Identification of five serum protein markers for detection of ovarian cancer by antibody arrays.
BACKGROUND:Protein and antibody arrays have emerged as a promising technology to study protein expression and protein function in a high-throughput manner. These arrays also represent a new opportunity to profile protein expression levels in cancer patients' samples and to identify useful biosi...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2013-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC3792870?pdf=render |
| _version_ | 1817979640005787648 |
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| author | Weidong Jiang Ruochun Huang Chaohui Duan Liwu Fu Yun Xi Yuebo Yang Wei-Min Yang Dongzi Yang Dong-Hua Yang Ruo-Pan Huang |
| author_facet | Weidong Jiang Ruochun Huang Chaohui Duan Liwu Fu Yun Xi Yuebo Yang Wei-Min Yang Dongzi Yang Dong-Hua Yang Ruo-Pan Huang |
| author_sort | Weidong Jiang |
| collection | DOAJ |
| description | BACKGROUND:Protein and antibody arrays have emerged as a promising technology to study protein expression and protein function in a high-throughput manner. These arrays also represent a new opportunity to profile protein expression levels in cancer patients' samples and to identify useful biosignatures for clinical diagnosis, disease classification, prediction, drug development and patient care. We applied antibody arrays to discover a panel of proteins which may serve as biomarkers to distinguish between patients with ovarian cancer and normal controls. METHODOLOGY/PRINCIPAL FINDINGS:Using a case-control study design of 34 ovarian cancer patients and 53 age-matched healthy controls, we profiled the expression levels of 174 proteins using antibody array technology and determined the CA125 level using ELISA. The expression levels of those proteins were analyzed using 3 discriminant methods, including artificial neural network, classification tree and split-point score analysis. A panel of 5 serum protein markers (MSP-alpha, TIMP-4, PDGF-R alpha, and OPG and CA125) was identified, which could effectively detect ovarian cancer with high specificity (95%) and high sensitivity (100%), with AUC =0.98, while CA125 alone had an AUC of 0.87. CONCLUSIONS/SIGNIFICANCE:Our pilot study has shown the promising set of 5 serum markers for ovarian cancer detection. |
| first_indexed | 2024-04-13T22:45:07Z |
| format | Article |
| id | doaj.art-f2c53b9e26c146a799231d78d8cd6883 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-04-13T22:45:07Z |
| publishDate | 2013-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-f2c53b9e26c146a799231d78d8cd68832022-12-22T02:26:28ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-01810e7679510.1371/journal.pone.0076795Identification of five serum protein markers for detection of ovarian cancer by antibody arrays.Weidong JiangRuochun HuangChaohui DuanLiwu FuYun XiYuebo YangWei-Min YangDongzi YangDong-Hua YangRuo-Pan HuangBACKGROUND:Protein and antibody arrays have emerged as a promising technology to study protein expression and protein function in a high-throughput manner. These arrays also represent a new opportunity to profile protein expression levels in cancer patients' samples and to identify useful biosignatures for clinical diagnosis, disease classification, prediction, drug development and patient care. We applied antibody arrays to discover a panel of proteins which may serve as biomarkers to distinguish between patients with ovarian cancer and normal controls. METHODOLOGY/PRINCIPAL FINDINGS:Using a case-control study design of 34 ovarian cancer patients and 53 age-matched healthy controls, we profiled the expression levels of 174 proteins using antibody array technology and determined the CA125 level using ELISA. The expression levels of those proteins were analyzed using 3 discriminant methods, including artificial neural network, classification tree and split-point score analysis. A panel of 5 serum protein markers (MSP-alpha, TIMP-4, PDGF-R alpha, and OPG and CA125) was identified, which could effectively detect ovarian cancer with high specificity (95%) and high sensitivity (100%), with AUC =0.98, while CA125 alone had an AUC of 0.87. CONCLUSIONS/SIGNIFICANCE:Our pilot study has shown the promising set of 5 serum markers for ovarian cancer detection.http://europepmc.org/articles/PMC3792870?pdf=render |
| spellingShingle | Weidong Jiang Ruochun Huang Chaohui Duan Liwu Fu Yun Xi Yuebo Yang Wei-Min Yang Dongzi Yang Dong-Hua Yang Ruo-Pan Huang Identification of five serum protein markers for detection of ovarian cancer by antibody arrays. PLoS ONE |
| title | Identification of five serum protein markers for detection of ovarian cancer by antibody arrays. |
| title_full | Identification of five serum protein markers for detection of ovarian cancer by antibody arrays. |
| title_fullStr | Identification of five serum protein markers for detection of ovarian cancer by antibody arrays. |
| title_full_unstemmed | Identification of five serum protein markers for detection of ovarian cancer by antibody arrays. |
| title_short | Identification of five serum protein markers for detection of ovarian cancer by antibody arrays. |
| title_sort | identification of five serum protein markers for detection of ovarian cancer by antibody arrays |
| url | http://europepmc.org/articles/PMC3792870?pdf=render |
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