Deep profiling of apoptotic pathways with mass cytometry identifies a synergistic drug combination for killing myeloma cells

Teh, Charis E.; Gong, Juanqin; Segal, David; Tan, Tania; Vandenberg, Cassandra J.; Fedele, Pasquale; Löw, Michael; Grigoriadis, George; Harrison, Simon; Strasser, Andreas; Roberts, Andrew W.; Huang, David C.S.; Nolan, Garry P.; Ko, Melissa E.

doi:10.1038/s41418-020-0498-z

Cited by 31 publications

(26 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We created a dataset based on 24 samples in total, consisting of peripheral blood mononuclear cell (PBMC) samples from three patients with chronic lymphocytic leukaemia (CLL) and PBMC from nine healthy controls (HC), each replicated across two batches of 12 samples ( Table 1 ). All samples were stained with a 31-antibody panel targeting 19 lineage ( Table 2 ) and 12 functional proteins ( Table 3 ) that were previously validated ( Teh et al, 2020 ). After processing the data (Methods), we applied an arcsinh-transformation defined as arcsinh (intensity/5) in all that follows.…”

Section: Resultsmentioning

confidence: 99%

Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets

Trussart

Teh

Tan

et al. 2020

eLife

Self Cite

View full text Add to dashboard Cite

Mass cytometry (CyTOF) is a technology that has revolutionised single cell biology. By detecting over 40 proteins on millions of single cells, CyTOF allows the characterisation of cell subpopulations in unprecedented detail. However most CyTOF studies require the integration of data from multiple CyTOF batches usually acquired on different days and possibly at different sites. To date, the integration of CyTOF datasets remains a challenge due to technical differences arising in multiple batches. To overcome this limitation, we developed an approach called CytofRUV for analysing multiple CyTOF batches which includes an R-Shiny application with diagnostics plots. CytofRUV can correct for batch effects and integrate data from large numbers of patients and conditions across batches, to confidently compare cellular changes and correlate these with clinically relevant outcomes.

show abstract

Section: Resultsmentioning

confidence: 99%

Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets

Trussart

Teh

Tan

et al. 2020

eLife

Self Cite

View full text Add to dashboard Cite

show abstract

“…CyTOF allows simultaneous interrogation of a wide array of cellular features including cell surface profiles 19 , cell cycle 20 , proliferation 21 , apoptosis 22 , metabolism 23 , phosphoproteins 24 , cytokine production 25 , transcription factors 26 and multiplexed RNA profiles 27 at single-cell resolution. Antibody staining variance, pipetting errors, detector drift between different samples on the same day and day-to-day variability of instrument performance are the main sources of technical variation.…”

Section: Discussionmentioning

confidence: 99%

Extended live-cell barcoding approach for multiplexed mass cytometry

Müftüoğlu

Liang

et al. 2021

Sci Rep

View full text Add to dashboard Cite

Sample barcoding is essential in mass cytometry analysis, since it can eliminate potential procedural variations, enhance throughput, and allow simultaneous sample processing and acquisition. Sample pooling after prior surface staining termed live-cell barcoding is more desirable than intracellular barcoding, where samples are pooled after fixation and permeabilization, since it does not depend on fixation-sensitive antigenic epitopes. In live-cell barcoding, the general approach uses two tags per sample out of a pool of antibodies paired with five palladium (Pd) isotopes in order to preserve appreciable signal-to-noise ratios and achieve higher yields after sample deconvolution. The number of samples that can be pooled in an experiment using live-cell barcoding is limited, due to weak signal intensities associated with Pd isotopes and the relatively low number of available tags. Here, we describe a novel barcoding technique utilizing 10 different tags, seven cadmium (Cd) tags and three Pd tags, with superior signal intensities that do not impinge on lanthanide detection, which enables enhanced pooling of samples with multiple experimental conditions and markedly enhances sample throughput.

show abstract

“…In recent years, new instrumentation and biological tools have facilitated dramatic updates to ex vivo readouts. These include the incorporation of high-throughput flow cytometry (Kuusanmaki et al 2020, Majumder et al 2019, Teh et al 2020) and imaging analysis ( Jacob et al 2016), both of which enable quantification of specific phenotypes on a single-cell level. These new techniques can then be combined with the multitude of highquality antibodies that are now available to organize cells into discrete biological populations as well as antibodies that can accurately distinguish between specific cell states (proliferation, death, activation) or measure drug impact on specific pathways (signaling, apoptosis, etc.).…”

Section: Evolving Readoutsmentioning

confidence: 99%

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

Tognon

Sears

Mills

et al. 2021

Annu. Rev. Cancer Biol.

View full text Add to dashboard Cite

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, 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 survey the history of ex vivo testing and the current state of the art for this field. We 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 consider the relative strengths and weaknesses of predicting drug activity across the broad biological context of cancer patients and tumor types. This includes 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. Expected final online publication date for the Annual Review of Cancer Biology, Volume 5 is March 4, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

show abstract

Deep profiling of apoptotic pathways with mass cytometry identifies a synergistic drug combination for killing myeloma cells

Cited by 31 publications

References 53 publications

Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets

Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets

Extended live-cell barcoding approach for multiplexed mass cytometry

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

Contact Info

Product

Resources

About