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A single-cell and single-nucleus RNA-seq toolbox for fresh and frozen human tumors
By
Michal Slyper,
Caroline B. M. Porter,
Orr Ashenberg,
Julia Waldman,
Eugene Drokhlyansky,
Isaac Wakiro,
Christopher Smillie,
Gabriela Smith-Rosario,
Jingyi Wu,
Danielle Dionne,
Sébastien Vigneau,
Judit Jané-Valbuena,
Sara Napolitano,
Mei-Ju Su,
Anand G. Patel,
Asa Karlstrom,
Simon Gritsch,
Masashi Nomura,
Avinash Waghray,
Satyen H. Gohil,
Alexander M. Tsankov,
Livnat Jerby-Arnon,
Ofir Cohen,
Johanna Klughammer,
Yanay Rosen,
Joshua Gould,
Bo Li,
Lan Nguyen,
Catherine J Wu,
Benjamin Izar,
Rizwan Haq,
F. Stephen Hodi,
Charles H. Yoon,
Aaron N. Hata,
Suzanne J. Baker,
Mario L. Suvà,
Raphael Bueno,
Elizabeth H. Stover,
Ursula A. Matulonis,
Michael R. Clay,
Michael A. Dyer,
Natalie B. Collins,
Nikhil Wagle,
Asaf Rotem,
Bruce E. Johnson,
Orit Rozenblatt-Rosen,
Aviv Regev
Posted 12 Sep 2019
bioRxiv DOI: 10.1101/761429
Single cell genomics is essential to chart the complex tumor ecosystem. While single cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumor tissues, single nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each strategy requires modifications to fit the unique characteristics of different tissue and tumor types, posing a barrier to adoption. Here, we developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We tested eight tumor types of varying tissue and sample characteristics (resection, biopsy, ascites, and orthotopic patient-derived xenograft): lung cancer, metastatic breast cancer, ovarian cancer, melanoma, neuroblastoma, pediatric sarcoma, glioblastoma, pediatric high-grade glioma, and chronic lymphocytic leukemia. Analyzing 212,498 cells and nuclei from 39 clinical samples, we evaluated protocols by cell quality, recovery rate, and cellular composition. We optimized protocols for fresh tissue dissociation for different tumor types using a decision tree to account for the technical and biological variation between clinical samples. We established methods for nucleus isolation from OCT embedded and fresh-frozen tissues, with an optimization matrix varying mechanical force, buffer, and detergent. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types and intrinsic expression profiles, but at different proportions. Our work provides direct guidance across 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.
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