A clinically applicable molecular-based classification for endometrial cancers.

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.

Detection of DNA mismatch repair (MMR) deficiencies by immunohistochemistry can effectively diagnose the microsatellite instability (MSI) phenotype in endometrial carcinomas.

BACKGROUND: A proportion of endometrial carcinomas (ECs) are associated with deficient DNA mismatch repair (MMR). These tumors are characterized by high levels of microsatellite instability (MSI). Identification of MSI is important in identifying women who should be tested for Lynch syndrome and identifying a phenotype that may have specific prognostic and predictive implications. Genomic characterization of ECs has shown that MSI tumors form a distinct subgroup. The two most common methodologies for MSI assessment have not been compared in EC. METHODS: Pentaplex mono and di-nucleotide PCR for MSI testing was compared to MMR IHC (presence/absence of MLH1, MSH2, MSH6, PMS2) in a cohort of patients with EC. Concordance, Kappa statistic, sensitivity, specificity, positive and negative predictive values were obtained on the cross-tabulation of results. RESULTS: Comparison of both MSI and MMR status was complete for 89 cases. Overall agreement between methods (concordance) was 93.3% (95% CI[85.9%-97.5%]). A one-sided test to determine whether the accuracy is better than the "no information rate," which is taken to be the largest class percentage in the data, is significant (p<0.00001). Unweighted Kappa was 0.84, along with the sensitivity (88.5%), specificity (95.2%), PPV (88.5%), and NPV (95.2%). The balanced accuracy (i.e. the average between sensitivity and specificity) was 92%. DISCUSSION: We show the equivalence of MSI testing and MMR IHC. We advocate the implementation of MMR IHC in future EC classification schemes, enabling stratification of cases for future clinical trials as well as assisting identification of Lynch syndrome, so that screening and risk reducing interventions can be undertaken.