Determining therapeutic susceptibility in multiple myeloma by single-cell mass accumulation

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

Microfluidic active loading of single cells enables analysis of complex clinical specimens

A fundamental trade-off between flow rate and measurement precision limits performance of many single-cell detection strategies, especially for applications that require biophysical measurements from living cells within complex and low-input samples. To address this, we introduce ‘active loading’, an automated, optically-triggered fluidic system that improves measurement throughput and robustness by controlling entry of individual cells into a measurement channel. We apply active loading to samples over a range of concentrations (1–1000 particles μL[superscript −1]), demonstrate that measurement time can be decreased by up to 20-fold, and show theoretically that performance of some types of existing single-cell microfluidic devices can be improved by implementing active loading. Finally, we demonstrate how active loading improves clinical feasibility for acute, single-cell drug sensitivity measurements by deploying it to a preclinical setting where we assess patient samples from normal brain, primary and metastatic brain cancers containing a complex, difficult-to-measure mixture of confounding biological debris.National Cancer Institute (U.S.) (R01 CA170592)National Cancer Institute (U.S.) (R33 CA191143)National Cancer Institute (U.S.) (Cancer Center Support (Core) Grant P30-CA14051)Bridge Projec

Microfluidic active loading of single cells enables analysis of complex clinical specimens

A fundamental trade-off between flow rate and measurement precision limits performance of many single-cell detection strategies, especially for applications that require biophysical measurements from living cells within complex and low-input samples. To address this, we introduce ‘active loading’, an automated, optically-triggered fluidic system that improves measurement throughput and robustness by controlling entry of individual cells into a measurement channel. We apply active loading to samples over a range of concentrations (1–1000 particles μL[superscript −1]), demonstrate that measurement time can be decreased by up to 20-fold, and show theoretically that performance of some types of existing single-cell microfluidic devices can be improved by implementing active loading. Finally, we demonstrate how active loading improves clinical feasibility for acute, single-cell drug sensitivity measurements by deploying it to a preclinical setting where we assess patient samples from normal brain, primary and metastatic brain cancers containing a complex, difficult-to-measure mixture of confounding biological debris.National Cancer Institute (U.S.) (R01 CA170592)National Cancer Institute (U.S.) (R33 CA191143)National Cancer Institute (U.S.) (Cancer Center Support (Core) Grant P30-CA14051)Bridge Projec

Trisomy of a Down Syndrome Critical Region Globally Amplifies Transcription via HMGN1 Overexpression

Down syndrome (DS, trisomy 21) is associated with developmental abnormalities and increased leukemia risk. To reconcile chromatin alterations with transcriptome changes, we performed paired exogenous spike-in normalized RNA and chromatin immunoprecipitation sequencing in DS models. Absolute normalization unmasks global amplification of gene expression associated with trisomy 21. Overexpression of the nucleosome binding protein HMGN1 (encoded on chr21q22) recapitulates transcriptional changes seen with triplication of a Down syndrome critical region on distal chromosome 21, and HMGN1 is necessary for B cell phenotypes in DS models. Absolute exogenous-normalized chromatin immunoprecipitation sequencing (ChIP-Rx) also reveals a global increase in histone H3K27 acetylation caused by HMGN1. Transcriptional amplification downstream of HMGN1 is enriched for stage-specific programs of B cells and B cell acute lymphoblastic leukemia, dependent on the developmental cellular context. These data offer a mechanistic explanation for DS transcriptional patterns and suggest that further study of HMGN1 and RNA amplification in diverse DS phenotypes is warranted. How trisomy 21 contributes to Down syndrome phenotypes, including increased leukemia risk, is not well understood. Mowery et al. use per-cell normalization approaches to reveal global transcriptional amplification in Down syndrome models. HMGN1 overexpression is sufficient to induce these alterations and promotes lineage-associated transcriptional programs, signaling, and B cell progenitor phenotypes

Drug sensitivity of single cancer cells is predicted by changes in mass accumulation rate

Assays that can determine the response of tumor cells to cancer therapeutics could greatly aid the selection of drug regimens for individual patients. However, the utility of current functional assays is limited, and predictive genetic biomarkers are available for only a small fraction of cancer therapies. We found that the single-cell mass accumulation rate (MAR), profiled over many hours with a suspended microchannel resonator, accurately defined the drug sensitivity or resistance of glioblastoma and B-cell acute lymphocytic leukemia cells. MAR revealed heterogeneity in drug sensitivity not only between different tumors, but also within individual tumors and tumor-derived cell lines. MAR measurement predicted drug response using samples as small as 25 μl of peripheral blood while maintaining cell viability and compatibility with downstream characterization. MAR measurement is a promising approach for directly assaying single-cell therapeutic responses and for identifying cellular subpopulations with phenotypic resistance in heterogeneous tumors.United States. National Institutes of Health (R01 CA170592)United States. National Institutes of Health (R33 CA191143)National Cancer Institute (U.S.) (U54 CA143874)United States. National Institutes of Health (NIH/NIGMS T32 GM008334

Quantification of somatic mutation flow across individual cell division events by lineage sequencing

