Generic placeholder image

Current Medicinal Chemistry

Editor-in-Chief

ISSN (Print): 0929-8673
ISSN (Online): 1875-533X

Review Article

Non-coding RNAs as Novel Biomarkers in Cancer Drug Resistance

Author(s): Haixiu Yang , Changlu Qi , Boyan Li and Liang Cheng *

Volume 29, Issue 5, 2022

Published on: 26 January, 2022

Page: [837 - 848] Pages: 12

DOI: 10.2174/0929867328666210804090644

Price: $65

Abstract

Chemotherapy is often the primary and most effective anticancer treatment; however, drug resistance remains a major obstacle to it being curative. Recent studies have demonstrated that non-coding RNAs (ncRNAs), especially microRNAs and long non-coding RNAs, are involved in drug resistance of tumor cells in many ways, such as modulation of apoptosis, drug efflux and metabolism, epithelial-to-mesenchymal transition, DNA repair, and cell cycle progression. Exploring the relationships between ncRNAs and drug resistance will not only contribute to our understanding of the mechanisms of drug resistance and provide ncRNA biomarkers of chemoresistance, but will also help realize personalized anticancer treatment regimens. Due to the high cost and low efficiency of biological experimentation, many researchers have opted to use computational methods to identify ncRNA biomarkers associated with drug resistance. In this review, we summarize recent discoveries related to ncRNA-mediated drug resistance and highlight the computational methods and resources available for ncRNA biomarkers involved in chemoresistance.

Keywords: ncRNA, miRNA, lncRNA, drug resistance, computational method, database.

