Login Register Cart 0
Generic placeholder image

Combinatorial Chemistry & High Throughput Screening

Editor-in-Chief

ISSN (Print): 1386-2073
ISSN (Online): 1875-5402

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Research Article

13-lncRNAs Signature to Improve Diagnostic and Prognostic Prediction of Hepatocellular Carcinoma

Author(s): Xinxin Zhang, Jia Yu, Juan Hu, Fang Tan, Juan Zhou, Xiaoyan Yang, Zhizhong Xie, Huifang Tang, Sen Dong and Xiaoyong Lei*

Volume 24, Issue 5, 2021

Published on: 14 September, 2020

Page: [656 - 667] Pages: 12

DOI: 10.2174/1386207323666200914095616

Price: $65

Abstract

Background: Hepatocellular carcinoma (HCC) is a common type of cancer with a high mortality rate and is usually detected at the middle or late stage, missing the optimal treatment period. The current study aims to identify potential long non-coding RNA (lncRNAs) biomarkers that contribute to the diagnosis and prognosis of HCC.

Methods: The differentially expressed lncRNAs (DElncRNAs) in HCC patients were detected from the Cancer Genome Atlas (TCGA) dataset. LncRNAs signature was screened by LASSO regression, univariate, and multivariate Cox regression. The models for predicting diagnosis and prognosis were established, respectively. The prognostic model was evaluated by Kaplan-Meier survival curve receiver operating characteristic (ROC) curve and stratified analysis. The diagnostic model was validated by ROC. The lncRNAs signature was further demonstrated by functional enrichment analysis.

Results: We found the 13-lncRNAs signature that had a good performance in predicting prognosis and could help to improve the value of diagnosis. In the training set, testing set, and entire cohort, the low-risk group had longer survival than the high-risk group (median OS: 3124 vs. 649 days, 2456 vs. 770 days and 3124 vs. 755 days). It performed well in 1-, 3-, and 5-year survival prediction. 13-lncRNAs-based risk score, age, and race were good predictors of prognosis. The AUC of diagnosis was 0.9487, 0.9265, and 0.9376, respectively. Meanwhile, the 13-lncRNAs were involved in important pathways, including the cell cycle and multiple metabolic pathways.

Conclusion: In our study, the 13-lncRNAs signature may be a potential marker for the prognosis of HCC and improve the diagnosis.

Keywords: lncRNAs, HCC, TCGA, diagnosis, prognosis, bioinformatics analysis.

