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M. Bill et al.
with a 17-genelow score had a lower median number of mutations and only three genes, namely, GATA2, CEBPA and KIT, were found to be mutated more frequently in this group. GATA2 mutations and biallelic CEBPA muta- tions are known to co-occur,43 and the higher incidence of KIT mutations in 17-genelow patients can be at least in part explained by the elevated frequency of CBF-AML in this group, since KIT mutations are associated with CBF- AML.37 Whereas both biallelic CEBPA mutations and GATA2 mutations, which occurred frequently in the 17- genelow score group, are associated with a favorable out- come, mutations associated with adverse outcome, such as those in the RUNX1, ASXL1, and TP53 genes,1,2,36,44-50 were more frequently found in patients with a 17-genehigh score.
We were also interested in characterizing further the prognostic significance of the 17-gene LSC score estab- lished by Ng et al.7 We not only validated its prognostic impact in a larger independent cohort of patients, but also asked the question whether the 17-gene LSC score could refine the well-established 2017 ELN classification.1 This is especially of interest because it appears that some patients classified as ELN Favorable-risk still have a poor outcome. These patients might benefit from other treatment options.1 When we classified the patients according to the ELN guidelines, we found significant differences in the distribution of patients with 17-genelow and 17-genehigh scores among specific ELN risk groups. In younger patients, the majority of 17-genelow score patients were classified as having Favorable-risk, whereas most patients in the 17-genehigh score group were in the Adverse-risk group.
With regard to clinical outcome, we found that the 17- gene LSC score is capable of refining the ELN classification in younger patients. In the Favorable-risk group, applica- tion of the 17-gene LSC score led to the identification of approximately 20% of patients with a 17-genehigh score who had a worse outcome than patients with a 17-genelow score. Prospective studies are needed to test whether these 17-genehigh score patients might benefit from different induction. A similar ability of the 17-gene LSC score to
identify patients with different outcomes was shown for the Adverse-risk group, despite the fact that the outcome of patients in this group is in general poor. The usefulness of the 17-gene LSC score in the ELN Intermediate-risk group seems to be limited, with patients with a 17-genelow score having a better OS but not better CR rates or DFS. Likewise, the 17-gene LSC score could not improve the ELN classification in older AML patients, who are known to have a generally poor prognosis.1-3
In summary, we found that the 17-gene LSC score is associated with distinct clinical and molecular features. Moreover, we not only validated the prognostic impact of the 17-gene LSC score but also showed for the first time that the score can refine the current 2017 ELN classifica- tion, at least in younger patients. This is important because the 17-gene LSC score is associated with well- established prognostic markers that are included in the ELN guidelines. Prospective studies are needed to deter- mine best treatment options for patients currently classi- fied as having Favorable-risk who are identified to have a worse prognosis by the use of the 17-gene LSC score.
Acknowledgments
The authors would like to thank the patients who consented to participate in these clinical trials and the families who supported them. Our thanks also to Donna Bucci and Christopher Manring, the CALGB/Alliance Leukemia Tissue Bank at The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA for sample processing and storage services and Lisa J. Sterling and Christine Finks for data management.
Funding
This work was supported in part by grants from the National Cancer Institute (Bethesda, MA, USA) [UG1CA233338, U10CA180821, U10CA180882 (to the Alliance), P30CA016058, P50CA140158, U10CA180850, U10CA180861, U10CA180866, U10CA180867, and U24CA196171]; the Leukemia Clinical Research Foundation; R35 CA198183 and the Warren D. Brown Foundation; and by an allocation of computing resources from The Ohio Supercomputer Center.
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