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High-Resolution Microscopy for Imaging Cancer Pathobiology

  • Yang LiuEmail author
  • Jianquan Xu
Update on Technological Innovations for Cancer Detection and Treatment (T Dickherber, Section Editor)
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Part of the following topical collections:
  1. Topical Collection on Update on Technological Innovations for Cancer Detection and Treatment

Abstract

Purpose of Review

Light microscopy plays an essential role in clinical diagnosis and understanding the pathogenesis of cancer. Conventional bright-field microscope is used to visualize abnormality in tissue architecture and nuclear morphology, but often suffers from many limitations. This review focuses on the potential of new imaging techniques to improve basic and clinical research in pathobiology.

Recent Findings

Light microscopy has significantly expanded its ability in resolution, imaging volume, speed, and contrast. It now allows 3D high-resolution volumetric imaging of tissue architecture from large tissue and molecular structures at nanometer resolution.

Summary

Pathologists and researchers now have access to various imaging tools to study cancer pathobiology in both breadth and depth. Although clinical adoption of a new technique is slow, the new imaging tools will provide significant new insights and open new avenues for improving early cancer detection and personalized risk assessment and identifying the best treatment strategies.

Keywords

Light microscopy 3D volumetric imaging Super-resolution microscopy Label-free imaging 

Notes

Acknowledgments

Due to the large body of literatures, we cannot cover all of the related topics and publications. We acknowledge Dr. Hongbin Ma for preparing Fig. 2d. We apologize to researchers whose work is missed in this review.

Funding Information

We acknowledge the funding support from National Institute of Health Grant Numbers R01CA185363 and R33CA225494.

Compliance With Ethical Standards

Conflict of Interest

Jianquan Xu declares no conflict of interest. Yang Liu is the co-inventor for several US patents on light microscopy techniques to analyze nanoscale nuclear architecture for cancer diagnosis and other applications, owned by the University of Pittsburgh.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

