A Novel Approach Based on Point Cut Set to Predict Associations of Diseases and LncRNAs

Author(s): Linai Kuang, Haochen Zhao, Lei Wang*, Zhanwei Xuan, Tingrui Pei.

Journal Name: Current Bioinformatics

Volume 14 , Issue 4 , 2019

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Graphical Abstract:


Background: In recent years, more evidence have progressively indicated that Long non-coding RNAs (lncRNAs) play vital roles in wide-ranging human diseases, which can serve as potential biomarkers and drug targets. Comparing with vast lncRNAs being found, the relationships between lncRNAs and diseases remain largely unknown.

Objective: The prediction of novel and potential associations between lncRNAs and diseases would contribute to dissect the complex mechanisms of disease pathogenesis.

Method: In this paper, a new computational method based on Point Cut Set is proposed to predict LncRNA-Disease Associations (PCSLDA) based on known lncRNA-disease associations. Compared with the existing state-of-the-art methods, the major novelty of PCSLDA lies in the incorporation of distance difference matrix and point cut set to set the distance correlation coefficient of nodes in the lncRNA-disease interaction network. Hence, PCSLDA can be applied to forecast potential lncRNAdisease associations while known disease-lncRNA associations are required only.

Results: Simulation results show that PCSLDA can significantly outperform previous state-of-the-art methods with reliable AUC of 0.8902 in the leave-one-out cross-validation and AUCs of 0.7634 and 0.8317 in 5-fold cross-validation and 10-fold cross-validation respectively. And additionally, 70% of top 10 predicted cancer-lncRNA associations can be confirmed.

Conclusion: It is anticipated that our proposed model can be a great addition to the biomedical research field.

Keywords: Point set cut, interactive network, LncRNA-disease associations, prediction, lncRNA similarity, disease similarity.

