Type-Specific Cell Line Models for Type-Specific Ovarian Cancer Research
OVARIAN CARCINOMAS CONSIST OF AT LEAST FIVE DISTINCT DISEASES: high-grade serous, low-grade serous, clear cell, endometrioid, and mucinous. Biomarker and molecular characterization may represent a more biologically relevant basis for grouping and treating this family of tumors, rather than site of o...
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| Veröffentlicht in: | PloS one Jg. 8; H. 9; S. e72162 |
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| Hauptverfasser: | , , , , , , , , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
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United States
Public Library of Science
04.09.2013
Public Library of Science (PLoS) |
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| ISSN: | 1932-6203, 1932-6203 |
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| Abstract | OVARIAN CARCINOMAS CONSIST OF AT LEAST FIVE DISTINCT DISEASES: high-grade serous, low-grade serous, clear cell, endometrioid, and mucinous. Biomarker and molecular characterization may represent a more biologically relevant basis for grouping and treating this family of tumors, rather than site of origin. Molecular characteristics have become the new standard for clinical pathology, however development of tailored type-specific therapies is hampered by a failure of basic research to recognize that model systems used to study these diseases must also be stratified. Unrelated model systems do offer value for study of biochemical processes but specific cellular context needs to be applied to assess relevant therapeutic strategies.
We have focused on the identification of clear cell carcinoma cell line models. A panel of 32 "ovarian cancer" cell lines has been classified into histotypes using a combination of mutation profiles, IHC mutation-surrogates, and a validated immunohistochemical model. All cell lines were identity verified using STR analysis.
Many described ovarian clear cell lines have characteristic mutations (including ARID1A and PIK3CA) and an overall molecular/immuno-profile typical of primary tumors. Mutations in TP53 were present in the majority of high-grade serous cell lines. Advanced genomic analysis of bona-fide clear cell carcinoma cell lines also support copy number changes in typical biomarkers such at MET and HNF1B and a lack of any recurrent expressed re-arrangements.
As with primary ovarian tumors, mutation status of cancer genes like ARID1A and TP53 and a general immuno-profile serve well for establishing histotype of ovarian cancer cell We describe specific biomarkers and molecular features to re-classify generic "ovarian carcinoma" cell lines into type specific categories. Our data supports the use of prototype clear cell lines, such as TOV21G and JHOC-5, and questions the use of SKOV3 and A2780 as models of high-grade serous carcinoma. |
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| AbstractList | OVARIAN CARCINOMAS CONSIST OF AT LEAST FIVE DISTINCT DISEASES: high-grade serous, low-grade serous, clear cell, endometrioid, and mucinous. Biomarker and molecular characterization may represent a more biologically relevant basis for grouping and treating this family of tumors, rather than site of origin. Molecular characteristics have become the new standard for clinical pathology, however development of tailored type-specific therapies is hampered by a failure of basic research to recognize that model systems used to study these diseases must also be stratified. Unrelated model systems do offer value for study of biochemical processes but specific cellular context needs to be applied to assess relevant therapeutic strategies.BACKGROUNDOVARIAN CARCINOMAS CONSIST OF AT LEAST FIVE DISTINCT DISEASES: high-grade serous, low-grade serous, clear cell, endometrioid, and mucinous. Biomarker and molecular characterization may represent a more biologically relevant basis for grouping and treating this family of tumors, rather than site of origin. Molecular characteristics have become the new standard for clinical pathology, however development of tailored type-specific therapies is hampered by a failure of basic research to recognize that model systems used to study these diseases must also be stratified. Unrelated model systems do offer value for study of biochemical processes but specific cellular context needs to be applied to assess relevant therapeutic strategies.We have focused on the identification of clear cell carcinoma cell line models. A panel of 32 "ovarian cancer" cell lines has been classified into histotypes using a combination of mutation profiles, IHC mutation-surrogates, and a validated immunohistochemical model. All cell lines were identity verified using STR analysis.METHODSWe have focused on the identification of clear cell carcinoma cell line models. A panel of 32 "ovarian cancer" cell lines has been classified into histotypes using a combination of mutation profiles, IHC