Literature DB >> 30536579

Rapid Assessment of Mitochondrial Complex I Activity and Metabolic Phenotyping of Breast Cancer Cells by NAD(p)H Cytometry.

V Krishnan Ramanujan1.   

Abstract

Cancer cells are known to display a variety of metabolic reprogramming strategies to fulfill their own growth and proliferative agenda. With the advent of high resolution imaging strategies, metabolomics techniques, and so forth, there is an increasing appreciation of critical role that tumor cell metabolism plays in the overall breast cancer (BC) growth. In this report, we demonstrate a sensitive, flow-cytometry-based assay for rapidly assessing the metabolic phenotypes in isolated suspensions of breast cancer cells. By measuring the temporal variation of NAD(p)H signals in unlabeled, living cancer cells, and by measuring mitochondrial membrane potential {Δψm } in fluorescently labeled cells, we demonstrate that these signals can reliably distinguish the metabolic phenotype of human breast cancer cells and can track the cellular sensitivity to drug candidates. We further show the utility of this metabolic ratio {Δψm /NAD(p)H} in monitoring mitochondrial functional improvement as well as metabolic heterogeneity in primary murine tumor cells isolated from tumor biopsies. Together, these results demonstrate a novel possibility for rapid metabolic functional screening applications as well as a metabolic phenotyping tool for determining drug sensitivity in living cancer cells.
© 2018 International Society for Advancement of Cytometry. © 2018 International Society for Advancement of Cytometry.

Entities:  

Keywords:  NAD(p)H; breast cancer; metabolic plasticity; metabolism; mitochondria; tumor heterogeneity

Year:  2018        PMID: 30536579      PMCID: PMC6329654          DOI: 10.1002/cyto.a.23681

Source DB:  PubMed          Journal:  Cytometry A        ISSN: 1552-4922            Impact factor:   4.355


  37 in total

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2.  On respiratory impairment in cancer cells.

Authors:  O WARBURG
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3.  MMTV-PyMT and Derived Met-1 Mouse Mammary Tumor Cells as Models for Studying the Role of the Androgen Receptor in Triple-Negative Breast Cancer Progression.

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4.  Transgenic Polyoma middle-T mice model premalignant mammary disease.

Authors:  J E Maglione; D Moghanaki; L J Young; C K Manner; L G Ellies; S O Joseph; B Nicholson; R D Cardiff; C L MacLeod
Journal:  Cancer Res       Date:  2001-11-15       Impact factor: 12.701

5.  Scaling behavior in mitochondrial redox fluctuations.

Authors:  V Krishnan Ramanujan; Gabriel Biener; Brian A Herman
Journal:  Biophys J       Date:  2006-03-24       Impact factor: 4.033

Review 6.  Isolation of mouse mammary epithelial subpopulations: a comparison of leading methods.

Authors:  Matthew J Smalley; Howard Kendrick; Julie M Sheridan; Joseph L Regan; Michael D Prater; Geoffrey J Lindeman; Christine J Watson; Jane E Visvader; John Stingl
Journal:  J Mammary Gland Biol Neoplasia       Date:  2012-05-30       Impact factor: 2.673

Review 7.  Metabolic transformation in cancer.

Authors:  Daniel A Tennant; Raúl V Durán; Houda Boulahbel; Eyal Gottlieb
Journal:  Carcinogenesis       Date:  2009-03-25       Impact factor: 4.944

8.  Comparison of the effect of mitochondrial inhibitors on mitochondrial membrane potential in two different cell lines using flow cytometry and spectrofluorometry.

Authors:  Marie Kalbácová; Marek Vrbacký; Zdenek Drahota; Zora Melková
Journal:  Cytometry A       Date:  2003-04       Impact factor: 4.355

Review 9.  Understanding the Warburg effect: the metabolic requirements of cell proliferation.

Authors:  Matthew G Vander Heiden; Lewis C Cantley; Craig B Thompson
Journal:  Science       Date:  2009-05-22       Impact factor: 47.728

10.  Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumors.

Authors:  Jason I Herschkowitz; Karl Simin; Victor J Weigman; Igor Mikaelian; Jerry Usary; Zhiyuan Hu; Karen E Rasmussen; Laundette P Jones; Shahin Assefnia; Subhashini Chandrasekharan; Michael G Backlund; Yuzhi Yin; Andrey I Khramtsov; Roy Bastein; John Quackenbush; Robert I Glazer; Powel H Brown; Jeffrey E Green; Levy Kopelovich; Priscilla A Furth; Juan P Palazzo; Olufunmilayo I Olopade; Philip S Bernard; Gary A Churchill; Terry Van Dyke; Charles M Perou
Journal:  Genome Biol       Date:  2007       Impact factor: 13.583

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  1 in total

1.  Quantitative Imaging of Morphometric and Metabolic Signatures Reveals Heterogeneity in Drug Response of Three-Dimensional Mammary Tumor Spheroids.

Authors:  V Krishnan Ramanujan
Journal:  Mol Imaging Biol       Date:  2019-06       Impact factor: 3.488

  1 in total

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