Biomarker-based ovarian carcinoma typing

A histologic investigation in the ovarian tumor tissue analysis consortium

Martin Köbel, Steve E. Kalloger, Sandra Lee, Maire A. Duggan, Linda E. Kelemen, Leah Prentice, Kimberly R. Kalli, Brooke L. Fridley, Daniel W Visscher, Gary Keeney, Robert A. Vierkant, Julie M Cunningham, Christine Chow, Roberta B. Ness, Kirsten Moysich, Robert Edwards, Francesmary Modugno, Clareann Bunker, Eva L. Wozniak, Elizabeth Benjamin & 7 others Simon A. Gayther, Aleksandra Gentry-Maharaj, Usha Menon, C. Blake Gilks, David G. Huntsman, Susan J. Ramus, Ellen L Goode

Research output: Contribution to journalArticle

45 Citations (Scopus)

Abstract

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. 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. 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. 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. 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.

Original languageEnglish (US)
Pages (from-to)1677-1686
Number of pages10
JournalCancer Epidemiology Biomarkers and Prevention
Volume22
Issue number10
DOIs
StatePublished - Oct 2013

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Biomarkers
Carcinoma
Endometrioid Carcinoma
Neoplasms
Research
Confidence Intervals
Pathology
Therapeutics

ASJC Scopus subject areas

  • Epidemiology
  • Oncology

Cite this

Biomarker-based ovarian carcinoma typing : A histologic investigation in the ovarian tumor tissue analysis consortium. / Köbel, Martin; Kalloger, Steve E.; Lee, Sandra; Duggan, Maire A.; Kelemen, Linda E.; Prentice, Leah; Kalli, Kimberly R.; Fridley, Brooke L.; Visscher, Daniel W; Keeney, Gary; 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.

In: Cancer Epidemiology Biomarkers and Prevention, Vol. 22, No. 10, 10.2013, p. 1677-1686.

Research output: Contribution to journalArticle

Köbel, M, Kalloger, SE, Lee, S, Duggan, MA, Kelemen, LE, Prentice, L, Kalli, KR, Fridley, BL, Visscher, DW, Keeney, G, Vierkant, RA, Cunningham, JM, Chow, C, Ness, RB, Moysich, K, Edwards, R, Modugno, F, Bunker, C, Wozniak, EL, Benjamin, E, Gayther, SA, Gentry-Maharaj, A, Menon, U, Gilks, CB, Huntsman, DG, Ramus, SJ & Goode, EL 2013, 'Biomarker-based ovarian carcinoma typing: A histologic investigation in the ovarian tumor tissue analysis consortium', Cancer Epidemiology Biomarkers and Prevention, vol. 22, no. 10, pp. 1677-1686. https://doi.org/10.1158/1055-9965.EPI-13-0391
Köbel, Martin ; Kalloger, Steve E. ; Lee, Sandra ; Duggan, Maire A. ; Kelemen, Linda E. ; Prentice, Leah ; Kalli, Kimberly R. ; Fridley, Brooke L. ; Visscher, Daniel W ; Keeney, Gary ; 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. / Biomarker-based ovarian carcinoma typing : A histologic investigation in the ovarian tumor tissue analysis consortium. In: Cancer Epidemiology Biomarkers and Prevention. 2013 ; Vol. 22, No. 10. pp. 1677-1686.
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abstract = "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. 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. 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. 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. 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.",
author = "Martin K{\"o}bel and Kalloger, {Steve E.} and Sandra Lee and Duggan, {Maire A.} and Kelemen, {Linda E.} and Leah Prentice and Kalli, {Kimberly R.} and Fridley, {Brooke L.} and Visscher, {Daniel W} and Gary Keeney and Vierkant, {Robert A.} and Cunningham, {Julie M} and Christine Chow and Ness, {Roberta B.} and Kirsten Moysich and Robert Edwards and Francesmary Modugno and Clareann Bunker and Wozniak, {Eva L.} and Elizabeth Benjamin and Gayther, {Simon A.} and Aleksandra Gentry-Maharaj and Usha Menon and Gilks, {C. Blake} and Huntsman, {David G.} and Ramus, {Susan J.} and Goode, {Ellen L}",
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T1 - Biomarker-based ovarian carcinoma typing

T2 - A histologic investigation in the ovarian tumor tissue analysis consortium

AU - Köbel, Martin

AU - Kalloger, Steve E.

AU - Lee, Sandra

AU - Duggan, Maire A.

AU - Kelemen, Linda E.

AU - Prentice, Leah

AU - Kalli, Kimberly R.

AU - Fridley, Brooke L.

AU - Visscher, Daniel W

AU - Keeney, Gary

AU - Vierkant, Robert A.

AU - Cunningham, Julie M

AU - Chow, Christine

AU - Ness, Roberta B.

AU - Moysich, Kirsten

AU - Edwards, Robert

AU - Modugno, Francesmary

AU - Bunker, Clareann

AU - Wozniak, Eva L.

AU - Benjamin, Elizabeth

AU - Gayther, Simon A.

AU - Gentry-Maharaj, Aleksandra

AU - Menon, Usha

AU - Gilks, C. Blake

AU - Huntsman, David G.

AU - Ramus, Susan J.

AU - Goode, Ellen L

PY - 2013/10

Y1 - 2013/10

N2 - 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. 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. 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. 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. 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.

AB - 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. 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. 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. 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. 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.

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