Phenotypic and functional characterization of a bortezomib-resistant multiple myeloma cell line by flow and mass cytometry

CD69 marks a subpopulation of acute myeloid leukemia with enhanced colony forming capacity and a unique signaling activation state

In acute myeloid leukemia (AML), leukemia stem cells (LSCs) have self-renewal potential and are responsible for relapse. We previously showed that, in Mll-AF9/NRASG12V murine AML, CD69 expression marks an LSC-enriched subpopulation with enhanced in vivo self-renewal capacity. Here, we used CyTOF to define activated signaling pathways in LSC subpopulations in Mll-AF9/NRASG12V AML. Furthermore, we compared the signaling activation states of CD69High and CD36High subsets of primary human AML. The human CD69High subset expresses low levels of Ki67 and high levels of NFκB and pMAPKAPKII. Additionally, the human CD69High AML subset also has enhanced colony-forming capacity. We applied Bayesian network modeling to compare the global signaling network within the human AML subsets. We find that distinct signaling states, distinguished by NFκB and pMAPKAPKII levels, correlate with divergent functional subsets, defined by CD69 and CD36 expression, in human AML. Targeting NFκB with proteasome inhibition diminished colony formation.

Single-cell technologies in multiple myeloma: new insights into disease pathogenesis and translational implications

Multiple myeloma (MM) is a hematological malignancy characterized by clonal proliferation of plasma cells. Although therapeutic advances have been made to improve clinical outcomes and to prolong patients' survival in the past two decades, MM remains largely incurable. Single-cell sequencing (SCS) is a powerful method to dissect the cellular and molecular landscape at single-cell resolution, instead of providing averaged results. The application of single-cell technologies promises to address outstanding questions in myeloma biology and has revolutionized our understanding of the inter- and intra-tumor heterogeneity, tumor microenvironment, and mechanisms of therapeutic resistance in MM. In this review, we summarize the recently developed SCS methodologies and latest MM research progress achieved by single-cell profiling, including information regarding the cancer and immune cell landscapes, tumor heterogeneities, underlying mechanisms and biomarkers associated with therapeutic response and resistance. We also discuss future directions of applying transformative SCS approaches with contribution to clinical translation.

Spatially resolved phosphoproteomics reveals fibroblast growth factor receptor recycling-driven regulation of autophagy and survival

Receptor Tyrosine Kinase (RTK) endocytosis-dependent signalling drives cell proliferation and motility during development and adult homeostasis, but is dysregulated in diseases, including cancer. The recruitment of RTK signalling partners during endocytosis, specifically during recycling to the plasma membrane, is still unknown. Focusing on Fibroblast Growth Factor Receptor 2b (FGFR2b) recycling, we reveal FGFR signalling partners proximal to recycling endosomes by developing a Spatially Resolved Phosphoproteomics (SRP) approach based on APEX2-driven biotinylation followed by phosphorylated peptides enrichment. Combining this with traditional phosphoproteomics, bioinformatics, and targeted assays, we uncover that FGFR2b stimulated by its recycling ligand FGF10 activates mTOR-dependent signalling and ULK1 at the recycling endosomes, leading to autophagy suppression and cell survival. This adds to the growing importance of RTK recycling in orchestrating cell fate and suggests a therapeutically targetable vulnerability in ligand-responsive cancer cells. Integrating SRP with other systems biology approaches provides a powerful tool to spatially resolve cellular signalling.

Prognostic significance of CD56 antigen in newly diagnosed multiple myeloma: A real-world retrospective study

