The development of a tumor‐associated autoantibodies panel to predict clinical outcomes for immune checkpoint inhibitor‐based treatment in patients with advanced non‐small‐cell lung cancer
Abstract Background Immune checkpoint inhibitors (ICIs) have become one important therapeutic strategy for advanced non‐small‐cell lung cancer (NSCLC). It remains imperative to identify reliable and convenient biomarkers to predict both the efficacy and toxicity of immunotherapy, and tumor‐associate...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023-02-01
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| Series: | Thoracic Cancer |
| Subjects: | |
| Online Access: | https://doi.org/10.1111/1759-7714.14772 |
| _version_ | 1828034267620311040 |
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| author | Jing Zhao Yang Wu Yuan Yue Minjiang Chen Yan Xu Xiangning Liu Xiaoyan Liu Xiaoxing Gao Hanping Wang Xiaoyan Si Wei Zhong Xiaotong Zhang Li Zhang Mengzhao Wang |
| author_facet | Jing Zhao Yang Wu Yuan Yue Minjiang Chen Yan Xu Xiangning Liu Xiaoyan Liu Xiaoxing Gao Hanping Wang Xiaoyan Si Wei Zhong Xiaotong Zhang Li Zhang Mengzhao Wang |
| author_sort | Jing Zhao |
| collection | DOAJ |
| description | Abstract Background Immune checkpoint inhibitors (ICIs) have become one important therapeutic strategy for advanced non‐small‐cell lung cancer (NSCLC). It remains imperative to identify reliable and convenient biomarkers to predict both the efficacy and toxicity of immunotherapy, and tumor‐associated autoantibodies (TAAbs) are recognized as one of the promising candidates for this. Patients and Methods This study enrolled 97 advanced NSCLC patients with ICI‐based immunotherapy treatment, who were divided into a training cohort (n = 48) and a validation cohort (n = 49), and measured for the serum level of 35 TAAbs. According to the statistical association between the serum positivity and clinical outcome of each TAAb in the training cohort, a TAAb panel was developed to predict the progression‐free survival (PFS), and further examined in the validation cohort and in different subgroups. Similarly, another TAAb panel was derived to predict the occurrence of immune‐related adverse events (irAEs). Results In the training cohort, a 7‐TAAb panel composed of p53, CAGE, MAGEA4, GAGE7, UTP14A, IMP2, and PSMC1 TAAbs was derived to predict PFS (median PFS [mPFS] 9.9 vs. 4.3 months, p = 0.043). The statistical association between the panel positivity and longer PFS was confirmed in the validation cohort (mPFS 11.1 vs. 4.8 months, p = 0.015) and in different subgroups of patients. Moreover, another 4‐TAAb panel of BRCA2, MAGEA4, ZNF768, and PARP TAAbs was developed to predict the occurrence of irAEs, showing higher risk in panel‐positive patients (71.43% vs. 28.91%, p = 0.0046). Conclusions Collectively, our study developed and validated two TAAb panels as valuable prognostic biomarkers for immunotherapy. |
| first_indexed | 2024-04-10T15:30:07Z |
| format | Article |
| id | doaj.art-56b3c9c16b634f28bb0a279bd5b01767 |
| institution | Directory Open Access Journal |
| issn | 1759-7706 1759-7714 |
| language | English |
| last_indexed | 2024-04-10T15:30:07Z |
| publishDate | 2023-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | Thoracic Cancer |
| spelling | doaj.art-56b3c9c16b634f28bb0a279bd5b017672023-02-14T02:01:34ZengWileyThoracic Cancer1759-77061759-77142023-02-0114549750510.1111/1759-7714.14772The development of a tumor‐associated autoantibodies panel to predict clinical outcomes for immune checkpoint inhibitor‐based treatment in patients with advanced non‐small‐cell lung cancerJing Zhao0Yang Wu1Yuan Yue2Minjiang Chen3Yan Xu4Xiangning Liu5Xiaoyan Liu6Xiaoxing Gao7Hanping Wang8Xiaoyan Si9Wei Zhong10Xiaotong Zhang11Li Zhang12Mengzhao Wang13Department of Respiratory and Critical Care Medicine Peking Union Medical College Hospital Beijing ChinaSchool of Medicine Tsinghua University Beijing ChinaDepartment of Respiratory and Critical Care Medicine Peking Union Medical College Hospital Beijing ChinaDepartment of Respiratory and Critical Care Medicine Peking Union Medical College Hospital Beijing ChinaDepartment of Respiratory and Critical Care Medicine Peking Union Medical College Hospital Beijing ChinaDepartment of Respiratory and Critical Care Medicine Peking Union Medical College Hospital Beijing ChinaDepartment of Respiratory and Critical Care Medicine Peking Union Medical College Hospital Beijing ChinaDepartment of Respiratory and Critical