Identification and immunological characterization of cuproptosis-related molecular clusters in ulcerative colitis
Abstract Background Ulcerative colitis is one of the two main forms of inflammatory bowel disease. Cuproptosis is reported to be a novel mode of cell death. Methods We examined clusters of cuproptosis related genes and immune cell infiltration molecules in 86 ulcerative colitis samples from the GSE1...
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| Format: | Article |
| Language: | English |
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BMC
2023-06-01
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| Series: | BMC Gastroenterology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12876-023-02831-2 |
| _version_ | 1797752697386958848 |
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| author | Yunfei Pu Xianzhi Meng Zhichen Zou |
| author_facet | Yunfei Pu Xianzhi Meng Zhichen Zou |
| author_sort | Yunfei Pu |
| collection | DOAJ |
| description | Abstract Background Ulcerative colitis is one of the two main forms of inflammatory bowel disease. Cuproptosis is reported to be a novel mode of cell death. Methods We examined clusters of cuproptosis related genes and immune cell infiltration molecules in 86 ulcerative colitis samples from the GSE179285 dataset. We identified the differentially expressed genes according to the clustering method, and the performance of the SVM model, the random forest model, the generalized linear model, and the limit gradient enhancement model were compared, and then the optimal machine model was selected. To assess the accuracy of the learning predictions, the nomogram and the calibration curve and decision curve analyses showed that the subtypes of ulcerative colitis have been accurately predicted. Results Significant cuproptosis-related genes and immune response cells were detected between the ulcerative colitis and control groups. Two cuproptosis-associated molecular clusters were identified. Immune infiltration analysis indicated that different clusters exhibited significant heterogeneity. The immune scores for Cluster2 were elevated. Both the residual error and root mean square error of the random forest machine model had clinical significance. There was a clear correlation between the differentially expressed genes in cluster 2 and the response of immune cells. The nomogram and the calibration curve and decision curve analyses showed that the subtypes of ulcerative colitis had sufficient accuracy. Conclusion We examined the complex relationship between cuproptosis and ulcerative colitis in a systematic manner. To estimate the likelihood that each subtype of cuproptosis will occur in ulcerative colitis patients and their disease outcome, we developed a promising prediction model. |
| first_indexed | 2024-03-12T17:08:19Z |
| format | Article |
| id | doaj.art-7545f58f3b71476f911fb1db5f713afd |
| institution | Directory Open Access Journal |
| issn | 1471-230X |
| language | English |
| last_indexed | 2024-03-12T17:08:19Z |
| publishDate | 2023-06-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Gastroenterology |
| spelling | doaj.art-7545f58f3b71476f911fb1db5f713afd2023-08-06T11:16:12ZengBMCBMC Gastroenterology1471-230X2023-06-0123111410.1186/s12876-023-02831-2Identification and immunological characterization of cuproptosis-related molecular clusters in ulcerative colitisYunfei Pu0Xianzhi Meng1Zhichen Zou2The First Affiliated Hospital of Harbin Medical UniversityDepartment of Minimally Invasive Biliary Surgery, The First Affiliated Hospital of Harbin Medical UniversityThe First Affiliated Hospital of Harbin Medical UniversityAbstract Background Ulcerative colitis is one of the two main forms of inflammatory bowel disease. Cuproptosis is reported to be a novel mode of cell death. Methods We examined clusters of cuproptosis related genes and immune cell infiltration molecules in 86 ulcerative colitis samples from the GSE179285 dataset. We identified the differentially expressed genes according to the clustering method, and the performance of the SVM model, the random forest model, the generalized linear model, and the limit gradient enhancement model were compared, and then the optimal machine model was selected. To assess the accuracy of the learning predictions, the nomogram and the calibration curve and decision curve analyses showed that the subtypes of ulcerative colitis have been accurately predicted. Results Significant cuproptosis-related genes and immune response cells were detected between the ulcerative colitis and control groups. Two cuproptosis-associated molecular clusters were identified. Immune infiltration analysis indicated that different clusters exhibited significant heterogeneity. The immune scores for Cluster2 were elevated. Both the residual error and root mean square error of the random forest machine model had clinical significance. There was a clear correlation between the differentially expressed genes in cluster 2 and the response of immune cells. The nomogram and the calibration curve and decision curve analyses showed that the subtypes of ulcerative colitis had sufficient accuracy. Conclusion We examined the complex relationship between cuproptosis and ulcerative colitis in a systematic manner. To estimate the likelihood that each subtype of cuproptosis will occur in ulcerative colitis patients and their disease outcome, we developed a promising prediction model.https://doi.org/10.1186/s12876-023-02831-2CuproptosisUlcerative colitisPrediction modelMolecular clustersMachine learning |
| spellingShingle | Yunfei Pu Xianzhi Meng Zhichen Zou Identification and immunological characterization of cuproptosis-related molecular clusters in ulcerative colitis BMC Gastroenterology Cuproptosis Ulcerative colitis Prediction model Molecular clusters Machine learning |
| title | Identification and immunological characterization of cuproptosis-related molecular clusters in ulcerative colitis |
| title_full | Identification and immunological characterization of cuproptosis-related molecular clusters in ulcerative colitis |
| title_fullStr | Identification and immunological characterization of cuproptosis-related molecular clusters in ulcerative colitis |
| title_full_unstemmed | Identification and immunological characterization of cuproptosis-related molecular clusters in ulcerative colitis |
| title_short | Identification and immunological characterization of cuproptosis-related molecular clusters in ulcerative colitis |
| title_sort | identification and immunological characterization of cuproptosis related molecular clusters in ulcerative colitis |
| topic | Cuproptosis Ulcerative colitis Prediction model Molecular clusters Machine learning |
| url | https://doi.org/10.1186/s12876-023-02831-2 |
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