A single-cell and single-nucleus RNA-Seq toolbox for fresh and frozen human tumors
-
Published:2020-05-01
Issue:5
Volume:26
Page:792-802
-
ISSN:1078-8956
-
Container-title:Nature Medicine
-
language:en
-
Short-container-title:Nat Med
Author:
Slyper Michal, Porter Caroline B. M., Ashenberg Orr, Waldman Julia, Drokhlyansky Eugene, Wakiro Isaac, Smillie Christopher, Smith-Rosario Gabriela, Wu Jingyi, Dionne Danielle, Vigneau Sébastien, Jané-Valbuena Judit, Tickle Timothy L., Napolitano Sara, Su Mei-Ju, Patel Anand G.ORCID, Karlstrom AsaORCID, Gritsch Simon, Nomura MasashiORCID, Waghray Avinash, Gohil Satyen H., Tsankov Alexander M., Jerby-Arnon Livnat, Cohen Ofir, Klughammer Johanna, Rosen Yanay, Gould JoshuaORCID, Nguyen Lan, Hofree Matan, Tramontozzi Peter J.ORCID, Li Bo, Wu Catherine J.ORCID, Izar Benjamin, Haq RizwanORCID, Hodi F. Stephen, Yoon Charles H., Hata Aaron N., Baker Suzanne J., Suvà Mario L.ORCID, Bueno Raphael, Stover Elizabeth H.ORCID, Clay Michael R.ORCID, Dyer Michael A., Collins Natalie B., Matulonis Ursula A., Wagle NikhilORCID, Johnson Bruce E., Rotem Asaf, Rozenblatt-Rosen OritORCID, Regev AvivORCID
Abstract
AbstractSingle-cell genomics is essential to chart tumor ecosystems. Although single-cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumors, single-nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each requires customization to different tissue and tumor types, posing a barrier to adoption. Here, we have developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We analyzed 216,490 cells and nuclei from 40 samples across 23 specimens spanning eight tumor types of varying tissue and sample characteristics. We evaluated protocols by cell and nucleus quality, recovery rate and cellular composition. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types, but at different proportions. Our work provides guidance for studies in a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases.
Publisher
Springer Science and Business Media LLC
Subject
General Biochemistry, Genetics and Molecular Biology,General Medicine
Reference45 articles.
1. Cieslik, M. & Chinnaiyan, A. M. Cancer transcriptome profiling at the juncture of clinical translation. Nat. Rev. Genet. 19, 93–109 (2018). 2. Filbin, M. G. et al. Developmental and oncogenic programs in H3K27M gliomas dissected by single-cell RNA-seq. Science 360, 331–335 (2018). 3. Jerby-Arnon, L. et al. A cancer cell program promotes T cell exclusion and resistance to checkpoint blockade. Cell 175, 984–997.e924 (2018). 4. Puram, S. V. et al. Single-cell transcriptomic analysis of primary and metastatic tumor ecosystems in head and neck cancer. Cell 171, 1611–1624.e1624 (2017). 5. Tirosh, I. et al. Single-cell RNA-seq supports a developmental hierarchy in human oligodendroglioma. Nature 539, 309–313 (2016).
Cited by
456 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|