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Clonal haematopoiesis of indeterminate potential (CHIP) is defined by the detection of somatic mutations in genes recurrently mutated in myeloid neoplasms (MNs), in the blood of healthy individuals with normal blood values and lack of morphological evidence of MN. Recent studies have highlighted the potential association between CHIP and the development of MN, in particular therapy-related MN (t-MN) in patients with lymphoma treated with chemotherapy and/or autologous stem-cell transplantation. In the present study, we investigated whether the presence of CHIP is associated with a higher risk for the development of t-MN in patients with chronic lymphocytic leukemia (CLL) treated with chemo(immuno)therapy, including fludarabine and cyclophosphamide combinations. To this end, we studied 9 patients with CLL who developed a t-MN [acute myeloid leukemia (AML): n=6, myelodysplastic syndrome (MDS): n=3] after the administration of chemo(immuno)therapy (FCR: n=7, other, n=2), with available samples collected both before CLL treatment and at diagnosis of t-MN. The median interval between the two samples was 26 months (range: 9-38months). NGS was performed on DNA extracted from bone marrow mononuclear cells (MNCs) at t-MN diagnosis, using the Trusight Myeloid Sequencing Panel (n=4) and the Archer VariantPlex Myeloid kit (n=5). Backtracking of the variants detected at the t-MN phase was performed by NGS of DNA extracted from peripheral blood MNCs (n=8) or CD19+ selected cells (n=1) in the samples from the CLL phase. In case no variants were detected in the t-MN phase, targeted digital droplet PCR (ddPCR) was also performed in paired CLL samples to confirm the presence of the variants. Moreover, using the Trusight Myeloid Sequencing Panel, we evaluated the prevalence of CHIP in a population cohort of 285 patients with CLL at the time of diagnosis. The variant allele frequency (VAF) cut-off for the detection of the variants was set to 5%. Variants were reported if meeting the following criteria: (i) located within an exonic or splicing region; (ii) be non-synonymous; (iii) not listed in the gnomAD database, if not also recurrently reported in Cosmic v85. Overall, 16 variants were detected in 7/9 cases analyzed at the time of t-MN [NRAS (n=4), DNMT3A (n=3), TET2 (n=2), EH2 (n=2), TP53 (n=2), KRAS (n=1), U2AF1 (n=1) and SF3B1 (n=1)], while no variants were detected in 2 t-MN samples. In 6/7 cases with detectable variants at t-MN diagnosis, the same variants were present at the CLL phase with either lower (n=4) or similar (n=2) VAF. Overall, CHIP was detectable in 6/9 (66.7%) CLL patients who later developed a t-MN. Among the untreated CLL patients, 45 CHIP-related variants were detected in 35/285 cases (12%) as 7 patients harbored more than one variant. The median VAF was 12.7% (5.1-58.6%) with 27/45 (60%) having a VAF MTV and TP contributed equally. EF and PB contributed equally. Disclosures Voso: Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Scarfo:Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AstraZeneca: Honoraria; Abbvie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Gilead: Membership on an entity's Board of Directors or advisory committees. Ghia:ArQule: Consultancy, Honoraria; BeiGene: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company), Research Funding; Acerta/AstraZeneca: Consultancy, Honoraria; Adaptive, Dynamo: Consultancy, Honoraria; Novartis: Research Funding; Janssen: Consultancy, Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company), Research Funding; Sunesis: Consultancy, Honoraria, Research Funding; MEI: Consultancy, Honoraria; Lilly: Consultancy, Honoraria; Celgene/Juno: Consultancy, Honoraria. Stamatopoulos:AstraZeneca: Honoraria; Janssen, Gilead, Abbvie: Honoraria, Research Funding.

