Identification of a Novel, EBV-Based Antibody Risk Stratification Signature for Early Detection of Nasopharyngeal Carcinoma in Taiwan
Background. Epstein–Barr virus (EBV) is necessary for the development of nasopharyngeal carcinoma (NPC). By adulthood, approximately 90% of individuals test EBV-positive, but only a fraction develop cancer. Factors that identify which individuals are most likely to develop disease, including differe...
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| Published in | Clinical cancer research Vol. 24; no. 6; pp. 1305 - 1314 |
|---|---|
| Main Authors | , , , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
American Association for Cancer Research Inc
15.03.2018
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1078-0432 1557-3265 1557-3265 |
| DOI | 10.1158/1078-0432.CCR-17-1929 |
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| Abstract | Background. Epstein–Barr virus (EBV) is necessary for the development of nasopharyngeal carcinoma (NPC). By adulthood, approximately 90% of individuals test EBV-positive, but only a fraction develop cancer. Factors that identify which individuals are most likely to develop disease, including differential antibody response to the virus, could facilitate detection at early stages when treatment is most effective.
Methods. We measured anti-EBV IgG and IgA antibody responses in 607 Taiwanese individuals. Antibodies were measured using a custom protein microarray targeting 199 sequences from 86 EBV proteins. Variation in response patterns between NPC cases and controls was used to develop an antibody-based risk score for predicting NPC. The overall accuracy [area under the curve (AUC)] of this risk score, and its performance relative to currently used biomarkers, was evaluated in two independent Taiwanese cohorts.
Findings. Levels of 60 IgA and 73 IgG anti-EBV antibodies differed between stage I/IIa NPC cases and controls (P < 0.0002). Risk prediction analyses identified antibody targets that best discriminated NPC status—BXLF1, LF2,BZLF1, BRLF1, EAd, BGLF2, BPLF1, BFRF1, and BORF1. When combined with currently used VCA/EBNA1 IgA biomarkers, the resulting risk score predicted NPC with 93% accuracy (95% CI, 87%–98%) in the general Taiwanese population, a significant improvement beyond current biomarkers alone (82%; 95% CI, 75%–90%, P ≤ 0.01). This EBV-based risk score also improved NPC prediction in genetically high-risk families (89%; 95% CI, 82%–96%) compared with current biomarkers (78%; 95% CI, 66%–90%, P ≤ 0.03).
Interpretation. We identified NPC-related differences in 133 anti-EBV antibodies and developed a risk score using this microarray dataset that targeted immune responses against EBV proteins from all stages of the viral life cycle, significantly improving the ability to predict NPC. Clin Cancer Res; 24(6); 1305–14. ©2017 AACR. |
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| AbstractList | Background. Epstein–Barr virus (EBV) is necessary for the development of nasopharyngeal carcinoma (NPC). By adulthood, approximately 90% of individuals test EBV-positive, but only a fraction develop cancer. Factors that identify which individuals are most likely to develop disease, including differential antibody response to the virus, could facilitate detection at early stages when treatment is most effective.Methods. We measured anti-EBV IgG and IgA antibody responses in 607 Taiwanese individuals. Antibodies were measured using a custom protein microarray targeting 199 sequences from 86 EBV proteins. Variation in response patterns between NPC cases and controls was used to develop an antibody-based risk score for predicting NPC. The overall accuracy [area under the curve (AUC)] of this risk score, and its performance relative to currently used biomarkers, was evaluated in two independent Taiwanese cohorts.Findings. Levels of 60 IgA and 73 IgG anti-EBV antibodies differed between stage I/IIa NPC cases and controls (P < 0.0002). Risk prediction analyses identified antibody targets that best discriminated NPC status—BXLF1, LF2,BZLF1, BRLF1, EAd, BGLF2, BPLF1, BFRF1, and BORF1. When combined with currently used VCA/EBNA1 IgA biomarkers, the resulting risk score predicted NPC with 93% accuracy (95% CI, 87%–98%) in the general Taiwanese population, a significant improvement beyond current biomarkers alone (82%; 95% CI, 75%–90%, P ≤ 0.01). This EBV-based risk score also improved NPC prediction in genetically high-risk families (89%; 95% CI, 82%–96%) compared