新單細胞工具可用於新鮮和冷凍人類腫瘤分析
作者:
小柯機器人發布時間:2020/5/14 12:37:42
美國麻省理工學院Aviv Regev、Orit Rozenblatt-Rosen等研究人員,合作開發了新單細胞工具可用於新鮮和冷凍人類腫瘤的分析。這一研究成果發表在2020年5月11日的《自然—醫學》上。
研究人員開發了系統型工具,即分別使用單細胞RNA-Seq(scRNA-Seq)和單核RNA-Seq(snRNA-Seq)對新鮮和冷凍的臨床腫瘤樣品進行分析。研究人員分析了23個標本中40個樣品的216,490個細胞和細胞核,這些標本涵蓋了八種不同組織和樣品特徵的腫瘤類型。
研究人員通過細胞和細胞核質量、恢復率和細胞組成評估了方案。匹配樣品中的scRNA-Seq和snRNA-Seq可得到相同的細胞類型,但比例不同。
這一工作為廣泛的腫瘤研究提供了指導,包括從其他腫瘤工具中測試和選擇方法的標準,從而為繪製腫瘤圖譜鋪平了道路。
據了解,單細胞基因組學對於繪製腫瘤生態系統至關重要。儘管單細胞RNA-Seq(scRNA-Seq)可以分析從新鮮腫瘤中分離的細胞中的RNA,但仍需要單核RNA-Seq(snRNA-Seq)來分析冷凍或難分離的腫瘤。每一種都需要針對不同的組織和腫瘤類型進行定製,這為採用提供了障礙。
附:英文原文
Title: A single-cell and single-nucleus RNA-Seq toolbox for fresh and frozen human tumors
Author: Michal Slyper, Caroline B. M. Porter, Orr Ashenberg, Julia Waldman, Eugene Drokhlyansky, Isaac Wakiro, Christopher Smillie, Gabriela Smith-Rosario, Jingyi Wu, Danielle Dionne, Sbastien Vigneau, Judit Jan-Valbuena, Timothy L. Tickle, 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, Lan Nguyen, Matan Hofree, Peter J. Tramontozzi, Bo Li, Catherine J. Wu, Benjamin Izar, Rizwan Haq, F. Stephen Hodi, Charles H. Yoon, Aaron N. Hata, Suzanne J. Baker, Mario L. Suv, Raphael Bueno, Elizabeth H. Stover, Michael R. Clay, Michael A. Dyer, Natalie B. Collins, Ursula A. Matulonis, Nikhil Wagle, Bruce E. Johnson, Asaf Rotem, Orit Rozenblatt-Rosen, Aviv Regev
Issue&Volume: 2020-05-11
Abstract: Single-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.
DOI: 10.1038/s41591-020-0844-1
Source: https://www.nature.com/articles/s41591-020-0844-1