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Immunoglobulin Gene Analysis in Chronic Lymphocytic Leukemia

  • Andreas Agathangelidis
  • Richard Rosenquist
  • Frederic Davi
  • Paolo Ghia
  • Chrysoula Belessi
  • Anastasia Hadzidimitriou
  • Kostas Stamatopoulos
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1881)

Abstract

The formation of B-cell receptor immunoglobulin (BcR IG) is the result of a multi-step process that starts at the pro-B cell stage with the VDJ gene recombination of IG genes of the heavy chain, followed by VJ recombination of the light chain genes at the pre-B II cell stage. As a result, a fully functional BcR IG is expressed on the surface of any given naive B cell. After antigen encounter, somatic hypermutation (SHM) and class-switch recombination (CSR) act on the rearranged IG genes within the context of affinity maturation, leading to the expression of a BcR IG with unique immunogenetic and functional characteristics. Since B-cell neoplasms arise from the transformation of a single B cell, this renders IG gene rearrangements ideal clonal markers as they will be identical in all neoplastic cells of each individual clone. Furthermore, the rearranged IG sequence can also serve as a cell development/maturation marker, given that its configuration is tightly linked to specific B-cell developmental stages. Finally, in certain instances, as in the case of chronic lymphocytic leukemia (CLL), the clonotypic IG sequence and, more specifically, the load of somatic hypermutations within the rearranged IG heavy variable (IGHV) gene, holds prognostic and potentially predictive value. However, in order to take full advantage of the information provided from the analysis of the clonotypic IG gene rearrangement sequences, robust methods and tools need to be applied. Here, we provide details regarding the methodologies necessary to ensure reliable IG sequence analysis based on the recognized expertise of the European Research initiative on CLL (ERIC). All methodological and analytical steps are described below, starting from the isolation of blood mononuclear cells (PBMC), moving to the identification of the clonotypic IG rearrangement and ending with the accurate interpretation of the SHM status.

Key words

Immunoglobulin gene CDR3 Somatic hypermutation Stereotypy 

Notes

Financial Support

Supported in part by H2020 “AEGLE, An analytics framework for integrated and personalized healthcare services in Europe,” by the EU; “MEDGENET, Medical Genomics and Epigenomics Network” (No.692298) by the EU; “TRANSCAN-179” NOVEL JTC 2016; “ESPA for young researchers 2017, Somatic hypermutation in Chronic Lymphocytic Leukemia: ontogenetic and clinical implications from the analysis of NGS immunogenetic data” (No. 5006864).