with current biomarkers (78%; 95% CI, 66%–90%, P ≤ 0.03).Interpretation. We identified NPC-related differences in 133 anti-EBV antibodies and developed a risk score using this microarray dataset that targeted immune responses against EBV proteins from all stages of the viral life cycle, significantly improving the ability to predict NPC. Clin Cancer Res; 24(6); 1305–14. ©2017 AACR. Background Epstein-Barr virus (EBV) is necessary for the development of nasopharyngeal carcinoma (NPC). By adulthood, approximately 90% of individuals test EBV-positive, but only a fraction develop cancer. Factors that identify which individuals are most likely to develop disease, including differential antibody response to the virus, could facilitate detection at early stages when treatment is most effective.Methods We measured anti-EBV IgG and IgA antibody responses in 607 Taiwanese individuals. Antibodies were measured using a custom protein microarray targeting 199 sequences from 86 EBV proteins. Variation in response patterns between NPC cases and controls was used to develop an antibody-based risk score for predicting NPC. The overall accuracy [area under the curve (AUC)] of this risk score, and its performance relative to currently used biomarkers, was evaluated in two independent Taiwanese cohorts.Findings Levels of 60 IgA and 73 IgG anti-EBV antibodies differed between stage I/IIa NPC cases and controls (P < 0.0002). Risk prediction analyses identified antibody targets that best discriminated NPC status-BXLF1, LF2,BZLF1, BRLF1, EAd, BGLF2, BPLF1, BFRF1, and BORF1. When combined with currently used VCA/EBNA1 IgA biomarkers, the resulting risk score predicted NPC with 93% accuracy (95% CI, 87%-98%) in the general Taiwanese population, a significant improvement beyond current biomarkers alone (82%; 95% CI, 75%-90%, P ≤ 0.01). This EBV-based risk score also improved NPC prediction in genetically high-risk families (89%; 95% CI, 82%-96%) compared with current biomarkers (78%; 95% CI, 66%-90%, P ≤ 0.03).Interpretation We identified NPC-related differences in 133 anti-EBV antibodies and developed a risk score using this microarray dataset that targeted immune responses against EBV proteins from all stages of the viral life cycle, significantly improving the ability to predict NPC. Clin Cancer Res; 24(6); 1305-14. ©2017 AACR.Background Epstein-Barr virus (EBV) is necessary for the development of nasopharyngeal carcinoma (NPC). By adulthood, approximately 90% of individuals test EBV-positive, but only a fraction develop cancer. Factors that identify which individuals are most likely to develop disease, including differential antibody response to the virus, could facilitate detection at early stages when treatment is most effective.Methods We measured anti-EBV IgG and IgA antibody responses in 607 Taiwanese individuals. Antibodies were measured using a custom protein microarray targeting 199 sequences from 86 EBV proteins. Variation in response patterns between NPC cases and controls was used to develop an antibody-based risk score for predicting NPC. The overall accuracy [area under the curve (AUC)] of this risk score, and its performance relative to currently used biomarkers, was evaluated in two independent Taiwanese cohorts.Findings Levels of 60 IgA and 73 IgG anti-EBV antibodies differed between stage I/IIa NPC cases and controls (P < 0.0002). Risk prediction analyses identified antibody targets that best discriminated NPC status-BXLF1, LF2,BZLF1, BRLF1, EAd, BGLF2, BPLF1, BFRF1, and BORF1. When combined with currently used VCA/EBNA1 IgA biomarkers, the resulting risk score predicted NPC with 93% accuracy (95% CI, 87%-98%) in the general Taiwanese population, a significant improvement beyond current biomarkers alone (82%; 95% CI, 75%-90%, P ≤ 0.01). This EBV-based risk score also improved NPC prediction in genetically high-risk families (89%; 95% CI, 82%-96%) compared with current biomarkers (78%; 95% CI, 66%-90%, P ≤ 0.03).Interpretation We identified NPC-related differences in 133 anti-EBV antibodies and developed a risk score using this microarray dataset that targeted immune responses against EBV proteins from all stages of the viral life cycle, significantly improving the ability to predict NPC. Clin Cancer Res; 24(6); 1305-14. ©2017 AACR. Epstein-Barr virus (EBV) is necessary for the development of nasopharyngeal carcinoma (NPC). By adulthood, approximately 90% of individuals test EBV-positive, but only a fraction develop cancer. Factors that