Project description:To identify genes responsible for the synergistic effect of DAC with Dex, we performed cDNA microarray analyses using cDNA prepared from Dex-resistant OPM1 cells treated with/without Dex, DAC or DAC+Dex.
Project description:Multiple myeloma (MM) progression is characterized by the seeding of cancer cells in different anatomic sites. To characterize this evolutionary process, we interrogated, by whole genome sequencing, 25 samples collected at autopsy from 4 patients with relapsed MM and an additional set of 125 whole exomes collected from 51 patients. Mutational signatures analysis showed how cytotoxic agents introduce hundreds of unique mutations in each surviving cancer cell, detectable by bulk sequencing only in cases of clonal expansion of a single cancer cell bearing the mutational signature. Thus, a unique, single-cell genomic barcode can link chemotherapy exposure to a discrete time window in a patient's life. We leveraged this concept to show that MM systemic seeding is accelerated at relapse and appears to be driven by the survival and subsequent expansion of a single myeloma cell following treatment with high-dose melphalan therapy and autologous stem cell transplant.
Project description:Multiple myeloma (MM) is accompanied by alterations to the normal plasma cell (PC) proteome, leading to changes to the tumor microenvironment and disease progression. There is a great need for understanding the consequences that lead to MM progression and for the discovery of new biomarkers that can aid clinical diagnostics and serve as targets for therapeutics. This study demonstrates the applicability of utilizing the single-cell high-definition liquid biopsy assay (HDSCA) and imaging mass cytometry to characterize the proteomic profile of myeloma. In our study, we analyzed ~87,000 cells from seven patient samples (bone marrow and peripheral blood) across the myeloma disease spectrum and utilized our multiplexed panel to characterize the expression of clinical markers for PC classification, additional potential therapeutic targets, and the tumor microenvironment cells. Our analysis showed BCMA, ICAM3 (CD50), CD221, and CS1 (SLAMF7) as the most abundantly expressed markers on PCs across all myeloma stages, with BCMA, ICAM3, and CD221 having significantly higher expression levels on disease versus precursor PCs. Additionally, we identify significantly elevated levels of expression for CD74, MUM1, CD229, CD44, IGLL5, Cyclin D1, UBA52, and CD317 on PCs from overt disease conditions compared to those from precursor states.
Project description:Multiple myeloma (MM), a malignancy of plasma cells, is characterized by widespread genomic heterogeneity and, consequently, differences in disease progression and drug response. Although recent large-scale sequencing studies have greatly improved our understanding of MM genomes, our knowledge about genomic structural variation in MM is attenuated due to the limitations of commonly used sequencing approaches. In this study, we present the application of optical mapping, a single-molecule, whole-genome analysis system, to discover new structural variants in a primary MM genome. Through our analysis, we have identified and characterized widespread structural variation in this tumor genome. Additionally, we describe our efforts toward comprehensive characterization of genome structure and variation by integrating our findings from optical mapping with those from DNA sequencing-based genomic analysis. Finally, by studying this MM genome at two time points during tumor progression, we have demonstrated an increase in mutational burden with tumor progression at all length scales of variation.
Project description:Objectives:New targets or strategies are needed to increase the success of immune checkpoint-based immunotherapy for multiple myeloma (MM). However, immune checkpoint signals in MM microenvironment have not been fully elucidated. Here, we aimed to have a broad overview of the different immune subsets and their immune checkpoint status, within the MM microenvironment, and to provide novel immunotherapeutic targets to treat MM patients. Methods:We performed immune checkpoint profiling of bone marrow (BM) samples from MM patients and healthy controls using mass cytometry. With high-dimensional single-cell analysis of 30 immune proteins containing 10 pairs of immune checkpoint axes in 0.55 million of BM cells, an immune landscape of MM was mapped. Results:We identified an abnormality of immune cell composition by demonstrating a significant increase in activated CD4 T, CD8 T, CD8+ natural killer T-like and NK cells in MM BM. Our data suggest a correlation between MM cells and immune checkpoint phenotypes and expand the view of MM immune signatures. Specifically, several critical immune checkpoints, such as programmed cell death 1 (PD-1)/PD ligand 2, galectin-9/T-cell immunoglobulin mucin-3, and inducible T-cell costimulator (ICOS)/ICOS ligand, on both MM and immune effector cells and a number of activated PD-1+ CD8 T cells lacking CD28 were distinguished in MM patients. Conclusion:A clear interaction between MM cells and the surrounding immune cells was established, leading to immune checkpoint dysregulation. The analysis of the immune landscape enhances our understanding of the MM immunological milieu and proposes novel targets for improving immune checkpoint blockade-based MM immunotherapy.
Project description:Multiple myeloma (MM) has benefited from significant advancements in treatment that have improved outcomes and reduced morbidity. However, the disease remains incurable and is characterized by high rates of drug resistance and relapse. Consequently, methods to select the most efficacious therapy are of great interest. Here we utilize a functional assay to assess the ex vivo drug sensitivity of single multiple myeloma cells based on measuring their mass accumulation rate (MAR). We show that MAR accurately and rapidly defines therapeutic susceptibility across human multiple myeloma cell lines to a gamut of standard-of-care therapies. Finally, we demonstrate that our MAR assay, without the need for extended culture ex vivo, correctly defines the response of nine patients to standard-of-care drugs according to their clinical diagnoses. This data highlights the MAR assay in both research and clinical applications as a promising tool for predicting therapeutic response using clinical samples.
Project description:Multiple myeloma (MM) remains an incurable disease, with a treatment-refractory state eventually developing in all patients. Constant clonal evolution and genetic heterogeneity of MM are a likely explanation for the emergence of drug-resistant disease. Monitoring of MM genomic evolution on therapy by serial bone marrow biopsy is unfortunately impractical because it involves an invasive and painful procedure. We describe how noninvasive and highly sensitive isolation and characterization of circulating tumor cells (CTCs) from peripheral blood at single-cell resolution recapitulate MM in the bone marrow. We demonstrate that CTCs provide the same genetic information as bone marrow MM cells and even reveal mutations with greater sensitivity than bone marrow biopsies in some cases. Single CTC RNA sequencing enables classification of MM and quantitative assessment of genes that are relevant for prognosis. We propose that the genomic characterization of CTCs should be included in clinical trials to follow the emergence of resistant subclones after MM therapy.