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Integration of single-cell and bulk RNA sequencing to establish a prognostic signature based on tumor-associated macrophages in colorectal cancer
Several studies have shown significant involvement of tumor-associated macrophages (TAMs) in the tumor microenvironment and cancer progression. However, no data on reliable TAM-related biomarkers are available for predicting the prognosis of patients with colorectal cancer (CRC). We analyzed the cli...
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/PMC10638776/ https://www.ncbi.nlm.nih.gov/pubmed/37950156 http://dx.doi.org/10.1186/s12876-023-03035-4 |
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author | Li, Hua Pan, Lujuan Guo, Junyu Lao, JianLe Wei, Mingwei Huang, Fuda |
author_facet | Li, Hua Pan, Lujuan Guo, Junyu Lao, JianLe Wei, Mingwei Huang, Fuda |
author_sort | Li, Hua |
collection | PubMed |
description | Several studies have shown significant involvement of tumor-associated macrophages (TAMs) in the tumor microenvironment and cancer progression. However, no data on reliable TAM-related biomarkers are available for predicting the prognosis of patients with colorectal cancer (CRC). We analyzed the clinical data and gene expression profiles of patients with CRC from databases. The single-cell transcriptomic data was applied to identify M2-like TAM-related differentially expressed genes. Univariate Cox and least absolute shrinkage and selection operator regression analyses were used to determine the prognostic signature genes. Then, seven key genes were screened to develop the prognostic signature. In the training and external validation cohorts, the overall survival (OS) of patients in the high-risk group was significantly shorter compared to the low-risk group. Consequently, we created a nomogram that could accurately and reliably predict the prognosis of patient with CRC. A significant correlation was observed between the patient’s prognosis, clinical features, sensitivity to anticancer drugs, TME, and risk scores. Moreover, risk score was strongly related to the response to immunotherapy in patients from GSE91061, GSE78220, and GSE60331 cohorts. Finally, high expression of HSPA1A, SERPINA1, CXCL1, and low expression of DNASE1L3 were found in human CRC tissue and normal tissue by using qRT-PCR. In conclusion, the M2-like TAM-related prognostic signature could predict the survival, prognosis, and response of patients with CRC to immunotherapy, which sheds light on the role of TAMs in CRCs and enhances our understanding of TAMs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12876-023-03035-4. |
format | Online Article Text |
id | pubmed-10638776 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-106387762023-11-11 Integration of single-cell and bulk RNA sequencing to establish a prognostic signature based on tumor-associated macrophages in colorectal cancer Li, Hua Pan, Lujuan Guo, Junyu Lao, JianLe Wei, Mingwei Huang, Fuda BMC Gastroenterol Research Several studies have shown significant involvement of tumor-associated macrophages (TAMs) in the tumor microenvironment and cancer progression. However, no data on reliable TAM-related biomarkers are available for predicting the prognosis of patients with colorectal cancer (CRC). We analyzed the clinical data and gene expression profiles of patients with CRC from databases. The single-cell transcriptomic data was applied to identify M2-like TAM-related differentially expressed genes. Univariate Cox and least absolute shrinkage and selection operator regression analyses were used to determine the prognostic signature genes. Then, seven key genes were screened to develop the prognostic signature. In the training and external validation cohorts, the overall survival (OS) of patients in the high-risk group was significantly shorter compared to the low-risk group. Consequently, we created a nomogram that could accurately and reliably predict the prognosis of patient with CRC. A significant correlation was observed between the patient’s prognosis, clinical features, sensitivity to anticancer drugs, TME, and risk scores. Moreover, risk score was strongly related to the response to immunotherapy in patients from GSE91061, GSE78220, and GSE60331 cohorts. Finally, high expression of HSPA1A, SERPINA1, CXCL1, and low expression of DNASE1L3 were found in human CRC tissue and normal tissue by using qRT-PCR. In conclusion, the M2-like TAM-related prognostic signature could predict the survival, prognosis, and response of patients with CRC to immunotherapy, which sheds light on the role of TAMs in CRCs and enhances our understanding of TAMs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12876-023-03035-4. BioMed Central 2023-11-10 /pmc/articles/PMC10638776/ /pubmed/37950156 http://dx.doi.org/10.1186/s12876-023-03035-4 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, Hua Pan, Lujuan Guo, Junyu Lao, JianLe Wei, Mingwei Huang, Fuda Integration of single-cell and bulk RNA sequencing to establish a prognostic signature based on tumor-associated macrophages in colorectal cancer |
title | Integration of single-cell and bulk RNA sequencing to establish a prognostic signature based on tumor-associated macrophages in colorectal cancer |
title_full | Integration of single-cell and bulk RNA sequencing to establish a prognostic signature based on tumor-associated macrophages in colorectal cancer |
title_fullStr | Integration of single-cell and bulk RNA sequencing to establish a prognostic signature based on tumor-associated macrophages in colorectal cancer |
title_full_unstemmed | Integration of single-cell and bulk RNA sequencing to establish a prognostic signature based on tumor-associated macrophages in colorectal cancer |
title_short | Integration of single-cell and bulk RNA sequencing to establish a prognostic signature based on tumor-associated macrophages in colorectal cancer |
title_sort | integration of single-cell and bulk rna sequencing to establish a prognostic signature based on tumor-associated macrophages in colorectal cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10638776/ https://www.ncbi.nlm.nih.gov/pubmed/37950156 http://dx.doi.org/10.1186/s12876-023-03035-4 |
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