Dataset Information

A clinically applicable molecular-based classification for endometrial cancers.

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.

SUBMITTER: Talhouk A

PROVIDER: S-EPMC4506381 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

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Publications

A clinically applicable molecular-based classification for endometrial cancers.

Talhouk A A McConechy M K MK Leung S S Li-Chang H H HH Kwon J S JS Melnyk N N Yang W W Senz J J Boyd N N Karnezis A N AN Huntsman D G DG Gilks C B CB McAlpine J N JN

British journal of cancer 20150630 2

<h4>Background</h4>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.<h4>Methods</h4>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 tha ...[more]

PMID: 26172027

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Project description:Our aim was to investigate whether molecular classification can be used to refine prognosis in grade 3 endometrial endometrioid carcinomas (EECs). Grade 3 EECs were classified into 4 subgroups: p53 abnormal, based on mutant-like immunostaining (p53abn); MMR deficient, based on loss of mismatch repair protein expression (MMRd); presence of POLE exonuclease domain hotspot mutation (POLE); no specific molecular profile (NSMP), in which none of these aberrations were present. Overall survival (OS) and recurrence-free survival (RFS) rates were compared using the Kaplan-Meier method (Log-rank test) and univariable and multivariable Cox proportional hazard models. In total, 381 patients were included. The median age was 66 years (range, 33 to 96?y). Federation Internationale de Gynecologie et d'Obstetrique stages (2009) were as follows: IA, 171 (44.9%); IB, 120 (31.5%); II, 24 (6.3%); III, 50 (13.1%); IV, 11 (2.9%). There were 49 (12.9%) POLE, 79 (20.7%) p53abn, 115 (30.2%) NSMP, and 138 (36.2%) MMRd tumors. Median follow-up of patients was 6.1 years (range, 0.2 to 17.0?y). Compared to patients with NSMP, patients with POLE mutant grade 3 EEC (OS: hazard ratio [HR], 0.36 [95% confidence interval, 0.18-0.70]; P=0.003; RFS: HR, 0.17 [0.05-0.54]; P=0.003) had a significantly better prognosis; patients with p53abn tumors had a significantly worse RFS (HR, 1.73 [1.09-2.74]; P=0.021); patients with MMRd tumors showed a trend toward better RFS. Estimated 5-year OS rates were as follows: POLE 89%, MMRd 75%, NSMP 69%, p53abn 55% (Log rank P=0.001). Five-year RFS rates were as follows: POLE 96%, MMRd 77%, NSMP 64%, p53abn 47% (P=0.000001), respectively. In a multivariable Cox model that included age and Federation Internationale de Gynecologie et d'Obstetrique stage, POLE and MMRd status remained independent prognostic factors for better RFS; p53 status was an independent prognostic factor for worse RFS. Molecular classification of grade 3 EECs reveals that these tumors are a mixture of molecular subtypes of endometrial carcinoma, rather than a homogeneous group. The addition of molecular markers identifies prognostic subgroups, with potential therapeutic implications.

Project description:BackgroundMultiplatform molecular subtyping has been put into clinical practice as an alternative for The Cancer Genome Atlas (TCGA)-based classification for endometrial cancer (EC), which proved a tool for predicting prognosis and guiding treatment. The traditional methods for the molecular classification of EC only based on pathological indicators are not accurate. The present study aimed to classify EC on a molecular level and explored the possibility of a one-time solution to guide clinical treatment and prognosis determination by utilizing data from a next-generation sequencing (NGS) panel. The ultimate aim was to utilize multiplatform testing to overcome disadvantages of long detection periods and limitations in the information regarding genetic variation.MethodsAn NGS-panel was produced using FFPE samples isolated from 86 patients pathologically diagnosed with EC, and molecular subtyping was performed according to the recommended criteria. In addition, 45 matched samples from 86 patients were randomly selected for immunohistochemical (IHC) staining of P53, MLH1, MSH2, PMS2, and MSH6. Another 41 samples were not analyzed due to incomplete IHC staining results. SPSS (V26.0; IBM Corp., Armonk, NY, USA) was used for receiver operating characteristic (ROC) curve analysis.ResultsThe molecular typing ratio of the 86 cases of endometrial carcinoma was calculated to be 16.28% for POLE type, 17.44% for MSI-H type, 47.67% for CN-L type, 12.79% for CN-H type, 5.81% for unclassified case. A comparison between IHC ProMisE-based subtyping and NGS-based subtyping of the 45 cases revealed that 3 cases were classified as MSI-H by IHC but as MSS by NGS. Among these cases, 1 case was deficient in MLH1 expression and PMS2 protein expression but had wild-type P53 protein, and the P53 sequencing data of this sample showed a missense mutation. Good overall consistency between the 2 determination methods was shown. Receiver operating characteristic (ROC) analysis showed that NGS had particularly high specificity and sensitivity for detecting the MSI and CN subtypes [area under the curve (AUC) =0.893>0.5, P=0.000029<0.01].ConclusionsThe present study suggested that NGS-based subtyping could serve as an effective approach for the molecular typing of EC. Both NGS and IHC bear their own unique advantages and challenges in clinical practice.

Dataset Information

A clinically applicable molecular-based classification for endometrial cancers.

Background

Methods

Results

Conclusions

Publications

A clinically applicable molecular-based classification for endometrial cancers.

Similar Datasets

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