Care Medicine Peking Union Medical College Hospital Beijing ChinaDepartment of Respiratory and Critical Care Medicine Peking Union Medical College Hospital Beijing ChinaDepartment of Respiratory and Critical Care Medicine Peking Union Medical College Hospital Beijing ChinaDepartment of Respiratory and Critical Care Medicine Peking Union Medical College Hospital Beijing ChinaDepartment of Respiratory and Critical Care Medicine Peking Union Medical College Hospital Beijing ChinaDepartment of Respiratory and Critical Care Medicine Peking Union Medical College Hospital Beijing ChinaDepartment of Respiratory and Critical Care Medicine Peking Union Medical College Hospital Beijing ChinaAbstract Background Immune checkpoint inhibitors (ICIs) have become one important therapeutic strategy for advanced non‐small‐cell lung cancer (NSCLC). It remains imperative to identify reliable and convenient biomarkers to predict both the efficacy and toxicity of immunotherapy, and tumor‐associated autoantibodies (TAAbs) are recognized as one of the promising candidates for this. Patients and Methods This study enrolled 97 advanced NSCLC patients with ICI‐based immunotherapy treatment, who were divided into a training cohort (n = 48) and a validation cohort (n = 49), and measured for the serum level of 35 TAAbs. According to the statistical association between the serum positivity and clinical outcome of each TAAb in the training cohort, a TAAb panel was developed to predict the progression‐free survival (PFS), and further examined in the validation cohort and in different subgroups. Similarly, another TAAb panel was derived to predict the occurrence of immune‐related adverse events (irAEs). Results In the training cohort, a 7‐TAAb panel composed of p53, CAGE, MAGEA4, GAGE7, UTP14A, IMP2, and PSMC1 TAAbs was derived to predict PFS (median PFS [mPFS] 9.9 vs. 4.3 months, p = 0.043). The statistical association between the panel positivity and longer PFS was confirmed in the validation cohort (mPFS 11.1 vs. 4.8 months, p = 0.015) and in different subgroups of patients. Moreover, another 4‐TAAb panel of BRCA2, MAGEA4, ZNF768, and PARP TAAbs was developed to predict the occurrence of irAEs, showing higher risk in panel‐positive patients (71.43% vs. 28.91%, p = 0.0046). Conclusions Collectively, our study developed and validated two TAAb panels as valuable prognostic biomarkers for immunotherapy.https://doi.org/10.1111/1759-7714.14772immune checkpoint inhibitorsnon‐small‐cell lung cancerprognostic biomarkertumor‐associated autoantibody |
| spellingShingle | Jing Zhao Yang Wu Yuan Yue Minjiang Chen Yan Xu Xiangning Liu Xiaoyan Liu Xiaoxing Gao Hanping Wang Xiaoyan Si Wei Zhong Xiaotong Zhang Li Zhang Mengzhao Wang The development of a tumor‐associated autoantibodies panel to predict clinical outcomes for immune checkpoint inhibitor‐based treatment in patients with advanced non‐small‐cell lung cancer Thoracic Cancer immune checkpoint inhibitors non‐small‐cell lung cancer prognostic biomarker tumor‐associated autoantibody |
| title | The development of a tumor‐associated autoantibodies panel to predict clinical outcomes for immune checkpoint inhibitor‐based treatment in patients with advanced non‐small‐cell lung cancer |
| title_full | The development of a tumor‐associated autoantibodies panel to predict clinical outcomes for immune checkpoint inhibitor‐based treatment in patients with advanced non‐small‐cell lung cancer |
| title_fullStr | The development of a tumor‐associated autoantibodies panel to predict clinical outcomes for immune checkpoint inhibitor‐based treatment in patients with advanced non‐small‐cell lung cancer |
| title_full_unstemmed | The development of a tumor‐associated autoantibodies panel to predict clinical outcomes for immune checkpoint inhibitor‐based treatment in patients with advanced non‐small‐cell lung cancer |
| title_short | The development of a tumor‐associated autoantibodies panel to predict clinical outcomes for immune checkpoint inhibitor‐based treatment in patients with advanced non‐small‐cell lung cancer |
| title_sort | development of a tumor associated autoantibodies panel to predict clinical outcomes for immune checkpoint inhibitor based treatment in patients with advanced non small cell lung cancer |
| topic | immune checkpoint inhibitors non‐small‐cell lung cancer prognostic biomarker tumor‐associated autoantibody |
| url | https://doi.org/10.1111/1759-7714.14772 |
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