Dataset Information

Mosaic analysis with double markers reveals tumor cell of origin in glioma.

ABSTRACT: Cancer cell of origin is difficult to identify by analyzing cells within terminal stage tumors, whose identity could be concealed by the acquired plasticity. Thus, an ideal approach to identify the cell of origin is to analyze proliferative abnormalities in distinct lineages prior to malignancy. Here, we use mosaic analysis with double markers (MADM) in mice to model gliomagenesis by initiating concurrent p53/Nf1 mutations sporadically in neural stem cells (NSCs). Surprisingly, MADM-based lineage tracing revealed significant aberrant growth prior to malignancy only in oligodendrocyte precursor cells (OPCs), but not in any other NSC-derived lineages or NSCs themselves. Upon tumor formation, phenotypic and transcriptome analyses of tumor cells revealed salient OPC features. Finally, introducing the same p53/Nf1 mutations directly into OPCs consistently led to gliomagenesis. Our findings suggest OPCs as the cell of origin in this model, even when initial mutations occur in NSCs, and highlight the importance of analyzing premalignant stages to identify the cancer cell of origin.

SUBMITTER: Liu C

PROVIDER: S-EPMC3143261 | biostudies-literature | 2011 Jul

REPOSITORIES: biostudies-literature

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Mosaic analysis with double markers reveals tumor cell of origin in glioma.

Liu Chong C Sage Jonathan C JC Miller Michael R MR Verhaak Roel G W RG Hippenmeyer Simon S Vogel Hannes H Foreman Oded O Bronson Roderick T RT Nishiyama Akiko A Luo Liqun L Zong Hui H

Cell 20110707 2

Cancer cell of origin is difficult to identify by analyzing cells within terminal stage tumors, whose identity could be concealed by the acquired plasticity. Thus, an ideal approach to identify the cell of origin is to analyze proliferative abnormalities in distinct lineages prior to malignancy. Here, we use mosaic analysis with double markers (MADM) in mice to model gliomagenesis by initiating concurrent p53/Nf1 mutations sporadically in neural stem cells (NSCs). Surprisingly, MADM-based lineag ...[more]

PMID: 21737130

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Project description:Cancer results from molecular mutations occurring in specific cell types, thus determining the cell-of-origin is critical for effective cancer treatment. Inferring such information from terminal tumors can be misleading because malignant tumor cells tend to acquire aberrant properties. Animal models are widely used because one can initiate mutations in specific cell types. However, cell-of-mutation that harbors initial molecular changes may not directly transform, rather merely passes along mutations to its progeny cell lineage, which then serves as cell-of-origin and finally transforms into malignancy. Such a problem is exemplified in the glioma field: glioma can be induced either by mutating tumor suppressor genes in neural stem cells (NSCs) or by over-expressing oncogenes in restricted progenitor cells such as oligodendrocyte precursor cells (OPCs). However, for the NSC glioma model, it remains unknown whether NSCs directly transform or simply pass along mutations to OPC lineage for malignancy. Here we use a genetic system termed Mosaic Analysis with Double Markers (MADM) to study the earliest stage of gliomagenesis from mutated NSCs. At an in vivo single-cell resolution, we unbiasedly analyzed tumorigenic potential of NSCs and all cell lineages derived from them. At pathologically undetectable pre-transforming phases, we found no significant aberrant growth of mutant NSCs and their derivatives except for the OPC lineage. We then tracked the tumor progression from earliest stage and confirmed the expansion of OPCs lead to gliomagenesis. Consistently, transcriptome profiling reveals that terminal-stage tumor cells display salient OPC features and resemble human proneural subtype of glioblastoma multiform (GBM). Most importantly, introducing the same mutations directly into OPCs was sufficient for malignant transformation and these tumor cells are indistinguishable in their gene expression profiles from those in which the first mutations were introduced into NSCs. Our findings strongly implicate OPCs as the transforming cell type for glioma even when initial mutations could occur in NSCs, and highlight the importance of analyzing early phases of tumorigenesis to distinguish cell-of-origin from cell-of-mutation.

