Characteristics and outcome of AKT1(E17K)-mutant breast cancer defined through AACR Project GENIE, a clinicogenomic registry Journal Article


Authors: Smyth, L. M.; Zhou, Q.; Nguyen, B.; Yu, C.; Lepisto, E. M.; Arnedos, M.; Hasset, M. J.; Lenoue-Newton, M. L.; Blauvelt, N.; Dogan, S.; Micheel, C. M.; Wathoo, C.; Horlings, H.; Hudecek, J.; Gross, B. E.; Kundra, R.; Sweeney, S. M.; Gao, J.; Schultz, N.; Zarski, A.; Gardos, S. M.; Lee, J.; Sheffler-Collins, S.; Park, B. H.; Sawyers, C. L.; André, F.; Levy, M.; Meric-Bernstam, F.; Bedard, P. L.; Iasonos, A.; Schrag, D.; Hyman, D. M.; for the AACR Project GENIE Consortium
Article Title: Characteristics and outcome of AKT1(E17K)-mutant breast cancer defined through AACR Project GENIE, a clinicogenomic registry
Abstract: AKT inhibitors have promising activity in AKT1E17K-mutant estrogen receptor (ER)-positive metastatic breast cancer, but the natural history of this rare genomic subtype remains unknown. Utilizing AACR Project GENIE, an international clinicogenomic data-sharing consortium, we conducted a comparative analysis of clinical outcomes of patients with matched AKT1E17K-mutant (n = 153) and AKT1-wild-type (n = 302) metastatic breast cancer. AKT1-mutant cases had similar adjusted overall survival (OS) compared with AKT1-wild-type controls (median OS, 24.1 vs. 29.9, respectively; P = 0.98). AKT1-mutant cases enjoyed longer durations on mTOR inhibitor therapy, an observation previously unrecognized in pivotal clinical trials due to the rarity of this alteration. Other baseline clinicopathologic features, as well as durations on other classes of therapy, were broadly similar. In summary, we demonstrate the feasibility of using a novel and publicly accessible clincogenomic registry to define outcomes in a rare genomically defined cancer subtype, an approach with broad applicability to precision oncology. SIGNIFICANCE: We delineate the natural history of a rare genomically distinct cancer, AKT1E17K-mutant ER-positive breast cancer, using a publicly accessible registry of real-world patient data, thereby illustrating the potential to inform drug registration through synthetic control data.See related commentary by Castellanos and Baxi, p. 490. ©2020 American Association for Cancer Research.
Journal Title: Cancer Discovery
Volume: 10
Issue: 4
ISSN: 2159-8274
Publisher: American Association for Cancer Research  
Date Published: 2020-04-01
Start Page: 526
End Page: 535
Language: English
DOI: 10.1158/2159-8290.Cd-19-1209
PUBMED: 31924700
PROVIDER: scopus
PMCID: PMC7125034
DOI/URL:
Notes: Article -- Source: Scopus
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MSK Authors
  1. Charles L Sawyers
    225 Sawyers
  2. Qin Zhou
    253 Zhou
  3. Alexia Elia Iasonos
    362 Iasonos
  4. David Hyman
    354 Hyman
  5. Jianjiong Gao
    132 Gao
  6. Nikolaus D Schultz
    486 Schultz
  7. Benjamin E Gross
    44 Gross
  8. Stuart M Gardos
    21 Gardos
  9. Lillian   Smyth
    42 Smyth
  10. Ritika   Kundra
    88 Kundra
  11. Andrew Zarski
    5 Zarski
  12. Bastien Nguyen
    31 Nguyen