Hydro-Seq enables contamination-free high-throughput single-cell RNA-sequencing for circulating tumor cells

Cheng, Yu; Chen, Yu‐Chih; Lin, Eric; Brien, Riley; Jung, Seungwon; Chen, Yuting; Lee, Wonchoel; Hao, Zhijian; Sahoo, Saswat; Kang, Hyun Min; Cong, Jason; Burness, Monika L.; Nagrath, Sunitha; Wicha, Max S.; Yoon, Euisik

doi:10.1038/s41467-019-10122-2

Cited by 193 publications

(173 citation statements)

References 51 publications

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“…The same study also reported heterogeneity concerning PIK3CA mutations [75]. CTCs also often appear heterogeneous in their epithelial-mesenchymal transition (EMT) status [20,35]. Furthermore, a recent study performed CTC analysis from different vascular sites and concluded that CTCs might also exhibit heterogeneity as a function of blood draw location [76].…”

Section: Ctc Heterogeneitymentioning

confidence: 97%

“…Combined with next-generation sequencing (NGS) and mass cytometry technologies, it is now possible to characterize the genome, transcriptome, methylome [18], and proteome [19] of individual cells. The recent development of a single-cell RNA-seq platform based on a hydrodynamic barcoding technique (Hydro-Seq) also shows a promising efficiency for wholetranscriptome analysis of CTCs [20]. As reviewed in the following sections, these approaches have already generated interesting observations, including the identification of oligoclonality in CTCs, the definition of specific molecular profiles in comparisons of primary and metastatic tumors, and the discovery of gene expression signatures that characterize metastatic precursors or differences between CTC subpopulations [21].…”

Section: Molecular Analysis Of Ctcsmentioning

confidence: 99%

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Tracking cancer progression: from circulating tumor cells to metastasis

2020

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The analysis of circulating tumor cells (CTCs) is an outstanding tool to provide insights into the biology of metastatic cancers, to monitor disease progression and with potential for use in liquid biopsy-based personalized cancer treatment. These goals are ambitious, yet recent studies are already allowing a sharper understanding of the strengths, challenges, and opportunities provided by liquid biopsy approaches. For instance, through single-cellresolution genomics and transcriptomics, it is becoming increasingly clear that CTCs are heterogeneous at multiple levels and that only a fraction of them is capable of initiating metastasis. It also appears that CTCs adopt multiple ways to enhance their metastatic potential, including homotypic clustering and heterotypic interactions with immune and stromal cells. On the clinical side, both CTC enumeration and molecular analysis may provide new means to monitor cancer progression and to take individualized treatment decisions, but their use for early cancer detection appears to be challenging compared to that of other tumor derivatives such as circulating tumor DNA. In this review, we summarize current data on CTC biology and CTC-based clinical applications that are likely to impact our understanding of the metastatic process and to influence the clinical management of patients with metastatic cancer, including new prospects that may favor the implementation of precision medicine. Publisher's NoteSpringer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Section: Ctc Heterogeneitymentioning

confidence: 97%

Section: Molecular Analysis Of Ctcsmentioning

confidence: 99%

Tracking cancer progression: from circulating tumor cells to metastasis

2020

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“…We further evaluated the pipelines with a human and mouse mixed dataset (Drop-HM dataset) created by mixing a human cell line (HEK) and a mouse cell line (3T3), which is commonly used in evaluating the single cell isolation fidelity of high-throughput scRNA-seq platforms [7,53,54,55]. Ideally, the quantification result of a single cell should only contain transcripts from either species, but not both.…”

Section: Demultiplexing and Transcript Quantificationmentioning

confidence: 99%

Comparison of High-Throughput Single-Cell RNA Sequencing Data Processing Pipelines

