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Discovery and Validation of a Novel Metastasis-Related lncRNA Prognostic Signature for Colorectal Cancer
Background: Cancer metastasis-related chemoresistance and tumour progression are the leading causes of death among CRC patients. Therefore, it is urgent to identify reliable novel biomarkers for predicting the metastasis of CRC. Methods: The gene expression and corresponding clinical data of CRC pat...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9162157/ https://www.ncbi.nlm.nih.gov/pubmed/35664303 http://dx.doi.org/10.3389/fgene.2022.704988 |
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author | Tang, Qiang Hu, Xin Guo, Qiong Shi, Yueyue Liu, Liming Ying, Guoguang |
author_facet | Tang, Qiang Hu, Xin Guo, Qiong Shi, Yueyue Liu, Liming Ying, Guoguang |
author_sort | Tang, Qiang |
collection | PubMed |
description | Background: Cancer metastasis-related chemoresistance and tumour progression are the leading causes of death among CRC patients. Therefore, it is urgent to identify reliable novel biomarkers for predicting the metastasis of CRC. Methods: The gene expression and corresponding clinical data of CRC patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Univariate and multivariate analyses were performed to identify prognostic metastasis-related lncRNAs. Nomograms were constructed, and the predictive accuracy of the nomogram model was assessed by ROC curve analysis. Then, the R package “pRRophetic” was used to predict chemotherapeutic response in CRC patients. In addition, the CIBERSORT database was introduced to evaluate tumour infiltrating immune cells between the high—and low-risk groups. The potential roles of SNHG7 and ZEB1-AS1 in CRC cell lines were further confirmed by in vitro experiments. Results: An 8-lncRNA (LINC00261, RP1-170O19.17, CAPN10-AS1, SNHG7, ZEB1-AS1, U47924.27, NIFK-AS1, and LINC00925) signature was constructed for CRC prognosis prediction, which stratified patients into two risk groups. Kaplan-Meier analysis revealed that patients in the higher-risk group had a lower survival probability than those in the lower-risk group [p < 0.001 (TCGA); P = 0.044 (GSE39582); and P = 0.0078 (GSE29621)] The AUCs of 1-, 3-, and 5-year survival were 0.678, 0.669, and 0.72 in TCGA; 0.58, 0.55, and 0.56 in GSE39582; and 0.75, 0.54, and 0.56 in GSE29621, respectively. In addition, the risk score was an independent risk factor for CRC patients. Nomograms were constructed, and the predictive accuracy was assessed by ROC curve analysis. This signature could effectively predict the immune status and chemotherapy response in CRC patients. Moreover, SNHG7 and ZEB1-AS1 depletion significantly suppressed the colony formation, migration, and invasion of CRC cells in vitro. Conclusion: We constructed a signature that could predict the metastasis of CRC and provide certain theoretical guidance for novel therapeutic approaches for CRC. |
format | Online Article Text |
id | pubmed-9162157 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91621572022-06-03 Discovery and Validation of a Novel Metastasis-Related lncRNA Prognostic Signature for Colorectal Cancer Tang, Qiang Hu, Xin Guo, Qiong Shi, Yueyue Liu, Liming Ying, Guoguang Front Genet Genetics Background: Cancer metastasis-related chemoresistance and tumour progression are the leading causes of death among CRC patients. Therefore, it is urgent to identify reliable novel biomarkers for predicting the metastasis of CRC. Methods: The gene expression and corresponding clinical data of CRC patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Univariate and multivariate analyses were performed to identify prognostic metastasis-related lncRNAs. Nomograms were constructed, and the predictive accuracy of the nomogram model was assessed by ROC curve analysis. Then, the R package “pRRophetic” was used to predict chemotherapeutic response in CRC patients. In addition, the CIBERSORT database was introduced to evaluate tumour infiltrating immune cells between the high—and low-risk groups. The potential roles of SNHG7 and ZEB1-AS1 in CRC cell lines were further confirmed by in vitro experiments. Results: An 8-lncRNA (LINC00261, RP1-170O19.17, CAPN10-AS1, SNHG7, ZEB1-AS1, U47924.27, NIFK-AS1, and LINC00925) signature was constructed for CRC prognosis prediction, which stratified patients into two risk groups. Kaplan-Meier analysis revealed that patients in the higher-risk group had a lower survival probability than those in the lower-risk group [p < 0.001 (TCGA); P = 0.044 (GSE39582); and P = 0.0078 (GSE29621)] The AUCs of 1-, 3-, and 5-year survival were 0.678, 0.669, and 0.72 in TCGA; 0.58, 0.55, and 0.56 in GSE39582; and 0.75, 0.54, and 0.56 in GSE29621, respectively. In addition, the risk score was an independent risk factor for CRC patients. Nomograms were constructed, and the predictive accuracy was assessed by ROC curve analysis. This signature could effectively predict the immune status and chemotherapy response in CRC patients. Moreover, SNHG7 and ZEB1-AS1 depletion significantly suppressed the colony formation, migration, and invasion of CRC cells in vitro. Conclusion: We constructed a signature that could predict the metastasis of CRC and provide certain theoretical guidance for novel therapeutic approaches for CRC. Frontiers Media S.A. 2022-05-19 /pmc/articles/PMC9162157/ /pubmed/35664303 http://dx.doi.org/10.3389/fgene.2022.704988 Text en Copyright © 2022 Tang, Hu, Guo, Shi, Liu and Ying. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Tang, Qiang Hu, Xin Guo, Qiong Shi, Yueyue Liu, Liming Ying, Guoguang Discovery and Validation of a Novel Metastasis-Related lncRNA Prognostic Signature for Colorectal Cancer |
title | Discovery and Validation of a Novel Metastasis-Related lncRNA Prognostic Signature for Colorectal Cancer |
title_full | Discovery and Validation of a Novel Metastasis-Related lncRNA Prognostic Signature for Colorectal Cancer |
title_fullStr | Discovery and Validation of a Novel Metastasis-Related lncRNA Prognostic Signature for Colorectal Cancer |
title_full_unstemmed | Discovery and Validation of a Novel Metastasis-Related lncRNA Prognostic Signature for Colorectal Cancer |
title_short | Discovery and Validation of a Novel Metastasis-Related lncRNA Prognostic Signature for Colorectal Cancer |
title_sort | discovery and validation of a novel metastasis-related lncrna prognostic signature for colorectal cancer |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9162157/ https://www.ncbi.nlm.nih.gov/pubmed/35664303 http://dx.doi.org/10.3389/fgene.2022.704988 |
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