Background: IKZF1 encodes IKAROS, a transcription factor and key regulator of lymphocyte differentiation. IKZF1 deletions (D IKZF1 ) are commonly detected in B‐ALL and their prognostic relevance differs between reports. Aims: We aimed to determine impact of D IKZF1 on event free survival (EFS) of patients with precursor B‐ALL aged 23–65 years recruited to UKALL14 (ISRCTN 66541317) between December 2010 and July 2018 when the trial closed to recruitment. Methods: From 655 recruits with B‐ALL, all available diagnostic DNA samples were screened by PCR (n = 497), MLPA P335 SALSA kit (n = 437) or by both (n = 419). A multiplex endpoint PCR, designed to make detection rapid and straightforward covered 4 deletions‐ the dominant negative (DN) D4–7 or the loss of function (LOF) Δ2–7, Δ4‐8, and Δ2‐8, with primer sites located close to the putative breakpoints. All PCR‐detected deletions were confirmed by Sanger sequencing. Results: In the cohort screened for both PCR and MLPA, 88/419 were not congruous. Fifty‐eight of 88 (66%) of these were explicably positive by MLPA only, due to the placement of PCR primers. Fifteen of 88 (17%) were detected by PCR but not MLPA, likely explained by the greater sensitivity of PCR. These cases are being investigated for D IKZF1 in a sub/minor clone. In order to resolve the remaining 15 disparate cases, we are in the process of mapping the breakpoint sites. By PCR, as expected, D4–7 was the most commonly detected deletion (n = 61, 12.3%) followed by D2‐7 (n = 27, 5.4%), D4–8 (n = 20, 4%) with D2‐8 being the rarest (n = 6, 1.2%). Overall, there was no significant impact of PCR‐detected D IKZF1 on EFS (see figure). In a multivariable Cox model, D IKZF1 significantly interacted with both age and Philadelphia chromosome (Ph) status, with no detrimental effect seen in Ph+ cases and any negative impact confined to Ph‐ cases which increased with increasing age. The change in effect with increasing age for the four groups ( ΔIKZF1 /wild type IKZF1 and Ph‐/Ph+) is shown in the figure, wherein no adverse effect is seen for ΔIKZF1 compared to wild type IKZF1 for Ph+ patients at any age, but an increased risk for ΔIKZF1 in Ph‐ ALL as age increases can be seen. Consistent with the technical approach, MLPA detected a wider range of deletions than PCR:‐ D1‐2 (n = 9, 1.8%), D1‐3 (n = 3, 0.6%), D1‐7 (n = 5, 1%), D1‐8 (n = 36, 7.2%), D2‐3 (n = 4 0.8%,) D2‐7 (n = 32, 6.4%), D2‐8 (n = 15, 3%), D4‐7 (n = 49, 9.9%), D4‐8 (n = 19, 3.8%), D6‐8 (n = 1, 0.2%). As with PCR‐detected lesions, there was no impact of MLPA‐detected D IKZF1 on EFS in univariable analysis. In multivariable analysis, the differing effect with age was less evident and did not reach significance, though the same interaction with Ph status was observed. We did not detect any differential impacts by analysing PCR or MLPA‐detected DN or LOF deletions separately. Summary/Conclusion: Both PCR and MLPA have limitations for routine detection of D IKZF1 in clinical trials. However, in this final report on the prognostic relevance of DIKZF1 on the UKALL14 trial, D IKZF1 did not have a strong impact on EFS. image
Background: Mixed lineage leukemia (MLL) is the most common leukemia in infant patients. This leukemia is due to chromosomal translocations at locus 11q23 and is associated with poor clinical outcome. Novel, targeted therapeutic approaches are needed. Protein phosphatase 2A (PP2A) is a serine threonine phosphatase which regulates the phosphorylation of several kinases, including Erk, Akt, GSK3 which are fundamental for MLL cells’ survival. PP2A is a trimeric protein complex in which a core dimer formed between the scaffold subunit and the catalytic subunit is associated with one of the many regulatory subunits that facilitate and direct the interaction of the trimer with substrate proteins. PP2A activity is regulated by interaction with PP2A inhibitor proteins (PIPs), as well as by post‐translational modifications of PP2A complex components. Aims: In this context, our aim is to understand how PP2A post‐translational modifications affect the activity of PP2A on its downstream targets and to investigate whether PP2A re‐activation, by preventing phosphorylation and activation of collateral pathways, might represent a valid therapeutic strategy for MLL. Methods: 12 different