Mapping the proteogenomic landscape enables prediction of drug response in acute myeloid leukemia.

Acute myeloid leukemia is a poor-prognosis cancer commonly stratified by genetic aberrations, but these mutations are often heterogeneous and fail to consistently predict therapeutic response. Here, we combine transcriptomic, proteomic, and phosphoproteomic datasets with ex vivo drug sensitivity data to help understand the underlying pathophysiology of AML beyond mutations. We measure the proteome and phosphoproteome of 210 patients and combine them with genomic and transcriptomic measurements to identify four proteogenomic subtypes that complement existing genetic subtypes. We build a predictor to classify samples into subtypes and map them to a "landscape" that identifies specific drug response patterns. We then build a drug response prediction model to identify drugs that target distinct subtypes and validate our findings on cell lines representing various stages of quizartinib resistance. Our results show how multiomics data together with drug sensitivity data can inform therapy stratification and drug combinations in AML.

Mass Spectrometry-Based Proteogenomics: New Therapeutic Opportunities for Precision Medicine.

Proteogenomics refers to the integration of comprehensive genomic, transcriptomic, and proteomic measurements from the same samples with the goal of fully understanding the regulatory processes converting genotypes to phenotypes, often with an emphasis on gaining a deeper understanding of disease processes. Although specific genetic mutations have long been known to drive the development of multiple cancers, gene mutations alone do not always predict prognosis or response to targeted therapy. The benefit of proteogenomics research is that information obtained from proteins and their corresponding pathways provides insight into therapeutic targets that can complement genomic information by providing an additional dimension regarding the underlying mechanisms and pathophysiology of tumors. This review describes the novel insights into tumor biology and drug resistance derived from proteogenomic analysis while highlighting the clinical potential of proteogenomic observations and advances in technique and analysis tools.

Secondary fusion proteins as a mechanism of BCR::ABL1 kinase-independent resistance in chronic myeloid leukaemia.

Drug resistance in chronic myeloid leukaemia (CML) may occur via mutations in the causative BCR::ABL1 fusion or BCR::ABL1-independent mechanisms. We analysed 48 patients with BCR::ABL1-independent resistance for the presence of secondary fusion genes by RNA sequencing. We identified 10 of the most frequently detected secondary fusions in 21 patients. Validation studies, cell line models, gene expression analysis and drug screening revealed differences with respect to proliferation rate, differentiation and drug sensitivity. Notably, expression of RUNX1::MECOM led to resistance to ABL1 tyrosine kinase inhibitors in vitro. These results suggest secondary fusions contribute to BCR::ABL1-independent resistance and may be amenable to combined therapies.

Comprehensive molecular characterization of a rare case of Philadelphia chromosome-positive acute myeloid leukemia.

The Philadelphia chromosome (Ph) resulting from the t(9;22) translocation generates the oncogenic BCR::ABL1 fusion protein that is most commonly associated with chronic myeloid leukemia (CML) and Ph-positive (Ph+) acute lymphoblastic leukemia (ALL). There are also rare instances of patients (≤1%) with newly diagnosed acute myeloid leukemia (AML) that harbor this translocation (Paietta et al., Leukemia 12: 1881 [1998]; Keung et al., Leuk Res 28: 579 [2004]; Soupir et al., Am J Clin Pathol 127: 642 [2007]). AML with BCR::ABL has only recently been provisionally classified by the World Health Organization as a diagnostically distinct subtype of AML. Discernment from the extremely close differential diagnosis of myeloid blast crisis CML is challenging, largely relying on medical history rather than clinical characteristics (Arber et al., Blood 127: 2391 [2016]). To gain insight into the genomic features underlying the evolution of AML with BCR::ABL, we identified a patient presenting with a high-risk myelodysplastic syndrome that acquired a BCR::ABL alteration after a peripheral blood stem cell transplant. Serial samples were collected and analyzed using whole-exome sequencing, RNA-seq, and ex vivo functional drug screens. Persistent subclones were identified, both at diagnosis and at relapse, including an SF3B1p.Lys700Glu mutation that later cooccurred with an NRASp.Gly12Cys mutation. Functional ex vivo drug screening performed on primary patient cells suggested that combination therapies of ABL1 with RAS or PI3K pathway inhibitors could have augmented the patient's response throughout the course of disease. Together, our findings argue for the importance of genomic profiling and the potential value of ABL1 inhibitor-inclusive combination treatment strategies in patients with this rare disease.

