ALBERT

Description: Introduction Acute lymphoblastic leukaemia (ALL) in infants has poor overall survival despite being characterized by very few genetic aberrations per case. The most common genetic change, present in over 75% of cases, is the rearrangement of the mixed lineage leukaemia (MLL/KMT2A) gene (MLL-R) that also occurs in AML and mixed phenotype acute leukaemia (MPAL). Because infant ALL is rare and distinctive, most Australian and New Zealand patients are enrolled on specific clinical trials. In earlier infant ALL trials, MRD was not used for risk stratification firstly because of the difficulty of finding sensitive markers for specific immunoglobulin and T-cell receptor (Ig/TCR) gene rearrangements and the secondly because, in infant ALL, Ig/TCR markers are often present in sub-clones that can be lost at relapse due to clonal selection. MRD testing is performed in the current Interfant 06 trial preferentially using markers based on the genomic breakpoint sequences of MLL gene rearrangements. The treatment of infant ALL remains very challenging with relatively poor survival rates attributable to both toxicity and relapse. The objectives of this study were therefore to analyse MRD data for Interfant 06 patients enrolled at ANZCHOG centres and to perform a pilot experiment evaluating gene expression for key genes in infant ALL samples on a microfluidics platform, as a basis for identifying potential targeted therapies. Methods MRD was measured in bone marrow DNA from Interfant 06 patients enrolled since 2006, using sensitive Real-time Quantitative PCR (PCR-MRD) patient-specific assays to detect either MLL gene rearrangements (in 17) and/or conventional immunoglobulin and T-cell receptor (Ig/TCR) markers (21). Gene expression levels for 90 genes important in childhood cancers were measured by Taqman-based microfluidic assays in duplicate using cDNA from 2 micrograms of total RNA from 10 infant ALL samples (5 MLL, 5 non-MLL) at diagnosis (6) or relapse (4). Results Patient-specific PCR-MRD tests were developed for 27 out of 28 Australian and New Zealand infant ALL patients. 17/18 MLL-R ALL patients had MLL-R assays and 21/28 patients had Ig/TCR MRD tests, with only 1 (non-MLL) patient having no MRD markers. There was a wide range of MRD responses to induction therapy (Figure 1). Bone marrow MRD at the end of induction was high (〉1x10-3) in 44% of MLL-R ALL infants compared to 25% of non-MLL ALL infants and 15% of older children enrolled on ANZCHOG ALL8. In 8/13 MLL-R patients who had both types of marker, MRD levels were higher when measured by their MLL-R marker than by their Ig/TCR marker. In a set of 90 genes selected for expression analysis, higher levels were found for 17 genes in 2 or more of the 10 infant ALL samples evaluated. These more highly expressed genes included potential or known drug targets BCL2, ERBB2, ERBB4, ILRA2, CSF1R and PARP1. Conclusions The quantitation of MRD based on MLL rearrangements in ALL is effective and can also be used to monitor response to therapy in infant ALL as well as MLL-R cases of AML and MPAL. The combined application of MLL-R and Ig/TCR markers allowed 97% of infant ALL patients to be MRD monitored with a sensitive marker. In most patients with both type of MRD marker, higher levels of MRD were detected in end of induction samples using the MLL versus Ig/TCR tests. One interpretation is that Ig/TCR genes are rearranged after the MLL rearrangement in ALL sub-clones that are both more mature and more chemo-sensitive. This finding also confirms the current consensus that disease-related MLL-R markers provide better risk assessment than Ig/TCR markers. Our Fluidigm analysis has shown that quantitative measurement of multiple gene expressions is feasible on small RNA samples and can be used to rapidly screen for specific expression of genes coding for drug targets in ALL patients. Support: NHMRC Australia APP1057746, Sporting Chance Cancer Foundation. Figure 1. Comparison of MRD response to induction therapy in MLL-R infant ALL compared with non-MLL infant ALL (Interfant 06) and older children (ANZCHOG ALL8). Figure 1. Comparison of MRD response to induction therapy in MLL-R infant ALL compared with non-MLL infant ALL (Interfant 06) and older children (ANZCHOG ALL8). Disclosures No relevant conflicts of interest to declare.