References

  1. 1.
    Vennalaganti P, Kanakadandi V, Goldblum JR, Mathur SC, Patil DT, Offerhaus GJ, et al. Discordance among pathologists in the United States and Europe in diagnosis of low-grade dysplasia for patients with Barrett’s esophagus. Gastroenterology. 2017;152(3):564–70 e4.  https://doi.org/10.1053/j.gastro.2016.10.041.CrossRefGoogle Scholar
  2. 2.
    Baker M. Building better biobanks. Nature. 2012;486:141–6.  https://doi.org/10.1038/486141a.CrossRefGoogle Scholar
  3. 3.
    Kose K, Gou M, Yelamos O, Cordova M, Rossi AM, Nehal KS, et al. Automated video-mosaicking approach for confocal microscopic imaging in vivo: an approach to address challenges in imaging living tissue and extend field of view. Sci Rep. 2017;7(1):10759.  https://doi.org/10.1038/s41598-017-11072-9.CrossRefGoogle Scholar
  4. 4.
    Glaser AK, Reder NP, Chen Y, McCarty EF, Yin C, Wei L, et al. Light-sheet microscopy for slide-free non-destructive pathology of large clinical specimens. Nat Biomed Eng. 2017;1:0084.  https://doi.org/10.1038/s41551-017-0084.CrossRefGoogle Scholar
  5. 5.
    Sun Y, You S, Tu H, Spillman DR Jr, Chaney EJ, Marjanovic M, et al. Intraoperative visualization of the tumor microenvironment and quantification of extracellular vesicles by label-free nonlinear imaging. Sci Adv. 2018;4(12):eaau5603.  https://doi.org/10.1126/sciadv.aau5603.CrossRefGoogle Scholar
  6. 6.
    Nandy S, Sanders M, Zhu Q. Classification and analysis of human ovarian tissue using full field optical coherence tomography. Biomed Opt Express. 2016;7(12):5182–7.  https://doi.org/10.1364/BOE.7.005182.CrossRefGoogle Scholar
  7. 7.
    Schlichenmeyer TC, Wang M, Elfer KN, Brown JQ. Video-rate structured illumination microscopy for high-throughput imaging of large tissue areas. Biomed Opt Express. 2014;5(2):366–77.  https://doi.org/10.1364/BOE.5.000366.CrossRefGoogle Scholar
  8. 8.
    Ji M, Orringer DA, Freudiger CW, Ramkissoon S, Liu X, Lau D, et al. Rapid, label-free detection of brain tumors with stimulated Raman scattering microscopy. Sci Transl Med. 2013;5(201):201ra119.  https://doi.org/10.1126/scitranslmed.3005954.CrossRefGoogle Scholar
  9. 9.
    Mittal S, Yeh K, Leslie LS, Kenkel S, Kajdacsy-Balla A, Bhargava R. Simultaneous cancer and tumor microenvironment subtyping using confocal infrared microscopy for all-digital molecular histopathology. Proc Natl Acad Sci U S A. 2018;115(25):E5651–E60.  https://doi.org/10.1073/pnas.1719551115. CrossRefGoogle Scholar
  10. 10.
    Fereidouni F, Harmany ZT, Tian M, Todd A, Kintner JA, McPherson JD, et al. Microscopy with ultraviolet surface excitation for rapid slide-free histology. Nat Biomed Eng. 2017;1:957–66.CrossRefGoogle Scholar
  11. 11.
    Rajadhyaksha M, Marghoob A, Rossi A, Halpern AC, Nehal KS. Reflectance confocal microscopy of skin in vivo: from bench to bedside. Lasers Surg Med. 2017;49(1):7–19.  https://doi.org/10.1002/lsm.22600.CrossRefGoogle Scholar
  12. 12.
    Fu YY, Lin CW, Enikolopov G, Sibley E, Chiang AS, Tang SC. Microtome-free 3-dimensional confocal imaging method for visualization of mouse intestine with subcellular-level resolution. Gastroenterology. 2009;137(2):453–65.  https://doi.org/10.1053/j.gastro.2009.05.008.CrossRefGoogle Scholar
  13. 13.
    Jain M, Rajadhyaksha M, Nehal K. Implementation of fluorescence confocal mosaicking microscopy by “early adopter” Mohs surgeons and dermatologists: recent progress. J Biomed Opt. 2017;22(2):24002.  https://doi.org/10.1117/1.JBO.22.2.024002.CrossRefGoogle Scholar
  14. 14.
    Karen JK, Gareau DS, Dusza SW, Tudisco M, Rajadhyaksha M, Nehal KS. Detection of basal cell carcinomas in Mohs excisions with fluorescence confocal mosaicing microscopy. Br J Dermatol. 2009;160(6):1242–50.  https://doi.org/10.1111/j.1365-2133.2009.09141.x.CrossRefGoogle Scholar
  15. 15.
    Ragazzi M, Piana S, Longo C, Castagnetti F, Foroni M, Ferrari G, et al. Fluorescence confocal microscopy for pathologists. Mod Pathol. 2014;27(3):460–71.  https://doi.org/10.1038/modpathol.2013.158.CrossRefGoogle Scholar
  16. 16.
