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Construction of a predictive model for breast cancer metastasis based on lncRNAs
BACKGROUND: There is currently a lack of biological markers to determine the risk of lymph node metastasis in breast cancer. A single long non-coding RNA (lncRNA) cannot accurately describe the heterogeneity of tumors. Thus, more accurate algorithms are needed to screen key pathogenic lncRNAs, and q...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007891/ https://www.ncbi.nlm.nih.gov/pubmed/36915588 http://dx.doi.org/10.21037/tcr-23-129 |
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author | Chen, Jing Ling, Chen |
author_facet | Chen, Jing Ling, Chen |
author_sort | Chen, Jing |
collection | PubMed |
description | BACKGROUND: There is currently a lack of biological markers to determine the risk of lymph node metastasis in breast cancer. A single long non-coding RNA (lncRNA) cannot accurately describe the heterogeneity of tumors. Thus, more accurate algorithms are needed to screen key pathogenic lncRNAs, and quantitative models are needed to describe the heterogeneity of breast cancer. METHODS: A whole transcriptome sequencing data set of breast cancer tissue samples was downloaded from The Cancer Genome Atlas database (n=1,091). A weighted correlation network analysis was conducted to identify the hub lncRNAs associated with lymph node metastasis. A logistic regression analysis was conducted to construct the risk score model. The relationship between the risk scores and the key lncRNAs and the infiltration of the immune cell subtypes was also explored. RESULTS: A total of 3 common lncRNAs were identified between the differentially expressed lncRNA set and the hub lncRNA set; that is, zinc finger protein 582-antisense RNA 1 (ZNF582-AS1), metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), and actin filament associated protein 1-antisense RNA 1 (AFAP1-AS1). The following formula was used to calculate the risk score: risk score =1.31 + 0.51 * ZNF582-AS1 – 0.66 * MALAT1 – 0.50 * AFAP1-AS1. The receiver operating characteristic curve showed that the areas under the curve for the risk score, ZNF582-AS1, MALAT1, and AFAP1-AS1 were 0.975, 0.793, 0.685, and 0764, respectively (P<0.05). The risk score was positively correlated with immune cell subtype infiltration. CONCLUSIONS: ZNF582-AS1, MALAT1, and AFAP1-AS1 are the key lncRNAs involved in the lymph node metastasis of breast cancer. Our risk score model, which was based on ZNF582-AS1, MALAT1 and AFAP1-AS1, can accurately predict the risk of breast cancer lymph node metastasis. ZNF582-AS1, MALAT1, and AFAP1-AS1 are potential biomarkers for the lymph node metastasis of breast cancer. |
format | Online Article Text |
id | pubmed-10007891 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-100078912023-03-12 Construction of a predictive model for breast cancer metastasis based on lncRNAs Chen, Jing Ling, Chen Transl Cancer Res Original Article BACKGROUND: There is currently a lack of biological markers to determine the risk of lymph node metastasis in breast cancer. A single long non-coding RNA (lncRNA) cannot accurately describe the heterogeneity of tumors. Thus, more accurate algorithms are needed to screen key pathogenic lncRNAs, and quantitative models are needed to describe the heterogeneity of breast cancer. METHODS: A whole transcriptome sequencing data set of breast cancer tissue samples was downloaded from The Cancer Genome Atlas database (n=1,091). A weighted correlation network analysis was conducted to identify the hub lncRNAs associated with lymph node metastasis. A logistic regression analysis was conducted to construct the risk score model. The relationship between the risk scores and the key lncRNAs and the infiltration of the immune cell subtypes was also explored. RESULTS: A total of 3 common lncRNAs were identified between the differentially expressed lncRNA set and the hub lncRNA set; that is, zinc finger protein 582-antisense RNA 1 (ZNF582-AS1), metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), and actin filament associated protein 1-antisense RNA 1 (AFAP1-AS1). The following formula was used to calculate the risk score: risk score =1.31 + 0.51 * ZNF582-AS1 – 0.66 * MALAT1 – 0.50 * AFAP1-AS1. The receiver operating characteristic curve showed that the areas under the curve for the risk score, ZNF582-AS1, MALAT1, and AFAP1-AS1 were 0.975, 0.793, 0.685, and 0764, respectively (P<0.05). The risk score was positively correlated with immune cell subtype infiltration. CONCLUSIONS: ZNF582-AS1, MALAT1, and AFAP1-AS1 are the key lncRNAs involved in the lymph node metastasis of breast cancer. Our risk score model, which was based on ZNF582-AS1, MALAT1 and AFAP1-AS1, can accurately predict the risk of breast cancer lymph node metastasis. ZNF582-AS1, MALAT1, and AFAP1-AS1 are potential biomarkers for the lymph node metastasis of breast cancer. AME Publishing Company 2023-02-27 2023-02-28 /pmc/articles/PMC10007891/ /pubmed/36915588 http://dx.doi.org/10.21037/tcr-23-129 Text en 2023 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Chen, Jing Ling, Chen Construction of a predictive model for breast cancer metastasis based on lncRNAs |
title | Construction of a predictive model for breast cancer metastasis based on lncRNAs |
title_full | Construction of a predictive model for breast cancer metastasis based on lncRNAs |
title_fullStr | Construction of a predictive model for breast cancer metastasis based on lncRNAs |
title_full_unstemmed | Construction of a predictive model for breast cancer metastasis based on lncRNAs |
title_short | Construction of a predictive model for breast cancer metastasis based on lncRNAs |
title_sort | construction of a predictive model for breast cancer metastasis based on lncrnas |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007891/ https://www.ncbi.nlm.nih.gov/pubmed/36915588 http://dx.doi.org/10.21037/tcr-23-129 |
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