Stratification system with dual human endogenous retroviruses for predicting immunotherapy efficacy in metastatic clear-cell renal cell carcinoma
Background Endogenous retrovirus (ERV) elements are genomic footprints of ancestral retroviral infections within the human genome. While the dysregulation of ERV transcription has been linked to immune cell infiltration in various cancers, its relationship with immune checkpoint inhibitor (ICI) resp...
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BMJ Publishing Group
2025-01-01
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| Series: | Journal for ImmunoTherapy of Cancer |
| Online Access: | https://jitc.bmj.com/content/13/1/e010386.full |
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| author | Li Xu Stephane Oudard Catherine Sautes-Fridman Xiaoping Su Gabriel G. Malouf Virginie Verkarre Salma Kotti Fangrong Yan Yann-Alexandre Vano Wolf Herve Fridman Cheng-Ming Sun Xiaofan Lu Wenxuan Cheng |
| author_facet | Li Xu Stephane Oudard Catherine Sautes-Fridman Xiaoping Su Gabriel G. Malouf Virginie Verkarre Salma Kotti Fangrong Yan Yann-Alexandre Vano Wolf Herve Fridman Cheng-Ming Sun Xiaofan Lu Wenxuan Cheng |
| author_sort | Li Xu |
| collection | DOAJ |
| description | Background Endogenous retrovirus (ERV) elements are genomic footprints of ancestral retroviral infections within the human genome. While the dysregulation of ERV transcription has been linked to immune cell infiltration in various cancers, its relationship with immune checkpoint inhibitor (ICI) response in solid tumors, particularly metastatic clear-cell renal cell carcinoma (ccRCC), remains inadequately explored.Methods This study analyzed patients with metastatic ccRCC from two prospective clinical trials, encompassing 181 patients receiving nivolumab in the CheckMate trials (−009 to –010 and −025) and 48 patients treated with the ipilimumab-nivolumab combination in the BIONIKK trial. ERV expression was quantified using the ERVmap algorithm from RNA sequencing data. Our primary objective was to correlate ERV expression with progression-free survival, with overall survival and time-to-second-treatment survival as secondary endpoints. We used bootstrap methods with univariate Cox regression on 666 substantially expressed ERVs to evaluate their prognostic significance and stability.Results Our analysis centered on two ERVs, E4421_chr17 and E1659_chr4, which consistently exhibited opposing prognostic impacts across both cohorts. We developed a stratification system based on their median expression levels, categorizing patients into four ERV subgroups. These subgroups were further consolidated into a three-tier risk model that significantly correlated with ICI treatment outcomes. The most responsive ERV risk category showed enhanced endothelial cell infiltration, whereas the resistant category was characterized by higher levels of myeloid dendritic cells, regulatory T cells, myeloid-derived suppressor cells, and markers of T-cell exhaustion. Notably, this ERV-based classification outperformed traditional transcriptomic signatures in predicting ICI efficacy and showed further improvement when combined with epigenetic DNA methylation markers.Conclusions Our findings introduce a dual ERV-based stratification system that effectively categorizes patient risk and predicts clinical outcomes for ccRCC patients undergoing ICI therapy. Beyond enhancing the predictive precision of existing transcriptomic models, this system paves the way for more targeted and individualized approaches in the realm of precision oncology. |
| format | Article |
| id | doaj-art-7fb67b5707894527a97cbcf52c52300b |
| institution | Kabale University |
| issn | 2051-1426 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMJ Publishing Group |
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| series | Journal for ImmunoTherapy of Cancer |
| spelling | doaj-art-7fb67b5707894527a97cbcf52c52300b2025-02-03T05:10:13ZengBMJ Publishing GroupJournal for ImmunoTherapy of Cancer2051-14262025-01-0113110.1136/jitc-2024-010386Stratification system with dual human endogenous retroviruses for predicting immunotherapy efficacy in metastatic clear-cell renal cell carcinomaLi Xu0Stephane Oudard1Catherine Sautes-Fridman2Xiaoping Su3Gabriel G. Malouf4Virginie Verkarre5Salma Kotti6Fangrong Yan7Yann-Alexandre Vano8Wolf Herve Fridman9Cheng-Ming Sun10Xiaofan Lu11Wenxuan Cheng12Department of Cancer and Functional Genomics, Institute of Genetics and Molecular and Cellular Biology (IGBMC), CNRS/INSERM/UNISTRA, Illkirch-Graffenstaden, France5Georges Pompidou European Hospital, Paris, France6Universite Paris-Cite, Paris, FranceDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USADepartment of Cancer and Functional Genomics, Institute of Genetics and Molecular and Cellular Biology (IGBMC), CNRS/INSERM/UNISTRA, Illkirch-Graffenstaden, FranceDepartment of