Comprehensive analyses of correlation and survival reveal informative lncRNA prognostic signatures in colon cancer
Background Colon cancer is a commonly worldwide cancer with high morbidity and mortality. Long non-coding RNAs (lncRNAs) are involved in many biological processes and are closely related to the occurrence of colon cancer. Identification of the prognostic signatures of lncRNAs in colon cancer has gre...
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| Veröffentlicht in: | World journal of surgical oncology Jg. 19; H. 1; S. 104 - 15 |
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BioMed Central
09.04.2021
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| Abstract | Background
Colon cancer is a commonly worldwide cancer with high morbidity and mortality. Long non-coding RNAs (lncRNAs) are involved in many biological processes and are closely related to the occurrence of colon cancer. Identification of the prognostic signatures of lncRNAs in colon cancer has great significance for its treatment.
Methods
We first identified the colon cancer-related mRNAs and lncRNAs according to the differential analysis methods using the expression data in TCGA. Then, we performed correlation analysis between the identified mRNAs and lncRNAs by integrating their expression values and secondary structure information to estimate the co-regulatory relationships between the cancer-related mRNAs and lncRNAs. Besides, the competing endogenous RNA regulation network based on co-regulatory relationships was constructed to reveal cancer-related regulatory patterns. Meanwhile, we used traditional regression analysis (univariate Cox analysis, random survival forest analysis, and lasso regression analysis) to screen the cancer-related lncRNAs. Finally, by combining the identified colon cancer-related lncRNAs according to the above analyses, we constructed a risk prognosis model for colon cancer through multivariate Cox analysis and also validated the model in the colon cancer dataset in TCGA cohorts.
Results
Six lncRNAs were found highly correlated with the overall survival of colon cancer patients, and a risk prognosis model based on them was constructed to predict the overall survival of colon cancer patients. In particular, EVX1-AS, ZNF667-AS1, CTC-428G20.6, and CTC-297N7.9 were first reported to be related to colon cancer by using our model, among which EVX1-AS and ZNF667-AS1 have been predicted to be related to colon cancer in LncRNADisease database.
Conclusions
This study identified the potential regulatory relationships between lncRNAs and mRNAs by integrating their expression values and secondary structure information and presented a significant 6-lncRNA risk prognosis model to predict the overall survival of colon cancer patients. |
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| AbstractList | Background Colon cancer is a commonly worldwide cancer with high morbidity and mortality. Long non-coding RNAs (lncRNAs) are involved in many biological processes and are closely related to the occurrence of colon cancer. Identification of the prognostic signatures of lncRNAs in colon cancer has great significance for its treatment. Methods We first identified the colon cancer-related mRNAs and lncRNAs according to the differential analysis methods using the expression data in TCGA. Then, we performed correlation analysis between the identified mRNAs and lncRNAs by integrating their expression values and secondary structure information to estimate the co-regulatory relationships between the cancer-related mRNAs and lncRNAs. Besides, the competing endogenous RNA regulation network based on co-regulatory relationships was constructed to reveal cancer-related regulatory patterns. Meanwhile, we used traditional regression analysis (univariate Cox analysis, random survival forest analysis, and lasso regression analysis) to screen the cancer-related lncRNAs. Finally, by combining the identified colon cancer-related lncRNAs according to