FLT3-ITD transduces autonomous growth signals during its biosynthetic trafficking in acute myelogenous leukemia cells

FMS-like tyrosine kinase 3 (FLT3) in hematopoietic cells binds to its ligand at the plasma membrane (PM), then transduces growth signals. FLT3 gene alterations that lead the kinase to assume its permanently active form, such as internal tandem duplication (ITD) and D835Y substitution, are found in 30–40% of acute myelogenous leukemia (AML) patients. Thus, drugs for molecular targeting of FLT3 mutants have been developed for the treatment of AML. Several groups have reported that compared with wild-type FLT3 (FLT3-wt), FLT3 mutants are retained in organelles, resulting in low levels of PM localization of the receptor. However, the precise subcellular localization of mutant FLT3 remains unclear, and the relationship between oncogenic signaling and the mislocalization is not completely understood. In this study, we show that in cell lines established from leukemia patients, endogenous FLT3-ITD but not FLT3-wt clearly accumulates in the perinuclear region. Our co-immunofluorescence assays demonstrate that Golgi markers are co-localized with the perinuclear region, indicating that FLT3-ITD mainly localizes to the Golgi region in AML cells. FLT3-ITD biosynthetically traffics to the Golgi apparatus and remains there in a manner dependent on its tyrosine kinase activity. Tyrosine kinase inhibitors, such as quizartinib (AC220) and midostaurin (PKC412), markedly decrease FLT3-ITD retention and increase PM levels of the mutant. FLT3-ITD activates downstream in the endoplasmic reticulum (ER) and the Golgi apparatus during its biosynthetic trafficking. Results of our trafficking inhibitor treatment assays show that FLT3-ITD in the ER activates STAT5, whereas that in the Golgi can cause the activation of AKT and ERK. We provide evidence that FLT3-ITD signals from the early secretory compartments before reaching the PM in AML cells.

Incidence of invasive fungal infection in acute lymphoblastic and acute myelogenous leukemia in the era of antimold prophylaxis

The incidence of invasive fungal infection (IFI) in patients with acute myeloid leukemia (AML) has decreased with the introduction of antimold prophylaxis. Although acute lymphoblastic leukemia (ALL) has a lower risk of IFI than does AML, the incidences of IFI in both AML and ALL in the era of antimold prophylaxis should be re-evaluated. We analyzed adults with AML or ALL who had undergone induction, re-induction, or consolidation chemotherapy from January 2017 to December 2019 at Seoul National University Hospital. Their clinical characteristics during each chemotherapy episode were reviewed, and cases with proven or probable diagnoses were regarded as positive for IFI. Of 552 episodes (393 in AML and 159 in ALL), 40 (7.2%) were IFI events. Of the IFI episodes, 8.1% (12/148) and 5.9% (13/220) (P = 0.856) occurred in cases of ALL without antimold prophylaxis and AML with antimold prophylaxis, respectively. After adjusting for clinical factors, a lack of antimold prophylaxis (adjusted odds ratio [aOR], 3.52; 95% confidence interval [CI], 1.35–9.22; P = 0.010) and a longer duration of neutropenia (per one day, aOR, 1.02; 95% CI, 1.01–1.04; P = 0.001) were independently associated with IFI. In conclusion, the incidence of IFI in ALL without antimold prophylaxis was not lower than that in AML. A lack of antimold prophylaxis and prolonged neutropenia were independent risk factors for IFI. Clinicians should be on guard for detecting IFI in patients with ALL, especially those with risk factors.

