Immunogram defines four cancer-immunity cycle phenotypes with distinct clonal selection patterns across solid tumors
Abstract Background The cancer-immunity cycle (CI cycle) provides a theoretical framework to illustrate the process of the anticancer immune response. Recently, the update of the CI cycle theory emphasizes the importance of tumor’s immunological phenotype. However, there is lack of immunological phe...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ying Hu [verfasserIn] Huaibo Sun [verfasserIn] Wei Shi [verfasserIn] Chen Chen [verfasserIn] Xueying Wu [verfasserIn] Yu Jiang [verfasserIn] Guoying Zhang [verfasserIn] Na Li [verfasserIn] Jin Song [verfasserIn] Hao Zhang [verfasserIn] Baiyong Shen [verfasserIn] Hui Zeng [verfasserIn] Henghui Zhang [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2024 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
In: Journal of Translational Medicine - BMC, 2003, 22(2024), 1, Seite 15 |
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| Übergeordnetes Werk: |
volume:22 ; year:2024 ; number:1 ; pages:15 |
| Links: |
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| DOI / URN: |
10.1186/s12967-023-04765-5 |
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| Katalog-ID: |
DOAJ097418072 |
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| 245 | 1 | 0 | |a Immunogram defines four cancer-immunity cycle phenotypes with distinct clonal selection patterns across solid tumors |
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| 520 | |a Abstract Background The cancer-immunity cycle (CI cycle) provides a theoretical framework to illustrate the process of the anticancer immune response. Recently, the update of the CI cycle theory emphasizes the importance of tumor’s immunological phenotype. However, there is lack of immunological phenotype of pan-cancer based on CI cycle theory. Methods Here, we applied a visualizing method termed ‘cancer immunogram’ to visualize the state of CI cycle of 8460 solid tumors from TCGA cohort. Unsupervised clustering of the cancer immunogram was performed using the nonnegative matrix factorization (NMF) analysis. We applied an evolutionary genomics approach (dN/dS ratio) to evaluate the clonal selection patterns of tumors with distinct immunogram subtypes. Results We defined four major CI cycle patterns across 32 cancer types using a cancer immunogram approach. Immunogram-I was characterized by ‘hot’ and ‘exhausted’ features, indicating a favorable prognosis. Strikingly, immunogram-II, immunogram-III, and immunogram-IV represented distinct immunosuppressive patterns of ‘cold’ tumor. Immunogram-II was characterized by ‘cold’ and ‘radical’ features, which represented increased expression of immune inhibitor molecules and high levels of positive selection, indicating the worst prognosis. Immunogram-III was characterized by ‘cold’ and ‘recognizable’ features and upregulated expression of MHC I molecules. Immunogram-IV was characterized by ‘cold’ and ‘inert’ features, which represented overall immunosuppression, lower levels of immunoediting and positive selection, and accumulation of more tumor neoantigens. In particular, favorable overall survival was observed in metastatic urothelial cancer patients with immunogram-I and immunogram-IV after immune checkpoint inhibitor (ICI) therapy. Meanwhile, a higher response rate to ICI therapy was observed in metastatic gastric cancer patients with immunogram-I phenotype. Conclusions Our findings provide new insight into the interaction between immunity and cancer evolution, which may contribute to optimizing immunotherapy strategies. | ||
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| 700 | 0 | |a Henghui Zhang |e verfasserin |4 aut | |
