Higher-order connections between stereotyped subsets: implications for improved patient classification in CLL

Author:

Agathangelidis Andreas1,Chatzidimitriou Anastasia12,Gemenetzi Katerina13,Giudicelli Veronique4ORCID,Karypidou Maria1,Plevova Karla56ORCID,Davis Zadie7,Yan Xiao-Jie8ORCID,Jeromin Sabine9,Schneider Christof10,Pedersen Lone Bredo11,Tschumper Renee C.12,Sutton Lesley-Ann2,Baliakas Panagiotis13,Scarfò Lydia14,van Gastel Ellen J.15,Armand Marine16,Tausch Eugen17,Biderman Bella18ORCID,Baer Constance9,Bagnara Davide19,Navarro Alba2021,Langlois de Septenville Anne16,Guido Valentina22,Mitterbauer-Hohendanner Gerlinde23,Dimovski Aleksandar24,Brieghel Christian11ORCID,Lawless Sarah25,Meggendorfer Manja9,Brazdilova Kamila56,Ritgen Matthias26,Facco Monica2728ORCID,Tresoldi Cristina29,Visentin Andrea2728,Patriarca Andrea30ORCID,Catherwood Mark25,Bonello Lisa31,Sudarikov Andrey18ORCID,Vanura Katrina23,Roumelioti Maria32,Skuhrova Francova Hana5,Moysiadis Theodoros1ORCID,Veronese Silvio22ORCID,Giannopoulos Krzysztof33,Mansouri Larry2,Karan-Djurasevic Teodora34,Sandaltzopoulos Raphael3,Bödör Csaba35,Fais Franco1936ORCID,Kater Arnon37ORCID,Panovska Irina38,Rossi Davide39,Alshemmari Salem40ORCID,Panagiotidis Panagiotis32,Costeas Paul4142,Espinet Blanca43ORCID,Antic Darko44,Foroni Letizia45,Montillo Marco22,Trentin Livio2728ORCID,Stavroyianni Niki46,Gaidano Gianluca30,Francia di Celle Paola31,Niemann Carsten11ORCID,Campo Elias202147ORCID,Anagnostopoulos Achilles45ORCID,Pott Christiane26,Fischer Kirsten48,Hallek Michael49,Oscier David7,Stilgenbauer Stephan17,Haferlach Claudia9,Jelinek Diane50,Chiorazzi Nicholas8,Pospisilova Sarka56ORCID,Lefranc Marie-Paule4ORCID,Kossida Sofia4ORCID,Langerak Anton W.15ORCID,Belessi Chrysoula51,Davi Frederic15,Rosenquist Richard252,Ghia Paolo14ORCID,Stamatopoulos Kostas12

Affiliation:

1. Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece;

2. Department of Molecular Medicine and Surgery, Karolinska Institute, Stockholm, Sweden;

3. Department of Molecular Biology and Genetics, Democritus University of Thrace, Alexandroupolis, Greece;

4. International ImMunoGeneTics Information System (IMGT), Laboratoire d’ImmunoGénétique Moléculaire (LIGM), Institut de Génétique Humaine (IGH), Unité Mixte de Recherche (UMR), Centre National de la Recherche Scientifique (CNRS), Université de Montpellier, Montpellier, France;

5. Department of Internal Medicine, Hematology and Oncology, Faculty of Medicine, Masaryk University–University Hospital Brno, Brno, Czech Republic;

6. Center of Molecular Medicine, Central European Institute of Technology, Masaryk University, Brno, Czech Republic;

7. Department of Haematology, Royal Bournemouth Hospital, Bournemouth, United Kingdom;

8. The Feinstein Institute for Medical Research, Northwell Health, Manhasset, NY;

9. MLL Munich Leukemia Laboratory, Munich, Germany;

10. University Hospital Medical Center, Ulm, Germany;

11. Deparment of Hematology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark;

12. Department of Immunology, Mayo Clinic, Rochester, MN;

13. Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden;

14. Strategic Research Program on CLL, B-Cell Neoplasia Unit, Division of Experimental Oncology, Università Vita-Salute San Raffaele/Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Ospedale San Raffaele, Milan, Italy;

15. Laboratory Medical Immunology, Department of Immunology, Erasmus MC, University Medical Center (UMC), Rotterdam, The Netherlands;

16. Assistance Publique–Hôpitaux de Paris (AP-HP), Hôpital Pitié-Salpêtrière, Department of Biological Hematology, Sorbonne Université, UMR_S 1138, Centre de Recherche des Cordeliers, Paris, France;

17. Department of Internal Medicine III, Ulm University, Ulm, Germany;

18. National Research Center for Hematology, Moscow, Russia;

19. Department of Experimental Medicine, University of Genoa, Genoa, Italy;

20. Centro de Investigacion Biomedica en Red en Oncologia (CIBERONC), Madrid, Spain;

21. Institut d’Investigacions Biomediques August Pi I Sunyer, Barcelona, Spain;

22. Molecular Pathology Unit, Haematology Department, Niguarda Cancer Center, Niguarda Hospital, Milan, Italy;

23. Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria;