« Previous Next »
[1]
Bray, F.; Ferlay, J.; Soerjomataram, I.; Siegel, R.L.; Torre, L.A.; Jemal, A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin., 2018, 68(6), 394-424.
[http://dx.doi.org/10.3322/caac.21492] [PMID: 30207593]
[2]
Fitzmaurice, C.; Allen, C.; Barber, R.M. Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life-years for 32 cancer groups, 1990 to 2015: a systematic analysis for the global burden of disease study. JAMA Oncol., 2017, 3(4), 524-548.
[http://dx.doi.org/10.1001/jamaoncol.2016.5688] [PMID: 27918777]
[3]
Kim, J.U.; Shariff, M.I.; Crossey, M.M.; Gomez-Romero, M.; Holmes, E.; Cox, I.J.; Fye, H.K.; Njie, R.; Taylor-Robinson, S.D. Hepatocellular carcinoma: Review of disease and tumor biomarkers. World J. Hepatol., 2016, 8(10), 471-484.
[http://dx.doi.org/10.4254/wjh.v8.i10.471] [PMID: 27057305]
[4]
El-Serag, H.B. Hepatocellular carcinoma. N. Engl. J. Med., 2011, 365(12), 1118-1127.
[http://dx.doi.org/10.1056/NEJMra1001683] [PMID: 21992124]
[5]
Siegel, R.L.; Miller, K.D.; Jemal, A. Cancer statistics, 2015. CA Cancer J. Clin., 2015, 65(1), 5-29.
[http://dx.doi.org/10.3322/caac.21254] [PMID: 25559415]
[6]
Liu, J.; Dang, H.; Wang, X.W. The significance of intertumor and intratumor heterogeneity in liver cancer. Exp. Mol. Med., 2018, 50(1)e416
[http://dx.doi.org/10.1038/emm.2017.165] [PMID: 29303512]
[7]
Solomon, J.P.; Hansel, D.E. Prognostic factors in urothelial carcinoma of the bladder: histologic and molecular correlates. Adv. Anat. Pathol., 2015, 22(2), 102-112.
[http://dx.doi.org/10.1097/PAP.0000000000000050] [PMID: 25664945]
[8]
Tellapuri, S.; Sutphin, P.D.; Beg, M.S.; Singal, A.G.; Kalva, S.P. Staging systems of hepatocellular carcinoma: A review. Indian J. Gastroenterol., 2018, 37(6), 481-491.
[http://dx.doi.org/10.1007/s12664-018-0915-0] [PMID: 30593649]
[9]
Tsai, M.C.; Spitale, R.C.; Chang, H.Y. Long intergenic noncoding RNAs: new links in cancer progression. Cancer Res., 2011, 71(1), 3-7.
[http://dx.doi.org/10.1158/0008-5472.CAN-10-2483] [PMID: 21199792]
[10]
Yang, F.; Zhang, L.; Huo, X.S.; Yuan, J.H.; Xu, D.; Yuan, S.X.; Zhu, N.; Zhou, W.P.; Yang, G.S.; Wang, Y.Z.; Shang, J.L.; Gao, C.F.; Zhang, F.R.; Wang, F.; Sun, S.H. Long noncoding RNA high expression in hepatocellular carcinoma facilitates tumor growth through enhancer of zeste homolog 2 in humans. Hepatology, 2011, 54(5), 1679-1689.
[http://dx.doi.org/10.1002/hep.24563] [PMID: 21769904]
[11]
Wang, Y-L.; Liu, J-Y.; Yang, J.E.; Yu, X.M.; Chen, Z.L.; Chen, Y.J.; Kuang, M.; Zhu, Y.; Zhuang, S.M. Lnc-UCID promotes G1/S transition and hepatoma growth by preventing dhx9-mediated cdk6 down-regulation. Hepatology, 2019, 70(1), 259-275.
[http://dx.doi.org/10.1002/hep.30613] [PMID: 30865310]
[12]
Li, T.; Xie, J.; Shen, C.; Cheng, D.; Shi, Y.; Wu, Z.; Deng, X.; Chen, H.; Shen, B.; Peng, C.; Li, H.; Zhan, Q.; Zhu, Z. Amplification of long noncoding RNA ZFAS1 promotes metastasis in hepatocellular carcinoma. Cancer Res., 2015, 75(15), 3181-3191.
[http://dx.doi.org/10.1158/0008-5472.CAN-14-3721] [PMID: 26069248]
[13]
Lai, M.C.; Yang, Z.; Zhou, L.; Zhu, Q.Q.; Xie, H.Y.; Zhang, F.; Wu, L.M.; Chen, L.M.; Zheng, S.S. Long non-coding RNA MALAT-1 overexpression predicts tumor recurrence of hepatocellular carcinoma after liver transplantation. Med. Oncol., 2012, 29(3), 1810-1816.