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10.1186/s12967-023-04765-5 doi (DE-627)DOAJ097418072 (DE-599)DOAJf03396aa98b249cab9801dcaa45b6298 DE-627 ger DE-627 rakwb eng Ying Hu verfasserin aut Immunogram defines four cancer-immunity cycle phenotypes with distinct clonal selection patterns across solid tumors 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background The cancer-immunity cycle (CI cycle) provides a theoretical framework to illustrate the process of the anticancer immune response. Recently, the update of the CI cycle theory emphasizes the importance of tumor’s immunological phenotype. However, there is lack of immunological phenotype of pan-cancer based on CI cycle theory. Methods Here, we applied a visualizing method termed ‘cancer immunogram’ to visualize the state of CI cycle of 8460 solid tumors from TCGA cohort. Unsupervised clustering of the cancer immunogram was performed using the nonnegative matrix factorization (NMF) analysis. We applied an evolutionary genomics approach (dN/dS ratio) to evaluate the clonal selection patterns of tumors with distinct immunogram subtypes. Results We defined four major CI cycle patterns across 32 cancer types using a cancer immunogram approach. Immunogram-I was characterized by ‘hot’ and ‘exhausted’ features, indicating a favorable prognosis. Strikingly, immunogram-II, immunogram-III, and immunogram-IV represented distinct immunosuppressive patterns of ‘cold’ tumor. Immunogram-II was characterized by ‘cold’ and ‘radical’ features, which represented increased expression of immune inhibitor molecules and high levels of positive selection, indicating the worst prognosis. Immunogram-III was characterized by ‘cold’ and ‘recognizable’ features and upregulated expression of MHC I molecules. Immunogram-IV was characterized by ‘cold’ and ‘inert’ features, which represented overall immunosuppression, lower levels of immunoediting and positive selection, and accumulation of more tumor neoantigens. In particular, favorable overall survival was observed in metastatic urothelial cancer patients with immunogram-I and immunogram-IV after immune checkpoint inhibitor (ICI) therapy. Meanwhile, a higher response rate to ICI therapy was observed in metastatic gastric cancer patients with immunogram-I phenotype. Conclusions Our findings provide new insight into the interaction between immunity and cancer evolution, which may contribute to optimizing immunotherapy strategies. Cancer-immunity cycle Immunogram Clonal selection Cancer evolution Immune checkpoint inhibitor Medicine R Huaibo Sun verfasserin aut Wei Shi verfasserin aut Chen Chen verfasserin aut Xueying Wu verfasserin aut Yu Jiang verfasserin aut Guoying Zhang verfasserin aut Na Li verfasserin aut Jin Song verfasserin aut Hao Zhang verfasserin aut Baiyong Shen verfasserin aut Hui Zeng verfasserin aut Henghui Zhang verfasserin aut In Journal of Translational Medicine BMC, 2003 22(2024), 1, Seite 15 (DE-627)369084136 (DE-600)2118570-0 14795876 nnns volume:22 year:2024 number:1 pages:15 https://doi.org/10.1186/s12967-023-04765-5 kostenfrei https://doaj.org/article/f03396aa98b249cab9801dcaa45b6298 kostenfrei https://doi.org/10.1186/s12967-023-04765-5 kostenfrei https://doaj.org/toc/1479-5876 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2024 1 15 |
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10.1186/s12967-023-04765-5 doi (DE-627)DOAJ097418072 (DE-599)DOAJf03396aa98b249cab9801dcaa45b6298 DE-627 ger DE-627 rakwb eng Ying Hu verfasserin aut Immunogram defines four cancer-immunity cycle phenotypes with distinct clonal selection patterns across solid tumors 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background The cancer-immunity cycle (CI cycle) provides a theoretical framework to illustrate the process of the anticancer immune response. Recently, the update of the CI cycle theory emphasizes the importance of tumor’s immunological phenotype. However, there is lack of immunological phenotype of pan-cancer based on CI cycle theory. Methods Here, we applied a visualizing method termed ‘cancer immunogram’ to visualize the state of CI cycle of 8460 solid tumors from TCGA cohort. Unsupervised clustering of the cancer immunogram was performed using the nonnegative matrix factorization (NMF) analysis. We applied an evolutionary genomics approach (dN/dS ratio) to evaluate the clonal selection patterns of tumors with distinct immunogram subtypes. Results We defined four major CI cycle patterns across 32 cancer types using a cancer immunogram approach. Immunogram-I was characterized by ‘hot’ and ‘exhausted’ features, indicating a favorable prognosis. Strikingly, immunogram-II, immunogram-III, and immunogram-IV represented