Construction of a fatty acid metabolism-related gene signature for predicting prognosis and immune response in breast cancer
Background: Breast cancer has the highest incidence among malignant tumors in women, and its prevalence ranks first in global cancer morbidity.Aim: This study aimed to explore the feasibility of a prognostic model for patients with breast cancer based on the differential expression of genes related...
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| Format: | Article |
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Frontiers Media S.A.
2023-03-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2023.1002157/full |
| _version_ | 1811162634625482752 |
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| author | Li Qian Yi-Fei Liu Shu-Min Lu Juan-Juan Yang Hua-Jie Miao Xin He Hua Huang Jian-Guo Zhang |
| author_facet | Li Qian Yi-Fei Liu Shu-Min Lu Juan-Juan Yang Hua-Jie Miao Xin He Hua Huang Jian-Guo Zhang |
| author_sort | Li Qian |
| collection | DOAJ |
| description | Background: Breast cancer has the highest incidence among malignant tumors in women, and its prevalence ranks first in global cancer morbidity.Aim: This study aimed to explore the feasibility of a prognostic model for patients with breast cancer based on the differential expression of genes related to fatty acid metabolism.Methods: The mRNA expression matrix of breast cancer and paracancer tissues was downloaded from The Cancer Genome Atlas database. The differentially expressed genes related to fatty acid metabolism were screened in R language. The TRRUST database was used to predict transcriptional regulators related to hub genes and construct an mRNA–transcription factor interaction network. A consensus clustering approach was used to identify different fatty acid regulatory patterns. In combination with patient survival data, Lasso and multivariate Cox proportional risk regression models were used to establish polygenic prognostic models based on fatty acid metabolism. The median risk score was used to categorize patients into high- and low-risk groups. Kaplan–Meier survival curves were used to analyze the survival differences between both groups. The Cox regression analysis included risk score and clinicopathological factors to determine whether risk score was an independent risk factor. Models based on genes associated with fatty acid metabolism were evaluated using receiver operating characteristic curves. A comparison was made between risk score levels and the fatty acid metabolism-associated genes in different subtypes of breast cancer. The differential gene sets of the Kyoto Encyclopedia of Genes and Genomes for screening high- and low-risk populations were compared using a gene set enrichment analysis. Furthermore, we utilized CIBERSORT to examine the abundance of immune cells in breast cancer in different clustering models.Results: High expression levels of ALDH1A1 and UBE2L6 prevented breast cancer, whereas high RDH16 expression levels increased its risk. Our comprehensive assessment of the association between prognostic risk scoring models and tumor microenvironment characteristics showed significant differences in the abundance of various immune cells between high- and low-risk breast cancer patients.Conclusions: By assessing fatty acid metabolism patterns, we gained a better understanding of the infiltration characteristics of the tumor microenvironment. Our findings are valuable for prognosis prediction and treatment of patients with breast cancer based on their clinicopathological characteristics. |
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| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-04-10T06:32:30Z |
| publishDate | 2023-03-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Genetics |
| spelling | doaj.art-03edef078ca44c349c439a5fdcf20f632023-03-01T05:18:46ZengFrontiers Media S.A.Frontiers in Genetics1664-80212023-03-011410.3389/fgene.2023.10021571002157Construction of a fatty acid metabolism-related gene signature for predicting prognosis and immune response in breast cancerLi Qian0Yi-Fei Liu1Shu-Min Lu2Juan-Juan Yang3Hua-Jie Miao4Xin He5Hua Huang6Jian-Guo Zhang7Department of Pathology, Affiliated Hospital of Nantong University, Nantong, ChinaDepartment of Pathology, Affiliated Hospital of Nantong University, Nantong, ChinaDepartment of Oncology, Shanghai Jiaotong University School of Medicine Xinhua Hospital, Shanghai, ChinaDepartment of Pathology, Affiliated Hospital of Nantong University, Nantong, ChinaDepartment of Pathology, Affiliated Hospital of Nantong University, Nantong, ChinaDepartment of Pathology, Affiliated Hospital of Nantong University, Nantong, ChinaDepartment of Pathology, Affiliated Hospital of Nantong University, Nantong, ChinaDepartment of Pathology, Affiliated Hospital of Nantong University, Nantong, ChinaBackground: Breast cancer has the highest incidence among malignant tumors in women, and its prevalence ranks first in global cancer morbidity.Aim: This study aimed to explore the feasibility of a prognostic model for patients with breast cancer based on the differential expression of genes related to fatty acid metabolism.Methods: The mRNA expression matrix of breast cancer and paracancer tissues was downloaded from The Cancer Genome Atlas database. The differentially expressed genes related to fatty acid metabolism were screened in R language. The TRRUST database was used to predict transcriptional regulators related to hub genes and construct an mRNA–transcription factor interaction network. A consensus clustering approach was used to identify different fatty acid regulatory patterns. In combination with patient survival data, Lasso and multivariate Cox proportional risk regression models were used to establish polygenic prognostic models based on fatty acid metabolism. The median risk score was used to categorize patients into high- and low-risk groups. Kaplan–Meier survival curves were used to analyze the survival differences between both groups. The Cox regression analysis included risk score and clinicopathological factors to determine whether risk score was an independent risk factor. Models based on genes associated with fatty acid metabolism were evaluated using receiver operating characteristic curves. A comparison was made between risk score levels and the fatty acid metabolism-associated genes in different subtypes of breast cancer. The differential gene sets of the Kyoto Encyclopedia of Genes and Genomes for screening high- and low-risk populations were compared using a gene set enrichment analysis. Furthermore, we utilized CIBERSORT to examine the abundance of immune cells in breast cancer in different clustering models.Results: High expression levels of ALDH1A1 and UBE2L6 prevented breast cancer, whereas high RDH16 expression levels increased its risk. Our comprehensive assessment of the association between prognostic risk scoring models and tumor microenvironment characteristics showed significant differences in the abundance of various immune cells between high- and low-risk breast cancer patients.Conclusions: By assessing fatty acid metabolism patterns, we gained a better understanding of the infiltration characteristics of the tumor microenvironment. Our findings are valuable for prognosis prediction and treatment of patients with breast cancer based on their clinicopathological characteristics.https://www.frontiersin.org/articles/10.3389/fgene.2023.1002157/fullbreast cancergene expressionfatty acid metabolismimmune cellsprognosis |
| spellingShingle | Li Qian Yi-Fei Liu Shu-Min Lu Juan-Juan Yang Hua-Jie Miao Xin He Hua Huang Jian-Guo Zhang Construction of a fatty acid metabolism-related gene signature for predicting prognosis and immune response in breast cancer Frontiers in Genetics breast cancer gene expression fatty acid metabolism immune cells prognosis |
| title | Construction of a fatty acid metabolism-related gene signature for predicting prognosis and immune response in breast cancer |
| title_full | Construction of a fatty acid metabolism-related gene signature for predicting prognosis and immune response in breast cancer |
| title_fullStr | Construction of a fatty acid metabolism-related gene signature for predicting prognosis and immune response in breast cancer |
| title_full_unstemmed | Construction of a fatty acid metabolism-related gene signature for predicting prognosis and immune response in breast cancer |
| title_short | Construction of a fatty acid metabolism-related gene signature for predicting prognosis and immune response in breast cancer |
| title_sort | construction of a fatty acid metabolism related gene signature for predicting prognosis and immune response in breast cancer |
| topic | breast cancer gene expression fatty acid metabolism immune cells prognosis |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2023.1002157/full |
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