[1]
Housman, G.; Byler, S.; Heerboth, S.; Lapinska, K.; Longacre, M.; Snyder, N.; Sarkar, S. Drug resistance in cancer: an overview. Cancers (Basel), 2014, 6(3), 1769-1792.
[http://dx.doi.org/10.3390/cancers6031769] [PMID: 25198391]
[2]
Zhang, Z.M.; Tan, J.X.; Wang, F.; Dao, F.Y.; Zhang, Z.Y.; Lin, H. Early diagnosis of hepatocellular carcinoma using machine learning method. Front. Bioeng. Biotechnol., 2020, 8, 254.
[http://dx.doi.org/10.3389/fbioe.2020.00254] [PMID: 32292778]
[3]
Garnett, M.J.; Edelman, E.J.; Heidorn, S.J.; Greenman, C.D.; Dastur, A.; Lau, K.W.; Greninger, P.; Thompson, I.R.; Luo, X.; Soares, J.; Liu, Q.; Iorio, F.; Surdez, D.; Chen, L.; Milano, R.J.; Bignell, G.R.; Tam, A.T.; Davies, H.; Stevenson, J.A.; Barthorpe, S.; Lutz, S.R.; Kogera, F.; Lawrence, K.; McLaren-Douglas, A.; Mitropoulos, X.; Mironenko, T.; Thi, H.; Richardson, L.; Zhou, W.; Jewitt, F.; Zhang, T.; O’Brien, P.; Boisvert, J.L.; Price, S.; Hur, W.; Yang, W.; Deng, X.; Butler, A.; Choi, H.G.; Chang, J.W.; Baselga, J.; Stamenkovic, I.; Engelman, J.A.; Sharma, S.V.; Delattre, O.; Saez-Rodriguez, J.; Gray, N.S.; Settleman, J.; Futreal, P.A.; Haber, D.A.; Stratton, M.R.; Ramaswamy, S.; McDermott, U.; Benes, C.H. Systematic identification of genomic markers of drug sensitivity in cancer cells. Nature, 2012, 483(7391), 570-575.
[http://dx.doi.org/10.1038/nature11005] [PMID: 22460902]
[4]
Yang, W.; Soares, J.; Greninger, P.; Edelman, E.J.; Lightfoot, H.; Forbes, S.; Bindal, N.; Beare, D.; Smith, J.A.; Thompson, I.R.; Ramaswamy, S.; Futreal, P.A.; Haber, D.A.; Stratton, M.R.; Benes, C.; McDermott, U.; Garnett, M.J. Genomics of drug sensitivity in cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells. Nucleic Acids Res., 2013, 41(Database issue), D955-D961.
[PMID: 23180760]
[5]
Lin, M.; Li, X.; Guo, H.; Ji, F.; Ye, L.; Ma, X.; Cheng, W. Identification of bone metastasis-associated genes of gastric cancer by genome-wide transcriptional profiling. Curr. Bioinform., 2019, 14(1), 62-69.
[http://dx.doi.org/10.2174/1574893612666171121154017]
[6]
Liang, C.; Changlu, Q.; He, Z.; Tongze, F.; Xue, Z. gutMDisorder: a comprehensive database for dysbiosis of the gut microbiota in disorders and interventions. Nucleic Acids Res., 2020, 48(D1), D554-D560.
[7]
Dong, Y-M.; Bi, J-H.; He, Q-E.; Song, K. ESDA: an improved approach to accurately identify human snornas for precision cancer therapy. Curr. Bioinform., 2020, 15(1), 34-40.
[http://dx.doi.org/10.2174/1574893614666190424162230]
[8]
Geeleher, P.; Cox, N.J.; Huang, R.S. Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines. Genome Biol., 2014, 15(3), R47.
[http://dx.doi.org/10.1186/gb-2014-15-3-r47] [PMID: 24580837]
[9]
Rees, M.G.; Seashore-Ludlow, B.; Cheah, J.H.; Adams, D.J.; Price, E.V.; Gill, S.; Javaid, S.; Coletti, M.E.; Jones, V.L.; Bodycombe, N.E.; Soule, C.K.; Alexander, B.; Li, A.; Montgomery, P.; Kotz, J.D.; Hon, C.S.; Munoz, B.; Liefeld, T.; Dančík, V.; Haber, D.A.; Clish, C.B.; Bittker, J.A.; Palmer, M.; Wagner, B.K.; Clemons, P.A.; Shamji, A.F.; Schreiber, S.L. Correlating chemical sensitivity and basal gene expression reveals mechanism of action. Nat. Chem. Biol., 2016, 12(2), 109-116.
[http://dx.doi.org/10.1038/nchembio.1986] [PMID: 26656090]
[10]
Yang, L.; Wang, S.; Zhang, Q.; Pan, Y.; Lv, Y.; Chen, X.; Zuo, Y.; Hao, D. Clinical significance of the immune microenvironment in ovarian cancer patients. Mol. Omics, 2018, 14(5), 341-351.
[http://dx.doi.org/10.1039/C8MO00128F] [PMID: 30129640]
[11]
