Immune gene features and prognosis in colorectal cancer: insights from ssGSEA typing
Abstract Background Colorectal cancer (CRC) is a molecularly heterogeneous disease, and its treatment and prognosis vary greatly among subgroups. Therefore, it is necessary to identify prognostic factors associated with the biological heterogeneity of CRC in order to improve patients' survival...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-02-01
|
| Series: | Discover Oncology |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s12672-025-01928-2 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1823862011094630400 |
|---|---|
| author | Anwen Huang Jinxiu Wu Jiakuan Wang Chengwen Jiao Yunfei Yang Huaiwen Xiao Li Yao |
| author_facet | Anwen Huang Jinxiu Wu Jiakuan Wang Chengwen Jiao Yunfei Yang Huaiwen Xiao Li Yao |
| author_sort | Anwen Huang |
| collection | DOAJ |
| description | Abstract Background Colorectal cancer (CRC) is a molecularly heterogeneous disease, and its treatment and prognosis vary greatly among subgroups. Therefore, it is necessary to identify prognostic factors associated with the biological heterogeneity of CRC in order to improve patients' survival expectations. Methods We obtained and merged RNA-Seq data along with clinical details for colorectal cancer (CRC) from The Cancer Genome Atlas (TCGA) repository, and then performed immunocluster typing on all CRC specimens. We conducted differential expression gene (DEG) analysis, gene set enrichment analysis (GSEA), and tumor microenvironment (TME) analysis on CRC samples that were divided into high and low Immunity categories. Moreover, we pinpointed prognostic genes from immune-related gene (IRGs) sets, developed a prognostic risk model, and executed survival analysis, receiver operating characteristic (ROC) curve analysis, and independent prognostic analysis. Additionally, we assessed the risk for patients categorized into high- and low-risk groups based on the model. Lastly, we created a Nomogram to customize the prediction of survival outcomes in CRC patients. Results CRC samples were divided into high and low Immunity groups based on the median value of the immunity score. Between the two groups, a total of 1550 DEGs were identified and 395 differentially expressed immune-related genes (DE-IRGs) were identified by intersection with 2483 IRGs. The DE-IRGs of the high Immunity group were dominated by Cytokine receptor interactions, chemokine signaling pathways and immune cell-mediated cytotoxicity, and molecule function of immune effector process. TME analysis showed that most of the 27 immune cells and functions were highly enriched in high Immunity group, whose Immune Score, Stromal Score and ESTIMATE Score were significantly higher. Subsequently, a prognostic risk model of CRC was constructed based on 12 prognostic genes, and the accuracy and reliability of the model prediction were verified. Finally, Nomogram enabled accurate individual prediction of the survival prognosis of CRC patients. Conclusions Our study develops an immune-related prognostic model and Nomogram that reliably predicts survival outcomes in CRC patients and enhances understanding of the tumor immunity and molecular mechanisms of CRC. |
| format | Article |
| id | doaj-art-e5aec00819114ce98a6d71fed0c48d2d |
| institution | Kabale University |
| issn | 2730-6011 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Oncology |
| spelling | doaj-art-e5aec00819114ce98a6d71fed0c48d2d2025-02-09T12:43:23ZengSpringerDiscover Oncology2730-60112025-02-0116111510.1007/s12672-025-01928-2Immune gene features and prognosis in colorectal cancer: insights from ssGSEA typingAnwen Huang0Jinxiu Wu1Jiakuan Wang2Chengwen Jiao3Yunfei Yang4Huaiwen Xiao5Li Yao6Department of Hepatopancreatobiliary Surgery, Shanghai Punan HospitalDepartment of General Surgery, Shanghai Punan HospitalDepartment of General Surgery, Shanghai Punan HospitalDepartment of General Surgery, Shanghai Punan HospitalDepartment of General Surgery, Shanghai Punan HospitalDepartment of General Surgery, Shanghai Punan HospitalDepartment of General