Cancer Epidemiology 39 (2015) 978–985
Contents lists available at ScienceDirect
Cancer Epidemiology The International Journal of Cancer Epidemiology, Detection, and Prevention journal homepage: www.cancerepidemiology.net
Polymorphisms in lncRNA HOTAIR and susceptibility to breast cancer in a Chinese population Rui Yana,1, Jingjing Caoa,1, Chunhua Songa,b,* , Yi Chena , Zhenzhen Wua , Kaijuan Wanga,b , Liping Daia,b a b
Department of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, Henan, PR China Henan Key Laboratory of Tumor Epidemiology, Zhengzhou 450001, Henan, PR China
A R T I C L E I N F O
A B S T R A C T
Article history: Received 27 June 2015 Received in revised form 19 October 2015 Accepted 27 October 2015 Available online xxx
Controversial data have emerged on the association between cancer risk and the single-nucleotide polymorphism (SNP, rs920778C > T) in Hox transcript antisense RNA (HOTAIR). No data on the association between HOTAIR polymorphism and breast cancer (BC) susceptibility and reproductive factors have been reported in China. In this study we investigated the association between HOTAIR polymorphisms and BC susceptibility in a population-based case–control study of 502 cases and 504 matched controls in China. Three haplotype tagging SNPs (rs1899663, rs4759314, rs920778) of HOTAIR were genotyped with polymerase chain reaction–restriction fragment-length polymorphism (PCR–RFLP) and createdrestriction-site PCR (CRS–RFLP) assays. False-positive report probability (FPRP) was calculated to test for false-positive associations. Interactions between the SNPs and reproductive factors were further evaluated by the multifactor dimensionality reduction (MDR) method. BC risk reduction was confined to subgroups of age at menarche >14 (OR: 0.42, 95%CI: 0.21, 0.82) and number of pregnancies >2 (OR: 0.65, 95%CI: 0.49, 0.95) for GT + TT rs1899663, and age at menopause 50 (OR: 0.97, 95%CI: 0.84, 0.99) for AG + GG rs4759314. Subjects with Trs920778 had a significantly increased risk of breast cancer (OR: 1.41, 95%CI: 1.13, 1.75). We observed a significant interaction between rs920778 and reproductive factors, including age at menopause, number of abortions, and family history. Our results were unlikely to be false positives according to FPRP calculation. In conclusion, genetic variant rs920778 in HOTAIR significantly increased the risk of BC, and it may have apparent interaction with reproductive factors in the progression on BC. These findings extend available data on the association between HOTAIR polymorphisms and BC susceptibility. ã 2015 Elsevier Ltd. All rights reserved.
Keywords: Breast cancer HOTAIR LncRNA Genetic susceptibility Interaction
1. Introduction Breast cancer (BC) is the most frequently diagnosed malignant tumor and the primary cause of death from cancer in women worldwide [1,2]. The etiology of breast cancer is complex and multifactorial. It is generally considered that genetic, environmental, and reproductive factors all contribute to the development of BC [3–5]. Long non-coding RNAs (lncRNAs) are defined as transcribed RNA molecules that are longer than 200 nucleotides, lack an open reading frame of significant length (14 or number of pregnancies >2 for GT + TT rs1899663, and age at menopause 50 for AG + GG rs4759314. The variant rs920778 was associated with higher breast cancer risk in this cohort, and was shown to have interactions with age at menopause, number of abortions and family history. Our results suggest that genetic variations in the HOTAIR might play important roles in the development of BC, and HOTAIR may be a useful marker to predict BC risk. Further studies with larger sample sizes and in different ethnic populations are needed to validate our findings. Conflict of interest The authors declare no conflict of interest. Authorship contribution Conception and design: Rui Yan, Chunhua Song. Development of methodology: Rui Yan, Jingjing Cao, Chunhua Song, Zhenzhen Wu. Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): Rui Yan, Jingjing Cao, Chunhua Song, Zhenzhen Wu, Yi Chen, Kaijuan Wang, Liping Dai. Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): Rui Yan, Jingjing Cao, Chunhua Song, Zhenzhen Wu. Writing, review and/or revision of the manuscript: Rui Yan, Jingjing Cao, Chunhua Song. Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): Chunhua Song, Kaijuan Wang, Liping Dai. Study supervision: Chunhua Song, Kaijuan Wang, Liping Dai. Acknowledgments The authors thank all the study participants and the interviewers for their contributions and commitment to this study. The authors are grateful for the support of the National Natural Science Foundation of China (81202278) and Medical Science and Technology Key Projects of Henan province (201303005) for their funding support.
