#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Analysis of the relationship of cytogenetic results with serum free light chain ratio κ/λ(FLC-r, FreeliteTM), heavy/light chain pairs of immunoglobulin ratio (HLC-r, HevyliteTM), and selected prognostic factors assessed at diagnosis of multiple myeloma


Authors: V. Ščudla 1,2;  J. Balcárková 2;  P. Lochman 3;  M. Mlynárčiková 2;  T. Pika 2;  J. Minařík 2;  J. Zapletalová 4;  M. Jarošová 2
Authors‘ workplace: 3. interní klinika-nefrologická, revmatologická a endokrinologická, Lékařská fakulta Univerzity Palackého a Fakultní nemocnice v Olomouci 1;  Hemato-onkologická klinika, Fakultní nemocnice a Lékařská fakulta Univerzity Palackého v Olomouci 2;  Oddělení klinické biochemie, Fakultní nemocnice v Olomouci 3;  Ústav lékařské biofyziky, Lékařská fakulta Univerzity Palackého v Olomouci 4
Published in: Transfuze Hematol. dnes,22, 2016, No. 2, p. 77-89.
Category: Comprehensive Reports, Original Papers, Case Reports

Overview

Introduction:
Assessment of serum levels of free light chains κ/λ(FLC-κ/λ) and recently of heavy/light chain immunoglobulin pairs (HLC) has extended the traditional algorithm of laboratory tests in multiple myeloma (MM). The aim of the study was to evaluate the relationship between standard prognostic MM factors, FLC-κ/λ ratio (sFLC-r), modified „involved/uninvolved“ FLC ratio (mFLC-r), the difference „involved – uninvolved“ FLC (FLC-dif), standard HLC-κ/λratio (sHLC-r), modified „involved/uninvolved” HLC ratio (mHLC-r), and the difference „involved-uninvolved“ HLC (HLC-dif) with the results of cytogenetic analysis at the time of MM diagnosis.

Patients and methods:
In a group of 97 patients with MM, we assessed serum levels of FLC using the FreeliteTM method and calculated the following indices: sFLC-r, mFLC-r and FLC- dif. Using the HevyliteTM method, we assessed serum levels of HLC pairs and calculated the following indices: sHLC-r, mHLC-r and HLC-dif. For cytogenetic analysis of myeloma plasmocytes, we used fluorescent in situ hybridization with immunofluorescent staining of plasma cells (FICTION, “Fluorescence Immunophenotyping and Interphase Cytogenetics as a Tool for the Investigation of Neoplasms“).

Results:
We confirmed a significant relationship between complex karyotype, del(13)(q14) and chromosome 1q21 gain with a decrease of Hb < 100 g/l; del(13)(q14) with thrombocytopenia < 150 x 109/l and increased creatinine levels; and in the case of t(14;16)(q32;q23) also a relationship with ß2-microglobulin (ß2-M) > 5.5 mg/l; deletion del(17)(p13) (TP53) with increased ß2-M and trisomy of chromosomes 15 and 17 with MIg > 25 g/L. sFLC-r index levels were significantly elevated only in the case of del(13q14). However, after focusing on the group with sFLC-r < 0.01 and > 100, we found a significant relationship with del(13)(q14), del(17)(p13) and complex karyotype. The presence of 1q21 gain, del (17)(p13), complex karyotype and trisomy 17 had significantly higher levels of mFLC-r and in patients with cut off ³ 79.6 we found del(13)(q14), chromosome 1q21 gain and complex karyotype. In the cohort with FLC-dif ³ 185 there was an association with del(13)(q14), del(17)(p13) and complex karyotype. The relationship between sHLC-r and other assessed cytogenetic markers was insignificant except for the relationship with t(4;14)(p16;q32). One original contribution is the discovery of significantly increased mHLC-r levels in the case of 1q21 gain, complex karyotype and trisomy of chromosome 17 as well as t(4;14)(p16;q32) translocation. This finding was confirmed by the corresponding results of HLC-dif analysis in the group with mHLC-r ³31.6. Significantly higher serum MIg concentration was found only in the case of chromosome 15 trisomy.

Conclusion:
The study confirmed a statistically significant relationship between „high-risk“ structural changes, i.e. t(14;16)(q32;q23), del(13)(q14), del(17)(p13), 1q21 gain and complex karyotype with standard prognostic factors characterized by their relationship with the extent and biological features of MM. Our contribution towards a deeper understanding of MM pathobiology is the uncovered significant relationship between mFLC-r and del(13)(q14), 1q21 gain and del(17)(p13), as well as our original discovery of the significant relationship between mHLC-r and also partly HLC-dif. with prognostically unfavourable aberrations t(4;14)(p16;q32), chromosome 1q21 gain and complex karyotype.