[http://dx.doi.org/10.1007/s12032-011-0004-z] [PMID: 21678027]
[14]
Wang, Y.; Zhu, P.; Luo, J.; Wang, J.; Liu, Z.; Wu, W.; Du, Y.; Ye, B.; Wang, D.; He, L.; Ren, W.; Wang, J.; Sun, X.; Chen, R.; Tian, Y.; Fan, Z. LncRNA HAND2-AS1 promotes liver cancer stem cell self-renewal via BMP signaling. EMBO J., 2019, 38(17)e101110
[http://dx.doi.org/10.15252/embj.2018101110] [PMID: 31334575]
[15]
Yu, Z.; Zhao, H.; Feng, X.; Li, H.; Qiu, C.; Yi, X.; Tang, H.; Zhang, J. Long non-coding RNA FENDRR acts as a miR-423-5p sponge to suppress the treg-mediated immune escape of hepatocellular carcinoma cells. Mol. Ther. Nucleic Acids, 2019, 17, 516-529.
[http://dx.doi.org/10.1016/j.omtn.2019.05.027] [PMID: 31351327]
[16]
Yuan, S.X.; Wang, J.; Yang, F.; Tao, Q.F.; Zhang, J.; Wang, L.L.; Yang, Y.; Liu, H.; Wang, Z.G.; Xu, Q.G.; Fan, J.; Liu, L.; Sun, S.H.; Zhou, W.P. Long noncoding RNA DANCR increases stemness features of hepatocellular carcinoma by derepression of CTNNB1. Hepatology, 2016, 63(2), 499-511.
[http://dx.doi.org/10.1002/hep.27893] [PMID: 25964079]
[17]
Higgs, B.W.; Morehouse, C.A.; Streicher, K.; Brohawn, P.Z.; Pilataxi, F.; Gupta, A.; Ranade, K. Interferon Gamma messenger RNA signature in tumor biopsies predicts outcomes in patients with non-small cell lung carcinoma or urothelial cancer treated with durvalumab. Clin. Cancer Res., 2018, 24(16), 3857-3866.
[http://dx.doi.org/10.1158/1078-0432.CCR-17-3451] [PMID: 29716923]
[18]
Shukla, S.; Evans, J.R.; Malik, R.; Feng, F.Y.; Dhanasekaran, S.M.; Cao, X.; Chen, G.; Beer, D.G.; Jiang, H.; Chinnaiyan, A.M. Development of a RNA-seq based prognostic signature in lung adenocarcinoma. J. Natl. Cancer Inst., 2016, 109(1), 1-9.
[PMID: 27707839]
[19]
Zhang, H.; Zhu, M.; Du, Y.; Zhang, H.; Zhang, Q.; Liu, Q.; Huang, Z.; Zhang, L.; Li, H.; Xu, L.; Zhou, X.; Zhu, W.; Shu, Y.; Liu, P. A panel of 12-lncRNA signature predicts survival of pancreatic adenocarcinoma. J. Cancer, 2019, 10(6), 1550-1559.
[http://dx.doi.org/10.7150/jca.27823] [PMID: 31031865]
[20]
Mathieu, F. Bakhoum; Bita Esmaeli. Molecular Characteristics of Uveal Melanoma: Insights from the Cancer Genome Atlas (TCGA) Project. Cancers (Basel), 2019, 11(8), 1061.
[http://dx.doi.org/10.3390/cancers11081061]
[21]
Wu, H.; Zhang, J. Decreased expression of TFAP2B in endometrial cancer predicts poor prognosis: A study based on TCGA data. Gynecol. Oncol., 2018, 149(3), 592-597.
[http://dx.doi.org/10.1016/j.ygyno.2018.03.057] [PMID: 29602546]
[22]
Liao, X.; Yang, C.; Huang, R.; Han, C.; Yu, T.; Huang, K.; Liu, X.; Yu, L.; Zhu, G.; Su, H.; Wang, X.; Qin, W.; Deng, J.; Zeng, X.; Ye, X.; Peng, T. Identification of potential prognostic long non-coding RNA biomarkers for predicting survival in patients with hepatocellular carcinoma. Cell. Physiol. Biochem., 2018, 48(5), 1854-1869.
[http://dx.doi.org/10.1159/000492507] [PMID: 30092592]
[23]
Ma, L.; Deng, C. Identification of a novel four-lncRNA signature as a prognostic indicator in cirrhotic hepatocellular carcinoma. PeerJ, 2019, 7e7413
[http://dx.doi.org/10.7717/peerj.7413] [PMID: 31396449]
[24]
