Identification of macrophage-related molecular subgroups and risk signature in colorectal cancer based on a bioinformatics analysis
Macrophages play a crucial role in tumor initiation and progression, while macrophage-associated gene signature in colorectal cancer (CRC) patients has not been investigated. Our study aimed to identify macrophage-related molecular subgroups and develop a macrophage-related risk model to predict CRC...
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| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | Autoimmunity |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/08916934.2024.2321908 |
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| author | Qi Liu Li Liao |
| author_facet | Qi Liu Li Liao |
| author_sort | Qi Liu |
| collection | DOAJ |
| description | Macrophages play a crucial role in tumor initiation and progression, while macrophage-associated gene signature in colorectal cancer (CRC) patients has not been investigated. Our study aimed to identify macrophage-related molecular subgroups and develop a macrophage-related risk model to predict CRC prognosis. The mRNA expression profile and clinical information of CRC patients were obtained from TCGA and GEO databases. CRC patients from TCGA were divided into high and low macrophage subgroups based on the median macrophage score. The ESTIMATE and CIBERSORT algorithms were used to assess immune cell infiltration between subgroups. GSVA and GSEA analyses were performed to investigate differences in enriched pathways between subgroups. Univariate and LASSO Cox regression were used to build a prognostic risk model, which was further validated in the GSE39582 dataset. A high macrophage score subgroup was associated with poor prognosis, highly activated immune-related pathways and an immune-active microenvironment. A total of 547 differentially expressed macrophage-related genes (DEMRGs) were identified, among which seven genes (including RIMKLB, UST, PCOLCE2, ZNF829, TMEM59L, CILP2, DTNA) were identified by COX regression analyses and used to build a risk score model. The risk model shows good predictive and diagnostic values for CRC patients in both TCGA and GSE39852 datasets. Furthermore, multivariate Cox regression analysis showed that the risk score was an independent risk factor for overall survival in CRC patients. Our findings provided a novel insight into macrophage heterogeneity and its immunological role in CRC. This risk score model may serve as an effective prognostic tool and contribute to personalised clinical management of CRC patients. |
| format | Article |
| id | doaj-art-1fd27ff8078b4f9ba91691e4cd22c6ab |
| institution | Kabale University |
| issn | 0891-6934 1607-842X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Autoimmunity |
| spelling | doaj-art-1fd27ff8078b4f9ba91691e4cd22c6ab2024-12-04T06:11:52ZengTaylor & Francis GroupAutoimmunity0891-69341607-842X2024-12-0157110.1080/08916934.2024.2321908Identification of macrophage-related molecular subgroups and risk signature in colorectal cancer based on a bioinformatics analysisQi Liu0Li Liao1Department of General Surgery, Heyuan People’s Hospital, Heyuan, ChinaDepartment of preventive health care, Heyuan People’s Hospital, Heyuan, ChinaMacrophages play a crucial role in tumor initiation and progression, while macrophage-associated gene signature in colorectal cancer (CRC) patients has not been investigated. Our study aimed to identify macrophage-related molecular subgroups and develop a macrophage-related risk model to predict CRC prognosis. The mRNA expression profile and clinical information of CRC patients were obtained from TCGA and GEO databases. CRC patients from TCGA were divided into high and low macrophage subgroups based on the median macrophage score. The ESTIMATE and CIBERSORT algorithms were used to assess immune cell infiltration between subgroups. GSVA and GSEA analyses were performed to investigate differences in enriched pathways between subgroups. Univariate and LASSO Cox regression were used to build a prognostic risk model, which was further validated in the GSE39582 dataset. A high macrophage score subgroup was associated with poor prognosis, highly activated immune-related pathways and an immune-active microenvironment. A total of 547 differentially expressed macrophage-related genes (DEMRGs) were identified, among which seven genes (including RIMKLB, UST, PCOLCE2, ZNF829, TMEM59L, CILP2, DTNA) were identified by COX regression analyses and used to build a risk score model. The risk model shows good predictive and diagnostic values for CRC patients in both TCGA and GSE39852 datasets. Furthermore, multivariate Cox regression analysis showed that the risk score was an independent risk factor for overall survival in CRC patients. Our findings provided a novel insight into macrophage heterogeneity and its immunological role in CRC. This risk score model may serve as an effective prognostic tool and contribute to personalised clinical management of CRC patients.https://www.tandfonline.com/doi/10.1080/08916934.2024.2321908Colorectal cancermacrophage-related genesrisk score modeltumour immunitymacrophage-related subtypes |
| spellingShingle | Qi Liu Li Liao Identification of macrophage-related molecular subgroups and risk signature in colorectal cancer based on a bioinformatics analysis Autoimmunity Colorectal cancer macrophage-related genes risk score model tumour immunity macrophage-related subtypes |
| title | Identification of macrophage-related molecular subgroups and risk signature in colorectal cancer based on a bioinformatics analysis |
| title_full | Identification of macrophage-related molecular subgroups and risk signature in colorectal cancer based on a bioinformatics analysis |
| title_fullStr | Identification of macrophage-related molecular subgroups and risk signature in colorectal cancer based on a bioinformatics analysis |
| title_full_unstemmed | Identification of macrophage-related molecular subgroups and risk signature in colorectal cancer based on a bioinformatics analysis |
| title_short | Identification of macrophage-related molecular subgroups and risk signature in colorectal cancer based on a bioinformatics analysis |
| title_sort | identification of macrophage related molecular subgroups and risk signature in colorectal cancer based on a bioinformatics analysis |
| topic | Colorectal cancer macrophage-related genes risk score model tumour immunity macrophage-related subtypes |
| url | https://www.tandfonline.com/doi/10.1080/08916934.2024.2321908 |
| work_keys_str_mv | AT qiliu identificationofmacrophagerelatedmolecularsubgroupsandrisksignatureincolorectalcancerbasedonabioinformaticsanalysis AT liliao identificationofmacrophagerelatedmolecularsubgroupsandrisksignatureincolorectalcancerbasedonabioinformaticsanalysis |