distinct immunosuppressive patterns of ‘cold’ tumor. Immunogram-II was characterized by ‘cold’ and ‘radical’ features, which represented increased expression of immune inhibitor molecules and high levels of positive selection, indicating the worst prognosis. Immunogram-III was characterized by ‘cold’ and ‘recognizable’ features and upregulated expression of MHC I molecules. Immunogram-IV was characterized by ‘cold’ and ‘inert’ features, which represented overall immunosuppression, lower levels of immunoediting and positive selection, and accumulation of more tumor neoantigens. In particular, favorable overall survival was observed in metastatic urothelial cancer patients with immunogram-I and immunogram-IV after immune checkpoint inhibitor (ICI) therapy. Meanwhile, a higher response rate to ICI therapy was observed in metastatic gastric cancer patients with immunogram-I phenotype. Conclusions Our findings provide new insight into the interaction between immunity and cancer evolution, which may contribute to optimizing immunotherapy strategies. Cancer-immunity cycle Immunogram Clonal selection Cancer evolution Immune checkpoint inhibitor Medicine R Huaibo Sun verfasserin aut Wei Shi verfasserin aut Chen Chen verfasserin aut Xueying Wu verfasserin aut Yu Jiang verfasserin aut Guoying Zhang verfasserin aut Na Li verfasserin aut Jin Song verfasserin aut Hao Zhang verfasserin aut Baiyong Shen verfasserin aut Hui Zeng verfasserin aut Henghui Zhang verfasserin aut In Journal of Translational Medicine BMC, 2003 22(2024), 1, Seite 15 (DE-627)369084136 (DE-600)2118570-0 14795876 nnns volume:22 year:2024 number:1 pages:15 https://doi.org/10.1186/s12967-023-04765-5 kostenfrei https://doaj.org/article/f03396aa98b249cab9801dcaa45b6298 kostenfrei https://doi.org/10.1186/s12967-023-04765-5 kostenfrei https://doaj.org/toc/1479-5876 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2024 1 15 |
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10.1186/s12967-023-04765-5 doi (DE-627)DOAJ097418072 (DE-599)DOAJf03396aa98b249cab9801dcaa45b6298 DE-627 ger DE-627 rakwb eng Ying Hu verfasserin aut Immunogram defines four cancer-immunity cycle phenotypes with distinct clonal selection patterns across solid tumors 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background The cancer-immunity cycle (CI cycle) provides a theoretical framework to illustrate the process of the anticancer immune response. Recently, the update of the CI cycle theory emphasizes the importance of tumor’s immunological phenotype. However, there is lack of immunological phenotype of pan-cancer based on CI cycle theory. Methods Here, we applied a visualizing method termed ‘cancer immunogram’ to visualize the state of CI cycle of 8460 solid tumors from TCGA cohort. Unsupervised clustering of the cancer immunogram was performed using the nonnegative matrix factorization (NMF) analysis. We applied an evolutionary genomics approach (dN/dS ratio) to evaluate the clonal selection patterns of tumors with distinct immunogram subtypes. Results We defined four major CI cycle patterns across 32 cancer types using a cancer immunogram approach. Immunogram-I was characterized by ‘hot’ and ‘exhausted’ features, indicating a favorable prognosis. Strikingly, immunogram-II, immunogram-III, and immunogram-IV represented distinct immunosuppressive patterns of ‘cold’ tumor. Immunogram-II was characterized by ‘cold’ and ‘radical’ features, which represented increased expression of immune inhibitor molecules and high levels of positive selection, indicating the worst prognosis. Immunogram-III was characterized by ‘cold’ and ‘recognizable’ features and upregulated expression of MHC I molecules. Immunogram-IV was characterized by ‘cold’ and ‘inert’ features, which represented overall immunosuppression, lower levels of immunoediting and positive selection, and accumulation of more tumor neoantigens. In particular, favorable overall survival was observed in metastatic urothelial cancer patients with immunogram-I and immunogram-IV after immune checkpoint inhibitor (ICI) therapy. Meanwhile, a higher response rate to ICI therapy was observed in metastatic gastric cancer patients with immunogram-I phenotype. Conclusions Our