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Machine Learning-Devised Immune-Related lncRNA Signature Panel Predicts the Prognosis and Immune Landscape in Breast Cancer Novel IRLP Signature in BRCA

Long noncoding RNAs (lncRNAs) actively participate in breast cancer (BRCA) tumorigenesis via epigenetic mechanisms. Our study identified immune-related lncRNA (irlncRNA) pairs and compiled them into a set of noncoding gene signatures able to stratify subtypes of BRCA associated with variable degrees...

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Autores principales: Zhu, Jun-Yu, Lyu, An-Qi, Wang, Zhang-Ting, Chan, Wai-Yee, Qin, Tao, Miu, Kai-Kei, Yao, He-Rui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9410861/
https://www.ncbi.nlm.nih.gov/pubmed/36033386
http://dx.doi.org/10.1155/2022/3704798
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author Zhu, Jun-Yu
Lyu, An-Qi
Wang, Zhang-Ting
Chan, Wai-Yee
Qin, Tao
Miu, Kai-Kei
Yao, He-Rui
author_facet Zhu, Jun-Yu
Lyu, An-Qi
Wang, Zhang-Ting
Chan, Wai-Yee
Qin, Tao
Miu, Kai-Kei
Yao, He-Rui
author_sort Zhu, Jun-Yu
collection PubMed
description Long noncoding RNAs (lncRNAs) actively participate in breast cancer (BRCA) tumorigenesis via epigenetic mechanisms. Our study identified immune-related lncRNA (irlncRNA) pairs and compiled them into a set of noncoding gene signatures able to stratify subtypes of BRCA associated with variable degrees of survival and immune cell infiltration. A 40 immune-related lncRNA pair (IRLP) signature including 43 irlncRNAs was built, with high sensitivity and specificity for the prediction of survival in different molecular subtypes of BRCA. Results demonstrated that the low-risk group showed a significantly longer survival rate, and this novel IRLP signature was highly associated with survival status, T stage, metastatic disease, and overall stage in BRCA. Immune infiltrating analyses found that the low-risk group has a lower expression level of macrophage M2 and a higher expression level of immunosuppressed biomarkers than the high-risk group. DEirlncRNAs were further proven to be significantly related to the MAPK signaling, Jak-STAT signaling, and ErbB signaling pathways in BRCA. In conclusion, the 40 IRLP signature showed a promising clinical prediction value in the prognosis of different molecular subtypes and immunotherapy response in BRCA, and the underlying mechanism for these IRLPs warrants further investigations.
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spelling pubmed-94108612022-08-26 Machine Learning-Devised Immune-Related lncRNA Signature Panel Predicts the Prognosis and Immune Landscape in Breast Cancer Novel IRLP Signature in BRCA Zhu, Jun-Yu Lyu, An-Qi Wang, Zhang-Ting Chan, Wai-Yee Qin, Tao Miu, Kai-Kei Yao, He-Rui J Immunol Res Research Article Long noncoding RNAs (lncRNAs) actively participate in breast cancer (BRCA) tumorigenesis via epigenetic mechanisms. Our study identified immune-related lncRNA (irlncRNA) pairs and compiled them into a set of noncoding gene signatures able to stratify subtypes of BRCA associated with variable degrees of survival and immune cell infiltration. A 40 immune-related lncRNA pair (IRLP) signature including 43 irlncRNAs was built, with high sensitivity and specificity for the prediction of survival in different molecular subtypes of BRCA. Results demonstrated that the low-risk group showed a significantly longer survival rate, and this novel IRLP signature was highly associated with survival status, T stage, metastatic disease, and overall stage in BRCA. Immune infiltrating analyses found that the low-risk group has a lower expression level of macrophage M2 and a higher expression level of immunosuppressed biomarkers than the high-risk group. DEirlncRNAs were further proven to be significantly related to the MAPK signaling, Jak-STAT signaling, and ErbB signaling pathways in BRCA. In conclusion, the 40 IRLP signature showed a promising clinical prediction value in the prognosis of different molecular subtypes and immunotherapy response in BRCA, and the underlying mechanism for these IRLPs warrants further investigations. Hindawi 2022-08-18 /pmc/articles/PMC9410861/ /pubmed/36033386 http://dx.doi.org/10.1155/2022/3704798 Text en Copyright © 2022 Jun-Yu Zhu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zhu, Jun-Yu
Lyu, An-Qi
Wang, Zhang-Ting
Chan, Wai-Yee
Qin, Tao
Miu, Kai-Kei
Yao, He-Rui
Machine Learning-Devised Immune-Related lncRNA Signature Panel Predicts the Prognosis and Immune Landscape in Breast Cancer Novel IRLP Signature in BRCA
title Machine Learning-Devised Immune-Related lncRNA Signature Panel Predicts the Prognosis and Immune Landscape in Breast Cancer Novel IRLP Signature in BRCA
title_full Machine Learning-Devised Immune-Related lncRNA Signature Panel Predicts the Prognosis and Immune Landscape in Breast Cancer Novel IRLP Signature in BRCA
title_fullStr Machine Learning-Devised Immune-Related lncRNA Signature Panel Predicts the Prognosis and Immune Landscape in Breast Cancer Novel IRLP Signature in BRCA
title_full_unstemmed Machine Learning-Devised Immune-Related lncRNA Signature Panel Predicts the Prognosis and Immune Landscape in Breast Cancer Novel IRLP Signature in BRCA
title_short Machine Learning-Devised Immune-Related lncRNA Signature Panel Predicts the Prognosis and Immune Landscape in Breast Cancer Novel IRLP Signature in BRCA
title_sort machine learning-devised immune-related lncrna signature panel predicts the prognosis and immune landscape in breast cancer novel irlp signature in brca
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9410861/
https://www.ncbi.nlm.nih.gov/pubmed/36033386
http://dx.doi.org/10.1155/2022/3704798
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