identify which individuals are most likely to develop disease, including differential antibody response to the virus, could facilitate detection at early stages when treatment is most effective. We measured anti-EBV IgG and IgA antibody responses in 607 Taiwanese individuals. Antibodies were measured using a custom protein microarray targeting 199 sequences from 86 EBV proteins. Variation in response patterns between NPC cases and controls was used to develop an antibody-based risk score for predicting NPC. The overall accuracy [area under the curve (AUC)] of this risk score, and its performance relative to currently used biomarkers, was evaluated in two independent Taiwanese cohorts. Levels of 60 IgA and 73 IgG anti-EBV antibodies differed between stage I/IIa NPC cases and controls ( < 0.0002). Risk prediction analyses identified antibody targets that best discriminated NPC status-BXLF1, LF2,BZLF1, BRLF1, EAd, BGLF2, BPLF1, BFRF1, and BORF1. When combined with currently used VCA/EBNA1 IgA biomarkers, the resulting risk score predicted NPC with 93% accuracy (95% CI, 87%-98%) in the general Taiwanese population, a significant improvement beyond current biomarkers alone (82%; 95% CI, 75%-90%, ≤ 0.01). This EBV-based risk score also improved NPC prediction in genetically high-risk families (89%; 95% CI, 82%-96%) compared with current biomarkers (78%; 95% CI, 66%-90%, ≤ 0.03). We identified NPC-related differences in 133 anti-EBV antibodies and developed a risk score using this microarray dataset that targeted immune responses against EBV proteins from all stages of the viral life cycle, significantly improving the ability to predict NPC. . Background. Epstein–Barr virus (EBV) is necessary for the development of nasopharyngeal carcinoma (NPC). By adulthood, approximately 90% of individuals test EBV-positive, but only a fraction develop cancer. Factors that identify which individuals are most likely to develop disease, including differential antibody response to the virus, could facilitate detection at early stages when treatment is most effective. Methods. We measured anti-EBV IgG and IgA antibody responses in 607 Taiwanese individuals. Antibodies were measured using a custom protein microarray targeting 199 sequences from 86 EBV proteins. Variation in response patterns between NPC cases and controls was used to develop an antibody-based risk score for predicting NPC. The overall accuracy [area under the curve (AUC)] of this risk score, and its performance relative to currently used biomarkers, was evaluated in two independent Taiwanese cohorts. Findings. Levels of 60 IgA and 73 IgG anti-EBV antibodies differed between stage I/IIa NPC cases and controls (P < 0.0002). Risk prediction analyses identified antibody targets that best discriminated NPC status—BXLF1, LF2,BZLF1, BRLF1, EAd, BGLF2, BPLF1, BFRF1, and BORF1. When combined with currently used VCA/EBNA1 IgA biomarkers, the resulting risk score predicted NPC with 93% accuracy (95% CI, 87%–98%) in the general Taiwanese population, a significant improvement beyond current biomarkers alone (82%; 95% CI, 75%–90%, P ≤ 0.01). This EBV-based risk score also improved NPC prediction in genetically high-risk families (89%; 95% CI, 82%–96%) compared with current biomarkers (78%; 95% CI, 66%–90%, P ≤ 0.03). Interpretation. We identified NPC-related differences in 133 anti-EBV antibodies and developed a risk score using this microarray dataset that targeted immune responses against EBV proteins from all stages of the viral life cycle, significantly improving the ability to predict NPC. Clin Cancer Res; 24(6); 1305–14. ©2017 AACR. |
| Author | Doolan, Denise L. Yu, Kelly J. Krause, Lutz Hildesheim, Allan Pfeiffer, Ruth M. Liu, Zhiwei Chen, Chien-Jen Hsu, Wan-Lun Mulvenna, Jason Chien, Yin-Chu Coghill, Anna E. Teng, Andy Wang, Cheng-Ping Proietti, Carla Pablo, Jocelyn Lekieffre, Lea Lou, Pei-Jen Bethony, Jeff Middeldorp, Jaap |
| AuthorAffiliation | 8 Department of Otolaryngology, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan 1 Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland 10 Department of Microbiology, Immunology, and Tropical Medicine, George Washington University Medical Center, Washington DC 7 Antigen Discovery Inc., Irvine, California, USA 2 Queensland Institute of Medical Research, Brisbane, Australia 5 Graduate Institute of Epidemiology and Prevention Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan 6 National Institute of Cancer Research, National Health Research Institute, Miaoli, Taiwan 3 Australian Institute of Tropical Health & Medicine, James Cook University, Cairns, Australia 4 Genomics Research Center, Academica Sinica, Taipei, Taiwan 9 Vrije University Medical Center, Amsterdam, Netherlands |
