Confirmation of ProMisE: A simple, genomics-based clinical classifier for endometrial cancer

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Related collections

Most cited references 21

Record: found
Abstract: found
Article: found

Is Open Access

A clinically applicable molecular-based classification for endometrial cancers

A Talhouk, M K McConechy, Richard S Leung … (2015)

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.

0 comments Cited 265 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Classification of endometrial carcinoma: more than two types.

Rajmohan Murali, Robert A. Soslow, Britta Weigelt (2014)

Endometrial cancer is the most common gynaecological malignancy in Europe and North America. Traditional classification of endometrial carcinoma is based either on clinical and endocrine features (eg, types I and II) or on histopathological characteristics (eg, endometrioid, serous, or clear-cell adenocarcinoma). Subtypes defined by the different classification systems correlate to some extent, but there is substantial heterogeneity in biological, pathological, and molecular features within tumour types from both classification systems. In this Review we provide an overview of traditional and newer genomic classifications of endometrial cancer. We discuss how a classification system that incorporates genomic and histopathological features to define biologically and clinically relevant subsets of the disease would be useful. Such integrated classification might facilitate development of treatments tailored to specific disease subgroups and could potentially enable delivery of precision medicine to patients with endometrial cancer. Copyright © 2014 Elsevier Ltd. All rights reserved.