Surgery, Shanghai Punan HospitalAbstract Background Colorectal cancer (CRC) is a molecularly heterogeneous disease, and its treatment and prognosis vary greatly among subgroups. Therefore, it is necessary to identify prognostic factors associated with the biological heterogeneity of CRC in order to improve patients' survival expectations. Methods We obtained and merged RNA-Seq data along with clinical details for colorectal cancer (CRC) from The Cancer Genome Atlas (TCGA) repository, and then performed immunocluster typing on all CRC specimens. We conducted differential expression gene (DEG) analysis, gene set enrichment analysis (GSEA), and tumor microenvironment (TME) analysis on CRC samples that were divided into high and low Immunity categories. Moreover, we pinpointed prognostic genes from immune-related gene (IRGs) sets, developed a prognostic risk model, and executed survival analysis, receiver operating characteristic (ROC) curve analysis, and independent prognostic analysis. Additionally, we assessed the risk for patients categorized into high- and low-risk groups based on the model. Lastly, we created a Nomogram to customize the prediction of survival outcomes in CRC patients. Results CRC samples were divided into high and low Immunity groups based on the median value of the immunity score. Between the two groups, a total of 1550 DEGs were identified and 395 differentially expressed immune-related genes (DE-IRGs) were identified by intersection with 2483 IRGs. The DE-IRGs of the high Immunity group were dominated by Cytokine receptor interactions, chemokine signaling pathways and immune cell-mediated cytotoxicity, and molecule function of immune effector process. TME analysis showed that most of the 27 immune cells and functions were highly enriched in high Immunity group, whose Immune Score, Stromal Score and ESTIMATE Score were significantly higher. Subsequently, a prognostic risk model of CRC was constructed based on 12 prognostic genes, and the accuracy and reliability of the model prediction were verified. Finally, Nomogram enabled accurate individual prediction of the survival prognosis of CRC patients. Conclusions Our study develops an immune-related prognostic model and Nomogram that reliably predicts survival outcomes in CRC patients and enhances understanding of the tumor immunity and molecular mechanisms of CRC.https://doi.org/10.1007/s12672-025-01928-2Colorectal cancerImmune genessGSEAPrognosis modelNomogram |
| spellingShingle | Anwen Huang Jinxiu Wu Jiakuan Wang Chengwen Jiao Yunfei Yang Huaiwen Xiao Li Yao Immune gene features and prognosis in colorectal cancer: insights from ssGSEA typing Discover Oncology Colorectal cancer Immune gene ssGSEA Prognosis model Nomogram |
| title | Immune gene features and prognosis in colorectal cancer: insights from ssGSEA typing |
| title_full | Immune gene features and prognosis in colorectal cancer: insights from ssGSEA typing |
| title_fullStr | Immune gene features and prognosis in colorectal cancer: insights from ssGSEA typing |
| title_full_unstemmed | Immune gene features and prognosis in colorectal cancer: insights from ssGSEA typing |
| title_short | Immune gene features and prognosis in colorectal cancer: insights from ssGSEA typing |
| title_sort | immune gene features and prognosis in colorectal cancer insights from ssgsea typing |
| topic | Colorectal cancer Immune gene ssGSEA Prognosis model Nomogram |
| url | https://doi.org/10.1007/s12672-025-01928-2 |
| work_keys_str_mv | AT anwenhuang immunegenefeaturesandprognosisincolorectalcancerinsightsfromssgseatyping AT jinxiuwu immunegenefeaturesandprognosisincolorectalcancerinsightsfromssgseatyping AT jiakuanwang immunegenefeaturesandprognosisincolorectalcancerinsightsfromssgseatyping AT chengwenjiao immunegenefeaturesandprognosisincolorectalcancerinsightsfromssgseatyping AT yunfeiyang immunegenefeaturesandprognosisincolorectalcancerinsightsfromssgseatyping AT huaiwenxiao immunegenefeaturesandprognosisincolorectalcancerinsightsfromssgseatyping AT liyao immunegenefeaturesandprognosisincolorectalcancerinsightsfromssgseatyping |