Wang, S.; Zhang, Q.; Yu, C.; Cao, Y.; Zuo, Y.; Yang, L. Immune cell infiltration-based signature for prognosis and immunogenomic analysis in breast cancer. Brief. Bioinform., 2021, 22(2), 2020-2031.
[http://dx.doi.org/10.1093/bib/bbaa311] [PMID: 32141494]
[12]
Yang, L.; Lv, Y.; Wang, S.; Zhang, Q.; Pan, Y.; Su, D.; Lu, Q.; Zuo, Y. Identifying FL11 subtype by characterizing tumor immune microenvironment in prostate adenocarcinoma via Chou’s 5-steps rule. Genomics, 2020, 112(2), 1500-1515.
[http://dx.doi.org/10.1016/j.ygeno.2019.08.021] [PMID: 31472243]
[13]
Zhao, X.; Chen, L.; Guo, Z-H.; Liu, T. Predicting drug side effects with compact integration of heterogeneous networks. Curr. Bioinform., 2019, 14(8), 709-720.
[http://dx.doi.org/10.2174/1574893614666190220114644]
[14]
Emad, A.; Cairns, J.; Kalari, K.R.; Wang, L.; Sinha, S. Knowledge-guided gene prioritization reveals new insights into the mechanisms of chemoresistance. Genome Biol., 2017, 18(1), 153.
[http://dx.doi.org/10.1186/s13059-017-1282-3] [PMID: 28800781]
[15]
Hombach, S.; Kretz, M. Non-coding RNAs: classification, biology and functioning. Adv. Exp. Med. Biol., 2016, 937, 3-17.
[http://dx.doi.org/10.1007/978-3-319-42059-2_1] [PMID: 27573892]
[16]
Cheng, L.; Hu, Y.; Sun, J.; Zhou, M.; Jiang, Q. DincRNA: a comprehensive web-based bioinformatics toolkit for exploring disease associations and ncRNA function. Bioinformatics, 2018, 34(11), 1953-1956.
[http://dx.doi.org/10.1093/bioinformatics/bty002] [PMID: 29365045]
[17]
Esteller, M. Non-coding RNAs in human disease. Nat. Rev. Genet., 2011, 12(12), 861-874.
[http://dx.doi.org/10.1038/nrg3074] [PMID: 22094949]
[18]
Zeng, W.; Wang, F.; Ma, Y.; Liang, X.; Chen, P. Dysfunctional mechanism of liver cancer mediated by transcription factor and non-coding RNA. Curr. Bioinform., 2019, 14(2), 100-107.
[http://dx.doi.org/10.2174/1574893614666181119121916]
[19]
Cheng, L.; Zhao, H.; Wang, P.; Zhou, W.; Luo, M.; Li, T.; Han, J.; Liu, S.; Jiang, Q. Computational methods for identifying similar diseases. Mol. Ther. Nucleic Acids, 2019, 18, 590-604.
[http://dx.doi.org/10.1016/j.omtn.2019.09.019] [PMID: 31678735]
[20]
Ayers, D.; Vandesompele, J. Influence of microRNAs and long non-coding RNAs in cancer chemoresistance. Genes (Basel), 2017, 8(3)E95
[http://dx.doi.org/10.3390/genes8030095] [PMID: 28273813]
[21]
Wang, W.T.; Han, C.; Sun, Y.M.; Chen, T.Q.; Chen, Y.Q. Noncoding RNAs in cancer therapy resistance and targeted drug development. J. Hematol. Oncol., 2019, 12(1), 55.
[http://dx.doi.org/10.1186/s13045-019-0748-z] [PMID: 31174564]
[22]
Wang, L.; Xuan, Z.; Zhou, S.; Kuang, L.; Pei, T. A novel model for predicting lncRNA-disease associations based on the LncRNA-MiRNA-disease interactive network. Curr. Bioinform., 2019, 14(3), 269-278.
[http://dx.doi.org/10.2174/1574893613666180703105258]
[23]
Cheng, L. Computational and biological methods for gene therapy. Curr. Gene Ther., 2019, 19(4), 210-210.
[http://dx.doi.org/10.2174/156652321904191022113307] [PMID: 31762421]
[24]
Khan, A.; Zahra, A.; Mumtaz, S.; Fatmi, M.Q.; Khan, M.J. Integrated in-silico analysis to study the role of microRNAs in the detection of chronic kidney diseases. Curr. Bioinform., 2020, 15(2), 144-154.
[http://dx.doi.org/10.2174/1574893614666190923115032]
[25]
Xu, G.; Li, X.; Yang, D.; Wu, S.; Wu, D.; Yan, M. Bioinformatics study of RNA interference on the effect of HIF-1 alpha on apelin expression in nasopharyngeal carcinoma cells. Curr. Bioinform., 2019, 14(5), 386-390.
[http://dx.doi.org/10.2174/1574893614666190109155825]
[26]
