Jevremović, Dragan

Abstract Measurable residual disease (MRD) assessment has become central to risk-adapted treatment strategies in multiple myeloma, yet the prognostic value of MRD negativity following autologous stem cell transplantation (ASCT) across individual high-risk cytogenetic abnormalities (HRCAs) remains unclear. We analyzed 351 newly diagnosed patients who achieved MRD negativity (sensitivity 2.4×10 − 6 ) at Day 100 following ASCT and had baseline cytogenetic data available. Median follow-up was 50.4 months. Standard-risk cytogenetics were present in 46% (n = 162), while 34% (n = 118) had one HRCA and 20% (n = 71) had ≥ 2 HRCAs. Despite uniform MRD negativity, several HRCAs continued to confer inferior progression-free survival (PFS). Compared with the standard-risk group (4-year PFS 84%), patients with del(17p), 1q21+, t(4;14), or MAF translocations [t(14;16)/t(14;20)] had significantly lower 4-year PFS rates: 56% (HR 2.89; p = 0.0001), 60% (HR 2.46; p = 0.0001), 43% (HR 3.50; p = 0.0001), and 58% (HR 2.51; p = 0.01), respectively. Isolated del(17p) and 1q21 + also conferred inferior PFS. The 4-year PFS was 65% for patients with one HRCA (HR 2.31; p = 0.0004) and 55% for those with ≥ 2 HRCAs (HR 2.75; p = 0.0001). In this large MRD-negative post-ASCT cohort, several HRCAs, including isolated HRCAs, remained clinically meaningful drivers of inferior PFS, highlighting that early MRD negativity does not uniformly mitigate the impact of high-risk biology.

ABSTRACT Background IDH mutations are found in 15%–20% of acute myeloid leukemia (AML). Recent evidence suggests that IDH mutation subtypes may respond differently to intensive chemotherapy. We evaluated blast clearance patterns, remission outcomes, and overall survival (OS) in AML patients with IDH2 R140, IDH2 R172, and IDH1 R132 mutations to assess differences in treatment response. Methods We retrospectively reviewed AML patients diagnosed at Mayo Clinic, Rochester (2016–2023) with NGS data and treated with intensive chemotherapy (7+3 or CPX‐351). Bone marrow blasts were assessed at diagnosis, mid‐induction, and end‐of‐cycle; blast clearance was defined as < 5%. Composite remission (CRc) included CR/CRi per ELN 2022. IDH2 responders were classified as early (after Cycle 1) or late (≥ 2 cycles). Blast reduction was calculated as log 10 (diagnosis blasts/end‐induction blasts) and normalized per day. OS was measured from diagnosis. Results Among 381 patients, 31 had IDH2 mutations (23 R140, 8 R172) and eight had IDH1 R132. Baseline blasts were similar. Mid‐cycle blasts were lower in R140 versus R172 (4% vs. 10%), with higher clearance (68% vs. 38%). End‐induction blasts were lower in R140 versus R172 (2% vs. 4%) with higher clearance (100% vs. 75%). IDH1 and IDH2 showed similar clearance patterns. Log 10 analyses showed deeper and faster blast reduction in R140 versus R172, with comparable kinetics between IDH1 and IDH2 . OS did not differ across subtypes. Early CRc in IDH2 ‐mutated patients was associated with numerically longer OS. Conclusion IDH2 R140 demonstrated faster blast clearance than R172, while remission and survival were similar across IDH subtypes. Trial Registration : The authors have confirmed clinical trial registration is not needed for this submission.

