Patient stratification based on urea cycle metabolism for exploration of combination immunotherapy in colon cancer
Abstract Background Owing to the low ratio of patients benefitting from immunotherapy, patient stratification becomes necessary. An accurate patient stratification contributes to therapy for different tumor types. Therefore, this study aimed to subdivide colon cancer patients for improved combinatio...
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| Format: | Article |
| Language: | English |
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BMC
2022-08-01
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| Series: | BMC Cancer |
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| Online Access: | https://doi.org/10.1186/s12885-022-09958-7 |
| _version_ | 1811215532948455424 |
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| author | Zirui Zhao Haohan Liu Deliang Fang Xingyu Zhou Shaoji Zhao Chaoyue Zhang Jinning Ye Jianbo Xu |
| author_facet | Zirui Zhao Haohan Liu Deliang Fang Xingyu Zhou Shaoji Zhao Chaoyue Zhang Jinning Ye Jianbo Xu |
| author_sort | Zirui Zhao |
| collection | DOAJ |
| description | Abstract Background Owing to the low ratio of patients benefitting from immunotherapy, patient stratification becomes necessary. An accurate patient stratification contributes to therapy for different tumor types. Therefore, this study aimed to subdivide colon cancer patients for improved combination immunotherapy. Methods We characterized the patients based on urea cycle metabolism, performed a consensus clustering analysis and constructed a risk model in the cancer genome atlas cohort. Colon cancer patients were further categorized into two tags: clusters, and risk groups, for the exploration of combination immunotherapy. In addition to external validation in the Gene Expression Omnibus datasets, several images of immunohistochemistry were used for further validation. Results Patient characterization based on urea cycle metabolism was related to immune infiltration. An analysis of consensus clustering and immune infiltration generated a cluster distribution and identified patients in cluster 1 with high immune infiltration levels as hot tumors for immunotherapy. A risk model of seven genes was constructed to subdivide the patients into low- and high-risk groups. Validation was performed using a cohort of 731 colon cancer patients. Patients in cluster 1 had a higher immunophenoscore (IPS) in immune checkpoint inhibitor therapy, and those other risk groups displayed varying sensitivities to potential combination immunotherapeutic agents. Finally, we subdivided the colon cancer patients into four groups to explore combination immunotherapy. Immunohistochemistry analysis showed that protein expression of two genes were upregulated while that of other two genes were downregulated or undetected in cancerous colon tissues. Conclusion Using subdivision to combine chemotherapy with immunotherapy would not only change the dilemma of immunotherapy in not hot tumors, but also promote the proposition of more rational personalized therapy strategies in future. |
| first_indexed | 2024-04-12T06:24:05Z |
| format | Article |
| id | doaj.art-dd58f0f20a8d4626a1ee07aac4d9de75 |
| institution | Directory Open Access Journal |
| issn | 1471-2407 |
| language | English |
| last_indexed | 2024-04-12T06:24:05Z |
| publishDate | 2022-08-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Cancer |
| spelling | doaj.art-dd58f0f20a8d4626a1ee07aac4d9de752022-12-22T03:44:14ZengBMCBMC Cancer1471-24072022-08-0122111510.1186/s12885-022-09958-7Patient stratification based on urea cycle metabolism for exploration of combination immunotherapy in colon cancerZirui Zhao0Haohan Liu1Deliang Fang2Xingyu Zhou3Shaoji Zhao4Chaoyue Zhang5Jinning Ye6Jianbo Xu7Department of Gastrointestinal Surgery, First Affiliated Hospital of Sun Yat-Sen UniversityDepartment of Gastrointestinal Surgery, First Affiliated Hospital of Sun Yat-Sen UniversityDepartment of Gastrointestinal Surgery, First Affiliated Hospital of Sun Yat-Sen UniversityDepartment of Gastrointestinal Surgery, First Affiliated Hospital of Sun Yat-Sen UniversityDepartment of Gastrointestinal Surgery, First Affiliated Hospital of Sun Yat-Sen UniversityDepartment of Gastrointestinal Surgery, First Affiliated Hospital of Sun Yat-Sen UniversityDepartment of Gastrointestinal Surgery, First Affiliated Hospital of Sun Yat-Sen UniversityDepartment of Gastrointestinal Surgery, First Affiliated Hospital of Sun Yat-Sen UniversityAbstract Background Owing to the low ratio of patients benefitting from immunotherapy, patient stratification becomes necessary. An accurate patient stratification contributes to therapy for different tumor types. Therefore, this study aimed to subdivide colon cancer patients for improved combination immunotherapy. Methods We characterized the patients based on urea cycle metabolism, performed a consensus clustering analysis and constructed a risk model in the cancer genome atlas cohort. Colon cancer patients were further categorized into two tags: clusters, and risk groups, for the exploration of combination immunotherapy. In addition to external validation in the Gene Expression Omnibus datasets, several images of immunohistochemistry were used for further validation. Results Patient characterization based on urea cycle metabolism was related to immune infiltration. An analysis of consensus clustering and immune infiltration generated a cluster distribution and identified patients in cluster 1 with high immune infiltration levels as hot tumors for immunotherapy. A risk model of seven genes was constructed to subdivide the patients into low- and high-risk groups. Validation was performed using a cohort of 731 colon cancer patients. Patients in cluster 1 had a higher immunophenoscore (IPS) in immune checkpoint inhibitor therapy, and those other risk groups displayed varying sensitivities to potential combination immunotherapeutic agents. Finally, we subdivided the colon cancer patients into four groups to explore combination immunotherapy. Immunohistochemistry analysis showed that protein expression of two genes were upregulated while that of other two genes were downregulated or undetected in cancerous colon tissues. Conclusion Using subdivision to combine chemotherapy with immunotherapy would not only change the dilemma of immunotherapy in not hot tumors, but also promote the proposition of more rational personalized therapy strategies in future.https://doi.org/10.1186/s12885-022-09958-7Urea cycle metabolismColon cancerHot tumorsSubdividingCombination immunotherapy |
| spellingShingle | Zirui Zhao Haohan Liu Deliang Fang Xingyu Zhou Shaoji Zhao Chaoyue Zhang Jinning Ye Jianbo Xu Patient stratification based on urea cycle metabolism for exploration of combination immunotherapy in colon cancer BMC Cancer Urea cycle metabolism Colon cancer Hot tumors Subdividing Combination immunotherapy |
| title | Patient stratification based on urea cycle metabolism for exploration of combination immunotherapy in colon cancer |
| title_full | Patient stratification based on urea cycle metabolism for exploration of combination immunotherapy in colon cancer |
| title_fullStr | Patient stratification based on urea cycle metabolism for exploration of combination immunotherapy in colon cancer |
| title_full_unstemmed | Patient stratification based on urea cycle metabolism for exploration of combination immunotherapy in colon cancer |
| title_short | Patient stratification based on urea cycle metabolism for exploration of combination immunotherapy in colon cancer |
| title_sort | patient stratification based on urea cycle metabolism for exploration of combination immunotherapy in colon cancer |
| topic | Urea cycle metabolism Colon cancer Hot tumors Subdividing Combination immunotherapy |
| url | https://doi.org/10.1186/s12885-022-09958-7 |
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