Paraskevopoulou, M.D.; Georgakilas, G.; Kostoulas, N.; Vlachos, I.S.; Vergoulis, T.; Reczko, M.; Filippidis, C.; Dalamagas, T.; Hatzigeorgiou, A.G. DIANA-microT web server v5.0: service integration into miRNA functional analysis workflows. Nucleic Acids Res,, 2013, 41(Web Server issue), W169-W173.
[27]
Zhao, T.; Hu, Y.; Peng, J.; Cheng, L. DeepLGP: a novel deep learning method for prioritizing lncRNA target genes. Bioinformatics, 2020, 36(16), 4466-4472.
[http://dx.doi.org/10.1093/bioinformatics/btaa428] [PMID: 32467970]
[28]
Hanna, J.; Hossain, G.S.; Kocerha, J. The potential for microRNA therapeutics and clinical research. Front. Genet., 2019, 10, 478.
[http://dx.doi.org/10.3389/fgene.2019.00478] [PMID: 31156715]
[29]
Deng, H.; Zhang, J.; Shi, J.; Guo, Z.; He, C.; Ding, L.; Tang, J.H.; Hou, Y. Role of long non-coding RNA in tumor drug resistance. Tumour Biol., 2016, 37(9), 11623-11631.
[http://dx.doi.org/10.1007/s13277-016-5125-8] [PMID: 27380056]
[30]
Qu, Y.; Tan, H.Y.; Chan, Y.T.; Jiang, H.; Wang, N.; Wang, D. The functional role of long noncoding RNA in resistance to anticancer treatment. Ther. Adv. Med. Oncol., 2020, 121758835920927850
[http://dx.doi.org/10.1177/1758835920927850] [PMID: 32536982]
[31]
Chowdhury, M.R.; Basak, J.; Bahadur, R.P. Elucidating the functional role of predicted miRNAs in post-transcriptional gene regulation along with symbiosis in medicago truncatula. Curr. Bioinform., 2020, 15(2), 108-120.
[http://dx.doi.org/10.2174/1574893614666191003114202]
[32]
Zhao, X.; Jiao, Q.; Li, H.; Wu, Y.; Wang, H.; Huang, S.; Wang, G. ECFS-DEA: an ensemble classifier-based feature selection for differential expression analysis on expression profiles. BMC Bioinformatics, 2020, 21(1), 43.
[http://dx.doi.org/10.1186/s12859-020-3388-y] [PMID: 32024464]
[33]
Wahid, F.; Shehzad, A.; Khan, T.; Kim, Y.Y. MicroRNAs: synthesis, mechanism, function, and recent clinical trials. Biochim. Biophys. Acta, 2010, 1803(11), 1231-1243.
[http://dx.doi.org/10.1016/j.bbamcr.2010.06.013] [PMID: 20619301]
[34]
Jeyaram, C.; Philip, M.; Perumal, R.C.; Benny, J.; Jayakumari, J.M.; Ramasamy, M.S. A computational approach to identify novel potential precursor mirnas and their targets from hepatocellular carcinoma cells. Curr. Bioinform., 2019, 14(1), 24-32.
[http://dx.doi.org/10.2174/1574893613666180413150351]
[35]
Cheng, L.; Hu, Y. Human disease system biology. Curr. Gene Ther., 2018, 18(5), 255-256.
[http://dx.doi.org/10.2174/1566523218666181010101114] [PMID: 30306867]
[36]
Kothandan, R.; Biswas, S. Comparison of kernel and decision tree-based algorithms for prediction of micrornas associated with cancer. Curr. Bioinform., 2016, 11(1), 143-151.
[http://dx.doi.org/10.2174/1574893611666151120102307]
[37]
Chowdhury, F.T.; Shohan, M.U.S.; Islam, T.; Mimu, T.T.; Palit, P. A therapeutic approach against leishmania donovani by predicting RNAi molecules against the surface protein, gp63. Curr. Bioinform., 2019, 14(6), 541-550.
[http://dx.doi.org/10.2174/1574893613666180828095737]
[38]
Pei, K.; Zhu, J.J.; Wang, C.E.; Xie, Q.L.; Guo, J.Y. MicroRNA-185-5p modulates chemosensitivity of human non-small cell lung cancer to cisplatin via targeting ABCC1. Eur. Rev. Med. Pharmacol. Sci., 2016, 20(22), 4697-4704.
[PMID: 27906433]
[39]
Zhang, P.; Zhu, J.; Zheng, Y.; Zhang, H.; Sun, H.; Gao, S. miRNA-574-3p inhibits metastasis and chemoresistance of epithelial ovarian cancer (EOC) by negatively regulating epidermal growth factor receptor (EGFR). Am. J. Transl. Res., 2019, 11(7), 4151-4165.
[PMID: 31396325]
[40]
Tsuchiya, Y.; Nakajima, M.; Takagi, S.; Taniya, T.; Yokoi, T. MicroRNA regulates the expression of human cytochrome P450 1B1. Cancer Res., 2006, 66(18), 9090-9098.
