scholarly journals The effects of proliferation status and cell cycle phase on the responses of single cells to chemotherapy

2020 ◽  
Vol 31 (8) ◽  
pp. 845-857 ◽  
Author(s):  
Adrián E. Granada ◽  
Alba Jiménez ◽  
Jacob Stewart-Ornstein ◽  
Nils Blüthgen ◽  
Simone Reber ◽  
...  

DNA-damaging chemotherapy often leaves residual tumor cells. Combining single-cell long-term live imaging with information theory, we found an unexpected effect: highly proliferative cells were more likely to arrest than to die, whereas more slowly proliferating cells showed a higher probability of death.

Cancers ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 210
Author(s):  
Kamal Pandey ◽  
Nar Bahadur Katuwal ◽  
Nahee Park ◽  
Jin Hur ◽  
Young Bin Cho ◽  
...  

Breast cancer remains a leading cancer burden among women worldwide. Acquired resistance of cyclin-dependent kinase (CDK) 4/6 inhibitors occurs in almost all hormone receptor (HR)-positive subtype cases, comprising 70% of breast cancers, although CDK4/6 inhibitors combined with endocrine therapy are highly effective. CDK4/6 inhibitors are not expected to cooperate with cytotoxic chemotherapy based on the basic cytotoxic chemotherapy mode of action that inhibits rapidly proliferating cells. The palbociclib-resistant preclinical model developed in the current study investigated whether the combination of abemaciclib, CDK4/6 inhibitor with eribulin, an antimitotic chemotherapy could be a strategy to overcome palbociclib-resistant HR-positive breast cancer. The current study demonstrated that sequential abemaciclib treatment following eribulin synergistically suppressed CDK4/6 inhibitor-resistant cells by inhibiting the G2/M cell cycle phase more effectively. The current study showed the significant association of the pole-like kinase 1 (PLK1) level and palbociclib resistance. Moreover, the cumulative PLK1 inhibition in the G2/M phase by each eribulin or abemaciclib proved to be a mechanism of the synergistic effect. The synergistic antitumor effect was also supported by in vivo study. The sequential combination of abemaciclib following eribulin merits further clinical trials to overcome resistance to CDK4/6 inhibitors in HR-positive breast cancer.


Cell Cycle ◽  
2007 ◽  
Vol 6 (16) ◽  
pp. 2071-2081 ◽  
Author(s):  
Paul J. Smith ◽  
Nuria Marquez ◽  
Marie Wiltshire ◽  
Sally Chappell ◽  
Kerenza Njoh ◽  
...  

2014 ◽  
Author(s):  
Lucas Dennis ◽  
Andrew McDavid ◽  
Patrick Danaher ◽  
Greg Finak ◽  
Michael Krouse ◽  
...  

Advances in high-throughput, single cell gene expression are allowing interrogation of cell heterogeneity. However, there is concern that the cell cycle phase of a cell might bias characterizations of gene expression at the single-cell level. We assess the effect of cell cycle phase on gene expression in single cells by measuring 333 genes in 930 cells across three phases and three cell lines. We determine each cell's phase non-invasively without chemical arrest and use it as a covariate in tests of differential expression. We observe bi-modal gene expression, a previously-described phenomenon, wherein the expression of otherwise abundant genes is either strongly positive, or undetectable within individual cells. This bi-modality is likely both biologically and technically driven. Irrespective of its source, we show that it should be modeled to draw accurate inferences from single cell expression experiments. To this end, we propose a semi-continuous modeling framework based on the generalized linear model, and use it to characterize genes with consistent cell cycle effects across three cell lines. Our new computational framework improves the detection of previously characterized cell-cycle genes compared to approaches that do not account for the bi-modality of single-cell data. We use our semi-continuous modelling framework to estimate single cell gene co-expression networks. These networks suggest that in addition to having phase-dependent shifts in expression (when averaged over many cells), some, but not all, canonical cell cycle genes tend to be co-expressed in groups in single cells. We estimate the amount of single cell expression variability attributable to the cell cycle. We find that the cell cycle explains only 5%-17% of expression variability, suggesting that the cell cycle will not tend to be a large nuisance factor in analysis of the single cell transcriptome.


1990 ◽  
Vol 52 (5) ◽  
pp. 986-992
Author(s):  
Takeshi KONO ◽  
Tsukasa TANII ◽  
Masayoshi FURUKAWA ◽  
Nobuyuki MIZUNO ◽  
Shoji TANIGUCHI ◽  
...  

1996 ◽  
Vol 88 (1-2) ◽  
pp. 82-82a ◽  
Author(s):  
Magali OLIVIER ◽  
Charles THEILLET

1988 ◽  
Vol 92 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Z. Agur ◽  
R. Arnon ◽  
B. Schechter

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