leukemic cell lines and 8 primary samples from MLL patients were included in this study. We measured the PP2A phosphatase activity by a colorimetric assay using a synthetic phospho‐peptide and malachite green reagent. The protein levels of PP2A, phospho‐PP2A, demethyl‐PP2A, LCMT‐1, PME‐1, Akt, phospho‐Akt, Erk, and phospho‐Erk were determined by western blot using specific antibodies. Results: Compared to healthy bone marrow, we found an increase in the phosphorylation at Tyrosine 307 (Tyr307) and a decrease in the methylation at Leucine 309 (Leu309) of the catalytic subunit of PP2A in MLL samples. These changes in the post‐translational modifications of the catalytic subunit correlated with a decrease in the phosphatase activity of PP2A. Methylation at Leu309 has been described as an absolute requirement for the binding of the regulatory subunit B55α to PP2A core. B55α was found up‐regulated in MLL cell lines and primary samples compared to healthy bone marrow. The methylation of the catalytic subunit of PP2A is catalyzed by leucine carboxyl methyltransferase (LCMT‐1), which we found down‐regulated in MLL samples, whereas demethylation is catalyzed by the phosphatase methylesterase (PME‐1) that was found up‐regulated in MLL. In line with the inactivation of PP2A in the MLL samples, PP2A downstream targets such as Akt and Erk were found hyper‐phosphorylated in MLL samples. Summary/Conclusion: Our results suggest that PP2A phosphatase activity inhibition might sustain in MLL samples a persistent serine/threonine phosphorylation of PP2A substrates, such as Akt and Erk that mediate pro‐survival and anti‐apoptotic signals. This inhibition might be explained, at least in part, by phosphorylation and demethylation of PP2A catalytic subunit. A better understanding of the mechanisms that regulate PP2A activity could provide new strategies to rescue PP2A phosphatase activity and target fundamental mechanisms of leukemic survival and chemotherapy resistance.
Abstract Background KMT2A -rearranged (KMT2A-R) is an aggressive and chemo-refractory acute leukemia which mostly affects children. Transcriptomics-based characterization and chemical interrogation identified kinases as key drivers of survival and drug resistance in KMT2A -R leukemia. In contrast, the contribution and regulation of phosphatases is unknown. We explored the role of SET, the endogenous inhibitor of SER/THR phosphatase PP2A in KMT2A -R leukemia. Material and Methods The expression of SET was analysed in a large acute myeloid leukemia (AML)- RNA-seq dataset and in primary KMT2A -R samples and aged matched-controls. Stable SET knockdown (KD) was established by RNA interference in three KMT2A wild-type (wt) and four KMT2A -R leukemic cell lines. Gene and protein expression were analysed by RT-qPCR, ChiP, IP and western blot. RNA-seq and phospho-proteomics were employed to evaluate the effect of the SET-PP2A inhibitor FTY720 on global protein phosphorylation and gene expression. The cellular impact of FTY720 was evaluated by analysing proliferation, cell cycle and apoptosis in leukemic cell lines and by colony formation assay in two patient-derived xenograft (PDX). Results SET mRNA was found expressed in blasts from KMT2A -R-patients and in leukemic stem cells. SET protein interacted with both KMT2A wt and fusion proteins. Knockdown of SET inhibited the transcription of KMT2A target genes HOXA9 and HOXA10 and abolished the self-renewal of KMT2A -R leukemic cells. Pharmacological inhibition of SET by FTY720 disrupted SET-PP2A interaction leading to cell cycle arrest, apoptosis and increased sensitivity to chemotherapy in KMT2A -R-leukemic models. Phospho-proteomic and western blot analyses revealed that FTY720 reduced the activity of kinases regulated by PP2A, including ERK1, GSK3b, ARKB, and led to degradation of MYC, supporting the hypothesis of a feedback loop among SET, PP2A and MYC. The RNA-seq indicated that FTY720 reduced the activity of signalling pathways implicated in gene transcription and it compromised the expression of several genes belonging to the KMT2A -R leukemia signature. Conclusions Taken together our results identify SET as a novel player in KMT2A -R leukemia and provide evidence that SET antagonism could serve as a novel strategy to treat this aggressive leukemia.
