Single cell transcriptomes from human kidneys reveal the cellular identity of renal tumors

By Matthew D. Young, T. Mitchell, F. A. Vieira Braga, Maxine G. B. Tran, B. Stewart, J. Ferdinand, G. Collord, R. Botting, Dorin-Mirel Popescu, K. Loudon and 28 more. Science, 2018

671 citations recorded by the source corpus.

Pediatric and adult kidney tumors differ Understanding tumor origins and the similarities and differences between organ-specific cancers is important for determining treatment options. Young et al. generated more than 72,000 single-cell transcriptomes from healthy and cancerous human kidneys. From these data, they determined that Wilms tumor, a pediatric kidney cancer, originates from aberrant fetal cells, whereas adult kidney cancers are likely derived from a specific subtype of proximal convoluted tubular cell. Science, this issue p. 594 Single-cell mRNAs of normal and cancerous kidney cells reveal the cellular identity of childhood and adult tumors. Messenger RNA encodes cellular function and phenotype. In the context of human cancer, it defines the identities of malignant cells and the diversity of tumor tissue. We studied 72,501 single-cell transcriptomes of human renal tumors and normal tissue from fetal, pediatric, and adult kidneys. We matched childhood Wilms tumor with specific fetal cell types, thus providing evidence for the hypothesis that Wilms tumor cells are aberrant fetal cells. In adult renal cell carcinoma, we identified a canonical cancer transcriptome that matched a little-known subtype of proximal convoluted tubular cell. Analyses of the tumor composition defined cancer-associated normal cells and delineated a complex vascular endothelial growth factor (VEGF) signaling circuit. Our findings reveal the precise cellular identities and compositions of human kidney tumors.

Subfields: Cancer Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/5e996cab099e14c6cd5afff536b4fc65521f2a43

How researchers see this paper

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In Cancer Research

1. Matthew D. Young
2. Sam Behjati
3. Fabian J Theis
4. Malte D. Luecken

In Molecular Biology

1. Matthew D. Young
2. Sam Behjati
3. Fabian J Theis
4. Malte D. Luecken

Citations in the corpus

• SoupX removes ambient RNA contamination from droplet-based single-cell RNA sequencing data (2018, positive): “For example, solid-tissue experiments are frequently highly contaminated with red blood cells and red cell lysis is used to prepare the samples [15].”