3D image analysis reveals differences of CD30 positive cells and network formation in reactive and malignant human lymphoid tissue (classical Hodgkin Lymphoma)

Autoři: Julia Liebers aff001;  Patrick Wurzel aff002;  Kerstin Bianca Reisinger aff001;  Martin-Leo Hansmann aff001
Působiště autorů: Reference and Consultant Center of Lymph Node and Lymphoma Pathology at Dr. Senckenberg Institute for Pathology, Frankfurt/Main, Hessen, Germany aff001;  Department of Molecular Bioinformatics, Johann Wolfgang Goethe-University Frankfurt/Main, Frankfurt/Main, Hessen, Germany aff002;  Johann-Wolfgang-Goethe-Universität Frankfurt am Main, Frankfurt Institute for Advanced Studies (FIAS), Frankfurt/Main, Hessen, Germany aff003
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
doi: 10.1371/journal.pone.0224156



The examination of histological sections is still the gold standard in diagnostic pathology. Important histopathological diagnostic criteria are nuclear shapes and chromatin distribution as well as nucleus-cytoplasm relation and immunohistochemical properties of surface and intracellular proteins. The aim of this investigation was to evaluate the benefits and drawbacks of three-dimensional imaging of CD30+ cells in classical Hodgkin Lymphoma (cHL) in comparison to CD30+ lymphoid cells in reactive lymphoid tissues.

Materials and results

Using immunoflourescence confocal microscopy and computer-based analysis, we compared CD30+ neoplastic cells in Nodular Sclerosis cHL (NScCHL), Mixed Cellularity cHL (MCcHL), with reactive CD30+ cells in Adenoids (AD) and Lymphadenitis (LAD). We confirmed that the percentage of CD30+ cell volume can be calculated. The amount in lymphadenitis was approx. 1.5%, in adenoids around 2%, in MCcHL up to 4,5% whereas the values for NScHL rose to more than 8% of the total cell cytoplasm. In addition, CD30+ tumour cells (HRS-cells) in cHL had larger volumes, and more protrusions compared to CD30+ reactive cells. Furthermore, the formation of large cell networks turned out to be a typical characteristic of NScHL.


In contrast to 2D histology, 3D laser scanning offers a visualisation of complete cells, their network interaction and spatial distribution in the tissue. The possibility to differentiate cells in regards to volume, surface, shape, and cluster formation enables a new view on further diagnostic and biological questions. 3D includes an increased amount of information as a basis of bioinformatical calculations.

Klíčová slova:

B cells – Cancer detection and diagnosis – Cell differentiation – Cytoplasm – Cytoplasmic staining – Histology – Image analysis – Hodgkin lymphoma


1. Rubin R, Strayer DS, editors. Rubin’s Pathology. Clinicopathologic foundations of medicine; [includes access to online text, cases, images, and audio review questions! 5th ed. Philadelphia, Pa: Wolters Kluwer/Lippincott Williams & Wilkins; 2008.

2. Pantanowitz L, Valenstein PN, Evans AJ, Kaplan KJ, Pfeifer JD, Wilbur DC, et al. Review of the current state of whole slide imaging in pathology. J Pathol Inform. 2011; 2. doi: 10.4103/2153-3539.83746 21886892

3. Kothari S, Phan JH, Stokes TH, Wang MD. Pathology imaging informatics for quantitative analysis of whole-slide images. J Am Med Inform Assoc. 2013; 20: 1099–1108. doi: 10.1136/amiajnl-2012-001540 23959844

4. Bongaerts O, Clevers C, Debets M, Paffen D, Senden L, Rijks K, et al. Conventional Microscopical versus Digital Whole-Slide Imaging-Based Diagnosis of Thin-Layer Cervical Specimens: A Validation Study. J Pathol Inform. 2018; 9. doi: 10.4103/jpi.jpi_28_18 30197818

5. Kuo K-H, Leo JM. Optical Versus Virtual Microscope for Medical Education: A Systematic Review. American Association of Anatomists. 2018; 28: 169. doi: 10.1002/ase.1844 30414261

