RNA-sequencing (RNA-seq) efforts in acute lymphoblastic leukaemia (ALL) have identified numerous prognostically significant genomic alterations which can guide diagnostic risk stratification and treatment choices when detected early. However, integrating RNA-seq in a clinical setting requires rapid detection and accurate reporting of clinically relevant alterations. Here we present RaScALL, an implementation of the k-mer based variant detection tool km, capable of identifying more than 100 prognostically significant lesions observed in ALL, including gene fusions, single nucleotide variants and focal gene deletions. We compared genomic alterations detected by RaScALL and those reported by alignment-based de novo variant detection tools in a study cohort of 180 Australian patient samples. Results were validated using 100 patient samples from a published North American cohort. RaScALL demonstrated a high degree of accuracy for reporting subtype defining genomic alterations. Gene fusions, including difficult to detect fusions involving EPOR and DUX4, were accurately identified in 98% of reported cases in the study cohort (n = 164) and 95% of samples (n = 63) in the validation cohort. Pathogenic sequence variants were correctly identified in 75% of tested samples, including all cases involving subtype defining variants PAX5 p.P80R (n = 12) and IKZF1 p.N159Y (n = 4). Intragenic IKZF1 deletions resulting in aberrant transcript isoforms were also detectable with 98% accuracy. Importantly, the median analysis time for detection of all targeted alterations averaged 22 minutes per sample, significantly shorter than standard alignment-based approaches. The application of RaScALL enables rapid identification and reporting of previously identified genomic alterations of known clinical relevance.

Table SI. Number of patients on immunosuppressive therapy (IST) and prednisone. Fig S1. Study flow diagram.

Background and Objective 15% of pediatric and 40% of adult T-cell Acute Lymphoblastic Leukemia (T-ALL) patients fail conventional therapy highlighting the need for novel therapeutic strategies based on genomic alterations of individuals. We interrogated genomic alterations in Australian T-ALL patients for patterns of mutation and druggable targets. A subset of samples were used to establish patient-derived xenograft (PDX) models to evaluate novel therapies. Methods T-ALL patients' samples underwent next generation genomic analyses (128 total samples including diagnosis, refractory and relapse timepoints from 118 patients of all age groups). mRNA sequencing (mRNAseq) identified gene fusions and structural variants and assessed gene expression (n=101 patients). Fusions were called when identified by 2/3 predictors (FusionCatcher, SOAPfuse, JAFFA). Variant calling utilized GATK HaplotypeCaller and underwent several filtering steps to eliminate possible germline alterations and common SNPs. DNA copy number variations (CNVs) were detected via Multiplex Ligation-dependent Probe Amplification (MLPA: P202, P335, P383; n=64 patients). Establishment of PDX models from patient material (bone marrow or peripheral blood) is ongoing. Recapitulation of human disease was confirmed by mRNAseq in a subset of xenografts. Results Genomic fusion genes were identified in 46/101 samples (46%) by mRNAseq; the most common fusion identified was STIL-TAL1 (n=6). Increased expression of LCK and/or LAT (encoded proteins are involved in T-cell receptor (TCR) signal transduction) was observed in 100% of patients with the STIL-TAL1 gene fusion indicating TCR signaling pathways may be perturbed in this sub-group. Other common gene fusions were MLLT10-DDX3X (n=5) and KMT2A-MLLT4/AFDN (n=4). We also observed the previously reported fusions SET-NUP214, KMT2A-MLLT1, PICALM-MLLT10, NUP214-ABL1, several fusions involving TCR subunits as well as novel fusions involving KMT2A, NOTCH1, LMO1, ZEB2. Numerous nonsynonymous mutations were identified in 81/101 patients (80%) with mRNAseq data available (Figure 1). Broadly, the mutated genes encode proteins in the following categories: oncoproteins (NRAS, KRAS); tumour suppressors (TP53, CHEK2, BRCA1, BRCA2, PTEN), epigenetic regulators (EZH2, SETD5, DNMT3A); regulators of NOTCH signalling (NOTCH1, NOTCH2, FBXW7); transcription factors and regulators (IKZF1, KMT2A, EP400, SMARCD1, RUNX1, AFF1, AFF3); kinase and cytokine signal regulators (ATM, JAK2, JAK3, TYK2, FLT3, PTPN11). INDELS in clinically relevant genes were identified in 37/101 patients (37%) including alterations to: NOTCH1, PHF6, PTEN, STAT1, IL7R, CDKN2A, LYL1, WT1, JAK3, LEF1. The most common copy number alterations identified in our patient cohort were CDKN2A/B deletions (30/64 patients, 47%), PHF6 duplication (20/64 patients, 31%) and MLLT3 deletion (13/64 patients, 20%). In patients with CDKN2A/B deletions and additional CNVs, PHF6 duplication (n=6) and MYB duplication (n=4) were mutually exclusive. However, one patient without CDKN2A/B deletions harbored both MYB and PHF6 duplications. MLLT3 deletion always co-occurred with CDKN2A/B deletions (13/13 patients with MLLT3 deletion), but was never observed with PTEN deletion (0/7 patients with PTEN deletion). Patients with either CDKN2A/B deletions or PHF6 duplications frequently harbored NOTCH1 abnormalities: 13/32 patients (41%) and 8/21 patients (38%), respectively. PDX primagrafts investigated the engraftment latency and peripheral organ infiltration. Primagrafts established from patients harboring NUP214-SET1 or NUP214-ABL1 fusions engrafted at a slower rate (82 d and 91 d, respectively) than primagrafts from patients harboring a STIL-TAL1 fusion (45 d) or CDKN2A/B deletions (31 d and 48 d). Conclusions In our T-ALL cohort we demonstrate that the majority of cases harbor rearrangements, structural variations and duplication/deletion of genes associated with malignant transformation. We identified several co-occurring lesions as well as mutually exclusive genomic abnormalities. The top 20 mutated genes in our patient cohort differ to those reported for a pediatric cohort (Roberts et al 2019 Blood 134:649), indicating an association between patient age and genomic alteration. Secondary PDX models investigating novel targeted treatment strategies are ongoing. Disclosures Hughes: Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. White:Bristol-Myers Squibb: Honoraria, Research Funding; Amgen: Honoraria.