R. Yan et al. / Cancer Epidemiology 39 (2015) 978–985
Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j. canep.2015.10.025. References [1] A. Jemal, F. Bray, M.M. Center, J. Ferlay, E. Ward, D. Forman, Global cancer statistics, CA Cancer J. Clin. 61 (2011) 69–90, doi:http://dx.doi.org/10.3322/ caac.20107. [2] C. DeSantis, J. Ma, L. Bryan, A. Jemal, Breast cancer statistics, 2013, CA Cancer J. Clin. 64 (2014) 52–62, doi:http://dx.doi.org/10.3322/caac.21203. [3] S. Volinia, M. Galasso, M.E. Sana, T.F. Wise, J. Palatini, K. Huebner, et al., Breast cancer signatures for invasiveness and prognosis defined by deep sequencing of microRNA, Proc. Natl. Acad. Sci. U. S. A. 109 (2012) 3024–3029, doi:http://dx. doi.org/10.1073/pnas.1200010109. [4] Y. Sapkota, J.R. Mackey, R. Lai, C. Franco-Villalobos, S. Lupichuk, P.J. Robson, et al., Assessing SNP–SNP interactions among DNA repair, modification and metabolism related pathway genes in breast cancer susceptibility, PLoS One 8 (2013) , doi:http://dx.doi.org/10.1371/journal.pone.0064896. [5] H.X. Li, A. Beeghly-Fadiel, W.Q. Wen, W. Lu, Y.T. Gao, Y.B. Xiang, et al., Gene– environment interactions for breast cancer risk among chinese women: a report from the shanghai breast cancer genetics study, Am. J. Epidemiol. 177 (2013) 161–170, doi:http://dx.doi.org/10.1093/aje/kws238. [6] P. Bertone, V. Stolc, T.E. Royce, J.S. Rozowsky, A.E. Urban, X.W. Zhu, et al., Global identification of human transcribed sequences with genome tiling arrays, Science 306 (2004) 2242–2246, doi:http://dx.doi.org/10.1126/ science.1103388. [7] T. Derrien, R. Johnson, G. Bussotti, A. Tanzer, S. Djebali, H. Tilgner, et al., The GENCODE v7 catalog of human long noncoding RNAs: analysis of their gene structure, evolution, and expression, Genome Res. 22 (2012) 1775–1789, doi: http://dx.doi.org/10.1101/gr.132159.111. [8] R.A. Gupta, N. Shah, K.C. Wang, J. Kim, H.M. Horlings, D.J. Wong, et al., Long non-coding RNA HOTAIR reprograms chromatin state to promote cancer metastasis, Nature 464 (2010) U148–1071, doi:http://dx.doi.org/10.1038/ nature08975. [9] P. Ji, S. Diederichs, W. Wang, S. Boing, R. Metzger, P.M. Schneider, et al., MALAT1, a novel noncoding RNA, and thymosin beta4 predict metastasis and survival in early-stage non-small cell lung cancer, Oncogene 22 (2003) 8031–8041, doi: http://dx.doi.org/10.1038/sj.onc.1206928. [10] M.Z. Ma, B.F. Chu, Y. Zhang, M.Z. Weng, Y.Y. Qin, W. Gong, et al., Long noncoding RNA CCAT1 promotes gallbladder cancer development via negative modulation of miRNA-218-5p, Cell Death Dis. 6 (2015) e1583, doi:http://dx. doi.org/10.1038/cddis.2014.541. [11] F.Q. Nie, M. Sun, J.S. Yang, M. Xie, T.P. Xu, R. Xia, N. Long, R.N.A. oncoding, et al., ANRIL promotes non-small cell lung cancer cell proliferation and inhibits apoptosis by silencing KLF2 and P21 Expression, Mol. Cancer Ther. 14 (2015) 268–277, doi:http://dx.doi.org/10.1158/1535-7163.mct-14-0492. [12] N. Li, P. Zhou, J. Zheng, J.Q. Deng, H.C. Wu, W. Li, et al., A Polymorphism rs12325489C > T in the LincRNA-ENST00000515084 exon was found to modulate breast cancer risk via GWAS-based association analyses, PLoS One 9 (2014) , doi:http://dx.doi.org/10.1371/journal.pone.0098251. [13] H.C. Wu, J. Zheng, J.Q. Deng, M. Hu, Y.H. You, N. Li, et al., A genetic polymorphism in lincRNA-uc003opf.1 is associated with susceptibility to esophageal squamous cell carcinoma in Chinese populations, Carcinogenesis 34 (2013) 2908–2917, doi:http://dx.doi.org/10.1093/carcin/bgt252. [14] J.L. Rinn, M. Kertesz, J.K. Wang, S.L. Squazzo, X. Xu, S.A. Brugmann, et al., Functional demarcation of active and silent chromatin domains in human HOX loci by noncoding RNAs, Cell 129 (2007) 1311–1323, doi:http://dx.doi.org/ 10.1016/j.cell.2007.05.022. [15] A.M. Khalil, M. Guttman, M. Huarte, M. Garber, A. Raj, D.R. Morales, et al., Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression, Proc. Natl. Acad. Sci. U. S. A. 106 (2009) 11667–11672, doi:http://dx.doi.org/10.1073/pnas.0904715106. [16] M.C. Tsai, O. Manor, Y. Wan, N. Mosammaparast, J.K. Wang, F. Lan, et al., Long noncoding RNA as modular scaffold of histone modification complexes, Science 329 (2010) 689–693, doi:http://dx.doi.org/10.1126/science.1192002. [17] M.C. Lai, Z. Yang, L. Zhou, Q.Q. Zhu, H.Y. Xie, F. Zhang, et al., Long non-coding RNA MALAT-1 overexpression predicts tumor recurrence of hepatocellular carcinoma after liver transplantation, Med. Oncol. 29 (2012) 1810–1816, doi: http://dx.doi.org/10.1007/s12032-011-0004-z. [18] M. Hajjari, M. Behmanesh, M. Sadeghizadeh, M. Zeinoddini, Up-regulation of HOTAIR long non-coding RNA in human gastric adenocarcinoma tissues, Med. Oncol. 30 (2013) , doi:http://dx.doi.org/10.1007/s12032-013-0670-0.
