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Construction and validation of a transient receptor potential-related long noncoding RNA signature for prognosis prediction in breast cancer patients

Breast cancer (BC) is the most commonly diagnosed malignancy in women around the world. Accumulating evidence suggests that transient receptor potential (TRP) channels play a significant role in tumor progression and immune cell infiltration. Hence, we conducted the study to investigate the correlat...

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Autores principales: Guo, Qiaonan, Qiu, Pengjun, Pan, Kelun, Chen, Jianpeng, Wang, Baiwei, Lin, Jianqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10659707/
https://www.ncbi.nlm.nih.gov/pubmed/37986367
http://dx.doi.org/10.1097/MD.0000000000035978
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author Guo, Qiaonan
Qiu, Pengjun
Pan, Kelun
Chen, Jianpeng
Wang, Baiwei
Lin, Jianqing
author_facet Guo, Qiaonan
Qiu, Pengjun
Pan, Kelun
Chen, Jianpeng
Wang, Baiwei
Lin, Jianqing
author_sort Guo, Qiaonan
collection PubMed
description Breast cancer (BC) is the most commonly diagnosed malignancy in women around the world. Accumulating evidence suggests that transient receptor potential (TRP) channels play a significant role in tumor progression and immune cell infiltration. Hence, we conducted the study to investigate the correlation between TRP-associated lncRNAs and the prognosis of breast carcinoma. In the current study, 33 TRP-associated genes were selected from a review published by Amrita Samanta et al, and the TRP-related lncRNAs were identified by Pearson analysis. Based on the sum of the expression levels of 12 lncRNAs provided by the Cancer Genome Atlas (TCGA), a TRP-associated lncRNA signature was established by using Cox regression analysis. According to the median value of the risk score in the training set, BC patients were separated into high- and low-risk groups. Subsequently, functional enrichment analysis was conducted on the differential expression genes (DEGs) between different risk groups. The Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression (ESTIMATE) Score was calculated by ESTIMATE, and the immune cell infiltration was evaluated by ssGSEA. Finally, the immune checkpoint gene expression levels, microsatellite instability (MSI), and immunophenoscore (IPS) were further assessed. The high-risk groups exhibited lower survival rates, while the low-risk groups showed higher survival rates. As a result, the DEGs between different risk groups were highly enriched in immune cell activation and immunoregulation. Besides, the ESTIMATE scores of patients in low-risk groups were higher than those in high-risk groups. The infiltration levels of several immune cells were remarkably elevated in low-risk groups, and various immune signatures were activated with a decreased risk score. Eventually, the TRP-associated lncRNA signature was confirmed with a highly potential ability to evaluate the immunotherapy response in breast carcinoma patients. The outcomes of the current study indicated that the 12-TRP-associated-lncRNA risk model was an independent prognostic risk factor for BC patients. This risk model could be closely related to the tumor immune microenvironment in BC. Our findings will provide new insights for future immunotherapy for BC treatment.
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spelling pubmed-106597072023-11-17 Construction and validation of a transient receptor potential-related long noncoding RNA signature for prognosis prediction in breast cancer patients Guo, Qiaonan Qiu, Pengjun Pan, Kelun Chen, Jianpeng Wang, Baiwei Lin, Jianqing Medicine (Baltimore) 5750 Breast cancer (BC) is the most commonly diagnosed malignancy in women around the world. Accumulating evidence suggests that transient receptor potential (TRP) channels play a significant role in tumor progression and immune cell infiltration. Hence, we conducted the study to investigate the correlation between TRP-associated lncRNAs and the prognosis of breast carcinoma. In the current study, 33 TRP-associated genes were selected from a review published by Amrita Samanta et al, and the TRP-related lncRNAs were identified by Pearson analysis. Based on the sum of the expression levels of 12 lncRNAs provided by the Cancer Genome Atlas (TCGA), a TRP-associated lncRNA signature was established by using Cox regression analysis. According to the median value of the risk score in the training set, BC patients were separated into high- and low-risk groups. Subsequently, functional enrichment analysis was conducted on the differential expression genes (DEGs) between different risk groups. The Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression (ESTIMATE) Score was calculated by ESTIMATE, and the immune cell infiltration was evaluated by ssGSEA. Finally, the immune checkpoint gene expression levels, microsatellite instability (MSI), and immunophenoscore (IPS) were further assessed. The high-risk groups exhibited lower survival rates, while the low-risk groups showed higher survival rates. As a result, the DEGs between different risk groups were highly enriched in immune cell activation and immunoregulation. Besides, the ESTIMATE scores of patients in low-risk groups were higher than those in high-risk groups. The infiltration levels of several immune cells were remarkably elevated in low-risk groups, and various immune signatures were activated with a decreased risk score. Eventually, the TRP-associated lncRNA signature was confirmed with a highly potential ability to evaluate the immunotherapy response in breast carcinoma patients. The outcomes of the current study indicated that the 12-TRP-associated-lncRNA risk model was an independent prognostic risk factor for BC patients. This risk model could be closely related to the tumor immune microenvironment in BC. Our findings will provide new insights for future immunotherapy for BC treatment. Lippincott Williams & Wilkins 2023-11-17 /pmc/articles/PMC10659707/ /pubmed/37986367 http://dx.doi.org/10.1097/MD.0000000000035978 Text en Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY) (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle 5750
Guo, Qiaonan
Qiu, Pengjun
Pan, Kelun
Chen, Jianpeng
Wang, Baiwei
Lin, Jianqing
Construction and validation of a transient receptor potential-related long noncoding RNA signature for prognosis prediction in breast cancer patients
title Construction and validation of a transient receptor potential-related long noncoding RNA signature for prognosis prediction in breast cancer patients
title_full Construction and validation of a transient receptor potential-related long noncoding RNA signature for prognosis prediction in breast cancer patients
title_fullStr Construction and validation of a transient receptor potential-related long noncoding RNA signature for prognosis prediction in breast cancer patients
title_full_unstemmed Construction and validation of a transient receptor potential-related long noncoding RNA signature for prognosis prediction in breast cancer patients
title_short Construction and validation of a transient receptor potential-related long noncoding RNA signature for prognosis prediction in breast cancer patients
title_sort construction and validation of a transient receptor potential-related long noncoding rna signature for prognosis prediction in breast cancer patients
topic 5750
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10659707/
https://www.ncbi.nlm.nih.gov/pubmed/37986367
http://dx.doi.org/10.1097/MD.0000000000035978
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