Pathology, Hôpital Européen Georges Pompidou, Institut du Cancer Paris CARPEM, APHP, Université Paris Cité, Paris, FranceDepartment of Medical Oncology, Hôpital Européen Georges Pompidou, Institut du Cancer Paris CARPEM, APHP, Université Paris Cité, Paris, FranceResearch Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu, ChinaDepartment of Medical Oncology, Hôpital Européen Georges Pompidou, Institut du Cancer Paris CARPEM, APHP, Université Paris Cité, Paris, FranceCentre de Recherche Cordeliers, Université de Paris Cité, Sorbonne Université, Equipe labellisée Ligue contre le Cancer, Paris, France2Centre de Recherche des Cordeliers, INSERM, Université Paris Cité, Sorbonne Université, Paris, FranceDepartment of Cancer and Functional Genomics, Institute of Genetics and Molecular and Cellular Biology (IGBMC), CNRS/INSERM/UNISTRA, Illkirch-Graffenstaden, FranceDepartment of Cancer and Functional Genomics, Institute of Genetics and Molecular and Cellular Biology (IGBMC), CNRS/INSERM/UNISTRA, Illkirch-Graffenstaden, FranceBackground Endogenous retrovirus (ERV) elements are genomic footprints of ancestral retroviral infections within the human genome. While the dysregulation of ERV transcription has been linked to immune cell infiltration in various cancers, its relationship with immune checkpoint inhibitor (ICI) response in solid tumors, particularly metastatic clear-cell renal cell carcinoma (ccRCC), remains inadequately explored.Methods This study analyzed patients with metastatic ccRCC from two prospective clinical trials, encompassing 181 patients receiving nivolumab in the CheckMate trials (−009 to –010 and −025) and 48 patients treated with the ipilimumab-nivolumab combination in the BIONIKK trial. ERV expression was quantified using the ERVmap algorithm from RNA sequencing data. Our primary objective was to correlate ERV expression with progression-free survival, with overall survival and time-to-second-treatment survival as secondary endpoints. We used bootstrap methods with univariate Cox regression on 666 substantially expressed ERVs to evaluate their prognostic significance and stability.Results Our analysis centered on two ERVs, E4421_chr17 and E1659_chr4, which consistently exhibited opposing prognostic impacts across both cohorts. We developed a stratification system based on their median expression levels, categorizing patients into four ERV subgroups. These subgroups were further consolidated into a three-tier risk model that significantly correlated with ICI treatment outcomes. The most responsive ERV risk category showed enhanced endothelial cell infiltration, whereas the resistant category was characterized by higher levels of myeloid dendritic cells, regulatory T cells, myeloid-derived suppressor cells, and markers of T-cell exhaustion. Notably, this ERV-based classification outperformed traditional transcriptomic signatures in predicting ICI efficacy and showed further improvement when combined with epigenetic DNA methylation markers.Conclusions Our findings introduce a dual ERV-based stratification system that effectively categorizes patient risk and predicts clinical outcomes for ccRCC patients undergoing ICI therapy. Beyond enhancing the predictive precision of existing transcriptomic models, this system paves the way for more targeted and individualized approaches in the realm of precision oncology.https://jitc.bmj.com/content/13/1/e010386.full |
| spellingShingle | Li Xu Stephane Oudard Catherine Sautes-Fridman Xiaoping Su Gabriel G. Malouf Virginie Verkarre Salma Kotti Fangrong Yan Yann-Alexandre Vano Wolf Herve Fridman Cheng-Ming Sun Xiaofan Lu Wenxuan Cheng Stratification system with dual human endogenous retroviruses for predicting immunotherapy efficacy in metastatic clear-cell renal cell carcinoma Journal for ImmunoTherapy of Cancer |
| title | Stratification system with dual human endogenous retroviruses for predicting immunotherapy efficacy in metastatic clear-cell renal cell carcinoma |
| title_full | Stratification system with dual human endogenous retroviruses for predicting immunotherapy efficacy in metastatic clear-cell renal cell carcinoma |
| title_fullStr | Stratification system with dual human endogenous retroviruses for predicting immunotherapy efficacy in metastatic clear-cell renal cell carcinoma |
| title_full_unstemmed | Stratification system with dual human endogenous retroviruses for predicting immunotherapy efficacy in metastatic clear-cell renal cell carcinoma |
| title_short | Stratification system with dual human endogenous retroviruses for predicting immunotherapy efficacy in metastatic clear-cell renal cell carcinoma |
| title_sort | stratification system with dual human endogenous retroviruses for predicting immunotherapy efficacy in metastatic clear cell renal cell carcinoma |
| url | https://jitc.bmj.com/content/13/1/e010386.full |
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