Tobacco Use Predicts Unique Mutagenesis Signature in Acute Myelogenous Leukemia

Background: Endogenous and exogenous processes are active in leukemia initiation. Single-base substitution (SBS) data permits aggregation into mutational signatures [MS] with potential for clinical application. Acetaldehyde and Benzo [a] pyrene (BaP) are tobacco mutagens that "drive" signature SBS4 [Catalog of Somatic Mutations in Cancer (COSMIC) https://cancer.sanger.ac.uk/signatures/sbs/] in lung cancer characterized by C>A transversion. This specific MS is associated with favorable response to immune-checkpoint therapy (ICT). Previous epidemiologic data correlate smoking with cancer including leukemia. Tobacco mutagens are ubiquitously distributed in organs once inhaled. However, how mutagenicity develops in hemopoietic stem cell/progenitor is unknown. In this study, our primary objective was to investigate the incidence of MS among patients (pt) diagnosed with Acute Myelogenous Leukemia (AML) with smoking exposure. Methods: After IRB approval, we performed retrospective analysis using the BCM AML database. Data from 58 AML pt was available. For all analysis, current and past smoking were aggregated into "positive exposure". SBSs (C>A, C>G, C>T, T>C, T>G, G>C, G>A, GT and AG) in smokers and never smoker were annotated from ELN 2017 predefined subgroups [i.e. CEBPA, NPM1, P53, ASLX1, RUNX1 and FLT3ITD] and all additional mutations in individual pt. We used descriptive statistics to detect differential clinical predictors for smoking induced MS. Chi-square was used to determine association between SBSs and smoking history. Stepwise logistic regression allowed identification of independent MS that correlated with smoking. Results: Median age for 58 AML pt was 65.5 years [y] (range, 22-89) and 58.3% were male. Smokers were 26/58 (44.8%). Whites, African Americans, Hispanics and Asians comprised 35/60 (58.3%), 7/60 (7.1%), 16/60 (26.6%) and 2/60 (2.3%), respectively. 112 myeloid mutations [91 SBSs, 16 duplications, 16 deletions, and 3 insertions] were recorded. 32/58 (55.1%) had positive smoking exposure. Previous reports suggest that C>A [COSMIC=SBS4], G>C [COSMIC= SBS2 and SBS13] and T>C [COSMIC=SBS5] retain strong smoking association with cancer. However, in addition to C>A [HR=0.10 (0.01-0.6), p=0.02], our logistic model identified G>A, HR=0.12 (0.02-0.4), p=0.002, as predictors of exposure. C>A+G>A MS was observed in 19/25 (76%) of AML pt with smoking exposure, OR=6.56 (1.8-23.9), p=0.002. By ELN-2017 defined subgroups, P53, ASXL1, RUNX1, FLT3 and NPM1 mut were detected in 11/58 (18.9%), 5/58 (8.6%), 4/58 (6.8%), 13/58 (22.4%) and 5/58 (8.6%). RAS was seen in 12/58 (20.6%), IDH 12/58 (20.6%), DNMT3A 10/58 (17.2%) and TET2 7/58 (12%). Interestingly, among smokers exhibiting or not C>A+G>A SBP substitution, P53 was identified in 3/3 (100%) v 0/3 (0%), p=0.05 and RAS in 75% v 25%, p=0.08. Conclusions: Our data suggest that C>A and G>A SBS substitutions are frequently observed in AML pt with smoking exposure. Hemopoietic stem cell/progenitors exposed to smoking products may initiate similar SBSs substitutions as those observed in tobacco induced solid tumors. Previously, lung cancer studies demonstrated that TP53 and KRAS mutations tumors exhibited high rate of C>A transversion associated with tumor-infiltrating lymphocytes (TIL) and high program-death 1 ligand (PD-L1) expression. Further similar studies are needed in adult diagnosed with P53 AML. Figure 1 Figure 1. Disclosures Mims: IDEC: Current holder of individual stocks in a privately-held company; Biogen: Current holder of individual stocks in a privately-held company; Incyte: Research Funding; Pfizer: Research Funding; AVEO: Research Funding; Celgene: Research Funding.

Allogeneic Stem Cell Transplantation for Patients with Acute Myelogenous Leukemia (AML) in Second Complete Remission (CR2) Transplanted from Unrelated Donors with Post Transplant Cyclophosphamide (PTCy). a Study on Behalf of the Acute Leukemia Working Party of the European Society for Blood and Marrow Transplantation