the above analyses, we constructed a risk prognosis model for colon cancer through multivariate Cox analysis and also validated the model in the colon cancer dataset in TCGA cohorts. Results Six lncRNAs were found highly correlated with the overall survival of colon cancer patients, and a risk prognosis model based on them was constructed to predict the overall survival of colon cancer patients. In particular, EVX1-AS, ZNF667-AS1, CTC-428G20.6, and CTC-297N7.9 were first reported to be related to colon cancer by using our model, among which EVX1-AS and ZNF667-AS1 have been predicted to be related to colon cancer in LncRNADisease database. Conclusions This study identified the potential regulatory relationships between lncRNAs and mRNAs by integrating their expression values and secondary structure information and presented a significant 6-lncRNA risk prognosis model to predict the overall survival of colon cancer patients. Keywords: Long non-coding RNAs, Secondary structure information, Regression analysis, Regulatory patterns, Risk prognosis model, Overall survival Colon cancer is a commonly worldwide cancer with high morbidity and mortality. Long non-coding RNAs (lncRNAs) are involved in many biological processes and are closely related to the occurrence of colon cancer. Identification of the prognostic signatures of lncRNAs in colon cancer has great significance for its treatment.BACKGROUNDColon cancer is a commonly worldwide cancer with high morbidity and mortality. Long non-coding RNAs (lncRNAs) are involved in many biological processes and are closely related to the occurrence of colon cancer. Identification of the prognostic signatures of lncRNAs in colon cancer has great significance for its treatment.We first identified the colon cancer-related mRNAs and lncRNAs according to the differential analysis methods using the expression data in TCGA. Then, we performed correlation analysis between the identified mRNAs and lncRNAs by integrating their expression values and secondary structure information to estimate the co-regulatory relationships between the cancer-related mRNAs and lncRNAs. Besides, the competing endogenous RNA regulation network based on co-regulatory relationships was constructed to reveal cancer-related regulatory patterns. Meanwhile, we used traditional regression analysis (univariate Cox analysis, random survival forest analysis, and lasso regression analysis) to screen the cancer-related lncRNAs. Finally, by combining the identified colon cancer-related lncRNAs according to the above analyses, we constructed a risk prognosis model for colon cancer through multivariate Cox analysis and also validated the model in the colon cancer dataset in TCGA cohorts.METHODSWe first identified the colon cancer-related mRNAs and lncRNAs according to the differential analysis methods using the expression data in TCGA. Then, we performed correlation analysis between the identified mRNAs and lncRNAs by integrating their expression values and secondary structure information to estimate the co-regulatory relationships between the cancer-related mRNAs and lncRNAs. Besides, the competing endogenous RNA regulation network based on co-regulatory relationships was constructed to reveal cancer-related regulatory patterns. Meanwhile, we used traditional regression analysis (univariate Cox analysis, random survival forest analysis, and lasso regression analysis) to screen the cancer-related lncRNAs. Finally, by combining the identified colon cancer-related lncRNAs according to the above analyses, we constructed a risk prognosis model for colon cancer through multivariate Cox analysis and also validated the model in the colon cancer dataset in TCGA cohorts.Six lncRNAs were found highly correlated with the overall survival of colon cancer patients, and a risk prognosis model based on them was constructed to predict the overall survival of colon cancer patients. In particular, EVX1-AS, ZNF667-AS1, CTC-428G20.6, and CTC-297N7.9 were first