7019 Background: Midostaurin is approved for FLT3 mutant-positive (FLT3+) acute myeloid leukemia (AML), however efficacy has also been observed in a subpopulation of FLT3 mutant-negative AML, suggesting that FLT3 mutation is not the only determinant in conferring midostaurin sensitivity. We previously described a phosphoproteomic signature significantly elevated in primary AML blasts that responded to midostaurin ex vivo (Casado et al Leukaemia 2018). This signature includes phosphorylation sites on protein kinase C delta (a midostaurin off-target) and its substrate GSK3A. In this study, we tested whether these phospho-signatures could group FLT3+ patients based on clinical responses to midostaurin plus chemotherapy. Methods: We obtained FLT3+ bone marrow (BM) and peripheral blood (PB) diagnosis specimens (n=56 cases) from the Leukemia Tissue Bank at Princess Margaret Cancer Centre. These patients were treated with standard chemotherapy plus midostaurin. Phospho-signatures quantified using mass spectrometry were analysed with a classification machine learning algorithm to group patients based on response to treatment as a function of phospho-signature status. Other features (e.g. genetic mutations, HSC-transplant) were also analysed. Differential survival analysis was carried out with Kaplan-Meier and Log Rank test methods. Phospho-signatures for BM and PB samples were analysed independently. Results: A first ML model was developed based on the signature described in the Casado et al study. Patients positive for this signature exhibited a survival probability of 243 weeks, compared to 126 weeks in signature negative patients (averages by geometric mean, Log Rank p = 9.88e-05). As the patients in the current study received chemotherapy, in addition to midostaurin, we also identified a new signature consisting of 26 phospho-sites (model 2), which partially overlapped with the first model. Patients positive for model 2 signature showed a markedly longer survival time than negative patients (269 vs 76 weeks, Log Rank p = 1.30e-05 for PB and 241 vs 56, Log Rank p = 2.13e-09 for BM specimens, Table). No other features separated survival as clearly as model 2. Conclusions: We have identified phospho-signatures with the potential to further stratify FLT3+ AML for midostaurin treatment. The presence of PRKCD signalling components in signatures provides a rationale for midostaurin activity in sensitive cases. Analysis will also be performed on FLT3 mutant-negative cases to validate the signature in this group.[Table: see text]
Background: Midostaurin plus intensive chemotherapy (M+IC) is approved for FLT3 mutant-positive (FLT3-MP) acute myeloid leukaemia (AML). The presence of refractory/early relapse (R/ER) disease following M+IC treatment suggests the existence of FLT3-independent determinants of M+IC response (Stone et al. NEJM 2017). We have previously reported a phosphoproteomic signature significantly elevated in primary AML blasts that responded to midostaurin ex vivo (Casado et al., 2018, Leukemia). Aims: To build and test a phosphoproteomics-based model to predict M+IC response from FLT3-MP AML patient samples collected at diagnosis. Methods: We retrospectively analysed peripheral blood (PB, n=37) and/or bone marrow (BM, n=34) diagnosis samples of 47 FLT3-MP AML patients subsequently treated with M+IC (median age at diagnosis 61, range 19-79y) using liquid chromatography-tandem mass spectrometry and MS1-based peptide quantification for phosphoproteomics analysis. Data from patients with extreme response profiles were used for model building; the “good-responder” (GR) group had a disease-free survival (DFS)>24 months (n=20), whereas the R/ER group had DFS<6 months (n=14, including refractory patients). Multivariate analysis and machine learning were used to build a phosphoproteomic signature-based model capable of predicting M+IC response from diagnosis samples. The model was validated on an independent, blinded retrospective set of 13 diagnosis FLT3-MP AML samples (median age 60, age range 33-73y, 9xPB and 4xBM). Results: In this study, we identify a highly-predictive phosphoproteomic signature of M+IC response in FLT3-MP AML diagnosis samples, and test it on an independent, blinded patient cohort. First, multivariate analysis of phosphoproteomic data identified several biochemically different groups of AML cases (Fig. 1A), highlighting potential distinct mechanisms of drug response. GR1 and GR2 groups showed upregulation of DNA damage response (DDR), and downregulation