A novel immunodiagnosis panel for hepatocellular carcinoma based on bioinformatics and the autoantibody‐antigen system. Issue 2 (14th December 2021)
- Record Type:
- Journal Article
- Title:
- A novel immunodiagnosis panel for hepatocellular carcinoma based on bioinformatics and the autoantibody‐antigen system. Issue 2 (14th December 2021)
- Main Title:
- A novel immunodiagnosis panel for hepatocellular carcinoma based on bioinformatics and the autoantibody‐antigen system
- Authors:
- Wu, Jinyu
Wang, Peng
Han, Zhuo
Li, Tiandong
Yi, Chuncheng
Qiu, Cuipeng
Yang, Qian
Sun, Guiying
Dai, Liping
Shi, Jianxiang
Wang, Keyan
Ye, Hua - Abstract:
- Abstract: Hepatocellular carcinoma (HCC) is a malignancy with a dismal survival rate. The novel autoantibodies panel may provide new insights for the diagnosis of HCC. Biomarkers screened by two methods (bioinformatics and the antigen‐antibody system) were taken as candidate tumor‐associated antigens (TAAs). Enzyme‐linked immunosorbent assay was used to detect the corresponding autoantibodies in 888 samples of verification and validation cohorts. The verification cohort was used to verify the autoantibodies. Samples in the validation cohort were randomly divided into a train set and a test set with the ratio of 6:4. A diagnostic model was established by support vector machines within the train set. The test set further verified the model. Eleven TAAs were selected (AAGAB, C17orf75, CDC37L1, DUSP6, EID3, PDIA2, RGS20, PCNA, TAF7L, TBC1D13, and ZIC2). The titer of six autoantibodies (PCNA, AAGAB, CDC37L1, TAF7L, DUSP6, and ZIC2) had a significant difference in any of the pairwise comparisons among the HCC, liver cirrhosis, and normal control groups. The titer of these autoantibodies had an increasing tendency. Finally, an optimum diagnostic model was constructed with the six autoantibodies. The AUCs were 0.826 in the train set and 0.773 in the test set. The area under the curve (AUC) of this panel for diagnosing early HCC was 0.889. The diagnostic ability of the panel reduced with the progress of HCC. The positive rate of the panel in diagnosing alpha‐fetoproteinAbstract: Hepatocellular carcinoma (HCC) is a malignancy with a dismal survival rate. The novel autoantibodies panel may provide new insights for the diagnosis of HCC. Biomarkers screened by two methods (bioinformatics and the antigen‐antibody system) were taken as candidate tumor‐associated antigens (TAAs). Enzyme‐linked immunosorbent assay was used to detect the corresponding autoantibodies in 888 samples of verification and validation cohorts. The verification cohort was used to verify the autoantibodies. Samples in the validation cohort were randomly divided into a train set and a test set with the ratio of 6:4. A diagnostic model was established by support vector machines within the train set. The test set further verified the model. Eleven TAAs were selected (AAGAB, C17orf75, CDC37L1, DUSP6, EID3, PDIA2, RGS20, PCNA, TAF7L, TBC1D13, and ZIC2). The titer of six autoantibodies (PCNA, AAGAB, CDC37L1, TAF7L, DUSP6, and ZIC2) had a significant difference in any of the pairwise comparisons among the HCC, liver cirrhosis, and normal control groups. The titer of these autoantibodies had an increasing tendency. Finally, an optimum diagnostic model was constructed with the six autoantibodies. The AUCs were 0.826 in the train set and 0.773 in the test set. The area under the curve (AUC) of this panel for diagnosing early HCC was 0.889. The diagnostic ability of the panel reduced with the progress of HCC. The positive rate of the panel in diagnosing alpha‐fetoprotein (AFP)‐negative patients was 75.6%. For early HCC, the sensitivity of the combination of AFP with the panel was 90.9% and superior to 53.2% of AFP alone. The novel immunodiagnosis panel combining AFP may be a new approach for the diagnosis of HCC, especially for early‐HCC cases. Abstract : A support vector machine was used to construct a panel composed of six autoantibodies for hepatocellular carcinoma (HCC) diagnosis. The panel's ability to identify HCC was 0.826, and its ability to diagnose early HCC and alpha‐fetoprotein (AFP)‐negative HCC was 0.889 and 0.781, respectively. This research showed that the novel autoantibodies panel may be used as an immunodiagnosis method for HCC, especially for early‐HCC and AFP‐negative patients. … (more)
- Is Part Of:
- Cancer science. Volume 113:Issue 2(2022)
- Journal:
- Cancer science
- Issue:
- Volume 113:Issue 2(2022)
- Issue Display:
- Volume 113, Issue 2 (2022)
- Year:
- 2022
- Volume:
- 113
- Issue:
- 2
- Issue Sort Value:
- 2022-0113-0002-0000
- Page Start:
- 411
- Page End:
- 422
- Publication Date:
- 2021-12-14
- Subjects:
- autoantibodies -- bioinformatics -- hepatocellular carcinoma -- immunodiagnosis -- panel
Cancer -- Periodicals
Neoplasms -- Periodicals
Research -- Periodicals
Electronic journals
616.994005 - Journal URLs:
- http://firstsearch.oclc.org ↗
http://firstsearch.oclc.org/journal=1347-9032;screen=info;ECOIP ↗
http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1349-7006 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/cas.15217 ↗
- Languages:
- English
- ISSNs:
- 1347-9032
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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- British Library DSC - 3046.603000
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- 20759.xml