The prognostic value of plasma cell CD56 expression of patients with multiple myeloma (MM) has been reported in many studies, but the results are controversial. This study aimed to examine the prognostic significance of CD56 in MM patients. Eighty seven patients with newly diagnosed MM were enrolled in this study, and their clinical characteristics, immunophenotypes, and cytogenetics were retrospectively analyzed to explore the prognostic significance of CD56 expression. Multiparameter flow cytometry was used to detect MM in bone marrow samples from all patients. Patients were divided into 2 groups based on whether they expressed CD56: CD56 + group and CD56 - group. After 4 cycles of chemotherapy, the overall response rate of the CD56 - patients was lower than that of the CD56 + patients (60.0% vs 81.1%, P = .036). Survival analysis showed that the median progression-free survival (PFS) was 10 months for the CD56 - group and 27 months for the CD56 + group (P = .007). The median overall survival (OS) of patients for the CD56 - group was 25 months versus not reached in the CD56 + group (P = .010). In addition, among the high-risk patients detected by fluorescence in situ hybridization (FISH), the median PFS was 4 months for the CD56 - group and 16 months for the CD56 + group (P = .012). The median OS of the CD56 + group and CD56 - group was 36 months and 15 months, respectively, with statistically significant differences (P = .017). Our study confirmed that CD56 - patients with MM had a worse prognosis than that of CD56 + patients with MM. Among the patients with ≥ 2 high-risk cytogenetics, the existence of the CD56 negativity can further identify MM patients with poor PFS and OS.

The surfaceome of multiple myeloma cells suggests potential immunotherapeutic strategies and protein markers of drug resistance

The myeloma surface proteome (surfaceome) determines tumor interaction with the microenvironment and serves as an emerging arena for therapeutic development. Here, we use glycoprotein capture proteomics to define the myeloma surfaceome at baseline, in drug resistance, and in response to acute drug treatment. We provide a scoring system for surface antigens and identify CCR10 as a promising target in this disease expressed widely on malignant plasma cells. We engineer proof-of-principle chimeric antigen receptor (CAR) T-cells targeting CCR10 using its natural ligand CCL27. In myeloma models we identify proteins that could serve as markers of resistance to bortezomib and lenalidomide, including CD53, CD10, EVI2B, and CD33. We find that acute lenalidomide treatment increases activity of MUC1-targeting CAR-T cells through antigen upregulation. Finally, we develop a miniaturized surface proteomic protocol for profiling primary plasma cell samples with low inputs. These approaches and datasets may contribute to the biological, therapeutic, and diagnostic understanding of myeloma.

secDrug: a pipeline to discover novel drug combinations to kill drug-resistant multiple myeloma cells using a greedy set cover algorithm and single-cell multi-omics

Multiple myeloma, the second-most common hematopoietic malignancy in the United States, still remains an incurable disease with dose-limiting toxicities and resistance to primary drugs like proteasome inhibitors (PIs) and Immunomodulatory drugs (IMiDs).We have created a computational pipeline that uses pharmacogenomics data-driven optimization-regularization/greedy algorithm to predict novel drugs ("secDrugs") against drug-resistant myeloma. Next, we used single-cell RNA sequencing (scRNAseq) as a screening tool to predict top combination candidates based on the enrichment of target genes. For in vitro validation of secDrugs, we used a panel of human myeloma cell lines representing drug-sensitive, innate/refractory, and acquired/relapsed PI- and IMiD resistance. Next, we performed single-cell proteomics (CyTOF or Cytometry time of flight) in patient-derived bone marrow cells (ex vivo), genome-wide transcriptome analysis (bulk RNA sequencing), and functional assays like CRISPR-based gene editing to explore molecular pathways underlying secDrug efficacy and drug synergy. Finally, we developed a universally applicable R-software package for predicting novel secondary therapies in chemotherapy-resistant cancers that outputs a list of the top drug combination candidates with rank and confidence scores.Thus, using 17AAG (HSP90 inhibitor) + FK866 (NAMPT inhibitor) as proof of principle secDrugs, we established a novel pipeline to introduce several new therapeutic options for the management of PI and IMiD-resistant myeloma.

Mass Cytometry in Hematologic Malignancies: Research Highlights and Potential Clinical Applications

Recent advances in global gene sequencing technologies and the effect they have had on disease diagnosis, therapy, and research have fueled interest in technologies capable of more broadly profiling not only genes but proteins, metabolites, cells, and almost any other component of biological systems. Mass cytometry is one such technology, which enables simultaneous characterization of over 40 parameters per cell, significantly more than can be achieved by even the most state-of-the-art flow cytometers. This mini-review will focus on how mass cytometry has been utilized to help advance the field of neoplastic hematology. Common themes among published studies include better defining lineage sub-populations, improved characterization of tumor microenvironments, and profiling intracellular signaling across multiple pathways simultaneously in various cell types. Reviewed studies highlight potential applications for disease diagnosis, prognostication, response to therapy, measurable residual disease analysis, and identifying new therapies.