Abstract Introduction The European Leukemia Net (ELN) 2022 stratified acute myeloid leukemia (AML) patients (pts) treated with intensive chemotherapy (IC) into three groups based on genetic features. ELN 2024 (Döhner et al, Blood) and Beat AML 2024 (Hoff et al, Blood Advances) proposed revised systems to better capture the impact of genetic features in pts receiving less-intensive therapy (LIT). Real-world validation across treatment settings, including allogeneic hematopoietic stem cell transplantation (allo-HCT), is warranted. Methods We evaluated the performance of ELN 2022, ELN 2024, and Beat AML 2024 among AML pts treated at Mayo Clinic from 2016 to 2025. Only treated pts with available molecular data included. Response was assessed according to the ELN 2022 criteria. Overall survival (OS) was calculated from diagnosis. Multivariable Cox proportional hazard (CPH) models were used to adjust for covariates. Model performances were assessed using Harrell's c-index. Results 426 AML pts (median age 68 years; 60% male) were included; 195 (46%) received IC and 231 (54%) received LIT, while Allo-HCT was performed in 133 (31%) pts. Complex karyotype was present in 126 (30%) and normal cytogenetics in 143 (34%) pts. Molecular mutations included TP53 (20%), TET2 (18%), DNMT3A (16%), SRSF2 (16%), RUNX1 (16%), ASXL1 (16%), and NPM1 (15%). Among evaluable pts (83%), complete remission (CR) after first-line therapy was achieved in 47%. Risk group assignments varied: ELN 2022 vs. ELN 2024 classified pts as favorable (20% vs. 55%), intermediate (20% vs. 24%), and adverse (60% vs. 20%); Beat AML 2024 categorized pts as favorable (41%), intermediate (21%), and adverse (38%). ELN 2024 reclassified 229 (54%) pts of whom 5% upstaged and 49% downstaged, primarily affecting ELN 2022 adverse (67%) and intermediate (46%) groups. Among LIT-treated, CR rates did not differ across groups in any classification. Per ELN 2024, CR was achieved in 43% (favorable), 67% (intermediate), and 29% (adverse) of the LIT-treated pts. However, among IC-treated pts, CR was higher in favorable/intermediate vs. adverse groups across all models (p&lt;0.0001). Allo-HCT was most common in ELN 2024 intermediate (41%) and favorable (32%) vs. adverse (16%) groups. Median OS (months; 95% CI) for the entire cohort was 15.7 (12.5–20.9) with median follow-up time of 49.8 (40.9-55). By ELN 2022, OS of the entire cohort was 49.4 (30.7–NA) for favorable, 50.0 (29.2–NA) for intermediate, and 8.8 (7.7–11.2) for adverse (p&lt;0.0001). Per ELN 2024, OS of the entire cohort was 25.4 (18.5–37.3), 20.3 (13.4–39.8), and 5.7 (3.4–8.2), respectively (p&lt;0.0001). Beat AML 2024 stratified OS of the entire cohort as 42.5 (30.7–NA), 11.4 (9.3–16.7), and 5.6 (3.5–8.0) for favorable, intermediate, and adverse groups (p&lt;0.0001). ELN 2024 stratified the OS of the pts treated with LIT as 15.7 (10.1-24.9), 8.0 (4.9-13.9), and 6.8 (3.4-10.2) for favorable, intermediate and adverse risk groups, (p &lt;0.0001). Among ELN 2022 adverse-risk pts, those reclassified as favorable per ELN 2024 had superior OS (15.0, 9.8–22.7) compared to intermediate (7.8, 5.0–9.3) or adverse (5.4, 3.3–8.0) risk groups, p&lt;0.0001. C-index (95% CI) for OS in the entire cohort was highest for Beat AML 2024 (0.658, 0.629–0.688), followed by ELN 2022 (0.627, 0.599–0.655), and ELN 2024 (0.600, 0.568–0.631). In LIT-treated pts, ELN 2024 (0.597, 0.558–0.637) and Beat AML 2024 (0.586, 0.545–0.627) outperformed ELN 2022 (0.559, 0.521–0.596). Among allo-HCT pts, regardless of treatment type, ELN 2022 (0.610, 0.539–0.681) performed better than ELN 2024 (0.568, 0.487–0.648). In multivariable CPH models adjusted for age, bone marrow blasts, treatment intensity, and complex karyotype, ELN 2022 and ELN 2024 adverse-risk groups had higher hazard of death (HR 2.4, 1.6–3.5 and HR 1.7, 1.1–2.5, respectively, vs. favorable). No significant difference was observed between intermediate and favorable risk for ELN 2022 (HR 1.4, 0.9–2.2) or ELN 2024 (HR 1.4, 0.9–1.9). Allo-HCT was associated with a lower hazard of death (HR 0.4, 0.3–0.5). Conclusions In this real-world AML cohort, ELN 2024 and Beat AML 2024 improved OS prediction in LIT-treated pts compared to ELN 2022. This advantage was not observed in allo-HCT pts. Multivariable analysis confirmed the adverse-risk group as having the worst prognosis across all models. These findings highlight the importance of aligning molecular risk stratification with treatment modalities to enhance prognostication in AML.