Key words:
multiple myeloma – prognostic factors – free light chains of immunoglobulin – heavy/light chain pairs of immunoglobulin – fluorescent in situ hybridization


Sources

1. Avet-Loiseau H, Facon T, Grosbois B, et al. Oncogenesis of multiple myeloma: 14q32 and 13q chromosomal abnormalities are not randomly distributed, but correlate with natural history, immunological features, and clinical presentation. Blood 2002; 99: 2185–2191.

2. Avet-Loiseau H, Attal M, Moreau M, et al. Genetic abnormalities and survival in multiple myeloma: the experience of the Intergroupe Francophone du Myélome. Blood 2007; 109: 3489–3495.

3. Kalff A, Spencer A. The t(4;14)(p16;q32) translocation and FGFR3 over expression in multiple myeloma: prognostic implications and current clinical strategies. Blood Cancer 2012; 2: 1–8.

4. Liebisch P, Döhner H. Cytogenetics and molecular cytogenetics in multiple myeloma. Eur J Cancer 2006; 42: 1520–1529.

5. Keats J, Reiman T, Maxwell Ch A, et al. In multiple myeloma, t(4;14(p16;q32) is an adverse prognostic factor irrespective of FGFR3 expression. Blood 2003; 101: 1520–1529.

6. Köningsberg R, Zojer N, Ackermann J, et al. Predictive role of interphase cytogenetics for survival of patients with multiple myeloma. J Clin Oncol 2000; 18: 804–812.

7. Kumar SK, Mikhael JR, Buadi F, et al. Management of newly diagnosed symptomatic multiple myeloma: updated Mayo stratification of myeloma and risk-adapted therapy (mSMART) consensus guidelines. Mayo Clin Proc 2009; 84: 1095–1110.

8. An G, Xu Y, Shi L, et al. Chromosome 1q21 gains confer inferior outcomes in multiple myeloma treated with bortezomib but copy number variation and percentage of plasma cells involved have no additional prognostic value. Haematologica 2014; 99: 353–359.

9. Fonseca R. International Myeloma Working Group molecular classification of multiple myeloma: spotlight review. Leukemia 2009; 23: 2210–2221.

10. Greenberg AJ, Rajkumar SV, Therneau TM, Singh PP, Dispenzieri A, Kumar SK. Relationship between initial clinical presentation and the molecular cytogenetic classification of myeloma. Leukemia 2014; 28: 398–403.

11. Kumar S, Fonseca R, Ketterling RP, et al. Trisomies in multiple myeloma: impact on survival in patients with high-risk cytogenetics. Blood 2012; 119: 2100–2105.

12. Dispenzieri A, Kyle RA, Merlini G, et al. International Myeloma Working Group guidelines for serum-free light chain analysis in multiple myeloma and related disorders. Leukemia 2009; 23: 215–224.

13. The Binding Site Group Ltd, editor. Serum free light chain analysis plus Hevylite. 7 th ed. Birmingham: The Binding Site Ltd, 2015.

14. Alexanian R. Blood volume in monoclonal gammopathy. Blood 1997; 49: 301–307.

15. Akilesh S, Christianson GJ, Roopenian DC, Shaw AS. Neonatal FcR expression in bone marrow-derived cell functions to protect serum IgG from catabolism. J Immunol 2007; 179: 4580–4588.

16. Bradwell AR, Harding SJ, Fourrier NJ, et al. Assessment of monoclonal gammopathies by nephelometric measurement of individual immunoglobulin k/l ratios. Clin Chemistry 2009; 55: 1646–1655.

17. Keren DF. Heavy/light-chain analysis of monoclonal gammopathies. Clin Chemistry 2009; 55: 1606–1608.

18. Katzmann JA, Kyle RA, Benson J, et al. Screening panels for detection of monoclonal gammopathies. Clin Chemistry 2009; 55: 1517–1522.

19. Ludwig H, Milosavljevic D, Zojer N, et al. Immunoglobulin heavy/light chain ratios improve paraprotein detection and monitoring, identify residual disease and correlate with survival in multiple myeloma patients. Leukemia 2013; 27: 213–219.