findings provide new insight into the interaction between immunity and cancer evolution, which may contribute to optimizing immunotherapy strategies. Cancer-immunity cycle Immunogram Clonal selection Cancer evolution Immune checkpoint inhibitor Medicine R Huaibo Sun verfasserin aut Wei Shi verfasserin aut Chen Chen verfasserin aut Xueying Wu verfasserin aut Yu Jiang verfasserin aut Guoying Zhang verfasserin aut Na Li verfasserin aut Jin Song verfasserin aut Hao Zhang verfasserin aut Baiyong Shen verfasserin aut Hui Zeng verfasserin aut Henghui Zhang verfasserin aut In Journal of Translational Medicine BMC, 2003 22(2024), 1, Seite 15 (DE-627)369084136 (DE-600)2118570-0 14795876 nnns volume:22 year:2024 number:1 pages:15 https://doi.org/10.1186/s12967-023-04765-5 kostenfrei https://doaj.org/article/f03396aa98b249cab9801dcaa45b6298 kostenfrei https://doi.org/10.1186/s12967-023-04765-5 kostenfrei https://doaj.org/toc/1479-5876 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2024 1 15 |
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10.1186/s12967-023-04765-5 doi (DE-627)DOAJ097418072 (DE-599)DOAJf03396aa98b249cab9801dcaa45b6298 DE-627 ger DE-627 rakwb eng Ying Hu verfasserin aut Immunogram defines four cancer-immunity cycle phenotypes with distinct clonal selection patterns across solid tumors 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background The cancer-immunity cycle (CI cycle) provides a theoretical framework to illustrate the process of the anticancer immune response. Recently, the update of the CI cycle theory emphasizes the importance of tumor’s immunological phenotype. However, there is lack of immunological phenotype of pan-cancer based on CI cycle theory. Methods Here, we applied a visualizing method termed ‘cancer immunogram’ to visualize the state of CI cycle of 8460 solid tumors from TCGA cohort. Unsupervised clustering of the cancer immunogram was performed using the nonnegative matrix factorization (NMF) analysis. We applied an evolutionary genomics approach (dN/dS ratio) to evaluate the clonal selection patterns of tumors with distinct immunogram subtypes. Results We defined four major CI cycle patterns across 32 cancer types using a cancer immunogram approach. Immunogram-I was characterized by ‘hot’ and ‘exhausted’ features, indicating a favorable prognosis. Strikingly, immunogram-II, immunogram-III, and immunogram-IV represented distinct immunosuppressive patterns of ‘cold’ tumor. Immunogram-II was characterized by ‘cold’ and ‘radical’ features, which represented increased expression of immune inhibitor molecules and high levels of positive selection, indicating the worst prognosis. Immunogram-III was characterized by ‘cold’ and ‘recognizable’ features and upregulated expression of MHC I molecules. Immunogram-IV was characterized by ‘cold’ and ‘inert’ features, which represented overall immunosuppression, lower levels of immunoediting and positive selection, and accumulation of more tumor neoantigens. In particular, favorable overall survival was observed in metastatic urothelial cancer patients with immunogram-I and immunogram-IV after immune checkpoint inhibitor (ICI) therapy. Meanwhile, a higher response rate to ICI therapy was observed in metastatic gastric cancer patients with immunogram-I phenotype. Conclusions Our findings provide new insight into the interaction between immunity and cancer evolution, which may contribute to optimizing immunotherapy strategies. Cancer-immunity cycle Immunogram Clonal selection Cancer evolution Immune checkpoint inhibitor Medicine R Huaibo Sun verfasserin aut Wei Shi verfasserin aut Chen Chen verfasserin aut Xueying Wu verfasserin aut Yu Jiang verfasserin aut Guoying Zhang verfasserin aut Na Li verfasserin aut Jin Song verfasserin aut Hao Zhang verfasserin aut Baiyong Shen verfasserin aut Hui Zeng verfasserin aut Henghui Zhang verfasserin aut In Journal of Translational Medicine BMC, 2003 22(2024), 1, Seite 15 (DE-627)369084136 (DE-600)2118570-0 14795876 nnns volume:22 year:2024 number:1 pages:15 https://doi.org/10.1186/s12967-023-04765-5 kostenfrei https://doaj.org/article/f03396aa98b249cab9801dcaa45b6298 kostenfrei https://doi.org/10.1186/s12967-023-04765-5 kostenfrei https://doaj.org/toc/1479-5876 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2024 1 15 |