Abstract Background Missense mutations in IDH1 are well-established therapeutic targets in acute myeloid leukemia (AML). In contrast, the synonymous IDH1 variant p.Gly105Gly (rs11554137), present in 5–10% of AML cases, has been considered a benign polymorphism due to its high population frequency (5.7% overall, 0.7–10.5%) and lack of protein-altering effect. However, prior studies have associated this variant with inferior outcomes (Wagner, J Clin Oncol, 2010), though findings have been inconsistent. Few studies have examined its prognostic significance in the context of treatment intensity or allogeneic stem cell transplantation (SCT). Methods With IRB approval, clinical and genomic data were extracted from the Mayo Clinic AML database for patients diagnosed between Jan 1, 2018, and Jan 31, 2025. Patients were stratified by IDH1 Gly105Gly (rs11554137) status via NGS on bone marrow. Outcomes included co-mutation profiles, treatment response, measurable residual disease (MRD) by multiparametric flow cytometry, and survival. Multivariable Cox and logistic regression models for relapse-free survival (RFS) and overall survival (OS) were adjusted for age at diagnosis, ELN 2022 risk category, and SCT conditioning regimen. Results Among 379 AML patients, 36 (9.5%) harbored the IDH1 Gly105Gly (rs11554137) variant (cases) (median VAF 49%, IQR 48–49.2). In the full cohort, median age was 68 years (IQR 59–74), M:F ratio was 1.5; 75% had de novo AML, and median follow-up was 52 months. Among cases, common cytogenetic abnormalities included complex karyotype (28%), del(7q) (14%), and trisomy 8 (6%), while frequently mutated genes included DNMT3A (19%), IDH2 (17%), and BCOR (14%). Of 345 treated patients, 43% received intensive, and 56% received low-intensity regimens, including hypomethylating agent (HMA) alone (n=13), HMA+venetoclax (n=159), and targeted therapy (n=7). Among cases, complete remission (CR) rates were higher with intensive vs. low-intensity therapy (70% vs. 17%, p=0.03). MRD positivity post induction was more common in cases (66% vs. 26%, p=0.01), suggesting suboptimal leukemic clearance. Among 103 patients who underwent allogeneic SCT in CR1 (47% received myeloablative conditioning), morphologic relapse occurred in 64.3% of cases compared to 23.6% of controls (p = 0.004). Cases experienced significantly inferior median RFS (8 months [95% CI 5–NA] vs. not reached for controls, p &lt;0.001), indicating more durable post-SCT remission in the control group. In a multivariable Cox proportional hazards model adjusting for age, ELN risk, conditioning intensity, MRD status, and complex karyotype, the IDH1 Gly105Gly variant remained independently associated with shorter RFS (HR 3.97, 95% CI: 1.74–9.05, p = 0.001). Complex karyotype was also an independent predictor of relapse (HR 3.35, 95% CI: 1.28–8.73, p = 0.014). Consistent with this, logistic regression revealed a significantly increased odds of post-SCT relapse among cases (OR 7.95, 95% CI: 2.19–35.27, p=0.001), independent of clinical covariates. Relapsed cases were significantly more likely to harbor FLT3-ITD mutations than relapsed controls (p=0.041). Pathway-level analysis revealed increased frequency of mutations in signal transduction genes (FLT3-ITD, CSF3R, NF1) (p=0.002). All CNS relapses among cases occurred in patients harboring at least one of these mutations. Despite the higher relapse rate, there were no significant differences in OS (14.4 vs. 11.3 months, p=0.36) between cases and controls. The IDH1 Gly105Gly variant was not independently associated with OS (HR 1.26, p=0.30). In contrast, age (p&lt;0.0001) and adverse ELN risk (p&lt;0.0001) were significant predictors of inferior OS. These findings suggest that the prognostic impact of IDH1 Gly105Gly is most pronounced in the post-SCT setting. Conclusion The synonymous IDH1 Gly105Gly variant (rs11554137) is an independent predictor of post-SCT relapse in AML, potentially mediated by co-occurring mutations in signal transduction pathways. Despite no observed impact on OS, likely due to effective salvage therapies, the variant's link to lower CR rates with low-intensity therapy and higher MRD burden suggests treatment intensity influences its clinical relevance. These findings support reevaluating the prognostic role of synonymous variants in AML and call for larger studies and mechanistic investigations into splicing, transcript stability, and translation.

