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A clinically applicable molecular-based classification for endometrial cancers.
Br J Cancer. 2015 Jul 14; 113(2):299-310.BJ

Abstract

BACKGROUND

Classification of endometrial carcinomas (ECs) by morphologic features is inconsistent, and yields limited prognostic and predictive information. A new system for classification based on the molecular categories identified in The Cancer Genome Atlas is proposed.

METHODS

Genomic data from the Cancer Genome Atlas (TCGA) support classification of endometrial carcinomas into four prognostically significant subgroups; we used the TCGA data set to develop surrogate assays that could replicate the TCGA classification, but without the need for the labor-intensive and cost-prohibitive genomic methodology. Combinations of the most relevant assays were carried forward and tested on a new independent cohort of 152 endometrial carcinoma cases, and molecular vs clinical risk group stratification was compared.

RESULTS

Replication of TCGA survival curves was achieved with statistical significance using multiple different molecular classification models (16 total tested). Internal validation supported carrying forward a classifier based on the following components: mismatch repair protein immunohistochemistry, POLE mutational analysis and p53 immunohistochemistry as a surrogate for 'copy-number' status. The proposed molecular classifier was associated with clinical outcomes, as was stage, grade, lymph-vascular space invasion, nodal involvement and adjuvant treatment. In multivariable analysis both molecular classification and clinical risk groups were associated with outcomes, but differed greatly in composition of cases within each category, with half of POLE and mismatch repair loss subgroups residing within the clinically defined 'high-risk' group. Combining the molecular classifier with clinicopathologic features or risk groups provided the highest C-index for discrimination of outcome survival curves.

CONCLUSIONS

Molecular classification of ECs can be achieved using clinically applicable methods on formalin-fixed paraffin-embedded samples, and provides independent prognostic information beyond established risk factors. This pragmatic molecular classification tool has potential to be used routinely in guiding treatment for individuals with endometrial carcinoma and in stratifying cases in future clinical trials.

Authors+Show Affiliations

Department of Pathology and Laboratory Medicine, University of British Columbia and BC Cancer Agency, 509-2660 Oak Street, Vancouver, British Columbia, Canada V6H 3Z6.Department of Pathology and Laboratory Medicine, University of British Columbia and BC Cancer Agency, 509-2660 Oak Street, Vancouver, British Columbia, Canada V6H 3Z6.Genetic Pathology Evaluation Centre, Department of Pathology and Laboratory Medicine, University of British Columbia, 509-2660 Oak Street, Vancouver, British Columbia, Canada V6H 3Z6.1] Department of Pathology and Laboratory Medicine, University of British Columbia and BC Cancer Agency, 509-2660 Oak Street, Vancouver, British Columbia, Canada V6H 3Z6 [2] Department of Laboratory Services, Royal Victoria Regional Health Centre, 201 Georgian Drive, Barrie, Ontario, Canada L4M 6M2.Department of Gynecology and Obstetrics, Division of Gynecologic Oncology, University of British Columbia, 2775 Laurel St. 6th Floor, Vancouver, British Columbia, Canada V5Z 1M9.Department of Pathology and Laboratory Medicine, University of British Columbia and BC Cancer Agency, 509-2660 Oak Street, Vancouver, British Columbia, Canada V6H 3Z6.Department of Pathology and Laboratory Medicine, University of British Columbia and BC Cancer Agency, 509-2660 Oak Street, Vancouver, British Columbia, Canada V6H 3Z6.Department of Pathology and Laboratory Medicine, University of British Columbia and BC Cancer Agency, 509-2660 Oak Street, Vancouver, British Columbia, Canada V6H 3Z6.Department of Pathology and Laboratory Medicine, University of British Columbia and BC Cancer Agency, 509-2660 Oak Street, Vancouver, British Columbia, Canada V6H 3Z6.Department of Pathology and Laboratory Medicine, University of British Columbia and BC Cancer Agency, 509-2660 Oak Street, Vancouver, British Columbia, Canada V6H 3Z6.Department of Pathology and Laboratory Medicine, University of British Columbia and BC Cancer Agency, 509-2660 Oak Street, Vancouver, British Columbia, Canada V6H 3Z6.Department of Pathology and Laboratory Medicine, University of British Columbia and BC Cancer Agency, 509-2660 Oak Street, Vancouver, British Columbia, Canada V6H 3Z6.Department of Gynecology and Obstetrics, Division of Gynecologic Oncology, University of British Columbia, 2775 Laurel St. 6th Floor, Vancouver, British Columbia, Canada V5Z 1M9.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