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[19] K. Kim, I. Jutooru, G. Chadalapaka, G. Johnson, J. Frank, R. Burghardt, et al., HOTAIR is a negative prognostic factor and exhibits pro-oncogenic activity in pancreatic cancer, Oncogene 32 (2013) 1616–1625, doi:http://dx.doi.org/ 10.1038/Onc.2012.193. [20] L.G. Lu, G.J. Zhu, C. Zhang, Q. Deng, D. Katsaros, S.T. Mayne, et al., Association of large noncoding RNA HOTAIR expression and its downstream intergenic CpG island methylation with survival in breast cancer, Breast Cancer Res. Treat. 136 (2012) 875–883, doi:http://dx.doi.org/10.1007/s10549-012-2314-z. [21] Y.L. Yao, J.M. Li, L.N. Wang, Large intervening non-coding RNA HOTAIR is an indicator of poor prognosis and a therapeutic target in human cancers, Int. J. Mol. Sci. 15 (2014) 18985–18999, doi:http://dx.doi.org/10.3390/ ijms151018985. [22] X.J. Zhang, L.Q. Zhou, G.B. Fu, F. Sun, J. Shi, J.Y. Wei, et al., The identification of an ESCC susceptibility SNP rs920778 that regulates the expression of lncRNA HOTAIR via a novel intronic enhancer, Carcinogenesis 35 (2014) 2062–2067, doi:http://dx.doi.org/10.1093/carcin/bgu103. [23] Y. Xue, D. Gu, G. Ma, L. Zhu, Q. Hua, H. Chu, et al., Genetic variants in lncRNA HOTAIR are associated with risk of colorectal cancer, Mutagenesis (2014) , doi: http://dx.doi.org/10.1093/mutage/geu076. [24] W. Guo, Z.M. Dong, Y.L. Bai, Y.L. Guo, S.P. Shen, G. Kuang, et al., Associations between polymorphisms of HOTAIR and risk of gastric cardia adenocarcinoma in a population of north China, Tumor Biol. 36 (2015) 2845–2854, doi:http:// dx.doi.org/10.1007/s13277-014-2912-y. [25] S. Bayram, A.T. Sumbul, C.Y. Batmaci, A. Genc, Effect of HOTAIR rs920778 polymorphism on breast cancer susceptibility and clinicopathologic features in a Turkish population, Tumour Biol. (2015) , doi:http://dx.doi.org/ 10.1007/s13277-014-3028-0. [26] S. Bayram, Y. Ulger, A.T. Sumbul, B.Y. Kaya, A. Rencuzogullari, A. Genc, et al., A functional HOTAIR rs920778 polymorphism does not contributes to gastric cancer in a Turkish population: a case-control study, Fam. Cancer (2015) , doi: http://dx.doi.org/10.1007/s10689-015-9813-0. [27] W. Pan, L. Liu, J. Wei, Y. Ge, J. Zhang, H. Chen, et al., A functional lncRNA HOTAIR genetic variant contributes to gastric cancer susceptibility, Mol. Carcinog. (2015) , doi:http://dx.doi.org/10.1002/mc.22261. [28] D.S.P. Tan, C. Marchio, R.L. Jones, K. Savage, I.E. Smith, M. Dowsett, et al., Triple negative breast cancer: molecular profiling and prognostic impact in adjuvant anthracycline-treated patients, Breast Cancer Res. Treat. 111 (2008) 27–44, doi: http://dx.doi.org/10.1007/s10549-007-9756-8. [29] R. Kogo, T. Shimamura, K. Mimori, K. Kawahara, S. Imoto, T.L. Sudo, N. ong, R.N. A. oncoding, HOTAIR regulates polycomb-dependent chromatin modification and is associated with poor prognosis in colorectal cancers, Cancer Res. 71 (2011) 6320, doi:http://dx.doi.org/10.1158/0008-5472 Can-12-0034. [30] H. Endo, T. Shiroki, T. Nakagawa, M. Yokoyama, K. Tamai, H. Yamanami, et al., Enhanced expression of long non-coding RNA HOTAIR is associated with the development of gastric cancer, PLoS One 8 (2013) , doi:http://dx.doi.org/ 10.1371/journal.pone.0077070. [31] M. Ishibashi, R. Kogo, K. Shibata, G. Sawada, Y. Takahashi, J. Kurashige, et al., Clinical significance of the expression of long non-coding RNA HOTAIR in primary hepatocellular carcinoma, Oncol. Rep. 29 (2013) 946–950, doi:http:// dx.doi.org/10.3892/or.2012.2219. [32] K.P. Sorensen, M. Thomassen, Q.H. Tan, M. Bak, S. Cold, M. Burton, et al., Long non-coding RNA HOTAIR is an independent prognostic marker of metastasis in estrogen receptor-positive primary breast cancer, Breast Cancer Res. Treat. 