Bolstad, B.M.; Irizarry, R.A.; Astrand, M.; Speed, T.P. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics, 2003, 19(2), 185-193.
[http://dx.doi.org/10.1093/bioinformatics/19.2.185] [PMID: 12538238]
[25]
Robinson, M.D.; McCarthy, D.J.; Smyth, G.K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics, 2010, 26(1), 139-140.
[http://dx.doi.org/10.1093/bioinformatics/btp616] [PMID: 19910308]
[26]
Kuhn, M. Building predictive models in R using the caret Package. J. Stat. Softw., 2008, 28, 1-26.
[http://dx.doi.org/10.18637/jss.v028.i05]
[27]
O’Quigley, J.; Moreau, T. Cox’s regression model: computing a goodness of fit statistic. Comput. Methods Programs Biomed., 1986, 22(3), 253-256.
[http://dx.doi.org/10.1016/0169-2607(86)90001-5] [PMID: 3524984]
[28]
Tibshirani, R. The lasso method for variable selection in the Cox model. Stat. Med., 1997, 16(4), 385-395.
[http://dx.doi.org/10.1002/(SICI)1097-0258(19970228)16:4<385::AID-SIM380>3.0.CO;2-3] [PMID: 9044528]
[29]
Friedman, J.; Hastie, T.; Tibshirani, R. regularization paths for generalized linear models via coordinate descent. J. Stat. Softw., 2010, 33(1), 1-22.
[http://dx.doi.org/10.18637/jss.v033.i01] [PMID: 20808728]
[30]
Yan, T.H.; Yang, H.; Jiang, J.H.; Lu, S.W.; Peng, C.X.; Que, H.X.; Lu, W.L.; Mao, J.F. Prognostic significance of long non-coding RNA PCAT-1 expression in human hepatocellular carcinoma. Int. J. Clin. Exp. Pathol., 2015, 8(4), 4126-4131.
[PMID: 26097602]
[31]
Li, M.; Spakowicz, D.; Burkart, J.; Patel, S.; Husain, M.; He, K.; Bertino, E.M.; Shields, P.G.; Carbone, D.P.; Verschraegen, C.F.; Presley, C.J.; Otterson, G.A.; Kendra, K.; Owen, D.H. Change in neutrophil to lymphocyte ratio during immunotherapy treatment is a non-linear predictor of patient outcomes in advanced cancers. J. Cancer Res. Clin. Oncol., 2019, 145(10), 2541-2546.
[http://dx.doi.org/10.1007/s00432-019-02982-4] [PMID: 31367835]
[32]
Feng, S.S.; Li, H.B.; Fan, F.; Li, J.; Cao, H.; Xia, Z.W.; Yang, K.; Zhu, X.S.; Cheng, T.T.; Cheng, Q. Clinical characteristics and disease-specific prognostic nomogram for primary gliosarcoma: a SEER population-based analysis. Sci. Rep., 2019, 9(1), 10744.
[http://dx.doi.org/10.1038/s41598-019-47211-7] [PMID: 31341246]
[33]
Araújo, T.; Khayat, A.; Quintana, L.; Calcagno, D.; Mourão, R.; Modesto, A.; Paiva, J.; Lima, A.; Moreira, F.; Oliveira, E.; Souza, M.; Othman, M.; Liehr, T.; Abdelhay, E.; Gomes, R.; Santos, S.; Assumpção, P. Piwi like RNA-mediated gene silencing 1 gene as a possible major player in gastric cancer. World J. Gastroenterol., 2018, 24(47), 5338-5350.
[http://dx.doi.org/10.3748/wjg.v24.i47.5338] [PMID: 30598579]
[34]
Yu, G.; Wang, L.G.; Han, Y.; He, Q.Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS, 2012, 16(5), 284-287.
[http://dx.doi.org/10.1089/omi.2011.0118] [PMID: 22455463]
[35]
Tejeda-Maldonado, J.; García-Juárez, I.; Aguirre-Valadez, J.; González-Aguirre, A.; Vilatobá-Chapa, M.; Armengol-Alonso, A.; Escobar-Penagos, F.; Torre, A.; Sánchez-Ávila, J.F.; Carrillo-Pérez, D.L. Diagnosis and treatment of hepatocellular carcinoma: An update. World J. Hepatol., 2015, 7(3), 362-376.
[http://dx.doi.org/10.4254/wjh.v7.i3.362] [PMID: 25848464]
[36]