20. Bhutani M, Landgren O, Korde N. Serum heavy-light chains (HLC) and free-light chains (FLC) as predictors for early CR in newly diagnosed myeloma patients treated with carfilzomib, lenalidomide, and dexamethasone. 55TH ASH Annual Meeting, 2013;Abstr. No. 762.

21. Batinic J, Perič Z, Šegulja D, et al. Immunoglobulin heavy/light chain analysis enhances the detection of residual disease and monitoring of multiple myeloma patients. Croat Med J 2015; 56: 263–271.

22. Jekarl DW, Min ChK, Kwon A, et al. Impact of genetic abnormalities on the prognosis and clinical parameters of patients with multiple myeloma. Ann Lab Med 2013; 33: 248–254.

23. Hanamura I, Stewart JP, Huang Y, et al. Frequent gain of chromosome band 1q21 in plasma-cell dyscrasias detected by fluorescence in situ hybridization: incidence increases from MGUS to relapsed myeloma and is related to prognosis and disease progression following tandem stem-cell transplantation. Blood 2006; 108: 1724–1732.

24. Hájek R, Adam Z, Ščudla V, et al. Diagnostika a léčba mnohočetného myelomu. Doporučení vypracované Českou myelomovou skupinou, Myelomovou sekcí ČHS a Slovenskou myelómovou Společností pro diagnostiku a léčbu mnohočetného myelomu. Transfuze Hematol dnes 2012; 18(Supplementum): 1–92.

25. International Myeloma Working Group criteria for the classification of monoclonal gammopathies, multiple myeloma and related disorders: a report of the International Myeloma Working Group. Brit J Haematol 2003; 121: 749–757.

26. Balcárková J, Procházková K, Ščudla V, et al. Molekulárně cytogenetická analýza plazmatických buněk u pacientů s mnohočetným myelomem. Transfuze Hematol dnes 2007; 13: 176–182.

27. Kyrtsonis MCH, Theodoros P, Vassilakopoulos TP, et al. Prognostic value of serum free light chain ratio at diagnosis in multiple myeloma. Br J Haematol 2007; 137: 240–243.

28. Ščudla V, Lochman P, Pika T, et al. Relationship of differences in immunoglobulin heavy/light chain pairs (HevyliteTM), selected laboratory parameters and stratification systems in different immunochemical types of multiple myeloma. Biomed Pap Med Fac Univ Palacky Olomouc 2016;159:(in press). Doi:10.5507/bp.2015.032 (Epub ahead of print).

29. Larsen JT, Kumar SK, Dispenzieri A, Kyle RA, Katzmann JA, Rajkumar SV. Serum free light chain ratio as a biomarker for high-risk smoldering multiple myeloma. Leukemia 2013; 27: 941–946.

30. Rajkumar SV, Dimopoulos MA, Palumbo A, et al. International Myeloma Working Group updated criteria for the diagnosis of multiple myeloma. Lancet Oncol 2014; 15: 538–548.

31. Ščudla V, Zemanová M, Minařík J, et al. International prognostic index (IPI) – a critical comparison with five multiple myeloma staging systems in the group of 270 patients treated by conventional chemotherapy. Neoplasma 2006; 53: 277–284.

32. Ghobrial I.M, Langren O. How I treat smoldering multiple myeloma. Blood 2014; 124: 3380–3388.

33. Ludwig H, Milosavljevic D, Zojer N, et al. Supression of the non-involved HLC pair correlates with survival in newly diagnosed and relapsed/refractory patients with myeloma. Congress of European Haematology Association, Milano 2014; P-980.

34. Keats JJ, Chessi M, Egan JB, et al. Clonal competition with alternating dominance in multiple myeloma. Blood 2012; 120: 1067–1076.

35. Brioli A, Giles H, Pawlyn Ch, et al. Serum free immunoglobulin light chain evaluation as a marker of impact from intraclonal heterogeneity on myeloma outcome. Blood 2014; 123: 3414–3419.

36. Mikhael JR, Dingli D, Vivek R, et al. Management of newly diagnosed symptomatic multiple myeloma: updated Mayo stratification of myeloma and risk-adapted therapy (mSMART) consensus guidelines 2013. May Clin Proc 2013; 88: 360–374.

37. Palumbo A, Avet-Loiseau H, Oliva S, et al. Revised International Staging System for multiple myeloma: A report from International Myeloma Working Group. J Clin Oncol 2015; 33: 2863–2869.