reported to be related to colon cancer by using our model, among which EVX1-AS and ZNF667-AS1 have been predicted to be related to colon cancer in LncRNADisease database.RESULTSSix lncRNAs were found highly correlated with the overall survival of colon cancer patients, and a risk prognosis model based on them was constructed to predict the overall survival of colon cancer patients. In particular, EVX1-AS, ZNF667-AS1, CTC-428G20.6, and CTC-297N7.9 were first reported to be related to colon cancer by using our model, among which EVX1-AS and ZNF667-AS1 have been predicted to be related to colon cancer in LncRNADisease database.This study identified the potential regulatory relationships between lncRNAs and mRNAs by integrating their expression values and secondary structure information and presented a significant 6-lncRNA risk prognosis model to predict the overall survival of colon cancer patients.CONCLUSIONSThis study identified the potential regulatory relationships between lncRNAs and mRNAs by integrating their expression values and secondary structure information and presented a significant 6-lncRNA risk prognosis model to predict the overall survival of colon cancer patients. Background Colon cancer is a commonly worldwide cancer with high morbidity and mortality. Long non-coding RNAs (lncRNAs) are involved in many biological processes and are closely related to the occurrence of colon cancer. Identification of the prognostic signatures of lncRNAs in colon cancer has great significance for its treatment. Methods We first identified the colon cancer-related mRNAs and lncRNAs according to the differential analysis methods using the expression data in TCGA. Then, we performed correlation analysis between the identified mRNAs and lncRNAs by integrating their expression values and secondary structure information to estimate the co-regulatory relationships between the cancer-related mRNAs and lncRNAs. Besides, the competing endogenous RNA regulation network based on co-regulatory relationships was constructed to reveal cancer-related regulatory patterns. Meanwhile, we used traditional regression analysis (univariate Cox analysis, random survival forest analysis, and lasso regression analysis) to screen the cancer-related lncRNAs. Finally, by combining the identified colon cancer-related lncRNAs according to the above analyses, we constructed a risk prognosis model for colon cancer through multivariate Cox analysis and also validated the model in the colon cancer dataset in TCGA cohorts. Results Six lncRNAs were found highly correlated with the overall survival of colon cancer patients, and a risk prognosis model based on them was constructed to predict the overall survival of colon cancer patients. In particular, EVX1-AS, ZNF667-AS1, CTC-428G20.6, and CTC-297N7.9 were first reported to be related to colon cancer by using our model, among which EVX1-AS and ZNF667-AS1 have been predicted to be related to colon cancer in LncRNADisease database. Conclusions This study identified the potential regulatory relationships between lncRNAs and mRNAs by integrating their expression values and secondary structure information and presented a significant 6-lncRNA risk prognosis model to predict the overall survival of colon cancer patients. Colon cancer is a commonly worldwide cancer with high morbidity and mortality. Long non-coding RNAs (lncRNAs) are involved in many biological processes and are closely related to the occurrence of colon cancer. Identification of the prognostic signatures of lncRNAs in colon cancer has great significance for its treatment. We first identified the colon cancer-related mRNAs and lncRNAs according to the differential analysis methods using the expression data in TCGA. Then, we performed correlation analysis between the identified mRNAs and lncRNAs by integrating their expression values and secondary structure information to estimate the co-regulatory relationships between the cancer-related mRNAs and lncRNAs. Besides, the