Grieco, A.; Pompili, M.; Caminiti, G.; Miele, L.; Covino, M.; Alfei, B.; Rapaccini, G.L.; Gasbarrini, G. Prognostic factors for survival in patients with early-intermediate hepatocellular carcinoma undergoing non-surgical therapy: comparison of Okuda, CLIP, and BCLC staging systems in a single Italian centre. Gut, 2005, 54(3), 411-418.
[http://dx.doi.org/10.1136/gut.2004.048124] [PMID: 15710992]
[37]
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.e20.
[http://dx.doi.org/10.1016/j.cell.2018.03.052] [PMID: 29677511]
[38]
Zhang, W.; Wu, Y.; Hou, B.; Wang, Y.; Deng, D.; Fu, Z.; Xu, Z. A SOX9-AS1/miR-5590-3p/SOX9 positive feedback loop drives tumor growth and metastasis in hepatocellular carcinoma through the Wnt/β-catenin pathway. Mol. Oncol., 2019, 13(10), 2194-2210.
[http://dx.doi.org/10.1002/1878-0261.12560] [PMID: 31402556]
[39]
Lan, T.; Yuan, K.; Yan, X.; Xu, L.; Liao, H.; Hao, X.; Wang, J.; Liu, H.; Chen, X.; Xie, K.; Li, J.; Liao, M.; Huang, J.; Zeng, Y.; Wu, H. LncRNA SNHG10 facilitates hepatocarcinogenesis and metastasis by modulating its homolog SCARNA13 via a positive feedback loop. Cancer Res., 2019, 79(13), 3220-3234.
[http://dx.doi.org/10.1158/0008-5472.CAN-18-4044] [PMID: 31101763]
[40]
Wang, F.; Yuan, J.H.; Wang, S.B.; Yang, F.; Yuan, S.X.; Ye, C.; Yang, N.; Zhou, W.P.; Li, W.L.; Li, W.; Sun, S.H. Oncofetal long noncoding RNA PVT1 promotes proliferation and stem cell-like property of hepatocellular carcinoma cells by stabilizing NOP2. Hepatology, 2014, 60(4), 1278-1290.
[http://dx.doi.org/10.1002/hep.27239] [PMID: 25043274]
[41]
Zhu, P.; Wang, Y.; Wu, J.; Huang, G.; Liu, B.; Ye, B.; Du, Y.; Gao, G.; Tian, Y.; He, L.; Fan, Z. LncBRM initiates YAP1 signalling activation to drive self-renewal of liver cancer stem cells. Nat. Commun., 2016, 7, 13608.
[http://dx.doi.org/10.1038/ncomms13608] [PMID: 27905400]
[42]
Chiu, H.S.; Somvanshi, S.; Patel, E.; Chen, T.W.; Singh, V.P.; Zorman, B.; Patil, S.L.; Pan, Y.; Chatterjee, S.S.; Sood, A.K.; Gunaratne, P.H.; Sumazin, P. Cancer Genome Atlas Research Network. Pan-Cancer Analysis of lncRNA regulation supports their targeting of cancer genes in each tumor context. Cell Rep., 2018, 23(1), 297-312.e12.
[http://dx.doi.org/10.1016/j.celrep.2018.03.064] [PMID: 29617668]
[43]
de Jong, J.J.; Liu, Y.; Robertson, A.G.; Seiler, R.; Groeneveld, C.S.; van der Heijden, M.S.; Wright, J.L.; Douglas, J.; Dall’Era, M.; Crabb, S.J.; van Rhijn, B.W.G.; van Kessel, K.E.M.; Davicioni, E.; Castro, M.A.A.; Lotan, Y.; Zwarthoff, E.C.; Black, P.C.; Boormans, J.L.; Gibb, E.A. Long non-coding RNAs identify a subset of luminal muscle-invasive bladder cancer patients with favorable prognosis. Genome Med., 2019, 11(1), 60.
[http://dx.doi.org/10.1186/s13073-019-0669-z] [PMID: 31619281]
[44]
Chen, T.; Zhang, C.; Liu, Y.; Zhao, Y.; Lin, D.; Hu, Y.; Yu, J.; Li, G. A gastric cancer LncRNAs model for MSI and survival prediction based on support vector machine. BMC Genomics, 2019, 20(1), 846.
[http://dx.doi.org/10.1186/s12864-019-6135-x] [PMID: 31722674]
[45]
Zhou, C.; Wang, S.; Zhou, Q.; Zhao, J.; Xia, X.; Chen, W.; Zheng, Y.; Xue, M.; Yang, F.; Fu, D.; Yin, Y.; Atyah, M.; Qin, L.; Zhao, Y.; Bruns, C.; Jia, H.; Ren, N.; Dong, Q. A Long Non-coding RNA signature to improve prognostic prediction of pancreatic ductal adenocarcinoma. Front. Oncol., 2019, 9, 1160.
