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Biomarker-Based Ovarian Carcinoma Typing: A Histologic Investigation in the Ovarian Tumor Tissue Analysis Consortium
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| Zeitschriftentitel: | Cancer Epidemiology, Biomarkers & Prevention |
|---|---|
| Personen und Körperschaften: | , , , , , , , , , , , , , , , , , , , , , , , , , , |
| In: | Cancer Epidemiology, Biomarkers & Prevention, 22, 2013, 10, S. 1677-1686 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
American Association for Cancer Research (AACR)
|
| Schlagwörter: |
| author_facet |
Köbel, Martin Kalloger, Steve E. Lee, Sandra Duggan, Máire A. Kelemen, Linda E. Prentice, Leah Kalli, Kimberly R. Fridley, Brooke L. Visscher, Daniel W. Keeney, Gary L. Vierkant, Robert A. Cunningham, Julie M. Chow, Christine Ness, Roberta B. Moysich, Kirsten Edwards, Robert Modugno, Francesmary Bunker, Clareann Wozniak, Eva L. Benjamin, Elizabeth Gayther, Simon A. Gentry-Maharaj, Aleksandra Menon, Usha Gilks, C. Blake Huntsman, David G. Ramus, Susan J. Goode, Ellen L. Köbel, Martin Kalloger, Steve E. Lee, Sandra Duggan, Máire A. Kelemen, Linda E. Prentice, Leah Kalli, Kimberly R. Fridley, Brooke L. Visscher, Daniel W. Keeney, Gary L. Vierkant, Robert A. Cunningham, Julie M. Chow, Christine Ness, Roberta B. Moysich, Kirsten Edwards, Robert Modugno, Francesmary Bunker, Clareann Wozniak, Eva L. Benjamin, Elizabeth Gayther, Simon A. Gentry-Maharaj, Aleksandra Menon, Usha Gilks, C. Blake Huntsman, David G. Ramus, Susan J. Goode, Ellen L. |
|---|---|
| author |
Köbel, Martin Kalloger, Steve E. Lee, Sandra Duggan, Máire A. Kelemen, Linda E. Prentice, Leah Kalli, Kimberly R. Fridley, Brooke L. Visscher, Daniel W. Keeney, Gary L. Vierkant, Robert A. Cunningham, Julie M. Chow, Christine Ness, Roberta B. Moysich, Kirsten Edwards, Robert Modugno, Francesmary Bunker, Clareann Wozniak, Eva L. Benjamin, Elizabeth Gayther, Simon A. Gentry-Maharaj, Aleksandra Menon, Usha Gilks, C. Blake Huntsman, David G. Ramus, Susan J. Goode, Ellen L. |
| spellingShingle |
Köbel, Martin Kalloger, Steve E. Lee, Sandra Duggan, Máire A. Kelemen, Linda E. Prentice, Leah Kalli, Kimberly R. Fridley, Brooke L. Visscher, Daniel W. Keeney, Gary L. Vierkant, Robert A. Cunningham, Julie M. Chow, Christine Ness, Roberta B. Moysich, Kirsten Edwards, Robert Modugno, Francesmary Bunker, Clareann Wozniak, Eva L. Benjamin, Elizabeth Gayther, Simon A. Gentry-Maharaj, Aleksandra Menon, Usha Gilks, C. Blake Huntsman, David G. Ramus, Susan J. Goode, Ellen L. Cancer Epidemiology, Biomarkers & Prevention Biomarker-Based Ovarian Carcinoma Typing: A Histologic Investigation in the Ovarian Tumor Tissue Analysis Consortium Oncology Epidemiology |
| author_sort |
köbel, martin |
| spelling |
Köbel, Martin Kalloger, Steve E. Lee, Sandra Duggan, Máire A. Kelemen, Linda E. Prentice, Leah Kalli, Kimberly R. Fridley, Brooke L. Visscher, Daniel W. Keeney, Gary L. Vierkant, Robert A. Cunningham, Julie M. Chow, Christine Ness, Roberta B. Moysich, Kirsten Edwards, Robert Modugno, Francesmary Bunker, Clareann Wozniak, Eva L. Benjamin, Elizabeth Gayther, Simon A. Gentry-Maharaj, Aleksandra Menon, Usha Gilks, C. Blake Huntsman, David G. Ramus, Susan J. Goode, Ellen L. 1055-9965 1538-7755 American Association for Cancer Research (AACR) Oncology Epidemiology http://dx.doi.org/10.1158/1055-9965.epi-13-0391 <jats:title>Abstract</jats:title> <jats:p>Background: Ovarian carcinoma is composed of five major histologic types, which associate with outcome and predict therapeutic response. Our aim was to evaluate histologic type assessments across the centers participating in the Ovarian Tumor Tissue Analysis (OTTA) consortium using an immunohistochemical (IHC) prediction model.