Heterogeneity Of Acute Myeloid Leukemia Research Articles

The clinical and prognostic significance of FIS1, SPI1, PDCD7 and Ang2 expression levels in acute myeloid leukemia

ObjectivesThe marked heterogeneity of acute myeloid leukemia (AML) renders precisely predicting patient prognosis extremely difficult. Genetic alterations, fusions and mutations, may result in misexpression of key genes in AML. We aimed to investigate the expression patterns of 4 novel genes; FIS1, SPI1, PDCD7 and Ang2 to determine their potential prognostic role in AML patients. MethodsBone marrow mononuclear cells were analyzed for of FIS1, SPI1, PDCD7 and Ang2 expression levels by real-time quantitative PCR as well as of FLT3/ITD and NPM1 mutations in 100 newly diagnosed cytogenetically normal (CN-AML) patients, and 100 non-malignant controls. ResultsFIS1, SPI1, PDCD7 and Ang2 were significantly overexpressed in CN-AML patients (p < 0.001). Their high expression levels were significantly associated with lower complete remission (CR) rate, shorter relapse-free survival (RFS) and overall survival (OS). On multivariate analysis, high FIS1 expression showed a significant impact on CR response after induction therapy (OR = 88.777, 95% C.I: 2.85–2765.78, p = 0.011) while high PDCD7 appeared to be an independent risk factor for RFS (HR = 5.107, 95% C.I: 1.731–15.066, p = 0.003) and OS (HR = 7.353, 95% C.I: 1.859–29.079, p = 0.004) in CN-AML patients. ConclusionsFIS1 and PDCD7 expression are considered independent risk factors and should be integrated into the current AML stratification system.

Intra-Tumor Heterogeneity in Acute Myeloid Leukemia (AML): Results from a Real Life Cohort

Context. AML is an oligoclonal disease. Intratumoral genetic heterogeneity (ITH) is pervasive in cancers and has often been linked to poor outcome. Except in patients (pts) with complex karyotypes (Bochtler, J Clin Oncol 2013), the clinical relevance of ITH remains unknown in AML. We assessed ITH in a real-life AML cohort.Methods. Since Nov 2015, all newly diagnosed AML pts at our institution were analyzed by targeted sequencing with a 60-gene myeloid panel at an average depth of 815X. Variant Allele Frequencies (VAF) were adjusted for copy number variation to estimate Cancer Cell Fractions (CCFs) and rank mutations by decreasing CCFs. Mutations were segregated into different clones when distant by >10% CCF. Ancestral (as opposed to secondary) mutations are defined as those belonging to the first clone (Figure). We could next derive for each pt the total number of clones and the ITH index, defined as the ratio of secondary to ancestral mutations (according to Turajlic, Cell 2018).Results. We studied 201 consecutive AML pts (median age 67 years, secondary AML 24%). The median number of mutations was 4 (range 0-12). Clonal heterogeneity (>1 clone) was found in 71% of pts with a median of 2 clones per pt (range 1-5). 140 pts received intensive chemotherapy (IC), 50 hypomethylating agents (HMA) and 11 best supportive care (BSC) only.Signaling (FLT3, NRAS, KRAS, KIT, JAK2, CBL, CSF3R, BRAF, NF1, PTPN11, RIT1, CALR and MPL, 60%), DNA methylation (DNTM3A, TET2, IDH1/2, 54%), NPM1 (29%), spliceosome (U2AF1, SRSF2, SF3B1, ZRSR2, PRPF8, 27.9%) and tumor suppressors (PHF6, TP53, WT1, 27.4%) were the most frequently mutated pathways. ELN 2017 risk category was favorable, intermediate, adverse and not evaluable in 35%, 27%, 35% and 3% of pts respectively. Increasing ITH was associated with a higher number of clones (p=0.001) and of mutations (p<0.001). ITH was greater in pts with at least one mutation in histone modifiers (ASXL1, ASXL2, EZH2, KMT2A-PTD KMT2D, KDM6A, p=0.0004), cohesin (STAG2, RAD21, SMC3, SMC1A, CTCF, p=0.0018) or signaling (p=0.002) genes but was not affected by the presence of mutations in DNA methylation or spliceosome, tumor suppressor genes, transcription factors (RUNX1, CEBPA, ETV6, GATA2) or co-activators (BCOR, BCORL1, EP300, CREBBP), all p>0.05. ITH was not different among ELN 2017 risk categories (p=0.15). ITH was independent of age, WBC count and type of AML (secondary vs de novo), all p>0.2.There was no significant difference in the number of mutations (p=0.12), clones (p=0.58) or ITH indexes (p=0.38) according to IC/HMA/BSC treatment strategies. We next performed a preliminary analysis of the prognostic impact of ITH in the 140 pts treated with IC (median age 58y), with a median follow-up of only 12.5 months. 117 (84%) pts achieved CR and 32 (23%) were transplanted in first CR. Median event-free survival (EFS) was 18.7 vs 8.0 months in pts with adv and non-adv ELN risk, respectively (p=0.016). In univariate analyses, DNA methylation (p=0.04) and spliceosome (p=0.007) mutations were the two pathways predicting adverse outcome. The number of mutations (p=0.6) or of clones (p=0.8) had no impact on EFS. Pts with fewer secondary than ancestral mutations (ITH <1, ‘ITH low’ group, n=64 [46%]) had a median EFS of 13.6 months vs 19.8 months in the 76 (54%) pts with ITH index ≥1 (‘ITH high’ group, p=0.067). In a multivariate Cox model accounting for age, log(WBC), ELN risk, AML type (secondary vs de novo), presence of DNA methylation and spliceosome mutations and ITH, ITH-high was identified as a significant predictor of improved EFS (HR=0.54, p=0.03), independently of older age (HR=1.02, p=0.07), adv ELN risk (HR=2.4, p=0.005) and higher WBC count (HR=1.27, p=0.004). Censoring at transplant in first CR did not affect this result. In 14 pts who relapsed after a median of 12.9 months since diagnosis with paired NGS at relapse, the number of clones significantly decreased at relapse (p=0.046).Conclusion. Our results confirm that most AMLs are oligoclonal. Surprisingly, higher ITH is not related to older age or secondary AML. Our preliminary results suggest that lower ITH translates into shorter EFS in pts treated with IC. Longer follow-up and/or increased pt numbers are warranted to determine whether NGS-based assessments of clonal heterogeneity can improve AML risk stratification. [Display omitted] DisclosuresFenaux:Otsuka: Honoraria, Research Funding; Jazz: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding.