Proteomic and phosphoproteomic measurements enhance ability to predict ex vivo drug response in AML.

Acute Myeloid Leukemia (AML) affects 20,000 patients in the US annually with a five-year survival rate of approximately 25%. One reason for the low survival rate is the high prevalence of clonal evolution that gives rise to heterogeneous sub-populations of leukemic cells with diverse mutation spectra, which eventually leads to disease relapse. This genetic heterogeneity drives the activation of complex signaling pathways that is reflected at the protein level. This diversity makes it difficult to treat AML with targeted therapy, requiring custom patient treatment protocols tailored to each individual's leukemia. Toward this end, the Beat AML research program prospectively collected genomic and transcriptomic data from over 1000 AML patients and carried out ex vivo drug sensitivity assays to identify genomic signatures that could predict patient-specific drug responses. However, there are inherent weaknesses in using only genetic and transcriptomic measurements as surrogates of drug response, particularly the absence of direct information about phosphorylation-mediated signal transduction. As a member of the Clinical Proteomic Tumor Analysis Consortium, we have extended the molecular characterization of this cohort by collecting proteomic and phosphoproteomic measurements from a subset of these patient samples (38 in total) to evaluate the hypothesis that proteomic signatures can improve the ability to predict response to 26 drugs in AML ex vivo samples. In this work we describe our systematic, multi-omic approach to evaluate proteomic signatures of drug response and compare protein levels to other markers of drug response such as mutational patterns. We explore the nuances of this approach using two drugs that target key pathways activated in AML: quizartinib (FLT3) and trametinib (Ras/MEK), and show how patient-derived signatures can be interpreted biologically and validated in cell lines. In conclusion, this pilot study demonstrates strong promise for proteomics-based patient stratification to assess drug sensitivity in AML.

Integrative analysis of drug response and clinical outcome in acute myeloid leukemia.

Acute myeloid leukemia (AML) is a cancer of myeloid-lineage cells with limited therapeutic options. We previously combined ex vivo drug sensitivity with genomic, transcriptomic, and clinical annotations for a large cohort of AML patients, which facilitated discovery of functional genomic correlates. Here, we present a dataset that has been harmonized with our initial report to yield a cumulative cohort of 805 patients (942 specimens). We show strong cross-cohort concordance and identify features of drug response. Further, deconvoluting transcriptomic data shows that drug sensitivity is governed broadly by AML cell differentiation state, sometimes conditionally affecting other correlates of response. Finally, modeling of clinical outcome reveals a single gene, PEAR1, to be among the strongest predictors of patient survival, especially for young patients. Collectively, this report expands a large functional genomic resource, offers avenues for mechanistic exploration and drug development, and reveals tools for predicting outcome in AML.

Identification and prioritization of myeloid malignancy germline variants in a large cohort of adult patients with AML.

Inherited predisposition to myeloid malignancies is more common than previously appreciated. We analyzed the whole-exome sequencing data of paired leukemia and skin biopsy samples from 391 adult patients from the Beat AML 1.0 consortium. Using the 2015 American College of Medical Genetics and Genomics (ACMG) guidelines for variant interpretation, we curated 1547 unique variants from 228 genes. The pathogenic/likely pathogenic (P/LP) germline variants were identified in 53 acute myeloid leukemia (AML) patients (13.6%) in 34 genes, including 6.39% (25/391) of patients harboring P/LP variants in genes considered clinically actionable (tier 1). 41.5% of the 53 patients with P/LP variants were in genes associated with the DNA damage response. The most frequently mutated genes were CHEK2 (8 patients) and DDX41 (7 patients). Pathogenic germline variants were also found in new candidate genes (DNAH5, DNAH9, DNMT3A, and SUZ12). No strong correlation was found between the germline mutational rate and age of AML onset. Among 49 patients who have a reported history of at least one family member affected with hematological malignancies, 6 patients harbored known P/LP germline variants and the remaining patients had at least one variant of uncertain significance, suggesting a need for further functional validation studies. Using CHEK2 as an example, we show that three-dimensional protein modeling can be one of the effective methodologies to prioritize variants of unknown significance for functional studies. Further, we evaluated an in silico approach that applies ACMG curation in an automated manner using the tool for assessment and (TAPES) prioritization in exome studies, which can minimize manual curation time for variants. Overall, our findings suggest a need to comprehensively understand the predisposition potential of many germline variants in order to enable closer monitoring for disease management and treatment interventions for affected patients and families.