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10.1186/s12967-023-04765-5 doi (DE-627)DOAJ097418072 (DE-599)DOAJf03396aa98b249cab9801dcaa45b6298 DE-627 ger DE-627 rakwb eng Ying Hu verfasserin aut Immunogram defines four cancer-immunity cycle phenotypes with distinct clonal selection patterns across solid tumors 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background The cancer-immunity cycle (CI cycle) provides a theoretical framework to illustrate the process of the anticancer immune response. Recently, the update of the CI cycle theory emphasizes the importance of tumor’s immunological phenotype. However, there is lack of immunological phenotype of pan-cancer based on CI cycle theory. Methods Here, we applied a visualizing method termed ‘cancer immunogram’ to visualize the state of CI cycle of 8460 solid tumors from TCGA cohort. Unsupervised clustering of the cancer immunogram was performed using the nonnegative matrix factorization (NMF) analysis. We applied an evolutionary genomics approach (dN/dS ratio) to evaluate the clonal selection patterns of tumors with distinct immunogram subtypes. Results We defined four major CI cycle patterns across 32 cancer types using a cancer immunogram approach. Immunogram-I was characterized by ‘hot’ and ‘exhausted’ features, indicating a favorable prognosis. Strikingly, immunogram-II, immunogram-III, and immunogram-IV represented distinct immunosuppressive patterns of ‘cold’ tumor. Immunogram-II was characterized by ‘cold’ and ‘radical’ features, which represented increased expression of immune inhibitor molecules and high levels of positive selection, indicating the worst prognosis. Immunogram-III was characterized by ‘cold’ and ‘recognizable’ features and upregulated expression of MHC I molecules. Immunogram-IV was characterized by ‘cold’ and ‘inert’ features, which represented overall immunosuppression, lower levels of immunoediting and positive selection, and accumulation of more tumor neoantigens. In particular, favorable overall survival was observed in metastatic urothelial cancer patients with immunogram-I and immunogram-IV after immune checkpoint inhibitor (ICI) therapy. Meanwhile, a higher response rate to ICI therapy was observed in metastatic gastric cancer patients with immunogram-I phenotype. Conclusions Our findings provide new insight into the interaction between immunity and cancer evolution, which may contribute to optimizing immunotherapy strategies. Cancer-immunity cycle Immunogram Clonal selection Cancer evolution Immune checkpoint inhibitor Medicine R Huaibo Sun verfasserin aut Wei Shi verfasserin aut Chen Chen verfasserin aut Xueying Wu verfasserin aut Yu Jiang verfasserin aut Guoying Zhang verfasserin aut Na Li verfasserin aut Jin Song verfasserin aut Hao Zhang verfasserin aut Baiyong Shen verfasserin aut Hui Zeng verfasserin aut Henghui Zhang verfasserin aut In Journal of Translational Medicine BMC, 2003 22(2024), 1, Seite 15 (DE-627)369084136 (DE-600)2118570-0 14795876 nnns volume:22 year:2024 number:1 pages:15 https://doi.org/10.1186/s12967-023-04765-5 kostenfrei https://doaj.org/article/f03396aa98b249cab9801dcaa45b6298 kostenfrei https://doi.org/10.1186/s12967-023-04765-5 kostenfrei https://doaj.org/toc/1479-5876 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2024 1 15 |
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Immunogram defines four cancer-immunity cycle phenotypes with distinct clonal selection patterns across solid tumors |
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Abstract Background The cancer-immunity cycle (CI cycle) provides a theoretical framework to illustrate the process of the anticancer immune response. Recently, the update of the CI cycle theory emphasizes the importance of tumor’s immunological phenotype. However, there is lack of immunological phenotype of pan-cancer based on CI cycle theory. Methods Here, we applied a visualizing method termed ‘cancer immunogram’ to visualize the state of CI cycle of 8460 solid tumors from TCGA cohort. Unsupervised clustering of the cancer immunogram was performed using the nonnegative matrix factorization (NMF) analysis. We applied an evolutionary genomics approach (dN/dS ratio) to evaluate the clonal selection patterns of tumors with distinct immunogram subtypes. Results We defined four major CI cycle patterns across 32 cancer types using a cancer immunogram approach. Immunogram-I was characterized by ‘hot’ and ‘exhausted’ features, indicating a favorable prognosis. Strikingly, immunogram-II, immunogram-III, and immunogram-IV represented distinct immunosuppressive patterns of ‘cold’ tumor. Immunogram-II was characterized by ‘cold’ and ‘radical’ features, which represented increased expression of immune inhibitor molecules and high levels of positive selection, indicating the worst prognosis. Immunogram-III was characterized by ‘cold’ and ‘recognizable’ features and upregulated expression of MHC I molecules. Immunogram-IV was characterized by ‘cold’ and ‘inert’ features, which represented overall immunosuppression, lower levels of immunoediting and positive selection, and accumulation of more tumor neoantigens. In particular, favorable overall survival was observed in metastatic urothelial cancer patients with immunogram-I and immunogram-IV after immune checkpoint inhibitor (ICI) therapy. Meanwhile, a higher response rate to ICI therapy was observed in metastatic gastric cancer patients with immunogram-I phenotype. Conclusions Our findings provide new insight into the interaction between immunity and cancer evolution, which may contribute to optimizing immunotherapy strategies. |
| abstractGer |
Abstract Background The cancer-immunity cycle (CI cycle) provides a theoretical framework to illustrate the process of the anticancer immune response. Recently, the update of the CI cycle theory emphasizes the importance of tumor’s immunological phenotype. However, there is lack of immunological phenotype of pan-cancer based on CI cycle theory. Methods Here, we applied a visualizing method termed ‘cancer immunogram’ to visualize the state of CI cycle of 8460 solid tumors from TCGA cohort. Unsupervised clustering of the cancer immunogram was performed using the nonnegative matrix factorization (NMF) analysis. We applied an evolutionary genomics approach (dN/dS ratio) to evaluate the clonal selection patterns of tumors with distinct immunogram subtypes. Results We defined four major CI cycle patterns across 32 cancer types using a cancer immunogram approach. Immunogram-I was characterized by ‘hot’ and ‘exhausted’ features, indicating a favorable prognosis. Strikingly, immunogram-II, immunogram-III, and immunogram-IV represented distinct immunosuppressive patterns of ‘cold’ tumor. Immunogram-II was characterized by ‘cold’ and ‘radical’ features, which represented increased expression of immune inhibitor molecules and high levels of positive selection, indicating the worst prognosis. Immunogram-III was characterized by ‘cold’ and ‘recognizable’ features and upregulated expression of MHC I molecules. Immunogram-IV was characterized by ‘cold’ and ‘inert’ features, which represented overall immunosuppression, lower levels of immunoediting and positive selection, and accumulation of more tumor neoantigens. In particular, favorable overall survival was observed in metastatic urothelial cancer patients with immunogram-I and immunogram-IV after immune checkpoint inhibitor (ICI) therapy. Meanwhile, a higher response rate to ICI therapy was observed in metastatic gastric cancer patients with immunogram-I phenotype. Conclusions Our findings provide new insight into the interaction between immunity and cancer evolution, which may contribute to optimizing immunotherapy strategies. |
| abstract_unstemmed |
