Cargando…
Comprehensive analysis of cuproptosis-related long noncoding RNA for predicting prognostic and diagnostic value and immune landscape in colorectal adenocarcinoma
BACKGROUND: Cuproptosis, as a copper-induced mitochondrial cell death, has attracted extensive attention recently, especially in cancer. Although some key regulatory genes have been identified in cuproptosis, the related lncRNAs have not been further studied. Exploring the prognostic and diagnostic...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10009981/ https://www.ncbi.nlm.nih.gov/pubmed/36915193 http://dx.doi.org/10.1186/s40246-023-00469-5 |
_version_ | 1784906096265134080 |
---|---|
author | Liu, Shichao Zhang, Shoucai Liu, Yingjie Yang, XiaoRong Zheng, Guixi |
author_facet | Liu, Shichao Zhang, Shoucai Liu, Yingjie Yang, XiaoRong Zheng, Guixi |
author_sort | Liu, Shichao |
collection | PubMed |
description | BACKGROUND: Cuproptosis, as a copper-induced mitochondrial cell death, has attracted extensive attention recently, especially in cancer. Although some key regulatory genes have been identified in cuproptosis, the related lncRNAs have not been further studied. Exploring the prognostic and diagnostic value of cuproptosis-related lncRNAs (CRLs) in colon adenocarcinoma and providing guidance for individualized immunotherapy for patients are of great significance. RESULTS: A total of 2003 lncRNAs were correlated with cuproptosis genes and considered as CRLs. We screened 33 survival-associated CRLs and established a prognostic signature base on 7 CRLs in the training group. The patients in the low-risk group had better outcomes in both training group (P < 0.001) and test group (P = 0.016). More exciting, our model showed good prognosis prediction in both stage I–II (P = 0.020) and stage III–IV (P = 0.001). The nomogram model could further improve the accuracy of prognosis prediction. Interestingly, glucose-related metabolic pathways, which were closely related to cuproptosis, were enriched in the low-risk group. Meanwhile, the immune infiltration scores were lower in the high-risk group. The high-risk group was more sensitive to OSI.906 and ABT.888, while low-risk group was more sensitive to Sorafenib. Three lncRNAs, FALEC, AC083967.1 and AC010997.4, were highly expressed in serum of COAD patients, and the AUC was 0.772, 0.726 and 0.714, respectively, indicating their valuable diagnostic value. CONCLUSIONS: Our research constructed a prognostic signature based on 7 CRLs and found three promising diagnostic markers for COAD patients. Our results provided a reference to the personalized immunotherapy strategies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40246-023-00469-5. |
format | Online Article Text |
id | pubmed-10009981 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-100099812023-03-14 Comprehensive analysis of cuproptosis-related long noncoding RNA for predicting prognostic and diagnostic value and immune landscape in colorectal adenocarcinoma Liu, Shichao Zhang, Shoucai Liu, Yingjie Yang, XiaoRong Zheng, Guixi Hum Genomics Research BACKGROUND: Cuproptosis, as a copper-induced mitochondrial cell death, has attracted extensive attention recently, especially in cancer. Although some key regulatory genes have been identified in cuproptosis, the related lncRNAs have not been further studied. Exploring the prognostic and diagnostic value of cuproptosis-related lncRNAs (CRLs) in colon adenocarcinoma and providing guidance for individualized immunotherapy for patients are of great significance. RESULTS: A total of 2003 lncRNAs were correlated with cuproptosis genes and considered as CRLs. We screened 33 survival-associated CRLs and established a prognostic signature base on 7 CRLs in the training group. The patients in the low-risk group had better outcomes in both training group (P < 0.001) and test group (P = 0.016). More exciting, our model showed good prognosis prediction in both stage I–II (P = 0.020) and stage III–IV (P = 0.001). The nomogram model could further improve the accuracy of prognosis prediction. Interestingly, glucose-related metabolic pathways, which were closely related to cuproptosis, were enriched in the low-risk group. Meanwhile, the immune infiltration scores were lower in the high-risk group. The high-risk group was more sensitive to OSI.906 and ABT.888, while low-risk group was more sensitive to Sorafenib. Three lncRNAs, FALEC, AC083967.1 and AC010997.4, were highly expressed in serum of COAD patients, and the AUC was 0.772, 0.726 and 0.714, respectively, indicating their valuable diagnostic value. CONCLUSIONS: Our research constructed a prognostic signature based on 7 CRLs and found three promising diagnostic markers for COAD patients. Our results provided a reference to the personalized immunotherapy strategies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40246-023-00469-5. BioMed Central 2023-03-13 /pmc/articles/PMC10009981/ /pubmed/36915193 http://dx.doi.org/10.1186/s40246-023-00469-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Liu, Shichao Zhang, Shoucai Liu, Yingjie Yang, XiaoRong Zheng, Guixi Comprehensive analysis of cuproptosis-related long noncoding RNA for predicting prognostic and diagnostic value and immune landscape in colorectal adenocarcinoma |
title | Comprehensive analysis of cuproptosis-related long noncoding RNA for predicting prognostic and diagnostic value and immune landscape in colorectal adenocarcinoma |
title_full | Comprehensive analysis of cuproptosis-related long noncoding RNA for predicting prognostic and diagnostic value and immune landscape in colorectal adenocarcinoma |
title_fullStr | Comprehensive analysis of cuproptosis-related long noncoding RNA for predicting prognostic and diagnostic value and immune landscape in colorectal adenocarcinoma |
title_full_unstemmed | Comprehensive analysis of cuproptosis-related long noncoding RNA for predicting prognostic and diagnostic value and immune landscape in colorectal adenocarcinoma |
title_short | Comprehensive analysis of cuproptosis-related long noncoding RNA for predicting prognostic and diagnostic value and immune landscape in colorectal adenocarcinoma |
title_sort | comprehensive analysis of cuproptosis-related long noncoding rna for predicting prognostic and diagnostic value and immune landscape in colorectal adenocarcinoma |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10009981/ https://www.ncbi.nlm.nih.gov/pubmed/36915193 http://dx.doi.org/10.1186/s40246-023-00469-5 |
work_keys_str_mv | AT liushichao comprehensiveanalysisofcuproptosisrelatedlongnoncodingrnaforpredictingprognosticanddiagnosticvalueandimmunelandscapeincolorectaladenocarcinoma AT zhangshoucai comprehensiveanalysisofcuproptosisrelatedlongnoncodingrnaforpredictingprognosticanddiagnosticvalueandimmunelandscapeincolorectaladenocarcinoma AT liuyingjie comprehensiveanalysisofcuproptosisrelatedlongnoncodingrnaforpredictingprognosticanddiagnosticvalueandimmunelandscapeincolorectaladenocarcinoma AT yangxiaorong comprehensiveanalysisofcuproptosisrelatedlongnoncodingrnaforpredictingprognosticanddiagnosticvalueandimmunelandscapeincolorectaladenocarcinoma AT zhengguixi comprehensiveanalysisofcuproptosisrelatedlongnoncodingrnaforpredictingprognosticanddiagnosticvalueandimmunelandscapeincolorectaladenocarcinoma |