26172027

Citation

Talhouk, A, et al. "A Clinically Applicable Molecular-based Classification for Endometrial Cancers." British Journal of Cancer, vol. 113, no. 2, 2015, pp. 299-310.
Talhouk A, McConechy MK, Leung S, et al. A clinically applicable molecular-based classification for endometrial cancers. Br J Cancer. 2015;113(2):299-310.
Talhouk, A., McConechy, M. K., Leung, S., Li-Chang, H. H., Kwon, J. S., Melnyk, N., Yang, W., Senz, J., Boyd, N., Karnezis, A. N., Huntsman, D. G., Gilks, C. B., & McAlpine, J. N. (2015). A clinically applicable molecular-based classification for endometrial cancers. British Journal of Cancer, 113(2), 299-310. https://doi.org/10.1038/bjc.2015.190
Talhouk A, et al. A Clinically Applicable Molecular-based Classification for Endometrial Cancers. Br J Cancer. 2015 Jul 14;113(2):299-310. PubMed PMID: 26172027.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - A clinically applicable molecular-based classification for endometrial cancers. AU - Talhouk,A, AU - McConechy,M K, AU - Leung,S, AU - Li-Chang,H H, AU - Kwon,J S, AU - Melnyk,N, AU - Yang,W, AU - Senz,J, AU - Boyd,N, AU - Karnezis,A N, AU - Huntsman,D G, AU - Gilks,C B, AU - McAlpine,J N, Y1 - 2015/06/30/ PY - 2015/02/25/received PY - 2015/04/14/revised PY - 2015/04/29/accepted PY - 2015/7/15/entrez PY - 2015/7/15/pubmed PY - 2015/10/1/medline SP - 299 EP - 310 JF - British journal of cancer JO - Br J Cancer VL - 113 IS - 2 N2 - BACKGROUND: Classification of endometrial carcinomas (ECs) by morphologic features is inconsistent, and yields limited prognostic and predictive information. A new system for classification based on the molecular categories identified in The Cancer Genome Atlas is proposed. METHODS: Genomic data from the Cancer Genome Atlas (TCGA) support classification of endometrial carcinomas into four prognostically significant subgroups; we used the TCGA data set to develop surrogate assays that could replicate the TCGA classification, but without the need for the labor-intensive and cost-prohibitive genomic methodology. Combinations of the most relevant assays were carried forward and tested on a new independent cohort of 152 endometrial carcinoma cases, and molecular vs clinical risk group stratification was compared. RESULTS: Replication of TCGA survival curves was achieved with statistical significance using multiple different molecular classification models (16 total tested). Internal validation supported carrying forward a classifier based on the following components: mismatch repair protein immunohistochemistry, POLE mutational analysis and p53 immunohistochemistry as a surrogate for 'copy-number' status. The proposed molecular classifier was associated with clinical outcomes, as was stage, grade, lymph-vascular space invasion, nodal involvement and adjuvant treatment. In multivariable analysis both molecular classification and clinical risk groups were associated with outcomes, but differed greatly in composition of cases within each category, with half of POLE and mismatch repair loss subgroups residing within the clinically defined 'high-risk' group. Combining the molecular classifier with clinicopathologic features or risk groups provided the highest C-index for discrimination of outcome survival curves. CONCLUSIONS: Molecular classification of ECs can be achieved using clinically applicable methods on formalin-fixed paraffin-embedded samples, and provides independent prognostic information beyond established risk factors. This pragmatic molecular classification tool has potential to be used routinely in guiding treatment for individuals with endometrial carcinoma and in stratifying cases in future clinical trials. SN - 1532-1827 UR - https://www.unboundmedicine.com/medline/citation/26172027/A_clinically_applicable_molecular_based_classification_for_endometrial_cancers_ L2 - https://doi.org/10.1038/bjc.2015.190 DB - PRIME DP - Unbound Medicine ER -