Confirmation of ProMisE: A simple, genomics‐based clinical classifier for endometrial cancer
BACKGROUND Classification of endometrial carcinomas (ECs) by morphologic features is irreproducible and imperfectly reflects tumor biology. The authors developed the Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE), a molecular classification system based on The Cancer Genome Atl...
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| Veröffentlicht in: | Cancer Jg. 123; H. 5; S. 802 - 813 |
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| Hauptverfasser: | , , , , , , , , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
United States
Wiley Subscription Services, Inc
01.03.2017
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| ISSN: | 0008-543X, 1097-0142 |
| Online-Zugang: | Volltext |
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| Abstract | BACKGROUND
Classification of endometrial carcinomas (ECs) by morphologic features is irreproducible and imperfectly reflects tumor biology. The authors developed the Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE), a molecular classification system based on The Cancer Genome Atlas genomic subgroups, and sought to confirm both feasibility and prognostic ability in a new, large cohort of ECs.
METHODS
Immunohistochemistry (IHC) for the presence or absence of mismatch repair (MMR) proteins (to identify MMR deficiency [MMR‐D]), sequencing for polymerase‐ɛ (POLE) exonuclease domain mutations (POLE EDMs), and IHC for tumor protein 53 (p53) (wild type vs null/missense mutations; p53 wt and p53 abn, respectively) were performed on 319 new EC samples. Subgroups were characterized and assessed relative to outcomes. The prognostic ability of ProMisE was compared with that of current risk‐stratification systems (European Society of Medical Oncology [ESMO]).
RESULTS
ProMisE decision‐tree classification achieved categorization of all cases and identified 4 prognostic subgroups with distinct overall, disease‐specific, and progression‐free survival (P < .001). Tumors with POLE EDMs had the most favorable prognosis, and those with p53 abn the worst prognosis, and separation of the 2 middle survival curves (p53 wt and MMR‐D) was observed. There were no significant differences in survival between the ESMO low‐risk and intermediate‐risk groups. ProMisE improved the ability to discriminate outcomes compared with ESMO risk stratification. There was substantial overlap (89%) between the p53 abn and high‐risk ESMO subgroups; but, otherwise, there were no predictable associations between molecular and ESMO risk groups.
CONCLUSIONS
Molecular classification of ECs can be achieved using clinically applicable methods and provides independent prognostic information beyond established clinicopathologic risk factors available at diagnosis. Consistent, biologically relevant categorization enables stratification for clinical trials and/or targeted therapy, identification of women who are at increased risk of having Lynch syndrome, and may guide clinical management. Cancer 2017;123:802–13. © 2016 American Cancer Society.
The prognostic ability of Cancer Genome Atlas–inspired, genomics‐based classification method in endometrial carcinomas is confirmed. This pragmatic system will enable more consistent categorization of tumors, stratification of clinical trials, more rapid identification of hereditary cancers, prognostic information, and potentially predictive applications to better guide clinical management.
See also pages 728–30. |
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| AbstractList | The prognostic ability of Cancer Genome Atlas–inspired, genomics‐based classification method in endometrial carcinomas is confirmed. This pragmatic system will enable more consistent categorization of tumors, stratification of clinical trials, more rapid identification of hereditary cancers, prognostic information, and potentially predictive applications to better guide clinical management.