24. Faculty of Pharmacy, Ss Cyril and Methodius University of Skopje, Skopje, Republic of Northern Macedonia;

25. Clinical Haematology, Belfast City Hospital, Belfast Health and Social Care Trust, Belfast, United Kingdom;

26. Second Medical Department, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany;

27. Hematology and Clinical Immunology Unit, Department of Medicine (DIMED), University of Padua, Padua, Italy;

28. Veneto Institute of Molecular Medicine, Padua, Italy;

29. Division of Immunology, Transplantation and Infectious Diseases, IRCCS San Raffaele Scientific Institute, Milan, Italy;

30. Division of Hematology, Department of Translational Medicine, University of Eastern Piedmont–Ospedale Maggiore della Carità, Novara, Italy;

31. General Anatomopathology and Molecular Oncogenetics, Azienda Ospedaliero Universitaria (AOU), City of Health and Science of Turin, Turin, Italy;

32. First Department of Propaedeutic Medicine, University of Athens, Athens, Greece;

33. Experimental Hematooncology Department, Medical University of Lublin, Lublin, Poland;

34. Institute of Molecular Genetics and Genetic Engineering, University of Belgrade, Belgrade, Serbia;

35. MTA-SE Momentum Molecular Oncohematology Research Group, First Department of Pathology and Experimental Cancer Research, Semmelweis University, Budapest, Hungary;

36. UO Molecular Pathology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy;

37. Department of Hematology, Amsterdam Infection and Immunity Institute, Cancer Center Amsterdam, Amsterdam UMC–University of Amsterdam, Amsterdam, The Netherlands;

38. Department of Hematology, Faculty of Medicine, Ss Cyril and Methodius University of Skopje, Skopje, Republic of Northern Macedonia;

39. Division of Hematology, Oncology Institute of Southern Switzerland, Bellinzona, Switzerland;

40. Department of Medicine, Faculty of Medicine, Kuwait University, Safat, Kuwait;

41. The Center for the Study of Haematological Malignancies, Nicosia, Cyprus;

42. Karaiskakio Foundation, Nicosia, Cyprus;

43. Laboratorio de Citogenètica Molecular, Laboratori de Citologia Hematològica, Servei de Patologia i Servei de Hematologia, Hospital del Mar, Barcelona, Spain;

44. Clinic for Hematology, Clinical Center of Serbia, Belgrade, Serbia;

45. Hammersmith Hospital, London, United Kingdom;

46. Hematocrit (HCT) Unit, Hematology Department, G. Papanicolaou Hospital, Thessaloniki, Greece;

47. Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain;

48. University Hospital Cologne, Cologne, Germany;

49. Department I of Internal Medicine, University of Cologne, Cologne, Germany;

50. Department of Immunology, Mayo Clinic, Scottsdale, AZ;

51. Hematology Department, Nikea General Hospital, Pireaus, Greece; and

52. Clinical Genetics, Karolinska University Laboratory, Karolinska University Hospital, Stockholm, Sweden

Abstract

Abstract Chronic lymphocytic leukemia (CLL) is characterized by the existence of subsets of patients with (quasi)identical, stereotyped B-cell receptor (BcR) immunoglobulins. Patients in certain major stereotyped subsets often display remarkably consistent clinicobiological profiles, suggesting that the study of BcR immunoglobulin stereotypy in CLL has important implications for understanding disease pathophysiology and refining clinical decision-making. Nevertheless, several issues remain open, especially pertaining to the actual frequency of BcR immunoglobulin stereotypy and major subsets, as well as the existence of higher-order connections between individual subsets. To address these issues, we investigated clonotypic IGHV-IGHD-IGHJ gene rearrangements in a series of 29 856 patients with CLL, by far the largest series worldwide. We report that the stereotyped fraction of CLL peaks at 41% of the entire cohort and that all 19 previously identified major subsets retained their relative size and ranking, while 10 new ones emerged; overall, major stereotyped subsets had a cumulative frequency of 13.5%. Higher-level relationships were evident between subsets, particularly for major stereotyped subsets with unmutated IGHV genes (U-CLL), for which close relations with other subsets, termed “satellites,” were identified. Satellite subsets accounted for 3% of the entire cohort. These results confirm our previous notion that major subsets can be robustly identified and are consistent in relative size, hence representing distinct disease variants amenable to compartmentalized research with the potential of overcoming the pronounced heterogeneity of CLL. Furthermore, the existence of satellite subsets reveals a novel aspect of repertoire restriction with implications for refined molecular classification of CLL.

Publisher

American Society of Hematology

Subject

Cell Biology,Hematology,Immunology,Biochemistry

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