</jats:p> <jats:p>Methods: Tissue microarrays (TMA) and clinical data were available for 524 pathologically confirmed ovarian carcinomas. Centralized IHC was conducted for ARID1A, CDKN2A, DKK1, HNF1B, MDM2, PGR, TP53, TFF3, VIM, and WT1, and three histologic type assessments were compared: the original pathologic type, an IHC-based calculated type (termed TB_COSPv2), and a WT1-assisted TMA core review.</jats:p> <jats:p>Results: The concordance between TB_COSPv2 type and original type was 73%. Applying WT1-assisted core review, the remaining 27% discordant cases subdivided into unclassifiable (6%), TB_COSPv2 error (6%), and original type error (15%). The largest discordant subgroup was classified as endometrioid carcinoma by original type and as high-grade serous carcinoma (HGSC) by TB_COSPv2. When TB_COSPv2 classification was used, the difference in overall survival of endometrioid carcinoma compared with HGSC became significant [RR 0.60; 95% confidence interval (CI), 0.37–0.93; P = 0.021], consistent with previous reports. In addition, 71 cases with unclear original type could be histologically classified by TB_COSPv2.</jats:p> <jats:p>Conclusions: Research cohorts, particularly those across different centers within consortia, show significant variability in original histologic type diagnosis. Our IHC-based reclassification produced more homogeneous types with respect to outcome than original type.</jats:p> <jats:p>Impact: Biomarker-based classification of ovarian carcinomas is feasible, improves comparability of results across research studies, and can reclassify cases which lack reliable original pathology. Cancer Epidemiol Biomarkers Prev; 22(10); 1677–86. ©2013 AACR.</jats:p> Biomarker-Based Ovarian Carcinoma Typing: A Histologic Investigation in the Ovarian Tumor Tissue Analysis Consortium Cancer Epidemiology, Biomarkers & Prevention |
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American Association for Cancer Research (AACR), 2013 |
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American Association for Cancer Research (AACR), 2013 |
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1055-9965 1538-7755 |
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2013 |
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American Association for Cancer Research (AACR) |
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Cancer Epidemiology, Biomarkers & Prevention |
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| title |
Biomarker-Based Ovarian Carcinoma Typing: A Histologic Investigation in the Ovarian Tumor Tissue Analysis Consortium |
| title_unstemmed |
Biomarker-Based Ovarian Carcinoma Typing: A Histologic Investigation in the Ovarian Tumor Tissue Analysis Consortium |
| title_full |
Biomarker-Based Ovarian Carcinoma Typing: A Histologic Investigation in the Ovarian Tumor Tissue Analysis Consortium |
| title_fullStr |
Biomarker-Based Ovarian Carcinoma Typing: A Histologic Investigation in the Ovarian Tumor Tissue Analysis Consortium |
| title_full_unstemmed |
Biomarker-Based Ovarian Carcinoma Typing: A Histologic Investigation in the Ovarian Tumor Tissue Analysis Consortium |
| title_short |
Biomarker-Based Ovarian Carcinoma Typing: A Histologic Investigation in the Ovarian Tumor Tissue Analysis Consortium |
| title_sort |
biomarker-based ovarian carcinoma typing: a histologic investigation in the ovarian tumor tissue analysis consortium |
