Molecular Imaging and Biology

, Volume 21, Issue 3, pp 410–416 | Cite as

Optical Redox Imaging Detects the Effects of DEK Oncogene Knockdown on the Redox State of MDA-MB-231 Breast Cancer Cells

  • Yu Wen
  • He N. Xu
  • Lisa Privette Vinnedge
  • Min Feng
  • Lin Z. LiEmail author
Brief Article



Optical redox imaging (ORI), based on collecting the endogenous fluorescence of reduced nicotinamide adenine dinucleotide (NADH) and oxidized flavoproteins (Fp) containing a redox cofactor flavin adenine dinucleotide (FAD), provides sensitive indicators of cellular metabolism and redox status. ORI indices (such as NADH, FAD, and their ratio) have been under investigation as potential progression/prognosis biomarkers for cancer. Higher FAD redox ratio (i.e., FAD/(FAD + NADH)) has been associated with higher invasive/metastatic potential in tumor xenografts and cultured cells. This study is to examine whether ORI indices can respond to the modulation of oncogene DEK activities that change cancer cell invasive/metastatic potential.


Using lentiviral shRNA, DEK gene expression was efficiently knocked down in MDA-MB-231 breast cancer cells (DEKsh). These DEKsh cells, along with scrambled shRNA-transduced control cells (NTsh), were imaged with a fluorescence microscope. In vitro invasive potential of the DEKsh cells and NTsh cells was also measured in parallel using the transwell assay.


FAD and FAD redox ratios in polyclonal cells with DEKsh were significantly lower than that in NTsh control cells. Consistently, the DEKsh cells demonstrated decreased invasive potential than their non-knockdown counterparts NTsh cells.


This study provides direct evidence that oncogene activities could mediate ORI-detected cellular redox state.

Key words

Optical redox imaging FAD NADH Redox ratio DEK gene Knock down Breast cancer Invasive potential 



The authors thank Ms. Jinxia Jiang for her assistance in part of the data acquisition and Dr. Zhenwu Lin for valuable discussion and support. The authors would also like to appreciate the valuable discussion with and support from Dr. Andrea Stout and Ms. Jasmine Zhao of Cell and Developmental Biology Microscopy Core, Perelman School of Medicine, University of Pennsylvania.

Funding Information

This work was financially supported by the NIH Grant R01CA191207 (L.Z. Li) and NIH grant R37CA218072 (LMPV).

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

Supplementary material

11307_2019_1321_MOESM1_ESM.docx (81 kb)
ESM 1 (DOCX 81.2 kb)