[http://dx.doi.org/10.1158/0008-5472.CAN-06-1403] [PMID: 16982751]
[41]
Zhong, S.; Li, W.; Chen, Z.; Xu, J.; Zhao, J. MiR-222 and miR-29a contribute to the drug-resistance of breast cancer cells. Gene, 2013, 531(1), 8-14.
[http://dx.doi.org/10.1016/j.gene.2013.08.062] [PMID: 23994196]
[42]
Shen, H.; Wang, D.; Li, L.; Yang, S.; Chen, X.; Zhou, S.; Zhong, S.; Zhao, J.; Tang, J. MiR-222 promotes drug-resistance of breast cancer cells to adriamycin via modulation of PTEN/Akt/FOXO1 pathway. Gene, 2017, 596, 110-118.
[http://dx.doi.org/10.1016/j.gene.2016.10.016] [PMID: 27746366]
[43]
Mercer, T.R.; Dinger, M.E.; Mattick, J.S. Long non-coding RNAs: insights into functions. Nat. Rev. Genet., 2009, 10(3), 155-159.
[http://dx.doi.org/10.1038/nrg2521] [PMID: 19188922]
[44]
Kuang, L.; Zhao, H.; Wang, L.; Xuan, Z.; Pei, T. A novel approach based on point cut set to predict associations of diseases and lncRNAs. Curr. Bioinform., 2019, 14(4), 333-343.
[http://dx.doi.org/10.2174/1574893613666181026122045]
[45]
Yang, Q.; Wu, J.; Zhao, J.; Xu, T.; Han, P.; Song, X. The expression profiles of lncrnas and their regulatory network during Smek1/2 knockout mouse neural stem cells differentiation. Curr. Bioinform., 2020, 15(1), 77-88.
[http://dx.doi.org/10.2174/1574893614666190308160507]
[46]
Wong, F.Y.; Liem, N.; Xie, C.; Yan, F.L.; Wong, W.C.; Wang, L.; Yong, W.P. Combination therapy with gossypol reveals synergism against gemcitabine resistance in cancer cells with high BCL-2 expression. PLoS One, 2012, 7(12)e50786
[http://dx.doi.org/10.1371/journal.pone.0050786] [PMID: 23226540]
[47]
Gu, M.; Zheng, W.; Zhang, M.; Dong, X.; Zhao, Y.; Wang, S.; Jiang, H.; Zheng, X. LncRNA NONHSAT141924 promotes paclitaxel chemotherapy resistance through p-CREB/Bcl-2 apoptosis signaling pathway in breast cancer. J. Cancer, 2020, 11(12), 3645-3654.
[http://dx.doi.org/10.7150/jca.39463] [PMID: 32284761]
[48]
Breier, A.; Gibalova, L.; Seres, M.; Barancik, M.; Sulova, Z. New insight into p-glycoprotein as a drug target. Anticancer. Agents Med. Chem., 2013, 13(1), 159-170.
[http://dx.doi.org/10.2174/187152013804487380] [PMID: 22931413]
[49]
Kun-Peng, Z.; Xiao-Long, M.; Chun-Lin, Z. LncRNA FENDRR sensitizes doxorubicin-resistance of osteosarcoma cells through down-regulating ABCB1 and ABCC1. Oncotarget, 2017, 8(42), 71881-71893.
[http://dx.doi.org/10.18632/oncotarget.17985] [PMID: 29069754]
[50]
Galluzzi, L.; Senovilla, L.; Vitale, I.; Michels, J.; Martins, I.; Kepp, O.; Castedo, M.; Kroemer, G. Molecular mechanisms of cisplatin resistance. Oncogene, 2012, 31(15), 1869-1883.
[http://dx.doi.org/10.1038/onc.2011.384] [PMID: 21892204]
[51]
Liu, Z.; Sun, M.; Lu, K.; Liu, J.; Zhang, M.; Wu, W.; De, W.; Wang, Z.; Wang, R. The long noncoding RNA HOTAIR contributes to cisplatin resistance of human lung adenocarcinoma cells via downregualtion of p21(WAF1/CIP1) expression. PLoS One, 2013, 8(10)e77293
[http://dx.doi.org/10.1371/journal.pone.0077293] [PMID: 24155936]
[52]
Radisky, D.C. Epithelial-mesenchymal transition. J. Cell Sci., 2005, 118(Pt 19), 4325-4326.
[http://dx.doi.org/10.1242/jcs.02552] [PMID: 16179603]
[53]
Gao, H.; Hao, G.; Sun, Y.; Li, L.; Wang, Y. Long noncoding RNA H19 mediated the chemosensitivity of breast cancer cells via Wnt pathway and EMT process. OncoTargets Ther., 2018, 11, 8001-8012.
[http://dx.doi.org/10.2147/OTT.S172379] [PMID: 30519041]
[54]
Hu, B.; Zheng, L.; Long, C.; Song, M.; Li, T.; Yang, L.; Zuo, Y. EmExplorer: a database for exploring time activation of gene expression in mammalian embryos. Open Biol., 2019, 9(6)190054
