression analysis and pathway analysis of these novel lncRNA signature and their target genes further revealed that these lncRNAs play important roles in the occurrence and development of bladder cancer. Additionally

a seven-lncRNA signature based risk score model for prognostic prediction of bladder cancer patients was established and validated. Notably

we identified the potential significance of two tumor-related antisense lncRNAs (OCIAD1-AS1 and RP11-553A21.3) in the prognosis of bladder cancer.

Conclusion

Our results suggest that these lncRNA markers may serve as potential prognosis predictors for bladder cancer and deserve further functional verification studies.

关键词

Keywords

references

Witjes JA , Compérat Eva , Cowan NC , et al . EAU Guidelines on Muscle-invasive and Metastatic Bladder Cancer: Summary of the 2013 Guidelines . Eur Urol 2014 ; 65 ( 4 ): 778 - 92 . doi: 10.1016/j.eururo.2013.11.046 10.1016/j.eururo.2013.11.046 . DOI: 10.1016/j.eururo.2013.11.046 http://doi.org/10.1016/j.eururo.2013.11.046 http://dx.doi.org/10.1016/j.eururo.2013.11.046 http://dx.doi.org/10.1016/j.eururo.2013.11.046

Ghafouri-Fard S , Nekoohesh L , Motevaseli E . Bladder cancer biomarkers: review and update . Asian Pac J Cancer Prev 2014 ; 15 ( 6 ): 2395 - 403 . doi: 10.7314/APJCP.2014.15.6.2395 10.7314/APJCP.2014.15.6.2395 . https://www.ncbi.nlm.nih.gov/pubmed/24761840 https://www.ncbi.nlm.nih.gov/pubmed/24761840

Dunham I , Kundaje A , Aldred SF , et al . An integrated encyclopedia of DNA elements in the human genome . Nature 2012 ; 489 ( 7414 ): 57 - 74 . doi: 10.1038/nature11247 10.1038/nature11247 . DOI: 10.1038/nature11247 http://doi.org/10.1038/nature11247 https://www.ncbi.nlm.nih.gov/pubmed/22955616 https://www.ncbi.nlm.nih.gov/pubmed/22955616

Brosnan CA , Voinnet O . The long and the short of noncoding RNAs . Curr Opin Cell Biol 2009 ; 21 ( 3 ): 416 - 25 . doi: 10.1016/j.ceb.2009.04.001 10.1016/j.ceb.2009.04.001 . DOI: 10.1016/j.ceb.2009.04.001 http://doi.org/10.1016/j.ceb.2009.04.001 http://www.sciencedirect.com/science/article/pii/S0955067409000866 http://www.sciencedirect.com/science/article/pii/S0955067409000866

Mercer TR , Dinger ME , Mattick JS . Long non-coding RNAs: insights into functions . Nat Rev Genet 2009 ; 10 ( 3 ): 155 - 9 . doi: 10.1038/nrg2521 10.1038/nrg2521 . https://www.ncbi.nlm.nih.gov/pubmed/19188922 https://www.ncbi.nlm.nih.gov/pubmed/19188922

Wu Y , Zhang L , Wang Y , et al . Long noncoding RNA HOTAIR involvement in cancer . Tumor Biol 2014 ; 35 ( 10 ): 9531 - 8 . doi: 10.1007/s13277-014-2523-7 10.1007/s13277-014-2523-7 .

Zhu X , Tian X , Yu C , et al . A long non-coding RNA signature to improve prognosis prediction of gastric cancer . Mol Cancer 2016 ; 15 ( 1 ): 60 . doi: 10.1186/s12943-016-0544-0 10.1186/s12943-016-0544-0 . https://www.ncbi.nlm.nih.gov/pubmed/27647437 https://www.ncbi.nlm.nih.gov/pubmed/27647437

Meng J , Li P , Zhang Q , et al . A four-long non-coding RNA signature in predicting breast cancer survival . J Exp Clin Cancer Res 2014 ; 33 ( 1 ): 84 . doi: 10.1186/s13046-014-0084-7 10.1186/s13046-014-0084-7 .

