Introduction:MYD88 (Myeloid Differentiation Primary Response 88) mutations are the most common genetic aberration in Waldenström's macroglobulinemia/lymphoplasmacytic lymphoma (LPL). Since the initial description of MYD88 mutations in LPL, the detection has gained great importance in diagnosing the disease. However, in some patients with other B cell malignancies, including chronic lymphocytic leukemia (CLL), MYD88 mutations are detectable.

Aim: We describe the molecular and cytogenetic profile of MYD88 mutated LPL in comparison to CLL, in order to identify aberration patterns potentially useful for diagnostic purposes.

Patients and Methods: We analyzed bone marrow samples of 78 LPL patients for MYD88 by highly sensitive allele specific PCR (ASP) for the L265P mutation and by next-generation sequencing (NGS) for MYD88 and CXCR4 (Chemokine (C-X-C Motif) Receptor 4) mutations. For CLL, 784 blood or bone marrow samples were sequenced for MYD88 (by NGS), IGHV, TP53, NOTCH1 and SF3B1 by Sanger or NGS as well as the MYD88 mutated CLL cases for CXCR4. For all samples, cytogenetic and multiparameter flow cytometry data was available.

Results: In LPL, 68/78 patients (87%) harbored a MYD88 mutation. In 13 cases with low bone marrow infiltration (median: 3%; range: 1-6%), the MYD88 mutation was detected by ASP only and not by NGS. However, one case was identified by NGS only because of a non-L265P mutation, which cannot be detected by ASP (1/68; 1%). In contrast, in CLL only 17/784 (2%) carried a MYD88 mutation. Interestingly, 5/17 (29%) were non-L265P mutations.

Of the MYD88 mutated LPL, 17/68 (25%) carried a genetic lesion in the C-terminal domain of CXCR4. In contrast to MYD88, the mutation spectrum of CXCR4 was much broader including non-sense mutations at amino acid S338 (10/18) but also frame shifts resulting in loss of regulatory serine residues. One patient had two independent CXCR4 mutations (S338* and S341Pfs*25). The mean bone marrow infiltration by flow cytometry was 14% and 9% in the CXCR4 mutated and unmuted subsets, respectively (p=0.17). Besides molecular genetic aberrations, 25% (17/68) of MYD88 mutated LPL cases carried cytogenetic aberration. The most frequent cytogenetic aberration in the MYD88 positive LPL was the deletion of 6q (10/68; 15%). Other recurrent cytogenetic abnormalities were gains of 4q (n=3), 8q (n=2), and 12q (n=4), as well as loss of 11q (n=4), 13q (n=2) and 17p (n=3). In the MYD88 unmutated group, we did neither identify any CXCR4 mutation nor any del(6q), suggesting different genetic driver events in this LPL subcohort.

Importantly, in the MYD88 positive CLL cohort, cytogenetic analysis did not reveal any patient with del(6q). Instead, del(13q)(q14) was the most prevalent cytogenetic aberration (12/17; 71%). Neither 11q deletions nor 17p deletions were detected. All MYD88 positive CLL had a mutated IGHV status (MYD88 unmutated CLL: 453/767; 59%; P<0.001). The TP53, NOTCH1 and SF3B1 mutational landscape did not reveal any differences between the MYD88 mutated and unmutated cohort. Finally, CXCR4 mutations were present in none of 15 analyzed MYD88 mutated CLL cases.

Conclusion: Besides multiparameter flow cytometry, MYD88 mutations are the most powerful tool in the diagnosis of LPL. MYD88 mutated LPL are characterized by a high frequency of CXCR4 mutations and del(6q), while MYD88 unmutated LPLs are associated with a different pattern of genetic abnormalities. MYD88 mutated CLL is a distinct CLL subset associated with mutated IGHV status, a high frequency of 13q deletions and low frequencies of 11q and 17p deletions. MYD88 mutated CLL differs from MYD88 mutated LPL with respect to the pattern of MYD88 mutations, cytogenetic aberrations and the absence of CXCR4 mutations. Highly sensitive ASP allows the L265P mutation detection even in LPL cases with very low bone marrow infiltration; whereas highly sensitive NGS assay are best applicable for detection of more heterogenic MYD88 mutations in CLL or CXCR mutations in LPL. Thus, an integrated molecular and cytogenetic approach allows the characterization of disease specific genetic patterns and should be analyzed for its clinical impact.

Disclosures

Baer:MLL Munich Leukemia Laboratory: Employment. Dicker:MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

Author notes

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Asterisk with author names denotes non-ASH members.

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