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Characterization of genomic instability-related genes predicts survival and therapeutic response in lung adenocarcinoma

BACKGROUND: Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer (NSCLC) and is the leading cause of cancer death worldwide. Its progression is characterized by genomic instability. In turn, the level of genomic instability affects the prognosis and immune status of pa...

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Autores principales: Li, Shuyang, Wang, Wei, Yu, Huihan, Zhang, Siyu, Bi, Wenxu, Sun, Suling, Hong, Bo, Fang, Zhiyou, Chen, Xueran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10655275/
https://www.ncbi.nlm.nih.gov/pubmed/37974107
http://dx.doi.org/10.1186/s12885-023-11580-0
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author Li, Shuyang
Wang, Wei
Yu, Huihan
Zhang, Siyu
Bi, Wenxu
Sun, Suling
Hong, Bo
Fang, Zhiyou
Chen, Xueran
author_facet Li, Shuyang
Wang, Wei
Yu, Huihan
Zhang, Siyu
Bi, Wenxu
Sun, Suling
Hong, Bo
Fang, Zhiyou
Chen, Xueran
author_sort Li, Shuyang
collection PubMed
description BACKGROUND: Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer (NSCLC) and is the leading cause of cancer death worldwide. Its progression is characterized by genomic instability. In turn, the level of genomic instability affects the prognosis and immune status of patients with LUAD. However, the impact of molecular features associated with genomic instability on the tumor microenvironment (TME) has not been well characterized. In addition, the effect of the genes related to genomic instability in LUAD on individualized treatment of LUAD is unknown. METHODS: The RNA-Sequencing, somatic mutation, and clinical data of LUAD patients were downloaded from publicly available databases. A genetic signature associated with genomic instability (GSAGI) was constructed by univariate Cox regression, Lasso regression, and multivariate Cox regression analysis. Bioinformatics analysis investigated the differences in prognosis, immune characteristics, and the most appropriate treatment strategy among different subtypes of LUAD patients. CCK-8 and colony formation verified the various effects of Etoposide on different subtypes of LUAD cell lines. Cell-to-cell communication analysis was performed using the “CellChat” R package. The expression of the risk factors in the GSAGI was verified using real-time quantitative PCR (qRT-PCR) and Immunohistochemistry (IHC). RESULTS: We constructed and validated the GSAGI, consisting of five genes: ANLN, RHOV, KRT6A, SIGLEC6, and KLRG2. The GSAGI was an independent prognostic factor for LUAD patients. Patients in the high-risk group distinguished by the GSAGI are more suitable for chemotherapy. More immune cells are infiltrating the tumor microenvironment of patients in the low-risk group, especially B cells. Low-risk group patients are more suitable for receiving immunotherapy. The single-cell level analysis confirmed the influence of the GSAGI on TME and revealed the Mode of action between tumor cells and other types of cells. qRT-PCR and IHC showed increased ANLN, RHOV, and KRT6A expression in the LUAD cells and tumor tissues. CONCLUSION: This study confirms that genes related to genomic instability can affect the prognosis and immune status of LUAD patients. The GSAGI we identified has the potential to guide clinicians in predicting clinical outcomes, assessing immunological status, and even developing personalized treatment plans for LUAD patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-11580-0.
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spelling pubmed-106552752023-11-16 Characterization of genomic instability-related genes predicts survival and therapeutic response in lung adenocarcinoma Li, Shuyang Wang, Wei Yu, Huihan Zhang, Siyu Bi, Wenxu Sun, Suling Hong, Bo Fang, Zhiyou Chen, Xueran BMC Cancer Research BACKGROUND: Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer (NSCLC) and is the leading cause of cancer death worldwide. Its progression is characterized by genomic instability. In turn, the level of genomic instability affects the prognosis and immune status of patients with LUAD. However, the impact of molecular features associated with genomic instability on the tumor microenvironment (TME) has not been well characterized. In addition, the effect of the genes related to genomic instability in LUAD on individualized treatment of LUAD is unknown. METHODS: The RNA-Sequencing, somatic mutation, and clinical data of LUAD patients were downloaded from publicly available databases. A genetic signature associated with genomic instability (GSAGI) was constructed by univariate Cox regression, Lasso regression, and multivariate Cox regression analysis. Bioinformatics analysis investigated the differences in prognosis, immune characteristics, and the most appropriate treatment strategy among different subtypes of LUAD patients. CCK-8 and colony formation verified the various effects of Etoposide on different subtypes of LUAD cell lines. Cell-to-cell communication analysis was performed using the “CellChat” R package. The expression of the risk factors in the GSAGI was verified using real-time quantitative PCR (qRT-PCR) and Immunohistochemistry (IHC). RESULTS: We constructed and validated the GSAGI, consisting of five genes: ANLN, RHOV, KRT6A, SIGLEC6, and KLRG2. The GSAGI was an independent prognostic factor for LUAD patients. Patients in the high-risk group distinguished by the GSAGI are more suitable for chemotherapy. More immune cells are infiltrating the tumor microenvironment of patients in the low-risk group, especially B cells. Low-risk group patients are more suitable for receiving immunotherapy. The single-cell level analysis confirmed the influence of the GSAGI on TME and revealed the Mode of action between tumor cells and other types of cells. qRT-PCR and IHC showed increased ANLN, RHOV, and KRT6A expression in the LUAD cells and tumor tissues. CONCLUSION: This study confirms that genes related to genomic instability can affect the prognosis and immune status of LUAD patients. The GSAGI we identified has the potential to guide clinicians in predicting clinical outcomes, assessing immunological status, and even developing personalized treatment plans for LUAD patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-11580-0. BioMed Central 2023-11-16 /pmc/articles/PMC10655275/ /pubmed/37974107 http://dx.doi.org/10.1186/s12885-023-11580-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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
Li, Shuyang
Wang, Wei
Yu, Huihan
Zhang, Siyu
Bi, Wenxu
Sun, Suling
Hong, Bo
Fang, Zhiyou
Chen, Xueran
Characterization of genomic instability-related genes predicts survival and therapeutic response in lung adenocarcinoma
title Characterization of genomic instability-related genes predicts survival and therapeutic response in lung adenocarcinoma
title_full Characterization of genomic instability-related genes predicts survival and therapeutic response in lung adenocarcinoma
title_fullStr Characterization of genomic instability-related genes predicts survival and therapeutic response in lung adenocarcinoma
title_full_unstemmed Characterization of genomic instability-related genes predicts survival and therapeutic response in lung adenocarcinoma
title_short Characterization of genomic instability-related genes predicts survival and therapeutic response in lung adenocarcinoma
title_sort characterization of genomic instability-related genes predicts survival and therapeutic response in lung adenocarcinoma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10655275/
https://www.ncbi.nlm.nih.gov/pubmed/37974107
http://dx.doi.org/10.1186/s12885-023-11580-0
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