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Eighty-six newly diagnosed Philadelphia-negative ALL pts were enrolled from 2012 to 2018, from 14 Australian centres; 82 pts were evaluable. Pts were stratified and treated as per the pediatric ANZCHOG Study 8 protocol based on BFM 2000. Response was assessed on day 33 and 79 by morphology, flow cytometry and RQ-PCR measurable residual disease (MRD) at a central lab according to EuroMRD criteria. Allogenic stem cell transplantation was permitted for high and very high-risk disease groups. Detailed genomic analysis was performed in 47 pts (to date), using whole transcriptome sequencing (mRNA Seq) and multiplex ligation-dependent probe amplification (MLPA) for recurrent ALL related gene deletions. Median age of the study was 24 (16 - 38) years; 28% were female; 59/82 (72%) had B-ALL. Median follow up was 36 (range 3-73) months. Induction mortality was 3.6%. CR rate at day 33 was 90.4% and day 79 (time point 2, TP2) 97.6%. Relapse free survival (RFS) at 2 years was 75.6% (95%CI 65.6 - 85.5%). CR rates at day 33 and day 79 were 90.4% and 97.6% respectively. The 2-year overall survival (OS) was 79.3% (18/82 events). In concordance with other studies, TP2 MRD predicted outcome in ALL06. MRD positive (pos) pts had a 2yr RFS of 68%, vs 98% in MRD negative (neg) pts (p=0.003). To date, 47 pts had mRNA Seq & MLPA; 11/47 pts had T cell ALL; 1/47 died during induction (2.1%). The median age of this subset was 21 (15-37) years, 23% were female and the RFS at 2 years was 73.97% (95%CI 65.6 - 91.44%). TP2 MRD remained predictive of outcome in this group with 2-year RFS in MRD pos pts 54% vs 95% in MRD neg pts (p=0.013, n=44). 13/47 pts have died with a 2-year OS of 73% (95%CI 62.7 - 90%). MPLA and mRNA Seq analysed independently of outcome data revealed 28/47 pts had genomic lesions categorise as High Risk (HR). These included fusions and structural genomic abnormalities involving KMT2A, IKZF1, IGH, ABL1, JAK, CRLF2, CDKN2A/B, PAX5, RAS and ZNF384. The remaining cases were classified as Standard Risk (SR) and included mainly hyperdiploid, T cell and ETV6-RUNX1 cases. Eleven of 13 pts who relapsed were genomic HR with poorer 2-RFS vs SR (59% vs 78.8%, p=0.023 respectively) (Fig 1.). We examined the relationship between genomics risk group and TP2 MRD, a known prognostic marker. Of the 22 pts who were MRD pos, 19 (86%) pts were in the HR genomics group. In contrast, for MRD neg pts, 13/22 were in the SR group (59%) (p=0.004 Fishers exact, Table 1). This demonstrates that the TP2 MRD positive group is strongly enriched for pts with HR genomics. Pts with HR genomics who were TP2 MRD pos had a 2 year RFS of 27% vs HR MRD neg or SR pts with a 2 yr RFS of 78% (p=0.001)(Fig. 2). Further, of the 13 deaths that were observed in this subset 9/13 (69%) fell within the group of pts with HR genomics/TP2 MRD+. The single induction mortality, for whom TP2 data was not available was also genomic HR. This is one of the first genomic surveys in a cohort of AYA pts, a group known for their inferior outcomes compared to children, treated on a pediatric inspired ALL protocol. Our overall outcomes compare favourably to other cohorts (EHA 2019 abstract 2416). In ALL06, genomic risk stratification based on previous published HR lesions, identified a HR cohort with significantly lower RFS and trend for inferior OS, vs a SR cohort. HR genomics was also associated with significantly higher rates of TP2 MRD positivity. Elucidation of targetable genomic lesions at the time of diagnosis may allow interventions to minimise MRD positivity and relapse in HR pts. Genomic information also improves understanding of underlying disease biology, providing targets for novel treatment discovery. Disclosures Yeung: Pfizer: Honoraria; Amgen: Honoraria; Novartis: Honoraria, Research Funding; BMS: Honoraria, Research Funding. Greenwood:Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Wei:AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties: AHW is a former employee of the Walter and Eliza Hall Institute and receives a fraction of its royalty stream related to venetoclax, Research Funding, Speakers Bureau; Astellas: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Macrogenics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Genentech: Honoraria, Membership on an entity's Board of Directors or advisory committees; Servier: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra Zeneca: Honoraria, Research Funding; Janssen: Honoraria. White:AMGEN: Honoraria, Speakers Bureau; BMS: Honoraria, Research Funding.