Unraveling the Complexity of the Cancer Microenvironment With Multidimensional Genomic and Cytometric Technologies

Cancers are characterized by extensive heterogeneity that occurs intratumorally, between lesions, and across patients. To study cancer as a complex biological system, multidimensional analyses of the tumor microenvironment are paramount. Single-cell technologies such as flow cytometry, mass cytometry, or single-cell RNA-sequencing have revolutionized our ability to characterize individual cells in great detail and, with that, shed light on the complexity of cancer microenvironments. However, a key limitation of these single-cell technologies is the lack of information on spatial context and multicellular interactions. Investigating spatial contexts of cells requires the incorporation of tissue-based techniques such as multiparameter immunofluorescence, imaging mass cytometry, or in situ detection of transcripts. In this Review, we describe the rise of multidimensional single-cell technologies and provide an overview of their strengths and weaknesses. In addition, we discuss the integration of transcriptomic, genomic, epigenomic, proteomic, and spatially-resolved data in the context of human cancers. Lastly, we will deliberate on how the integration of multi-omics data will help to shed light on the complex role of cell types present within the human tumor microenvironment, and how such system-wide approaches may pave the way toward more effective therapies for the treatment of cancer.

Tracking myeloma tumor DNA in peripheral blood

Over the past years, the emergence of liquid biopsy technologies has dramatically expanded our ability to assess multiple myeloma without the need for invasive sampling. Interrogation of cell-free DNA from the peripheral blood recapitulates the mutational landscape at excellent concordance with matching bone marrow aspirates. It can quantify disease burden and identify previously undetected resistance mechanisms which may inform clinical management in real-time. The convenience of sample acquisition and storage provides strong procedural benefits over currently available testing. Further investigations will have to define the role of cell-free DNA as a diagnostic measure by determining clinically relevant tumor thresholds in comparison to existing routine parameters. This review presents an overview of currently available assays and discusses the clinical value, potential and limitations of cell-free DNA technologies for the assessment of this challenging disease.

The future of myeloma precision medicine: integrating the compendium of known drug resistance mechanisms with emerging tumor profiling technologies

Multiple myeloma (MM) is a hematologic malignancy that is considered mostly incurable in large part due to the inability of standard of care therapies to overcome refractory disease and inevitable drug-resistant relapse. The post-genomic era has been a productive period of discovery where modern sequencing methods have been applied to large MM patient cohorts to modernize our current perception of myeloma pathobiology and establish an appreciation for the vast heterogeneity that exists between and within MM patients. Numerous pre-clinical studies conducted in the last two decades have unveiled a compendium of mechanisms by which malignant plasma cells can escape standard therapies, many of which have potentially quantifiable biomarkers. Exhaustive pre-clinical efforts have evaluated countless putative anti-MM therapeutic agents and many of these have begun to enter clinical trial evaluation. While the palette of available anti-MM therapies is continuing to expand it is also clear that malignant plasma cells still have mechanistic avenues by which they can evade even the most promising new therapies. It is therefore becoming increasingly clear that there is an outstanding need to develop and employ precision medicine strategies in MM management that harness emerging tumor profiling technologies to identify biomarkers that predict efficacy or resistance within an individual's sub-clonally heterogeneous tumor. In this review we present an updated overview of broad classes of therapeutic resistance mechanisms and describe selected examples of putative biomarkers. We also outline several emerging tumor profiling technologies that have the potential to accurately quantify biomarkers for therapeutic sensitivity and resistance at genomic, transcriptomic and proteomic levels. Finally, we comment on the future of implementation for precision medicine strategies in MM and the clear need for a paradigm shift in clinical trial design and disease management.

