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Background. Recently, the somatic MYD88L265P mutation has been found as the hallmark of Waldenström Macroglobulinemia (WM), being detectable in nearly 90% of cases, as well as in up to 50% of IgM MGUS, rarely in other non-Hodgkin lymphomas and never in multiple myeloma (MM). Beyond its potential diagnostic role, this mutation has been associated with tumor growth and therapy resistance. Moreover, MYD88L265P might represent an ideal marker for minimal residual disease (MRD) monitoring in a disease whose therapeutic scenario has been rapidly changing, with many new available and highly effective drugs (nucleoside analogues, proteasome and BTK-inhibitors). However, the current MYD88L265P allele-specific quantitative PCR (ASqPCR) diagnostic tool lacks sensitivity (1.00E-03) and thus is not suitable for MRD. Moreover, is not useful to test peripheral blood (PB), that harbors low concentrations of circulating tumor cells (especially after immunochemotherapy), neither to assess cell-free DNA (cfDNA), usually present at very low amount in plasma. Therefore, our study aims: 1) to assess whether a highly sensitive tool as droplet digital PCR (ddPCR) might be helpful in MYD88L265P screening; 2) to evaluate whether MYD88L265P might be a suitable marker for MRD monitoring in WM. Methods. Bone marrow (BM) and PB samples were collected at diagnosis and during follow-up from a local series of patients affected by WM, IgM MGUS and IgG-secreting lymphoplasmacytic lymphoma (LPL), as well as samples from healthy subjects and MM were used as negative controls. Genomic (gDNA) and cell-free DNA (cfDNA) were extracted as recommended (Qiagen). MYD88L265P was assessed on 100 ng of gDNA by ASqPCR as previously described [Xu 2013] and by ddPCR, using a custom dual labelled probe assay (Bio-Rad). When available, 50 ng of cfDNA were tested for MYD88L265P, only by ddPCR. ddPCR was performed on 20 µl of reaction at 55°C for 40 cycles, run on QX100 droplet reader and analyzed by QuantaSoft v1.6.6 (Bio-Rad). MYD88L265P ASqPCR level was estimated as described [Treon 2012]. ΔCT Results. Once the ddPCR assay was optimized, the sensitivity of MYD88L265P ddPCR was compared to ASqPCR on a ten-fold serial dilution standard curves built with a 70% MYD88L265P mutated WM sample, previously identified by Sanger sequencing [Treon 2012]. Whereas ASqPCR confirmed the reported sensitivity of 1.00E−03, ddPCR reached a sensitivity of 5.00E−05. Thereafter, overall 105 samples (48 BM, 57 PB, 52 diagnosis and 53 follow up) from 58 patients (49 WM, 5 IgM MGUS and 4 LPL) as well as 20 controls (15 healthy subjects and 5 MM) were tested by both methods. 32/33 (97%) diagnostic BM scored positive for MYD88L265P by both ddPCR and ASqPCR (being the only one negative a WM), while ddPCR, was able to detect more mutated cases, than ASqPCR, among diagnostic PB samples: 15/19 (79%) vs 9/19 (47%) (Table1). Moreover, to investigate whether the MYD88L265P ddPCR tool could be used for MRD detection we compared it to the standardized IGH-based MRD. An IGH-based MRD marker was found in 40/53 (75%) patients (37 WM and 3 LPL). Five Patients, so far analyzed, with baseline and follow up samples (18 BM, 5 PB) showed highly superimposable results between the two methods. Finally, pivotal results on cfDNA from 10 patients showed higher median levels of MYD88L265P mutation in plasma if compared to PB. Conclusions. We developed a new tool for diagnosis and MRD monitoring in WM, showing that: 1) ddPCR is a highly sensitive tool for MYD88L265P detection, especially useful in low infiltrated samples, like PB; 2) MYD88L265P can be effectively and easily used for MRD monitoring in WM, achieving similar results to standardized IGH-based MRD; 3) cfDNA recovered from plasma might be an attractive alternative for MYD88L265P detection, deserving further investigation. Methodological validation against IgH-based MRD detection and Flow cytometry and correlations with clinical impact are currently ongoing on external samples series. Table 1.PATIENTSWM (45)LPL (2)IgM MGUS (5)TISSUEBMPBBMPBBMPBSAMPLES31141114MYD88L265P ddPCR/ASqPCR30/3011/71/10/01/14/2 TABLE 1. MYD88L265P mutation detection in diagnostic samples: ddPCR vs ASqPCR Disclosures Boccadoro: Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Onyx Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen-Cilag: Consultancy, Membership on an entity's Board of Directors or advisory committees.