competing endogenous RNA regulation network based on co-regulatory relationships was constructed to reveal cancer-related regulatory patterns. Meanwhile, we used traditional regression analysis (univariate Cox analysis, random survival forest analysis, and lasso regression analysis) to screen the cancer-related lncRNAs. Finally, by combining the identified colon cancer-related lncRNAs according to the above analyses, we constructed a risk prognosis model for colon cancer through multivariate Cox analysis and also validated the model in the colon cancer dataset in TCGA cohorts. Six lncRNAs were found highly correlated with the overall survival of colon cancer patients, and a risk prognosis model based on them was constructed to predict the overall survival of colon cancer patients. In particular, EVX1-AS, ZNF667-AS1, CTC-428G20.6, and CTC-297N7.9 were first reported to be related to colon cancer by using our model, among which EVX1-AS and ZNF667-AS1 have been predicted to be related to colon cancer in LncRNADisease database. This study identified the potential regulatory relationships between lncRNAs and mRNAs by integrating their expression values and secondary structure information and presented a significant 6-lncRNA risk prognosis model to predict the overall survival of colon cancer patients. Abstract Background Colon cancer is a commonly worldwide cancer with high morbidity and mortality. Long non-coding RNAs (lncRNAs) are involved in many biological processes and are closely related to the occurrence of colon cancer. Identification of the prognostic signatures of lncRNAs in colon cancer has great significance for its treatment. Methods We first identified the colon cancer-related mRNAs and lncRNAs according to the differential analysis methods using the expression data in TCGA. Then, we performed correlation analysis between the identified mRNAs and lncRNAs by integrating their expression values and secondary structure information to estimate the co-regulatory relationships between the cancer-related mRNAs and lncRNAs. Besides, the competing endogenous RNA regulation network based on co-regulatory relationships was constructed to reveal cancer-related regulatory patterns. Meanwhile, we used traditional regression analysis (univariate Cox analysis, random survival forest analysis, and lasso regression analysis) to screen the cancer-related lncRNAs. Finally, by combining the identified colon cancer-related lncRNAs according to the above analyses, we constructed a risk prognosis model for colon cancer through multivariate Cox analysis and also validated the model in the colon cancer dataset in TCGA cohorts. Results Six lncRNAs were found highly correlated with the overall survival of colon cancer patients, and a risk prognosis model based on them was constructed to predict the overall survival of colon cancer patients. In particular, EVX1-AS, ZNF667-AS1, CTC-428G20.6, and CTC-297N7.9 were first reported to be related to colon cancer by using our model, among which EVX1-AS and ZNF667-AS1 have been predicted to be related to colon cancer in LncRNADisease database. Conclusions This study identified the potential regulatory relationships between lncRNAs and mRNAs by integrating their expression values and secondary structure information and presented a significant 6-lncRNA risk prognosis model to predict the overall survival of colon cancer patients. Colon cancer is a commonly worldwide cancer with high morbidity and mortality. Long non-coding RNAs (lncRNAs) are involved in many biological processes and are closely related to the occurrence of colon cancer. Identification of the prognostic signatures of lncRNAs in colon cancer has great significance for its treatment. We first identified the colon cancer-related mRNAs and lncRNAs according to the differential analysis methods using the expression data in TCGA. Then, we performed correlation analysis between the identified mRNAs and lncRNAs by integrating their expression values and