Discovery of Novel Ovarian Cancer Biomarkers via Proteomics and Mass Spectrometry
Proteins secreted or shed by tumors can be found in serum. Detecting these proteins by mass spectrometry (MS) is difficult, due to the wide dynamic range of protein concentrations in serum. To circumvent this issue, we mined the conditioned media of epithelial ovarian cancer (EOC) cell lines which...
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ndltd-LACETR-oai-collectionscanada.gc.ca-OTU.1807-247612013-11-02T03:42:22ZDiscovery of Novel Ovarian Cancer Biomarkers via Proteomics and Mass SpectrometryGunawardana, Chinthaka GeethOvarian CancerBiomarkersChromatographyMass SpectrometryELISA0571Proteins secreted or shed by tumors can be found in serum. Detecting these proteins by mass spectrometry (MS) is difficult, due to the wide dynamic range of protein concentrations in serum. To circumvent this issue, we mined the conditioned media of epithelial ovarian cancer (EOC) cell lines which is a less complex fluid to work with. We hypothesize that some of the proteins shed or secreted by EOC cell lines are similar to those secreted or shed by EOC tumors and that some of these proteins can be used as biomarkers. We mined the conditioned medium of four ovarian cancer cell lines (HTB75, TOV-112D, TOV-21G and RMUG-S) by two-dimensional liquid chromatography-mass spectrometry. Our study identified 1208, 1252, 885, and 463 proteins from the HTB-75, TOV-112D, TOV-21G, and RMUG-S cell lines respectively. In all, we identified 2039 proteins from which we focused on 420 extracellular and plasma membrane proteins. High abundance proteins such as albumin and immunoglobulins, which are problematic for serum proteomics, did not interfere with our study. Several known markers of EOC including CA-125, HE4, Mesothelin, and KLK6, were identified in this study. The list of 420 extracellular and membrane proteins was cross-referenced with the proteome of ascites fluid to generate a final list of 51 potential candidates. According to Ingenuity Pathway Analysis, two of the top 10 diseases associated with our list of 51 proteins were cancer and reproductive diseases. Of the 51 candidates, 10 proteins were selected for verification in sera from ovarian cancer patients and healthy individuals. Clusterin showed a significant difference between cancer patients and normal, with sera from cancer patients showing higher levels. Another protein, NPC2, did not show a difference in sera between cancer and normals. Protein expression studies using immunohistochemistry showed that NPC2 is highly expressed in ovarian cancer tissue and absent in normal ovarian surface epithelium. In summary, clusterin and NPC2 appear to play a role in ovarian cancer pathobiology and their role in EOC need to be studied further.Diamandis, Eleftherios P.2010-062010-08-12T19:42:43ZNO_RESTRICTION2010-08-12T19:42:43Z2010-08-12T19:42:43ZThesishttp://hdl.handle.net/1807/24761en_ca |
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Ovarian Cancer Biomarkers Chromatography Mass Spectrometry ELISA 0571 |
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Ovarian Cancer Biomarkers Chromatography Mass Spectrometry ELISA 0571 Gunawardana, Chinthaka Geeth Discovery of Novel Ovarian Cancer Biomarkers via Proteomics and Mass Spectrometry |
description |
Proteins secreted or shed by tumors can be found in serum. Detecting these proteins by mass spectrometry (MS) is difficult, due to the wide dynamic range of protein concentrations in serum. To circumvent this issue, we mined the conditioned media of epithelial ovarian cancer (EOC) cell lines which is a less complex fluid to work with. We hypothesize that some of the proteins shed or secreted by EOC cell lines are similar to those secreted or shed by EOC tumors and that some of these proteins can be used as biomarkers. We mined the conditioned medium of four ovarian cancer cell lines (HTB75, TOV-112D, TOV-21G and RMUG-S) by two-dimensional liquid chromatography-mass spectrometry. Our study identified 1208, 1252, 885, and 463 proteins from the HTB-75, TOV-112D, TOV-21G, and RMUG-S cell lines respectively. In all, we identified 2039 proteins from which we focused on 420 extracellular and plasma membrane proteins. High abundance proteins such as albumin and immunoglobulins, which are problematic for serum proteomics, did not interfere with our study. Several known markers of EOC including CA-125, HE4, Mesothelin, and KLK6, were identified in this study. The list of 420 extracellular and membrane proteins was cross-referenced with the proteome of ascites fluid to generate a final list of 51 potential candidates. According to Ingenuity Pathway Analysis, two of the top 10 diseases associated with our list of 51 proteins were cancer and reproductive diseases. Of the 51 candidates, 10 proteins were selected for verification in sera from ovarian cancer patients and healthy individuals. Clusterin showed a significant difference between cancer patients and normal, with sera from cancer patients showing higher levels. Another protein, NPC2, did not show a difference in sera between cancer and normals. Protein expression studies using immunohistochemistry showed that NPC2 is highly expressed in ovarian cancer tissue and absent in normal ovarian surface epithelium. In summary, clusterin and NPC2 appear to play a role in ovarian cancer pathobiology and their role in EOC need to be studied further. |
author2 |
Diamandis, Eleftherios P. |
author_facet |
Diamandis, Eleftherios P. Gunawardana, Chinthaka Geeth |
author |
Gunawardana, Chinthaka Geeth |
author_sort |
Gunawardana, Chinthaka Geeth |
title |
Discovery of Novel Ovarian Cancer Biomarkers via Proteomics and Mass Spectrometry |
title_short |
Discovery of Novel Ovarian Cancer Biomarkers via Proteomics and Mass Spectrometry |
title_full |
Discovery of Novel Ovarian Cancer Biomarkers via Proteomics and Mass Spectrometry |
title_fullStr |
Discovery of Novel Ovarian Cancer Biomarkers via Proteomics and Mass Spectrometry |
title_full_unstemmed |
Discovery of Novel Ovarian Cancer Biomarkers via Proteomics and Mass Spectrometry |
title_sort |
discovery of novel ovarian cancer biomarkers via proteomics and mass spectrometry |
publishDate |
2010 |
url |
http://hdl.handle.net/1807/24761 |
work_keys_str_mv |
AT gunawardanachinthakageeth discoveryofnovelovariancancerbiomarkersviaproteomicsandmassspectrometry |
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1716611887431417856 |