See also pages 728–30. Classification of endometrial carcinomas (ECs) by morphologic features is irreproducible and imperfectly reflects tumor biology. The authors developed the Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE), a molecular classification system based on The Cancer Genome Atlas genomic subgroups, and sought to confirm both feasibility and prognostic ability in a new, large cohort of ECs. Immunohistochemistry (IHC) for the presence or absence of mismatch repair (MMR) proteins (to identify MMR deficiency [MMR-D]), sequencing for polymerase-ɛ (POLE) exonuclease domain mutations (POLE EDMs), and IHC for tumor protein 53 (p53) (wild type vs null/missense mutations; p53 wt and p53 abn, respectively) were performed on 319 new EC samples. Subgroups were characterized and assessed relative to outcomes. The prognostic ability of ProMisE was compared with that of current risk-stratification systems (European Society of Medical Oncology [ESMO]). ProMisE decision-tree classification achieved categorization of all cases and identified 4 prognostic subgroups with distinct overall, disease-specific, and progression-free survival (P < .001). Tumors with POLE EDMs had the most favorable prognosis, and those with p53 abn the worst prognosis, and separation of the 2 middle survival curves (p53 wt and MMR-D) was observed. There were no significant differences in survival between the ESMO low-risk and intermediate-risk groups. ProMisE improved the ability to discriminate outcomes compared with ESMO risk stratification. There was substantial overlap (89%) between the p53 abn and high-risk ESMO subgroups; but, otherwise, there were no predictable associations between molecular and ESMO risk groups. Molecular classification of ECs can be achieved using clinically applicable methods and provides independent prognostic information beyond established clinicopathologic risk factors available at diagnosis. Consistent, biologically relevant categorization enables stratification for clinical trials and/or targeted therapy, identification of women who are at increased risk of having Lynch syndrome, and may guide clinical management. Cancer 2017;123:802-13. © 2016 American Cancer Society. BACKGROUND Classification of endometrial carcinomas (ECs) by morphologic features is irreproducible and imperfectly reflects tumor biology. The authors developed the Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE), a molecular classification system based on The Cancer Genome Atlas genomic subgroups, and sought to confirm both feasibility and prognostic ability in a new, large cohort of ECs. METHODS Immunohistochemistry (IHC) for the presence or absence of mismatch repair (MMR) proteins (to identify MMR deficiency [MMR-D]), sequencing for polymerase- (POLE) exonuclease domain mutations (POLE EDMs), and IHC for tumor protein 53 (p53) (wild type vs null/missense mutations; p53 wt and p53 abn, respectively) were performed on 319 new EC samples. Subgroups were characterized and assessed relative to outcomes. The prognostic ability of ProMisE was compared with that of current risk-stratification systems (European Society of Medical Oncology [ESMO]). RESULTS ProMisE decision-tree classification achieved categorization of all cases and identified 4 prognostic subgroups with distinct overall, disease-specific, and progression-free survival (P<.001). Tumors with POLE EDMs had the most favorable prognosis, and those with p53 abn the worst prognosis, and separation of the 2 middle survival curves (p53 wt and MMR-D) was observed. There were no significant differences in survival between the ESMO low-risk and intermediate-risk groups. ProMisE improved the ability to discriminate outcomes compared with ESMO risk stratification. There was substantial overlap (89%) between the p53 abn and high-risk ESMO subgroups; but, otherwise, there were no predictable associations between molecular and ESMO risk groups. CONCLUSIONS Molecular classification of ECs can be achieved using clinically applicable methods and provides independent prognostic information beyond established clinicopathologic risk factors available at diagnosis. Consistent, biologically relevant categorization enables stratification for clinical trials and/or targeted therapy, identification of women who are at increased risk of having Lynch syndrome, and may guide clinical management. Cancer 2017; 123:802-13. copyright 2016 American Cancer Society. The prognostic ability of Cancer Genome Atlas-inspired, genomics-based classification method in endometrial carcinomas is confirmed. This pragmatic system will enable more consistent categorization of tumors, stratification of clinical trials, more rapid identification of hereditary cancers, prognostic information, and potentially predictive applications to better guide clinical management. See also pages 728-30. BACKGROUND Classification of endometrial carcinomas (ECs) by morphologic features is irreproducible and imperfectly reflects tumor biology. The authors developed the Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE), a molecular classification system based on The Cancer Genome Atlas genomic subgroups, and sought to confirm both feasibility and prognostic ability in a new, large cohort of ECs. METHODS Immunohistochemistry (IHC) for the presence or absence of mismatch repair (MMR) proteins (to identify MMR deficiency [MMR‐D]), sequencing for polymerase‐ɛ (POLE) exonuclease domain mutations (POLE EDMs), and IHC for tumor protein 53 (p53) (wild type vs null/missense mutations; p53 wt and p53 abn, respectively) were performed on 319 new EC samples. Subgroups were characterized and assessed relative to outcomes. The prognostic ability of ProMisE was compared with that of current risk‐stratification systems (European Society of Medical Oncology [ESMO]). RESULTS ProMisE decision‐tree classification achieved categorization of all cases and identified 4 prognostic subgroups with distinct overall, disease‐specific, and progression‐free survival (P < .001). Tumors with POLE EDMs had the most favorable prognosis, and those with p53 abn the worst prognosis, and separation of the 2 middle survival curves (p53 wt and MMR‐D) was observed. There were no significant differences in survival between the ESMO low‐risk and intermediate‐risk groups. ProMisE improved the ability to discriminate outcomes compared with ESMO risk stratification. There was substantial overlap (89%) between the p53 abn and high‐risk ESMO subgroups; but, otherwise, there were no predictable associations between molecular and ESMO risk groups. CONCLUSIONS Molecular classification of ECs can be achieved using clinically applicable methods and provides independent prognostic information beyond established clinicopathologic risk factors available at diagnosis. Consistent, biologically relevant categorization enables stratification for clinical trials and/or targeted therapy, identification of women who are at increased risk of having Lynch syndrome, and may guide clinical management. Cancer 2017;123:802–13. © 2016 American Cancer Society. The prognostic ability of Cancer Genome Atlas–inspired, genomics‐based classification method in endometrial carcinomas is confirmed. This pragmatic system will enable more consistent categorization of tumors, stratification of clinical trials, more rapid identification of hereditary cancers, prognostic information, and potentially predictive applications to better guide clinical management. See also pages 728–30. BACKGROUNDClassification of endometrial carcinomas (ECs) by morphologic features is irreproducible and imperfectly reflects tumor biology. The authors developed the Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE), a molecular classification system based on The Cancer Genome Atlas genomic subgroups, and sought to confirm both feasibility and prognostic ability in a new, large cohort of ECs.METHODSImmunohistochemistry (IHC) for the presence or absence of mismatch repair (MMR) proteins (to identify MMR deficiency [MMR‐D]), sequencing for polymerase‐ɛ (POLE) exonuclease domain mutations (POLE EDMs), and IHC for tumor protein 53 (p53) (wild type vs null/missense mutations; p53 wt and p53 abn, respectively) were performed on 319 new EC samples. Subgroups were characterized and assessed relative to outcomes. The prognostic ability of ProMisE was compared with that of current risk‐stratification systems (European Society of Medical Oncology [ESMO]).RESULTSProMisE decision‐tree classification achieved categorization of all cases and identified 4 prognostic subgroups with distinct overall, disease‐specific, and progression‐free survival (P < .001). Tumors with POLE EDMs had the most favorable prognosis, and those with p53 abn the worst prognosis, and separation of the 2 middle survival curves (p53 wt and MMR‐D) was observed. There were no significant differences in survival between the ESMO low‐risk and intermediate‐risk groups. ProMisE improved the ability to discriminate outcomes compared with ESMO risk stratification. There was substantial overlap (89%) between the p53 abn and high‐risk ESMO subgroups; but, otherwise, there were no predictable associations between molecular and ESMO risk groups.CONCLUSIONSMolecular classification of ECs can be achieved using clinically applicable methods and provides independent prognostic information beyond established clinicopathologic risk factors available at diagnosis. Consistent, biologically relevant categorization enables stratification for clinical trials and/or targeted therapy, identification of women who are at increased risk of having Lynch syndrome, and may guide clinical management. Cancer 2017;123:802–13. © 2016 American Cancer Society. |
| Author | Karnezis, Anthony N. Leung, Samuel Anglesio, Michael Yang, Winnie Pike, Judith Huntsman, David G. Boyd, Niki Kwon, Janice S. Senz, Janine Talhouk, Aline McAlpine, Jessica N. McConechy, Melissa K. Lum, Amy Gilks, C. Blake |