Abstract Introduction In 2018, our institution implemented a MALDI-TOF mass spectrometry (MS) method (Mass-Fix) to detect myeloma associated M-proteins in blood. Currently, the lab has performed more than 500K tests by Mass-Fix. While Mass-Fix has been found to be more sensitive and specific than IFE, an ESI-Q-TOF (High Resolution Mass-Fix) method has demonstrated the potential to detect M-proteins at significantly lower levels. Blood minimal residual disease (MRD) detection in lieu of bone marrow (BM) is desirable since blood is easier and less expensive to obtain and analyze. This feature can allow for more frequent MRD monitoring for myeloma patients. Methods 66 residual blood samples from myeloma patients with varying M-protein varying isotypes were diluted into healthy blood to estimate the limit of detection of HR-Mass-Fix method. 179 Rochester Mayo Clinic patients who had a clinically ordered BM MRD assessment by next generation flow (NGF) cytometry (2 x 10-6), a blood sample available within 7 days of the BM biopsy, and a pre-treatment measured M-protein mass by Mass-Fix were utilized to assess the concordance of the BM and blood MRD status. Results The average limit of detection (LOD) of the HR-Mass-Fix was found to be significantly lower than Mass-Fix (0.0003 g/dL and 0.01 g/dL, respectively). The treated patient cohort utilized for comparison consisted of 145 myeloma, 21 AL amyloid, 4 LPL lymphoma and 9 other PCDs. Comparing the Mass-Fix and HR-Mass-Fix results, 100% of blood positive MRD results by Mass-Fix were positive by HR-Mass-Fix. HR-Mass-Fix detected residual M-proteins (mass within +/- 1 Da of pre-treatment) in 29 samples (40%) that were negative by Mass-Fix. Thus, HR-Mass-Fix increased the overall blood MRD positivity rate from 57% by Mass-Fix to 78%. The BM NGF MRD positivity was lower at 54%. The overall agreement of blood and BM by Mass-Fix was 71% (kappa 0.4) which decreased to 0.63 (kappa 0.3) with HR-Mass-Fix. Most of the disagreements were HR-Mass-Fix Blood (+)/BM NGF (-). Blood M-protein MRD appeared to be affected by M-protein half-lives. To determine this, the M-protein isotype distribution of Blood/BM MRD status was compared the M-protein isotype distribution of the overall cohort. The half-lives are as follows: IgG 23 days, IgA 6 days, IgM 5 days and FLC 0.25 days. When both blood and BM were positive, the isotype distribution was not significantly different than the overall cohort. For blood(+)/BM(-) patients, IgG (with the longest half-life) were significantly overrepresented compared to the overall cohort (74% vs 51%) . For blood(-)/BM(+) cases, there were no IgG M-proteins, and the majority were FLC patients. These results suggest that patients with shorter half-life M-proteins (non-IgG) are more likely to be Blood MRD(-) than patients with longer half-life M-proteins. M-protein rate changes over time will likely be needed to resolve the M-protein half- life affect. Conclusions HR-Mass-Fix can significantly increase the detection of M-proteins in comparison to our current Mass-Fix method. Ig recycling was found to be a likely reason for the disagreement between BM and blood. Therefore, a negative blood MRD status by HR-Mass-Fix is most likely to be the most significant in predicting patient outcomes.