    Walsh AJ, Cook RS, Manning HC, Hicks DJ, Lafontant A, Arteaga CL, et al. Optical metabolic imaging identifies glycolytic levels, subtypes, and early-treatment response in breast cancer. Cancer Res. 2013;73(20):6164–74.  https://doi.org/10.1158/0008-5472.CAN-13-0527.CrossRefGoogle Scholar
  17. 17.
    Walsh AJ, Cook RS, Sanders ME, Aurisicchio L, Ciliberto G, Arteaga CL, et al. Quantitative optical imaging of primary tumor organoid metabolism predicts drug response in breast cancer. Cancer Res. 2014;74(18):5184–94.  https://doi.org/10.1158/0008-5472.CAN-14-0663.CrossRefGoogle Scholar
  18. 18.
    Pouli D, Balu M, Alonzo CA, Liu Z, Quinn KP, Rius-Diaz F, et al. Imaging mitochondrial dynamics in human skin reveals depth-dependent hypoxia and malignant potential for diagnosis. Sci Transl Med. 2016;8(367):367ra169.  https://doi.org/10.1126/scitranslmed.aag2202.CrossRefGoogle Scholar
  19. 19.
    Tilbury KB, Campbell KR, Eliceiri KW, Salih SM, Patankar M, Campagnola PJ. Stromal alterations in ovarian cancers via wavelength dependent second harmonic generation microscopy and optical scattering. BMC Cancer. 2017;17(1):102.  https://doi.org/10.1186/s12885-017-3090-2.CrossRefGoogle Scholar
  20. 20.
    Mayerich D, Abbott L, McCormick B. Knife-edge scanning microscopy for imaging and reconstruction of three-dimensional anatomical structures of the mouse brain. J Microsc. 2008;231(Pt 1:134–43.  https://doi.org/10.1111/j.1365-2818.2008.02024.x.CrossRefGoogle Scholar
  21. 21.
    Nojima S, Susaki EA, Yoshida K, Takemoto H, Tsujimura N, Iijima S, et al. CUBIC pathology: three-dimensional imaging for pathological diagnosis. Sci Rep. 2017;7(1):9269.  https://doi.org/10.1038/s41598-017-09117-0.CrossRefGoogle Scholar
  22. 22.
    Rust MJ, Bates M, Zhuang XW. Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM). Nat Methods. 2006;3:793–5.CrossRefGoogle Scholar
  23. 23.
    Heilemann M, van de Linde S, Schuttpelz M, Kasper R, Seefeldt B, Mukherjee A, et al. Subdiffraction-resolution fluorescence imaging with conventional fluorescent probes. Angew Chem Int Ed Engl. 2008;47(33):6172–6.  https://doi.org/10.1002/anie.200802376.CrossRefGoogle Scholar
  24. 24.
    Hess ST, Girirajan TPK, Mason MD. Ultra-high resolution imaging by fluorescence photoactivation localization microscopy. Biophys J. 2006;91:4258–72.  https://doi.org/10.1529/biophysj.106.091116.CrossRefGoogle Scholar
  25. 25.
    Betzig E, Patterson GH, Sougrat R, Lindwasser OW, Olenych S, Bonifacino JS, et al. Imaging proteins intracellular at nanometer fluorescent resolution. Science. 2006;313:1642–5.CrossRefGoogle Scholar
  26. 26.
    Klar TA, Jakobs S, Dyba M, Egner A, Hell SW. Fluorescence microscopy with diffraction resolution barrier broken by stimulated emission. Proc Natl Acad Sci U S A. 2000;97:8206–10.CrossRefGoogle Scholar
  27. 27.
    Gustafsson MG, Shao L, Carlton PM, Wang CJ, Golubovskaya IN, Cande WZ, et al. Three-dimensional resolution doubling in wide-field fluorescence microscopy by structured illumination. Biophys J. 2008;94:4957–70.  https://doi.org/10.1529/biophysj.107.120345.CrossRefGoogle Scholar
  28. 28.
    Chozinski TJ, Halpern AR, Okawa H, Kim HJ, Tremel GJ, Wong ROL, et al. Expansion microscopy with conventional antibodies and fluorescent proteins. Nat Methods. 2016;13:485–8.  https://doi.org/10.1038/nmeth.3833.CrossRefGoogle Scholar
  29. 29.
    Chen F, Tillberg PW, Boyden ES. Expansion microscopy. Science. 2015;347:543–8.  https://doi.org/10.1126/science.1260088.CrossRefGoogle Scholar
  30. 30.
    Feinberg AP, Koldobskiy MA, Göndör A. Epigenetic modulators, modifiers and mediators in cancer aetiology and progression. Nat Rev Genet. 2016;17:284–99.  https://doi.org/10.1038/nrg.2016.13.CrossRefGoogle Scholar
  31. 31.
    Feinberg AP. The key role of epigenetics in human disease prevention and mitigation. N Engl J Med. 2018;378(14):1323–34.  https://doi.org/10.1056/NEJMra1402513.CrossRefGoogle Scholar
  32. 32.
    Feinberg AP, Ohlsson R, Henikoff S. The epigenetic progenitor origin of human cancer. Nat Rev Genet. 2006;7:21–33.  https://doi.org/10.1038/nrg1748.CrossRefGoogle Scholar
  33. 33.
