Review Article

非编码 RNA 作为癌症耐药性的新型生物标志物

卷 29, 期 5, 2022

发表于: 26 January, 2022

页: [837 - 848] 页: 12

弟呕挨: 10.2174/0929867328666210804090644

价格: $65

摘要

化疗通常是主要和最有效的抗癌治疗;然而,耐药性仍然是其治愈的主要障碍。最近的研究表明,非编码 RNAs (ncRNAs),尤其是 microRNAs 和长链非编码 RNAs,以多种方式参与肿瘤细胞的耐药性,如调节细胞凋亡、药物流出和代谢、上皮间质DNA 修复和细胞周期进程。探索ncRNAs与耐药性之间的关系,不仅有助于我们理解耐药性机制,提供化疗耐药性的ncRNA生物标志物,也有助于实现个性化的抗癌治疗方案。由于生物实验成本高、效率低,许多研究人员选择使用计算方法来识别与耐药性相关的 ncRNA 生物标志物。在这篇综述中,我们总结了与 ncRNA 介导的耐药性相关的最新发现,并强调了可用于与化学耐药性相关的 ncRNA 生物标志物的计算方法和资源。

关键词: ncRNA、miRNA、lncRNA、耐药性、计算方法、数据库。

[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