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A clinically applicable molecular-based classification for endometrial cancers
by
McConechy, M K
, Kwon, J S
, McAlpine, J N
, Karnezis, A N
, Talhouk, A
, Yang, W
, Li-Chang, H H
, Melnyk, N
, Leung, S
, Senz, J
, Huntsman, D G
, Gilks, C B
, Boyd, N
in
Aged
/ Biomedical and Life Sciences
/ Biomedicine
/ Cancer Research
/ DNA Polymerase II - genetics
/ Drug Resistance
/ Endometrial Neoplasms - classification
/ Endometrial Neoplasms - genetics
/ Endometrial Neoplasms - mortality
/ Endometrial Neoplasms - pathology
/ Epidemiology
/ Female
/ Genes, p53
/ Humans
/ Middle Aged
/ Molecular Diagnostics
/ Molecular Medicine
/ Mutation
/ Oncology
/ Poly-ADP-Ribose Binding Proteins
/ PTEN Phosphohydrolase - genetics
/ Retrospective Studies
2015
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A clinically applicable molecular-based classification for endometrial cancers
by
McConechy, M K
, Kwon, J S
, McAlpine, J N
, Karnezis, A N
, Talhouk, A
, Yang, W
, Li-Chang, H H
, Melnyk, N
, Leung, S
, Senz, J
, Huntsman, D G
, Gilks, C B
, Boyd, N
in
Aged
/ Biomedical and Life Sciences
/ Biomedicine
/ Cancer Research
/ DNA Polymerase II - genetics
/ Drug Resistance
/ Endometrial Neoplasms - classification
/ Endometrial Neoplasms - genetics
/ Endometrial Neoplasms - mortality
/ Endometrial Neoplasms - pathology
/ Epidemiology
/ Female
/ Genes, p53
/ Humans
/ Middle Aged
/ Molecular Diagnostics
/ Molecular Medicine
/ Mutation
/ Oncology
/ Poly-ADP-Ribose Binding Proteins
/ PTEN Phosphohydrolase - genetics
/ Retrospective Studies
2015
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A clinically applicable molecular-based classification for endometrial cancers
by
McConechy, M K
, Kwon, J S
, McAlpine, J N
, Karnezis, A N
, Talhouk, A
, Yang, W
, Li-Chang, H H
, Melnyk, N
, Leung, S
, Senz, J
, Huntsman, D G
, Gilks, C B
, Boyd, N
in
Aged
/ Biomedical and Life Sciences
/ Biomedicine
/ Cancer Research
/ DNA Polymerase II - genetics
/ Drug Resistance
/ Endometrial Neoplasms - classification
/ Endometrial Neoplasms - genetics
/ Endometrial Neoplasms - mortality
/ Endometrial Neoplasms - pathology
/ Epidemiology
/ Female
/ Genes, p53
/ Humans
/ Middle Aged
/ Molecular Diagnostics
/ Molecular Medicine
/ Mutation
/ Oncology
/ Poly-ADP-Ribose Binding Proteins
/ PTEN Phosphohydrolase - genetics
/ Retrospective Studies
2015
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A clinically applicable molecular-based classification for endometrial cancers
Journal Article
A clinically applicable molecular-based classification for endometrial cancers
2015
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Overview
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.
Publisher
Nature Publishing Group UK,Nature Publishing Group
Subject
/ Biomedical and Life Sciences
/ DNA Polymerase II - genetics
/ Endometrial Neoplasms - classification
/ Endometrial Neoplasms - genetics
/ Endometrial Neoplasms - mortality
/ Endometrial Neoplasms - pathology
/ Female
/ Humans
/ Mutation
/ Oncology
/ Poly-ADP-Ribose Binding Proteins
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