Single-Cell Mass Cytometry Characterizes Phenotypic and Functional Heterogeneity in Acute Myeloid Leukemia at Diagnosis, in Remission and Relapse

Single-Cell Mass Cytometry Characterizes Phenotypic and Functional Heterogeneity in Acute Myeloid Leukemia at Diagnosis, in Remission and Relapse

1028P - Prognostic factors of clinical use in acute myeloid leukemia

Background: The heterogeneity in acute myeloid leukemia (AML) is influenced by disease and host-specific factors. In recent years, independent molecular factors and host characteristics that affect prognosis have been described. Nevertheless, data is needed to warrant their clinical use. Methods: We retrospectively reviewed data on 356 AML patients from October 2008 to June 2017, including age, Charlson Comorbity Index (CCI), ECOG performance status (PS), laboratory parameters (complete blood count, bone marrow blasts, lactic dehydrogenase) and disease factors (de novo or secondary AML (sAML), genetic alterations). The 2017 European Leukemia Net genetics risk stratification (GRS) was used. Univariate and multivariate Cox regression analysis was performed. Results: The intensive chemotherapy (IC) group comprised of 241 patients, median age 58 years (y), 95% having PS ≤ 1, 67% CCI ≤2 and 22% were sAML. GRS was 23% favorable, 44% intermediate, 27% adverse and 6% unknown. Median overall survival (OS) was 15 months (mo), with 28% 3y-OS. In multivariate analysis (Table), age older than 60y (median 6 versus (vs) 22mo), PS ≥ 2 (median 7 vs 15mo) and higher risk GRS (median 35mo favorable vs 13mo intermediate and 11mo adverse) impacted on survival. The non-IC group included 112 patients, median age 67y, 76% having PS ≤ 1, 6% CCI ≤2 and 37% were sAML. GRS was 12% favorable, 49% intermediate, 24% adverse and 15% unknown. Median OS was 3mo, with 10% 3y-OS. In multivariate analysis (Table), age older than 60y (median 2 vs 17mo), PS ≥ 2 (median 1 vs 5mo) and higher risk GRS (median not reached in favorable vs 4mo intermediate and 1mo adverse) impacted on prognosis.Table: 1028PIntensive chemotherapy HR [95% CI]Non-intensive therapy HR [95% CI]Age≤60 yearsRefRef>60 years2.41 [1.76-3.31]3.09 [1.70-5.65]ECOG PS≤ 1RefRef> 12.36 [1.23-4.53]2.25 [1.27-3.98]ELN2017 geneticsFavorableRefRefIntermediate2.04 [1.33-3.14]3.26 [1.30-8.15]Adverse2.26 [1.42-3.59]5.55 [2.13-14.44] Open table in a new tab Conclusions: In spite of the high number of recognized risk factors, in real-life only GRS, age and PS were of clinical use to predict survival in both IC and non-IC sets. In our sample, there was no significant impact of sAML, CCI and laboratory parameters. Efforts are needed to identify more factors that aid clinical decision in the treatment of AML. Legal entity responsible for the study: Clinical Hematology Department, Centro Hospitalar São João, EPE. Funding: Has not received any funding. Disclosure: All authors have declared no conflicts of interest.