mutation-surrogates, and a validated immunohistochemical model. All cell lines were identity verified using STR analysis.Many described ovarian clear cell lines have characteristic mutations (including ARID1A and PIK3CA) and an overall molecular/immuno-profile typical of primary tumors. Mutations in TP53 were present in the majority of high-grade serous cell lines. Advanced genomic analysis of bona-fide clear cell carcinoma cell lines also support copy number changes in typical biomarkers such at MET and HNF1B and a lack of any recurrent expressed re-arrangements.RESULTSMany described ovarian clear cell lines have characteristic mutations (including ARID1A and PIK3CA) and an overall molecular/immuno-profile typical of primary tumors. Mutations in TP53 were present in the majority of high-grade serous cell lines. Advanced genomic analysis of bona-fide clear cell carcinoma cell lines also support copy number changes in typical biomarkers such at MET and HNF1B and a lack of any recurrent expressed re-arrangements.As with primary ovarian tumors, mutation status of cancer genes like ARID1A and TP53 and a general immuno-profile serve well for establishing histotype of ovarian cancer cell We describe specific biomarkers and molecular features to re-classify generic "ovarian carcinoma" cell lines into type specific categories. Our data supports the use of prototype clear cell lines, such as TOV21G and JHOC-5, and questions the use of SKOV3 and A2780 as models of high-grade serous carcinoma.CONCLUSIONSAs with primary ovarian tumors, mutation status of cancer genes like ARID1A and TP53 and a general immuno-profile serve well for establishing histotype of ovarian cancer cell We describe specific biomarkers and molecular features to re-classify generic "ovarian carcinoma" cell lines into type specific categories. Our data supports the use of prototype clear cell lines, such as TOV21G and JHOC-5, and questions the use of SKOV3 and A2780 as models of high-grade serous carcinoma. Ovarian carcinomas consist of at least five distinct diseases: high-grade serous, low-grade serous, clear cell, endometrioid, and mucinous. Biomarker and molecular characterization may represent a more biologically relevant basis for grouping and treating this family of tumors, rather than site of origin. Molecular characteristics have become the new standard for clinical pathology, however development of tailored type-specific therapies is hampered by a failure of basic research to recognize that model systems used to study these diseases must also be stratified. Unrelated model systems do offer value for study of biochemical processes but specific cellular context needs to be applied to assess relevant therapeutic strategies. We have focused on the identification of clear cell carcinoma cell line models. A panel of 32 "ovarian cancer" cell lines has been classified into histotypes using a combination of mutation profiles, IHC mutation-surrogates, and a validated immunohistochemical model. All cell lines were identity verified using STR analysis. Many described ovarian clear cell lines have characteristic mutations (including ARID1A and PIK3CA) and an overall molecular/immuno-profile typical of primary tumors. Mutations in TP53 were present in the majority of high-grade serous cell lines. Advanced genomic analysis of bona-fide clear cell carcinoma cell lines also support copy number changes in typical biomarkers such at MET and HNF1B and a lack of any recurrent expressed re-arrangements. Background Ovarian carcinomas consist of at least five distinct diseases: high-grade serous, low-grade serous, clear cell, endometrioid, and mucinous. Biomarker and molecular characterization may represent a more biologically relevant basis for grouping and treating this family of tumors, rather than site of origin. Molecular characteristics have become the new standard for clinical pathology, however development of tailored type-specific therapies is hampered by a failure of basic research to recognize that model systems used to study these diseases must also be stratified. Unrelated model systems do offer value for study of biochemical processes but specific cellular context needs to be applied to assess relevant therapeutic strategies. Methods We have focused on the identification of clear cell carcinoma cell line models. A panel of 32 "ovarian cancer" cell lines has been classified into histotypes using a combination of mutation profiles, IHC mutation-surrogates, and a validated immunohistochemical model. All cell lines were identity verified using STR analysis. Results Many described ovarian clear cell lines have characteristic mutations (including ARID1A and PIK3CA) and an overall molecular/immuno-profile typical of primary tumors. Mutations in TP53 were present in the majority of high-grade serous cell lines. Advanced genomic analysis of bona-fide clear cell carcinoma cell lines also support copy number changes in typical biomarkers such at MET and HNF1B and a lack