Description: Background Mutation of genes linked to hematologic cancer have recently been reported in CML and are associated with early progression and resistance (Reviewed in Branford, Kim Leuk 2019). The mutations comprise single nucleotide variants (SNVs) and small insertions/deletions (indels), plus gene fusions and large focal gene deletions. In 39 patients (pts) in blast crisis (BC), all had at least 1 cancer gene mutation, including fusions in 33%: partner genes MLL, RUNX1, IKZF1, MECOM and CBFB. 50% of the fusions were novel and some were present at chronic phase diagnosis. BCR-ABL1 mutations rarely occurred as the sole mutant. NGS offers critical information for resistance assessment. For many clinical purposes, targeted DNA sequencing (seq) using panels of specific disease related genes is the most cost effective screening choice. However, this strategy could miss relevant fusions and deletions. Aim To determine whether an RNA based approach is more informative than DNA for detecting a broad range of mutations. Method A hybridization capture NGS gene panel was developed to target 126 genes relevant for myeloid/lymphoid leukemia. In a pilot study, DNA and RNA derived from 5 leukemia cell lines with well characterized mutations, including fusions and deletions, were panel sequenced. An additional 6 cell lines were sequenced using RNA, plus 49 pt samples with RNA stored for up to 14.6 years: 45 at diagnosis and 4 at BC/resistance. Six of these pt samples had prior whole exome and/or whole transcriptome seq. We used total RNA that detected intronic splice region variants from pre-spliced RNA. SNVs/indels were called from DNA/RNA with FreeBayes. Manta called focal deletions from DNA. Known and novel RNA fusions and novel splice junctions were detected using the STAR aligner. Gene expression used edgeR. Results For the 5 cell lines with DNA versus (v) RNA seq, SNVs/indels were reliably called in RNA, with a strong positive correlation of mutant allele frequency: DNA v RNA, r = 0.93. Two TP53 small deletions of 26 and 46 bp were not called in RNA, but were instead detected as novel RNA splice junctions. Read counts were 5.2 fold higher for RNA than DNA at sites of clinically relevant mutants, consistent with enrichment of seq read depth proportional to expression. Overall, RNA revealed a higher number of relevant mutants than DNA: RNA = 49 v DNA = 37, Fig A-C. Notably, the functional effect of splice region disrupting mutants and large focal deletions were evident by novel RNA splicing, Fig D-F. In the total 11 cell lines tested with RNA, all 13 reported fusions were called, including BCR-ABL1 and RUNX1, MLL, ETV6 and CBFB fusions. For 7 cell lines with variants described in the COSMIC Cell Lines Project, 23/23 cancer gene SNVs/indels were called, plus 7 cancer gene SNVs/indels not reported. These were verified by DNA seq. 15 gene deletions were evident by atypical RNA splicing and verified by DNA seq: IKZF1, CDKN2A/B, PAX5, BTG1, RB1 and NCOR1. Five other cell lines had verified CDKN2A deletions that were evident by loss of gene expression, Fig G. Two BTG1 deletions were not detected. For the 6 pt samples re-sequenced by the RNA panel, 8/8 verified fusion transcripts were detected with a 31 fold enrichment of read counts. 11/11 cancer gene SNVs/indels were called and 3/4 gene deletions. The exception was a CDKN2A deletion not detected by novel splicing but evident as loss of expression, Fig G. Seven other cancer gene SNVs were found at low allele frequency, including a resistant BCR-ABL1 mutation at 1.7% in the oldest sample. Of the 43 diagnosis samples without prior NGS, BCR-ABL1 transcripts were detected in all. BCR-ABL1 genomic breakpoints were called at base pair resolution in 39, 91%. Two pts had mutated ASXL1 at diagnosis and both failed imatinib by 9 months with mutant BCR-ABL1. By gene expression analysis, all but 1 of the total 45 diagnosis samples clustered together. The exception was a pt who transformed to lymphoid BC at 6 months that clustered with the lymphoid cell lines and lymphoid BC pts, Fig H. Conclusion RNA gene panel seq demonstrated enhanced sensitivity and an increased yield of clinically relevant mutations compared with DNA panel seq. A single RNA assay has the capacity to detect SNV/indels, known and novel gene fusions, focal deletions and the likely functional effect of splice disrupting mutations. RNA panel seq is a valuable tool for the comprehensive assessment of mutations that drive CML treatment failure and drug resistance. Disclosures Branford: Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Honoraria, Speakers Bureau; Qiagen: Consultancy, Honoraria; Cepheid: Consultancy, Honoraria. Shanmuganathan:Gilead: Other: Travel Support; Janssen: Other: Travel Support; Amgen: Other: Travel Support; Bristol-Myers Squibb: Honoraria, Other: Travel Support; Novartis: Honoraria, Other: Travel Support. Scott:Celgene: Honoraria. Hughes:Novartis, Bristol-Myers Squibb: Consultancy, Other: Travel; Novartis, Bristol-Myers Squibb, Celgene: Research Funding.