Mass cytometry: a powerful tool for dissecting the immune landscape

Advancement in methodologies for single cell analysis has historically been a major driver of progress in immunology. Currently, high dimensional flow cytometry, mass cytometry and various forms of single cell sequencing-based analysis methods are being widely adopted to expose the staggering heterogeneity of immune cells in many contexts. Here, we focus on mass cytometry, a form of flow cytometry that allows for simultaneous interrogation of more than 40 different marker molecules, including cytokines and transcription factors, without the need for spectral compensation. We argue that mass cytometry occupies an important niche within the landscape of single-cell analysis platforms that enables the efficient and in-depth study of diverse immune cell subsets with an ability to zoom-in on myeloid and lymphoid compartments in various tissues in health and disease. We further discuss the unique features of mass cytometry that are favorable for combining multiplex peptide-MHC multimer technology and phenotypic characterization of antigen specific T cells. By referring to recent studies revealing the complexities of tumor immune infiltrates, we highlight the particular importance of this technology for studying cancer in the context of cancer immunotherapy. Finally, we provide thoughts on current technical limitations and how we imagine these being overcome.

Comprehensive characterization of circulating and bone marrow-derived multiple myeloma cells at minimal residual disease

The presence or absence of minimal residual disease (MRD) in patients with multiple myeloma (MM) has emerged as a useful marker to determine the depth of remission. MRD negativity as an endpoint has been shown to be associated with improved progression-free survival in many studies. MRD detection is therefore part of numerous clinical trial protocols for MM. At the present time, two methodologies are most widely accepted for MRD detection: (1) multicolor flow cytometry and (2) next-generation sequencing-based clonotype detection. While both of those methodologies enable accurate quantification of MRD in the bone marrow (BM), with sensitivity as low as 10^-5 to 10^-6, there are several limitations to these methods. First, these approaches reveal the presence or absence of MRD but provide limited molecular information about MM. More comprehensive characterization of MM cells at the MRD stage may identify molecular mechanisms of drug resistance. Second, MRD detection in the BM is typically performed at one time point only, but more frequent detection may define the duration of the MRD status and thus refine its prognostic value. Third, less-invasive approaches that avoid the discomfort and risk associated with BM biopsy would be highly desirable, especially in elderly or frail patients. "Liquid biopsy" for the detection and characterization of circulating MM cells may address these issues. Although MRD detection in the peripheral blood at the same sensitivity as in the BM may be challenging, the identification of patients who do not achieve MRD negativity might reduce the need for BM biopsies. Here, we give an overview of approaches that have been described to detect and characterize MM cells when they occur at very low frequencies in the peripheral blood or in the BM, emphasizing recently described next-generation sequencing approaches for more comprehensive characterization of circulating MM cells.

Integrated functional and mass spectrometry-based flow cytometric phenotyping to describe the immune microenvironment in acute myeloid leukemia

A hallmark of the development of cancer is its ability to avoid detection and elimination by the immune system. There are many identified mechanisms of this immune evasion that can be measured both phenotypically and functionally. Functional studies directly show the ability of the tumor microenvironment to suppress immune responses, typically measured as lymphocyte proliferation, cytokine production or killing ability. While a direct measurement of function is ideal, these assays require ex vivo activation which may not accurately mimic in vivo conditions. Phenotypic assays can directly measure the distribution and activation of immune cell types rapidly after isolation, preserving the conditions present in the patient. While conventional flow cytometry is a rapid and well established assay, it currently allows for measurement of only 12-14 parameters. Mass spectrometry-based flow cytometry, or CyTOF, offers the ability to measure 3-fold more parameters than conventional optical-based modalities providing an advantage in depth of analysis that can be crucial for precious human samples. The goal of this report is to describe the system our group has developed to measure both the phenotype and function of immune cells in the bone marrow of patients with acute myeloid leukemia. We hope to explain our system in the context of previous studies aimed at measuring immune status in tumors and to inform the reader as to some experimental approaches our group has found useful in developing the basic data required to rationally pursue immune-based therapies for patients with cancer.