Anti-TROVE2 Antibody Determined by Immune-Related Array May Serve as a Predictive Marker for Adalimumab Immunogenicity and Effectiveness in RA
Anti-drug antibody (ADAb) development is associated with secondary therapeutic failure in biologic-treated rheumatoid arthritis (RA) patients. With a treat-to-target goal, we aimed to identify biomarkers for predicting ADAb development and therapeutic response in adalimumab-treated patients. Three i...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Journal of Immunology Research |
| Online Access: | http://dx.doi.org/10.1155/2021/6656121 |
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| author | Po-Ku Chen Joung-Liang Lan Yi-Ming Chen Hsin-Hua Chen Shih-Hsin Chang Chia-Min Chung Nurul H. Rutt Ti-Myen Tan Raja Nurashirin Raja Mamat Nur Diana Anuar Jonathan M. Blackburn Der-Yuan Chen |
| author_facet | Po-Ku Chen Joung-Liang Lan Yi-Ming Chen Hsin-Hua Chen Shih-Hsin Chang Chia-Min Chung Nurul H. Rutt Ti-Myen Tan Raja Nurashirin Raja Mamat Nur Diana Anuar Jonathan M. Blackburn Der-Yuan Chen |
| author_sort | Po-Ku Chen |
| collection | DOAJ |
| description | Anti-drug antibody (ADAb) development is associated with secondary therapeutic failure in biologic-treated rheumatoid arthritis (RA) patients. With a treat-to-target goal, we aimed to identify biomarkers for predicting ADAb development and therapeutic response in adalimumab-treated patients. Three independent cohorts were enrolled. In Cohort-1, 24 plasma samples (6 ADAb-positive and 6 ADAb-negative patients at baseline and week 24 of adalimumab therapy, respectively) were assayed with immune-related microarray containing 1,636 correctly folded functional proteins. Next, we executed statistically powered autoantibody profiling analysis of 50 samples in Cohort-2 (24 ADAb-positive and 26 ADAb-negative patients). Subsequently, immunofluorescence assay was performed on 48 samples in Cohort-3 to correlate with ADAb titers and drug levels. The biomarkers were identified for predicting ADAb development and therapeutic response using the immune-related microarray and machine learning approach. ADAb-positive patients had lower drug levels at week 24 (median=0.024 μg/ml) compared with ADAb-negative patients (median=6.38 μg/ml, p<0.001). ROC analysis based on the ADAb status revealed the top 20 autoantibodies with AUC≥0.7 in differentiating both groups in Cohort-1. Analysis of Cohort-2 dataset identified a panel of 8 biomarkers (TROVE2, SSB, NDE1, ZHX2, SH3GL1, CARD9, PTPN20, and KLHL12) with 80.6% specificity, 77.4% sensitivity, and 79.0% accuracy in discriminating poor from EULAR responders. Immunofluorescence assay validated that anti-TROVE2 antibody could highly predict ADAb development and poor EULAR response (AUC 0.79 and 0.89, respectively). Multivariate regression analysis proved anti-TROVE2 antibody to be an independent predictor for developing ADAb. Immune-related protein microarray and replication analysis identified anti-TROVE2 antibody as a useful biomarker for predicting ADAb development and therapeutic response in adalimumab-treated patients. |
| format | Article |
| id | doaj-art-cf7d1144e6b9487a9fdd196f98b05e13 |
| institution | Kabale University |
| issn | 2314-8861 2314-7156 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Immunology Research |
| spelling | doaj-art-cf7d1144e6b9487a9fdd196f98b05e132025-02-03T06:46:14ZengWileyJournal of Immunology Research2314-88612314-71562021-01-01202110.1155/2021/66561216656121Anti-TROVE2 Antibody Determined by Immune-Related Array May Serve as a Predictive Marker for Adalimumab Immunogenicity and Effectiveness in RAPo-Ku Chen0Joung-Liang Lan1Yi-Ming Chen2Hsin-Hua Chen3Shih-Hsin Chang4Chia-Min Chung5Nurul H. Rutt6Ti-Myen Tan7Raja Nurashirin Raja Mamat8Nur Diana Anuar9Jonathan M. Blackburn10Der-Yuan Chen11Translational Medicine Laboratory, Rheumatic Diseases Research Center, China Medical University Hospital, Taichung, TaiwanCollege of Medicine, China Medical University, Taichung, TaiwanDepartment of Medical Research, Taichung Veterans