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Serum Autoantibodies against LRDD, STC1, and FOXA1 as Biomarkers in the Detection of Ovarian Cancer

PURPOSE: This study is aimed at evaluating serum autoantibodies against four tumor-associated antigens, including LRDD, STC1, FOXA1, and EDNRB, as biomarkers in the immunodiagnosis of ovarian cancer (OC). METHODS: The autoantibodies against LRDD, STC1, FOXA1, and EDNRB were measured using an enzyme-...

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Autores principales: Duan, Yaru, Cui, Chi, Qiu, Cuipeng, Sun, Guiying, Wang, Xiao, Wang, Peng, Ye, Hua, Dai, Liping, Shi, Jianxiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8904091/
https://www.ncbi.nlm.nih.gov/pubmed/35273656
http://dx.doi.org/10.1155/2022/6657820
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author Duan, Yaru
Cui, Chi
Qiu, Cuipeng
Sun, Guiying
Wang, Xiao
Wang, Peng
Ye, Hua
Dai, Liping
Shi, Jianxiang
author_facet Duan, Yaru
Cui, Chi
Qiu, Cuipeng
Sun, Guiying
Wang, Xiao
Wang, Peng
Ye, Hua
Dai, Liping
Shi, Jianxiang
author_sort Duan, Yaru
collection PubMed
description PURPOSE: This study is aimed at evaluating serum autoantibodies against four tumor-associated antigens, including LRDD, STC1, FOXA1, and EDNRB, as biomarkers in the immunodiagnosis of ovarian cancer (OC). METHODS: The autoantibodies against LRDD, STC1, FOXA1, and EDNRB were measured using an enzyme-linked immunosorbent assay (ELISA) in 94 OC patients and 94 normal healthy controls (NHC) in the research group. In addition, the diagnostic values of different autoantibodies were validated in another independent validation group, which comprised 136 OC patients, 136 NHC, and 181 patients with benign ovarian diseases (BOD). RESULTS: In the research group, autoantibodies against LRDD, STC1, and FOXA1 had higher serum titer in OC patients than NHC (P < 0.001). The area under receiver operating characteristic curves (AUCs) of these three autoantibodies were 0.910, 0.879, and 0.817, respectively. In the validation group, they showed AUCs of 0.759, 0.762, and 0.817 and sensitivities of 49.3%, 42.7%, and 48.5%, respectively, at specificity over 90% for discriminating OC patients from NHC. For discriminating OC patients from BOD, they showed AUCs of 0.718, 0.729, and 0.814 and sensitivities of 47.1%, 39.0%, and 51.5%, respectively, at specificity over 90%. The parallel analyses demonstrated that the combination of anti-LRDD and anti-FOXA1 autoantibodies achieved the optimal diagnostic performance with the sensitivity of 58.1% at 87.5% specificity and accuracy of 72.8%. The positive rate of the optimal autoantibody panel improved from 62.4% to 87.1% when combined with CA125 in detecting OC patients. CONCLUSION: Serum autoantibodies against LRDD, STC1, and FOXA1 have potential diagnostic values in detecting OC.
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spelling pubmed-89040912022-03-09 Serum Autoantibodies against LRDD, STC1, and FOXA1 as Biomarkers in the Detection of Ovarian Cancer Duan, Yaru Cui, Chi Qiu, Cuipeng Sun, Guiying Wang, Xiao Wang, Peng Ye, Hua Dai, Liping Shi, Jianxiang Dis Markers Research Article PURPOSE: This study is aimed at evaluating serum autoantibodies against four tumor-associated antigens, including LRDD, STC1, FOXA1, and EDNRB, as biomarkers in the immunodiagnosis of ovarian cancer (OC). METHODS: The autoantibodies against LRDD, STC1, FOXA1, and EDNRB were measured using an enzyme-linked immunosorbent assay (ELISA) in 94 OC patients and 94 normal healthy controls (NHC) in the research group. In addition, the diagnostic values of different autoantibodies were validated in another independent validation group, which comprised 136 OC patients, 136 NHC, and 181 patients with benign ovarian diseases (BOD). RESULTS: In the research group, autoantibodies against LRDD, STC1, and FOXA1 had higher serum titer in OC patients than NHC (P < 0.001). The area under receiver operating characteristic curves (AUCs) of these three autoantibodies were 0.910, 0.879, and 0.817, respectively. In the validation group, they showed AUCs of 0.759, 0.762, and 0.817 and sensitivities of 49.3%, 42.7%, and 48.5%, respectively, at specificity over 90% for discriminating OC patients from NHC. For discriminating OC patients from BOD, they showed AUCs of 0.718, 0.729, and 0.814 and sensitivities of 47.1%, 39.0%, and 51.5%, respectively, at specificity over 90%. The parallel analyses demonstrated that the combination of anti-LRDD and anti-FOXA1 autoantibodies achieved the optimal diagnostic performance with the sensitivity of 58.1% at 87.5% specificity and accuracy of 72.8%. The positive rate of the optimal autoantibody panel improved from 62.4% to 87.1% when combined with CA125 in detecting OC patients. CONCLUSION: Serum autoantibodies against LRDD, STC1, and FOXA1 have potential diagnostic values in detecting OC. Hindawi 2022-03-01 /pmc/articles/PMC8904091/ /pubmed/35273656 http://dx.doi.org/10.1155/2022/6657820 Text en Copyright © 2022 Yaru Duan et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Duan, Yaru
Cui, Chi
Qiu, Cuipeng
Sun, Guiying
Wang, Xiao
Wang, Peng
Ye, Hua
Dai, Liping
Shi, Jianxiang
Serum Autoantibodies against LRDD, STC1, and FOXA1 as Biomarkers in the Detection of Ovarian Cancer
title Serum Autoantibodies against LRDD, STC1, and FOXA1 as Biomarkers in the Detection of Ovarian Cancer
title_full Serum Autoantibodies against LRDD, STC1, and FOXA1 as Biomarkers in the Detection of Ovarian Cancer
title_fullStr Serum Autoantibodies against LRDD, STC1, and FOXA1 as Biomarkers in the Detection of Ovarian Cancer
title_full_unstemmed Serum Autoantibodies against LRDD, STC1, and FOXA1 as Biomarkers in the Detection of Ovarian Cancer
title_short Serum Autoantibodies against LRDD, STC1, and FOXA1 as Biomarkers in the Detection of Ovarian Cancer
title_sort serum autoantibodies against lrdd, stc1, and foxa1 as biomarkers in the detection of ovarian cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8904091/
https://www.ncbi.nlm.nih.gov/pubmed/35273656
http://dx.doi.org/10.1155/2022/6657820
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