of any recurrent expressed re-arrangements. Conclusions: As with primary ovarian tumors, mutation status of cancer genes like ARID1A and TP53 and a general immuno-profile serve well for establishing histotype of ovarian cancer cell We describe specific biomarkers and molecular features to re-classify generic "ovarian carcinoma" cell lines into type specific categories. Our data supports the use of prototype clear cell lines, such as TOV21G and JHOC-5, and questions the use of SKOV3 and A2780 as models of high-grade serous carcinoma. Background Ovarian carcinomas consist of at least five distinct diseases: high-grade serous, low-grade serous, clear cell, endometrioid, and mucinous. Biomarker and molecular characterization may represent a more biologically relevant basis for grouping and treating this family of tumors, rather than site of origin. Molecular characteristics have become the new standard for clinical pathology, however development of tailored type-specific therapies is hampered by a failure of basic research to recognize that model systems used to study these diseases must also be stratified. Unrelated model systems do offer value for study of biochemical processes but specific cellular context needs to be applied to assess relevant therapeutic strategies. Methods We have focused on the identification of clear cell carcinoma cell line models. A panel of 32 “ovarian cancer” cell lines has been classified into histotypes using a combination of mutation profiles, IHC mutation-surrogates, and a validated immunohistochemical model. All cell lines were identity verified using STR analysis. Results Many described ovarian clear cell lines have characteristic mutations (including ARID1A and PIK3CA) and an overall molecular/immuno-profile typical of primary tumors. Mutations in TP53 were present in the majority of high-grade serous cell lines. Advanced genomic analysis of bona-fide clear cell carcinoma cell lines also support copy number changes in typical biomarkers such at MET and HNF1B and a lack of any recurrent expressed re-arrangements. Conclusions: As with primary ovarian tumors, mutation status of cancer genes like ARID1A and TP53 and a general immuno-profile serve well for establishing histotype of ovarian cancer cell We describe specific biomarkers and molecular features to re-classify generic “ovarian carcinoma” cell lines into type specific categories. Our data supports the use of prototype clear cell lines, such as TOV21G and JHOC-5, and questions the use of SKOV3 and A2780 as models of high-grade serous carcinoma. OVARIAN CARCINOMAS CONSIST OF AT LEAST FIVE DISTINCT DISEASES: high-grade serous, low-grade serous, clear cell, endometrioid, and mucinous. Biomarker and molecular characterization may represent a more biologically relevant basis for grouping and treating this family of tumors, rather than site of origin. Molecular characteristics have become the new standard for clinical pathology, however development of tailored type-specific therapies is hampered by a failure of basic research to recognize that model systems used to study these diseases must also be stratified. Unrelated model systems do offer value for study of biochemical processes but specific cellular context needs to be applied to assess relevant therapeutic strategies. We have focused on the identification of clear cell carcinoma cell line models. A panel of 32 "ovarian cancer" cell lines has been classified into histotypes using a combination of mutation profiles, IHC mutation-surrogates, and a validated immunohistochemical model. All cell lines were identity verified using STR analysis. Many described ovarian clear cell lines have characteristic mutations (including ARID1A and PIK3CA) and an overall molecular/immuno-profile typical of primary tumors. Mutations in TP53 were present in the majority of high-grade serous cell lines. Advanced genomic analysis of bona-fide clear cell carcinoma cell lines also support copy number changes in typical biomarkers such at MET and HNF1B and a lack of any recurrent expressed re-arrangements. As with primary ovarian tumors, mutation status of cancer genes like ARID1A and TP53 and a general immuno-profile serve well for establishing histotype of ovarian cancer cell We describe specific biomarkers and molecular features to re-classify generic "ovarian carcinoma" cell lines into type specific categories. Our data supports the use of prototype clear cell lines, such as TOV21G and JHOC-5, and questions the use of SKOV3 and A2780 as models of high-grade serous carcinoma. |
| Audience | Academic |
| Author | Wiegand, Kimberly C. Kalloger, Steve E. Salamanca, Clara Chow, Christine Yang, Winnie Huntsman, David G. Senz, Janine Anglesio, Michael S. Shah, Sohrab P. Melnyk, Nataliya Cochrane, Dawn R. Spillman, Monique A. Prentice, Leah M. Shumansky, Karey |