Mutation data reveal the dynamic equilibrium between DNA damage and repair processes in cells and are indispensable to the understanding of age-related diseases, tumor evolution, and the acquisition of drug resistance. However, available genome-wide methods have a limited ability to resolve rare somatic variants and the relationships between these variants. Here, we present lineage sequencing, a new genome sequencing approach that enables somatic event reconstruction by providing quality somatic mutation call sets with resolution as high as the single-cell level in subject lineages. Lineage sequencing entails sampling single cells from a population and sequencing subclonal sample sets derived from these cells such that knowledge of relationships among the cells can be used to jointly call variants across the sample set. This approach integrates data from multiple sequence libraries to support each variant and precisely assigns mutations to lineage segments. We applied lineage sequencing to a human colon cancer cell line with a DNA polymerase epsilon (POLE) proofreading deficiency (HT115) and a human retinal epithelial cell line immortalized by constitutive telomerase expression (RPE1). Cells were cultured under continuous observation to link observed single-cell phenotypes with single-cell mutation data. The high sensitivity, specificity, and resolution of the data provide a unique opportunity for quantitative analysis of variation in mutation rate, spectrum, and correlations among variants. Our data show that mutations arrive with nonuniform probability across sublineages and that DNA lesion dynamics may cause strong correlations between certain mutations.National Institute of Environmental Health Sciences (Core Center Grant P30-ES002109)National Institute of Allergy and Infectious Diseases (U.S.) (Grant R21AI110787

Microfluidic platform for characterizing TCR–pMHC interactions

The physical characteristics of the T cell receptor (TCR)-peptide-major histocompatibility complex (pMHC) interaction are known to play a central role in determining T cell function in the initial stages of the adaptive immune response. State-of-the-art assays can probe the kinetics of this interaction with single-molecularbond resolution, but this precision typically comes at the cost of low throughput, since the complexity of these measurements largely precludes "scaling up." Here, we explore the feasibility of detecting specific TCR-pMHC interactions by flowing T cells past immobilized pMHC and measuring the reduction in cell speed due to the mechanical force of the receptor-ligand interaction. To test this new fluidic measurement modality, we fabricated a microfluidic device in which pMHC-coated beads are immobilized in hydrodynamic traps along the length of a serpentine channel. As T cells flow past the immobilized beads, their change in speed is tracked via microscopy. We validated this approach using two model systems: primary CD8+ T cells from an OT-1 TCR transgenic mouse with beads conjugated with H-2Kb:SIINFEKL, and Jurkat T cells with beads conjugated with anti-CD3 and anti-CD28 antibodies.National Institutes of Health (U.S.) (U54 CA143874)National Institutes of Health (U.S.) (R21 AI110787

A microfluidic platform enabling single-cell RNA-seq of multigenerational lineages

We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multi-generational lineage tracking under controlled culture conditions. We use this platform to generate whole-transcriptome profiles of primary, activated murine CD8+ T-cell and lymphocytic leukemia cell line lineages. Here we report that both cell types have greater intra- than inter-lineage transcriptional similarity. For CD8+ T-cells, genes with functional annotation relating to lymphocyte differentiation and function—including Granzyme B—are enriched among the genes that demonstrate greater intra-lineage expression level similarity. Analysis of gene expression covariance with matched measurements of time since division reveals cell type-specific transcriptional signatures that correspond with cell cycle progression. We believe that the ability to directly measure the effects of lineage and cell cycle-dependent transcriptional profiles of single cells will be broadly useful to fields where heterogeneous populations of cells display distinct clonal trajectories, including immunology, cancer, and developmental biology.National Institutes of Health (U.S.) (Contract R21AI110787)National Cancer Institute (U.S.). Physical Sciences Oncology Center (U54CA143874)National Cancer Institute (U.S.) (Koch Institute Support (Core) Grant P30-CA14051)National Science Foundation (U.S.). Graduate Research FellowshipNational Institutes of Health (U.S.) (Ruth L. Kirschstein National Research Service Award F32CA1800586)Kinship Foundation. Searle Scholars ProgramBeckman Young Investigator ProgramNational Institutes of Health (U.S.) (New Innovator Award DP2 OD020839

High-throughput measurement of single-cell growth rates using serial microfluidic mass sensor arrays

Methods to rapidly assess cell growth would be useful for many applications, including drug susceptibility testing, but current technologies have limited sensitivity or throughput. Here we present an approach to precisely and rapidly measure growth rates of many individual cells simultaneously. We flow cells in suspension through a microfluidic channel with 10-12 resonant mass sensors distributed along its length, weighing each cell repeatedly over the 4-20 min it spends in the channel. Because multiple cells traverse the channel at the same time, we obtain growth rates for >60 cells/h with a resolution of 0.2 pg/h for mammalian cells and 0.02 pg/h for bacteria. We measure the growth of single lymphocytic cells, mouse and human T cells, primary human leukemia cells, yeast, Escherichia coli and Enterococcus faecalis. Our system reveals subpopulations of cells with divergent growth kinetics and enables assessment of cellular responses to antibiotics and antimicrobial peptides within minutes.United States. Army Research Office (Grant W911NF-09-D-0001)National Science Foundation (U.S.) (Grant 1129359)National Cancer Institute (U.S.) (Grant U54CA143874)National Cancer Institute (U.S.) (Grant P30-CA14051)National Cancer Institute (U.S.) (Grant R33-CA191143)National Institutes of Health (U.S.) (Grant T32-GM008334)National Institute of General Medical Sciences (U.S.) (Grant T32-GM008334