Abstract Background: Waldenström Macroglobulinemia (WM) is an indolent B-cell lymphoplasmacytic lymphoma characterized by heterogeneous clinical behavior and variable progression patterns. While MYD88L265Pand CXCR4 mutations are frequently encountered, the broader genomic landscape underpinning disease evolution from smoldering WM (SWM) to active treatment naïve WM (TNWM), post-treatment remission WM (PTWM) and relapsed/refractory WM (RRWM) remains incompletely understood. To address this gap, we studied the mutational profile across the WM disease spectrum. Methods We performed whole exome sequencing (WES) on sorted (CD19 and/or CD138) bone marrow aspirates of patients across the spectrum of WM. Paired germline sequencing was performed using peripheral blood mononuclear cells (PBMCs). Unique molecular identifier-tagged reads were deduplicated using fgbio. WES data were processed through the Sarek pipeline. Any valid mutation from either caller, present on the index or in COSMIC was considered. Copy number variations (CNVs) were inferred via CNVkit and summarized at the gene and arm level (≥50% directional change). Mean tumor and germline coverages were 174X and 74X, respectively. Fisher's exact test was used for enrichment and hypergeometric test for overlap analyses. Results A total of 78 high-quality WM samples [15 SWM, 44 TNWM, 13 RRWM, 6 PTWM in remission (all with paired TNWM samples)] were sequenced. The mutational burden varied across disease states (median SWM=1.48 m/Mb, TNWM= 1.12 m/Mb, RRWM = 1.59 m/Mb; p=0.04). Density plots revealed bimodal VAF distributions, consistent with clonal and subclonal architectures in WM. Overall, 77% harbored a MYD88L265P mutation by WES. Among MYD88^WT^ patients, AS-PCR identified MYD88L265P in 4 (25%) not detected by WES, raising the overall mutation rate to 83%, plus one with a non-L265P variant. Low VAF (&lt;10%) MYD88L265P mutations were seen in 6% of matched PBMCs. MYD88 copy number gain was seen in 2 (17%) MYD88WT TNWM patients. CXCR4 mutations were detected in 38% by WES (18% each frameshift and nonsense). Two (4%) CXCR4WT samples were positive by PCR, giving an overall rate of 40%. CXCR4 mutations were more frequent in RRWM (54%) vs TNWM (41%) and SWM (27%), though not statistically significant. Del(6q) and Del(17p) were noted in 16% (n=12) and 7% (n=5) of patient samples. All del(17p) events were noted in TNWM samples and in one paired post-treatment sample. Overall rate of del(17p) and TP53 mutation was 14% (n=11). RRWM was enriched in ARID1A alterations, a gene implicated in chromatin remodeling and plasma cell identity formation [38% (n=5) in RRWM vs. 11% (n=6) in TNWM and SWM], compared to TNWM and SWM p=0.03]. Alterations in NF-kB signaling gene MAP3K14 were more frequent in RRWM (31%, n=4) compared to the SWM/TNWM cohort [(7%), n=4; p=0.036). We noted an enrichment in the TP53 mutation rate in RRMW [n=3, 23%, OR 7.7] compared to TNWM and SWM cohorts [n=2, 4%), p=0.04]. Mutations in FUBP1 (p=0.03), an upstream regulator of MYC, and CARD11 (p=.043), a B-cell signaling scaffold protein were also more frequent in RRWM. Notably, none of the SWM patients harbored an ARID1A alteration (p=0.057), suggesting acquisition during progression. CNV analysis revealed that MAP3K14 amplifications were frequent in RRWM (n=3, 23%) compared to SWM/TNWM [n=2 (4%), p=0.043]. RRWM samples showed increased CD79B mutations (15%) and significant overlap with the C5/ABC diffuse large B-cell lymphoma (DLBCL) genomic cluster (Chapuy et al., Nat. Med. 2018; p=0.007). This overlap remained significant after excluding MYD88L265P (p=0.019), driven by CARD11, CD79B, and IGLL5, suggesting that a subset of RRWM may acquire an ABC DLBCL-like mutational profile. These findings warrant further investigation using transcriptional profiling. Conclusions This study provides a genomic map of WM evolution from precursor to relapse. Increasing somatic mutations and CNVs support stepwise progression. Enrichment of genes involved in chromatin remodeling and plasma cell identity formation (ARID1A), NF-kB or BCR signaling (CARD11, MAP3K14), and DNA damage repair (TP53) were noted at relapse, all of which have been shown to drive aggressive disease biology. Emergence of an ABC-like genotype in a proportion of RRWM indicates convergent evolution with aggressive lymphomas. Transcriptional studies are warranted to explore this further.