[http://dx.doi.org/10.1098/rsob.190054] [PMID: 31164042]
[55]
Liu, Y.; Wang, M.; Xi, J.; Luo, F.; Li, A. PTM-ssMP: a web server for predicting different types of post-translational modification sites using novel site-specific modification profile. Int. J. Biol. Sci., 2018, 14(8), 946-956.
[http://dx.doi.org/10.7150/ijbs.24121] [PMID: 29989096]
[56]
Chen, W.X.; Xu, L.Y.; Qian, Q.; He, X.; Peng, W.T.; Zhu, Y.L.; Cheng, L. Analysis of miRNA signature differentially expressed in exosomes from adriamycin-resistant and parental human breast cancer cells. Biosci. Rep., 2018, 38(6)BSR20181090
[http://dx.doi.org/10.1042/BSR20181090] [PMID: 30201690]
[57]
Xue, W.; Li, L.; Tian, X.; Fan, Z.; Yue, Y.; Zhang, C.; Ding, X.; Song, X.; Ma, B.; Zhai, Y.; Lu, J.; Kan, Q.; Zhao, J. Integrated analysis profiles of long non-coding RNAs reveal potential biomarkers of drug resistance in lung cancer. Oncotarget, 2017, 8(38), 62868-62879.
[http://dx.doi.org/10.18632/oncotarget.16444] [PMID: 28968955]
[58]
Chen, Q.; Yang, H.; Zhu, X.; Xiong, S.; Chi, H.; Xu, W. Integrative analysis of the doxorubicin-associated LncRNA-mRNA network identifies chemoresistance-associated lnc-TRDMT1-5 as a biomarker of breast cancer progression. Front. Genet., 2020, 11, 566.
[http://dx.doi.org/10.3389/fgene.2020.00566] [PMID: 32547604]
[59]
Hu, J.; Xu, Y.; Cai, S. Specific microRNAs as novel biomarkers for combination chemotherapy resistance detection of colon adenocarcinoma. Eur. J. Med. Res., 2015, 20, 95.
[http://dx.doi.org/10.1186/s40001-015-0183-8] [PMID: 26626874]
[60]
Sun, Q.L.; Zhao, C.P.; Wang, T.Y.; Hao, X.B.; Wang, X.Y.; Zhang, X.; Li, Y.C. Expression profile analysis of long non-coding RNA associated with vincristine resistance in colon cancer cells by next-generation sequencing. Gene, 2015, 572(1), 79-86.
[http://dx.doi.org/10.1016/j.gene.2015.06.087] [PMID: 26164760]
[61]
Islam, M.S.; Hoque, M.A.; Islam, M.S.; Ali, M.; Hossen, M.B.; Binyamin, M.; Merican, A.F.; Akazawa, K.; Kumar, N.; Sugimoto, M. Mining gene expression profile with missing values: a integration of kernel PCA and robust singular values decomposition. Curr. Bioinform., 2019, 14(1), 78-89.
[http://dx.doi.org/10.2174/1574893613666180413151654]
[62]
Varmeh, S.; Vanden Borre, P.; Gunda, V.; Brauner, E.; Holm, T.; Wang, Y.; Sadreyev, R.I.; Parangi, S. Genome-wide analysis of differentially expressed miRNA in PLX4720-resistant and parental human thyroid cancer cell lines. Surgery, 2016, 159(1), 152-162.
[http://dx.doi.org/10.1016/j.surg.2015.06.046] [PMID: 26456124]
[63]
Yan, J.; Chen, D.; Chen, X.; Sun, X.; Dong, Q.; Du, Z.; Wang, T. Identification of imatinib-resistant long non-coding RNAs in gastrointestinal stromal tumors. Oncol. Lett., 2019, 17(2), 2283-2295.
[PMID: 30675294]
[64]
Jin, L.; Zhang, N.; Zhang, Q.; Ding, G.; Yang, Z.; Zhang, Z. Serum microRNAs as potential new biomarkers for cisplatin resistance in gastric cancer patients. PeerJ, 2020, 8e8943
[http://dx.doi.org/10.7717/peerj.8943] [PMID: 32328349]
[65]
Xu, J.; Wu, J.; Fu, C.; Teng, F.; Liu, S.; Dai, C.; Shen, R.; Jia, X. Multidrug resistant lncRNA profile in chemotherapeutic sensitive and resistant ovarian cancer cells. J. Cell. Physiol., 2018, 233(6), 5034-5043.
[http://dx.doi.org/10.1002/jcp.26369] [PMID: 29219179]
[66]
Feng, Y.; Hang, W.; Sang, Z.; Li, S.; Xu, W.; Miao, Y.; Xi, X.; Huang, Q. Identification of exosomal and non exosomal microRNAs associated with the drug resistance of ovarian cancer. Mol. Med. Rep., 2019, 19(5), 3376-3392.