| topic |
Oncology Epidemiology |
| url |
http://dx.doi.org/10.1158/1055-9965.epi-13-0391 |
| publishDate |
2013 |
| physical |
1677-1686 |
| description |
<jats:title>Abstract</jats:title>
<jats:p>Background: Ovarian carcinoma is composed of five major histologic types, which associate with outcome and predict therapeutic response. Our aim was to evaluate histologic type assessments across the centers participating in the Ovarian Tumor Tissue Analysis (OTTA) consortium using an immunohistochemical (IHC) prediction model.</jats:p>
<jats:p>Methods: Tissue microarrays (TMA) and clinical data were available for 524 pathologically confirmed ovarian carcinomas. Centralized IHC was conducted for ARID1A, CDKN2A, DKK1, HNF1B, MDM2, PGR, TP53, TFF3, VIM, and WT1, and three histologic type assessments were compared: the original pathologic type, an IHC-based calculated type (termed TB_COSPv2), and a WT1-assisted TMA core review.</jats:p>
<jats:p>Results: The concordance between TB_COSPv2 type and original type was 73%. Applying WT1-assisted core review, the remaining 27% discordant cases subdivided into unclassifiable (6%), TB_COSPv2 error (6%), and original type error (15%). The largest discordant subgroup was classified as endometrioid carcinoma by original type and as high-grade serous carcinoma (HGSC) by TB_COSPv2. When TB_COSPv2 classification was used, the difference in overall survival of endometrioid carcinoma compared with HGSC became significant [RR 0.60; 95% confidence interval (CI), 0.37–0.93; P = 0.021], consistent with previous reports. In addition, 71 cases with unclear original type could be histologically classified by TB_COSPv2.</jats:p>
<jats:p>Conclusions: Research cohorts, particularly those across different centers within consortia, show significant variability in original histologic type diagnosis. Our IHC-based reclassification produced more homogeneous types with respect to outcome than original type.</jats:p>
<jats:p>Impact: Biomarker-based classification of ovarian carcinomas is feasible, improves comparability of results across research studies, and can reclassify cases which lack reliable original pathology. Cancer Epidemiol Biomarkers Prev; 22(10); 1677–86. ©2013 AACR.</jats:p> |
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| author | Köbel, Martin, Kalloger, Steve E., Lee, Sandra, Duggan, Máire A., Kelemen, Linda E., Prentice, Leah, Kalli, Kimberly R., Fridley, Brooke L., Visscher, Daniel W., Keeney, Gary L., Vierkant, Robert A., Cunningham, Julie M., Chow, Christine, Ness, Roberta B., Moysich, Kirsten, Edwards, Robert, Modugno, Francesmary, Bunker, Clareann, Wozniak, Eva L., Benjamin, Elizabeth, Gayther, Simon A., Gentry-Maharaj, Aleksandra, Menon, Usha, Gilks, C. Blake, Huntsman, David G., Ramus, Susan J., Goode, Ellen L. |
| author_facet | Köbel, Martin, Kalloger, Steve E., Lee, Sandra, Duggan, Máire A., Kelemen, Linda E., Prentice, Leah, Kalli, Kimberly R., Fridley, Brooke L., Visscher, Daniel W., Keeney, Gary L., Vierkant, Robert A., Cunningham, Julie M., Chow, Christine, Ness, Roberta B., Moysich, Kirsten, Edwards, Robert, Modugno, Francesmary, Bunker, Clareann, Wozniak, Eva L., Benjamin, Elizabeth, Gayther, Simon A., Gentry-Maharaj, Aleksandra, Menon, Usha, Gilks, C. Blake, Huntsman, David G., Ramus, Susan J., Goode, Ellen L., Köbel, Martin, Kalloger, Steve E., Lee, Sandra, Duggan, Máire A., Kelemen, Linda E., Prentice, Leah, Kalli, Kimberly R., Fridley, Brooke L., Visscher, Daniel W., Keeney, Gary L., Vierkant, Robert A., Cunningham, Julie M., Chow, Christine, Ness, Roberta B., Moysich, Kirsten, Edwards, Robert, Modugno, Francesmary, Bunker, Clareann, Wozniak, Eva L., Benjamin, Elizabeth, Gayther, Simon A., Gentry-Maharaj, Aleksandra, Menon, Usha, Gilks, C. Blake, Huntsman, David G., Ramus, Susan J., Goode, Ellen L. |
