Single‐cell technologies are revolutionizing the approach to rare cells

Proserpio, Valentina; Lönnberg, Tapio

doi:10.1038/icb.2015.106

Cited by 70 publications

(53 citation statements)

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“…In particular, the ability to computationally cluster data from related cell populations could provide an in silico method to isolate data from rare exfoliated tumor cells (as compared to contaminant urothelial cells) [133][134][135] and could also indicate distinct subpopulations of cancerous cells that would likely benefit from treatment with a coordinated, concerted panel of drugs informed by knowledge of the characteristics of individual cells [136][137][138]. More broadly, application of single-cell transcriptomics to exfoliated bladder cancer cells from a large population of patients would provide a reference transcriptomic dataset of bladder cancer variants, useful for placing patients within a broader context of prior knowledge and for predicting efficacy of potential treatment paths based on historical data [139].…”

Section: Discussionmentioning

confidence: 99%

Microdevices for Non-Invasive Detection of Bladder Cancer

et al. 2017

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Bladder cancer holds the record for the highest lifetime cost on a per-patient basis. This is due to high recurrence rates, which necessitate invasive and costly long-term evaluation methods such as cystoscopy and imaging. Microfluidics is emerging as an important approach to contribute to initial diagnosis and follow-up, by enabling the precise manipulation of biological samples. Specifically, microdevices have been used for the isolation of cells or genetic material from blood samples, sparking significant interest as a versatile platform for non-invasive bladder cancer detection with voided urine. In this review, we revisit the methods of bladder cancer detection and describe various types of markers currently used for evaluation. We detail cutting-edge technologies and evaluate their merits in the detection, screening, and diagnosis of bladder cancer. Advantages of microscale devices over standard methods of detection, as well as their limitations, are provided. We conclude with a discussion of criteria for guiding microdevice development that could deepen our understanding of prognoses at the level of individual patients and the underlying biology of bladder cancer development. Collectively, the development and widespread application of improved microfluidic devices for bladder cancer could drive treatment breakthroughs and establish widespread, tangible outcomes on patients' long-term survival.

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Section: Discussionmentioning

confidence: 99%

Microdevices for Non-Invasive Detection of Bladder Cancer

et al. 2017

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“…The inherent strength of these approaches is in the ability to resolve cellular heterogeneity at great detail in an unbiased way. This obviously opens up many new possibilities in the analyses of rare cell populations, as we discuss in our contribution 1 …”

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confidence: 98%

Cutting‐edge single‐cell genomics and modelling in immunology

Proserpio

Lönnberg

2016

Immunol Cell Biol

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M ore than a decade after the beginning of the genomic era that has completely reshaped medical and life sciences, we are now entering a new equally revolutionary phase, the single-cell era. To date, most of our biological knowledge has been obtained by populationlevel studies, based on the fundamental assumption that every cell within a defined population contributes equally to its characteristics and behaviour. As our understanding of the dynamics of cell populations improves, it is becoming increasingly evident that this assumption is not true in many cases. An important example is presented by the immune system, the function of which can be profoundly influenced by the activity of relatively rare cells such as antigen-specific T and B cells. The development of a plethora of single-cell technologies during the last few years has provided us with powerful tools to finally tackle this issue in a systematic way. These technologies span from transcriptomics and proteomics to imaging approaches enabling the study of living cells over time.In this Special Feature, we present a series of reviews that highlight how advances in both instrumentation and computational methodologies are transforming the study of cell biology and immunology. The inherent strength of these approaches is in the ability to resolve cellular heterogeneity at great detail in an unbiased way. This obviously opens up many new possibilities in the analyses of rare cell populations, as we discuss in our contribution. 1 Importantly, single-cell resolution has also proved highly informative in studies on developmental and differentiation processes, during which cells can typically be found in a continuous gradient of transitional states. In the review by Cvejic, 2 these principles are illustrated in the study of haematopoiesis. A conceptually related process with tremendous immunological significance is the diversification of T and B lymphocytes into numerous functionally specialized effector and memory cell subpopulations. The first wave of research reports has already indicated the great promise of single-cell approaches in dissecting this heterogeneity. The dense data sets generated in such experiments also provide useful opportunities for generation and validation of quantitative models of cell behaviour. In the review by Gerritsen and Pandit, 3 the modelling approaches are discussed in the context of CD8 T-cell state transitions from naive to effector and memory states.When attempting to investigate the process of clonal expansion of lymphocytes, where a small number of precursor cells proliferate into expanded clones, single-cell live imaging can provide good insights into cell numbers, proliferation, death and differentiation rates.In their review, Polonsky et al. 4 explore the possible applications of live imaging of single cells within microwell arrays and discuss their significant advances with respect to population analysis.One limitation of most of the single-cell technologies mentioned above lies in the lack of information about cell mor...

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“…Further steps of stem cell genome analysis will also be to combine with single cell phenotypic analysis, and the connection between the phenotype and genotype of specific stem cells. [20][21][22] Stem cell-based analysis of the biology of a genetic variation currently provides tools for disease mechanism study, drug screening, and in some cases for the creation of replacement cells and organs. In many instances, the analysis is conducted in patient-derived stem cells, which represent the basis for personalized therapeutics.…”

Section: Genetic Traits Of Donors Are Represented In Stem Cellsmentioning

confidence: 99%