Project description:During cerebellar development, granule cell progenitors (GCPs) proliferate exponentially for a fixed period, promoted by paracrine mitogenic factor Sonic Hedgehog (Shh) secreted from Purkinje cells (PCs). Dysregulation of Shh signaling leads to uncontrolled GCP proliferation and medulloblastoma. Serendipitously our previous work discovered insulin-like growth factor 1 (IGF1) as another key driver for medulloblastoma, which led to the current investigation into the role of IGF1 in GCPs during normal development. While the IGF1R conditional knockout model revealed GCP defects in anterior cerebellum, the posterior cerebellum was mostly intact, likely owing to incomplete excision of floxed alleles. To circumvent this hurdle, we enlisted a mouse genetic system called Mosaic Analysis of Double Markers (MADM), which sporadically generates homozygous null cells unequivocally labeled with GFP and their wildtype sibling cells labeled with RFP, enabling phenotypic analysis at single-cell resolution. Using MADM, we found that loss of IGF1R resulted in a 10-fold reduction of GCs in both anterior and posterior cerebellum; and that hindered S phase entry and increased cell cycle exit collectively led to this phenotype. Genetic interaction studies showed that IGF1 signaling prevents GCP cell cycle exit at least partially through suppressing the level of p27kip1, a negative regulator of cell cycle. Finally, we found that IGF1 is produced by PCs in a temporally regulated fashion: it is highly expressed early in development when GCPs proliferate exponentially, then gradually decline as GCPs commit to cell cycle exit. Taken together, our studies reveal IGF1 as a paracrine factor that positively regulates GCP cell cycle in cooperation with Shh, through dampening the level of p27 to prevent precocious cell cycle exit. Our work not only showcases the power of phenotypic analysis by the MADM system but also provides an excellent example of multi-factorial regulation of robust developmental programs.

Project description:Bilateral renal clear cell carcinoma (BRCC) is a rare type of renal cell carcinoma (RCC) that accounts for only 1-5% of RCC cases and has a poor clinical prognosis. The origin, tumor microenvironment, cellular molecular features, and intra-tumoral heterogeneity of BRCC are still unclear. We downloaded BRCC single-cell transcriptome sequencing data from the gene expression omnibus database biochip GSE171306, containing 3,575 cells from left-sided clear cell renal cell carcinoma (ccRCC) and 3,568 cells from right-sided ccRCC, and used a series of R packages for data quality control (QC) and subsequent analysis of BRCC single-cell transcriptome data, including the use of the R packages Seurat and scCancer for cell QC, identification of major cell types, and cell annotation; R package scran for calculation of cell cycle scores; R package infercnv for malignancy scoring of tumor cells; R package ReactomeGSA for functional enrichment analysis; R package Monocle 2 for the analysis of cell differentiation trajectories; and R package CellphoneDB for the analysis of intercellular interactions. In this study, by analyzing the high-quality single-cell transcriptome data of BRCC, we identified 18 cell types and found that left- and right-sided ccRCC were approximately the same in terms of cell type and the number of each cell but differed significantly in terms of tumor cell malignancy score, tumor microenvironment, and cell stemness score. In the cell differentiation trajectory analysis of BRCC, we found that endothelial cells and macrophages play an extremely important role in its tumor progression. Further cell communication analysis was performed, and we found that it may signal through ligand-receptors, such as vascular endothelial growth factor-vascular endothelial growth factor receptor1 (VEGF-VEGFR1), MIF-(CD74-CXCR4), and growth arrest-specific protein 6-AXL, to influence the development of BRCC. The analysis of single-cell transcriptomic data of human BRCC suggests that left- and right-sided ccRCC may be of the same tumor origin, but the left-sided ccRCC is more malignant and has a better immune response.

Dataset Information

Mosaic analysis with double markers reveals tumor cell of origin in glioma.

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Mosaic analysis with double markers reveals tumor cell of origin in glioma.

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