of receptor tyrosine kinase (RTK) signalling, and either downregulation of immune response (IR) pathways (GR1), or upregulation of chromatin remodellers (GR2). GR3 showed upregulation of RTK signalling and IR pathways, and downregulation of DDR. A phosphoproteomic signature made of a subset of more than a hundred phosphopeptides discriminating between at least two of these four patient groups (R/ER, GR1-GR3) was used to build a response-prediction model. On the expanded training dataset, including patients with DFS between 6 months and 24 months (n=13), response stratification was achieved with log rank p<1x10-9 (not shown); median DFS was 17.7 weeks for the signature-negative patients, and was not reached for signature-positive patients. The model was then tested on a blinded independent cohort of 13 FLT3-MP patients (Fig. 1B and C), with those positive for our signature showing markedly increased survival than signature-negative patients (median DFS 0 weeks vs not reached, log-rank p<0.0008). The overall model accuracy, with “response” defined as DFS>6 months, was 100% for signature-negative samples (5/5) and 85% for signature-positive samples (6/7, data was censored before 6 months for one patient). Summary/Conclusion: Using MS1-based quantitation of phosphoproteomic data, we identified several potential mechanisms of sensitivity to M+IC. Accounting for response heterogeneity enabled the creation of a model based on a highly-predictive phosphoproteomic signature of M+IC response. In an independent blinded patient cohort of 13 FLT3-MP patients this model predicted M+IC response with 92% accuracy.Keywords: Survival prediction, Acute myeloid leukemia, flt3 inhibitor, Phosphorylation
Since being identified in China in December 2019, coronavirus disease 2019 (COVID-19) has rapidly evolved into a global pandemic with over 4 million cases and more than 270 000 deaths.1 Following the first reported cases in the United Kingdom (UK) in late January 2020, numbers have continued to rise, with 223 060 cases and 32 065 deaths reported as of May 11, 2020.2 Initial reports from China have indicated that COVID-19 has an overall mortality rate of 1·4%. However, the prognosis varies widely between groups, with age over 60 years and underlying conditions (including hypertension, diabetes, cardiovascular disease and cancer) identified as risk factors for severe disease and death.3 The initial reports from China show that patients with cancer are over-represented among individuals who develop severe COVID-19 after contracting the virus.4 Patients with haematological malignancies are expected to be at increased risk of adverse outcomes from this viral infection, due to being immunosuppressed as a consequence of the underlying cancer, and from the effects of therapy. This has led to a variety of recommendations to reduce the risk from COVID-19, including 'shielding' by self-isolating at home for prolonged periods and alterations to therapy such as delaying or even omitting chemotherapy, radiotherapy or transplantation.5-8 However, at the time of writing there are virtually no published data on the impact of COVID-19 in patients with haematological malignancies. We identified 35 adult patients with a known diagnosis of a haematological malignancy under the care of Barts Cancer Centre who developed a laboratory-confirmed COVID-19 infection between March 11 and May 11, 2020. A confirmed case of COVID-19 was defined by a positive result on a reverse-transcriptase–polymerase-chain-reaction (RT-PCR) assay of a specimen collected on a nasopharyngeal swab. Only laboratory-confirmed cases were included, and each patient had at least 14 days of follow-up. The demographic and clinical characteristics of the patients are shown in Table I. The median age of the patients was 69 years; 66% were men. Of 12 patients who had multiple myeloma, five patients had chronic lymphocytic leukaemia, four patients had each of diffuse large B cell lymphoma and acute lymphoblastic leukaemia, three patients had follicular lymphoma, two patients had acute myeloid leukaemia, along with one patient with each of aplastic leukaemia, myelofibrosis, monoclonal gammopathy of undetermined significance, mantle cell lymphoma and myelodysplastic syndrome. 54% of patients were known to have pre-existing hypogammaglobulinaemia at baseline. 