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Identification and verification of an ALYREF-involved 5-methylcytosine based signature for stratification of prostate cancer patients and prediction of clinical outcome and response to therapies

OBJECTIVES: Due to the heterogeneity of PCa, the clinical indicators used for PCa can't satisfy risk prognostication and personalized treatment. It is imperative to develop novel biomarkers for prognosis prediction and therapy response in PCa. Accumulating evidence shows that non-mutational epi...

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Autores principales: Tan, Xiao, Cai, Zhouda, Chen, Guo, Cai, Chao, Chen, Jiahong, Liang, Yingke, Zhuo, Yangjia, Liu, Jianming, Huang, Liangliang, Ouyang, Bin, Wei, Yanni, Jia, Zhenyu, Deng, Junhong, Zhong, Weide, Lu, Jianming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10167087/
https://www.ncbi.nlm.nih.gov/pubmed/37155024
http://dx.doi.org/10.1007/s12672-023-00671-w
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author Tan, Xiao
Cai, Zhouda
Chen, Guo
Cai, Chao
Chen, Jiahong
Liang, Yingke
Zhuo, Yangjia
Liu, Jianming
Huang, Liangliang
Ouyang, Bin
Wei, Yanni
Jia, Zhenyu
Deng, Junhong
Zhong, Weide
Lu, Jianming
author_facet Tan, Xiao
Cai, Zhouda
Chen, Guo
Cai, Chao
Chen, Jiahong
Liang, Yingke
Zhuo, Yangjia
Liu, Jianming
Huang, Liangliang
Ouyang, Bin
Wei, Yanni
Jia, Zhenyu
Deng, Junhong
Zhong, Weide
Lu, Jianming
author_sort Tan, Xiao
collection PubMed
description OBJECTIVES: Due to the heterogeneity of PCa, the clinical indicators used for PCa can't satisfy risk prognostication and personalized treatment. It is imperative to develop novel biomarkers for prognosis prediction and therapy response in PCa. Accumulating evidence shows that non-mutational epigenetic reprogramming, independent from genomic instability and mutation, serves as a newly added hallmark in cancer progression. METHODS: In this study, we integrated multi-center cohorts (N > 1300) to develop a RNA 5-methylcytosine regulator-based signature, the m5C score. We performed unsupervised clustering and LASSO regression to identify novel m5C-related subtypes and calculate the m5C score. Then we assessed the role of m5C cluster and m5C score in several clinical aspects such as prognosis in various molecular subtypes, responses to chemotherapy, androgen receptor signaling inhibitor (ARSI) therapy and immunotherapy in PCa. Finally, we validated the cancer-promoting performance of ALYREF through clinical data analysis and experiments in vivo and in vitro. RESULTS: The investigation revealed that the m5C score could accurately predict the biochemical recurrence (BCR) in different subtypes (the PAM50 subtypes and immunophenotypes) and the responses to chemotherapy, ARSI therapy, and immunotherapy (PD1/PD-L1). A high m5C score indicated a poor BCR prognosis in every subtype of PCa, unfavorable responses in ARSI therapy and immunotherapy (PD1/PD-L1). Moreover, the m5C reader gene termed ALYREF, yielding the highest weighed coefficient, promoted PCa progression through in silico analysis and experimental validations (in vivo and in vitro). CONCLUSIONS: The m5C signature can function in many aspects of PCa, such as the development and prognosis of the disease, and multiple therapy responses. Further, the m5C reader, ALYREF, was identified as a prognostic biomarker and a potential therapeutic target for PCa. The m5C signature could act as a brand-new tool for predicting the prognosis of patients in different molecular subtypes and patients’ therapy responses and promoting customized treatments. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12672-023-00671-w.