    Sathitruangsak C, Righolt CH, Klewes L, Tammur P, Ilus T, Tamm A, et al. Quantitative superresolution microscopy reveals differences in nuclear DNA organization of multiple myeloma and monoclonal gammopathy of undetermined significance. J Cell Biochem. 2015;116(5):704–10.  https://doi.org/10.1002/jcb.25030.CrossRefGoogle Scholar
  34. 34.
    Ilgen P, Stoldt S, Conradi LC, Wurm CA, Ruschoff J, Ghadimi BM, et al. STED super-resolution microscopy of clinical paraffin-embedded human rectal cancer tissue. PLoS One. 2014;9:e101563.  https://doi.org/10.1371/journal.pone.0101563.CrossRefGoogle Scholar
  35. 35.
    Creech MK, Wang J, Nan X, Gibbs SL. Superresolution imaging of clinical formalin fixed paraffin embedded breast cancer with single molecule localization microscopy. Sci Rep. 2016;7:40766.  https://doi.org/10.1038/srep40766.CrossRefGoogle Scholar
  36. 36.
    Tobin SJ, Wakefield DL, Jones V, Liu X, Schmolze D, Jovanovic-Talisman T. Single molecule localization microscopy coupled with touch preparation for the quantification of trastuzumab-bound HER2. Sci Rep. 2018;8(1):15154.  https://doi.org/10.1038/s41598-018-33225-0.CrossRefGoogle Scholar
  37. 37.
    Zhao Y, Bucur O, Irshad H, Chen F, Weins A, Stancu AL, et al. Nanoscale imaging of clinical specimens using pathology-optimized expansion microscopy. Nat Biotechnol. 2017;35(8):757–64.  https://doi.org/10.1038/nbt.3892.CrossRefGoogle Scholar
  38. 38.
    Ma H, Jiang W, Xu J, Liu Y. Enhanced super-resolution microscopy by extreme value based emitter recovery. bioRxiv. 2018:295261.  https://doi.org/10.1101/295261.
  39. 39.
    Ma H, Xu J, Liu Y. WindSTORM: robust online image processing for high-throughput nanoscopy. Sci Adv. 2019;5:eaaw0683.CrossRefGoogle Scholar
  40. 40.
    Xu J, Ma H, Ma H, Jiang W, Duan M, Zhao S, et al. Super-resolution imaging reveals the evolution of higher-order chromatin folding in early carcinogenesis. bioRxiv. 2019:672105.  https://doi.org/10.1101/672105.
  41. 41.
    Ma H, Fu R, Xu J, Liu Y. A simple and cost-effective setup for super-resolution localization microscopy. Sci Rep. 2017;7:1542.  https://doi.org/10.1038/s41598-017-01606-6.CrossRefGoogle Scholar
  42. 42.
    Paidi SK, Diaz PM, Dadgar S, Jenkins SV, Quick CM, Griffin RJ, et al. Label-free Raman spectroscopy reveals signatures of radiation resistance in the tumor microenvironment. Cancer Res. 2019;79(8):2054–64.  https://doi.org/10.1158/0008-5472.CAN-18-2732.CrossRefGoogle Scholar
  43. 43.
    Georgakoudi I, Jacobson BC, Van Dam J, Backman V, Wallace MB, Muller MG, et al. Fluorescence, reflectance, and light-scattering spectroscopy for evaluating dysplasia in patients with Barrett’s esophagus. Gastroenterology. 2001;120(7):1620–9.CrossRefGoogle Scholar
  44. 44.
    Park Y, Depeursinge C, Popescu G. Quantitative phase imaging in biomedicine. Nat Photonics. 2018;12(10):578–89.  https://doi.org/10.1038/s41566-018-0253-x.CrossRefGoogle Scholar
  45. 45.
    Subramanian H, Pradhan P, Liu Y, Capoglu IR, Li X, Rogers JD, et al. Optical methodology for detecting histologically unapparent nanoscale consequences of genetic alterations in biological cells. Proc Natl Acad Sci U S A. 2008;105:20118–23.  https://doi.org/10.1073/pnas.0804723105.CrossRefGoogle Scholar
  46. 46.
    Itzkan I, Qiu L, Fang H, Zaman MM, Vitkin E, Ghiran IC, et al. Confocal light absorption and scattering spectroscopic microscopy monitors organelles in live cells with no exogenous labels. Proc Natl Acad Sci U S A. 2007;104:17255–60.  https://doi.org/10.1073/pnas.0708669104.CrossRefGoogle Scholar
  47. 47.
    Ho D, Drake TK, Smith-McCune KK, Darragh TM, Hwang LY, Wax A. Feasibility of clinical detection of cervical dysplasia using angle-resolved low coherence interferometry measurements of depth-resolved nuclear morphology. Int J Cancer. 2017;140(6):1447–56.  https://doi.org/10.1002/ijc.30539.CrossRefGoogle Scholar
  48. 48.
    Alexandrov SA, Uttam S, Bista RK, Staton KD, Liu Y. Spectral encoding of spatial frequency approach for characterization of nanoscale structures. Appl Phys Lett. 2012;101:33702.CrossRefGoogle Scholar
  49. 49.
