Immunogenomic correlates of immune-related adverse events for anti–programmed cell death 1 therapy
Despite impressive antitumor efficacy of programmed cell death 1 (PD-1) inhibitors, this inhibition can induce mild to severe autoimmune toxicities, termed immune-related adverse events (irAEs). Yet, predictive pretreatment biomarkers for irAEs development across cancer types remain elusive. We firs...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-11-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2022.1032221/full |
| _version_ | 1811186695101480960 |
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| author | Lei Zhang Lei Zhang Yuankai Shi Xiaohong Han |
| author_facet | Lei Zhang Lei Zhang Yuankai Shi Xiaohong Han |
| author_sort | Lei Zhang |
| collection | DOAJ |
| description | Despite impressive antitumor efficacy of programmed cell death 1 (PD-1) inhibitors, this inhibition can induce mild to severe autoimmune toxicities, termed immune-related adverse events (irAEs). Yet, predictive pretreatment biomarkers for irAEs development across cancer types remain elusive. We first assessed cellular and molecular factors. To determine factors predicting the risk of irAEs for anti–PD-1 immunotherapy across multiple cancer types, an integrative analysis of cellular and molecular factors from 9104 patients across 21 cancer types and 4865522 postmarketing adverse event reports retrieved from adverse event reporting system was then performed. Accuracy of predictions was quantified as Pearson correlation coefficient determined using leave-one-out cross-validation. Independent validation sets included small cell lung cancer and melanoma cohorts. Out of 4865522 eligible adverse events reports, 10412 cases received anti–PD-1 monotherapy, of which, 2997 (28.78%) exhibited at least one irAE. Among established immunogenomic factors, dendritic cells (DC) abundance showed the strongest correlation with irAEs risk, followed by tumor mutational burden (TMB). Further predictive accuracy was achieved by DC and TMB in combination with CD4+ naive T-cells abundance, and then validated in the small cell lung cancer cohort. Additionally, global screening of multiomics data identified 11 novel predictors of irAEs. Of these, IRF4 showed the highest correlation. Best predictive performance was observed in the IRF4 – TCL1A – SHC-pY317 trivariate model. Associations of IRF4 and TCL1A expression with irAEs development were verified in the melanoma cohort receiving immune checkpoint inhibitors. Collectively, pretreatment cellular and molecular irAEs-associated features as well as their combinations are identified regardless of cancer types. These findings may deepen our knowledge of irAEs pathogenesis and, ultimately, aid in early detection of high-risk patients and management of irAEs. |
| first_indexed | 2024-04-11T13:49:26Z |
| format | Article |
| id | doaj.art-a64e87c142b24409b9dbbaf5770f35eb |
| institution | Directory Open Access Journal |
| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-04-11T13:49:26Z |
| publishDate | 2022-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj.art-a64e87c142b24409b9dbbaf5770f35eb2022-12-22T04:20:43ZengFrontiers Media S.A.Frontiers in Immunology1664-32242022-11-011310.3389/fimmu.2022.10322211032221Immunogenomic correlates of immune-related adverse events for anti–programmed cell death 1 therapyLei Zhang0Lei Zhang1Yuankai Shi2Xiaohong Han3Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, Beijing, ChinaMedical Research Center, Key Laboratory of Digital Technology in Medical Diagnostics of Zhejiang Province, Hangzhou, ChinaDepartment of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, Beijing, ChinaClinical Pharmacology Research Center, Peking Union Medical College Hospital, State Key Laboratory of Complex Severe and Rare Diseases, NMPA Key Laboratory for Clinical Research and Evaluation of Drug, Beijing Key Laboratory of Clinical PK & PD Investigation for Innovative Drugs, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, ChinaDespite impressive antitumor efficacy of programmed cell death 1 (PD-1) inhibitors, this inhibition can induce mild to severe autoimmune toxicities, termed immune-related adverse events (irAEs). Yet, predictive pretreatment biomarkers for irAEs development across cancer types remain elusive. We first assessed cellular and molecular factors. To determine factors predicting the risk of irAEs for anti–PD-1 immunotherapy across multiple cancer types, an integrative analysis of cellular and molecular factors from 9104 patients across 21 cancer types and 4865522 postmarketing adverse event reports retrieved from adverse event reporting system was then performed. Accuracy of predictions was quantified as Pearson correlation coefficient determined using leave-one-out cross-validation. Independent validation sets included small cell lung cancer and melanoma cohorts. Out of 4865522 eligible adverse events reports, 10412 cases received anti–PD-1 monotherapy, of which, 2997 (28.78%) exhibited at least one irAE. Among established immunogenomic factors, dendritic cells (DC) abundance showed the strongest correlation with irAEs risk, followed by tumor mutational burden (TMB). Further predictive accuracy was achieved by DC and TMB in combination with CD4+ naive T-cells abundance, and then validated in the small cell lung cancer cohort. Additionally, global screening of multiomics data identified 11 novel predictors of irAEs. Of these, IRF4 showed the highest correlation. Best predictive performance was observed in the IRF4 – TCL1A – SHC-pY317 trivariate model. Associations of IRF4 and TCL1A expression with irAEs development were verified in the melanoma cohort receiving immune checkpoint inhibitors. Collectively, pretreatment cellular and molecular irAEs-associated features as well as their combinations are identified regardless of cancer types. These findings may deepen our knowledge of irAEs pathogenesis and, ultimately, aid in early detection of high-risk patients and management of irAEs.https://www.frontiersin.org/articles/10.3389/fimmu.2022.1032221/fullimmune-related adverse eventcellular biomarkermolecular biomarkerimmune cellimmunotherapy |
| spellingShingle | Lei Zhang Lei Zhang Yuankai Shi Xiaohong Han Immunogenomic correlates of immune-related adverse events for anti–programmed cell death 1 therapy Frontiers in Immunology immune-related adverse event cellular biomarker molecular biomarker immune cell immunotherapy |
| title | Immunogenomic correlates of immune-related adverse events for anti–programmed cell death 1 therapy |
| title_full | Immunogenomic correlates of immune-related adverse events for anti–programmed cell death 1 therapy |
| title_fullStr | Immunogenomic correlates of immune-related adverse events for anti–programmed cell death 1 therapy |
| title_full_unstemmed | Immunogenomic correlates of immune-related adverse events for anti–programmed cell death 1 therapy |
| title_short | Immunogenomic correlates of immune-related adverse events for anti–programmed cell death 1 therapy |
| title_sort | immunogenomic correlates of immune related adverse events for anti programmed cell death 1 therapy |
| topic | immune-related adverse event cellular biomarker molecular biomarker immune cell immunotherapy |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2022.1032221/full |
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