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| description | <jats:title>Abstract</jats:title> <jats:p>Background: Ovarian carcinoma is composed of five major histologic types, which associate with outcome and predict therapeutic response. Our aim was to evaluate histologic type assessments across the centers participating in the Ovarian Tumor Tissue Analysis (OTTA) consortium using an immunohistochemical (IHC) prediction model.</jats:p> <jats:p>Methods: Tissue microarrays (TMA) and clinical data were available for 524 pathologically confirmed ovarian carcinomas. Centralized IHC was conducted for ARID1A, CDKN2A, DKK1, HNF1B, MDM2, PGR, TP53, TFF3, VIM, and WT1, and three histologic type assessments were compared: the original pathologic type, an IHC-based calculated type (termed TB_COSPv2), and a WT1-assisted TMA core review.</jats:p> <jats:p>Results: The concordance between TB_COSPv2 type and original type was 73%. Applying WT1-assisted core review, the remaining 27% discordant cases subdivided into unclassifiable (6%), TB_COSPv2 error (6%), and original type error (15%). The largest discordant subgroup was classified as endometrioid carcinoma by original type and as high-grade serous carcinoma (HGSC) by TB_COSPv2. When TB_COSPv2 classification was used, the difference in overall survival of endometrioid carcinoma compared with HGSC became significant [RR 0.60; 95% confidence interval (CI), 0.37–0.93; P = 0.021], consistent with previous reports. In addition, 71 cases with unclear original type could be histologically classified by TB_COSPv2.</jats:p> <jats:p>Conclusions: Research cohorts, particularly those across different centers within consortia, show significant variability in original histologic type diagnosis. Our IHC-based reclassification produced more homogeneous types with respect to outcome than original type.</jats:p> <jats:p>Impact: Biomarker-based classification of ovarian carcinomas is feasible, improves comparability of results across research studies, and can reclassify cases which lack reliable original pathology. Cancer Epidemiol Biomarkers Prev; 22(10); 1677–86. ©2013 AACR.</jats:p> |
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| spelling | Köbel, Martin Kalloger, Steve E. Lee, Sandra Duggan, Máire A. Kelemen, Linda E. Prentice, Leah Kalli, Kimberly R. Fridley, Brooke L. Visscher, Daniel W. Keeney, Gary L. Vierkant, Robert A. Cunningham, Julie M. Chow, Christine Ness, Roberta B. Moysich, Kirsten Edwards, Robert Modugno, Francesmary Bunker, Clareann Wozniak, Eva L. Benjamin, Elizabeth Gayther, Simon A. Gentry-Maharaj, Aleksandra Menon, Usha Gilks, C. Blake Huntsman, David G. Ramus, Susan J. Goode, Ellen L. 1055-9965 1538-7755 American Association for Cancer Research (AACR) Oncology Epidemiology http://dx.doi.org/10.1158/1055-9965.epi-13-0391 <jats:title>Abstract</jats:title> <jats:p>Background: Ovarian carcinoma is composed of five major histologic types, which associate with outcome and predict therapeutic response. Our aim was to evaluate histologic type assessments across the centers participating in the Ovarian Tumor Tissue Analysis (OTTA) consortium using an immunohistochemical (IHC) prediction model.