Conflict of interest:The authors declare no relevant conflict of interest in relation to the work described.AML with biallelic mutations in the CCAAT/enhancer-binding-protein-alpha gene (CEBPA bi ) 1 has now been included in the 2016 revision of the World Health Organization (WHO) 2 classification of myeloid neoplasms as a definite entity due to its association with distinct 3 biological and clinical features as well as its prognostic significance. 1 Mutations in CEBPA 4 (CEBPA mut ) predominantly occur in acute myeloid leukemia (AML) with normal cytogenetics 5 (CN; ~15%), and approximately 60% of the mutated cases carry biallelic mutations. Several 6 studies concordantly showed that in particular patients with CEBPA bi have a favorable 7 outcome compared to monoallelic mutated or wildtype CEBPA (CEBPA wt ) patients. 2,3 8Recently, mutations in the transcription factor GATA2 were identified as genetic lesions 9 potentially cooperating with CEBPA bi with a co-incidence of 18-41%. 4,5 Both, CEBPA and 10 GATA2 are involved in the control of proliferation and differentiation of myeloid progenitors, 11 and germline mutations in both genes have been found predisposing affected individuals for 12 the development of AML. 3,6 GATA2 knockout mice suffer from severe anemia and die around 13 3 day ten of embryonic development. 7 Data from functional studies showed that there is an 14 important interplay between the two genes, e.g. through direct protein-protein-interaction. 8 In 15addition, the C/EBPα dependent activation of target genes is enhanced through 16 coexpression of GATA2 wt . Finally, preliminary data suggest that GATA2 mut allow further 17 refinement of CEBPA mut AML patients with regard to their clinical outcome. 5 18In our study we evaluated the frequency and the clinical impact of GATA2 mut within a large 19 cohort of CEBPA mut AML patients. In total 202 AML patients (age 18 to 78 years) with 20 CEBPA single (CEBPA sm , n=89) or CEBPA bi (n=113) mutations were analyzed for the 21 presence of concurrent GATA2 mut . All patients were enrolled in one of 6 AMLSG treatment 22 trials applying intensive therapy [AMLHD93 n=15; 9 AMLHD98A (NCT00146120) n=53; 23 AMLHD98B n=13; 10 AMLSG 07-04 (NCT00151242) n=74; AMLSG 06-04 (NCT00151255) 24 n=25 and AMLSG 12-09 (NCT01180322) n=22]. The clinical studies were approved by the 25 local ethics review committees and all patients gave informed consent for treatment, 26 molecular analysis and cryopreservation of leukemia samples according to the Declaration of 27Helsinki. In the AMLHD 98B-and AMLSG 06-04 trials patients over the age of 60 were 28 enrolled. The AMLSG 12-09 trial had no upper age limit. In the remaining trials patients 18 to 29 60 years of age were eligible. GATA2 mut screening was performed using a DNA-based PCR-30 assay covering exons 2 to 6 followed by Sanger sequencing. 4 31Among the 202 CEBPA mut AML patients, we identified 42 GATA2 mut in 40 of the 202 patients 32 (20%). Within the subgroup of CEBPA bi mutated patients 38 GATA2 mut were identified in 36 33 o...

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Sequencing of cancer genomes, or parts thereof, has become widespread and will soon be implemented as part of routine clinical diagnostics. However the clinical ramifications of this have not been fully assessed. Here we assess the utility of sequencing large and clinically well-annotated cancer cohorts to derive personalized predictions about treatment outcome. To this end we study a cohort of 1,540 patients with AML (acute myeloid leukemia) with genetic profiles from 111 cancer genes, cytogenetic data and diagnostic blood counts. We test existing and develop new models to compute the probability of six different clinical outcomes based on more than 100 genetic and clinical variables. The predictions derived from our knowledge bank are more detailed and outperform strata currently used in clinical practice (concordance C=72% v C=64%), and are validated on three cohorts and data from TCGA (C=70%).Our prognostic algorithm is available as an online tool (http://cancer.sanger.ac.uk/aml-multistage). A simulation of different treatment scenarios indicates that a refined risk stratification could reduce the number of bonemarrow transplants by up to 25%, while achieving the same survival.Power calculation show that the inclusion of further genes most likely has small effects on the prognostic accuracy; increasing the number of cases will further reduce the error of personalized predictions.not peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission.The copyright holder for this preprint (which was . http://dx.doi.org/10.1101/057497 doi: bioRxiv preprint first posted online Jun. 7, 2016; Led by a small number of high-profile successes, there has been considerable enthusiasm for the concept of personally tailoring cancer management based on individual genomic profiles 1,2 . Mutations in cancer genes fundamentally drive the tumor's growth; applications of genomics in cancer medicine include enhanced diagnostic accuracy through molecular characterization, personalized forecasts of a given patient's prognosis and support for choosing between different therapeutic options 3,4 . There are complications to this narrative. Surprisingly few cancer genes are straightforward therapeutic targets. Many cancer genes are only rarely mutated in a given tumor type. Each patient's tumor typically has several driver mutations. Above all other complications, though, is the challenge that there are hundreds to thousands of different combinations of driver mutations observed across patients for most tumor types 5-7 .The promise of precision medicine has triggered considerable funding commitments, such as the Precision Medicine Initiative in USA, Genomics England in UK and similar efforts in several other countries 8,9 . Central to these initiatives is the concept of a so-called "cancer knowledge network" 9 , in which molecular data on patients' cancers will be matched with their clinical outcomes to enable personalized management strategies. Despite these investments reaching hundreds of milli...