Gynecologic Oncology Consult

A new way to classify endometrial cancer


 

These tumors tend to be associated with a higher-grade endometrioid cell type, the presence of lymphovascular space invasion, and an advanced stage. Patients with tumors that have been described as MSI high are candidates for “immune therapy” with the PDL1 inhibitor pembrolizumab because of their proinflammatory state and observed favorable responses in clinical trials.4

Copy number high/low

Copy number (CN) high and low refers to the results of microarrays in which hierarchical clustering was applied to identify reoccurring amplification or deletion regions. The CN-high group was associated with the poorest outcomes (recurrence and survival). There is significant overlap with mutations in TP53. Most serous carcinomas were CN high; however, 25% of patients with high-grade endometrioid cell type shared the CN-high classification. These tumors shared great molecular similarity to high-grade serous ovarian cancers and basal-like breast cancer.

Those patients who did not possess mutations that classified them as POLE hypermutated, MSI high, or CN high were classified as CN low. This group included predominantly grades 1 and 2 endometrioid adenocarcinomas of an early stage and had a favorable prognostic profile, though less favorable than those with a POLE ultramutated state, which appears to be somewhat protective.

Molecular/metabolic interactions

While molecular data are clearly important in driving a cancer cell’s behavior, other clinical and metabolic factors influence cancer behavior. For example, body mass index, adiposity, glucose, and lipid metabolism have been shown to be important drivers of cellular behavior and responsiveness to targeted therapies.5,6 Additionally age, race, and other metabolic states contribute to oncologic behavior. Future classifications of endometrial cancer are unlikely to use molecular profiles in isolation but will need to incorporate these additional patient-specific data to better predict and prognosticate outcomes.

Clinical applications

If researchers can better define and describe a patient’s endometrial cancer from the time of their biopsy, important clinical decisions might be able to be tackled. For example, in a premenopausal patient with an endometrial cancer who is considering fertility-sparing treatments, preoperative knowledge of a POLE ultramutated state (and therefore an anticipated good prognosis) might favor fertility preservation or avoid comprehensive staging which may be of limited value. Similarly, if an MSI-high profile is identified leading to a Lynch syndrome diagnosis, she may be more inclined to undergo a hysterectomy with bilateral salpingo-oophorectomy and staging as she is at known increased risk for a more advanced endometrial cancer, as well as the potential for ovarian cancer.

Postoperative incorporation of molecular data promises to be particularly helpful in guiding adjuvant therapies and sparing some women from unnecessary treatments. For example, women with high-grade endometrioid tumors who are CN high were historically treated with radiotherapy but might do better treated with systemic adjuvant therapies traditionally reserved for nonendometrioid carcinomas. Costly therapies such as immunotherapy can be directed toward those with MSI-high tumors, and the rare patient with a POLE ultramutated state who has a recurrence or advanced disease. Clinical trials will be able to cluster enrollment of patients with CN-high, serouslike cancers with those with serous cancers, rather than combining them with patients whose cancers predictably behave much differently.

Much work is still needed to validate this molecular profiling in endometrial cancer and define the algorithms associated with treatment decisions; however, it is likely that the way we describe endometrial cancer in the near future will be quite different.

Dr. Rossi is an assistant professor in the division of gynecologic oncology at the University of North Carolina at Chapel Hill. She has no disclosures.

References

1. Bokhman JV. Two pathogenetic types of endometrial carcinoma. Gynecol Oncol. 1983;15(1):10-7.

2. Clarke BA et al. Endometrial carcinoma: controversies in histopathological assessment of grade and tumour cell type. J Clin Pathol. 2010;63(5):410-5.

3. Cancer Genome Atlas Research Network. Integrated genomic characterization of endometrial carcinoma. Nature. 2013;497(7447):67-73.

4. Ott PA et al. Pembrolizumab in advanced endometrial cancer: Preliminary results from the phase Ib KEYNOTE-028 study. J Clin Oncol. 2016;34(suppl):Abstract 5581.

5. Roque DR et al. Association between differential gene expression and body mass index among endometrial cancers from the Cancer Genome Atlas Project. Gynecol Oncol. 2016;142(2):317-22.

6. Talhouk A et al. New classification of endometrial cancers: The development and potential applications of genomic-based classification in research and clinical care. Gynecol Oncol Res Pract. 2016 Dec;3:14.

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