Highlights from Recent Cancer Literature

Highlights from Recent Cancer Literature

Clonal heterogeneity of acute myeloid leukemia treated with the IDH2 inhibitor enasidenib.

Mutations in the gene encoding isocitrate dehydrogenase 2 (IDH2) occur in several types of cancer, including acute myeloid leukemia (AML). In model systems, mutant IDH2 causes hematopoietic differentiation arrest. Enasidenib, a selective small-molecule inhibitor of mutant IDH2, produces a clinical response in 40% of treated patients with relapsed/refractory AML by promoting leukemic cell differentiation. Here, we studied the clonal basis of response and acquired resistance to enasidenib treatment. Using sequential patient samples, we determined the clonal structure of hematopoietic cell populations at different stages of differentiation. Before therapy, IDH2-mutant clones showed variable differentiation arrest. Enasidenib treatment promoted hematopoietic differentiation from either terminal or ancestral mutant clones; less frequently, treatment promoted differentiation of nonmutant cells. Analysis of paired diagnosis/relapse samples did not identify second-site mutations in IDH2 at relapse. Instead, relapse arose by clonal evolution or selection of terminal or ancestral clones, thus highlighting multiple bypass pathways that could potentially be targeted to restore differentiation arrest. These results show how mapping of clonal structure in cell populations at different stages of differentiation can reveal the response and evolution of clones during treatment response and relapse.

Inhibition of interleukin-1 receptor-associated kinase-1 is a therapeutic strategy for acute myeloid leukemia subtypes.

Interleukin-1 receptor-associated kinase 1 (IRAK1), an essential mediator of innate immunity and inflammatory responses, is constitutively active in multiple cancers. We evaluated the role of IRAK1 in acute myeloid leukemia (AML) and assessed the inhibitory activity of multikinase inhibitor pacritinib on IRAK1 in AML. We demonstrated that IRAK1 is overexpressed in AML and provides a survival signal to AML cells. Genetic knockdown of IRAK1 in primary AML samples and xenograft model showed a significant reduction in leukemia burden. Kinase profiling indicated pacritinib has potent inhibitory activity against IRAK1. Computational modeling combined with site-directed mutagenesis demonstrated high-affinity binding of pacritinib to the IRAK1 kinase domain. Pacritinib exposure reduced IRAK1 phosphorylation in AML cells. A higher percentage of primary AML samples showed robust sensitivity to pacritinib, which inhibits FLT3, JAK2, and IRAK1, relative to FLT3 inhibitor quizartinib or JAK1/2 inhibitor ruxolitinib, demonstrating the importance of IRAK1 inhibition. Pacritinib inhibited the growth of AML cells harboring a variety of genetic abnormalities not limited to FLT3 and JAK2. Pacritinib treatment reduced AML progenitors in vitro and the leukemia burden in AML xenograft model. Overall, IRAK1 contributes to the survival of leukemic cells, and the suppression of IRAK1 may be beneficial among heterogeneous AML subtypes.

A Functional Approach to Precision Medicine Identifies Targeted Therapies for Acute Myeloid Leukemia