[http://dx.doi.org/10.3892/mmr.2019.10008] [PMID: 30864705]
[67]
Cilek, E.E.; Ozturk, H.; Gur Dedeoglu, B. Construction of miRNA-miRNA networks revealing the complexity of miRNA-mediated mechanisms in trastuzumab treated breast cancer cell lines. PLoS One, 2017, 12(10)e0185558
[http://dx.doi.org/10.1371/journal.pone.0185558] [PMID: 28981542]
[68]
Fang, L.; Wang, H.; Li, P. Systematic analysis reveals a lncRNA-mRNA co-expression network associated with platinum resistance in high-grade serous ovarian cancer. Invest. New Drugs, 2018, 36(2), 187-194.
[http://dx.doi.org/10.1007/s10637-017-0523-3] [PMID: 29082457]
[69]
Dai, E.; Wang, J.; Yang, F.; Zhou, X.; Song, Q.; Wang, S.; Yu, X.; Liu, D.; Yang, Q.; Dai, H.; Jiang, W.; Ling, H. Accurate prediction and elucidation of drug resistance based on the robust and reproducible chemoresponse communities. Int. J. Cancer, 2018, 142(7), 1427-1439.
[http://dx.doi.org/10.1002/ijc.31158] [PMID: 29143332]
[70]
Qi, X.; Yu, C.; Wang, Y.; Lin, Y.; Shen, B. Network vulnerability-based and knowledge-guided identification of microRNA biomarkers indicating platinum resistance in high-grade serous ovarian cancer. Clin. Transl. Med., 2019, 8(1), 28.
[http://dx.doi.org/10.1186/s40169-019-0245-6] [PMID: 31664600]
[71]
Huang, Y.E.; Zhou, S.; Liu, H.; Zhou, X.; Yuan, M.; Hou, F.; Wang, L.; Jiang, W. Identification of drug resistance associated ncRNAs based on comprehensive heterogeneous network. Life Sci., 2020, 243117256
[http://dx.doi.org/10.1016/j.lfs.2020.117256] [PMID: 31923419]
[72]
Liu, H.; Wang, S.; Zhou, S.; Meng, Q.; Ma, X.; Song, X.; Wang, L.; Jiang, W. Drug Resistance-related competing interactions of lncRNA and mRNA across 19 cancer types. Mol. Ther. Nucleic Acids, 2019, 16, 442-451.
[http://dx.doi.org/10.1016/j.omtn.2019.03.011] [PMID: 31048183]
[73]
Zhu, K.P.; Zhang, C.L.; Ma, X.L.; Hu, J.P.; Cai, T.; Zhang, L. Analyzing the interactions of mRNAs and ncRNAs to predict competing endogenous RNA networks in osteosarcoma chemo-resistance. Mol. Ther., 2019, 27(3), 518-530.
[74]
Kong, X.; Hu, S.; Yuan, Y.; Du, Y.; Zhu, Z.; Song, Z.; Lu, S.; Zhao, C.; Yan, D. Analysis of lncRNA, miRNA and mRNA-associated ceRNA networks and identification of potential drug targets for drug-resistant non-small cell lung cancer. J. Cancer, 2020, 11(11), 3357-3368.
[http://dx.doi.org/10.7150/jca.40729] [PMID: 32231742]
[75]
Zhang, Y.; Li, X.; Zhou, D.; Zhi, H.; Wang, P.; Gao, Y.; Guo, M.; Yue, M.; Wang, Y.; Shen, W.; Ning, S.; Li, Y.; Li, X. Inferences of individual drug responses across diverse cancer types using a novel competing endogenous RNA network. Mol. Oncol., 2018, 12(9), 1429-1446.
[http://dx.doi.org/10.1002/1878-0261.12181] [PMID: 29464864]
[76]
Bester, A.C.; Lee, J.D.; Chavez, A.; Lee, Y.R.; Nachmani, D.; Vora, S.; Victor, J.; Sauvageau, M.; Monteleone, E.; Rinn, J.L.; Provero, P.; Church, G.M.; Clohessy, J.G.; Pandolfi, P.P. An integrated genome-wide CRISPRa approach to functionalize lncRNAs in drug resistance. Cell, 2018, 173(3), 649-664.
[http://dx.doi.org/10.1016/j.cell.2018.03.052] [PMID: 29677511]
[77]
Chen, H.; Zhang, D.; Zhang, G.; Li, X.; Liang, Y.; Kasukurthi, M.V.; Li, S.; Borchert, G.M.; Huang, J. A semantics-oriented computational approach to investigate microRNA regulation on glucocorticoid resistance in pediatric acute lymphoblastic leukemia. BMC Med. Inform. Decis. Mak., 2018, 18(Suppl. 2), 57.
[http://dx.doi.org/10.1186/s12911-018-0637-3] [PMID: 30066657]
[78]
Huang, Y.A.; Hu, P.; Chan, K.C.C.; You, Z.H. Graph convolution for predicting associations between miRNA and drug resistance. Bioinformatics, 2020, 36(3), 851-858.