| AuthorAffiliation | 4 Department of Obstetrics & Gynecology, University of Colorado, Anschutz Medical Campus, Aurora, Colorado, United States of America 3 Centre for Translational and Applied Genomics (CTAG), BC Cancer Agency, Vancouver, British Columbia, Canada 1 Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada Kinghorn Cancer Centre, Garvan Institute of Medical Research, Australia 2 Genetic Pathology Evaluation Centre, University of British Columbia and Vancouver General Hospital, Vancouver, British Columbia, Canada 5 Department of Molecular Oncology, BC Cancer Agency Cancer Research Centre, Vancouver, British Columbia, Canada |
| AuthorAffiliation_xml | – name: 2 Genetic Pathology Evaluation Centre, University of British Columbia and Vancouver General Hospital, Vancouver, British Columbia, Canada – name: 3 Centre for Translational and Applied Genomics (CTAG), BC Cancer Agency, Vancouver, British Columbia, Canada – name: 5 Department of Molecular Oncology, BC Cancer Agency Cancer Research Centre, Vancouver, British Columbia, Canada – name: 1 Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada – name: 4 Department of Obstetrics & Gynecology, University of Colorado, Anschutz Medical Campus, Aurora, Colorado, United States of America – name: Kinghorn Cancer Centre, Garvan Institute of Medical Research, Australia |
| Author_xml | – sequence: 1 givenname: Michael S. surname: Anglesio fullname: Anglesio, Michael S. – sequence: 2 givenname: Kimberly C. surname: Wiegand fullname: Wiegand, Kimberly C. – sequence: 3 givenname: Nataliya surname: Melnyk fullname: Melnyk, Nataliya – sequence: 4 givenname: Christine surname: Chow fullname: Chow, Christine – sequence: 5 givenname: Clara surname: Salamanca fullname: Salamanca, Clara – sequence: 6 givenname: Leah M. surname: Prentice fullname: Prentice, Leah M. – sequence: 7 givenname: Janine surname: Senz fullname: Senz, Janine – sequence: 8 givenname: Winnie surname: Yang fullname: Yang, Winnie – sequence: 9 givenname: Monique A. surname: Spillman fullname: Spillman, Monique A. – sequence: 10 givenname: Dawn R. surname: Cochrane fullname: Cochrane, Dawn R. – sequence: 11 givenname: Karey surname: Shumansky fullname: Shumansky, Karey – sequence: 12 givenname: Sohrab P. surname: Shah fullname: Shah, Sohrab P. – sequence: 13 givenname: Steve E. surname: Kalloger fullname: Kalloger, Steve E. – sequence: 14 givenname: David G. surname: Huntsman fullname: Huntsman, David G. |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/24023729$$D View this record in MEDLINE/PubMed |
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| Copyright | COPYRIGHT 2013 Public Library of Science 2013 Anglesio et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2013 Anglesio et al 2013 Anglesio et al |
| Copyright_xml | – notice: COPYRIGHT 2013 Public Library of Science – notice: 2013 Anglesio et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. – notice: 2013 Anglesio et al 2013 Anglesio et al |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Conceived and designed the experiments: MSA SEK DGH. Performed the experiments: MSA KCW CS CC JS WY NM LMP. Analyzed the data: MSA KS SEK. Contributed reagents/materials/analysis tools: MSA KCW DGH SPS MAS DRC. Wrote the paper: MSA SEK DRC LMP KCW MAS DGH. Competing Interests: The authors have declared that no competing interests exist. |
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| Snippet | OVARIAN CARCINOMAS CONSIST OF AT LEAST FIVE DISTINCT DISEASES: high-grade serous, low-grade serous, clear cell, endometrioid, and mucinous. Biomarker and... Background Ovarian carcinomas consist of at least five distinct diseases: high-grade serous, low-grade serous, clear cell, endometrioid, and mucinous.... Ovarian carcinomas consist of at least five distinct diseases: high-grade serous, low-grade serous, clear cell, endometrioid, and mucinous. Biomarker and... BACKGROUND:OVARIAN CARCINOMAS CONSIST OF AT LEAST FIVE DISTINCT DISEASES: high-grade serous, low-grade serous, clear cell, endometrioid, and mucinous.... Background Ovarian carcinomas consist of at least five distinct diseases: high-grade serous, low-grade serous, clear cell, endometrioid, and mucinous.... |
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| SubjectTerms | Analysis Biology Biomarkers Biotechnology Cancer Cancer research Carcinoma, Ovarian Epithelial Cell culture Cell Line, Tumor Chemotherapy Copy number Cystadenocarcinoma, Serous - genetics Cystadenocarcinoma, Serous - pathology Endometrial cancer Female Genomic analysis Genomics Histology Humans Identification methods Laboratories Medical research Medicine Mutation Neoplasms, Glandular and Epithelial - genetics Neoplasms, Glandular and Epithelial - pathology Ovarian cancer Ovarian carcinoma Ovarian Neoplasms - genetics Ovarian Neoplasms - pathology p53 Protein Pathology Quality Studies Tumor cell lines Tumor proteins Tumor Suppressor Protein p53 - genetics Tumors |
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| Title | Type-Specific Cell Line Models for Type-Specific Ovarian Cancer Research |
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