Acute myeloid leukemia (AML) is the overall most common form of acute leukemia, characterized by a high relapse frequency and low long-term survival rate especially for adults. Even though children with AML have a better prognosis than adults, patients with recurrent AML - independent of age - show poorer overall survival, accelerated disease progression and they often do not respond to conventional treatment. Therefore, a more personalized treatment approach is required to prolong event free survival (EFS) and expand treatment options for relapse and primary resistant (R/PR) AML patients. During the last decade, AML research has largely been focused on improving diagnostic and prognostic tools in AML by investigating data derived from whole genome- and whole exome sequencing (WGS and WES, respectively), gene panels or differential expression analyses of individual genes and gene-fusions. Nevertheless, studies on relapsing AML incorporating WGS data are rare, although necessary to investigate the full repertoire of genetic aberrations underlying AML progression and therapy resistance. To this end, we applied a combination of WGS (WES for a subset of cases) and RNA-seq of longitudinal samples from 48 adult and 21 pediatric R/PR AML cases from the Nordic countries. These comprised tumor samples collected at diagnosis (n=49) and relapse (n=76), as well as PR specimens (n=6). Normal bone marrow (BM) derived stromal cells were cultivated from leukemic BM as a source of patient-matched constitutional DNA, while CD34+ BM cells from five healthy donors were used as a source of normal control RNA. Our findings reveal recurrent relapse specific mutations in CSF1R (2.9% of relapse cases) not previously reported in de novo AML, suggesting the use of receptor tyrosine kinase inhibitors as a novel therapeutic option for a subset of AML relapse cases. Further, we report specific differences in the mutational spectrum between adult and pediatric R/PR AML. In adults, we detected higher mutational frequencies of, for instance, ARID1A (6.3%), H3F3A (6.3%) and MGA (10.4%) compared with previous AML studies of only specimens from initial diagnosis, while these mutations were not seen in pediatric AML. In contrast, internal tandem duplications (ITDs) in UBTF were detected solely in pediatric relapsing AML (n=3 [14.3%]). IKZF1 was more frequently mutated in pediatric R/PR AML (14.3%) than previously reported (0.5-2.7%; Bolouri et al., Nat Med. 2018; Shiba et al., Br J Haematol, 2016). Also, differential gene expression analysis identified IKZF1 as downregulated in pediatric chemotherapy resistant samples in comparison with treatment responsive counterparts, independent of IKZF1 mutational status. By investigating differential gene expression patterns of longitudinal samples, we found lower expression of the complement inhibitor CR1/CD35 at relapse compared to their patient matched diagnostic samples in both adults and children. Additionally, IL1R1, encoding a key regulator of inflammation and immune response, was upregulated in both adult and pediatric diagnosis specimens from cases with short EFS, indicating a pronounced role of chronic inflammation during disease progression and AML cell survival. Finally, our findings reveal overexpression of GLI2 and SGMS2 among samples associated with short EFS. Overexpression of these genes may prevent excessive cell proliferation while increasing stemness and dormancy, leading to increased chemotherapy resistance and shorter EFS. Taken together, our results emphasize the advantage of applying a combination of WGS and RNA-seq, to be able to gain a more complete picture of alterations, including mutations, gene fusions and copy number alterations combined with gene expression analysis, when attempting to characterize AML at relapse. This is the first study of both adult and pediatric AML incorporating WGS and RNA-seq analyses on sequential AML samples. Knowledge gathered from this study has provided critical new insights into the biologic basis of this complex disease and will hopefully help to pave the way for improved and individualized treatment strategies. Disclosures No relevant conflicts of interest to declare.

