Massively parallel digital transcriptional profiling of single cells

Nature Communications, Journal Year: 2017, Volume and Issue: 8(1)

Published: Jan. 16, 2017

Abstract Characterizing the transcriptome of individual cells is fundamental to understanding complex biological systems. We describe a droplet-based system that enables 3′ mRNA counting tens thousands single per sample. Cell encapsulation, up 8 samples at time, takes place in ∼6 min, with ∼50% cell capture efficiency. To demonstrate system’s technical performance, we collected data from ∼250k across 29 samples. validated sensitivity and its ability detect rare populations using lines synthetic RNAs. profiled 68k peripheral blood mononuclear characterize large immune populations. Finally, used sequence variation determine host donor chimerism single-cell resolution bone marrow isolated transplant patients.

Language: Английский

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Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq

Science, Journal Year: 2016, Volume and Issue: 352(6282), P. 189 - 196

Published: April 7, 2016

To explore the distinct genotypic and phenotypic states of melanoma tumors, we applied single-cell RNA sequencing (RNA-seq) to 4645 single cells isolated from 19 patients, profiling malignant, immune, stromal, endothelial cells. Malignant within same tumor displayed transcriptional heterogeneity associated with cell cycle, spatial context, a drug-resistance program. In particular, all tumors harbored malignant two states, such that characterized by high levels MITF transcription factor also contained low elevated AXL kinase. Single-cell analyses suggested microenvironmental patterns, including cell-to-cell interactions. Analysis tumor-infiltrating T revealed exhaustion programs, their connection activation clonal expansion, variability across patients. Overall, begin unravel cellular ecosystem how genomics offers insights implications for both targeted immune therapies.

Language: Английский

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Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis

Cell, Journal Year: 2015, Volume and Issue: 162(1), P. 184 - 197

Published: June 18, 2015

Language: Английский

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Single-Cell Transcriptomic Analysis of Primary and Metastatic Tumor Ecosystems in Head and Neck Cancer

Cell, Journal Year: 2017, Volume and Issue: 171(7), P. 1611 - 1624.e24

Published: Nov. 30, 2017

Language: Английский

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Single-cell chromatin accessibility reveals principles of regulatory variation

Nature, Journal Year: 2015, Volume and Issue: 523(7561), P. 486 - 490

Published: June 17, 2015

Language: Английский

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The history and advances in cancer immunotherapy: understanding the characteristics of tumor-infiltrating immune cells and their therapeutic implications

Cellular and Molecular Immunology, Journal Year: 2020, Volume and Issue: 17(8), P. 807 - 821

Published: July 1, 2020

Abstract Immunotherapy has revolutionized cancer treatment and rejuvenated the field of tumor immunology. Several types immunotherapy, including adoptive cell transfer (ACT) immune checkpoint inhibitors (ICIs), have obtained durable clinical responses, but their efficacies vary, only subsets patients can benefit from them. Immune infiltrates in microenvironment (TME) been shown to play a key role development will affect outcomes patients. Comprehensive profiling tumor-infiltrating cells would shed light on mechanisms cancer–immune evasion, thus providing opportunities for novel therapeutic strategies. However, highly heterogeneous dynamic nature TME impedes precise dissection intratumoral cells. With recent advances single-cell technologies such as RNA sequencing (scRNA-seq) mass cytometry, systematic interrogation is feasible provide insights into functional diversities In this review, we outline progress particularly by focusing landmark studies characterization tumor-associated cells, summarize phenotypic connections with immunotherapy. We believe review could strengthen our understanding facilitate elucidation modulation progression, guide immunotherapies treatment.

Language: Английский

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An Integrative Model of Cellular States, Plasticity, and Genetics for Glioblastoma

Cell, Journal Year: 2019, Volume and Issue: 178(4), P. 835 - 849.e21

Published: July 18, 2019

Language: Английский

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Deep generative modeling for single-cell transcriptomics

Nature Methods, Journal Year: 2018, Volume and Issue: 15(12), P. 1053 - 1058

Published: Nov. 21, 2018

Language: Английский

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Metastatic colonization by circulating tumour cells

Nature, Journal Year: 2016, Volume and Issue: 529(7586), P. 298 - 306

Published: Jan. 1, 2016

Language: Английский

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Current best practices in single‐cell RNA‐seq analysis: a tutorial

Molecular Systems Biology, Journal Year: 2019, Volume and Issue: 15(6)

Published: June 1, 2019

Single-cell RNA-seq has enabled gene expression to be studied at an unprecedented resolution. The promise of this technology is attracting a growing user base for single-cell analysis methods. As more tools are becoming available, it increasingly difficult navigate landscape and produce up-to-date workflow analyse one's data. Here, we detail the steps typical analysis, including pre-processing (quality control, normalization, data correction, feature selection, dimensionality reduction) cell- gene-level downstream analysis. We formulate current best-practice recommendations these based on independent comparison studies. have integrated into workflow, which apply public dataset further illustrate how work in practice. Our documented case study can found https://www.github.com/theislab/single-cell-tutorial This review will serve as tutorial new entrants field, help established users update their pipelines.

Language: Английский

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