secondary structure information to estimate the co-regulatory relationships between the cancer-related mRNAs and lncRNAs. Besides, the competing endogenous RNA regulation network based on co-regulatory relationships was constructed to reveal cancer-related regulatory patterns. Meanwhile, we used traditional regression analysis (univariate Cox analysis, random survival forest analysis, and lasso regression analysis) to screen the cancer-related lncRNAs. Finally, by combining the identified colon cancer-related lncRNAs according to the above analyses, we constructed a risk prognosis model for colon cancer through multivariate Cox analysis and also validated the model in the colon cancer dataset in TCGA cohorts. Six lncRNAs were found highly correlated with the overall survival of colon cancer patients, and a risk prognosis model based on them was constructed to predict the overall survival of colon cancer patients. In particular, EVX1-AS, ZNF667-AS1, CTC-428G20.6, and CTC-297N7.9 were first reported to be related to colon cancer by using our model, among which EVX1-AS and ZNF667-AS1 have been predicted to be related to colon cancer in LncRNADisease database. This study identified the potential regulatory relationships between lncRNAs and mRNAs by integrating their expression values and secondary structure information and presented a significant 6-lncRNA risk prognosis model to predict the overall survival of colon cancer patients. Background Colon cancer is a commonly worldwide cancer with high morbidity and mortality. Long non-coding RNAs (lncRNAs) are involved in many biological processes and are closely related to the occurrence of colon cancer. Identification of the prognostic signatures of lncRNAs in colon cancer has great significance for its treatment. Methods We first identified the colon cancer-related mRNAs and lncRNAs according to the differential analysis methods using the expression data in TCGA. Then, we performed correlation analysis between the identified mRNAs and lncRNAs by integrating their expression values and secondary structure information to estimate the co-regulatory relationships between the cancer-related mRNAs and lncRNAs. Besides, the competing endogenous RNA regulation network based on co-regulatory relationships was constructed to reveal cancer-related regulatory patterns. Meanwhile, we used traditional regression analysis (univariate Cox analysis, random survival forest analysis, and lasso regression analysis) to screen the cancer-related lncRNAs. Finally, by combining the identified colon cancer-related lncRNAs according to the above analyses, we constructed a risk prognosis model for colon cancer through multivariate Cox analysis and also validated the model in the colon cancer dataset in TCGA cohorts. Results Six lncRNAs were found highly correlated with the overall survival of colon cancer patients, and a risk prognosis model based on them was constructed to predict the overall survival of colon cancer patients. In particular, EVX1-AS, ZNF667-AS1, CTC-428G20.6, and CTC-297N7.9 were first reported to be related to colon cancer by using our model, among which EVX1-AS and ZNF667-AS1 have been predicted to be related to colon cancer in LncRNADisease database. Conclusions This study identified the potential regulatory relationships between lncRNAs and mRNAs by integrating their expression values and secondary structure information and presented a significant 6-lncRNA risk prognosis model to predict the overall survival of colon cancer patients. |
| ArticleNumber | 104 |
| Audience | Academic |
| Author | Shang, Xuequn Xiao, Yifu Guo, Yang Gao, Meihong |