The KMT2A gene is rearranged in pediatric and adult acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML). By fusing with a number of different partner genes, the KMT2A gene generates chimeric proteins with oncogenic abilities. Due to the promiscuity of the gene, routine genetic analysis of KMT2A-rearranged leukemia is time-consuming as it often involves chromosome and FISH analyses, RT-PCR or southern blot. We have thus developed a captured-based next generation sequencing approach to detect KMT2A fusion genes, especially useful when routine methods indicate a rearrangement but cannot identify the specific fusion partner. First, we analyzed bone marrow samples from two AML cases with deletions of the distal part of the KMT2A gene and, as a control, a pre B-ALL with a known KMT2A-AFF1 fusion. The capture was carried out using custom hybridization probes (SureSelect, Agilent) encompassing the entire KMT2A gene. Sequencing was performed on the Ion Torrent PGM, a sequencing instrument well suited for routine diagnostics given its rapid turn-around time. Putative fusions were identified from sequencing reads connecting an exon within KMT2A to an exon from any other gene and the results were confirmed by RT-PCR. As comparison we performed the standard RNA-sequencing protocol using Ion Proton. In the two patients with unknown KMT2A-rearrangements, the capture approach identified 3034 and 2118 reads over a KMT2A-MLLT4 gene fusion, while only 4 and 2 reads, were detected with the standard RNA-sequencing protocol (Table 1). Similarly, RNA-sequencing and the capture approach detected in the control a KMT2A-AFF1 fusion, with a sequencing depth of 4 and 144 reads, respectively. Interestingly, with the capture approach we obtained 5032 reads encompassing the reciprocal fusion, AFF1-KMT2A, underlining the importance of the reciprocal transcript in this entity. Hence, the KMT2A capture approach resulted in a 5000-35000-fold enrichment of the KMT2A fusions compared to standard RNA-sequencing. Although the standard RNA-sequencing detected reads covering the fusion genes, it yielded far too low sequencing depth to be of diagnostic use. We then performed the KMT2A capture approach on three additional cases with distal KMT2A deletions. In one case, we detected a KMT2A-ARHGEF12 fusion, resulting from a 20Mb interstitial deletion (Table 1). This aberration is missed by standard cytogenetics and consequently likely under-diagnosed. However, in two other cases no KMT2A-fusions were identified. In these cases, the 11q-deletion was present only in a proportion of cells and in one, the deletion was absent at relapse, indicating that it was not likely the primary event in this leukemia. These results demonstrate the importance of establishing if a suspected KMT2A-rearrangement truly generates a KMT2A-fusion. In summary, the hybridization-based capture sequencing approach efficiently detects KMT2A-fusion transcripts and reliably identifies canonical and cryptic KMT2A-rearrangements, generating significantly higher number of fusion breakpoint reads, as compared to RNA-sequencing. Furthermore, sensitive RT-PCRs for follow-up (MRD) can be readily designed using the sequence information. Abstract 2406. Table 1. Sequencing results using KMT2A-capture and standard RNA-sequencing Patients (diagnosis) G-banding KMT2AFISH analysisa RNA-seq (Proton) KMT2A capture (PGM) (% cells) Fusion No of reads % of total reads Fusion No of reads % of total reads #1 (pre B-ALL) 46,XX,t(4;11)(q21;q23),i(7)(q10)[18]/46,XX[2] t(4;11)(q21;q23) (94%) KMT2A-AFF1 4 5x10-6 KMT2A-AFF1 144 0,01 AFF1-KMT2A 26 3x10-5 AFF1-KMT2A 5032 0,20 #2 (AML) 46,XX[20] del(11)(q23q23) (80%) KMT2A-MLLT4 4 5x10-6 KMT2A-MLLT4 3034 0,10 #3 (AML) 46,XY[20] del(11)(q23q23) (83%) KMT2A-MLLT4 2 2x10-6 KMT2A-MLLT4 2118 0,07 #4 (pre B-ALL) 46,XX,der(9)t(3;9)(p21;q34)[9]/46,idem,der(9)t(3;9)[10] del(11)(q23q23) (87%) b - - KMT2A-ARHG EF12 296 0,02 #5 (AML) 46,XY[25] del(11)(q23q23) (25%) b - - c - - #6 (AML) 47,XY,del(6)(q14q21),+8[20] del(11)(q23q23) (14%) b - - c - - All results are from bone marrow samples taken at time of diagnosis.aKMT2A specific FISH-analysis was performed using Vysis KMT2A break apart probe. bRNA-sequencing not performed. c No KMT2A-fusion detected. Disclosures No relevant conflicts of interest to declare.