| Author_xml | – sequence: 1 givenname: Aline surname: Talhouk fullname: Talhouk, Aline organization: University of British Columbia and British Columbia Cancer Agency – sequence: 2 givenname: Melissa K. surname: McConechy fullname: McConechy, Melissa K. organization: McGill University, Research Institute of the McGill University Health Network – sequence: 3 givenname: Samuel surname: Leung fullname: Leung, Samuel organization: Department of Pathology and Laboratory Medicine, University of British Columbia – sequence: 4 givenname: Winnie surname: Yang fullname: Yang, Winnie organization: University of British Columbia and British Columbia Cancer Agency – sequence: 5 givenname: Amy surname: Lum fullname: Lum, Amy organization: University of British Columbia and British Columbia Cancer Agency – sequence: 6 givenname: Janine surname: Senz fullname: Senz, Janine organization: University of British Columbia and British Columbia Cancer Agency – sequence: 7 givenname: Niki surname: Boyd fullname: Boyd, Niki organization: University of British Columbia and British Columbia Cancer Agency – sequence: 8 givenname: Judith surname: Pike fullname: Pike, Judith organization: Division of Gynecologic Oncology, University of British Columbia – sequence: 9 givenname: Michael surname: Anglesio fullname: Anglesio, Michael organization: University of British Columbia and British Columbia Cancer Agency – sequence: 10 givenname: Janice S. surname: Kwon fullname: Kwon, Janice S. organization: Division of Gynecologic Oncology, University of British Columbia – sequence: 11 givenname: Anthony N. surname: Karnezis fullname: Karnezis, Anthony N. organization: University of British Columbia and British Columbia Cancer Agency – sequence: 12 givenname: David G. surname: Huntsman fullname: Huntsman, David G. organization: University of British Columbia and British Columbia Cancer Agency – sequence: 13 givenname: C. Blake surname: Gilks fullname: Gilks, C. Blake organization: University of British Columbia and Vancouver General Hospital – sequence: 14 givenname: Jessica N. surname: McAlpine fullname: McAlpine, Jessica N. email: jessica.mcalpine@vch.ca organization: Division of Gynecologic Oncology, University of British Columbia |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/28061006$$D View this record in MEDLINE/PubMed |
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| References | 2015; 1 1995; 51 2013; 26 2012 2013; 24 2013; 63 2016; 387 2016; 143 2016; 16 2009; 114 2014; 134 2015; 372 2015; 194 2013; 37 2015; 28 2015; 137 2015; 113 2010; 29 2015; 112 2013; 497 2014; 15 2011; 21 2014; 57 2014 2016; 23 2016; 22 2001; 54 e_1_2_8_28_1 e_1_2_8_29_1 e_1_2_8_24_1 e_1_2_8_25_1 e_1_2_8_26_1 e_1_2_8_27_1 e_1_2_8_2_1 e_1_2_8_5_1 e_1_2_8_4_1 e_1_2_8_7_1 e_1_2_8_6_1 e_1_2_8_9_1 e_1_2_8_8_1 Canadian Cancer Society's Advisory Committee on Cancer Statistics (e_1_2_8_3_1) 2014 e_1_2_8_20_1 e_1_2_8_21_1 e_1_2_8_22_1 e_1_2_8_23_1 e_1_2_8_17_1 e_1_2_8_18_1 e_1_2_8_19_1 e_1_2_8_13_1 e_1_2_8_14_1 e_1_2_8_15_1 e_1_2_8_16_1 e_1_2_8_32_1 e_1_2_8_10_1 e_1_2_8_31_1 e_1_2_8_11_1 e_1_2_8_12_1 e_1_2_8_33_1 e_1_2_8_30_1 28061001 - Cancer. 2017 Mar 1;123(5):728-730 |
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Classification of endometrial carcinomas (ECs) by morphologic features is irreproducible and imperfectly reflects tumor biology. The authors... The prognostic ability of Cancer Genome Atlas–inspired, genomics‐based classification method in endometrial carcinomas is confirmed. This pragmatic system will... Classification of endometrial carcinomas (ECs) by morphologic features is irreproducible and imperfectly reflects tumor biology. The authors developed the... BACKGROUNDClassification of endometrial carcinomas (ECs) by morphologic features is irreproducible and imperfectly reflects tumor biology. The authors... BACKGROUND Classification of endometrial carcinomas (ECs) by morphologic features is irreproducible and imperfectly reflects tumor biology. The authors... |
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| SubjectTerms | Adult Aged Biomarkers, Tumor - genetics Cancer Carcinoma Classification Classifiers Clinical trials Colorectal cancer Disease-Free Survival DNA Mismatch Repair - genetics DNA Polymerase II - genetics Endometrial cancer endometrial carcinoma Endometrial Neoplasms - classification Endometrial Neoplasms - genetics Endometrial Neoplasms - pathology Endometrium Exonuclease Feasibility studies Female Genetic disorders Genomes Genomics Health risks histotype Humans Immunohistochemistry Medical prognosis Medical research Microsatellite Instability Mismatch repair Missense mutation Mutation Mutation, Missense Neoplasm Staging Oncology p53 p53 Protein Pathology, Molecular Poly-ADP-Ribose Binding Proteins polymerase‐ɛ (POLE) Prognosis prognostic Proteins Risk analysis Risk Factors Risk groups Risk management risk‐stratification system Subgroups Survival The Cancer Genome Atlas (TCGA) Tumor Suppressor Protein p53 - genetics Tumors Uterine cancer |
| Title | Confirmation of ProMisE: A simple, genomics‐based clinical classifier for endometrial cancer |
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