38. Avet-Loiseau H. Role of genetics in prognostication in myeloma. Best Pract Res Clin Haematol 2007; 20: 625–635.

39. Shah JJ, Narang M, Abonour R, et al. Clinical outcomes in patients with newly diagnosed multiple myeloma and t(4;14)(p16;q32) in the connect MM registry. Clin Lymphoma Myeloma 2015; 15, Suppl 3: e137.

40. Gertz MA, Lacy MQ, Dispenzieri A, et al. Clinical implications of t(11;14)(q13;q32)(q13;q32), t(4;14)(p16;q32)(p16,3;q32), and -17p13 in myeloma patients treated with high-dose therapy. Blood 2005; 106: 2837–2840.

41. Avet-Loiseau H, Malard F, Campion L, et al. Translocation t(14;16)(q32;q23) and multiple myeloma: is it really an independent prognostic factor? Blood 2011; 117: 2009–2011.

42. Zojer N, Königsberg R, Ackermann J, et al. Deletion of 13q14 remains an independent adverse prognostic variable in multiple myeloma despite its frequent detection by interphase fluorescence. Blood 2000; 95: 1925–1930.

43. Facon T, Avet-Loiseau H, Guillerm G, et al. Chromosome 13 abnormalities identified by FISH analysis and serum beta2-microglobulin produce a powerful myeloma staging system for patients recveiving high-dose therapy. Blood 2001; 97:1566–1571.

44. Lodé L, Eveillard M, Trichet V, et al. Mutation in TP53 are exclusively associated with del(17p) in multiple myeloma. Haematologica 2010; 95: 1973–1976.

45. Kumar S, Zhang L, Dispenzieri A, et al. Relationship between elevated immunoglobulin free light chain and the presence of IgH translocations in multiple myeloma. Leukemia 2010; 24: 1498–1505.

46. Zhan F, Huang Y, Colla S, et al. The molecular classification of multiple myeloma. Blood 2006; 108: 2020–2028.

47. Shaughnessy JD Jr, Zhan F, Burington BE, et al. A validated gene expression model of high-risk multiple myeloma is defined by deregulated expression of genes mapping to chromosome 1. Blood 2007; 109: 2276-2284.

48. Wu KL, Beverloo B, Lokhorst HM, et al. Abnormalities of chromosome 1p/q are highly associated with chromosome 13/13q deletions and are an adverse prognostic factor for the outcome of high-dose chemotherapy in patients with multiple myeloma. Br J Haematol 2007; 136: 615–623.

49. Hebraud B, Leleu X, Lauwers-Cances V, et al. Deletion of the 1p32 region is a major independent prognostic factor in young patients with myeloma: the IFM experience on 1195 patients. Leukemia 2014; 28: 675–679.

50. Fonseca R, Van Wier SA, Chang WJ, et al. Prognostic value of chromosome +q21 gain by fluorescent in situ hybridization and increase CKS1B expression in myeloma. Leukemia 2006; 20: 2034–2040.

51. Fonseca R, Blood ER, Oken MM, et al. Myeloma and the t(11;14)(q13;q32)(q13;q32); evidence for a biologically defined unique subset of patients. Blood 2002; 99: 3735–3741.

52. Karlin L, Soulier J, Chandesris O, et al. Clinical and biological features of t(4;14)(p16;q32) multiple myeloma: a prospective study. Leu Lymphoma 2011; 52: 238–246.

53. Bradwell AR, Harding S, Fourrier N, et al. Prognostic utility of intact immunoglobulin Ig´kappa/Ig´lambda ratios in multiple myeloma patients. Leukemia 2013; 27: 202–207.

54. Moreau P, Facon T, Leleu X, et al. Recurrent 14q32 translocations determine the prognosis of multiple myeloma, especially in patients receiving intensive chemotherapy. Blood 2002; 100: 1579–1583.

55. Katzmann JA, Clark R, Kyle RA, et al. Supression of uninvolved immunoglobulins defined by heavy/light chain pair suppression is a risk factor for progression of MGUS. Leukemia 2013; 27: 208–212.

Labels
Haematology Internal medicine Clinical oncology

Article was published in

Transfusion and Haematology Today

Issue 2

2016 Issue 2

Most read in this issue
Login
Forgotten password

Enter the email address that you registered with. We will send you instructions on how to set a new password.

Login

Don‘t have an account?  Create new account

#ADS_BOTTOM_SCRIPTS#