BACKGROUND: In the recent years, numerous studies based on multicolor flowcytometry have analyzed the different subpopulations of bone marrow (BM) hematopoietic stem and progenitor cells (HSPCs) (Manz MG et al, PNAS 2002; Majeti R et al, Cell Stem Cell 2007): the common myeloid progenitors (CMPs: Lin-CD34+CD38+CD45RA-CD123+), the granulocyte-macrophage progenitors (GMPs: Lin-CD34+CD38+CD45RA+CD123+) and the megakaryocyte-erythroid progenitors (MEPs: Lin-CD34+CD38+CD45RA-CD123-) constitute the progenitor compartment, while the hematopoietic stem cells (HSCs: Lin-CD34+CD38- CD45RA-CD90+), the multipotent progenitors (MPPs: Lin-CD34+CD38- CD45RA-CD90-) and the lymphoid-myeloid multipotent progenitors (LMPPs: Lin-CD34+CD38- CD45RA+CD90-) represent the more immature HSPCs. In animal models, the progenitor compartment includes short-term repopulating cells, leading to the hematological recovery in the first 5 weeks after transplantation, whereas the stem cell compartment comprehends the long-term repopulation cells, responsible for the long-term hematological recovery. However, very little is known about the different subpopulations of HSPCs among peripheral blood (PB) CD34+ in basal state and after mobilization for harvest and transplantation. Our study was conducted to analyze PB CD34+ cells from healthy volunteers and from hematological patients during CD34+ cells mobilization. Our main aim was to understand if the proportions of different HSPCs among PB CD34+ cells were similar to those found in BM and whether the mobilizing regimens employed in chemo treated patients differently affected CD34+ cells subfractions in PB. METHODS: multicolor flowcytometry was used to analyze CD34+ cells from 4 BM samples and 9 PB samples from healthy volunteers and 32 PB samples from hematological patients prior CD34+ cells harvesting. RESULTS: Percentages of CD34+ cells subpopulations were different in basal PB compared to the BM: indeed, CMPs, GMPs and MEPs constituted respectively 27.6% ± 9.5, 23.8% ± 7.2 and 27.6% ± 16.2 of BM CD34+ cells and 47.8% ± 9.5, 10.3% ± 6.9 and 16.1% ± 7.6 of the total PB CD34+ cells. HSCs constituted 2.1% of BM and 1.5% of PB CD34+ cells. The differences between BM and circulating CMPs and GMPs were significant (p No differences in subpopulations proportions were shown comparing G-CSF mobilized and basal PB CD34+ cells. Interestingly, the 2 patients mobilized with AMD3100 (the inhibitory molecule for CXCR4) showed a higher percentage of GMPs (33.8% and 37.8% versus the average 16.3% ± 9.8 in G-CSF mobilized samples) and a lower fraction of CMPs (29.5% and 41.6% versus the average 58% ± 12 in G-CSF mobilized samples). In order to understand this result, we looked then at the CXCR4 mean fluorescence intensity among the progenitor subsets: GMPs showed significantly higher levels of this molecule compared to CMPs and MEPs. Regarding the mobilizing chemotherapy regimens, CMPs percentages were higher (61.1% versus 49.1%, p: 0.038) and GMPs’ were significantly lower (11.1% versus 27.6%, p A linear positive correlation between the number of mobilized CD34+ cells and the number of mobilized CMPs, GMPs, and MEPs was observed indicating that the proportions of different HSPCs did not significantly change among high- and low-mobilizers. There were no correlations between the number of mobilized subpopulations and leucocytes, hemoglobin and platelets levels. CONCLUSIONS: Our data displayed the heterogeneity of HSPC compartment between PB and BM. Many factors could contribute to this variegated scenario. These mechanisms comprehension can help us to choose the most suitable chemotherapy and cytokine administrations in order to improve clinical outcomes as infections complications, length of aplasia and transfusion requirements during an hematopoietic stem cell transplantation. Disclosures Palumbo: Bristol-Myers Squibb: Consultancy, Honoraria; Genmab A/S: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen-Cilag: Consultancy, Honoraria; Millennium Pharmaceuticals, Inc.: Consultancy, Honoraria; Onyx Pharmaceuticals: Consultancy, Honoraria; Array BioPharma: Honoraria; Amgen: Consultancy, Honoraria; Sanofi: Honoraria. Boccadoro:Celgene: Honoraria; Janssen: Honoraria; Onyx: Honoraria.