6. McGhee J. 3-D visualization and animation technologies in anatomical imaging. J Anat. 2009; 216: 264–270. doi: 10.1111/j.1469-7580.2009.01165.x 20002229

7. Giovannini E, Lazzeri P, Milano A, Gaeta M, Ciarmiello A. Clinical Applications of Choline PET/CT in Brain Tumors. CPD. 2014; 21: 121–127. doi: 10.2174/1381612820666140915120742 25225894

8. Schenk JP, Waag K-L, Graf N, Wunsch R, Jourdan C, Behnisch W, et al. 3-D-Visualisierung in der MRT zur Operationsplanung von Wilms-Tumoren. Rofo. 2004; 176: 1447–1452. doi: 10.1055/s-2004-813398

9. Kherlopian AR, Song T, Duan Q, Neimark MA, Po MJ, Gohagan JK, et al. A review of imaging techniques for systems biology. BMC Syst Biol. 2008; 2: 74. doi: 10.1186/1752-0509-2-74 18700030

10. Mankovich NJ, Robertson DR, Cheeseman AM. Three-dimensional image display in medicine. J Digit Imaging. 1990; 3: 69–80. doi: 10.1007/bf03170565 2092812

11. Hacker J, Deutsche Akademie der Naturforscher DAd, editors. Jahrbuch 2017. Deutsche Akademie der Naturforscher Leopoldina—Nationale Akademie der Wissenschaften. 1st ed. Stuttgart: Wissenschaftliche Verlagsgesellschaft; 2018.

12. Hipp JD, Fernandez A, Compton CC, Balis UJ. Why a pathology image should not be considered as a radiology image. J Pathol Inform. 2011; 2. doi: 10.4103/2153-3539.82051 21773057

13. Swerdlow SH, editor. WHO classification of tumours of haematopoietic and lymphoid tissues. … reflects the views of a working group that convened for an Editorial and Consensus Conference at the International Agency for Research on Cancer (IARC), Lyon, October 25–27, 2007. 4th ed. Lyon: Internat. Agency for Research on Cancer; 2008.

14. van der Weyden CA, Pileri SA, Feldman AL, Whisstock J, Prince HM. Understanding CD30 biology and therapeutic targeting: a historical perspective providing insight into future directions. Blood Cancer Journal. 2017; 7: e603 EP -. doi: 10.1038/bcj.2017.85 28885612

15. Küppers R, Klein U, Hansmann ML, Rajewsky K. Cellular origin of human B-cell lymphomas. N Engl J Med. 1999; 341: 1520–1529. doi: 10.1056/NEJM199911113412007 10559454

16. Bräuninger A, Hansmann ML, Strickler JG, Dummer R, Burg G, Rajewsky K, et al. Identification of common germinal-center B-cell precursors in two patients with both Hodgkin’s disease and non-Hodgkin’s lymphoma. N Engl J Med. 1999; 340: 1239–1247. doi: 10.1056/NEJM199904223401604 10210707

17. Kanzler H. Hodgkin and Reed-Sternberg cells in Hodgkin’s disease represent the outgrowth of a dominant tumor clone derived from (crippled) germinal center B cells. J Exp Med. 1996; 184: 1495–1505. doi: 10.1084/jem.184.4.1495 8879220

18. Schwering I, Bräuninger A, Klein U, Jungnickel B, Tinguely M, Diehl V, et al. Loss of the B-lineage-specific gene expression program in Hodgkin and Reed-Sternberg cells of Hodgkin lymphoma. Proceedings of the National Academy of Sciences. 2003; 101: 1505–1512. doi: 10.1182/blood-2002-03-0839

19. Stein H, Gerdes J, Schwab U, Lemke H, Mason DY, Ziegler A, et al. Identification of Hodgkin and Sternberg-reed cells as a unique cell type derived from a newly-detected small-cell population. Int J Cancer. 1982; 30: 445–459. doi: 10.1002/ijc.2910300411 6754630