</jats:p> <jats:p>Methods: Tissue microarrays (TMA) and clinical data were available for 524 pathologically confirmed ovarian carcinomas. Centralized IHC was conducted for ARID1A, CDKN2A, DKK1, HNF1B, MDM2, PGR, TP53, TFF3, VIM, and WT1, and three histologic type assessments were compared: the original pathologic type, an IHC-based calculated type (termed TB_COSPv2), and a WT1-assisted TMA core review.</jats:p> <jats:p>Results: The concordance between TB_COSPv2 type and original type was 73%. Applying WT1-assisted core review, the remaining 27% discordant cases subdivided into unclassifiable (6%), TB_COSPv2 error (6%), and original type error (15%). The largest discordant subgroup was classified as endometrioid carcinoma by original type and as high-grade serous carcinoma (HGSC) by TB_COSPv2. When TB_COSPv2 classification was used, the difference in overall survival of endometrioid carcinoma compared with HGSC became significant [RR 0.60; 95% confidence interval (CI), 0.37–0.93; P = 0.021], consistent with previous reports. In addition, 71 cases with unclear original type could be histologically classified by TB_COSPv2.</jats:p> <jats:p>Conclusions: Research cohorts, particularly those across different centers within consortia, show significant variability in original histologic type diagnosis. Our IHC-based reclassification produced more homogeneous types with respect to outcome than original type.</jats:p> <jats:p>Impact: Biomarker-based classification of ovarian carcinomas is feasible, improves comparability of results across research studies, and can reclassify cases which lack reliable original pathology. Cancer Epidemiol Biomarkers Prev; 22(10); 1677–86. ©2013 AACR.</jats:p> Biomarker-Based Ovarian Carcinoma Typing: A Histologic Investigation in the Ovarian Tumor Tissue Analysis Consortium Cancer Epidemiology, Biomarkers & Prevention |
| spellingShingle | Köbel, Martin, Kalloger, Steve E., Lee, Sandra, Duggan, Máire A., Kelemen, Linda E., Prentice, Leah, Kalli, Kimberly R., Fridley, Brooke L., Visscher, Daniel W., Keeney, Gary L., Vierkant, Robert A., Cunningham, Julie M., Chow, Christine, Ness, Roberta B., Moysich, Kirsten, Edwards, Robert, Modugno, Francesmary, Bunker, Clareann, Wozniak, Eva L., Benjamin, Elizabeth, Gayther, Simon A., Gentry-Maharaj, Aleksandra, Menon, Usha, Gilks, C. Blake, Huntsman, David G., Ramus, Susan J., Goode, Ellen L., Cancer Epidemiology, Biomarkers & Prevention, Biomarker-Based Ovarian Carcinoma Typing: A Histologic Investigation in the Ovarian Tumor Tissue Analysis Consortium, Oncology, Epidemiology |
| title | Biomarker-Based Ovarian Carcinoma Typing: A Histologic Investigation in the Ovarian Tumor Tissue Analysis Consortium |
| title_full | Biomarker-Based Ovarian Carcinoma Typing: A Histologic Investigation in the Ovarian Tumor Tissue Analysis Consortium |
| title_fullStr | Biomarker-Based Ovarian Carcinoma Typing: A Histologic Investigation in the Ovarian Tumor Tissue Analysis Consortium |
| title_full_unstemmed | Biomarker-Based Ovarian Carcinoma Typing: A Histologic Investigation in the Ovarian Tumor Tissue Analysis Consortium |
| title_short | Biomarker-Based Ovarian Carcinoma Typing: A Histologic Investigation in the Ovarian Tumor Tissue Analysis Consortium |
| title_sort | biomarker-based ovarian carcinoma typing: a histologic investigation in the ovarian tumor tissue analysis consortium |
| title_unstemmed | Biomarker-Based Ovarian Carcinoma Typing: A Histologic Investigation in the Ovarian Tumor Tissue Analysis Consortium |
| topic | Oncology, Epidemiology |
| url | http://dx.doi.org/10.1158/1055-9965.epi-13-0391 |