Abstract Background The prognostic relevance of fluorescence in-situ hybridization (FISH) abnormalities is well-established in multiple myeloma (MM), where high-risk (HR) abnormalities are associated with poor survival. In AL amyloidosis, however, the cytogenetic landscape and its implications might be different. For example, t(11;14), common in AL amyloidosis, has historically been linked to inferior outcomes in the pre-daratumumab era. HR FISH abnormalities are less common and less well-defined in this setting, underscoring the need to evaluate their significance in this disease. Methods We retrospectively analyzed 698 newly diagnosed AL amyloidosis patients seen at Mayo Clinic, Rochester, between 2012–2021 who had baseline FISH testing. HR FISH was defined as del(17p)/monosomy 17, t(4;14), t(14;16) or t(14;20). Baseline characteristics and treatment patterns were compared between the HR and the standard-risk (SR) groups. Staging used the Mayo 2004 system with European modification. Hematologic responses were assessed at 2 and 6 months, and cardiac/renal responses at 3, 6, 12, and 24 months per consensus criteria. Overall response rate (ORR) for hematologic and organ responses included patients who achieved partial response (PR), very good partial response (VGPR), and complete response (CR). Overall survival (OS) was estimated via Kaplan-Meier; comparisons used log-rank testing. Cox regression was used for univariate and multivariable analyses. Results Among 698 patients, 73 (10.4%) had HR FISH. The most common HR abnormality was t(14;16) (n=34, 4.9%), followed by del(17p)/monosomy 17 (n=21, 3%), and t(4;14)/t(14;20) (n=12 each, 1.7%). Across the cohort, t(11;14) was most frequent (51.3%), followed by del(13q) (36.2%), hyperdiploidy/tetraploidy (26.3%), and 1q gain/amp (23.6%). Compared to SR group, HR FISH group had fewer males (43% vs. 69%, p&lt;0.0001), with no difference in age (62.5 vs. 65, p=0.44), cardiac (73% each, p=1) or renal involvement (52% vs. 54%, p=0.71). More HR patients had early cardiac stage (69% vs. 55.9%, p=0.04). Both groups were predominantly lambda isotype (82% vs. 74%, p=0.15), with similar baseline dFLC (21.6 vs. 28.4 mg/dL; p=0.81). Intact immunoglobulin secretion was more common in the HR group (68% vs. 45%, p=0.004). The HR group more often underwent advanced bone imaging (44% vs. 29%, p = 0.015) and had a higher incidence of lytic lesions or fractures (27% vs. 15%, p = 0.046). Use of bortezomib-based therapy, primarily CyBorD, was similar between the groups (67% each). Daratumumab-based therapy (16% vs. 11%, p=0.25) and autologous stem cell transplantation (ASCT) (33% vs. 25%, p=0.16) were numerically higher in the HR group, though not statistically significant. Post-ASCT maintenance was more frequent in the HR group (17% vs. 7%, p=0.006). At 2 months, hematologic ORR was higher in the HR group (90% vs. 72%, p=0.007), with higher ≥VGPR (67% vs. 32%, p&lt;0.0001) and CR rates (24% vs. 8%, p=0.0004). At 6 months, the HR group maintained higher ≥VGPR (89% vs. 71%, p=0.008) and CR rates (41% vs. 26%, p=0.04), with no difference in ORR (98% vs. 92%, p=0.18). Cardiac responses at 6 months favored the HR group (VGPR or better: 29% vs. 12%, p=0.013; CR: 13% vs. 3%, p=0.007). At 12 months, cardiac ≥VGPR remained higher (50% vs. 29%, p=0.01), though CR was not significantly different (18% vs. 9%, p=0.1). Renal ≥VGPR at 6 months was more common in the HR group (47% vs. 22%, p=0.004), but not renal CR (9% vs. 7%, p=0.95). At 12 months, renal ≥VGPR remained higher in HR (61% vs. 40%, p=0.004). With a median follow-up of 87 months, median OS was not reached in HR (95% CI: 72.6–NR) vs. 88.9 months (95% CI: 72.8–110.5) in SR (p=0.03). In multivariable analysis, age ≥65 (HR 1.56, p=0.0001) and &gt;2 organ involvement (HR 1.46, p=0.002) were associated with worse OS, while ASCT (HR 0.35, p&lt;0.0001) and cardiac stage I/II (HR 0.48, p&lt;0.0001) predicted better OS. HR FISH was not independently associated with OS (HR 0.74, p=0.14). Conclusions HR FISH abnormalities in AL amyloidosis are not independently associated with OS, unlike in MM. Patients with HR FISH abnormalities more often presented with earlier cardiac stage and demonstrated deeper hematologic and organ responses than patients with SR FISH abnormalities. This study underscores how clonal characteristics can potentially aid in more personalized treatment approaches for patients.

