Waldenström's macroglobulinemia (WM) is a B-cell lymphoproliferative disorder characterized by bone marrow (BM) infiltration by small lymphoplasmacytic lymphoma (LPL) cells that secrete monoclonal IgM immunoglobulin. Even though our understanding of the pathobiology of WM has grown significantly over the last few years through the application of technological advances, there is limited data on the significant heterogeneity that is observed in the depth of response to ibrutinib and in clinical responses that allude to mechanisms beyond mere tumor debulking. Studies have shown that patients with MYD88L265P/CXCR4WT achieve deeper and faster responses compared to patients with MYD88L265P/CXCR4MUT and even more to patients with MYD88WT/CXCR4WT. Furthermore, there is a significant heterogeneity in the type of response to BTK inhibitors with some patients responding rapidly while others at a slower pace, indicating involvement of mechanisms beyond tumor debulking.
The aim of this study was to identify and characterize the mechanisms of resistance to BTK therapy, and specifically to ibrutinib, in previously untreated patients with WM by integrating single cell RNA seq (scRNAseq) and whole genome sequencing (WGS) profiling approaches. We used a well-characterized WM patients' cohort, to define the role, contribution and prevalence of gene expressions/ mutations in the promotion of resistance.
We have performed droplet-based scRNAseq analysis on bone marrow mononuclear cells (BMNCs) from 49 fresh bone marrow aspirates of 23 WM patients; 20 patient samples from pre and 6 moths post ibrutinib therapy (n=40 samples total) and 3 patient samples from pre, 6 month and 12 months post ibrutinib therapy (n=9 samples total). The responder group (RG) consisted of 16 patients while the non-responder group (NRG) consisted of 7 patients. Within our cohort of NRG patients, 4 patients had a MYD88WTand 2 patients had a CXCR4MUT genotype. One patient from the NRG was wild type to CXCR4 at the diagnosis stage but a frameshift deletion occurred after therapy. B Cell Receptor sequencing was also performed, allowing us to better investigate the clonality of the B cell population. Finally, we performed WGS in 7 patients pre and post therapy (14 samples total) which included 3 NRG and 4 RG patients.
ScRNAseq analysis show that the B cell population is significantly higher in the NRG before therapy compared to the RG (11202 (25%) vs 7496 B cells (16%), respectively; median 2030 vs 240 B cells per patient, respectively) while CD14 population is more prominent in the RG compared to the NRG (9958 (31%) vs 1929 (6%) CD14 cells, respectively; median 239 vs 101 CD14 cells per patient, respectively). Clonality assessment showed that the majority of the B cells pre- and post- treatment were clonal. Responders tend to have a higher percentage of normal B-cells before and after treatment compared to NRG. Notably, after 6 months of ibrutinib treatment, there was only a slight decrease of malignant B cells in the RG patients, whereas malignant cells seem to increase in the NRG after treatment. Heatmap analysis of the 25 top differentially expressed genes (DEG) in B cells between RG and NRG, identified genes such as CHST15, EIF4E3, GSDME, IL17RB upregulated in responders and genes such as EGR1, S100A4, S100A6 upregulated in non-responders. From the WGS analysis, the top mutated genes seen in both groups included CXCR4 (29%), FLG2 (29%), MUC5AC (29%), RBMXL3 (29%) and MAP3K14 (21%). Of the genes most relevant to the WM, CD79B, TBL1XR1, SEMA3C and TP53 were only mutated in one patient (14%) within the RG. Comparing the top mutated genes exclusive to each group, genes mutated in the NRG include FAM186A, CDH20, CNTN1, SOX6 and TRAF3 while genes mutated in the RG included FAT3, SEMA3C and CD79B. Furthermore, CNV profiling between the RG and NRG showed the presence of chromosome 12 amplification only among the non-responder group which has previously been associated with poor PFS.
In conclusion, our results show a distinct transcriptomic and genomic profiles between WM patients with different responses to ibrutinib therapy, highlighting potential mechanism of resistance that could serve for the identification of predictive biomarkers for BTK-based therapy in WM.
Fotiou:Sanofi: Honoraria; Janssen: Honoraria. Gavriatopoulou:Genesis Pharma: Honoraria; Amgen: Consultancy; Takeda: Consultancy, Honoraria; Swixx: Honoraria; Beigene: Research Funding; AbbVie: Honoraria; Janssen Cilag: Honoraria; Karyopharm: Consultancy; BMS: Research Funding; Cellectar Biosciences: Research Funding; Integris: Honoraria; GSK: Consultancy, Honoraria. Terpos:EUSA Pharma: Honoraria, Other: Travel expenses; GSK: Honoraria, Research Funding; AstraZeneca: Honoraria, Other: Travel expenses; Amgen: Honoraria, Other: Travel expenses, Research Funding; BMS: Honoraria; Janssen: Honoraria, Research Funding; Menarini/Stemline: Honoraria; Pfizer: Honoraria; Sanofi: Honoraria, Other: Travel expenses, Research Funding; Takeda: Honoraria, Other: Travel expenses, Research Funding; Novartis: Honoraria; Antengene: Honoraria, Research Funding; Swixx: Honoraria. Kastritis:Janssen-Cilag: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding; GSK: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Sanofi: Honoraria. Dimopoulos:BMS: Honoraria; BEIGENE: Honoraria; JANSSEN: Honoraria; REGENERON: Honoraria; SANOFI: Honoraria; ASTRA ZENECA: Honoraria; MENARINI: Honoraria; TAKEDA: Honoraria; GSK: Honoraria; SWIXX: Honoraria; AMGEN: Honoraria, Membership on an entity's Board of Directors or advisory committees.
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