24 patients (69%) were on active treatment at the time of COVID-19 diagnosis; the treatment history for each case is given in Data S1. Many patients had co-existing chronic medical conditions: most frequently, hypertension (29%), chronic kidney disease (14%) and diabetes mellitus (15%). The most common symptoms were fever (77%), cough (60%) and shortness of breath (54%). Table II shows the correlation of clinical and laboratory findings with outcome. As of May 11, 14 patients (40%) had died and 21 (60%) had recovered. Age was most significantly associated with outcome in our series, with all but one of the patients who died being 70 years or older at the time of COVID-19 diagnosis. The number of co-existing comorbidities (such as hypertension, chronic kidney disease or diabetes) was also predictive of outcome, with patients who died having significantly more concurrent diagnoses than patients who recovered. This reflects the observations seen in initial studies where the elderly and those with underlying conditions were at a significantly higher risk for severe disease and death.3 Importantly, we did not see a correlation between active treatment and outcome in our series. Furthermore, we document 15 patients who have recovered from COVID-19 despite being on treatment at the time of diagnosis of their infection, including patients on highly immunosuppressive regimens such as R-CHOP for lymphoma, induction regimens for acute leukaemia and triplet combinations for myeloma. In terms of laboratory parameters, hypoxia on admission and a highly elevated C-reactive protein level were predictive of a poor outcome. In contrast, there was no association between admission haemoglobin concentration, platelet count or neutrophil/lymphocyte ratio and outcome. Perhaps unexpectedly, patients who recovered had a lower neutrophil and lymphocyte count on admission than the patients who died. This probably reflects inclusion of younger, fitter patients receiving more myelosuppressive and lymphodepleting therapy who nevertheless went on to recover from their infection. However, this highlights that the impact of COVID-19 on haematological parameters such as a lymphopenia or the prognostic utility of neutrophil/lymphocyte ratio may be confounded by other factors in haemato-oncology patients.9, 10 Given the focus on hospital-based testing for suspected COVID-19 in the UK, a crude case fatality rate in a comparable group of hospital-assessed patients of 14·4% can be calculated from current UK government statistics.2 In contrast, we observed a case fatality rate of 40% in haemato-oncology patients, which is comparable to the proportion of patients with cancer who reached a composite endpoint of requiring admission to intensive care, invasive ventilation or death in a previous report.4 Therefore, our patients who developed COVID-19 had an approximately three-fold increased risk of death compared to the general population. Due to the current lack of widespread community testing for COVID-19 in the UK, the case fatality rate reported here is likely to be an overestimate within this patient group. While only patients with laboratory-confirmed COVID-19 were included in our series, we were aware of other haemato-oncology patients who had mild symptoms and were advised to self-isolate at home rather than visit hospital for assessment and were therefore not tested for SARS-CoV-2. Furthermore, it is likely that other patients with no or mild symptoms have not presented to our network. Our study does have several limitations, including the relatively small sample size and lack of data on patients who developed COVID-19 in the community and were not tested. Ultimately, some of these questions will be addressed by larger multi-national and registry studies. However, given the rapidly-evolving nature of the global COVID-19 pandemic, there is a place for case series in guiding haematological practice during these challenging times. Our data demonstrate that while patients with haematological cancers have worse outcomes after COVID-19 than the background population, the majority still survive. The authors declare no potential conflicts of interest. J.A. and J.C.R. devised and directed the research project, analysed the data and wrote the paper. J.K.D., J.G.G., J.D.C. and R.L.A. provided the clinical data, contributed to the interpretation of results and wrote the paper. S.L.H., S.M., S.A., H.O., B.S., M.S., J.O., B.W., V.F., S.A., R.L.D., K.Z., E.T. and T.E. worked on patient enrolment and provided clinical data. All authors provided critical feedback and approved the final version of the manuscript. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. 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