    Uttam S, Pham HV, LaFace J, Leibowitz B, Yu J, Brand RE, et al. Early prediction of cancer progression by depth-resolved nanoscale mapping of nuclear architecture from unstained tissue specimens. Cancer Res. 2015;75:4718–27.  https://doi.org/10.1158/0008-5472.CAN-15-1274.CrossRefGoogle Scholar
  50. 50.
    Cherkezyan L, Stypula-Cyrus Y, Subramanian H, White C, Dela Cruz M, Wali RK, et al. Nanoscale changes in chromatin organization represent the initial steps of tumorigenesis: a transmission electron microscopy study. BMC Cancer. 2014;14:189.  https://doi.org/10.1186/1471-2407-14-189.CrossRefGoogle Scholar
  51. 51.
    Sridharan S, Macias V, Tangella K, Kajdacsy-Balla A, Popescu G. Prediction of prostate cancer recurrence using quantitative phase imaging. Sci Rep. 2015;5:9976.  https://doi.org/10.1038/srep09976.CrossRefGoogle Scholar
  52. 52.
    Pham HV, Pantanowitz L, Liu Y. Quantitative phase imaging to improve the diagnostic accuracy of urine cytology. Cancer Cytopathol. 2016;124(9):641–50.  https://doi.org/10.1002/cncy.21734.CrossRefGoogle Scholar
  53. 53.
    Bauer GM, Stypula-Cyrus Y, Subramanian H, Cherkezyan L, Viswanathan P, Zhang D, et al. The transformation of the nuclear nanoarchitecture in human field carcinogenesis. Future Sci OA. 2017;3(3):FSO206.  https://doi.org/10.4155/fsoa-2017-0027.CrossRefGoogle Scholar
  54. 54.
    Lenz P, Bettenworth D, Krausewitz P, Bruckner M, Ketelhut S, von Bally G, et al. Digital holographic microscopy quantifies the degree of inflammation in experimental colitis. Integr Biol (Camb). 2013;5(3):624–30.  https://doi.org/10.1039/c2ib20227a.CrossRefGoogle Scholar
  55. 55.
    Subramanian H, Roy HK, Pradhan P, Goldberg MJ, Muldoon J, Brand RE, et al. Nanoscale cellular changes in field carcinogenesis detected by partial wave spectroscopy. Cancer Res. 2009;69:5357–63.  https://doi.org/10.1158/0008-5472.Can-08-3895.CrossRefGoogle Scholar
  56. 56.
    Wax A, Terry NG, Dellon ES, Shaheen NJ. Angle-resolved low coherence interferometry for detection of dysplasia in Barrett’s esophagus. Gastroenterology. 2011;141(2):443–7, 7 e1–2.  https://doi.org/10.1053/j.gastro.2011.06.020.CrossRefGoogle Scholar
  57. 57.
    Uttam S, Liu Y. Fourier phase based depth-resolved nanoscale nuclear architecture mapping for cancer detection. Methods. 2018;136:134–51.  https://doi.org/10.1016/j.ymeth.2017.10.011.CrossRefGoogle Scholar
  58. 58.
    Uttam S, Liu Y. Fourier phase in Fourier-domain optical coherence tomography. J Opt Soc Am A Opt Image Sci Vis. 2015;32:2286–306.CrossRefGoogle Scholar
  59. 59.
    Stanly TA, Fritzsche M, Banerji S, Garcia E, Bernardino de la Serna J, Jackson DG, et al. Critical importance of appropriate fixation conditions for faithful imaging of receptor microclusters. Biol Open. 2016;5(9):1343–50.  https://doi.org/10.1242/bio.019943.CrossRefGoogle Scholar
  60. 60.
    Richter KN, Revelo NH, Seitz KJ, Helm MS, Sarkar D, Saleeb RS, et al. Glyoxal as an alternative fixative to formaldehyde in immunostaining and super-resolution microscopy. EMBO J. 2017;37:e201695709.  https://doi.org/10.15252/embj.201695709.Google Scholar
  61. 61.
    Kerr E, Kiyuna T, Boyle S, Saito A, Thomas JS, Bickmore WA. Changes in chromatin structure during processing of wax-embedded tissue sections. Chromosom Res. 2010;18:677–88.  https://doi.org/10.1007/s10577-010-9147-6.CrossRefGoogle Scholar
  62. 62.
    Xu J, Ma H, Liu Y. Stochastic optical reconstruction microscopy (STORM). Curr Protoc Cytom. 2017;2017:12.46.1–12.46.27.  https://doi.org/10.1002/cpcy.23.CrossRefGoogle Scholar
  63. 63.
    Hammond ME, Hayes DF, Dowsett M, Allred DC, Hagerty KL, Badve S, et al. American Society of Clinical Oncology/College of American Pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer (unabridged version). Arch Pathol Lab Med. 2010;134(7):e48–72.  https://doi.org/10.1043/1543-2165-134.7.e48.Google Scholar

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Authors and Affiliations

  1. 1.Biomedical Optical Imaging Laboratory, Departments of Medicine and BioengineeringUniversity of PittsburghPittsburghUSA

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