Evaluation of Differential Peptide Loading on Tandem Mass Tag-Based Proteomic and Phosphoproteomic Data Quality.

Global and phosphoproteome profiling has demonstrated great utility for the analysis of clinical specimens. One barrier to the broad clinical application of proteomic profiling is the large amount of biological material required, particularly for phosphoproteomics─currently on the order of 25 mg wet tissue weight. For hematopoietic cancers such as acute myeloid leukemia (AML), the sample requirement is ≥10 million peripheral blood mononuclear cells (PBMCs). Across large study cohorts, this requirement will exceed what is obtainable for many individual patients/time points. For this reason, we were interested in the impact of differential peptide loading across multiplex channels on proteomic data quality. To achieve this, we tested a range of channel loading amounts (approximately the material obtainable from 5E5, 1E6, 2.5E6, 5E6, and 1E7 AML patient cells) to assess proteome coverage, quantification precision, and peptide/phosphopeptide detection in experiments utilizing isobaric tandem mass tag (TMT) labeling. As expected, fewer missing values were observed in TMT channels with higher peptide loading amounts compared to lower loadings. Moreover, channels with a lower loading have greater quantitative variability than channels with higher loadings. A statistical analysis showed that decreased loading amounts result in an increase in the type I error rate. We then examined the impact of differential loading on the detection of known differences between distinct AML cell lines. Similar patterns of increased data missingness and higher quantitative variability were observed as loading was decreased resulting in fewer statistical differences; however, we found good agreement in features identified as differential, demonstrating the value of this approach.

Ex Vivo Analysis of Primary Tumor Specimens for Evaluation of Cancer Therapeutics.

The use of ex vivo drug sensitivity testing to predict drug activity in individual patients has been actively explored for almost 50 years without delivering a generally useful predictive capability. However, extended failure should not be an indicator of futility. This is especially true in cancer research where ultimate success is often preceded by less successful attempts. For example, both immune- and genetic-based targeted therapies for cancer underwent numerous failed attempts before biological understanding, improved targets, and optimized drug development matured to facilitate an arsenal of transformational drugs. Similarly, the concept of directly assessing drug sensitivity of primary tumor biopsies-and the use of this information to help direct therapeutic approaches-has a long history with a definitive learning curve. In this review, we will survey the history of ex vivo testing as well as the current state of the art for this field. We will present an update on methodologies and approaches, describe the use of these technologies to test cutting-edge drug classes, and describe an increasingly nuanced understanding of tumor types and models for which this strategy is most likely to succeed. We will consider the relative strengths and weaknesses of predicting drug activity across the broad biological context of cancer patients and tumor types. This will include an analysis of the potential for ex vivo drug sensitivity testing to accurately predict drug activity within each of the biological hallmarks of cancer pathogenesis.

Bayesian multi-source regression and monocyte-associated gene expression predict BCL-2 inhibitor resistance in acute myeloid leukemia.

The FDA recently approved eight targeted therapies for acute myeloid leukemia (AML), including the BCL-2 inhibitor venetoclax. Maximizing efficacy of these treatments requires refining patient selection. To this end, we analyzed two recent AML studies profiling the gene expression and ex vivo drug response of primary patient samples. We find that ex vivo samples often exhibit a general sensitivity to (any) drug exposure, independent of drug target. We observe that this "general response across drugs" (GRD) is associated with FLT3-ITD mutations, clinical response to standard induction chemotherapy, and overall survival. Further, incorporating GRD into expression-based regression models trained on one of the studies improved their performance in predicting ex vivo response in the second study, thus signifying its relevance to precision oncology efforts. We find that venetoclax response is independent of GRD but instead show that it is linked to expression of monocyte-associated genes by developing and applying a multi-source Bayesian regression approach. The method shares information across studies to robustly identify biomarkers of drug response and is broadly applicable in integrative analyses.