[PMID: 31397851]
[79]
Dai, E.; Yang, F.; Wang, J.; Zhou, X.; Song, Q.; An, W.; Wang, L.; Jiang, W. ncDR: a comprehensive resource of non-coding RNAs involved in drug resistance. Bioinformatics, 2017, 33(24), 4010-4011.
[http://dx.doi.org/10.1093/bioinformatics/btx523] [PMID: 28961690]
[80]
Li, J.; Han, L.; Roebuck, P.; Diao, L.; Liu, L.; Yuan, Y.; Weinstein, J.N.; Liang, H. TANRIC: An interactive open platform to explore the function of lncRNAs in cancer. Cancer Res., 2015, 75(18), 3728-3737.
[http://dx.doi.org/10.1158/0008-5472.CAN-15-0273] [PMID: 26208906]
[81]
Li, Y.; Li, L.; Wang, Z.; Pan, T.; Sahni, N.; Jin, X.; Wang, G.; Li, J.; Zheng, X.; Zhang, Y.; Xu, J.; Yi, S.; Li, X. LncMAP: Pan-cancer atlas of long noncoding RNA-mediated transcriptional network perturbations. Nucleic Acids Res., 2018, 46(3), 1113-1123.
[http://dx.doi.org/10.1093/nar/gkx1311] [PMID: 29325141]
[82]
Ghandi, M.; Huang, F.W.; Jané-Valbuena, J.; Kryukov, G.V.; Lo, C.C.; McDonald, E.R., III; Barretina, J.; Gelfand, E.T.; Bielski, C.M.; Li, H.; Hu, K.; Andreev-Drakhlin, A.Y.; Kim, J.; Hess, J.M.; Haas, B.J.; Aguet, F.; Weir, B.A.; Rothberg, M.V.; Paolella, B.R.; Lawrence, M.S.; Akbani, R.; Lu, Y.; Tiv, H.L.; Gokhale, P.C.; de Weck, A.; Mansour, A.A.; Oh, C.; Shih, J.; Hadi, K.; Rosen, Y.; Bistline, J.; Venkatesan, K.; Reddy, A.; Sonkin, D.; Liu, M.; Lehar, J.; Korn, J.M.; Porter, D.A.; Jones, M.D.; Golji, J.; Caponigro, G.; Taylor, J.E.; Dunning, C.M.; Creech, A.L.; Warren, A.C.; McFarland, J.M.; Zamanighomi, M.; Kauffmann, A.; Stransky, N.; Imielinski, M.; Maruvka, Y.E.; Cherniack, A.D.; Tsherniak, A.; Vazquez, F.; Jaffe, J.D.; Lane, A.A.; Weinstock, D.M.; Johannessen, C.M.; Morrissey, M.P.; Stegmeier, F.; Schlegel, R.; Hahn, W.C.; Getz, G.; Mills, G.B.; Boehm, J.S.; Golub, T.R.; Garraway, L.A.; Sellers, W.R. Next-generation characterization of the Cancer Cell Line Encyclopedia. Nature, 2019, 569(7757), 503-508.
[http://dx.doi.org/10.1038/s41586-019-1186-3] [PMID: 31068700]
[83]
Zhao, H.; Shi, J.; Zhang, Y.; Xie, A.; Yu, L.; Zhang, C.; Lei, J.; Xu, H.; Leng, Z.; Li, T.; Huang, W.; Lin, S.; Wang, L.; Xiao, Y.; Li, X. LncTarD: a manually-curated database of experimentally-supported functional lncRNA-target regulations in human diseases. Nucleic Acids Res., 2020, 48(D1), D118-D126.
[PMID: 31713618]
[84]
Li, L.; Wu, P.; Wang, Z.; Meng, X.; Zha, C.; Li, Z.; Qi, T.; Zhang, Y.; Han, B.; Li, S.; Jiang, C.; Zhao, Z.; Cai, J. NoncoRNA: a database of experimentally supported non-coding RNAs and drug targets in cancer. J. Hematol. Oncol., 2020, 13(1), 15.
[http://dx.doi.org/10.1186/s13045-020-00849-7] [PMID: 32111231]
[85]
Zhang, T.; Tan, P.; Wang, L.; Jin, N.; Li, Y.; Zhang, L.; Yang, H.; Hu, Z.; Zhang, L.; Hu, C.; Li, C.; Qian, K.; Zhang, C.; Huang, Y.; Li, K.; Lin, H.; Wang, D. RNALocate: a resource for RNA subcellular localizations. Nucleic Acids Res., 2017, 45(D1), D135-D138.
[PMID: 27543076]
[86]
Zhang, Z.Y.; Yang, Y.H.; Ding, H.; Wang, D.; Chen, W.; Lin, H. Design powerful predictor for mRNA subcellular location prediction in Homo sapiens. Brief. Bioinform., 2021, 22(1), 526-535.
[http://dx.doi.org/10.1093/bib/bbz177] [PMID: 31994694]
[87]
Gopinath, K.; Karthikeyan, M. Understanding the evolutionary relationship of m2 channel protein of influenza A virus and its structural variation and drug resistance. Curr. Bioinform., 2017, 12(3), 265-274.
[http://dx.doi.org/10.2174/1574893611666161123153103]

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy