scholarly journals Pan-cancer single cell RNA-seq uncovers recurring programs of cellular heterogeneity

2019 ◽  
Author(s):  
Gabriela S. Kinker ◽  
Alissa C. Greenwald ◽  
Rotem Tal ◽  
Zhanna Orlova ◽  
Michael S. Cuoco ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Lines ◽  
Cancer Cell ◽  
Cancer Cell Lines ◽  
Human Tumors ◽  
Model Systems ◽  
Cellular Heterogeneity ◽  
Specific Cell ◽  
Rna Seq ◽  
Mesenchymal Transition

AbstractCultured cell lines are the workhorse of cancer research, but it is unclear to what extent they recapitulate the cellular heterogeneity observed among malignant cells in tumors, given the absence of a native tumor microenvironment. Here, we used multiplexed single cell RNA-seq to profile ~200 cancer cell lines. We uncovered expression programs that are recurrently heterogeneous within many cancer cell lines and are largely independent of observed genetic diversity. These programs of heterogeneity are associated with diverse biological processes, including cell cycle, senescence, stress and interferon responses, epithelial-to-mesenchymal transition, and protein maturation and degradation. Notably, some of these recurrent programs recapitulate those seen in human tumors, suggesting a prominent role of intrinsic plasticity in generating intra-tumoral heterogeneity. Moreover, the data allowed us to prioritize specific cell lines as model systems of cellular plasticity. We used two such models to demonstrate the dynamics, regulation and drug sensitivities associated with a cancer senescence program also observed in human tumors. Our work describes the landscape of cellular heterogeneity in diverse cancer cell lines, and identifies recurrent patterns of expression heterogeneity that are shared between tumors and specific cell lines and can thus be further explored in follow up studies.

scholarly journals SMARTer single cell total RNA sequencing

2019 ◽  
Vol 47 (16) ◽  
pp. e93-e93 ◽  
Author(s):  
Karen Verboom ◽  
Celine Everaert ◽  
Nathalie Bolduc ◽  
Kenneth J Livak ◽  
Nurten Yigit ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Cell Lines ◽  
Cancer Cell ◽  
Expression Patterns ◽  
Cancer Cell Lines ◽  
Cellular Heterogeneity ◽  
Circular Rnas ◽  
Rna Seq ◽  
Total Rna

Abstract Single cell RNA sequencing methods have been increasingly used to understand cellular heterogeneity. Nevertheless, most of these methods suffer from one or more limitations, such as focusing only on polyadenylated RNA, sequencing of only the 3′ end of the transcript, an exuberant fraction of reads mapping to ribosomal RNA, and the unstranded nature of the sequencing data. Here, we developed a novel single cell strand-specific total RNA library preparation method addressing all the aforementioned shortcomings. Our method was validated on a microfluidics system using three different cancer cell lines undergoing a chemical or genetic perturbation and on two other cancer cell lines sorted in microplates. We demonstrate that our total RNA-seq method detects an equal or higher number of genes compared to classic polyA[+] RNA-seq, including novel and non-polyadenylated genes. The obtained RNA expression patterns also recapitulate the expected biological signal. Inherent to total RNA-seq, our method is also able to detect circular RNAs. Taken together, SMARTer single cell total RNA sequencing is very well suited for any single cell sequencing experiment in which transcript level information is needed beyond polyadenylated genes.

scholarly journals Quantification of XRCC and DNA-PK proteins in cancer cell lines and human tumors by LC–MS/MS

Bioanalysis ◽  
2014 ◽  
Vol 6 (22) ◽  
pp. 2969-2983 ◽  
Author(s):  
Matthew V Myers ◽  
Stephen E Maxwell ◽  
Xiaomin Wang
Keyword(s):  
Cell Lines ◽  
Cancer Cell ◽  
Cancer Cell Lines ◽  
Human Tumors

scholarly journals Epithelial-to-Mesenchymal Transition Is Not a Major Modulating Factor in the Cytotoxic Response to Natural Products in Cancer Cell Lines

Molecules ◽  
2021 ◽  
Vol 26 (19) ◽  
pp. 5858
Author(s):  
Baris Kucukkaraduman ◽  
Ekin Gokce Cicek ◽  
Muhammad Waqas Akbar ◽  
Secil Demirkol Canli ◽  
Burcak Vural ◽  
...  
Keyword(s):  
Natural Products ◽  
Cancer Cells ◽  
Cell Lines ◽  
Cancer Cell ◽  
Epithelial To Mesenchymal Transition ◽  
Epigallocatechin Gallate ◽  
Cancer Cell Lines ◽  
Vimentin Expression ◽  
Mesenchymal Transition ◽  
Urolithin A

Numerous natural products exhibit antiproliferative activity against cancer cells by modulating various biological pathways. In this study, we investigated the potential use of eight natural compounds (apigenin, curcumin, epigallocatechin gallate, fisetin, forskolin, procyanidin B2, resveratrol, urolithin A) and two repurposed agents (fulvestrant and metformin) as chemotherapy enhancers and mesenchymal-to-epithelial (MET) inducers of cancer cells. Screening of these compounds in various colon, breast, and pancreatic cancer cell lines revealed anti-cancer activity for all compounds, with curcumin being the most effective among these in all cell lines. Although some of the natural products were able to induce MET in some cancer cell lines, the MET induction was not related to increased synergy with either 5-FU, irinotecan, gemcitabine, or gefitinib. When synergy was observed, for example with curcumin and irinotecan, this was unrelated to MET induction, as assessed by changes in E-cadherin and vimentin expression. Our results show that MET induction is compound and cell line specific, and that MET is not necessarily related to enhanced chemosensitivity.

scholarly journals Joint single cell DNA-seq and RNA-seq of gastric cancer cell lines reveals rules of in vitro evolution

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Noemi Andor ◽  
Billy T Lau ◽  
Claudia Catalanotti ◽  
Anuja Sathe ◽  
Matthew Kubit ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Single Cell ◽  
Cell Line ◽  
Cell Lines ◽  
Cancer Cell ◽  
Gastric Cancer Cell ◽  
Phenotypic Diversity ◽  
Single Cells ◽  
Cancer Cell Lines ◽  
Gastric Cancer Cell Lines

Abstract Cancer cell lines are not homogeneous nor are they static in their genetic state and biological properties. Genetic, transcriptional and phenotypic diversity within cell lines contributes to the lack of experimental reproducibility frequently observed in tissue-culture-based studies. While cancer cell line heterogeneity has been generally recognized, there are no studies which quantify the number of clones that coexist within cell lines and their distinguishing characteristics. We used a single-cell DNA sequencing approach to characterize the cellular diversity within nine gastric cancer cell lines and integrated this information with single-cell RNA sequencing. Overall, we sequenced the genomes of 8824 cells, identifying between 2 and 12 clones per cell line. Using the transcriptomes of more than 28 000 single cells from the same cell lines, we independently corroborated 88% of the clonal structure determined from single cell DNA analysis. For one of these cell lines, we identified cell surface markers that distinguished two subpopulations and used flow cytometry to sort these two clones. We identified substantial proportions of replicating cells in each cell line, assigned these cells to subclones detected among the G0/G1 population and used the proportion of replicating cells per subclone as a surrogate of each subclone's growth rate.

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