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 . Sci Rep 2016 ; 6 ( 1 ): 1 - 10 . doi: 10.1038/srep27842 10.1038/srep27842 . DOI: 10.1038/s41598-016-0001-8 http://doi.org/10.1038/s41598-016-0001-8 https://www.ncbi.nlm.nih.gov/pubmed/28442746 https://www.ncbi.nlm.nih.gov/pubmed/28442746

Cao W , Liu J , 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 . Oral Oncol 2017 ; 65 : 94 - 101 . doi: 10.1016/j.oraloncology.2016.12.017 10.1016/j.oraloncology.2016.12.017 . DOI: 10.1016/j.oraloncology.2016.12.017 http://doi.org/10.1016/j.oraloncology.2016.12.017 https://www.ncbi.nlm.nih.gov/pubmed/28109476 https://www.ncbi.nlm.nih.gov/pubmed/28109476

Song J , Zhang W , Wang S , et al . A panel of 7 prognosis-related long non-coding RNAs to improve platinum-based chemoresistance prediction in ovarian cancer . Int J Oncol 2018 ; 53 ( 2 ): 866 - 76 . doi: 10.3892/ijo.2018.4403 10.3892/ijo.2018.4403 . DOI: 10.3892/ijo.2018.4403 http://doi.org/10.3892/ijo.2018.4403 https://www.ncbi.nlm.nih.gov/pubmed/29749482 https://www.ncbi.nlm.nih.gov/pubmed/29749482

Mao X , Qin X , Li L , et al . A 15-long non-coding RNA signature to improve prognosis prediction of cervical squamous cell carcinoma . Gynecol Oncol 2018 ; 149 ( 1 ): 181 - 7 . doi: 10.1016/j.ygyno.2017.12.011 10.1016/j.ygyno.2017.12.011 . DOI: 10.1016/j.ygyno.2017.12.011 http://doi.org/10.1016/j.ygyno.2017.12.011 https://www.ncbi.nlm.nih.gov/pubmed/29525275 https://www.ncbi.nlm.nih.gov/pubmed/29525275

Zhang Q , Su M , Lu G , et al . The complexity of bladder cancer: long noncoding RNAs are on the stage . Mol Cancer 2013 ; 12 ( 1 ): 101 . doi: 10.1186/1476-4598-12-101 10.1186/1476-4598-12-101 . DOI: 10.1186/1476-4598-12-101 http://doi.org/10.1186/1476-4598-12-101 https://www.ncbi.nlm.nih.gov/pubmed/24006935 https://www.ncbi.nlm.nih.gov/pubmed/24006935

Robertson AG , Kim J , Al-Ahmadie H , et al . Comprehensive molecular characterization of muscle-invasive bladder cancer cell 2017 ; 171 ( 3 ): 540 - 56 . e25 . doi: 10.1016/j.cell.2017.09.007 10.1016/j.cell.2017.09.007 .

Xue Y , Ma G , Zhang Z , et al . A novel antisense long noncoding RNA regulates the expression of MDC1 in bladder cancer . Oncotarget 2015 ; 6 ( 1 ): 484 - 93 . doi: 10.18632/oncotarget.2861 10.18632/oncotarget.2861 . https://www.ncbi.nlm.nih.gov/pubmed/25514464 https://www.ncbi.nlm.nih.gov/pubmed/25514464

Dudek AM , Boer SJ , Boon N , et al . Identification of long non-coding RNAs that stimulate cell survival in bladder cancer . Oncotarget 2017 ; 8 ( 21 ): 34442 - 52 . doi: 10.18632/oncotarget.16284 10.18632/oncotarget.16284 . DOI: 10.18632/oncotarget.16284 http://doi.org/10.18632/oncotarget.16284 https://www.ncbi.nlm.nih.gov/pubmed/28415801 https://www.ncbi.nlm.nih.gov/pubmed/28415801

Duan W , Du L , Jiang X , et al . Identification of a serum circulating lncRNA panel for the diagnosis and recurrence prediction of bladder cancer . Oncotarget 2016 ; 7 ( 48 ): 78850 - 8 . doi: 10.18632/oncotarget.12880 10.18632/oncotarget.12880 . https://www.ncbi.nlm.nih.gov/pubmed/27793008 https://www.ncbi.nlm.nih.gov/pubmed/27793008