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spelling pubmed-101670872023-05-10 Identification and verification of an ALYREF-involved 5-methylcytosine based signature for stratification of prostate cancer patients and prediction of clinical outcome and response to therapies Tan, Xiao Cai, Zhouda Chen, Guo Cai, Chao Chen, Jiahong Liang, Yingke Zhuo, Yangjia Liu, Jianming Huang, Liangliang Ouyang, Bin Wei, Yanni Jia, Zhenyu Deng, Junhong Zhong, Weide Lu, Jianming Discov Oncol Research OBJECTIVES: Due to the heterogeneity of PCa, the clinical indicators used for PCa can't satisfy risk prognostication and personalized treatment. It is imperative to develop novel biomarkers for prognosis prediction and therapy response in PCa. Accumulating evidence shows that non-mutational epigenetic reprogramming, independent from genomic instability and mutation, serves as a newly added hallmark in cancer progression. METHODS: In this study, we integrated multi-center cohorts (N > 1300) to develop a RNA 5-methylcytosine regulator-based signature, the m5C score. We performed unsupervised clustering and LASSO regression to identify novel m5C-related subtypes and calculate the m5C score. Then we assessed the role of m5C cluster and m5C score in several clinical aspects such as prognosis in various molecular subtypes, responses to chemotherapy, androgen receptor signaling inhibitor (ARSI) therapy and immunotherapy in PCa. Finally, we validated the cancer-promoting performance of ALYREF through clinical data analysis and experiments in vivo and in vitro. RESULTS: The investigation revealed that the m5C score could accurately predict the biochemical recurrence (BCR) in different subtypes (the PAM50 subtypes and immunophenotypes) and the responses to chemotherapy, ARSI therapy, and immunotherapy (PD1/PD-L1). A high m5C score indicated a poor BCR prognosis in every subtype of PCa, unfavorable responses in ARSI therapy and immunotherapy (PD1/PD-L1). Moreover, the m5C reader gene termed ALYREF, yielding the highest weighed coefficient, promoted PCa progression through in silico analysis and experimental validations (in vivo and in vitro). CONCLUSIONS: The m5C signature can function in many aspects of PCa, such as the development and prognosis of the disease, and multiple therapy responses. Further, the m5C reader, ALYREF, was identified as a prognostic biomarker and a potential therapeutic target for PCa. The m5C signature could act as a brand-new tool for predicting the prognosis of patients in different molecular subtypes and patients’ therapy responses and promoting customized treatments. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12672-023-00671-w. Springer US 2023-05-08 /pmc/articles/PMC10167087/ /pubmed/37155024 http://dx.doi.org/10.1007/s12672-023-00671-w 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/) .
spellingShingle Research
Tan, Xiao
Cai, Zhouda
Chen, Guo
Cai, Chao
Chen, Jiahong
Liang, Yingke
Zhuo, Yangjia
Liu, Jianming
Huang, Liangliang
Ouyang, Bin
Wei, Yanni
Jia, Zhenyu
Deng, Junhong
Zhong, Weide
Lu, Jianming
Identification and verification of an ALYREF-involved 5-methylcytosine based signature for stratification of prostate cancer patients and prediction of clinical outcome and response to therapies
title Identification and verification of an ALYREF-involved 5-methylcytosine based signature for stratification of prostate cancer patients and prediction of clinical outcome and response to therapies
title_full Identification and verification of an ALYREF-involved 5-methylcytosine based signature for stratification of prostate cancer patients and prediction of clinical outcome and response to therapies
title_fullStr Identification and verification of an ALYREF-involved 5-methylcytosine based signature for stratification of prostate cancer patients and prediction of clinical outcome and response to therapies
title_full_unstemmed Identification and verification of an ALYREF-involved 5-methylcytosine based signature for stratification of prostate cancer patients and prediction of clinical outcome and response to therapies
title_short Identification and verification of an ALYREF-involved 5-methylcytosine based signature for stratification of prostate cancer patients and prediction of clinical outcome and response to therapies
title_sort identification and verification of an alyref-involved 5-methylcytosine based signature for stratification of prostate cancer patients and prediction of clinical outcome and response to therapies
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10167087/
https://www.ncbi.nlm.nih.gov/pubmed/37155024
http://dx.doi.org/10.1007/s12672-023-00671-w
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