Objectives: Histologic classification along with clinical stage predominantly drive management of patients with endometrial cancer. However, current clinico-pathologic risk-based stratification has proven suboptimal, inciting efforts to identify additional molecular classifiers, such as L1CAM. This is of particular relevance for the TCGA-defined Nonspecific Molecular Profile (NSMP) and MMR-deficient (MMR-d) groups of tumors, both of which are classified as having an intermediate prognosis. In current practice, L1CAM immunostaining is reserved for NSMP tumors that have been classified as MMR-proficient. The aim of this study is to investigate L1CAM testing in tandem, rather than sequential with that of MMR. Methods: A total of 149 MMR-tested endometrial carcinoma cases from 2019–2020 were identified, of which, 45 had also undergone L1CAM immunostaining. Clinical information including grade, stage, and treatment was reviewed. This was correlated with percentage of L1CAM positivity and MMR-status. Results: L1CAM positivity was noted in 7/45 (15.6%) cases with 6/45 (13.3%) additional cases demonstrating only focal positivity. MMR deficiency was noted in 24/45 (53.3%) of the cases in which L1CAM was performed. Of the cases that showed L1CAM positivity, 6/7 (85.7%), were found to be MMR-deficient. Within the remaining group in which L1CAM was not performed, 24/104 (23.1%) of cases showed MMR deficiency. Conclusions: Current findings suggest that L1CAM positivity is not mutually exclusive when correlating with MMR status. Performing L1CAM immunostaining on all endometrial carcinomas may assist in appropriate treatment for patients with L1CAM positivity, and in particular, in MMR-proficient cases classified within the NSMP category.
Bibliographical noteFunding Information:
The authors acknowledge the technical support they received from the immunohistochemical laboratory of MHealth-Fairview organization. We also thank all the peer reviewers for their opinions and suggestions.
©2021 The Author(s).
- Endometrial cancer
- Molecular classification
- Testing algorithm