Wang M , Niu Z , Zhou L , et al . Prognostic impact of cell division cycle zssociated 2 expression on pancreatic ductal adenocarcinom . Chin Med Sci J 2016 ; 31 ( 3 ): 149 - 54 . doi: 10.1016/S1001-9294(16)30043-8 10.1016/S1001-9294(16)30043-8 . DOI: 10.1016/s1001-9294(16)30043-8 http://doi.org/10.1016/s1001-9294(16)30043-8 https://www.ncbi.nlm.nih.gov/pubmed/27733221 https://www.ncbi.nlm.nih.gov/pubmed/27733221

Renaud G , Stenzel U , Maricic T , et al . DeML: robust demultiplexing of Illumina sequences using a likelihood-based approach . Bioinformatics 2015 ; 31 ( 5 ): 770 - 2 . doi: 10.1093/bioinformatics/btu719 10.1093/bioinformatics/btu719 . DOI: 10.1093/bioinformatics/btu719 http://doi.org/10.1093/bioinformatics/btu719 https://www.ncbi.nlm.nih.gov/pubmed/25359895 https://www.ncbi.nlm.nih.gov/pubmed/25359895

Chen EY , Tan CM , Kou Y , et al . Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool . BMC Bioinformatics 2013 ; 14 ( 1 ): 128 . doi: 10.1186/1471-2105-14-128 10.1186/1471-2105-14-128 . DOI: 10.1186/1471-2105-14-128 http://doi.org/10.1186/1471-2105-14-128 http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-14-128 http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-14-128

Kuleshov MV , Jones MR , Rouillard AD , et al . Enrichr: a comprehensive gene set enrichment analysis web server 2016 update . Nucleic Acids Res 2016 ; 44 ( W1 ): W90 - W7 . doi: 10.1093/nar/gkw377 10.1093/nar/gkw377 . https://www.ncbi.nlm.nih.gov/pubmed/27141961 https://www.ncbi.nlm.nih.gov/pubmed/27141961

Heagerty PJ , Lumley T , Pepe MS . Time-dependent ROC curves for censored survival data and a diagnostic marker . Biometrics 2000 ; 56 ( 2 ): 337 - 44 . doi: 10.1111/j.0006-341X.2000.00337.x 10.1111/j.0006-341X.2000.00337.x . https://www.ncbi.nlm.nih.gov/pubmed/10877287 https://www.ncbi.nlm.nih.gov/pubmed/10877287

Yokoyama M , Ichinoe M , Okina S , et al . CD109, a negative regulator of TGF-β signaling, is a putative risk marker in diffuse large B-cell lymphoma . Int J Hematol 2017 ; 105 ( 5 ): 614 - 22 . doi: 10.1007/s12185-016-2173-1 10.1007/s12185-016-2173-1 . DOI: 10.1007/s12185-016-2173-1 http://doi.org/10.1007/s12185-016-2173-1 https://www.ncbi.nlm.nih.gov/pubmed/28032275 https://www.ncbi.nlm.nih.gov/pubmed/28032275

Jia W , Ren C , Wang L , et al . CD109 is identified as a potential nasopharyngeal carcinoma biomarker using aptamer selected by cell-SELEX . Oncotarget 2016 ; 7 ( 34 ): 55328 - 42 . doi: 10.18632/oncotarget.10530 10.18632/oncotarget.10530 . https://www.ncbi.nlm.nih.gov/pubmed/27419372 https://www.ncbi.nlm.nih.gov/pubmed/27419372

Pelechano V , Steinmetz LM . Gene regulation by antisense transcription . Nat Rev Genetics 2013 ; 14 ( 12 ): 880 - 93 . doi: 10.1038/nrg3594 10.1038/nrg3594 . DOI: 10.1038/nrg3594 http://doi.org/10.1038/nrg3594 https://www.ncbi.nlm.nih.gov/pubmed/24217315 https://www.ncbi.nlm.nih.gov/pubmed/24217315

