A simple and fast microfluidic approach of same-single-cell analysis (SASCA) for the study of multidrug resistance modulation in cancer cells

Lab on a Chip ◽  
2011 ◽  
Vol 11 (7) ◽  
pp. 1378 ◽  
Author(s):  
XiuJun Li ◽  
Yuchun Chen ◽  
Paul C. H. Li
Keyword(s):  
Multidrug Resistance ◽  
Single Cell ◽  
Cancer Cells ◽  
Single Cell Analysis ◽  
Cell Analysis ◽  
Resistance Modulation

scholarly journals Single-cell analysis reveals a stem-cell program in human metastatic breast cancer cells

Nature ◽  
2015 ◽  
Vol 526 (7571) ◽  
pp. 131-135 ◽  
Author(s):  
Devon A. Lawson ◽  
Nirav R. Bhakta ◽  
Kai Kessenbrock ◽  
Karin D. Prummel ◽  
Ying Yu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Stem Cell ◽  
Metastatic Breast Cancer ◽  
Single Cell ◽  
Cancer Cells ◽  
Breast Cancer Cells ◽  
Single Cell Analysis ◽  
Metastatic Breast ◽  
Cell Analysis

scholarly journals Single-cell lipidomics with high structural specificity by mass spectrometry

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Zishuai Li ◽  
Simin Cheng ◽  
Qiaohong Lin ◽  
Wenbo Cao ◽  
Jing Yang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Single Cell ◽  
Cancer Cells ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Mass Spectrometry Analysis ◽  
Human Lung Cancer ◽  
Cell Analysis ◽  
Structural Specificity ◽  
Spectrometry Analysis

AbstractSingle-cell analysis is critical to revealing cell-to-cell heterogeneity that would otherwise be lost in ensemble analysis. Detailed lipidome characterization for single cells is still far from mature, especially when considering the highly complex structural diversity of lipids and the limited sample amounts available from a single cell. We report the development of a general strategy enabling single-cell lipidomic analysis with high structural specificity. Cell fixation is applied to retain lipids in the cell during batch treatments prior to single-cell analysis. In addition to tandem mass spectrometry analysis revealing the class and fatty acyl-chain for lipids, batch photochemical derivatization and single-cell droplet treatment are performed to identify the C=C locations and sn-positions of lipids, respectively. Electro-migration combined with droplet-assisted electrospray ionization enables single-cell mass spectrometry analysis with easy operation but high efficiency in sample usage. Four subtypes of human breast cancer cells are correctly classified through quantitative analysis of lipid C=C location or sn-position isomers in ~160 cells. Most importantly, the single-cell deep lipidomics strategy successfully discriminates gefitinib-resistant cells from a population of wild-type human lung cancer cells (HCC827), highlighting its unique capability to promote precision medicine.

scholarly journals Single-cell analysis of clonal maintenance of transcriptional and epigenetic states in cancer cells

2020 ◽  
Vol 52 (7) ◽  
pp. 709-718 ◽  
Author(s):  
Zohar Meir ◽  
Zohar Mukamel ◽  
Elad Chomsky ◽  
Aviezer Lifshitz ◽  
Amos Tanay
Keyword(s):  
Single Cell ◽  
Cancer Cells ◽  
Single Cell Analysis ◽  
Cell Analysis

scholarly journals Single-cell and spatial analyses of cancer cells: toward elucidating the molecular mechanisms of clonal evolution and drug resistance acquisition

2021 ◽  
Vol 41 (1) ◽  
Author(s):  
Satoi Nagasawa ◽  
Yukie Kashima ◽  
Ayako Suzuki ◽  
Yutaka Suzuki
Keyword(s):  
Drug Resistance ◽  
Single Cell ◽  
Cancer Cells ◽  
Single Cell Analysis ◽  
Clonal Evolution ◽  
Cell Cancer ◽  
Single Type ◽  
Cell Analysis ◽  
Effective Prevention ◽  
Optimal Drug

AbstractEven within a single type of cancer, cells of various types exist and play interrelated roles. Each of the individual cells resides in a distinct microenvironment and behaves differently. Such heterogeneity is the most cumbersome nature of cancers, which is occasionally uncountable when effective prevention or total elimination of cancers is attempted. To understand the heterogeneous nature of each cell, the use of conventional methods for the analysis of “bulk” cells is insufficient. Although some methods are high-throughput and compressive regarding the genes being detected, the obtained data would be from the cell mass, and the average of a large number of the component cells would no longer be measured. Single-cell analysis, which has developed rapidly in recent years, is causing a drastic change. Genome, transcriptome, and epigenome analyses at single-cell resolution currently target cancer cells, cancer-associated fibroblasts, endothelial cells of vessels, and circulating and infiltrating immune cells. In fact, surprisingly diverse features of clonal evolution of cancer cells, during the development of cancer or acquisition of drug resistance, accompanied by corresponding gene expression changes in the circumstantial stromal cells, appeared in recent single-cell analyses. Based on the obtained novel insights, better optimal drug selection and new drug administration sequences were started. Even a remaining concern of the single cell analyses is being addressed. Until very recently, it was impossible to obtain positional information of cells in cancer via single-cell analysis because such information is lost during preparation of single-cell suspensions. A new method, collectively called spatial transcriptome (ST) analysis, has been developed and rapidly applied to various clinical specimens. In this review, we first outline the recent achievements of single-cell cancer analysis in analyzing the molecular basis underlying the acquisition of drug resistance, particularly focusing on the latest anti-epidermal growth factor receptor tyrosine kinase inhibitor, osimertinib. Further, we review the currently available ST analysis methods and introduce our recent attempts regarding the respective topics.

Abstract LB-076: Single-cell analysis of transcription factors provides deeper characterization of cancer cells

2017 ◽  
Author(s):  
Camila Egidio ◽  
Robert Durruthy-Durruthy ◽  
Michael Gonzales ◽  
Manisha Ray ◽  
Jason McKinney
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
Cancer Cells ◽  
Single Cell Analysis ◽  
Cell Analysis

Single-cell analysis of population-based phenotypic switching of cancer cells

2018 ◽  
Vol 14 (5) ◽  
pp. 1806
Author(s):  
Yuen San Chan ◽  
Edwin Wai-Kin Yu ◽  
William Weimao Wang ◽  
Chi-Chun Fong ◽  
Timothy Tak-Chun Yip ◽  
...  
Keyword(s):  
Single Cell ◽  
Cancer Cells ◽  
Single Cell Analysis ◽  
Population Based ◽  
Phenotypic Switching ◽  
Cell Analysis

scholarly journals Abstract 3938: Dynamic interconversion of cancer cells: single-cell analysis of population-based equilibrium

2017 ◽  
Author(s):  
Yuen San Chan ◽  
Edwin-Wai Kin Yu ◽  
William Weimao Wang ◽  
Chi-Chun Fong ◽  
Timothy Tak-Chun Yip ◽  
...  
Keyword(s):  
Single Cell ◽  
Cancer Cells ◽  
Single Cell Analysis ◽  
Population Based ◽  
Cell Analysis
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