The AML microenvironment catalyzes a stepwise evolution to gilteritinib resistance.

Our study details the stepwise evolution of gilteritinib resistance in FLT3-mutated acute myeloid leukemia (AML). Early resistance is mediated by the bone marrow microenvironment, which protects residual leukemia cells. Over time, leukemia cells evolve intrinsic mechanisms of resistance, or late resistance. We mechanistically define both early and late resistance by integrating whole-exome sequencing, CRISPR-Cas9, metabolomics, proteomics, and pharmacologic approaches. Early resistant cells undergo metabolic reprogramming, grow more slowly, and are dependent upon Aurora kinase B (AURKB). Late resistant cells are characterized by expansion of pre-existing NRAS mutant subclones and continued metabolic reprogramming. Our model closely mirrors the timing and mutations of AML patients treated with gilteritinib. Pharmacological inhibition of AURKB resensitizes both early resistant cell cultures and primary leukemia cells from gilteritinib-treated AML patients. These findings support a combinatorial strategy to target early resistant AML cells with AURKB inhibitors and gilteritinib before the expansion of pre-existing resistance mutations occurs.

Matched Targeted Therapy for Pediatric Patients with Relapsed, Refractory, or High-Risk Leukemias: A Report from the LEAP Consortium.

Despite a remarkable increase in the genomic profiling of cancer, integration of genomic discoveries into clinical care has lagged behind. We report the feasibility of rapid identification of targetable mutations in 153 pediatric patients with relapsed/refractory or high-risk leukemias enrolled on a prospective clinical trial conducted by the LEAP Consortium. Eighteen percent of patients had a high confidence Tier 1 or 2 recommendation. We describe clinical responses in the 14% of patients with relapsed/refractory leukemia who received the matched targeted therapy. Further, in order to inform future targeted therapy for patients, we validated variants of uncertain significance, performed ex vivo drug-sensitivity testing in patient leukemia samples, and identified new combinations of targeted therapies in cell lines and patient-derived xenograft models. These data and our collaborative approach should inform the design of future precision medicine trials. SIGNIFICANCE: Patients with relapsed/refractory leukemias face limited treatment options. Systematic integration of precision medicine efforts can inform therapy. We report the feasibility of identifying targetable mutations in children with leukemia and describe correlative biology studies validating therapeutic hypotheses and novel mutations.See related commentary by Bornhauser and Bourquin, p. 1322.This article is highlighted in the In This Issue feature, p. 1307.

NT157, an IGF1R-IRS1/2 inhibitor, exhibits antineoplastic effects in pre-clinical models of chronic myeloid leukemia.

Chronic myeloid leukemia (CML) is successfully treated with BCR-ABL1 tyrosine kinase inhibitors, but a significant percentage of patients develop resistance. Insulin receptor substrate 1 (IRS1) has been shown to constitutively associate with BCR-ABL1, and IRS1-specific silencing leads to antineoplastic effects in CML cell lines. Here, we characterized the efficacy of NT157, a pharmacological inhibitor of IGF1R-IRS1/2, in CML cells and observed significantly reduced cell viability and proliferation, accompanied by induction of apoptosis. In human K562 cells and in murine Ba/F3 cells, engineered to express either wild-type BCR-ABL1 or the imatinib-resistant BCR-ABL1T315I mutant, NT157 inhibited BCR-ABL1, IGF1R, IRS1/2, PI3K/AKT/mTOR, and STAT3/5 signaling, increased CDKN1A, FOS and JUN tumor suppressor gene expression, and reduced MYC and BCL2 oncogenes. NT157 significantly reduced colony formation of human primary CML cells with minimal effect on normal hematopoietic cells. Exposure of primary CML cells harboring BCR-ABL1T315I to NT157 resulted in increased apoptosis, reduced cell proliferation and decreased phospho-CRKL levels. In conclusion, NT157 has antineoplastic effects on BCR-ABL1 leukemogenesis, independent of T315I mutational status.

Genomic markers of midostaurin drug sensitivity in FLT3 mutated and FLT3 wild-type acute myeloid leukemia patients.