142 (2013) 529–536, doi:http://dx.doi.org/10.1007/s10549-013-2776-7. [33] H.M. Colhoun, P.M. McKeigue, G.D. Smith, Problems of reporting genetic associations with complex outcomes, Lancet 361 (2003) 865–872, doi:http:// dx.doi.org/10.1016/s0140-6736(03) 12715-8. [34] J.P.A. Ioannidis, E.E. Ntzani, T.A. Trikalinos, D.G. Contopoulos-Ioannidis, Replication validity of genetic association studies, Nat Genet. 29 (2001) 306–309, doi:http://dx.doi.org/10.1038/Ng749. [35] J.A. Sterne, S. Davey, G. mith, Sifting the evidence-what’s wrong with significance tests? BMJ 322 (2001) 226–231, doi:http://dx.doi.org/10.1136/ bmj.322.7280.226. [36] R.C. Travis, G.K. Reeves, J. Green, D. Bull, S.J. Tipper, K. Baker, et al., Geneenvironment interactions in 7610 women with breast cancer: prospective evidence from the Million Women Study, Lancet 375 (2010) 2143–2151, doi: http://dx.doi.org/10.1016/S0140-6736(10)60636-8. [37] R.L. Milne, M.M. Gaudet, A.B. Spurdle, P.A. Fasching, F.J. Couch, J. 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Contents lists available at ScienceDirect
Cancer Epidemiology The International Journal of Cancer Epidemiology, Detection, and Prevention journal homepage: www.cancerepidemiology.net
Polymorphisms in lncRNA HOTAIR and susceptibility to breast cancer in a Chinese population Rui Yana,1, Jingjing Caoa,1, Chunhua Songa,b,* , Yi Chena , Zhenzhen Wua , Kaijuan Wanga,b , Liping Daia,b a b
Department of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, Henan, PR China Henan Key Laboratory of Tumor Epidemiology, Zhengzhou 450001, Henan, PR China
A R T I C L E I N F O
A B S T R A C T
Article history: Received 27 June 2015 Received in revised form 19 October 2015 Accepted 27 October 2015 Available online xxx
Controversial data have emerged on the association between cancer risk and the single-nucleotide polymorphism (SNP, rs920778C > T) in Hox transcript antisense RNA (HOTAIR). No data on the association between HOTAIR polymorphism and breast cancer (BC) susceptibility and reproductive factors have been reported in China. In this study we investigated the association between HOTAIR polymorphisms and BC susceptibility in a population-based case–control study of 502 cases and 504 matched controls in China. Three haplotype tagging SNPs (rs1899663, rs4759314, rs920778) of HOTAIR were genotyped with polymerase chain reaction–restriction fragment-length polymorphism (PCR–RFLP) and createdrestriction-site PCR (CRS–RFLP) assays. False-positive report probability (FPRP) was calculated to test for false-positive associations. Interactions between the SNPs and reproductive factors were further evaluated by the multifactor dimensionality reduction (MDR) method. BC risk reduction was confined to subgroups of age at menarche >14 (OR: 0.42, 95%CI: 0.21, 0.82) and number of pregnancies >2 (OR: 0.65, 95%CI: 0.49, 0.95) for GT + TT rs1899663, and age at menopause 50 (OR: 0.97, 95%CI: 0.84, 0.99) for AG + GG rs4759314. Subjects with Trs920778 had a significantly increased risk of breast cancer (OR: 1.41, 95%CI: 1.13, 1.75). We observed a significant interaction between rs920778 and reproductive factors, including age at menopause, number of abortions, and family history. Our results were unlikely to be false positives according to FPRP calculation. In conclusion, genetic variant rs920778 in HOTAIR significantly increased the risk of BC, and it may have apparent interaction with reproductive factors in the progression on BC. These findings extend available data on the association between HOTAIR polymorphisms and BC susceptibility. ã 2015 Elsevier Ltd. All rights reserved.