General Hospital, TaiwanDepartment of Medical Research, Taichung Veterans General Hospital, TaiwanCollege of Medicine, China Medical University, Taichung, TaiwanCenter for Drug Abuse and Addiction, China Medical University Hospital, Taichung, TaiwanSengenics Corporation Pte Ltd., SingaporeSengenics Corporation Pte Ltd., SingaporeSengenics Corporation Pte Ltd., SingaporeSengenics Corporation Pte Ltd., SingaporeSengenics Corporation Pte Ltd., SingaporeTranslational Medicine Laboratory, Rheumatic Diseases Research Center, China Medical University Hospital, Taichung, TaiwanAnti-drug antibody (ADAb) development is associated with secondary therapeutic failure in biologic-treated rheumatoid arthritis (RA) patients. With a treat-to-target goal, we aimed to identify biomarkers for predicting ADAb development and therapeutic response in adalimumab-treated patients. Three independent cohorts were enrolled. In Cohort-1, 24 plasma samples (6 ADAb-positive and 6 ADAb-negative patients at baseline and week 24 of adalimumab therapy, respectively) were assayed with immune-related microarray containing 1,636 correctly folded functional proteins. Next, we executed statistically powered autoantibody profiling analysis of 50 samples in Cohort-2 (24 ADAb-positive and 26 ADAb-negative patients). Subsequently, immunofluorescence assay was performed on 48 samples in Cohort-3 to correlate with ADAb titers and drug levels. The biomarkers were identified for predicting ADAb development and therapeutic response using the immune-related microarray and machine learning approach. ADAb-positive patients had lower drug levels at week 24 (median=0.024 μg/ml) compared with ADAb-negative patients (median=6.38 μg/ml, p<0.001). ROC analysis based on the ADAb status revealed the top 20 autoantibodies with AUC≥0.7 in differentiating both groups in Cohort-1. Analysis of Cohort-2 dataset identified a panel of 8 biomarkers (TROVE2, SSB, NDE1, ZHX2, SH3GL1, CARD9, PTPN20, and KLHL12) with 80.6% specificity, 77.4% sensitivity, and 79.0% accuracy in discriminating poor from EULAR responders. Immunofluorescence assay validated that anti-TROVE2 antibody could highly predict ADAb development and poor EULAR response (AUC 0.79 and 0.89, respectively). Multivariate regression analysis proved anti-TROVE2 antibody to be an independent predictor for developing ADAb. Immune-related protein microarray and replication analysis identified anti-TROVE2 antibody as a useful biomarker for predicting ADAb development and therapeutic response in adalimumab-treated patients.http://dx.doi.org/10.1155/2021/6656121 |
| spellingShingle | Po-Ku Chen Joung-Liang Lan Yi-Ming Chen Hsin-Hua Chen Shih-Hsin Chang Chia-Min Chung Nurul H. Rutt Ti-Myen Tan Raja Nurashirin Raja Mamat Nur Diana Anuar Jonathan M. Blackburn Der-Yuan Chen Anti-TROVE2 Antibody Determined by Immune-Related Array May Serve as a Predictive Marker for Adalimumab Immunogenicity and Effectiveness in RA Journal of Immunology Research |
| title | Anti-TROVE2 Antibody Determined by Immune-Related Array May Serve as a Predictive Marker for Adalimumab Immunogenicity and Effectiveness in RA |
| title_full | Anti-TROVE2 Antibody Determined by Immune-Related Array May Serve as a Predictive Marker for Adalimumab Immunogenicity and Effectiveness in RA |
| title_fullStr | Anti-TROVE2 Antibody Determined by Immune-Related Array May Serve as a Predictive Marker for Adalimumab Immunogenicity and Effectiveness in RA |
| title_full_unstemmed | Anti-TROVE2 Antibody Determined by Immune-Related Array May Serve as a Predictive Marker for Adalimumab Immunogenicity and Effectiveness in RA |
| title_short | Anti-TROVE2 Antibody Determined by Immune-Related Array May Serve as a Predictive Marker for Adalimumab Immunogenicity and Effectiveness in RA |
| title_sort | anti trove2 antibody determined by immune related array may serve as a predictive marker for adalimumab immunogenicity and effectiveness in ra |
| url | http://dx.doi.org/10.1155/2021/6656121 |
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