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Final validation of the ProMisE molecular classifier for endometrial carcinoma in a large population-based case series
Open accessAbstract
Background: We have previously developed and confirmed a pragmatic molecular classifier for endometrial cancers; ProMisE (Proactive Molecular Risk Classifier for Endometrial Cancer). Inspired by the Cancer Genome Atlas, ProMisE identifies four prognostically distinct molecular subtypes and can be applied to diagnostic specimens (biopsy/curettings) enabling earlier informed decision-making. We have strictly adhered to the Institute of Medicine (IOM) guidelines for the development of genomic biomarkers, and herein present the final validation step of a locked-down classifier before clinical application. Patients and methods: We assessed a retrospective cohort of women from the Tübingen University Women's Hospital treated for endometrial carcinoma between 2003 and 2013. Primary outcomes of overall, disease-specific, and progression-free survival were evaluated for clinical, pathological, and molecular features. Results: Complete clinical and molecular data were evaluable from 452 women. Patient age ranged from 29 to 93 (median 65) years, and 87.8% cases were endometrioid histotype. Grade distribution included 282 (62.4%) G1, 75 (16.6%) G2, and 95 (21.0%) G3 tumors. 276 (61.1%) patients had stage IA disease, with the remaining stage IB [89 (19.7%)], stage II [26 (5.8%)], and stage III/IV [61 (13.5%)]. ProMisE molecular classification yielded 127 (28.1%) MMR-D, 42 (9.3%) POLE, 55 (12.2%) p53abn, and 228 (50.4%) p53wt. ProMisE was a prognostic marker for progression-free (P = 0.001) and disease-specific (P = 0.03) survival even after adjusting for known risk factors. Concordance between diagnostic and surgical specimens was highly favorable; accuracy 0.91, κ 0.88. Discussion: We have developed, confirmed, and now validated a pragmatic molecular classification tool (ProMisE) that provides consistent categorization of tumors and identifies four distinct prognostic molecular subtypes. ProMisE can be applied to diagnostic samples and thus could be used to inform surgical procedure(s) and/or need for adjuvant therapy. Based on the IOM guidelines this classifier is now ready for clinical evaluation through prospective clinical trials.
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The Measurement of Observer Agreement for Categorical Data
Landis, J. R., & Koch, G. G. (1977) · Biometrics · doi:10.2307/2529310 · Cited by 81,148
Stelloo, E., Bosse, T., Nout, R. A., MacKay, H. J., Church, D. N., Nijman, H. W., Leary, A., Edmondson, R. J., Powell, M. E., Crosbie, E. J., et al. (2015) · Modern Pathology · doi:10.1038/modpathol.2015.43 · Cited by 486
Cited by
León-Castillo, A., de Boer, S. M., Powell, M. E., Mileshkin, L. R., Mackay, H. J., Leary, A., Nijman, H. W., Singh, N., Pollock, P. M., Bessette, P., et al. (2020) · Journal of Clinical Oncology · doi:10.1200/jco.20.00549 · Cited by 855
Clinical actionability of molecular targets in endometrial cancer
Urick, M. E., & Bell, D. W. (2019) · Nature Reviews Cancer · doi:10.1038/s41568-019-0177-x · Cited by 405
Metadata
- Authors
- Kommoss, S., McConechy, M. K., Kommoss, F., Leung, S., Bunz, A., Magrill, J., Britton, H., Kommoss, F., Grevenkamp, F., Karnezis, A., Yang, W., Lum, A., Krämer, B., Taran, F., Staebler, A., Lax, S., Brucker, S. Y., Huntsman, D. G., Gilks, C. B., McAlpine, J. N., & Talhouk., A.
- Venue
- Annals of Oncology
- Publisher
- Elsevier BV
- Published
- 2018-05
- Volume
- 29
- Issue
- 5
- Pages
- 1180-1188
- ISSN
- 0923-7534 (ISSN-L)
- OpenAlex
- W2793281906
- Cited by
- 776
- References
- 2
- FWCI
- 46.58
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- The paper
- Kommoss, S., McConechy, M. K., Kommoss, F., Leung, S., Bunz, A., Magrill, J., Britton, H., Kommoss, F., Grevenkamp, F., Karnezis, A., Yang, W., Lum, A., Krämer, B., Taran, F., Staebler, A., Lax, S., Brucker, S. Y., Huntsman, D. G., Gilks, C. B., . . . Talhouk., A. (2018). Final validation of the ProMisE molecular classifier for endometrial carcinoma in a large population-based case series. Annals of Oncology. https://doi.org/10.1093/annonc/mdy058
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