Identification of genetic heterogeneity in acute myeloid leukemia (AML) has provided a unique opportunity for the greater individualization of therapy. However the implementation of new therapies has lagged far behind the ability to initially recognize operationally important genetic lesions. Until we have further bridged this gap between the identification of genetic lesions and the resultant knowledge of effective therapies, alternative strategies for rapidly identifying candidate therapies can become an important tool for precision medicine. Since most agents, regardless of whether “cytotoxic” or “targeted” ultimately function by activating the mitochondrial apoptotic pathway, we hypothesized that a tool that measures mitochondrial sensitivity may serve as a broadly predictable biomarker. We developed a dynamic BH3 profiling (DBP) technique that measures early death signaling within 8-16 hours after exposure to drugs. Increased cell death signaling is reflected by increased mitochondrial sensitivity (i.e. increased priming) to standardized BH3 peptides mimicking pro-apoptotic proteins.To develop a personalized therapy for AML using DBP, we utilized 20 independent patient derived xenograft (PDX) models, established from de novo, primary refractory or relapsed (R/R) patients (available at http://www.PRoXe.org). Human myeloblasts from spleen and bone marrow of xenotransplanted NSG mice were exposed to 30 targeted and 3 standard of care drugs to determine mitochondrial responses. Unsupervised hierarchical clustering of ex-vivo DBP measurements across AML PDXs revealed several distinct clusters. Majority of targeted agents with an ability to induce priming in selective PDXs were enriched within a cluster, including kinase inhibitors, epigenetic modifiers, SMAC mimetic and chemotherapy drugs. In contrast, a discrete subcluster of drugs showed sensitivity across majority of PDXs, including BH3 mimetics, CDK9 inhibitors and HDAC inhibitors. Drugs with identical mechanism of action showed similar priming patterns across PDXs. Of note, 3 non-myeloid PDXs clustered distinctly from AML, an indication of differential priming responses owing to their cells of origin. AML PDXs developed from treatment naïve patients clustered adjacently and showed greater priming responses to a large number of drugs as opposed to PDXs from R/R patients that formed a discrete cluster. These data reveal that mitochondrial priming can stratify AML PDXs according to its predicted sensitivity to targeted agents.Next, we validated ability of DBP to predict in-vivo responses of single agent birinapant (SMAC mimetic), JQ-1 (BRD-4 inhibitor), quizartinib (FLT-3 inhibitor), and venetoclax (BCL-2 inhibitor) across 6 AML PDX models, prioritized based on their greatest range of priming responses. We found that birinapant was most efficacious nonetheless as expected from ex-vivo DBP studies, responses varied between different PDX models. Myeloblasts of those PDXs that showed the greatest drug-induced changes in apoptotic priming were indeed the PDXs with the highest in-vivo responses. When we compared the ability of DBP to identify sensitive PDXs with additional precision medicine tools such as genomics, we found that DBP was able to accurately predict quizartinib activity in PDXs expressing WT FLT-3, which would have been predicted to be unresponsive based on genomic analysis. Collectively, priming responses obtained from ex-vivo DBP was able to rank different PDX models according to their sensitivities to targeted agents (AUC of ROC curve 0.8731, p<0.005). To investigate if DBP can predict combination therapies in relapsed settings, we first developed resistant models of single agents and then repeated DBP. Myeloblasts from relapsing clone showed reduced overall mitochondrial priming and lacked acquisition of a new chemical dependency compared to initial clone. This suggests that targeting of pre-existing dependencies might be more crucial than therapy induced dependency for AML.In summary, our findings highlight that mitochondria-based measurements could identifying individualized therapy for a heterogeneous population and may serve as a as a powerful biomarker to identify the best responders to patient therapies. DisclosuresLetai:AbbVie, AstraZeneca, Novartis: Consultancy, Research Funding.

Application of NSG in Newly Diagnosed AML

Acute myeloid leukemia (AML) is a hematologic disease characterized by maturation arrest and proliferation of primitive clonal hematopoietic stem cells (blasts) resulting in bone marrow (BM) failure and eventually death if not timely treated. In 2017, approximately 20,000 new cases of AML and 10,000 disease-related deaths occurred in the United States alone. The median age at diagnosis is 67 years and the incidence of the disease increases with age. According to SEER/NCI database, survival in the US AML patients’ population is 26.6% for the last 5 years. Importantly, AML comprises several distinct entities that are cytogenetically and molecularly heterogeneous. Cytogenetic and molecular heterogeneity is clinically relevant, and it has been used for disease classification, prognostication and treatment selection. Despite cytogenetic/molecular risk-based approaches, however, only approximately 40% of younger (<60 year/old) and 10% of older (>60 years) patients achieve cure when treated with currently available chemotherapies. Even if allogeneic hematopoietic stem cells (alloHCT) may improve cure rate, the long-term success of this procedure may be somewhat limited by transplant-related toxicity and disease relapse. Thus, “one size fits all” treatments are insufficient to achieve complete remission (CR) and eventually long-term survival in the vast majority of the molecularly heterogeneous AML patients. Emerging new technologies for sequencing of the human genome have provided the tools for a deeper understanding of the mechanisms of malignant myeloid transformation, and have discovered previously unreported gene mutations and aberrantly silenced or expressed genes that participate in leukemogenesis and treatment resistance and, therefore may be use as therapeutic targets. These novel approaches however have also unveiled the magnitude of the biological complexity of the single AML blasts. Indeed, a myriad of genes have been found concurrently mutated, epigenetically modified or aberrantly expressed in unique molecular profiles of individual patients and contribute to clinical outcome. Thus, the challenge is how to match these complex profiles comprising concurrent mutations, epigenetic changes and aberrantly expressed genes with the most appropriate molecular targeting therapies in individual patients. Although the most pragmatic use of genomic data analyses is to apply a reductive approach and utilize only a relatively small number of genes, novel algorithms for molecular data prioritization and comprehensive analyses must be implemented to capture the entire biologic diversity among distinct AML cells and utilize this information for “personalized” clinical intervention. We will review how the development of molecular profiling using data from different omics platforms may be used for a comprehensive view of the disease biology and to match integrated profiles with the most appropriate cutting- edge treatment for individual AML patients.

Tumor Trp53 status and genotype affect the bone marrow microenvironment in acute myeloid leukemia.