Gao

Ling

Tang

et al. 2020

Preprint

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With the development of single-cell RNA sequencing (scRNA-seq) technology, it has become possible to perform large-scale transcript profiling for tens of thousands of cells in a single experiment. Many analysis pipelines have been developed for data generated from different high-throughput scRNA-seq platforms, bringing a new challenge to users to choose a proper workflow that is efficient, robust and reliable for a specific sequencing platform. Moreover, as the amount of public scRNA-seq data has increased rapidly, integrated analysis of scRNAseq data from different sources has become increasingly popular. However, it remains unclear whether such integrated analysis would be biased if the data were processed by different upstream pipelines. In this study, we encapsulated seven existing high-throughput scRNA-seq data processing pipelines with Nextflow, a general integrative workflow management framework, and evaluated their performances in terms of running time, computational resource consumption, and data processing consistency using nine public datasets generated from five different high-throughput scRNA-seq platforms. Our work provides a useful guideline for the selection of scRNA-seq data processing pipelines based on their performances on different real datasets. In addition, these guidelines can serve as a performance evaluation framework for future developments in high-throughput scRNA-seq data processing.Since the emergence of the first single-cell RNA sequencing (scRNA-seq) platform [1], many research achievements have been made at the cellular and subcellular levels with unprecedented resolutions with the aid of this technology. Recent advances in microfluidics and next generation sequencing (NGS) have further increased the efficiency and throughput of scRNA-seq, enabling more cells to be identified and the expression information of more genes for each cell to be quantified simultaneously [2,3,4]. From microcapillary pipettes in 2012 [5,6] and nanoliter droplet-based microfluidic chips in 2015 [7,8] to the latest liquid barcoding combined with split-pool methods [9], the number of cells analysed in parallel has increased from several to tens of thousands [10], bringing new challenges for the processing of a large amount of barcoded NGS data for efficient and accurate quantification of the transcript information of single cells.To meet the needs of high-throughput scRNA-seq data processing, several pipelines that integrate multiple functions have been developed. As one of the first high-throughput scRNA-seq platforms, Drop-seq [7] was introduced in 2015. Moreover, Drop-seq-tools in combination with Picard tools were introduced and provided a user-friendly Application Programming Interface (API) to process the data from Drop-seq. Later in 2017, three additional pipelines were published including Cell Ranger [11], umis [12] and UMItools [13]. Cell Ranger [11] was developed along with the widely adopted 10X Genomics platform which can process multiple biological samples separated by sample barcodes in paral...

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“…Recently, Cheng et al combined a scalable hydrodynamic chip with scRNA‐seq barcoding method to capture and analyze rare circulate tumor cells (CTCs) with high‐throughput in a single chip. With efficient capture of CTCs and contamination removal capability from blood samples, this strategy successfully identified breast cancer drug targets and tracked individual cells expressing markers of epithelial/ mesenchymal cell state and cancer stem cells . The cancer heterogeneity study is also extended to clinical applications.…”

Section: Applicationsmentioning

confidence: 99%

Microfluidic Single‐Cell Omics Analysis

Wang

et al. 2019

Small

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The commonly existing cellular heterogeneity plays a critical role in biological processes such as embryonic development, cell differentiation, and disease progress. Single‐cell omics‐based heterogeneous studies have great significance for identifying different cell populations, discovering new cell types, revealing informative cell features, and uncovering significant interrelationships between cells. Recently, microfluidics has evolved to be a powerful technology for single‐cell omics analysis due to its merits of throughput, sensitivity, and accuracy. Herein, the recent advances of microfluidic single‐cell omics analysis, including different microfluidic platform designs, lysis strategies, and omics analysis techniques, are reviewed. Representative applications of microfluidic single‐cell omics analysis in complex biological studies are then summarized. Finally, a few perspectives on the future challenges and development trends of microfluidic‐assisted single‐cell omics analysis are discussed.

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Hydro-Seq enables contamination-free high-throughput single-cell RNA-sequencing for circulating tumor cells

Cited by 193 publications

References 51 publications

Tracking cancer progression: from circulating tumor cells to metastasis

Tracking cancer progression: from circulating tumor cells to metastasis

Comparison of High-Throughput Single-Cell RNA Sequencing Data Processing Pipelines

Microfluidic Single‐Cell Omics Analysis

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