Keywords: Breast cancer HOTAIR LncRNA Genetic susceptibility Interaction
1. Introduction Breast cancer (BC) is the most frequently diagnosed malignant tumor and the primary cause of death from cancer in women worldwide [1,2]. The etiology of breast cancer is complex and multifactorial. It is generally considered that genetic, environmental, and reproductive factors all contribute to the development of BC [3–5]. Long non-coding RNAs (lncRNAs) are defined as transcribed RNA molecules that are longer than 200 nucleotides, lack an open reading frame of significant length (14 or number of pregnancies >2 for GT + TT rs1899663, and age at menopause 50 for AG + GG rs4759314. The variant rs920778 was associated with higher breast cancer risk in this cohort, and was shown to have interactions with age at menopause, number of abortions and family history. Our results suggest that genetic variations in the HOTAIR might play important roles in the development of BC, and HOTAIR may be a useful marker to predict BC risk. Further studies with larger sample sizes and in different ethnic populations are needed to validate our findings. Conflict of interest The authors declare no conflict of interest. Authorship contribution Conception and design: Rui Yan, Chunhua Song. Development of methodology: Rui Yan, Jingjing Cao, Chunhua Song, Zhenzhen Wu. Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): Rui Yan, Jingjing Cao, Chunhua Song, Zhenzhen Wu, Yi Chen, Kaijuan Wang, Liping Dai. Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): Rui Yan, Jingjing Cao, Chunhua Song, Zhenzhen Wu. Writing, review and/or revision of the manuscript: Rui Yan, Jingjing Cao, Chunhua Song. Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): Chunhua Song, Kaijuan Wang, Liping Dai. Study supervision: Chunhua Song, Kaijuan Wang, Liping Dai. Acknowledgments The authors thank all the study participants and the interviewers for their contributions and commitment to this study. The authors are grateful for the support of the National Natural Science Foundation of China (81202278) and Medical Science and Technology Key Projects of Henan province (201303005) for their funding support.
R. Yan et al. / Cancer Epidemiology 39 (2015) 978–985
Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j. canep.2015.10.025. References [1] A. Jemal, F. Bray, M.M. Center, J. Ferlay, E. Ward, D. Forman, Global cancer statistics, CA Cancer J. Clin. 61 (2011) 69–90, doi:http://dx.doi.org/10.3322/ caac.20107. [2] C. DeSantis, J. Ma, L. Bryan, A. Jemal, Breast cancer statistics, 2013, CA Cancer J. Clin. 64 (2014) 52–62, doi:http://dx.doi.org/10.3322/caac.21203. [3] S. Volinia, M. Galasso, M.E. Sana, T.F. Wise, J. Palatini, K. Huebner, et al., Breast cancer signatures for invasiveness and prognosis defined by deep sequencing of microRNA, Proc. Natl. Acad. Sci. U. S. A. 109 (2012) 3024–3029, doi:http://dx. doi.org/10.1073/pnas.1200010109. [4] Y. Sapkota, J.R. Mackey, R. Lai, C. Franco-Villalobos, S. Lupichuk, P.J. Robson, et al., Assessing SNP–SNP interactions among DNA repair, modification and metabolism related pathway genes in breast cancer susceptibility, PLoS One 8 (2013) , doi:http://dx.doi.org/10.1371/journal.pone.0064896. [5] H.X. Li, A. Beeghly-Fadiel, W.Q. Wen, W. Lu, Y.T. Gao, Y.B. Xiang, et al., Gene– environment interactions for breast cancer risk among chinese women: a report from the shanghai breast cancer genetics study, Am. J. Epidemiol. 