The genetic heterogeneity of acute myeloid leukemia (AML) and the variable responses of individual patients to therapy suggest that different AML genotypes may influence the bone marrow (BM) microenvironment in different ways. We performed gene expression profiling of bone marrow mesenchymal stromal cells (BM-MSC) isolated from normal C57BL/6 mice or mice inoculated with syngeneic murine leukemia cells carrying different human AML genotypes, developed in mice with Trp53 wild-type or nullgenetic backgrounds. We identified a set of genes whose expression in BM-MSC was modulated by all four AML genotypes tested. In addition, there were sets of differentially-expressed genes in AML-exposed BM-MSC that were unique to the particular AML genotype or Trp53 status. Our findings support the hypothesis that leukemia cells alter the transcriptome of surrounding BM stromal cells, in both common and genotype-specific ways. These changes are likely to be advantageous to AML cells, affecting disease progression and response to chemotherapy, and suggest opportunities for stroma-targeting therapy, including those based on AML genotype.

CD123 target validation and preclinical evaluation of ADCC activity of anti-CD123 antibody CSL362 in combination with NKs from AML patients in remission

Despite the heterogeneity of acute myeloid leukemia (AML), overexpression of the interleukin-3 receptor-α (CD123) on both the more differentiated leukemic blast and leukemic stem cells (LSCs) provides a therapeutic target for antibody treatment. Here we present data on the potential clinical activity of the monoclonal antibody CSL362, which binds to CD123 with high affinity. We first validated the expression of CD123 by 100% (52/52) of patient samples and the correlation of NPM1 and FLT3-ITD mutations with the high frequency of CD123 in AML. In vitro studies demonstrated that CSL362 potently induced antibody-dependent cell cytotoxicity (ADCC) of AML blasts including CD34+CD38−CD123+ LSCs by natural killer cells (NKs). Importantly, compared with healthy donor (HD) NKs, NKs drawn from AML patients in remission had a comparable ADCC activity against leukemic cells; of note, during remission, immature NKs were five times higher in AML patients than that in HDs. Significantly, we report a case where leukemic cells were resistant to autologous ADCC; however, the blasts were effectively lysed by CSL362 together with donor-derived NKs after allogeneic hematopoietic stem cell transplantation. These studies highlight CSL362 as a promising therapeutic option following chemotherapy and transplant so as to improve the outcome of AML patients.

Role Of Early Evaluation For Clonal Heterogeneity In Acute Myeloid Leukemia

Role Of Early Evaluation For Clonal Heterogeneity In Acute Myeloid Leukemia

Inhibition of the Enzyme Dihydroorotate Dehydrogenase Overcomes Differentiation Blockade in Acute Myeloid Leukemia

BackgroundThe prognosis for adults diagnosed with acute myeloid leukemia (AML) remains poor, with a five-year survival of 25%. This prognosis is even more dismal in older patients, and those who are not well enough to receive standard induction chemotherapy. Speaking to the need for new therapies is the fact that our therapeutic backbone - a combination of cytarabine and an anthracycline - remains unchanged for 40 years.Differentiation therapy (e.g. ATRA and Arsenic trioxide) revolutionized care for the small subset of patients diagnosed with acute promyelocytic leukemia (APL). Where APL was once the worst form of myeloid leukemia, it now carries the best prognosis, with a five-year survival exceeding 85%. Replicating the success of differentiation therapy in the remaining 90% of patients with AML has remained elusive, and was the motivation behind our studies.HypothesisAML comprises disparate genetic sub-types, but one shared hallmark is that the leukemic blasts are frozen at an immature and self-renewing stage of development. Despite AML's heterogeneity, 70% of cases overexpress HoxA9, a gene that must be downregulated in the process of normal myeloid cell differentiation. We hypothesized that the process through which HoxA9 maintains the undifferentiated state represented a commonly dysregulated node, and that therapies that bypass this node would be useful in the treatment of AML. Thus, we asked the question: 'can we identify small molecules that overcome myeloid differentiation arrest?'A Phenotypic Differentiation ScreenWe established a HoxA9-based AML screening system that permitted an unbiased flow cytometry phenotypic differentiation screen. We screened 330,000 small molecules for those with myeloid differentiation activity. Target identification of our lead compounds led to the unexpected discovery that inhibitors of dihydroorotate dehydrogenase (DHODH) can overcome myeloid differentiation arrest. DHODH is a mitochondrial enzyme involved in the endogenous synthesis of pyrimidines. The modulation of DHODH had not previously been shown to affect myeloid differentiation.DHODH Inhibitors in the Treatment of LeukemiaThe small molecule brequinar is a potent DHODH inhibitor (Panel A). Brequinar triggered myeloid differentiation in vitro (Panel B) and in vivo. Brequinar was highly active in vivo, as demonstrated in syngeneic murine AML models (HoxA9+Meis1 and MLL/AF9) as well as xenotransplant AML models (THP1, HL60, MOLM13, OCI/AML3).In an aggressive MLL/AF9 model of AML, treatment of mice with brequinar caused myeloid differentiation (Panel D), reduced leukemic cell burden, and improved overall survival (Panel C). Furthermore, treatment with brequinar reduced the number of leukemia stem cells, reduced colony-formation activity, and depleted the number of leukemia initiating cell activity (Panel E). These findings support the hypothesis that the myeloid differentiation resulting from DHODH inhibition is both phenotypic and functional, such that the matured leukemia cells lose their self-renewing capability.DHODH Inhibitors and Normal HematopoiesisTreatment with brequinar was better-tolerated and more effective than treatment with cytotoxic chemotherapy. Unlike cytarabine and doxorubicin, brequinar could be given for many weeks without cumulative toxicity. To assay the effect of DHODH inhibition on normal cells, we performed competitive bone marrow transplantation assays. Mice were treated with brequinar, 5-fluorouracil or induction chemotherapy. Their bone marrow was transplanted in competition (1:1) with normal (untreated) bone marrow, to gauge the effect of therapy on hematopoietic stem cell (HSC) function. Treatment with 5-FU and induction chemotherapy led to a dramatic loss of HSC fitness. In contrast, HSCs from mice treated with brequinar were functionally equivalent to those of untreated mice (Panel F) supporting the notion that DHODH inhibition does not lead to detrimental differentiation of the HSC compartment.DiscussionThe mechanism for the selective vulnerability of leukemia cells to DHODH inhibition remains under investigation. Our studies point towards DHODH as a new metabolic target; DHODH inhibitors may provide differentiation therapy for patients with AML. [Display omitted] DisclosuresSykes:Bayer Pharma AG: Research Funding. Meyer:Bayer Pharma AG: Employment. Stoeckigt:Bayer Pharma AG: Employment. Janzer:Bayer Pharma AG: Employment. Scadden:GlaxoSmithKline: Research Funding; Dr. Reddy’s: Consultancy; Fate Therapeutics: Consultancy, Equity Ownership, Membership on an entity’s Board of Directors or advisory committees, Patents & Royalties; Teva: Consultancy; Apotex: Consultancy; Bone Therapeutics: Consultancy; Magenta Therapeutics: Consultancy, Equity Ownership, Membership on an entity’s Board of Directors or advisory committees, Patents & Royalties.