Sengupta S , Michener CM , Escobar P , et al . Ovarian cancer immuno-reactive antigen domain containing 1 (OCIAD1), a key player in ovarian cancer cell adhesion . Gynecol Oncol 2008 ; 109 ( 2 ): 226 - 33 . doi: 10.1016/j.ygyno.2007.12.024 10.1016/j.ygyno.2007.12.024 . DOI: 10.1016/j.ygyno.2007.12.024 http://doi.org/10.1016/j.ygyno.2007.12.024 https://www.ncbi.nlm.nih.gov/pubmed/18328549 https://www.ncbi.nlm.nih.gov/pubmed/18328549

Kornienko AE , Guenzl PM , Barlow DP , et al . Gene regulation by the act of long non-coding RNA transcription . BMC Biol 2013 ; 11 ( 1 ): 59 . doi: 10.1186/1741-7007-11-59 10.1186/1741-7007-11-59 . DOI: 10.1186/1741-7007-11-59 http://doi.org/10.1186/1741-7007-11-59 http://bmcbiol.biomedcentral.com/articles/10.1186/1741-7007-11-59 http://bmcbiol.biomedcentral.com/articles/10.1186/1741-7007-11-59

Liao Q , Liu C , Yuan X , et al . Large-scale prediction of long non-coding RNA functions in a coding-non-coding gene co-expression network . Nucleic Acids Res 2011 ; 39 ( 9 ): 3864 - 78 . doi: 10.1093/nar/gkq1348 10.1093/nar/gkq1348 . DOI: 10.1093/nar/gkq1348 http://doi.org/10.1093/nar/gkq1348 https://www.ncbi.nlm.nih.gov/pubmed/21247874 https://www.ncbi.nlm.nih.gov/pubmed/21247874

McLean GW , Carragher NO , Avizienyte E , et al . The role of focal-adhesion kinase in cancer—a new therapeutic opportunity . Nat Rev Cancer 2005 ; 5 ( 7 ): 505 - 15 . doi: 10.1038/nrc1647 10.1038/nrc1647 . DOI: 10.1038/nrc1647 http://doi.org/10.1038/nrc1647 https://www.ncbi.nlm.nih.gov/pubmed/16069815 https://www.ncbi.nlm.nih.gov/pubmed/16069815

Badylak SF . Xenogeneic extracellular matrix as a scaffold for tissue reconstruction . Transpl Immunol 2004 ; 12 ( 3-4 ): 367 - 77 . doi: 10.1016/j.trim.2003.12.016 10.1016/j.trim.2003.12.016 . DOI: 10.1016/j.trim.2003.12.016 http://doi.org/10.1016/j.trim.2003.12.016 https://www.ncbi.nlm.nih.gov/pubmed/15157928 https://www.ncbi.nlm.nih.gov/pubmed/15157928

Krupp M , Maass T , Marquardt JU , et al . The functional cancer map: a systems-level synopsis of genetic deregulation in cancer . BMC Med Genomics 2011 ; 4 ( 1 ): 53 . doi: 10.1186/1755-8794-4-53 10.1186/1755-8794-4-53 . DOI: 10.1186/1755-8794-4-53 http://doi.org/10.1186/1755-8794-4-53 http://bmcmedgenomics.biomedcentral.com/articles/10.1186/1755-8794-4-53 http://bmcmedgenomics.biomedcentral.com/articles/10.1186/1755-8794-4-53

Sasisekharan R , Shriver Z , Venkataraman G , et al . Roles of heparan-sulphate glycosaminoglycans in cancer . Nat Rev Cancer 2002 ; 2 ( 7 ): 521 - 8 . doi: 10.1038/nrc842 10.1038/nrc842 . DOI: 10.1038/nrc842 http://doi.org/10.1038/nrc842 https://www.ncbi.nlm.nih.gov/pubmed/12094238 https://www.ncbi.nlm.nih.gov/pubmed/12094238

Rangel MP , de Sá VK , Prieto T , et al . Biomolecular analysis of matrix proteoglycans as biomarkers in non small cell lung cancer . Glycoconj J 2018 ; 35 ( 2 ): 233 - 42 . doi: 10.1007/s10719-018-9815-x 10.1007/s10719-018-9815-x . DOI: 10.1007/s10719-018-9815-x http://doi.org/10.1007/s10719-018-9815-x https://www.ncbi.nlm.nih.gov/pubmed/29502190 https://www.ncbi.nlm.nih.gov/pubmed/29502190