| Author_xml | – sequence: 1 givenname: Meihong surname: Gao fullname: Gao, Meihong organization: School of Computer Science and Engineering, Northwestern Polytechnical University – sequence: 2 givenname: Yang surname: Guo fullname: Guo, Yang organization: School of Computer Science and Engineering, Northwestern Polytechnical University – sequence: 3 givenname: Yifu surname: Xiao fullname: Xiao, Yifu organization: School of Computer Science and Engineering, Northwestern Polytechnical University – sequence: 4 givenname: Xuequn surname: Shang fullname: Shang, Xuequn email: shang@nwpu.edu.cn organization: School of Computer Science and Engineering, Northwestern Polytechnical University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33836755$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1093/bioinformatics/btt426 10.1109/BIBE.2018.00060 10.1101/gr.1239303 10.1136/bmj.g7327 10.1038/s41598-016-0001-8 10.1093/nar/gky1096 10.1002/jcp.29360 10.1007/BF00818163 10.1186/1748-7188-6-26 10.1016/j.ctrv.2003.07.007 10.1038/nrg3074 10.3322/caac.21492 10.1111/j.2517-6161.1995.tb02031.x 10.1016/j.ebiom.2019.09.037 10.1093/nar/gkaa845 10.1016/j.molcel.2017.01.023 10.3389/fonc.2019.01269 10.1109/TCBB.2020.3040706 10.1109/TCBB.2017.2687442 10.1002/cam4.1813 10.1093/nar/gkv007 10.3390/cells8091015 10.1038/35094067 10.1186/s12881-019-0812-0 10.3390/ijms18010197 10.1002/jcp.26383 10.1016/j.molcel.2017.09.015 10.1111/j.1467-789X.2009.00607.x 10.1038/nature06005 10.1093/bioinformatics/bty525 10.1002/jcb.27630 10.1186/s12967-018-1725-y 10.1186/s12957-020-01921-9 10.1093/nar/gkx279 10.3389/fonc.2019.00712 10.1002/jcb.27195 10.1093/nar/gkv233 10.1016/j.bbagrm.2014.08.012 10.1101/cshperspect.a006098 10.1186/1471-2105-15-S6-S6 10.1002/cbin.11196 10.1002/jcb.26548 10.1016/j.biopha.2019.109079 10.1038/nature12943 10.1634/theoncologist.2009-0233 10.1016/S1470-2045(05)70422-8 10.1097/IGC.0000000000000828 10.1038/nrm.2017.104 10.2147/OTT.S158309 |
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| Keywords | Risk prognosis model Secondary structure information Long non-coding RNAs Regression analysis Overall survival Regulatory patterns |
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| PublicationTitle | World journal of surgical oncology |
| PublicationTitleAbbrev | World J Surg Onc |
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| PublicationYear | 2021 |
| Publisher | BioMed Central BioMed Central Ltd BMC |
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| References | R Lorenz (2196_CR43) 2011; 6 Q Fan (2196_CR34) 2018; 119 Q Fan (2196_CR25) 2018; 11 RJ Xavier (2196_CR4) 2007; 448 M Ali (2196_CR8) 2019; 20 Y Li (2196_CR23) 2019; 16 J Zhang (2196_CR16) 2018; 34 X Zhao (2196_CR22) 2020; PP Q Wu (2196_CR30) 2018; 233 TM Therneau (2196_CR45) 2013 Y Liu (2196_CR33) 2019; 9 H Zhang (2196_CR26) 2019; 8 M Esteller (2196_CR13) 2011; 12 C Ziegenhain (2196_CR31) 2017; 65 P Cheng (2196_CR36) 2018; 119 IL Hofacker (2196_CR42) 1994; 125 W Zhou (2196_CR35) 2019; 18 J-Z Huang (2196_CR28) 2017; 68 X-F Huang (2196_CR47) 2009; 10 R Fodde (2196_CR52) 2001; 1 FI Bray (2196_CR1) 2018; 68 R Sever (2196_CR51) 2015; 5 JD Ransohoff (2196_CR18) 2018; 19 Y Gao (2196_CR20) 2019; 47 JÁF Vara (2196_CR53) 2004; 30 H Ren (2196_CR46) 2020; 235 P Shannon (2196_CR44) 2003; 13 A Necsulea (2196_CR19) 2014; 505 F Tatangelo (2196_CR27) 2018; 16 J Zhang (2196_CR37) 2019; 118 I Marmol (2196_CR9) 2017; 18 JJY Sung (2196_CR2) 2005; 6 F Emmert-Streib (2196_CR6) 2014; 15 M Cui (2196_CR29) 2019; 120 Y Yang (2196_CR48) 2019; 43 P Wang (2196_CR15) 2015; 43 G Yang (2196_CR17) 2014; 1839 H Zhao (2196_CR21) 2020; 48 X Chen (2196_CR10) 2013; 29 J Sun (2196_CR50) 2016; 6 M Mann (2196_CR24) 2017; 45 Y Benjamini (2196_CR40) 1995; 57 Y Chi (2196_CR14) 2019; 8 ME Ritchie (2196_CR39) 2015; 43 P Sedgwick (2196_CR41) 2014; 349 Y Zhong (2196_CR11) 2016; 26 S Tejpar (2196_CR5) 2010; 15 2196_CR38 F Zhou (2196_CR49) 2019; 23 2196_CR3 S Chen (2196_CR7) 2020; 18 Y Jiang (2196_CR12) 2019; 48 Q Huang (2196_CR32) 2019; 9 |