References

  1. 1.
    Swerdlow SH, Campo E, Harris NL, Jaffe ES, Pileri SA, Stein H et al (2017) WHO classification of tumors of haematopoietic and lymphoid tissues. IARC PublicationsGoogle Scholar
  2. 2.
    Baliakas P, Mattsson M, Stamatopoulos K, Rosenquist R (2016) Prognostic indices in chronic lymphocytic leukaemia: where do we stand how do we proceed? J Intern Med 279(4):347–357CrossRefGoogle Scholar
  3. 3.
    Sutton LA, Rosenquist R (2015) The complex interplay between cell-intrinsic and cell-extrinsic factors driving the evolution of chronic lymphocytic leukemia. Semin Cancer Biol 34:22–35CrossRefGoogle Scholar
  4. 4.
    Mina A, Sandoval Sus J, Sleiman E, Pinilla-Ibarz J, Awan FT, Kharfan-Dabaja MA (2017) Using prognostic models in CLL to personalize approach to clinical care: are we there yet? Blood RevGoogle Scholar
  5. 5.
    Sutton LA, Hadzidimitriou A, Baliakas P, Agathangelidis A, Langerak AW, Stilgenbauer S et al (2017) Immunoglobulin genes in chronic lymphocytic leukemia: key to understanding the disease and improving risk stratification. Haematologica 102(6):968–971CrossRefGoogle Scholar
  6. 6.
    Damle RN, Wasil T, Fais F, Ghiotto F, Valetto A, Allen SL et al (1999) Ig V gene mutation status and CD38 expression as novel prognostic indicators in chronic lymphocytic leukemia. Blood 94(6):1840–1847PubMedGoogle Scholar
  7. 7.
    Hamblin TJ, Davis Z, Gardiner A, Oscier DG, Stevenson FK (1999) Unmutated Ig V(H) genes are associated with a more aggressive form of chronic lymphocytic leukemia. Blood 94(6):1848–1854PubMedGoogle Scholar
  8. 8.
    Burger JA, Chiorazzi N (2013) B cell receptor signaling in chronic lymphocytic leukemia. Trends Immunol 34(12):592–601CrossRefGoogle Scholar
  9. 9.
    Agathangelidis A, Darzentas N, Hadzidimitriou A, Brochet X, Murray F, Yan XJ et al (2012) Stereotyped B-cell receptors in one-third of chronic lymphocytic leukemia: a molecular classification with implications for targeted therapies. Blood 119(19):4467–4475CrossRefGoogle Scholar
  10. 10.
    Stamatopoulos K, Belessi C, Moreno C, Boudjograh M, Guida G, Smilevska T et al (2007) Over 20% of patients with chronic lymphocytic leukemia carry stereotyped receptors: pathogenetic implications and clinical correlations. Blood 109(1):259–270CrossRefGoogle Scholar
  11. 11.
    Gounari M, Ntoufa S, Apollonio B, Papakonstantinou N, Ponzoni M, Chu CC et al (2015) Excessive antigen reactivity may underlie the clinical aggressiveness of chronic lymphocytic leukemia stereotyped subset #8. Blood 125(23):3580–3587CrossRefGoogle Scholar
  12. 12.
    Navrkalova V, Young E, Baliakas P, Radova L, Sutton LA, Plevova K et al (2016) ATM mutations in major stereotyped subsets of chronic lymphocytic leukemia: enrichment in subset #2 is associated with markedly short telomeres. Haematologica 101(9):e369–e373CrossRefGoogle Scholar
  13. 13.
    Rossi D, Spina V, Bomben R, Rasi S, Dal-Bo M, Bruscaggin A et al (2013) Association between molecular lesions and specific B-cell receptor subsets in chronic lymphocytic leukemia. Blood 121(24):4902–4905CrossRefGoogle Scholar
  14. 14.
    Sutton LA, Young E, Baliakas P, Hadzidimitriou A, Moysiadis T, Plevova K et al (2016) Different spectra of recurrent gene mutations in subsets of chronic lymphocytic leukemia harboring stereotyped B-cell receptors. Haematologica 101(8):959–967CrossRefGoogle Scholar
  15. 15.
    Baliakas P, Hadzidimitriou A, Sutton L, Minga E, Agathagelidis A, Nichelatti M et al (2014) Clinical effect of stereotyped B-cell receptor immunoglobulins in chronic lymphocytic leukaemia: a retrospective multicentre study. Lancet Haematol 1(2):74–84CrossRefGoogle Scholar
  16. 16.
    Fischer K, Bahlo J, Fink AM, Goede V, Herling CD, Cramer P et al (2016) Long-term remissions after FCR chemoimmunotherapy in previously untreated patients with CLL: updated results of the CLL8 trial. Blood 127(2):208–215CrossRefGoogle Scholar
  17. 17.
    Rossi D, Terzi-di-Bergamo L, De Paoli L, Cerri M, Ghilardi G, Chiarenza A et al (2015) Molecular prediction of durable remission after first-line fludarabine-cyclophosphamide-rituximab in chronic lymphocytic leukemia. Blood 126(16):1921–1924CrossRefGoogle Scholar
  18. 18.
    Bystry V, Agathangelidis A, Bikos V, Sutton LA, Baliakas P, Hadzidimitriou A et al (2015) ARResT/AssignSubsets: a novel application for robust subclassification of chronic lymphocytic leukemia based on B cell receptor IG stereotypy. Bioinformatics 31(23):3844–3846PubMedGoogle Scholar
  19. 19.
    Rosenquist R, Ghia P, Hadzidimitriou A, Sutton LA, Agathangelidis A, Baliakas P et al (2017) Immunoglobulin gene sequence analysis in chronic lymphocytic leukemia: updated ERIC recommendations. Leukemia 31(7):1477–1481CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Andreas Agathangelidis
    • 1
  • Richard Rosenquist
    • 2
  • Frederic Davi
    • 3
  • Paolo Ghia
    • 4
  • Chrysoula Belessi
    • 5
  • Anastasia Hadzidimitriou
    • 1
  • Kostas Stamatopoulos
    • 1
    • 2
    • 6
  1. 1.Institute of Applied Biosciences, Center for Research and TechnologyThessalonikiGreece
  2. 2.Department of Molecular Medicine and SurgeryKarolinska InstituteStockholmSweden
  3. 3.Hôpital Pitié-SalpêtrièreUniversité Pierre et Marie CurieParisFrance
  4. 4.IRCCS Istituto Scientifico San RaffaeleUniversità Vita-Salute San RaffaeleMilanItaly
  5. 5.Nikea G. HospitalAthensGreece
  6. 6.Department of Immunology, Genetics and PathologyUppsala UniversityUppsalaSweden

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