Description: Background Mutated cancer genes in patients (pts) with TKI failure and blast crisis (BC) CML have recently been described. RUNX1 mutations, namely single nucleotide variants (SNVs) and indels, were the most frequently detected besides BCR-ABL1 [reviewed in Branford, Kim Leuk 2019]. They were found in ~18% of pts, although splice variants were rarely described. RNA splicing events were associated with focal deletion of IKZF1 and RUNX1 in TKI resistant pts that were identified by copy number analysis and RNAseq [Branford Blood 2018]. Novel splicing associated with mutation of cancer genes is an unexplored area of study in resistance. RNA sequencing can assess the functional effect of splice site variants, which lead to splicing errors due to the use of alternative or cryptic splice sites and cause alterations to protein function. Aim We determined whether novel splicing can identify cancer genes with potential altered function. Methods RNAseq analysis was performed for 48 pts at diagnosis and 33 at BC using a protocol that preserved intron-retaining precursor RNA. Coverage of intron-exon borders was sufficient to detect intronic splice region variants. The STAR aligner was used to bioinformatically collate unannotated RNA splice junctions. 54 cancer genes were assessed and aberrant splice events were filtered based on the number of samples in which a splice junction occurred. Manual inspection of the splice junctions was performed using the Integrative Genomics Viewer. This approach identified previously verified aberrant splicing associated with IKZF1 and RUNX1 deletions. Results Ten previously undetected novel splice junctions were revealed in 9/33 pts (27%) in BC within key tumor suppressor genes CDKN2A/B (5), RB1 (1), ATM (1), and RUNX1 (3). The aberrant splicing pattern of CDKN2A and RB1 (Fig A/B) in 6 pts suggested large deletions, as previously described in our cohort with IKZF1 and RUNX1 deletions. Breakpoints associated with deletions ranging from 53 to 181 Kb were detected in the 5 pts with CDKN2A aberrant splicing. Similarly, a 90 Kb deletion of exons 18-27 of the RB1 gene led to the aberrant splicing. The pts transformed to lymphoid BC (median 5 months). 4 of these 6 pts were tested at diagnosis and the deletions were not detected, indicating they were gained at resistance. The aberrant splicing patterns of ATM and RUNX1 did not predict large deletions. These were related to somatic SNVs at canonical splice sites in ATM and in 2 of the pts with RUNX1 aberrant splicing. A splice acceptor site SNV in ATM resulted in skipping of exon 61 (Fig C) and protein truncation. This novel SNV has not been reported in any population or somatic variant database. Two pts in myeloid BC at 28 and 48 months after diagnosis had an identical somatic RUNX1 mutation at the canonical splice donor site of exon 5. The SNV was not detectable prior to imatinib treatment in both pts. The splice site SNV led to activation of a cryptic splice site within exon 5 in both pts (Fig D), which predicted premature termination. While this mutation is novel, an adjacent intronic SNV occurs in familial platelet disorder, leading to activation of the same cryptic splice site. The atypical RUNX1 splicing of the 3rd patient was associated with retention of 55 bp of intron 6 as a cryptic exon (Fig E), leading to protein truncation. A deep intronic SNV identified at lymphoid BC at 6 months of imatinib was detected near the cryptic exon by RNAseq and verified as somatic by DNA Sanger sequencing. This was predicted to activate cryptic RNA splicing elements and lead to intron sequence retention in a RUNX1 transcript. We sequenced the diagnosis sample using an RNA-based gene panel method under development that provides enhanced sensitivity of variant detection. The same pattern of atypical splicing was observed and the intronic SNV was present at low level. The RUNX1 mutation at diagnosis may have contributed to early BC. To our knowledge this is the first report of a RUNX1 truncating variant in CML involving a cryptic exon. Conclusion Enhanced bioinformatic analysis of RNAseq data has revealed a high proportion of pts with truncating mutations in cancer genes indicated by novel RNA splicing (27% pts in BC). Using RNA-based sequencing allows an evaluation of the potential functional effect of variants that are not apparent by DNA-based mutation analysis. We suggest that future studies include RNA sequencing to detect a broader spectrum of mutations associated with TKI resistance. Disclosures Shanmuganathan: Gilead: Other: Travel Support; Janssen: Other: Travel Support; Amgen: Other: Travel Support; Bristol-Myers Squibb: Honoraria, Other: Travel Support; Novartis: Honoraria, Other: Travel Support. Yeung:Novartis: Honoraria, Research Funding; BMS: Honoraria, Research Funding; Pfizer: Honoraria; Amgen: Honoraria. Scott:Celgene: Honoraria. Hughes:Novartis, Bristol-Myers Squibb, Celgene: Research Funding; Novartis, Bristol-Myers Squibb: Consultancy, Other: Travel. Branford:Cepheid: Consultancy, Honoraria; Qiagen: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Honoraria, Speakers Bureau.