[http://dx.doi.org/10.3389/fonc.2019.01160] [PMID: 31781487]
[46]
Liu, H.; Sun, Y.; Tian, H.; Xiao, X.; Zhang, J.; Wang, Y.; Yu, F. Characterization of long non-coding RNA and messenger RNA profiles in laryngeal cancer by weighted gene co-expression network analysis. Aging (Albany NY), 2019, 11(22), 10074-10099.
[http://dx.doi.org/10.18632/aging.102419] [PMID: 31739287]
[47]
Hu, J.; Xu, L.; Shou, T.; Chen, Q. Systematic analysis identifies three-lncRNA signature as a potentially prognostic biomarker for lung squamous cell carcinoma using bioinformatics strategy. Transl. Lung Cancer Res., 2019, 8(5), 614-635.
[http://dx.doi.org/10.21037/tlcr.2019.09.13] [PMID: 31737498]
[48]
Ma, X.; Liu, C.; Xu, X.; Liu, L.; Gao, C.; Zhuang, J.; Li, H.; Feng, F.; Zhou, C.; Liu, Z.; Li, J.; Wei, J.; Wang, L.; Sun, C. Biomarker expression analysis in different age groups revealed age was a risk factor for breast cancer. J. Cell. Physiol., 2020, 235(5), 4268-4278.
[http://dx.doi.org/10.1002/jcp.29304] [PMID: 31608996]
[49]
Unfried, J.P.; Serrano, G.; Suárez, B.; Sangro, P.; Ferretti, V.; Prior, C.; Boix, L.; Bruix, J.; Sangro, B.; Segura, V.; Fortes, P. Identification of coding and long noncoding RNAs differentially expressed in tumors and preferentially expressed in healthy tissues. Cancer Res., 2019, 79(20), 5167-5180.
[http://dx.doi.org/10.1158/0008-5472.CAN-19-0400] [PMID: 31387921]
[50]
Ali, M.M.; Akhade, V.S.; Kosalai, S.T.; Subhash, S.; Statello, L.; Meryet-Figuiere, M.; Abrahamsson, J.; Mondal, T.; Kanduri, C. PAN-cancer analysis of S-phase enriched lncRNAs identifies oncogenic drivers and biomarkers. Nat. Commun., 2018, 9(1), 883.
[http://dx.doi.org/10.1038/s41467-018-03265-1] [PMID: 29491376]
[51]
Liu, H.; Zhao, P.; Jin, X.; Zhao, Y.; Chen, Y.; Yan, T.; Wang, J.; Wu, L.; Sun, Y. A 9‑lncRNA risk score system for predicting the prognosis of patients with hepatitis B virus‑positive hepatocellular carcinoma. Mol. Med. Rep., 2019, 20(1), 573-583.
[http://dx.doi.org/10.3892/mmr.2019.10262] [PMID: 31115573]
[52]
Sun, Y.; Zhang, F.; Wang, L.; Song, X.; Jing, J.; Zhang, F.; Yu, S.; Liu, H. A five lncRNA signature for prognosis prediction in hepatocellular carcinoma. Mol. Med. Rep., 2019, 19(6), 5237-5250.
[http://dx.doi.org/10.3892/mmr.2019.10203] [PMID: 31059056]
[53]
Bai, Y.; Long, J.; Liu, Z.; Lin, J.; Huang, H.; Wang, D.; Yang, X.; Miao, F.; Mao, Y.; Sang, X.; Zhao, H. Comprehensive analysis of a ceRNA network reveals potential prognostic cytoplasmic lncRNAs involved in HCC progression. J. Cell. Physiol., 2019, 234(10), 18837-18848.
[http://dx.doi.org/10.1002/jcp.28522] [PMID: 30916406]
[54]
Yang, Z.; Yang, Y.; Zhou, G.; Luo, Y.; Yang, W.; Zhou, Y.; Yang, J. The prediction of survival in hepatocellular carcinoma based on a four long non-coding RNAs expression signature. J. Cancer, 2020, 11(14), 4132-4144.
[http://dx.doi.org/10.7150/jca.40621] [PMID: 32368296]
[55]
Gu, J.X.; Zhang, X.; Miao, R.C.; Xiang, X.H.; Fu, Y.N.; Zhang, J.Y.; Liu, C.; Qu, K. Six-long non-coding RNA signature predicts recurrence-free survival in hepatocellular carcinoma. World J. Gastroenterol., 2019, 25(2), 220-232.
