Abstract
A major hurdle for the treatment of cancer is the incomplete understanding of its evolution through the course of its emergence, dispersal, and relapse. Genetic and epigenetic changes in combination with external cues and selective forces are the driving factors behind tumor heterogeneity. Understanding this variability within and across patients may partly explain the unpredictable outcomes of cancer treatments. Measuring the variation of gene expression levels within cells of the same tumor is a crucial part of this endeavor. Hence, the recently developed single-cell RNA-sequencing (scRNA-seq) technologies have become a valuable tool for cancer research. In practice, however, this is still challenging, especially for clinical samples. Here, we describe mcSCRB-seq (molecular crowding single-cell RNA barcoding and sequencing), a highly sensitive and powerful plate-based scRNA-seq method, which shows great capability to generate transcriptome data for cancer cells. mcSCRB-seq is not only characterized by high sensitivity due to molecular crowding and the use of unique molecular identifiers (UMIs) but also features an easy workflow and a low per-cell cost and does not require specialized equipment.
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Bagnoli, J.W., Wange, L.E., Janjic, A., Enard, W. (2019). Studying Cancer Heterogeneity by Single-Cell RNA Sequencing. In: Küppers, R. (eds) Lymphoma. Methods in Molecular Biology, vol 1956. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-9151-8_14
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DOI: https://doi.org/10.1007/978-1-4939-9151-8_14
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