Network-based transfer of pan-cancer immunotherapy responses to guide breast cancer prognosis
Abstract Breast cancer prognosis is complicated by tumor heterogeneity. Traditional methods focus on cancer-specific gene signatures, but cross-cancer strategies that provide deeper insights into tumor homogeneity are rarely used. Immunotherapy, particularly immune checkpoint inhibitors, results fro...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | npj Systems Biology and Applications |
| Online Access: | https://doi.org/10.1038/s41540-024-00486-7 |
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| _version_ | 1841544521179987968 |
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| author | Xiaobao Ding Lin Zhang Ming Fan Lihua Li |
| author_facet | Xiaobao Ding Lin Zhang Ming Fan Lihua Li |
| author_sort | Xiaobao Ding |
| collection | DOAJ |
| description | Abstract Breast cancer prognosis is complicated by tumor heterogeneity. Traditional methods focus on cancer-specific gene signatures, but cross-cancer strategies that provide deeper insights into tumor homogeneity are rarely used. Immunotherapy, particularly immune checkpoint inhibitors, results from variable responses across cancers, offering valuable prognostic insights. We introduced a network-based transfer (NBT) of pan-cancer immunotherapy responses to enhance breast cancer prognosis using node embedding and heat diffusion algorithms, identifying gene signatures netNE and netHD. Our results showed that netHD and netNE outperformed seven established breast cancer signatures in prognostic metrics, with netHD excelling. All nine gene signatures were grouped into three clusters, with netHD and netNE enriching the immune-related interferon-gamma pathway. Stratifying TCGA patients into two groups based on netHD revealed significant immunological differences and variations in 20 of 50 cancer hallmarks, emphasizing immune-related markers. This approach leverages pan-cancer insights to enhance breast cancer prognosis, facilitating insight transfer and improving tumor homogeneity understanding. Abstract graph of network-based insights translating pan-cancer immunotherapy responses to breast cancer prognosis. This abstract graph illustrates the conceptual framework for transferring immunotherapy response insights from pan-cancer studies to breast cancer prognosis. It highlights the integration of PPI networks to bridge genetic data and clinical phenotypes. The network-based method facilitates the identification of prognostic gene signatures in breast cancer by leveraging immunotherapy response information, providing a novel perspective on tumor homogeneity and its implications for clinical outcomes. |
| format | Article |
| id | doaj-art-7c9a2e82f300452aa3a2e58feba096c2 |
| institution | Kabale University |
| issn | 2056-7189 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Systems Biology and Applications |
| spelling | doaj-art-7c9a2e82f300452aa3a2e58feba096c22025-01-12T12:28:51ZengNature Portfolionpj Systems Biology and Applications2056-71892025-01-0111111210.1038/s41540-024-00486-7Network-based transfer of pan-cancer immunotherapy responses to guide breast cancer prognosisXiaobao Ding0Lin Zhang1Ming Fan2Lihua Li3Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi UniversityInstitute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi UniversityInstitute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi UniversityInstitute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi UniversityAbstract Breast cancer prognosis is complicated by tumor heterogeneity. Traditional methods focus on cancer-specific gene signatures, but cross-cancer strategies that provide deeper insights into tumor homogeneity are rarely used. Immunotherapy, particularly immune checkpoint inhibitors, results from variable responses across cancers, offering valuable prognostic insights. We introduced a network-based transfer (NBT) of pan-cancer immunotherapy responses to enhance breast cancer prognosis using node embedding and heat diffusion algorithms, identifying gene signatures netNE and netHD. Our results showed that netHD and netNE outperformed seven established breast cancer signatures in prognostic metrics, with netHD excelling. All nine gene signatures were grouped into three clusters, with netHD and netNE enriching the immune-related interferon-gamma pathway. Stratifying TCGA patients into two groups based on netHD revealed significant immunological differences and variations in 20 of 50 cancer hallmarks, emphasizing immune-related markers. This approach leverages pan-cancer insights to enhance breast cancer prognosis, facilitating insight transfer and improving tumor homogeneity understanding. Abstract graph of network-based insights translating pan-cancer immunotherapy responses to breast cancer prognosis. This abstract graph illustrates the conceptual framework for transferring immunotherapy response insights from pan-cancer studies to breast cancer prognosis. It highlights the integration of PPI networks to bridge genetic data and clinical phenotypes. The network-based method facilitates the identification of prognostic gene signatures in breast cancer by leveraging immunotherapy response information, providing a novel perspective on tumor homogeneity and its implications for clinical outcomes.https://doi.org/10.1038/s41540-024-00486-7 |
| spellingShingle | Xiaobao Ding Lin Zhang Ming Fan Lihua Li Network-based transfer of pan-cancer immunotherapy responses to guide breast cancer prognosis npj Systems Biology and Applications |
| title | Network-based transfer of pan-cancer immunotherapy responses to guide breast cancer prognosis |
| title_full | Network-based transfer of pan-cancer immunotherapy responses to guide breast cancer prognosis |
| title_fullStr | Network-based transfer of pan-cancer immunotherapy responses to guide breast cancer prognosis |
| title_full_unstemmed | Network-based transfer of pan-cancer immunotherapy responses to guide breast cancer prognosis |
| title_short | Network-based transfer of pan-cancer immunotherapy responses to guide breast cancer prognosis |
| title_sort | network based transfer of pan cancer immunotherapy responses to guide breast cancer prognosis |
| url | https://doi.org/10.1038/s41540-024-00486-7 |
| work_keys_str_mv | AT xiaobaoding networkbasedtransferofpancancerimmunotherapyresponsestoguidebreastcancerprognosis AT linzhang networkbasedtransferofpancancerimmunotherapyresponsestoguidebreastcancerprognosis AT mingfan networkbasedtransferofpancancerimmunotherapyresponsestoguidebreastcancerprognosis AT lihuali networkbasedtransferofpancancerimmunotherapyresponsestoguidebreastcancerprognosis |