| References_xml | – volume: 29 start-page: 2617 issue: 20 year: 2013 ident: 2196_CR10 publication-title: Bioinformatics doi: 10.1093/bioinformatics/btt426 – ident: 2196_CR38 doi: 10.1109/BIBE.2018.00060 – volume: 13 start-page: 2498 issue: 11 year: 2003 ident: 2196_CR44 publication-title: Genome Res doi: 10.1101/gr.1239303 – volume: 349 start-page: 7327 year: 2014 ident: 2196_CR41 publication-title: Bmj doi: 10.1136/bmj.g7327 – volume: 6 start-page: 1 issue: 1 year: 2016 ident: 2196_CR50 publication-title: Sci Rep doi: 10.1038/s41598-016-0001-8 – volume: 47 start-page: 1028 year: 2019 ident: 2196_CR20 publication-title: Nucleic Acids Res doi: 10.1093/nar/gky1096 – volume: 235 start-page: 4824 issue: 5 year: 2020 ident: 2196_CR46 publication-title: J Cell Physiol doi: 10.1002/jcp.29360 – volume: 125 start-page: 167 issue: 2 year: 1994 ident: 2196_CR42 publication-title: Monatsh Chem doi: 10.1007/BF00818163 – volume: 6 start-page: 26 issue: 1 year: 2011 ident: 2196_CR43 publication-title: Algorithms Mol Biol doi: 10.1186/1748-7188-6-26 – volume: 30 start-page: 193 issue: 2 year: 2004 ident: 2196_CR53 publication-title: Cancer Treat Rev doi: 10.1016/j.ctrv.2003.07.007 – volume: 12 start-page: 861 issue: 12 year: 2011 ident: 2196_CR13 publication-title: Nat Rev Genet doi: 10.1038/nrg3074 – volume: 68 start-page: 394 issue: 6 year: 2018 ident: 2196_CR1 publication-title: CA Cancer J Clin doi: 10.3322/caac.21492 – volume: 57 start-page: 289 issue: 1 year: 1995 ident: 2196_CR40 publication-title: J R Stat Soc Ser B Methodol doi: 10.1111/j.2517-6161.1995.tb02031.x – volume: 48 start-page: 36 year: 2019 ident: 2196_CR12 publication-title: EBioMedicine doi: 10.1016/j.ebiom.2019.09.037 – volume: 48 start-page: 118 year: 2020 ident: 2196_CR21 publication-title: Nucleic Acids Res doi: 10.1093/nar/gkaa845 – volume: 65 start-page: 631 issue: 4 year: 2017 ident: 2196_CR31 publication-title: Mol Cell doi: 10.1016/j.molcel.2017.01.023 – volume: 9 start-page: 1269 year: 2019 ident: 2196_CR33 publication-title: Front Oncol doi: 10.3389/fonc.2019.01269 – volume: PP start-page: 1 issue: 99 year: 2020 ident: 2196_CR22 publication-title: IEEE/ACM Trans Comput Biol Bioinforma doi: 10.1109/TCBB.2020.3040706 – volume: 16 start-page: 1288 issue: 4 year: 2019 ident: 2196_CR23 publication-title: IEEE/ACM Trans Comput Biol Bioinforma doi: 10.1109/TCBB.2017.2687442 – volume: 8 start-page: 863 issue: 3 year: 2019 ident: 2196_CR26 publication-title: Cancer Med doi: 10.1002/cam4.1813 – ident: 2196_CR3 – volume: 43 start-page: e47 issue: 7 year: 2015 ident: 2196_CR39 publication-title: Nucleic Acids Res doi: 10.1093/nar/gkv007 – volume: 8 start-page: 1015 issue: 9 year: 2019 ident: 2196_CR14 publication-title: Cells doi: 10.3390/cells8091015 – volume: 1 start-page: 55 issue: 1 year: 2001 ident: 2196_CR52 publication-title: Nat Rev Cancer doi: 10.1038/35094067 – volume: 23 start-page: 3742 issue: 9 year: 2019 ident: 2196_CR49 publication-title: Eur Rev Med Pharmacol Scie – volume: 20 start-page: 1 issue: 1 year: 2019 ident: 2196_CR8 publication-title: BMC Med Genet doi: 10.1186/s12881-019-0812-0 – volume: 18 start-page: 197 issue: 1 year: 2017 ident: 2196_CR9 publication-title: Int J Mol Sci doi: 10.3390/ijms18010197 – volume: 233 start-page: 6750 issue: 9 year: 2018 ident: 2196_CR30 publication-title: J Cell Physiol doi: 10.1002/jcp.26383 – volume: 68 start-page: 171 issue: 1 year: 2017 ident: 2196_CR28 publication-title: Mol Cell doi: 10.1016/j.molcel.2017.09.015 – volume: 10 start-page: 610 issue: 6 year: 2009 ident: 2196_CR47 publication-title: Obes Rev doi: 10.1111/j.1467-789X.2009.00607.x – volume: 448 start-page: 427 issue: 7152 year: 2007 ident: 2196_CR4 publication-title: Nature doi: 10.1038/nature06005 – volume: 34 start-page: 4232 issue: 24 year: 2018 ident: 2196_CR16 publication-title: Bioinformatics doi: 10.1093/bioinformatics/bty525 – volume: 120 start-page: 6926 issue: 5 year: 2019 ident: 2196_CR29 publication-title: J Cell Biochem doi: 10.1002/jcb.27630 – volume: 16 start-page: 350 issue: 1 year: 2018 ident: 2196_CR27 publication-title: J Transl Med doi: 10.1186/s12967-018-1725-y – volume: 18 start-page: 1 issue: 1 year: 2020 ident: 2196_CR7 publication-title: World J Surg Oncol doi: 10.1186/s12957-020-01921-9 – volume: 45 start-page: 435 year: 2017 ident: 2196_CR24 publication-title: Nucleic Acids Res doi: 10.1093/nar/gkx279 – volume: 9 start-page: 712 year: 2019 ident: 2196_CR32 publication-title: Front Oncol doi: 10.3389/fonc.2019.00712 – volume: 119 start-page: 9261 issue: 2 year: 2018 ident: 2196_CR36 publication-title: J Cell Biochem doi: 10.1002/jcb.27195 – volume-title: Modeling survival data: extending the Cox Model year: 2013 ident: 2196_CR45 – volume: 43 start-page: 3478 issue: 7 year: 2015 ident: 2196_CR15 publication-title: Nucleic Acids Res doi: 10.1093/nar/gkv233 – volume: 18 start-page: 3705 issue: 4 year: 2019 ident: 2196_CR35 publication-title: Oncol Lett – volume: 1839 start-page: 1097 issue: 11 year: 2014 ident: 2196_CR17 publication-title: Biochim Biophys Acta (BBA)-Gene Regul Mech doi: 10.1016/j.bbagrm.2014.08.012 – volume: 5 start-page: 006098 issue: 4 year: 2015 ident: 2196_CR51 publication-title: Cold Spring Harb Perspect Med doi: 10.1101/cshperspect.a006098 – volume: 15 start-page: 6 issue: S6 year: 2014 ident: 2196_CR6 publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-15-S6-S6 – volume: 43 start-page: 1463 issue: 12 year: 2019 ident: 2196_CR48 publication-title: Cell Biol Int doi: 10.1002/cbin.11196 – volume: 119 start-page: 3574 year: 2018 ident: 2196_CR34 publication-title: J Cell Biochem doi: 10.1002/jcb.26548 – volume: 118 start-page: 109079 year: 2019 ident: 2196_CR37 publication-title: Biomed Pharmacother doi: 10.1016/j.biopha.2019.109079 – volume: 505 start-page: 635 issue: 7485 year: 2014 ident: 2196_CR19 publication-title: Nature doi: 10.1038/nature12943 – volume: 15 start-page: 390 issue: 4 year: 2010 ident: 2196_CR5 publication-title: Oncologist doi: 10.1634/theoncologist.2009-0233 – volume: 6 start-page: 871 issue: 11 year: 2005 ident: 2196_CR2 publication-title: Lancet Oncol doi: 10.1016/S1470-2045(05)70422-8 – volume: 26 start-page: 1564 issue: 9 year: 2016 ident: 2196_CR11 publication-title: Int J Gynecol Cancer doi: 10.1097/IGC.0000000000000828 – volume: 19 start-page: 143 issue: 3 year: 2018 ident: 2196_CR18 publication-title: Nat Rev Mol Cell Biol doi: 10.1038/nrm.2017.104 – volume: 11 start-page: 2453 year: 2018 ident: 2196_CR25 publication-title: OncoTargets Ther doi: 10.2147/OTT.S158309 |
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| Snippet | Background
Colon cancer is a commonly worldwide cancer with high morbidity and mortality. Long non-coding RNAs (lncRNAs) are involved in many biological... Colon cancer is a commonly worldwide cancer with high morbidity and mortality. Long non-coding RNAs (lncRNAs) are involved in many biological processes and are... Background Colon cancer is a commonly worldwide cancer with high morbidity and mortality. Long non-coding RNAs (lncRNAs) are involved in many biological... Abstract Background Colon cancer is a commonly worldwide cancer with high morbidity and mortality. Long non-coding RNAs (lncRNAs) are involved in many... |
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| SubjectTerms | Biological activity Biomarkers, Tumor - genetics Cancer Cancer therapies Care and treatment Colon Colon cancer Colonic Neoplasms - genetics Colorectal cancer Construction Correlation analysis Current Evidence and Future Directions in the Treatment of Colorectal Cancer Development and progression Gene expression Gene Expression Regulation, Neoplastic Gene Regulatory Networks Genes Genetic aspects Health aspects Humans Kaplan-Meier Estimate Long non-coding RNAs Medical prognosis Medicine Medicine & Public Health MicroRNAs Model testing Morbidity Non-coding RNA Overall survival Prognosis Protein structure Regression analysis Regulatory patterns Risk Risk prognosis model RNA, Long Noncoding - genetics Secondary structure Secondary structure information Signatures Software Surgical Oncology Survival |
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| Title | Comprehensive analyses of correlation and survival reveal informative lncRNA prognostic signatures in colon cancer |
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