  1. 1.
    Li LZ (2012) Imaging mitochondrial redox potential and its possible link to tumor metastatic potential. J Bioenerg Biomembr 44:645–653CrossRefGoogle Scholar
  2. 2.
    Xu HN, Li LZ (2014) Quantitative redox imaging biomarkers for studying tissue metabolic state and its heterogeneity. J Innov Opt Health Sci 7:1430002CrossRefGoogle Scholar
  3. 3.
    Alzbeta C, Dusan C (2014) Tissue fluorophores and their spectroscopic characteristics. In Fluorescence lifetime spectroscopy and imaging. CRC Press, Boca Raton, pp 47–84Google Scholar
  4. 4.
    Chance B, Schoener B, Oshino R, Itshak F, Nakase Y (1979) Oxidation-reduction ratio studies of mitochondria in freeze-trapped samples. NADH and flavoprotein fluorescence signals. J Biol Chem 254:4764–4771Google Scholar
  5. 5.
    Li LZ, Xu HN, Ranji M, Nioka S, Chance B (2009) Mitochondrial redox imaging for cancer diagnostic and therapeutic studies. J Innov Opt Health Sci 2:325–341CrossRefGoogle Scholar
  6. 6.
    Ozawa K, Chance B, Tanaka A, Iwata S, Kitai T, Ikai I (1992) Linear correlation between acetoacetate/beta-hydroxybutyrate in arterial blood and oxidized flavoprotein/reduced pyridine nucleotide in freeze-trapped human liver tissue. Biochim Biophys Acta 1138:350–352CrossRefGoogle Scholar
  7. 7.
    Varone A, Xylas J, Quinn KP, Pouli D, Sridharan G, McLaughlin-Drubin ME, Alonzo C, Lee K, Munger K, Georgakoudi I (2014) Endogenous two-photon fluorescence imaging elucidates metabolic changes related to enhanced glycolysis and glutamine consumption in precancerous epithelial tissues. Cancer Res 74:3067–3075CrossRefGoogle Scholar
  8. 8.
    Li LZ, Sun N (2014) Autofluorescence perspective of cancer diagnostics. In: Ghukasyan V, Heikal AA (eds) Natural biomarkers for cellular metabolism: biology, techniques, and applications. CRC Press, New York, pp 273–297CrossRefGoogle Scholar
  9. 9.
    Kolenc OI, Quinn KP (2018) Evaluating cell metabolism through autofluorescence imaging of NAD(P)H and FAD. Antioxid Redox Signal.
  10. 10.
    Li LZ, Zhou R, Xu HN, Moon L, Zhong T, Kim EJ, Qiao H, Reddy R, Leeper D, Chance B, Glickson JD (2009) Quantitative magnetic resonance and optical imaging biomarkers of melanoma metastatic potential. Proc Natl Acad Sci U S A 106:6608–6613CrossRefGoogle Scholar
  11. 11.
    Xu HN, Tchou J, Feng M, Zhao H, Li LZ (2016) Optical redox imaging indices discriminate human breast cancer from normal tissues. J Biomed Opt 21:114003CrossRefGoogle Scholar
  12. 12.
    Xu HN, Nioka S, Glickson JD, Chance B, Li LZ (2010) Quantitative mitochondrial redox imaging of breast cancer metastatic potential. J Biomed Opt 15:036010CrossRefGoogle Scholar
  13. 13.
    Walsh A, Cook RS, Rexer B, Arteaga CL, Skala MC (2012) Optical imaging of metabolism in HER2 overexpressing breast cancer cells. Biomed Optics Express 3:75–85CrossRefGoogle Scholar
  14. 14.
    Ostrander JH, McMahon CM, Lem S et al (2010) Optical redox ratio differentiates breast cancer cell lines based on estrogen receptor status. Cancer Res 70:4759–4766CrossRefGoogle Scholar
  15. 15.
    Sun N, Xu HN, Luo Q, Li LZ (2016) Potential indexing of the invasiveness of breast cancer cells by mitochondrial redox ratios. Adv Exp Med Biol 923:121–127CrossRefGoogle Scholar
  16. 16.
    Cairns RA, Harris IS, Mak TW (2011) Regulation of cancer cell metabolism. Nat Rev Cancer 11:85–95CrossRefGoogle Scholar
  17. 17.
    DeBerardinis RJ, Chandel NS (2016) Fundamentals of cancer metabolism. Sci Adv 2:e1600200CrossRefGoogle Scholar
  18. 18.
    Xu HN, Feng M, Moon L et al (2013) Redox imaging of the p53-dependent mitochondrial redox state in colon cancer ex vivo. J Innov Opt Health Sci 6:1350016CrossRefGoogle Scholar
  19. 19.
    Xu HN, Nioka S, Li LZ (2013) Imaging heterogeneity in the mitochondrial redox state of premalignant pancreas in the pancreas-specific PTEN-null transgenic mouse model. Biomark Res 1:6CrossRefGoogle Scholar
  20. 20.
    Privette Vinnedge LM, McClaine R, Wagh PK, Wikenheiser-Brokamp KA, Waltz SE, Wells SI (2011) The human DEK oncogene stimulates beta-catenin signaling, invasion and mammosphere formation in breast cancer. Oncogene 30:2741–2752CrossRefGoogle Scholar
  21. 21.
    Yu L, Huang X, Zhang W, Zhao H, Wu G, Lv F, Shi L, Teng Y (2016) Critical role of DEK and its regulation in tumorigenesis and metastasis of hepatocellular carcinoma. Oncotarget 7:26844–26855Google Scholar