Gao F , Alwhaibi A , Artham S , et al . Endothelial Akt1 loss promotes prostate cancer metastasis via β-catenin-regulated tight-junction protein turnover . Br J Cancer 2018 ; 118 ( 11 ): 1464 - 75 . doi: 10.1038/s41416-018-0110-1 10.1038/s41416-018-0110-1 . https://www.ncbi.nlm.nih.gov/pubmed/29755115 https://www.ncbi.nlm.nih.gov/pubmed/29755115

Runkle EA , Mu D . Tight junction proteins: from barrier to tumorigenesis . Cancer Let 2013 ; 337 ( 1 ): 41 - 8 . doi: 10.1016/j.canlet.2013.05.038 10.1016/j.canlet.2013.05.038 . DOI: 10.1016/j.canlet.2013.05.038 http://doi.org/10.1016/j.canlet.2013.05.038 https://linkinghub.elsevier.com/retrieve/pii/S0304383513004242 https://linkinghub.elsevier.com/retrieve/pii/S0304383513004242

Soini Y . Tight junctions in lung cancer and lung metastasis: a review . Int J Clin Exp Pathol 2012 ; 5 ( 2 ): 126 - 36 . https://www.ncbi.nlm.nih.gov/pubmed/22400072 https://www.ncbi.nlm.nih.gov/pubmed/22400072

Chen YZ , Xue JY , Chen CM , et al . PPAR signaling pathway may be an important predictor of breast cancer response to neoadjuvant chemotherapy . Cancer Chemother Pharmacol 2012 ; 70 ( 5 ): 637 - 44 . doi: 10.1007/s00280-012-1949-0 10.1007/s00280-012-1949-0 . https://www.ncbi.nlm.nih.gov/pubmed/22903535 https://www.ncbi.nlm.nih.gov/pubmed/22903535

Pazienza V , Vinciguerra M , Mazzoccoli G . PPARs signaling and cancer in the gastrointestinal system . PPAR Res 2012 ; 2012 : 560846 . doi: 10.1155/2012/560846 10.1155/2012/560846 . DOI: 10.1155/2012/560846 http://doi.org/10.1155/2012/560846 https://www.ncbi.nlm.nih.gov/pubmed/23028383 https://www.ncbi.nlm.nih.gov/pubmed/23028383

Fanale D , Amodeo V , Caruso S . The interplay between metabolism, PPAR signaling pathway, and cancer . PPAR Res 2017 ; 2017 : 1830626 . doi: 10.1155/2017/1830626 10.1155/2017/1830626 . DOI: 10.1155/2017/1830626 http://doi.org/10.1155/2017/1830626 https://www.ncbi.nlm.nih.gov/pubmed/28529521 https://www.ncbi.nlm.nih.gov/pubmed/28529521

0

浏览量

640

Downloads

0

CSCD

>

文章被引用时，请邮件提醒。

Submit

关联资源

相关文章

Cuproptosis-Related 4-Gene Risk Model for Predicting Immunotherapy Drug Response and Prognosis of Kidney Renal Clear Cell Carcinoma

Identifying and Validating a Novel miRNA-mRNA Regulatory Network Associated with Prognosis in Lung Adenocarcinoma

Postoperative Complications and Survival Analysis of Surgical Resection for Hilar Cholangiocarcinoma: A Retrospective Study of Fifty-Nine Consecutive Patients

Five-year Clinical Outcomes of CAD Patients Complicated with Diabetes after StentBoost-optimized Percutaneous Coronary Intervention

Prediction of Hidden Blood Loss During Posterior Spinal Surgery

相关作者

丁昊

吴鹏宇

辛子怡

李建新

曹现秀

马振海

郭金帅

陈天兵

相关机构

大连医科大学附属第二医院乳腺外科

平壤医科大学附属医院普外科

皖南医学院弋矶山医院中心实验室

皖南医学院重大疾病非编码RNA转化研究安徽普通高校重点实验室

Department of Hepatobiliary Surgery, Peking University People’s Hospital

⁰