Aberrant splicing and drug resistance in AML.

The advent of next-generation sequencing technologies has unveiled a new window into the heterogeneity of acute myeloid leukemia (AML). In particular, recurrent mutations in spliceosome machinery and genome-wide aberrant splicing events have been recognized as a prominent component of this disease. This review will focus on how these factors influence drug resistance through altered splicing of tumor suppressor and oncogenes and dysregulation of the apoptotic signaling network. A better understanding of these factors in disease progression is necessary to design appropriate therapeutic strategies recognizing specific alternatively spliced or mutated oncogenic targets.

Distinct evolution and dynamics of epigenetic and genetic heterogeneity in acute myeloid leukemia.

Genetic heterogeneity contributes to clinical outcome and progression of most tumors. Yet, little is known regarding allelic diversity for epigenetic compartments and almost no data exists for acute myeloid leukemia (AML). Here we examined epigenetic heterogeneity as assessed by cytosine methylation within defined genomic loci with four CpGs (epigenetic alleles), somatic mutations and transcriptomes of AML patient samples at serial time points. We observe that epigenetic allele burden is linked to inferior outcome and varies considerably during disease progression. Epigenetic and genetic allelic burden and patterning follow different patterns and kinetics during disease progression. We observed a subset of AMLs with high epiallele and low somatic mutation burden at diagnosis, a subset with high somatic mutation and lower epiallele burdens at diagnosis, and a subset with a mixed profile, suggesting distinct modes of tumor heterogeneity. Genes linked to promoter-associated epiallele shifts during tumor progression display increased single-cell transcriptional variance and differential expression, suggesting functional impact on gene regulation. Thus, genetic and epigenetic heterogeneity can occur with distinct kinetics, each likely able to impact biological and clinical features of tumors.

Identification of Effective Targeted Drug Combinations Using Functional Ex Vivo Screening of Primary Patient Specimens

Identification of Effective Targeted Drug Combinations Using Functional Ex Vivo Screening of Primary Patient Specimens

Abstract A32: Computational dissection of phenotypic and functional heterogeneity in acute myeloid leukemia.

