A single-cell and single-nucleus RNA-seq toolbox for fresh and frozen human tumors

Abstract

<jats:title>Abstract</jats:title><jats:p>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.</jats:p>

RAAS blockade, kidney disease, and expression ofACE2, the entry receptor for SARS-CoV-2, in kidney epithelial and endothelial cells

“…Frozen kidney biopsy specimens or frozen samples of macroscopically normal cortex from tumor nephrectomies (distant from the tumor site), were obtained after appropriate patient (discarded tissue) consent and in accordance with Partners Healthcare IRB and institutional guidelines. One of two protocols (utilizing either nuclei EZ lysis buffer (Sigma-Aldrich, St. Louis, USA) or a salt Tris-based buffer (27,28)) was used to isolate nuclei from these; in the case of kidney biopsy tissue, the surrounding OCT embedding medium was first removed using PBS. 8,000 or 10,000 single nuclei were loaded into each channel of the Chromium single cell 3' chip, according to use of the v2 or v3 kit respectively (10x Genomics, Pleasanton, USA).…”

“Single-nucleus RNA-seq2 reveals a functional crosstalk between liver zonation and ploidy”

“…Thirdly, it relies on the isolation of intact cells from fresh tissues, which hinders its clinical application on human samples. In this context, single-nucleus RNA-seq has emerged as a complementary approach that relies on the unbiased assessment of nuclei from all cells present in a tissue [20,21,36]. The analysis of the nuclear transcriptome has been proven to be very powerful to study cell type diversity in the mouse and human tissues, including brain [21,[23][24][25][26][27]111]; spinal cord [50]; breast cancer [51]; kidney [29][30][31][32]; lung [28]; heart [33,34]; and a variety of human tumor samples [36].…”

“…S1C). This correlation shows that single-nucleus RNA-seq2 is a robust and reliable approach to study transcriptional profiles of individual cells from archived frozen tissues [20,23,25,36,[50][51][52]. The main improvement of our approach relies on the addition of a supplementary lysis buffer compatible with the generation of full-length cDNA and library preparation without the need for additional clean-up steps.…”

“…Single-nucleus RNA-seq (snRNA-seq) has emerged as a complementary approach to study complex tissues at a single-cell level [20,21], including brain [21][22][23][24][25][26][27], lung [28], kidney [29][30][31][32] and heart [33,34] in mouse and human frozen samples [35,36]. However, there are no snRNA-seq methods tailored for frozen liver tissues.…”

Cumulus: a cloud-based data analysis framework for large-scale single-cell and single-nucleus RNA-seq

“…While a complex framework such as Cumulus cannot provide an optimal combination of specialized algorithms for each application, it will accelerate research by providing an integrated and fast approach that enables more labs to analyze large-scale single-cell and single-nucleus datasets. In a separate study 49 , we demonstrated Cumulus by analyzing single-cell and single-nucleus RNA-seq data from fresh and frozen tumor from the Human Tumor Atlas Pilot Project (HTAPP). As the community produces data sets at substantially larger scales, we hope that Cumulus will play a key role in the effort to build atlases of complex tissues and organs at higher cellular resolution and leveraging them to understand the human body in health and disease.…”