20. Schwab U, Stein H, Gerdes J, Lemke H, Kirchner H, Schaadt M, et al. Production of a monoclonal antibody specific for Hodgkin and Sternberg–Reed cells of Hodgkin’s disease and a subset of normal lymphoid cells. Nature. 1982; 299: 65–67. doi: 10.1038/299065a0

21. Saalfeld S, Fetter R, Cardona A, Tomancak P. Elastic volume reconstruction from series of ultra-thin microscopy sections. Nature Methods. 2012; 9: 717 EP -. doi: 10.1038/nmeth.2072 22688414

22. Verhoef EI, van Cappellen WA, Slotman JA, Kremers G-J, Ewing-Graham PC, Houtsmuller AB, et al. Three-dimensional architecture of common benign and pre-cancerous prostate epithelial lesions. Histopathology. 2019. doi: 10.1111/his.13848

23. 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. doi: 10.1038/s41598-017-09117-0 28839164

24. Schäfer H, Schäfer T, Ackermann J, Dichter N, Döring C, Hartmann S, et al. CD30 cell graphs of Hodgkin lymphoma are not scale-free—an image analysis approach. Bioinformatics. 2016; 32: 122–129. doi: 10.1093/bioinformatics/btv542

25. He L, Long LR, Antani S, Thoma GR. Histology image analysis for carcinoma detection and grading. Comput Methods Programs Biomed. 2012; 107: 538–556. doi: 10.1016/j.cmpb.2011.12.007 22436890

26. Oswald MS, Hansmann M-L. 3D approach visualizing cellular networks in human lymph nodes. Acta Histochem. 2018; 120: 720–727. doi: 10.1016/j.acthis.2018.08.001 30104013

27. Schwarting R, Gerdes J, Dürkop H, Falini B, Pileri S, Stein H. BER-H2: a new anti-Ki-1 (CD30) monoclonal antibody directed at a formol-resistant epitope. Proceedings of the National Academy of Sciences. 1989; 74: 1678–1689.

28. Kadin ME. Regulation of CD30 antigen expression and its potential significance for human disease. Am J Pathol. 2000; 156: 1479–1484. doi: 10.1016/S0002-9440(10)65018-3 10793058

29. Weniger MA, Tiacci E, Schneider S, Arnolds J, Rüschenbaum S, Duppach J, et al. Human CD30+ B cells represent a unique subset related to Hodgkin lymphoma cells. J Clin Invest. 2018; 128: 2996–3007. doi: 10.1172/JCI95993 29889102

30. Sperling S, Fiedler P, Lechner M, Pollithy A, Ehrenberg S, Schiefer A-I, et al. Chronic CD30 signaling in B cells results in lymphomagenesis by driving the expansion of plasmablasts and B1 cells. Blood. 2019; 133: 2597–2609. doi: 10.1182/blood.2018880138 30962205

31. Hansen HP, Engels H-M, Dams M, Paes Leme AF, Pauletti BA, Simhadri VL, et al. Protrusion-guided extracellular vesicles mediate CD30 trans-signalling in the microenvironment of Hodgkin’s lymphoma. J Pathol. 2014; 232: 405–414. doi: 10.1002/path.4306 24659185

32. Sethi T, van Nguyen, Li S, Morgan D, Greer J, Reddy N. Differences in outcome of patients with syncytial variant Hodgkin lymphoma compared with typical nodular sclerosis Hodgkin lymphoma. Ther Adv Hematol. 2017; 8: 13–20. doi: 10.1177/2040620716676256 28042455

33. Al-Antary E, Jesudas R, George A, Poulik J, Savaşan S. Syncytial Variant Nodular Sclerosis Classical Hodgkin Lymphoma in an Adolescent and Review of the Literature: A Unique Entity. J Pediatr Hematol Oncol. 2018. doi: 10.1097/MPH.0000000000001245 30028823

34. Rengstl B, Newrzela S, Heinrich T, Weiser C, Thalheimer FB, Schmid F, et al. Incomplete cytokinesis and re-fusion of small mononucleated Hodgkin cells lead to giant multinucleated Reed-Sternberg cells. Proceedings of the National Academy of Sciences. 2013; 110: 20729–20734. doi: 10.1073/pnas.1312509110 24302766

35. Skinnider BF, Mak TW. The role of cytokines in classical Hodgkin lymphoma. Proceedings of the National Academy of Sciences. 2002; 99: 4283–4297. doi: 10.1182/blood-2002-01-0099 12036854

36. Rengstl B, Kim S, Döring C, Weiser C, Bein J, Bankov K, et al. Small and big Hodgkin-Reed-Sternberg cells of Hodgkin lymphoma cell lines L-428 and L-1236 lack consistent differences in gene expression profiles and are capable to reconstitute each other. PLoS ONE. 2017; 12: e0177378. doi: 10.1371/journal.pone.0177378 28505189

37. Janz M, Hummel M, Truss M, Wollert-Wulf B, Mathas S, Jöhrens K, et al. Classical Hodgkin lymphoma is characterized by high constitutive expression of activating transcription factor 3 (ATF3), which promotes viability of Hodgkin/Reed-Sternberg cells. Proceedings of the National Academy of Sciences. 2006; 107: 2536–2539.16263788

38. de Jong D, Roemer MGM, Chan JKC, Goodlad J, Gratzinger D, Chadburn A, et al. B-Cell and Classical Hodgkin Lymphomas Associated With Immunodeficiency: 2015 SH/EAHP Workshop Report—Part 2. Am J Clin Pathol. 2017; 147: 153–170. doi: 10.1093/ajcp/aqw216

39. Scott LJ. Brentuximab Vedotin: A Review in CD30-Positive Hodgkin Lymphoma. Drugs. 2017; 77: 435–445. doi: 10.1007/s40265-017-0705-5 28190142

40. Isherwood B, Timpson P, McGhee EJ, Anderson KI, Canel M, Serrels A, et al. Live cell in vitro and in vivo imaging applications: accelerating drug discovery. Pharmaceutics. 2011; 3: 141–170. doi: 10.3390/pharmaceutics3020141 24310493

41. Zhang LW, Monteiro-Riviere NA. Use of confocal microscopy for nanoparticle drug delivery through skin. J Biomed Opt. 2013; 18: 61214. doi: 10.1117/1.JBO.18.6.061214 23224242

42. Donnadieu E, Michel Y, Hansmann M-L. Live Imaging of Resident T-Cell Migration in Human Lymphoid Tissue Slices Using Confocal Microscopy. Methods Mol Biol. 2019; 1930: 75–82. doi: 10.1007/978-1-4939-9036-8_10 30610601

43. Fugl A, Andersen CL. Epstein-Barr virus and its association with disease—a review of relevance to general practice. BMC Fam Pract. 2019; 20: 62. doi: 10.1186/s12875-019-0954-3

44. Pavlovic A, Glavina Durdov M, Capkun V, Jakelic Pitesa J, Bozic Sakic M. Classical Hodgkin Lymphoma with Positive Epstein-Barr Virus Status is Associated with More FOXP3 Regulatory T Cells. Med Sci Monit. 2016; 22: 2340–2346. doi: 10.12659/MSM.896629 27377121

45. Murray PG, Young LS. An etiological role for the Epstein-Barr virus in the pathogenesis of classical Hodgkin lymphoma. Blood. 2019; 134: 591–596. doi: 10.1182/blood.2019000568 31186275

46. Dörsam B, Bösl T, Reiners KS, Barnert S, Schubert R, Shatnyeva O, et al. Hodgkin Lymphoma-Derived Extracellular Vesicles Change the Secretome of Fibroblasts Toward a CAF Phenotype. Front Immunol. 2018; 9: 1358. doi: 10.3389/fimmu.2018.01358 29967610

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