  22. 22.
    Privette Vinnedge LM, Benight NM, Wagh PK, Pease NA, Nashu MA, Serrano-Lopez J, Adams AK, Cancelas JA, Waltz SE, Wells SI (2015) The DEK oncogene promotes cellular proliferation through paracrine Wnt signaling in Ron receptor-positive breast cancers. Oncogene 34:2325–2336CrossRefGoogle Scholar
  23. 23.
    Matrka MC, Cimperman KA, Haas SR, Guasch G, Ehrman LA, Waclaw RR, Komurov K, Lane A, Wikenheiser-Brokamp KA, Wells SI (2018) Dek overexpression in murine epithelia increases overt esophageal squamous cell carcinoma incidence. PLoS Genet 14:e1007227CrossRefGoogle Scholar
  24. 24.
    Liu G, Xiong D, Zeng J et al (2017) Prognostic role of DEK in human solid tumors: a meta-analysis. Oncotarget 8:98985–98992Google Scholar
  25. 25.
    Ying G, Wu Y (2015) DEK: a novel early screening and prognostic marker for breast cancer. Mol Med Rep 12:7491–7495CrossRefGoogle Scholar
  26. 26.
    Lin Z, Xu HN, Wang Y, Floros J, Li LZ (2018) Differential expression of PGC1alpha in intratumor redox subpopulations of breast cancer. Adv Exp Med Biol 1072:177–181CrossRefGoogle Scholar
  27. 27.
    Wise-Draper TM, Allen HV, Thobe MN, Jones EE, Habash KB, Munger K, Wells SI (2005) The human DEK proto-oncogene is a senescence inhibitor and an upregulated target of high-risk human papillomavirus E7. J Virol 79:14309–14317CrossRefGoogle Scholar
  28. 28.
    Pate KT, Stringari C, Sprowl-Tanio S, Wang K, TeSlaa T, Hoverter NP, McQuade M, Garner C, Digman MA, Teitell MA, Edwards RA, Gratton E, Waterman ML (2014) Wnt signaling directs a metabolic program of glycolysis and angiogenesis in colon cancer. EMBO J 33:1454–1473Google Scholar
  29. 29.
    Matrka MC, Watanabe M, Muraleedharan R, Lambert PF, Lane AN, Romick-Rosendale LE, Wells SI (2017) Overexpression of the human DEK oncogene reprograms cellular metabolism and promotes glycolysis. PLoS One 12:e0177952CrossRefGoogle Scholar
  30. 30.
    Walsh AJ, Cook RS, Sanders ME, Aurisicchio L, Ciliberto G, Arteaga CL, Skala MC (2014) Quantitative optical imaging of primary tumor organoid metabolism predicts drug response in breast cancer. Cancer Res 74:5184–5194CrossRefGoogle Scholar
  31. 31.
    Alhallak K, Rebello LG, Muldoon TJ, Quinn KP, Rajaram N (2016) Optical redox ratio identifies metastatic potential-dependent changes in breast cancer cell metabolism. Biomed Opt Express 7:4364–4374CrossRefGoogle Scholar
  32. 32.
    Santidrian AF, Matsuno-Yagi A, Ritland M, Seo BB, LeBoeuf SE, Gay LJ, Yagi T, Felding-Habermann B (2013) Mitochondrial complex I activity and NAD+/NADH balance regulate breast cancer progression. J Clin Invest 123:1068–1081CrossRefGoogle Scholar
  33. 33.
    Kunz WS (1988) Evaluation of electron-transfer flavoprotein and alpha-lipoamide dehydrogenase redox states by two-channel fluorimetry and its application to the investigation of beta-oxidation. Biochim Biophys Acta 932:8–16CrossRefGoogle Scholar
  34. 34.
    Kunz WS, Gellerich FN (1993) Quantification of the content of fluorescent flavoproteins in mitochondria from liver, kidney cortex, skeletal muscle, and brain. Biochem Med Metab Biol 50:103–110CrossRefGoogle Scholar
  35. 35.
    Rehman AU, Anwer AG, Gosnell ME, Mahbub SB, Liu G, Goldys EM (2017) Fluorescence quenching of free and bound NADH in HeLa cells determined by hyperspectral imaging and unmixing of cell autofluorescence. Biomed Opt Express 8:1488–1498CrossRefGoogle Scholar
  36. 36.
    Banerjee R (2008) Redox biochemistry. John Wiley & Sons, HobokenGoogle Scholar
  37. 37.
    Holmgren A (1989) Thioredoxin and glutaredoxin systems. J Biol Chem 264:13963–13966Google Scholar
  38. 38.
    Jorgenson TC, Zhong W, Oberley TD (2013) Redox imbalance and biochemical changes in cancer. Cancer Res 73:6118–6123CrossRefGoogle Scholar

Copyright information

© World Molecular Imaging Society 2019

Authors and Affiliations

  1. 1.Rutgers Cancer Institute of New JerseyNew BrunswickUSA
  2. 2.Department of Radiology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaUSA
  3. 3.Cincinnati Children’s Hospital Medical CenterCancer and Blood Diseases InstituteCincinnatiUSA
  4. 4.Department of PediatricsUniversity of Cincinnati College of MedicineCincinnatiUSA
  5. 5.Abramson Cancer Center and Institute of Translational Medicine and Therapeutics, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaUSA

Personalised recommendations