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Establishing a prognostic model of chromatin modulators and identifying potential drug candidates in renal clear cell patients
BACKGROUND: Renal carcinoma is a common malignant tumor of the urinary system. Advanced renal carcinoma has a low 5-year survival rate and a poor prognosis. More and more studies have confirmed that chromatin regulators (CRs) can regulate the occurrence and development of cancer. This article invest...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10029171/ https://www.ncbi.nlm.nih.gov/pubmed/36941564 http://dx.doi.org/10.1186/s12859-023-05229-9 |
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author | Liu, Puyu Luo, Jihang Tan, Na Li, Chengfang Xu, Jieyu Yang, Xiaorong |
author_facet | Liu, Puyu Luo, Jihang Tan, Na Li, Chengfang Xu, Jieyu Yang, Xiaorong |
author_sort | Liu, Puyu |
collection | PubMed |
description | BACKGROUND: Renal carcinoma is a common malignant tumor of the urinary system. Advanced renal carcinoma has a low 5-year survival rate and a poor prognosis. More and more studies have confirmed that chromatin regulators (CRs) can regulate the occurrence and development of cancer. This article investigates the functional and prognostic value of CRs in renal carcinoma patients. METHODS: mRNA expression and clinical information were obtained from The Cancer Genome Atlas database. Univariate Cox regression analysis and LASSO regression analysis were used to select prognostic chromatin-regulated genes and use them to construct a risk model for predicting the prognosis of renal cancer. Differences in prognosis between high-risk and low-risk groups were compared using Kaplan–Meier analysis. In addition, we analyzed the relationship between chromatin regulators and tumor immune infiltration, and explored differences in drug sensitivity between risk groups. RESULTS: We constructed a model consisting of 11 CRs to predict the prognosis of renal cancer patients. We not only successfully validated its feasibility, but also found that the 11 CR-based model was an independent prognostic factor. Functional analysis showed that CRs were mainly enriched in cancer development-related signalling pathways. We also found through the TIMER database that CR-based models were also associated with immune cell infiltration and immune checkpoints. At the same time, the genomics of drug sensitivity in cancer database was used to analyze the commonly used drugs of renal clear cell carcinoma patients. It was found that patients in the low-risk group were sensitive to medicines such as axitinib, pazopanib, sorafenib, and gemcitabine. In contrast, those in the high-risk group may be sensitive to sunitinib. CONCLUSION: The chromatin regulator-related prognostic model we constructed can be used to assess the prognostic risk of patients with clear cell renal cell carcinoma. The results of this study can bring new ideas for targeted therapy of clear cell renal carcinoma, helping doctors to take corresponding measures in advance for patients with different risks. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05229-9. |
format | Online Article Text |
id | pubmed-10029171 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-100291712023-03-22 Establishing a prognostic model of chromatin modulators and identifying potential drug candidates in renal clear cell patients Liu, Puyu Luo, Jihang Tan, Na Li, Chengfang Xu, Jieyu Yang, Xiaorong BMC Bioinformatics Research BACKGROUND: Renal carcinoma is a common malignant tumor of the urinary system. Advanced renal carcinoma has a low 5-year survival rate and a poor prognosis. More and more studies have confirmed that chromatin regulators (CRs) can regulate the occurrence and development of cancer. This article investigates the functional and prognostic value of CRs in renal carcinoma patients. METHODS: mRNA expression and clinical information were obtained from The Cancer Genome Atlas database. Univariate Cox regression analysis and LASSO regression analysis were used to select prognostic chromatin-regulated genes and use them to construct a risk model for predicting the prognosis of renal cancer. Differences in prognosis between high-risk and low-risk groups were compared using Kaplan–Meier analysis. In addition, we analyzed the relationship between chromatin regulators and tumor immune infiltration, and explored differences in drug sensitivity between risk groups. RESULTS: We constructed a model consisting of 11 CRs to predict the prognosis of renal cancer patients. We not only successfully validated its feasibility, but also found that the 11 CR-based model was an independent prognostic factor. Functional analysis showed that CRs were mainly enriched in cancer development-related signalling pathways. We also found through the TIMER database that CR-based models were also associated with immune cell infiltration and immune checkpoints. At the same time, the genomics of drug sensitivity in cancer database was used to analyze the commonly used drugs of renal clear cell carcinoma patients. It was found that patients in the low-risk group were sensitive to medicines such as axitinib, pazopanib, sorafenib, and gemcitabine. In contrast, those in the high-risk group may be sensitive to sunitinib. CONCLUSION: The chromatin regulator-related prognostic model we constructed can be used to assess the prognostic risk of patients with clear cell renal cell carcinoma. The results of this study can bring new ideas for targeted therapy of clear cell renal carcinoma, helping doctors to take corresponding measures in advance for patients with different risks. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05229-9. BioMed Central 2023-03-20 /pmc/articles/PMC10029171/ /pubmed/36941564 http://dx.doi.org/10.1186/s12859-023-05229-9 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, Puyu Luo, Jihang Tan, Na Li, Chengfang Xu, Jieyu Yang, Xiaorong Establishing a prognostic model of chromatin modulators and identifying potential drug candidates in renal clear cell patients |
title | Establishing a prognostic model of chromatin modulators and identifying potential drug candidates in renal clear cell patients |
title_full | Establishing a prognostic model of chromatin modulators and identifying potential drug candidates in renal clear cell patients |
title_fullStr | Establishing a prognostic model of chromatin modulators and identifying potential drug candidates in renal clear cell patients |
title_full_unstemmed | Establishing a prognostic model of chromatin modulators and identifying potential drug candidates in renal clear cell patients |
title_short | Establishing a prognostic model of chromatin modulators and identifying potential drug candidates in renal clear cell patients |
title_sort | establishing a prognostic model of chromatin modulators and identifying potential drug candidates in renal clear cell patients |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10029171/ https://www.ncbi.nlm.nih.gov/pubmed/36941564 http://dx.doi.org/10.1186/s12859-023-05229-9 |
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