| AuthorAffiliation_xml | – name: 2 Queensland Institute of Medical Research, Brisbane, Australia – name: 5 Graduate Institute of Epidemiology and Prevention Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan – name: 6 National Institute of Cancer Research, National Health Research Institute, Miaoli, Taiwan – name: 9 Vrije University Medical Center, Amsterdam, Netherlands – name: 10 Department of Microbiology, Immunology, and Tropical Medicine, George Washington University Medical Center, Washington DC – name: 7 Antigen Discovery Inc., Irvine, California, USA – name: 3 Australian Institute of Tropical Health & Medicine, James Cook University, Cairns, Australia – name: 8 Department of Otolaryngology, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan – name: 1 Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland – name: 4 Genomics Research Center, Academica Sinica, Taipei, Taiwan |
| Author_xml | – sequence: 1 givenname: Anna E. surname: Coghill fullname: Coghill, Anna E. – sequence: 2 givenname: Ruth M. surname: Pfeiffer fullname: Pfeiffer, Ruth M. – sequence: 3 givenname: Carla surname: Proietti fullname: Proietti, Carla – sequence: 4 givenname: Wan-Lun surname: Hsu fullname: Hsu, Wan-Lun – sequence: 5 givenname: Yin-Chu surname: Chien fullname: Chien, Yin-Chu – sequence: 6 givenname: Lea surname: Lekieffre fullname: Lekieffre, Lea – sequence: 7 givenname: Lutz surname: Krause fullname: Krause, Lutz – sequence: 8 givenname: Andy surname: Teng fullname: Teng, Andy – sequence: 9 givenname: Jocelyn surname: Pablo fullname: Pablo, Jocelyn – sequence: 10 givenname: Kelly J. surname: Yu fullname: Yu, Kelly J. – sequence: 11 givenname: Pei-Jen surname: Lou fullname: Lou, Pei-Jen – sequence: 12 givenname: Cheng-Ping surname: Wang fullname: Wang, Cheng-Ping – sequence: 13 givenname: Zhiwei surname: Liu fullname: Liu, Zhiwei – sequence: 14 givenname: Chien-Jen surname: Chen fullname: Chen, Chien-Jen – sequence: 15 givenname: Jaap surname: Middeldorp fullname: Middeldorp, Jaap – sequence: 16 givenname: Jason surname: Mulvenna fullname: Mulvenna, Jason – sequence: 17 givenname: Jeff surname: Bethony fullname: Bethony, Jeff – sequence: 18 givenname: Allan surname: Hildesheim fullname: Hildesheim, Allan – sequence: 19 givenname: Denise L. surname: Doolan fullname: Doolan, Denise L. |
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| Copyright | 2018 American Association for Cancer Research. Copyright American Association for Cancer Research Inc Mar 15, 2018 |
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| Snippet | Background. Epstein–Barr virus (EBV) is necessary for the development of nasopharyngeal carcinoma (NPC). By adulthood, approximately 90% of individuals test... Epstein-Barr virus (EBV) is necessary for the development of nasopharyngeal carcinoma (NPC). By adulthood, approximately 90% of individuals test EBV-positive,... Background Epstein-Barr virus (EBV) is necessary for the development of nasopharyngeal carcinoma (NPC). By adulthood, approximately 90% of individuals test... |
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| SubjectTerms | Adult Aged Antibodies Antibodies, Viral - immunology Antibody response Biomarkers BZLF1 protein Cancer Case-Control Studies Cross-Sectional Studies Early Detection of Cancer - methods Epstein-Barr virus Epstein-Barr Virus Infections - complications Epstein-Barr Virus Infections - immunology Epstein-Barr Virus Infections - virology Female Herpesvirus 4, Human - immunology Humans Immune response Immunoglobulin A Immunoglobulin A - blood Immunoglobulin A - immunology Immunoglobulin G Immunoglobulin G - blood Immunoglobulin G - immunology Immunoglobulins Life cycle engineering Life cycles Male Mass Screening Measurement methods Middle Aged Nasopharyngeal carcinoma Nasopharyngeal Carcinoma - diagnosis Nasopharyngeal Carcinoma - epidemiology Nasopharyngeal Carcinoma - etiology Neoplasm Staging Predictive control Protein arrays Proteins Risk Assessment Risk management ROC Curve Taiwan - epidemiology Target recognition Viruses Young Adult |
| Title | Identification of a Novel, EBV-Based Antibody Risk Stratification Signature for Early Detection of Nasopharyngeal Carcinoma in Taiwan |
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