TY - JOUR
T1 - Nanogrid single-nucleus RNA sequencing reveals phenotypic diversity in breast cancer
AU - Gao, Ruli
AU - Kim, Charissa
AU - Sei, Emi
AU - Foukakis, Theodoros
AU - Crosetto, Nicola
AU - Chan, Leong Keat
AU - Srinivasan, Maithreyan
AU - Zhang, Hong
AU - Meric-Bernstam, Funda
AU - Navin, Nicholas
N1 - Funding Information:
This work was supported by grants to N.N. from the Lefkofsky Family Foundation, NCI (1RO1CA169244-01), and from the American Cancer Society (129098-RSG-16-092-01- TBG). N.N. is a T.C. Hsu Endowed Scholar, AAAS Wachtel Scholar, and Andrew Sabin Family Fellow. The study was supported by grants from the Breast Cancer Research Foundation and the Swedish Cancer Society to T.F. and the Soderberg Fellowship to N.C. The work was also supported by a Sister Institution Network Grant (SINF) through the Global Access Program (GAP) at MD Anderson). The study also supported by a TL1 fellowship (TL1TR000369 and UL1TR000371) and American Legion Auxiliary fellowship to C.K., and a Susan Komen Postdoctoral Fellowship (PDF17487910) and AACR-John and Elizabeth Leonard Family Foundation Basic Cancer Research Fellowship (17-40-42-GAO) to R.G. We also thank support from the UT MD Anderson Cancer Center Sequencing Core grant (CA016672 SMF). We are also grateful to the employees of Wafergen Inc. for their support and collaboration and Adriana Paulucci for assistance with microscopy. We thank Aislyn Schalck for preparing illustrations that were used in the figures.
Publisher Copyright:
© 2017 The Author(s).
PY - 2017/12/1
Y1 - 2017/12/1
N2 - Single cell RNA sequencing has emerged as a powerful tool for resolving transcriptional diversity in tumors, but is limited by throughput, cost and the ability to process archival frozen tissue samples. Here we develop a high-throughput 3′ single-nucleus RNA sequencing approach that combines nanogrid technology, automated imaging, and cell selection to sequence up to ~1800 single nuclei in parallel. We compare the transcriptomes of 485 single nuclei to 424 single cells in a breast cancer cell line, which shows a high concordance (93.34%) in gene levels and abundance. We also analyze 416 nuclei from a frozen breast tumor sample and 380 nuclei from normal breast tissue. These data reveal heterogeneity in cancer cell phenotypes, including angiogenesis, proliferation, and stemness, and a minor subpopulation (19%) with many overexpressed cancer genes. Our studies demonstrate the utility of nanogrid single-nucleus RNA sequencing for studying the transcriptional programs of tumor nuclei in frozen archival tissue samples.
AB - Single cell RNA sequencing has emerged as a powerful tool for resolving transcriptional diversity in tumors, but is limited by throughput, cost and the ability to process archival frozen tissue samples. Here we develop a high-throughput 3′ single-nucleus RNA sequencing approach that combines nanogrid technology, automated imaging, and cell selection to sequence up to ~1800 single nuclei in parallel. We compare the transcriptomes of 485 single nuclei to 424 single cells in a breast cancer cell line, which shows a high concordance (93.34%) in gene levels and abundance. We also analyze 416 nuclei from a frozen breast tumor sample and 380 nuclei from normal breast tissue. These data reveal heterogeneity in cancer cell phenotypes, including angiogenesis, proliferation, and stemness, and a minor subpopulation (19%) with many overexpressed cancer genes. Our studies demonstrate the utility of nanogrid single-nucleus RNA sequencing for studying the transcriptional programs of tumor nuclei in frozen archival tissue samples.
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U2 - 10.1038/s41467-017-00244-w
DO - 10.1038/s41467-017-00244-w
M3 - Article
C2 - 28794488
AN - SCOPUS:85027226013
SN - 2041-1723
VL - 8
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 228
ER -
