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The ferroptosis-related long non-coding RNAs signature predicts biochemical recurrence and immune cell infiltration in prostate cancer

BACKGROUND: Findings from numerous studies have revealed that ferroptosis is closely related to tumorigenesis and immune cell infiltration. Long non-coding RNAs (lncRNAs) are reportedly involved in the progression of various cancers, including prostate cancer (PCa). This study was designed to establ...

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Autores principales: Liu, Chunhui, Gao, Yue, Ni, Jiaxuan, Chen, Saisai, Hu, Qiang, Wang, Can, Hu, Mingjin, Chen, Ming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9290257/
https://www.ncbi.nlm.nih.gov/pubmed/35850679
http://dx.doi.org/10.1186/s12885-022-09876-8
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author Liu, Chunhui
Gao, Yue
Ni, Jiaxuan
Chen, Saisai
Hu, Qiang
Wang, Can
Hu, Mingjin
Chen, Ming
author_facet Liu, Chunhui
Gao, Yue
Ni, Jiaxuan
Chen, Saisai
Hu, Qiang
Wang, Can
Hu, Mingjin
Chen, Ming
author_sort Liu, Chunhui
collection PubMed
description BACKGROUND: Findings from numerous studies have revealed that ferroptosis is closely related to tumorigenesis and immune cell infiltration. Long non-coding RNAs (lncRNAs) are reportedly involved in the progression of various cancers, including prostate cancer (PCa). This study was designed to establish a ferroptosis-related lncRNA (frlncRNA) signature to predict PCa prognosis. METHODS: The frlncRNAs were identified by studying their expression by Pearson’s correlation analysis. Differentially expressed prognosis related frlncRNAs were identified by the Wilcoxon test and univariate Cox regression analysis. The LASSO Cox regression model was used to build a model to predict biochemical recurrence (BCR) based on frlncRNAs. The GSEA software (version 4.1.0) was used to explore the enriched pathways in high- and low- risk groups. Patients with PCa were clustered into different subgroups by unsupervised clustering based on the frlncRNAs considered in the prognostic model. Real-time PCR and CCK8 assays were performed to verify the expression and function of frlncRNAs. RESULTS: We identified 35 differentially expressed prognosis related frlncRNAs based on data on PCa from TCGA. A risk signature based on five frlncRNAs (AP006284.1, AC132938.1, BCRP3, AL360181.4 and AL135999.1), was confirmed to perform well in predicting BCR. The high-risk group had higher disease grades and a greater number of infiltrating immune cells. Besides this, we found that the five frlncRNAs were connected with typical immune checkpoints. With respect to molecular mechanisms, several metabolic pathways were found to enriched in the low-risk group. Furthermore, patients could be classified into different subtypes with different PSA-free times using the five frlncRNAs. Notably, AP006284.1, AC132938.1, BCRP3 and AL135999.1 were upregulated in PCa cells and tissues, whereas AL360181.4 exhibited the opposite trend. The downregulation of BCRP3 and AP006284.1 impaired the proliferation of 22RV1 cells. CONCLUSION: We generated a prognostic model based on five frlncRNAs, with clinical usefulness, and thus provided a novel strategy for predicting the BCR of patients with PCa. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-09876-8.
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spelling pubmed-92902572022-07-19 The ferroptosis-related long non-coding RNAs signature predicts biochemical recurrence and immune cell infiltration in prostate cancer Liu, Chunhui Gao, Yue Ni, Jiaxuan Chen, Saisai Hu, Qiang Wang, Can Hu, Mingjin Chen, Ming BMC Cancer Research BACKGROUND: Findings from numerous studies have revealed that ferroptosis is closely related to tumorigenesis and immune cell infiltration. Long non-coding RNAs (lncRNAs) are reportedly involved in the progression of various cancers, including prostate cancer (PCa). This study was designed to establish a ferroptosis-related lncRNA (frlncRNA) signature to predict PCa prognosis. METHODS: The frlncRNAs were identified by studying their expression by Pearson’s correlation analysis. Differentially expressed prognosis related frlncRNAs were identified by the Wilcoxon test and univariate Cox regression analysis. The LASSO Cox regression model was used to build a model to predict biochemical recurrence (BCR) based on frlncRNAs. The GSEA software (version 4.1.0) was used to explore the enriched pathways in high- and low- risk groups. Patients with PCa were clustered into different subgroups by unsupervised clustering based on the frlncRNAs considered in the prognostic model. Real-time PCR and CCK8 assays were performed to verify the expression and function of frlncRNAs. RESULTS: We identified 35 differentially expressed prognosis related frlncRNAs based on data on PCa from TCGA. A risk signature based on five frlncRNAs (AP006284.1, AC132938.1, BCRP3, AL360181.4 and AL135999.1), was confirmed to perform well in predicting BCR. The high-risk group had higher disease grades and a greater number of infiltrating immune cells. Besides this, we found that the five frlncRNAs were connected with typical immune checkpoints. With respect to molecular mechanisms, several metabolic pathways were found to enriched in the low-risk group. Furthermore, patients could be classified into different subtypes with different PSA-free times using the five frlncRNAs. Notably, AP006284.1, AC132938.1, BCRP3 and AL135999.1 were upregulated in PCa cells and tissues, whereas AL360181.4 exhibited the opposite trend. The downregulation of BCRP3 and AP006284.1 impaired the proliferation of 22RV1 cells. CONCLUSION: We generated a prognostic model based on five frlncRNAs, with clinical usefulness, and thus provided a novel strategy for predicting the BCR of patients with PCa. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-09876-8. BioMed Central 2022-07-18 /pmc/articles/PMC9290257/ /pubmed/35850679 http://dx.doi.org/10.1186/s12885-022-09876-8 Text en © The Author(s) 2022 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, Chunhui
Gao, Yue
Ni, Jiaxuan
Chen, Saisai
Hu, Qiang
Wang, Can
Hu, Mingjin
Chen, Ming
The ferroptosis-related long non-coding RNAs signature predicts biochemical recurrence and immune cell infiltration in prostate cancer
title The ferroptosis-related long non-coding RNAs signature predicts biochemical recurrence and immune cell infiltration in prostate cancer
title_full The ferroptosis-related long non-coding RNAs signature predicts biochemical recurrence and immune cell infiltration in prostate cancer
title_fullStr The ferroptosis-related long non-coding RNAs signature predicts biochemical recurrence and immune cell infiltration in prostate cancer
title_full_unstemmed The ferroptosis-related long non-coding RNAs signature predicts biochemical recurrence and immune cell infiltration in prostate cancer
title_short The ferroptosis-related long non-coding RNAs signature predicts biochemical recurrence and immune cell infiltration in prostate cancer
title_sort ferroptosis-related long non-coding rnas signature predicts biochemical recurrence and immune cell infiltration in prostate cancer
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9290257/
https://www.ncbi.nlm.nih.gov/pubmed/35850679
http://dx.doi.org/10.1186/s12885-022-09876-8
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