4.8 Article

Occult polyclonality of preclinical pancreatic cancer models drives in vitro evolution

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NATURE COMMUNICATIONS
卷 13, 期 1, 页码 -

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NATURE PORTFOLIO
DOI: 10.1038/s41467-022-31376-3

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资金

  1. MD Anderson Pancreatic Cancer Moon Shot Program
  2. Khalifa Bin Zayed Al-Nahyan Foundation
  3. National Institutes of Health [NIH U01CA196403, U01CA200468, P50CA221707]
  4. NIH [U54CA096300, U54CA096297, T32CA217789, T32CA009599]
  5. German Research Foundation [SE-2616/2-1]

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The use of single-cell technologies has revealed the heterogeneity and polyclonality in pancreatic cancer cell lines and patient-derived organoids. The study also highlights the impact of laboratory variations and the transition from 2D to 3D models on transcriptomic profiles. These findings raise concerns about the validity of commonly used control lines and the predictive abilities of organoids over time.
Heterogeneity is a hallmark of cancer. The advent of single-cell technologies has helped uncover heterogeneity in a high-throughput manner in different cancers across varied contexts. Here we apply single-cell sequencing technologies to reveal inherent heterogeneity in assumptively monoclonal pancreatic cancer (PDAC) cell lines and patient-derived organoids (PDOs). Our findings reveal a high degree of both genomic and transcriptomic polyclonality in monolayer PDAC cell lines, custodial variation induced by growing apparently identical cell lines in different laboratories, and transcriptomic shifts in transitioning from 2D to 3D spheroid growth models. Our findings also call into question the validity of widely available immortalized, non-transformed pancreatic lines as contemporaneous control lines in experiments. We confirm these findings using a variety of independent assays, including but not limited to whole exome sequencing, single-cell copy number variation sequencing (scCNVseq), single-nuclei assay for transposase-accessible chromatin with sequencing, fluorescence in-situ hybridization, and single-cell RNA sequencing (scRNAseq). We map scRNA expression data to unique genomic clones identified by orthogonally-gathered scCNVseq data of these same PDAC cell lines. Further, while PDOs are known to reflect the cognate in vivo biology of the parental tumor, we identify transcriptomic shifts during ex vivo passage that might hamper their predictive abilities over time. The impact of these findings on rigor and reproducibility of experimental data generated using established preclinical PDAC models between and across laboratories is uncertain, but a matter of concern.

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