177 (2013) 161–170, doi:http://dx.doi.org/10.1093/aje/kws238. [6] P. Bertone, V. Stolc, T.E. Royce, J.S. Rozowsky, A.E. Urban, X.W. Zhu, et al., Global identification of human transcribed sequences with genome tiling arrays, Science 306 (2004) 2242–2246, doi:http://dx.doi.org/10.1126/ science.1103388. [7] T. Derrien, R. Johnson, G. Bussotti, A. Tanzer, S. Djebali, H. Tilgner, et al., The GENCODE v7 catalog of human long noncoding RNAs: analysis of their gene structure, evolution, and expression, Genome Res. 22 (2012) 1775–1789, doi: http://dx.doi.org/10.1101/gr.132159.111. [8] R.A. Gupta, N. Shah, K.C. Wang, J. Kim, H.M. Horlings, D.J. Wong, et al., Long non-coding RNA HOTAIR reprograms chromatin state to promote cancer metastasis, Nature 464 (2010) U148–1071, doi:http://dx.doi.org/10.1038/ nature08975. [9] P. Ji, S. Diederichs, W. Wang, S. Boing, R. Metzger, P.M. Schneider, et al., MALAT1, a novel noncoding RNA, and thymosin beta4 predict metastasis and survival in early-stage non-small cell lung cancer, Oncogene 22 (2003) 8031–8041, doi: http://dx.doi.org/10.1038/sj.onc.1206928. [10] M.Z. Ma, B.F. Chu, Y. Zhang, M.Z. Weng, Y.Y. Qin, W. Gong, et al., Long noncoding RNA CCAT1 promotes gallbladder cancer development via negative modulation of miRNA-218-5p, Cell Death Dis. 6 (2015) e1583, doi:http://dx. doi.org/10.1038/cddis.2014.541. [11] F.Q. Nie, M. Sun, J.S. Yang, M. Xie, T.P. Xu, R. Xia, N. Long, R.N.A. oncoding, et al., ANRIL promotes non-small cell lung cancer cell proliferation and inhibits apoptosis by silencing KLF2 and P21 Expression, Mol. Cancer Ther. 14 (2015) 268–277, doi:http://dx.doi.org/10.1158/1535-7163.mct-14-0492. [12] N. Li, P. Zhou, J. Zheng, J.Q. Deng, H.C. Wu, W. Li, et al., A Polymorphism rs12325489C > T in the LincRNA-ENST00000515084 exon was found to modulate breast cancer risk via GWAS-based association analyses, PLoS One 9 (2014) , doi:http://dx.doi.org/10.1371/journal.pone.0098251. [13] H.C. Wu, J. Zheng, J.Q. Deng, M. Hu, Y.H. You, N. Li, et al., A genetic polymorphism in lincRNA-uc003opf.1 is associated with susceptibility to esophageal squamous cell carcinoma in Chinese populations, Carcinogenesis 34 (2013) 2908–2917, doi:http://dx.doi.org/10.1093/carcin/bgt252. [14] J.L. Rinn, M. Kertesz, J.K. Wang, S.L. Squazzo, X. Xu, S.A. Brugmann, et al., Functional demarcation of active and silent chromatin domains in human HOX loci by noncoding RNAs, Cell 129 (2007) 1311–1323, doi:http://dx.doi.org/ 10.1016/j.cell.2007.05.022. [15] A.M. Khalil, M. Guttman, M. Huarte, M. Garber, A. Raj, D.R. Morales, et al., Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression, Proc. Natl. Acad. Sci. U. S. A. 106 (2009) 11667–11672, doi:http://dx.doi.org/10.1073/pnas.0904715106. [16] M.C. Tsai, O. Manor, Y. Wan, N. Mosammaparast, J.K. Wang, F. Lan, et al., Long noncoding RNA as modular scaffold of histone modification complexes, Science 329 (2010) 689–693, doi:http://dx.doi.org/10.1126/science.1192002. [17] M.C. Lai, Z. Yang, L. Zhou, Q.Q. Zhu, H.Y. Xie, F. Zhang, et al., Long non-coding RNA MALAT-1 overexpression predicts tumor recurrence of hepatocellular carcinoma after liver transplantation, Med. Oncol. 29 (2012) 1810–1816, doi: http://dx.doi.org/10.1007/s12032-011-0004-z. [18] M. Hajjari, M. Behmanesh, M. Sadeghizadeh, M. Zeinoddini, Up-regulation of HOTAIR long non-coding RNA in human gastric adenocarcinoma tissues, Med. Oncol. 30 (2013) , doi:http://dx.doi.org/10.1007/s12032-013-0670-0.
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