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DNA damage repair gene signature model for predicting prognosis and chemotherapy outcomes in lung squamous cell carcinoma

BACKGROUND: Lung squamous cell carcinoma (LUSC) is prone to metastasis and likely to develop resistance to chemotherapeutic drugs. DNA repair has been reported to be involved in the progression and chemoresistance of LUSC. However, the relationship between LUSC patient prognosis and DNA damage repai...

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Autores principales: Wang, Xinshu, Huang, Zhiyuan, Li, Lei, Wang, Guangxue, Dong, Lin, Li, Qinchuan, Yuan, Jian, Li, Yunhui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9361681/
https://www.ncbi.nlm.nih.gov/pubmed/35941578
http://dx.doi.org/10.1186/s12885-022-09954-x
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author Wang, Xinshu
Huang, Zhiyuan
Li, Lei
Wang, Guangxue
Dong, Lin
Li, Qinchuan
Yuan, Jian
Li, Yunhui
author_facet Wang, Xinshu
Huang, Zhiyuan
Li, Lei
Wang, Guangxue
Dong, Lin
Li, Qinchuan
Yuan, Jian
Li, Yunhui
author_sort Wang, Xinshu
collection PubMed
description BACKGROUND: Lung squamous cell carcinoma (LUSC) is prone to metastasis and likely to develop resistance to chemotherapeutic drugs. DNA repair has been reported to be involved in the progression and chemoresistance of LUSC. However, the relationship between LUSC patient prognosis and DNA damage repair genes is still unclear. METHODS: The clinical information of LUSC patients and tumour gene expression level data were downloaded from the TCGA database. Unsupervised clustering and Cox regression were performed to obtain molecular subtypes and prognosis-related significant genes based on a list including 150 DNA damage repair genes downloaded from the GSEA database. The coefficients determined by the multivariate Cox regression analysis and the expression level of prognosis-related DNA damage repair genes were employed to calculate the risk score, which divided LUSC patients into two groups: the high-risk group and the low-risk group. Immune viability, overall survival, and anticarcinogen sensitivity analyses of the two groups of LUSC patients were performed by Kaplan–Meier analysis with the log rank test, ssGSEA and the pRRophetic package in R software. A time-dependent ROC curve was applied to compare the survival prediction ability of the risk score, which was used to construct a survival prediction model by multivariate Cox regression. The prediction model was used to build a nomogram, the discriminative ability of which was confirmed by C-index assessment, and its calibration was validated by calibration curve analysis. Differentially expressed DNA damage repair genes in LUSC patient tissues were retrieved by the Wilcoxon test and validated by qRT–PCR and IHC. RESULT: LUSC patients were separated into two clusters based on molecular subtypes, of which Cluster 2 was associated with worse overall survival. A prognostic prediction model for LUSC patients was constructed and validated, and a risk score calculated based on the expression levels of ten DNA damage repair genes was employed. The clinical utility was evaluated by drug sensitivity and immune filtration analyses. Thirteen-one genes were upregulated in LUSC patient samples, and we selected the top four genes that were validated by RT–PCR and IHC. CONCLUSION: We established a novel prognostic model based on DNA damage repair gene expression that can be used to predict therapeutic efficacy in LUSC patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-09954-x.
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spelling pubmed-93616812022-08-10 DNA damage repair gene signature model for predicting prognosis and chemotherapy outcomes in lung squamous cell carcinoma Wang, Xinshu Huang, Zhiyuan Li, Lei Wang, Guangxue Dong, Lin Li, Qinchuan Yuan, Jian Li, Yunhui BMC Cancer Research BACKGROUND: Lung squamous cell carcinoma (LUSC) is prone to metastasis and likely to develop resistance to chemotherapeutic drugs. DNA repair has been reported to be involved in the progression and chemoresistance of LUSC. However, the relationship between LUSC patient prognosis and DNA damage repair genes is still unclear. METHODS: The clinical information of LUSC patients and tumour gene expression level data were downloaded from the TCGA database. Unsupervised clustering and Cox regression were performed to obtain molecular subtypes and prognosis-related significant genes based on a list including 150 DNA damage repair genes downloaded from the GSEA database. The coefficients determined by the multivariate Cox regression analysis and the expression level of prognosis-related DNA damage repair genes were employed to calculate the risk score, which divided LUSC patients into two groups: the high-risk group and the low-risk group. Immune viability, overall survival, and anticarcinogen sensitivity analyses of the two groups of LUSC patients were performed by Kaplan–Meier analysis with the log rank test, ssGSEA and the pRRophetic package in R software. A time-dependent ROC curve was applied to compare the survival prediction ability of the risk score, which was used to construct a survival prediction model by multivariate Cox regression. The prediction model was used to build a nomogram, the discriminative ability of which was confirmed by C-index assessment, and its calibration was validated by calibration curve analysis. Differentially expressed DNA damage repair genes in LUSC patient tissues were retrieved by the Wilcoxon test and validated by qRT–PCR and IHC. RESULT: LUSC patients were separated into two clusters based on molecular subtypes, of which Cluster 2 was associated with worse overall survival. A prognostic prediction model for LUSC patients was constructed and validated, and a risk score calculated based on the expression levels of ten DNA damage repair genes was employed. The clinical utility was evaluated by drug sensitivity and immune filtration analyses. Thirteen-one genes were upregulated in LUSC patient samples, and we selected the top four genes that were validated by RT–PCR and IHC. CONCLUSION: We established a novel prognostic model based on DNA damage repair gene expression that can be used to predict therapeutic efficacy in LUSC patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-09954-x. BioMed Central 2022-08-08 /pmc/articles/PMC9361681/ /pubmed/35941578 http://dx.doi.org/10.1186/s12885-022-09954-x 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
Wang, Xinshu
Huang, Zhiyuan
Li, Lei
Wang, Guangxue
Dong, Lin
Li, Qinchuan
Yuan, Jian
Li, Yunhui
DNA damage repair gene signature model for predicting prognosis and chemotherapy outcomes in lung squamous cell carcinoma
title DNA damage repair gene signature model for predicting prognosis and chemotherapy outcomes in lung squamous cell carcinoma
title_full DNA damage repair gene signature model for predicting prognosis and chemotherapy outcomes in lung squamous cell carcinoma
title_fullStr DNA damage repair gene signature model for predicting prognosis and chemotherapy outcomes in lung squamous cell carcinoma
title_full_unstemmed DNA damage repair gene signature model for predicting prognosis and chemotherapy outcomes in lung squamous cell carcinoma
title_short DNA damage repair gene signature model for predicting prognosis and chemotherapy outcomes in lung squamous cell carcinoma
title_sort dna damage repair gene signature model for predicting prognosis and chemotherapy outcomes in lung squamous cell carcinoma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9361681/
https://www.ncbi.nlm.nih.gov/pubmed/35941578
http://dx.doi.org/10.1186/s12885-022-09954-x
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