Background: Post-transplant cyclophosphamide (PTCy) has been shown to significantly reduce transplant related mortality (TRM) post hematopoietic stem cell transplantation (HSCT) and is being increasingly used for acute myelogenous leukemia (AML) patients (pts) undergoing HSCT including from unrelated donors (UD). These publications mainly include pts transplanted in first complete remission (CR1). We recently reported outcome in 1879 AML pts transplanted in second CR (CR2) with conventional graft-versus-host disease (GVHD) prophylaxis (Leukemia 2020). Results may differ in transplantation with PTCy as GVHD prophylaxis, eliminating proliferating alloreactive T cells, and upregulating T regulatory cells while suppressing host natural killer (NK) cells immediately after transplantation, changing the biology and characteristics of the transplantation. Methods: The study aim was to assess outcome of adult AML pts, aged ≥18 years in CR2 undergoing HSCT from a 9-10/10 UD with PTCy, in 2010-2019.Statistics included multivariate analysis (MVA) adjusting for potential confounding factors was performed using a Cox's proportional-hazards regression model for main outcomes. Results: In total, 127 pts were included. Median follow-up was 19.2 (95% CI, 14.7-28) months (mos). Median age was 45.5 (range, 18.2-71.3) years. 54.3% were male. Cytogenetic risk (MRC classification) was favorable, intermediate, and adverse in 15.7%, 55.9%, and 5.5% of pts, respectively (missing data-22.8percentage) Median year of transplantation was 2017. Time from diagnosis to transplantation was 20.4 (range, 4.1-182.4) months. All pts were at CR2 at time of transplantation. Donors were 10/10 and 9/10 UD in 60.6% and 39.4% of pts, respectively. 77.8% and 47.2% of the pts and donors, respectively, were cytomegalovirus (CMV) seropositive. Conditioning was myeloablative in 50.4% and reduced intensity in 49.6%. The most frequent (61.4%) conditioning consisted of busulfan and fludarabine. All pts received PTCy as anti GVHD prophylaxis in combination with immunosuppression, which was cyclosporine A /mycophenolate mofetil (MMF) in 21.3% and MMF/tacrolimus in 23.6%. 33.9% of the pts received In vivo T-cell depletion. Grafts were peripheral blood in 93.7% and bone marrow in 6.3% of transplants. Karnofsky performance score (KPS) was > 90 in 71.2% and the hematopoietic cell transplantation-specific comorbidity index (HCT-CI) was zero in 61.5% of the pts. Engraftment was achieved by 97.6% with day (d) 60 absolute neutrophil count (ANC) > 0.5 x 10 9/L in 96.8%, and d 180 incidence of acute (a) GVHD II-IV and III-IV was 26.2% and 9.2%, respectively. The 2-year total and extensive chronic (c) GVHD was 34.3% and 13.8 %, respectively. The 2-year non-relapse mortality (NRM) was 17.2%. The 2-year relapse incidence (RI) was 21.1%. RI was the main cause of death in 41% of pts who died, followed by infections (23.1%) and GVHD (20.5%). The 2-year leukemia-free survival (LFS), overall survival (OS) and GVHD-free, relapse-free survival (GRFS) was 61.7%, 65.2% and 49.3%, respectively (Figure). In MVA time from diagnosis to transplant was significant prognostic factor for RI, LFS, OS and GRFS hazard ratio (HR) =0.19 (95% CI 0.07-0.48, p<0.001), HR=0.3 (95% CI 0.16-0.56, p<10-3) and HR=0.31 (95% CI 0.15-0.61, p< 0.001), HR=0.40 (95% CI 0.24-0.69, p<0.001), respectively. Year of transplant significantly predict GRFS and aGVHD HR =0.87 (95% CI 0.78-0.97, p<0.009) and HR=0.84 (95% CI 0.73-0.98, p=0.027), respectively. Age was prognostic factor for NRM and good risk cytogenetics for OS HR=1.83 (95% CI 1.24-2.69, p=0.002) and HR=0.21 (95% CI 0.05-0.91, p=0.036), respectively. Finally, female to male combination and RIC were prognostic factors for cGVHD HR=0.15 (95% CI 0.03-0.64, p=0.011), and HR=3.74 (95% CI 1.52-9.18, p=0.004), respectively. Conclusions: Outcome of AML pts undergoing HSCT from a 9-10/10 MUD in CR with PTCy as GVHD prophylaxis, are similar to previous reports using conventional GVHD prophylaxis with 26% of pts developing aGVHD ,34% cGVHD and NRM of 17%. These results are also similar to those we previously observed in pts undergoing HSCT from UD with PTCy while in CR1. Figure 1 Figure 1. Disclosures Labopin: Jazz Pharmaceuticals: Honoraria. Kulagin: X4 Pharmaceuticals, Alexion, Apellis, Biocad: Research Funding; Novartis, Generium, Sanofi, Roche, Johnson & Johnson, Pfizer: Speakers Bureau. Blaise: Jazz Pharmaceuticals: Honoraria. Yakoub-Agha: Jazz Pharmaceuticals: Honoraria. Ciceri: IRCCS Ospedale San Raffaele: Current Employment. Mohty: Sanofi: Honoraria, Research Funding; Pfizer: Honoraria; Novartis: Honoraria; Takeda: Honoraria; Jazz: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Gilead: Honoraria; Celgene: Honoraria, Research Funding; Bristol Myers Squibb: Honoraria; Astellas: Honoraria; Amgen: Honoraria; Adaptive Biotechnologies: Honoraria.