Abstract Background The cancer-immunity cycle (CI cycle) provides a theoretical framework to illustrate the process of the anticancer immune response. Recently, the update of the CI cycle theory emphasizes the importance of tumor’s immunological phenotype. However, there is lack of immunological phenotype of pan-cancer based on CI cycle theory. Methods Here, we applied a visualizing method termed ‘cancer immunogram’ to visualize the state of CI cycle of 8460 solid tumors from TCGA cohort. Unsupervised clustering of the cancer immunogram was performed using the nonnegative matrix factorization (NMF) analysis. We applied an evolutionary genomics approach (dN/dS ratio) to evaluate the clonal selection patterns of tumors with distinct immunogram subtypes. Results We defined four major CI cycle patterns across 32 cancer types using a cancer immunogram approach. Immunogram-I was characterized by ‘hot’ and ‘exhausted’ features, indicating a favorable prognosis. Strikingly, immunogram-II, immunogram-III, and immunogram-IV represented distinct immunosuppressive patterns of ‘cold’ tumor. Immunogram-II was characterized by ‘cold’ and ‘radical’ features, which represented increased expression of immune inhibitor molecules and high levels of positive selection, indicating the worst prognosis. Immunogram-III was characterized by ‘cold’ and ‘recognizable’ features and upregulated expression of MHC I molecules. Immunogram-IV was characterized by ‘cold’ and ‘inert’ features, which represented overall immunosuppression, lower levels of immunoediting and positive selection, and accumulation of more tumor neoantigens. In particular, favorable overall survival was observed in metastatic urothelial cancer patients with immunogram-I and immunogram-IV after immune checkpoint inhibitor (ICI) therapy. Meanwhile, a higher response rate to ICI therapy was observed in metastatic gastric cancer patients with immunogram-I phenotype. Conclusions Our findings provide new insight into the interaction between immunity and cancer evolution, which may contribute to optimizing immunotherapy strategies. |
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Immunogram defines four cancer-immunity cycle phenotypes with distinct clonal selection patterns across solid tumors |
| url |
https://doi.org/10.1186/s12967-023-04765-5 https://doaj.org/article/f03396aa98b249cab9801dcaa45b6298 https://doaj.org/toc/1479-5876 |
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Huaibo Sun Wei Shi Chen Chen Xueying Wu Yu Jiang Guoying Zhang Na Li Jin Song Hao Zhang Baiyong Shen Hui Zeng Henghui Zhang |
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Huaibo Sun Wei Shi Chen Chen Xueying Wu Yu Jiang Guoying Zhang Na Li Jin Song Hao Zhang Baiyong Shen Hui Zeng Henghui Zhang |
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10.1186/s12967-023-04765-5 |
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2024-07-04T01:08:53.422Z |
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Recently, the update of the CI cycle theory emphasizes the importance of tumor’s immunological phenotype. However, there is lack of immunological phenotype of pan-cancer based on CI cycle theory. Methods Here, we applied a visualizing method termed ‘cancer immunogram’ to visualize the state of CI cycle of 8460 solid tumors from TCGA cohort. Unsupervised clustering of the cancer immunogram was performed using the nonnegative matrix factorization (NMF) analysis. We applied an evolutionary genomics approach (dN/dS ratio) to evaluate the clonal selection patterns of tumors with distinct immunogram subtypes. Results We defined four major CI cycle patterns across 32 cancer types using a cancer immunogram approach. Immunogram-I was characterized by ‘hot’ and ‘exhausted’ features, indicating a favorable prognosis. Strikingly, immunogram-II, immunogram-III, and immunogram-IV represented distinct immunosuppressive patterns of ‘cold’ tumor. Immunogram-II was characterized by ‘cold’ and ‘radical’ features, which represented increased expression of immune inhibitor molecules and high levels of positive selection, indicating the worst prognosis. Immunogram-III was characterized by ‘cold’ and ‘recognizable’ features and upregulated expression of MHC I molecules. Immunogram-IV was characterized by ‘cold’ and ‘inert’ features, which represented overall immunosuppression, lower levels of immunoediting and positive selection, and accumulation of more tumor neoantigens. In particular, favorable overall survival was observed in metastatic urothelial cancer patients with immunogram-I and immunogram-IV after immune checkpoint inhibitor (ICI) therapy. Meanwhile, a higher response rate to ICI therapy was observed in metastatic gastric cancer patients with immunogram-I phenotype. 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