[http://dx.doi.org/10.3748/wjg.v25.i2.220] [PMID: 30670911]
[56]
Liao, X.; Wang, X.; Huang, K.; Han, C.; Deng, J.; Yu, T.; Yang, C.; Huang, R.; Liu, X.; Yu, L.; Zhu, G.; Su, H.; Qin, W.; Zeng, X.; Han, B.; Han, Q.; Liu, Z.; Zhou, X.; Gong, Y.; Liu, Z.; Huang, J.; Winkler, C.A.; O’Brien, S.J.; Ye, X.; Peng, T. Integrated analysis of competing endogenous RNA network revealing potential prognostic biomarkers of hepatocellular carcinoma. J. Cancer, 2019, 10(14), 3267-3283.
[http://dx.doi.org/10.7150/jca.29986] [PMID: 31289599]
[57]
Yue, C.; Ren, Y.; Ge, H.; Liang, C.; Xu, Y.; Li, G.; Wu, J. Comprehensive analysis of potential prognostic genes for the construction of a competing endogenous RNA regulatory network in hepatocellular carcinoma. OncoTargets Ther., 2019, 12, 561-576.
[http://dx.doi.org/10.2147/OTT.S188913] [PMID: 30679912]
[58]
Wang, Y.; Fu, J.; Wang, Z.; Lv, Z.; Fan, Z.; Lei, T. Screening key lncRNAs for human lung adenocarcinoma based on machine learning and weighted gene co-expression network analysis. Cancer Biomark., 2019, 25(4), 313-324.
[http://dx.doi.org/10.3233/CBM-190225] [PMID: 31322548]
[59]
Liu, Y.; Zhu, J.; Ma, X.; Han, S.; Xiao, D.; Jia, Y.; Wang, Y. ceRNA network construction and comparison of gastric cancer with or without Helicobacter pylori infection. J. Cell. Physiol., 2019, 234(5), 7128-7140.
[http://dx.doi.org/10.1002/jcp.27467] [PMID: 30370523]
[60]
Chen, W.J.; Tang, R.X.; He, R.Q.; Li, D.Y.; Liang, L.; Zeng, J.H.; Hu, X.H.; Ma, J.; Li, S.K.; Chen, G. Clinical roles of the aberrantly expressed lncRNAs in lung squamous cell carcinoma: a study based on RNA-sequencing and microarray data mining. Oncotarget, 2017, 8(37), 61282-61304.
[http://dx.doi.org/10.18632/oncotarget.18058] [PMID: 28977863]
[61]
Yang, X.; Yang, J.; Wang, J.; Wen, Q.; Wang, H.; He, J.; Hu, S.; He, W.; Du, X.; Liu, S.; Ma, L. Microarray analysis of long noncoding RNA and mRNA expression profiles in human macrophages infected with Mycobacterium tuberculosis. Sci. Rep., 2016, 6, 38963.
[http://dx.doi.org/10.1038/srep38963] [PMID: 27966580]
[62]
Sakamoto, Y.; Yamamoto, T.; Sugano, N.; Takahashi, D.; Watanabe, T.; Atsumi, T.; Nakamura, J.; Hasegawa, Y.; Akashi, K.; Narita, I.; Miyamoto, T.; Takeuchi, T.; Ikari, K.; Amano, K.; Fujie, A.; Kubo, T.; Tada, Y.; Kaneuji, A.; Nakamura, H.; Miyamura, T.; Kabata, T.; Yamaji, K.; Okawa, T.; Sudo, A.; Ohzono, K.; Tanaka, Y.; Yasunaga, Y.; Matsuda, S.; Imai, Y. Japanese Research Committee on Idiopathic Osteonecrosis of the Femoral, H.; Akiyama, M.; Kubo, M.; Kamatani, Y.; Iwamoto, Y.; Ikegawa, S. Genome-wide association study of idiopathic osteonecrosis of the femoral head. Sci. Rep., 2017, 7(1), 15035.
[http://dx.doi.org/10.1038/s41598-017-14778-y] [PMID: 29118346]
[63]
Ma, P.Y.; Mao, X.; Tey, S.; Ko, C.F.; Yam, J.W.P. The clinical relevance functional role of ACADM in Hepatocellular Carcinoma. 25th Biennial Congress of the European Association for Cancer Research (EACR25), Amsterdam, Netherlands30 June-3 July 2018

Rights & Permissions Print Cite
Article Metrics
33
1
© 2024 Bentham Science Publishers | Privacy Policy