Description: Sphingolipid dysregulation is often associated with insulin resistance, while the enzymes controlling sphingolipid metabolism are emerging as therapeutic targets for improving insulin sensitivity. We report herein that sphingosine kinase 2 (SphK2), a key enzyme in sphingolipid catabolism, plays a critical role in the regulation of hepatic insulin signaling and glucose homeostasis both in vitro and in vivo. Hepatocyte-specific Sphk2 knockout mice exhibit pronounced insulin resistance and glucose intolerance. Likewise, SphK2-deficient hepatocytes are resistant to insulin-induced activation of the phosphoinositide 3-kinase (PI3K)-Akt-FoxO1 pathway and elevated hepatic glucose production. Mechanistically, SphK2 deficiency leads to the accumulation of sphingosine that, in turn, suppresses hepatic insulin signaling by inhibiting PI3K activation in hepatocytes. Either reexpressing functional SphK2 or pharmacologically inhibiting sphingosine production restores insulin sensitivity in SphK2-deficient hepatocytes. In conclusion, the current study provides both experimental findings and mechanistic data showing that SphK2 and sphingosine in the liver are critical regulators of insulin sensitivity and glucose homeostasis.

Description: Background Patients with chronic myeloid leukemia (CML) who develop blast crisis are resistant to TKI therapy. A key focus in CML research is the identification of genetic factors that promote blast crisis and TKI resistance. By using an integrative genomic approach we recently reported frequent structural variation in CML patients, particularly at lymphoid blast crisis (LBC) (Blood, 2018). Developing lymphocytes are uniquely equipped with a molecular toolkit capable of programmed DNA damage and structural variant formation; the V(D)J recombination pathway. Recombination activating genes (RAG1 and RAG2) are involved in cleavage and recombination of immunoglobulin genes to provide diversity in antibodies and T cell receptors. Off target RAG activity is reported to occur in lymphoid malignancies and cause oncogenic structural rearrangements. However, RAG expression and the extent of RAG mediated structural variation in CML are largely uncharacterized. Aim To elucidate the role of RAG mediated recombination as a source of oncogenic structural rearrangement in CML. Methods In a study of samples of 49 patients at chronic phase (CP) diagnosis (Dx), 20 at LBC and 19 at myeloid blast crisis (MBC), we performed whole exome sequencing and/or RNAseq. Bioinformatic analyses included fusion detection (Manta & STAR), gene expression analysis (EdgeR), and copy number variation analysis (in house developed tool). Unsupervised motif detection of sequences surrounding breakpoints was performed with MEME, and fusions were visualized with Jcircos. To identify off target RAG mediated mutation we interrogated the breakpoints of structural variants, excluding those associated with the Philadelphia translocation and those solely involving antigen receptor gene rearrangement. Results 33 structural variants were identified in 22 patients with samples at Dx and/or blast crisis involving genes regularly mutated in hematologic malignancy such as MLL, MECOM, RUNX1 and IKZF1. Differential expression analysis between patients at Dx, MBC and LBC revealed 〉1000 genes that were differentially expressed, P

Description: Key Points Next-generation sequencing revealed variants in cancer-associated genes at diagnosis of CML more frequently in patients with poor outcomes. All patients at BC had mutated cancer genes, including fusions, that predated BCR-ABL1 kinase domain mutations in a majority.