Leu K, Obermayer B, Rajamani S, Gerland U, Chen IA. The prebiotic evolutionary advantage of transferring genetic information from RNA to DNA. Nucleic Acids Res 2011; 39(18): 8135-47.
Wang L, Peng H, Zheng J. Similarities/Dissimilarities Analysis of Protein Sequences Based on Recurrence Quantification Analysis Current Bioinformatics 2015; 10(1): 112-9.
Lander ES, Linton LM, Birren B, et al. Initial sequencing and analysis of the human genome 2001; 409(6822): 860-921.
Batista PJ, Chang HY. Long noncoding RNAs: cellular address codes in development and disease. Cell 2013; 152(6): 1298-307.
Gibb EA, Brown CJ, Lam WL. The functional role of long non-coding RNA in human carcinomas. Mol Cancer 2011; 10(1): 38.
Geisler S, Coller J. RNA in unexpected places: long non-coding RNA functions in diverse cellular contexts. Nat Rev Mol Cell Biol 2013; 14(11): 699-712.
He X, Tan X, Wang X, et al. C-Myc-activated long noncoding RNA CCAT1 promotes colon cancer cell proliferation and invasion. Tumour Biol 2014; 35(12): 12181-8.
Gupta RA, Shah N, Wang KC, et al. Long non-coding RNA HOTAIR reprograms chromatin state to promote cancer metastasis. Nature 2010; 464(7291): 1071-6.
Chung S, Nakagawa H, Uemura M, et al. Association of a novel long non-coding RNA in 8q24 with prostate cancer susceptibility. Cancer Sci 2011; 102(1): 245-52.
Uchida S, Dimmeler S. Long noncoding RNAs in cardiovascular diseases. Circ Res 2015; 116(4): 737-50.
Congrains A, Kamide K, Oguro R, et al. Genetic variants at the 9p21 locus contribute to atherosclerosis through modulation of ANRIL and CDKN2A/B. Atherosclerosis 2012; 220(2): 449-55.
Huang WT, Guo XQ, Dai JP, et al. MicroRNA and lncRNA in Neurodegenerative Diseases. Prog Biochem Biophys 2010; 37(8): 826-33.
Johnson R. Long non-coding RNAs in Huntington’s disease neurodegeneration. Neurobiol Dis 2012; 46(2): 245-54.
Liu JY, Yao J, Li XM, et al. Pathogenic role of lncRNA-MALAT1 in endothelial cell dysfunction in diabetes mellitus. Cell Death Dis 2014; 5(10): e1506.
Wahlestedt C. Targeting long non-coding RNA to therapeutically upregulate gene expression. Nat Rev Drug Discov 2013; 12(6): 433-46.
Fenoglio C, Ridolfi E, Galimberti D, Scarpini E. An emerging role for long non-coding RNA dysregulation in neurological disorders. Int J Mol Sci 2013; 14(10): 20427-42.
Bu D, Yu K, Sun S, et al. NONCODE v3.0: integrative annotation of long noncoding RNAs. Nucleic Acids Res 2012; 40: D210-5.
Amaral PP, Clark MB, Gascoigne DK, Dinger ME, Mattick JS. lncRNAdb: a reference database for long noncoding RNAs. Nucleic Acids Res 2011; 39: D146-51.
Chen G, Wang Z, Wang D, et al. LncRNADisease: a database for long-non-coding RNA-associated diseases. Nucleic Acids Res 2013; 41: D983-6.
Peng H, Lan C, Zheng Y, Hutvagner G, Tao D, Li J. Cross disease analysis of co-functional microRNA pairs on a reconstructed network of disease-gene-microRNA tripartite. BMC Bioinformatics 2017; 18(1): 193.
Lan W, Li M, Zhao K, et al. LDAP: a web server for lncRNA-disease association prediction. Bioinformatics 2017; 33(3): 458-60.
Ping P, Zhu X, Wang L. Similarities/dissimilarities analysis of protein sequences based on pca-fft. J Biol Syst 2017; 25: 1-17.
Chen X, Yan GY. Novel human lncRNA-disease association inference based on lncRNA expression profiles. Bioinformatics 2013; 29(20): 2617-24.
Yang X, Gao L, Guo X, et al. A network based method for analysis of lncRNA-disease associations and prediction of lncRNAs implicated in diseases. PLoS One 2014; 9(1): e87797.
Sun J, Shi H, Wang Z, et al. Inferring novel lncRNA-disease associations based on a random walk model of a lncRNA functional similarity network. Mol Biosyst 2014; 10(8): 2074-81.
Lu C, Yang M, Luo F, et al. Prediction of lncRNA-disease associations based on inductive matrix completion. Bioinformatics 2018; 34(19): 3357-64.
Zhang L, Deng Q, Su Y, et al. A Box-Covering-Based Routing Algorithm for Large-Scale SDNs. IEEE Access 2017; 5(99): 4048-56.
Gunia S, Kakies C, Erbersdobler A, Hakenberg OW, Koch S, May M. Expression of p53, p21 and cyclin D1 in penile cancer: p53 predicts poor prognosis. J Clin Pathol 2012; 65(3): 232-6.
Ruprecht B, Zaal EA, Zecha J, et al. Lapatinib Resistance in Breast Cancer Cells Is Accompanied by Phosphorylation-Mediated Reprogramming of Glycolysis. Cancer Res 2017; 77(8): 1842-53.
Barton MK. Local consolidative therapy may be beneficial in patients with oligometastatic non-small cell lung cancer. CA Cancer J Clin 2017; 67(2): 89-90.
Aarnio M, Sankila R, Pukkala E, et al. Cancer risk in mutation carriers of DNA-mismatch-repair genes. Int J Cancer 1999; 81(2): 214-8.
Xu S, Sui S, Zhang J, et al. Downregulation of long noncoding RNA MALAT1 induces epithelial-to-mesenchymal transition via the PI3K-AKT pathway in breast cancer. Int J Clin Exp Pathol 2015; 8(5): 4881-91.
Hu T, Lu YR. BCYRN1, a c-MYC-activated long non-coding RNA, regulates cell metastasis of non-small-cell lung cancer. Cancer Cell Int 2015; 15(1): 36.
Zhu M, Chen Q, Liu X, et al. lncRNA H19/miR-675 axis represses prostate cancer metastasis by targeting TGFBI. FEBS J 2014; 281(16): 3766-75.
Cremers RG, Eeles RA, Bancroft EK, et al. The role of the prostate cancer gene 3 urine test in addition to serum prostate-specific antigen level in prostate cancer screening among breast cancer, early-onset gene mutation carriers. Urol Oncol 2015; 33(5): 202.e19-28.
Enciso-Mora V, Hosking FJ, Houlston RS. Risk of breast and prostate cancer is not associated with increased homozygosity in outbred populations. Eur J Hum Genet 2010; 18(8): 909-14.
Nanchari SR, Cingeetham A, Meka P, et al. Rrp1B gene polymorphism (1307T>C) in metastatic progression of breast cancer. Tumour Biol 2015; 36(2): 615-21.
Chen X. Predicting lncRNA-disease associations and constructing lncRNA functional similarity network based on the information of miRNA. Sci Rep 2015; 5: 13186.
Wang Y, Chen L, Chen B, et al. Mammalian ncRNA-disease repository: a global view of ncRNA-mediated disease network. Cell Death Dis 2013; 4(8): e765.

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Article Details

Year: 2019
Page: [333 - 343]
Pages: 11
DOI: 10.2174/1574893613666181026122045
Price: $58

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