Proteomic Profiling of Acute Promyelocytic Leukemia Identifies Two Protein Signatures Associated with Relapse

Proteomic and phosphoproteomic landscapes of acute myeloid leukemia

We have developed a deep-scale proteome and phosphoproteome database from 44 representative acute myeloid leukemia (AML) patients from the LAML TCGA dataset and 6 healthy bone marrow-derived controls. After confirming data quality, we orthogonally validated several previously undescribed features of AML revealed by the proteomic data. We identified examples of posttranscriptionally regulated proteins both globally (ie, in all AML samples) and also in patients with recurrent AML driver mutations. For example, samples with IDH1/2 mutations displayed elevated levels of the 2-oxoglutarate-dependent histone demethylases KDM4A/B/C, despite no changes in messenger RNA levels for these genes; we confirmed this finding in vitro. In samples with NPMc mutations, we identified several nuclear importins with posttranscriptionally increased protein abundance and showed that they interact with NPMc but not wild-type NPM1. We identified 2 cell surface proteins (CD180 and MRC1/CD206) expressed on AML blasts of many patients (but not healthy CD34+ stem/progenitor cells) that could represent novel targets for immunologic therapies and confirmed these targets via flow cytometry. Finally, we detected nearly 30 000 phosphosites in these samples; globally, AML samples were associated with the abnormal phosphorylation of specific residues in PTPN11, STAT3, AKT1, and PRKCD. FLT3-TKD samples were associated with increased phosphorylation of activating tyrosines on the cytoplasmic Src-family tyrosine kinases FGR and HCK and related signaling proteins. PML-RARA-initiated AML samples displayed a unique phosphorylation signature, and TP53-mutant samples showed abundant phosphorylation of serine-183 on TP53 itself. This publicly available database will serve as a foundation for further investigations of protein dysregulation in AML pathogenesis.

Genetic and Epigenetic Signatures in Acute Promyelocytic Leukemia Treatment and Molecular Remission

Acute myeloid leukemia (AML) is an aggressive, heterogeneous group of malignancies with different clinical behaviors and different responses to therapy. For many types of cancer, finding cancer early makes it easier to treat. Identifying prognostic molecular markers and understanding their biology are the first steps toward developing novel diagnostic tools or therapies for patients with AML. In this study, we defined proteins and genes that can be used in the prognosis of different acute leukemia cases and found possible uses in diagnostics and therapy. We analyzed newly diagnosed acute leukemia cases positive for t (15; 17) (q22; q21) PML-RAR alpha, acute promyelocytic leukemia (APL). The samples of bone marrow cells were collected from patients at the diagnosis stage, as follow-up samples during standard treatment with all-trans retinoic acid, idarubicin, and mitoxantrone, and at the molecular remission. We determined changes in the expression of genes involved in leukemia cell growth, apoptosis, and differentiation. We observed that WT1, CALR, CAV1, and MYC genes’ expression in all APL patients with no relapse history was downregulated after treatment and could be potential markers associated with the pathology, thereby revealing the potential value of this approach for a better characterization of the prediction of APL outcomes.

Proteomic profiling based classification of CLL provides prognostication for modern therapy and identifies novel therapeutic targets

Protein expression for 384 total and post-translationally modified proteins was assessed in 871 CLL and MSBL patients and was integrated with clinical data to identify strategies for improving diagnostics and therapy, making this the largest CLL proteomics study to date. Proteomics identified six recurrent signatures that were highly prognostic of survival and time to first or second treatment at three levels: individual proteins, when grouped into 40 functionally related groups (PFGs), and systemically in signatures (SGs). A novel SG characterized by hairy cell leukemia like proteomics but poor therapy response was discovered. SG membership superseded other prognostic factors (Rai Staging, IGHV Status) and were prognostic for response to modern (BTK inhibition) and older CLL therapies. SGs and PFGs membership provided novel drug targets and defined optimal candidates for Watch and Wait vs. early intervention. Collectively proteomics demonstrates promise for improving classification, therapeutic strategy selection, and identifying novel therapeutic targets.

Reverse phase protein arrays in acute leukemia: investigative and methodological challenges

INTRODUCTION

Acute leukemia results from a series of mutational events that alter cell growth and proliferation. Mutations result in protein changes that orchestrate growth alterations characteristic of leukemia. Proteomics is a methodology appropriate for study of protein changes found in leukemia. The high-throughput reverse phase protein array (RPPA) technology is particularly well-suited for the assessment of protein changes in samples derived from clinical trials.

AREAS COVERED

This review discusses the technical, methodological, and analytical issues related to the successful development of acute leukemia RPPAs.

EXPERT COMMENTARY

To obtain representative protein sample lysates, samples should be prepared from freshly collected blood or bone marrow material. Variables such as sample shipment, transit time, and holding temperature only have minimal effects on protein expression. CellSave preservation tubes are preferred for cells collected after exposure to chemotherapy, and incorporation of standardized guidelines for antibody validation is recommended. A more systematic biological approach to analyze protein expression is desired, searching for recurrent patterns of protein expression that allow classification of patients into risk groups, or groups of patients that may be treated similarly. Comparing RPPA protein analysis between cell lines and primary samples shows that cell lines are not representative of patient proteomic patterns.

Targeted therapy in acute myeloid leukemia: current status and new insights from a proteomic perspective

Introduction: The biological heterogeneity of acute myeloid leukemia (AML) complicates personalized medicine. Individual prognosis is typically based on the presence of chromosomal and genetic lesions. Nevertheless, these classifications often lack a priori information about response to therapy. Since the protein expression landscape reflects the functional activity state of cells, we hypothesize that analyzing this can be used for the identification of protein activity markers to provide better risk stratification as well as may provide targeted therapeutic guidance in AML.Areas covered: Herein, we review recently new adopted drugs in the treatment for AML and discuss how quantitative proteomic techniques may contribute to better therapeutic selection in AML.Expert commentary: The net functional state of the cell is defined by the activity of protein within all the pathways that are active in the cell. Recognition of the proteomic profile of the leukemic blast could, therefore, complement current classification systems by providing a better a priori description of what pathways are important within a cell as a guide to the selection of therapy for the patient.

Proteomic Profiling of Acute Promyelocytic Leukemia Identifies Two Protein Signatures Associated with Relapse

PURPOSE

Acute promyelocytic leukemia (APL) is the most prognostically favorable subtype of Acute myeloid leukemia (AML). Defining the features that allow identification of APL patients likely to relapse after therapy remains challenging.

EXPERIMENTAL DESIGN

Proteomic profiling is performed on 20 newly diagnosed APL, 205 non-APL AML, and 10 normal CD34+ samples using Reverse Phase Protein Arrays probed with 230 antibodies.

RESULTS

Comparison between APL and non-APL AML samples identifies 8.3% of the proteins to be differentially expressed. Proteins higher expressed in APL are involved in the pro-apoptotic pathways or are linked to higher proliferation. The "MetaGalaxy" approach that considers proteins in relation to other assayed proteins stratifies the APL patients into two protein signatures. All of the relapse patients (n = 4/4) are in protein signature 2 (S2). Comparison of proteins between the signatures shows significant differences in relative expression for 38 proteins. Protein expression summary plots suggest less translational activity in combination with a less proliferative character for S2 compared to signature 1.

CONCLUSIONS AND CLINICAL RELEVANCE

This study provides a potential proteomic-based classification of APL patients that may be useful for risk stratification and therapeutic guidance. Validation in a larger independent cohort is required.