Abstract Cells within a single tumor are known to display extensive phenotypic and functional heterogeneity. Many life-threatening features of cancer, including drug resistance, metastasis and relapse, are facets of intratumor heterogeneity. With emerging single-cell measurement technologies, the field is poised to make important strides in understanding and controlling this heterogeneity. However, these technologies require coordinated advances in analytical methods to interpret the complex data they produce. Acute myeloid leukemia (AML) is an aggressive bone marrow malignancy in which the importance of cellular heterogeneity has been well characterized. However, previous studies have only scraped the surface of the heterogeneity in this disease. Using mass cytometry, which measures single cells in ~40 simultaneous proteomic features, we developed novel methods for analyzing phenotypic heterogeneity in cancer. Our approach provides an extensive compendium of surface-marker and signaling phenotypes in AML that extends current boundaries of knowledge. The heart of our approach is a graph-based representation of the single-cell samples. In this representation, each cell is modeled by a node connected to its neighbors—the cells most phenotypically similar to it. Constructed by local rules connecting cells, the graph as a whole represents the phenotypic structure of the sample. The graph can be partitioned into subsets of densely interconnected nodes, called communities, which represent distinct phenotypic subpopulations. Unlike parametric methods such as mixture models, this method makes no assumption about the size, distribution, or number of subpopulations. Using our graph-based approach, we deconstructed several AML samples into discrete phenotypes. Comparing phenotypes across patients, we found a striking degree of order. Every phenotype identifiable phenotype was discoverable in multiple (but not all) patients, implying a constraint on the space of allowable AML phenotypes. For each phenotype we also identified cognate healthy cell types at different stages of bone marrow maturation, indicating a constraint that is linked to normal developmental programs. Our data contain measurements of under various environmental perturbations and we designed a method to statistically quantify evoked signaling responses, producing high-dimensional signaling phenotypes for each subpopulation, which we regard as a representation of cellular functional potential. We found a tight coupling between surface and signaling phenotypes in healthy cells that is disrupted in AML. We identified a primitive signaling phenotype, derived from healthy stem and progenitor cells, which was not correlated with the primitive surface marker profile typically used to define primitive cells in AML. Using single-cell frequencies to deconvolve existing bulk gene expression data, we identified genes associated with this primitive signaling phenotype. These genes are enriched for primitive hematopoietic annotations and produce a clinically predictive signature that is more powerful than genes associated with the primitive surface profile, validating the utility of our approach and indicating novel regulators of the primitive hematopoietic cell state. Citation Format: Jacob H. Levine, Erin F. Simonds, Sean C. Bendall, Garry P. Nolan, Dana Pe'er. Computational dissection of phenotypic and functional heterogeneity in acute myeloid leukemia. [abstract]. In: Proceedings of the AACR Special Conference on Hematologic Malignancies: Translating Discoveries to Novel Therapies; Sep 20-23, 2014; Philadelphia, PA. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(17 Suppl):Abstract nr A32.

Regulatory Roles of KLF3 in Hematopoiesis of K562 Leukemia Cells

Objective: KLF3 (Kruppel-like factor 3) is involved in the differentiation and development of a wide range of cell lineages. However, the regulatory roles of KLF3 in hematopoiesis of K562 leukemia cells remain largely unknown. Methods: The public gene expression databases that represent the heterogeneity of acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL) disease were downloaded from GEO datasets in NCBI. KLF3-deficient K562 stable cells were established and microarray datasets were analyzed. Gene Ontology (GO) analysis was used to identify the affected hematopoiesis-associated genes in KLF3-deficient K562 cells. Ingenuity Pathways Analysis (IPA) was used to identify the affected hematopoiesis-associated functions, interaction networks, pathways and the upstream regulators involving differentially expressed genes (DEGs). KLF3-deficient K562 cells were respectively induced towards erythrocytes and megakaryocytes with hemin and PMA, and phenotypic analyses were performed. We also utilized qPCR technique to analyze KLF3 expression during erythroid and megakaryocyte differentiation of K562 cells. Results: We report that KLF3 is aberrantly expressed at low levels in primary acute leukemia blast cells from patients that are associated with the accumulation of immature myeloid or lymphoid phenotypes of leukemia cells. The bioinformatics analyses reveal that KLF3 is closely involved in hematopoiesis-associated functions in K562 leukemia cells, and potentially regulates hematopoiesis of different blood cell lineages, including erythrocytes and megakaryocytes. KLF3 is probably associated with the pathology of hematological diseases. Finally, the functional analysis demonstrated that KLF3 deficiency accelerates K562 leukemia cells towards erythroid and megakaryocyte differentiation, and is indispensable for the early stage of hematopoiesis in K562 leukemia cells. We also proposed the potential mechanisms that KLF3 regulates hematopoiesis in K562 cells. Conclusion: Our results first reveal that KLF3 regulates erythroid and megakaryocyte differentiation of K562 leukemia cells, and KLF3 deficiency is indispensible for the early stage of erythroid and megakaryocyte differentiation in K562 leukemia cells.

Cytogenetic heterogeneity negatively impacts outcomes in patients with acute myeloid leukemia.

