Clinical utility of prospective molecular characterization in advanced endometrial cancer Journal Article


Authors: Soumerai, T. E.; Donoghue, M. T. A.; Bandlamudi, C.; Srinivasan, P.; Chang, M. T.; Zamarin, D.; Cadoo, K. A.; Grisham, R. N.; O'Cearbhaill, R. E.; Tew, W. P.; Konner, J. A.; Hensley, M. L.; Makker, V.; Sabbatini, P.; Spriggs, D. R.; Troso-Sandoval, T. A.; Charen, A. S.; Friedman, C.; Gorsky, M.; Schweber, S. J.; Middha, S.; Murali, R.; Chiang, S.; Park, K. J.; Soslow, R. A.; Ladanyi, M.; Li, B. T.; Mueller, J.; Weigelt, B.; Zehir, A.; Berger, M. F.; Abu-Rustum, N. R.; Aghajanian, C.; DeLair, D. F.; Solit, D. B.; Taylor, B. S.; Hyman, D. M.
Article Title: Clinical utility of prospective molecular characterization in advanced endometrial cancer
Abstract: Purpose: Advanced-stage endometrial cancers have limited treatment options and poor prognosis, highlighting the need to understand genetic drivers of therapeutic vulnerabilities and/or prognostic predictors. We examined whether prospective molecular characterization of recurrent and metastatic disease can reveal grade and histology-specific differences, facilitating enrollment onto clinical trials. Experimental Design: We integrated prospective clinical sequencing and IHC data with detailed clinical and treatment histories for 197 tumors, profiled by MSK-IMPACT from 189 patients treated at Memorial Sloan Kettering Cancer Center. Results: Patients had advanced disease and high-grade histologies, with poor progression-free survival on first-line therapy (PFS1). When matched for histology and grade, the genomic landscape was similar to that of primary untreated disease profiled by TCGA. Using multiple complementary genomic and mutational signature-based methods, we identified patients with microsatellite instability (MSI), even when standard MMR protein IHC staining failed. Tumor and matched normal DNA sequencing identified rare pathogenic germline mutations in BRCA2 and MLH1. Clustering the pattern of DNA copy-number alterations revealed a novel subset characterized by heterozygous losses across the genome and significantly worse outcomes compared with other clusters (median PFS1 9.6 months vs. 17.0 and 17.4 months; P 1⁄4 0.006). Of the 68% of patients harboring potentially actionable mutations, 27% were enrolled to matched clinical trials, of which 47% of these achieved clinical benefit. Conclusions: Prospective clinical sequencing of advanced endometrial cancer can help refine prognosis and aid treatment decision making by simultaneously detecting microsatellite status, germline predisposition syndromes, and potentially actionable mutations. A small overall proportion of all patients tested received investigational, genomically matched therapy as part of clinical trials. © 2018 American Association for Cancer Research.
Journal Title: Clinical Cancer Research
Volume: 24
Issue: 23
ISSN: 1078-0432
Publisher: American Association for Cancer Research  
Date Published: 2018-12-01
Start Page: 5939
End Page: 5947
Language: English
DOI: 10.1158/1078-0432.Ccr-18-0412
PROVIDER: scopus
PMCID: PMC6279519
PUBMED: 30068706
DOI/URL:
Notes: Clin. Cancer Res. -- Export Date: 2 January 2019 -- Article -- CODEN: CCREF -- Source: Scopus
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MSK Authors
  1. Vicky Makker
    108 Makker
  2. Mila Gorsky
    6 Gorsky
  3. David Solit
    544 Solit
  4. Jason Konner
    105 Konner
  5. Dmitriy Zamarin
    84 Zamarin
  6. Paul J Sabbatini
    226 Sabbatini
  7. Marc Ladanyi
    1043 Ladanyi
  8. Kay Jung Park
    207 Park
  9. Rachel Nicole Grisham
    54 Grisham
  10. Martee L Hensley
    237 Hensley
  11. Robert Soslow
    710 Soslow
  12. David Hyman
    302 Hyman
  13. Ahmet Zehir
    214 Zehir
  14. Rajmohan Murali
    167 Murali
  15. William P Tew
    154 Tew
  16. David R Spriggs
    323 Spriggs
  17. Michael Forman Berger
    497 Berger
  18. Deborah F DeLair
    98 DeLair
  19. Barry Stephen Taylor
    191 Taylor
  20. Karen Anne Cadoo
    65 Cadoo
  21. Britta Weigelt
    347 Weigelt
  22. Jennifer Jean Mueller
    50 Mueller
  23. Sarah   Chiang
    66 Chiang
  24. Matthew   Chang
    24 Chang
  25. Bob Tingkan Li
    99 Li
  26. Sumit   Middha
    78 Middha