Acute myeloid leukemia (AML) is a heterogeneous malignancy with the most common genomic alterations in NPM1, DNMT3A, and FLT3. Midostaurin was the first FLT3 inhibitor FDA approved for AML and is standard of care for FLT3 mutant patients undergoing induction chemotherapy [1, 2]. As there is a spectrum of response, we hypothesized that biological factors beyond FLT3 could play a role in drug sensitivity and that select FLT3-ITD negative samples may also demonstrate sensitivity. Thus, we aimed to identify features that would predict response to midostaurin in FLT3 mutant and wild-type samples. We performed an ex vivo drug sensitivity screen on primary and relapsed AML samples with corresponding targeted sequencing and RNA sequencing. We observed a correlation between FLT3-ITD mutations and midostaurin sensitivity as expected and observed KRAS and TP53 mutations correlating with midostaurin resistance in FLT3-ITD negative samples. Further, we identified genes differentially expressed in sensitive vs. resistant samples independent of FLT3-ITD status. Within FLT3-ITD mutant samples, over-expression of RGL4, oncogene and regulator of the Ras-Raf-MEK-ERK cascade, distinguished resistant from sensitive samples. Overall, this study highlights the complexity underlying midostaurin response. And, our results suggest that therapies that target both FLT3 and MAPK/ERK signaling may help circumvent some cases of resistance.

Reversible suppression of T cell function in the bone marrow microenvironment of acute myeloid leukemia.

Acute myeloid leukemia (AML) is the most common acute leukemia in adults, with approximately four new cases per 100,000 persons per year. Standard treatment for AML consists of induction chemotherapy with remission achieved in 50 to 75% of cases. Unfortunately, most patients will relapse and die from their disease, as 5-y survival is roughly 29%. Therefore, other treatment options are urgently needed. In recent years, immune-based therapies have led to unprecedented rates of survival among patients with some advanced cancers. Suppression of T cell function in the tumor microenvironment is commonly observed and may play a role in AML. We found that there is a significant association between T cell infiltration in the bone marrow microenvironment of newly diagnosed patients with AML and increased overall survival. Functional studies aimed at establishing the degree of T cell suppression in patients with AML revealed impaired T cell function in many patients. In most cases, T cell proliferation could be restored by blocking the immune checkpoint molecules PD-1, CTLA-4, or TIM3. Our data demonstrate that AML establishes an immune suppressive environment in the bone marrow, in part through T cell checkpoint function.

Discovery and characterization of targetable NTRK point mutations in hematologic neoplasms.

Much of what is known about the neurotrophic receptor tyrosine kinase (NTRK) genes in cancer was revealed through identification and characterization of activating Trk fusions across many tumor types. A resurgence of interest in these receptors has emerged owing to the realization that they are promising therapeutic targets. The remarkable efficacy of pan-Trk inhibitors larotrectinib and entrectinib in clinical trials led to their accelerated, tissue-agnostic US Food and Drug Administration (FDA) approval for adult and pediatric patients with Trk-driven solid tumors. Despite our enhanced understanding of Trk biology in solid tumors, the importance of Trk signaling in hematological malignancies is underexplored and warrants further investigation. Herein, we describe mutations in NTRK2 and NTRK3 identified via deep sequencing of 185 patients with hematological malignancies. Ten patients contained a point mutation in NTRK2 or NTRK3; among these, we identified 9 unique point mutations. Of these 9 mutations, 4 were oncogenic (NTRK2A203T, NTRK2R458G, NTRK3E176D, and NTRK3L449F), determined via cytokine-independent cellular assays. Our data demonstrate that these mutations have transformative potential to promote downstream survival signaling and leukemogenesis. Specifically, the 3 mutations located within extracellular (ie, NTRK2A203T and NTRK3E176D) and transmembrane (ie, NTRK3L449F) domains increased receptor dimerization and cell-surface abundance. The fourth mutation, NTRK2R458G, residing in the juxtamembrane domain, activates TrkB via noncanonical mechanisms that may involve altered interactions between the mutant receptor and lipids in the surrounding environment. Importantly, these 4 activating mutations can be clinically targeted using entrectinib. Our findings contribute to ongoing efforts to define the mutational landscape driving hematological malignancies and underscore the utility of FDA-approved Trk inhibitors for patients with aggressive Trk-driven leukemias.