Clonal heterogeneity is a hallmark of malignant transformation. In acute myeloid leukemia, acquired cytogenetic abnormalities are important independent predictors of initial response to therapy, remission duration, and overall survival. However, whether the presence of multiple cytogenetically characterized clones affects outcomes in acute myeloid leukemia is still not well defined. The aim of this study was to assess the prognostic impact of cytogenetic clonal heterogeneity in acute myeloid leukemia. This analysis included 1403 newly diagnosed acute myeloid leukemia patients fit for intensive chemotherapy, aged between 15 and 88 years, enrolled on Southwest Oncology Group protocols. The presence of multiple cytogenetic clones was found in 164 (24%) patients with abnormal karyotype. The proportion of patients with clonal heterogeneity increased with age, being present in 20% of patients under 40 years of age, but in 30% of those aged over 70 years (P=0.03). Clonal heterogeneity was significantly more common in association with unfavorable karyotype. Clonal heterogeneity was associated with decreased response rates and inferior event-free, relapse-free and overall survival, and was confirmed as an independent predictor of poor prognosis in multivariable analysis. Subgroup analysis showed that clonal heterogeneity adds prognostic information particularly in the unfavorable karyotype group. Our results confirm the negative prognostic impact of clonal heterogeneity in acute myeloid leukemia patients with abnormal karyotype. (clinicaltrials.gov identifiers: 014343329; 01338974; 00899171; 1059734; 01059734; 00899743; 0143329; 00023777; 00085709; 01360125; 00004217).

Standard Proteomic Analysis (SPA) in AML: An Integrated Procedure for Discovering Hypoxia and Angiogenesis Patterns

IntroductionThe heterogeneity of acute myeloid leukemia (AML) remains a great barrier to finding a cure for the disease. Despite our best efforts, the current classification system based on phenotypes and genetic mutations are insufficient to capture and characterize each AML subpopulation. This could result in a mismatch of drugs for a particular patient, an impediment to drug discovery, and an inadequate understanding of AML biology. A promising solution to this challenge is profiling patient samples using proteomics. However, researchers are restricted in their power to fully interpret this massive proteomic data due to a lack of standard AML-tailored computational procedures.In this study, we developed a cocktail of computational methods to analyze the AML proteomic data in conjunction with clinical data. This procedure, Standard Proteomic Analysis (SPA), is designed to help researchers identify unique patient groups, discover prognostic biomarkers, find drug targets and understand transitions between pathway activation states. We applied SPA to a set of AML proteomic data with a focus on hypoxia and angiogenesis to illustrate its utility.MethodsThe procedure of SPA is shown in Figure 1. We used Prototype Clustering to estimate the optimal number of patient clusters, and used k-means to obtain the cluster assignment for each patient. Standard Kaplan-Meier curve and log-rank tests were performed to examine how patient clustering impacts patient survival, whereas chi-square test was performed to evaluate the association between clinical correlates and the clustering. Principal Component Analysis was used to map the normal samples on top of the patient samples, in order to distinguish normal states from diseased states. To expand searches for drug targets beyond the key proteins, we built a protein network by combining the computationally derived connections from the data using glasso with the experimentally validated connections from public databases (e.g. String and KEGG). All of the results were visualized using an interactive platform Easel, where each patient could be tracked simultaneously across graphs.The example AML proteomic dataset was obtained by assaying 511 new AML patient samples using reverse phase protein array (RPPA). The RPPA was probed with 231 strictly validated antibodies, including antibodies against three hypoxia regulators (HIF1A, VHL, EGLN1) and two angiogenesis regulators (KDR, VASP). The normal bone marrow derived CD34+ cells were used for comparison.ResultsUsing SPA, we first identified four patient clusters with distinct protein expression patterns (Figure 1A). Most patients displayed canonical hypoxic (C3) and non-hypoxic (C2) patterns, featuring high and low HIF1A with opposite expression of the others. The two non-canonical patterns (C1 & C4) indicate a decoupling between HIF1A and its known regulators (e.g., EGLN, VHL) and targets (e.g., KDR). C1 features high HIF1A, EGLN and VHL but low KDR and VASP. C4 is the opposite. The mapping of normal samples to patient samples (Figure 1B) suggested that non-canonical patterns might be disease specific. From the clinical correlates table (Figure 1D), we observed an association between canonical patterns and cell lineage differentiation, with C3 governing undifferentiated FAB M0/M1 cases and C2 dominant in monocytic M4/M5 subtypes. Furthermore, C1 was associated with favorable cytogenetics, but hypoxic patterns (C1 & C3) were adverse factors for overall survival among patients with intermediate cytogenetics (Figure 1C). The expanded protein networks (Figure 1E) revealed an umbrella of proteins in other pathways associated with each of the five proteins, including, e.g. a negative correlation between VASP and apoptosis proteins (BAD, BCL2, AIFM1), which has not been reported before.ConclusionsWe developed and applied an AML-tailored procedure, SPA, to analyze hypoxia and angiogenesis clinical proteomic data. Using SPA, we were able to identify four AML subpopulations with two disease specific patterns, discover the dependency between cell lineage development and canonical patterns, and explore potential drug targets beyond hypoxia and angiogenesis that are associated with each pattern. We believe SPA could be applied broadly and greatly expedite the drug discovery process in leukemia. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.