Abstract Introduction: The DEAD-box helicase 41 (DDX41) gene, located on chromosome 5q35, is a tumor suppressor gene involved in RNA processing. Germline mutations in this gene can predispose patients to myeloid malignancies. Studies have suggested a more favorable prognosis in those with germline mutations in DDX41, with progression of disease being a frequently encountered cause of death. In this retrospective study, we explored the causes of death in a cohort of patients with pathogenic DDX41 mutations. Methods: This was a retrospective study of patients diagnosed with myeloid neoplasms between 2009-2024 and found to have DDX41 mutation (DDX41m) via next generation sequencing (NGS) at our institution. Myeloid NGS was obtained at or after the diagnosis of myeloid disease. Germline testing (when available) was performed through buccal/skin samples. Carriers of DDX41m without a myeloid neoplasm diagnosis and patients with only DDX41m VUS were excluded. Baseline characteristics at the time of myeloid neoplasm diagnosis included age at diagnosis, DDX41m variant allele frequency (VAF), blood counts (hemoglobin, white blood cell count, platelets), cytogenetics, bone marrow blast percentage, number of co-mutations, and treatment received. Unadjusted comparisons were made using continuous or categorical variables. Median overall survival (OS) was calculated from the time of diagnosis with myeloid neoplasm to the time of death, using BlueSky Statistics V.10.3.4. Results: Of the 112 patients identified to have pathogenic DDX41m, 29 (26%) patients were deceased at the time of data analysis. In this cohort of 29 patients (median age at diagnosis 72 years, 17 (59%) males), disease groups at initial diagnosis included 17 (59%) patients with MDS, 9 (31%) AML, and 3 (10%) MPN. Fourteen of the 17 (82%) of the patients with MDS were classified as MDS-EB1 or MDS-EB2. Seven of the 17 (41%) patients with MDS progressed to AML at the time of death, with 57% of the patients having more than 30% bone marrow blasts at time of progression. Blood counts at diagnosis in the cohort included a median hemoglobin of 9.8 g/dL, platelets of 83 x 109/L, and white blood cell count of 2.1 x 109/L. Twenty-one (72%) of patients had normal cytogenetics. Nine (31%) patients had both a pathogenic mutation and a variant of uncertain significance (VUS) in DDX41, with the remaining 20 patients harboring only a pathogenic DDX41 mutation. Eight (27%) patients underwent germline testing, with 7 confirmed to harbor a germline DDX41m. In the deceased cohort, 9 (31%) patients underwent HSCT. Three of the patients with AML and 1 patient with MDS were observed and did not undergo treatment. Median overall survival of the deceased cohort was 29 months. The median time to AML progression in the group with MDS was 14 months. Causes of death included infection in 11 (38%) patients, 9 (31%) with disease progression/relapse, 3 (10%) with acute gastrointestinal graft versus host disease (GVHD), and 1 (3%) from cerebral bleed. The cause of death was unknown in the remaining 5 (17.2%) patients. Infections included pneumonia, bacteremia, neutropenic enterocolitis, fungal, and unknown etiology. Of the 4 patients who were observed, 2 died from unknown cause and 2 died from disease progression. Of the 16 patients with AML at time of death, 9 (56%) died from disease progression or relapse, 3 (19%) from infection, 2 (13%) from GVHD, and 2 (13%) from unknown causes. Of the 10 deaths in the MDS group, 7 (70%) were from infection, 1 (10%) from GVHD, 1 (10%) from cerebral bleed, and 1 (10%) from an unknown cause. Three cases of infection in the MDS group occurred during remission. Infection was a more common cause of death in the MDS group compared to the AML group, where disease progression prevailed as a cause of death (70% vs 19%, p=0.01). Eight (80%) of the patients with MDS who died from infection were neutropenic prior to death, and 4 (50%) of those patients were on neutropenic antimicrobial prophylaxis. Conclusions: In this cohort of 29 deceased patients with a DDX41-mutated myeloid neoplasm, we characterized causes of death. Disease progression/relapse was a significantly more common cause of death in those with AML, compared to infection in patients with MDS. Our work underscores the need for additional studies looking into non-leukemic causes of death in patients with DDX41m myeloid diseases and potential strategies to mitigate infection-related mortality in this population.

Abstract Background: Clonal cytopenia of undetermined significance (CCUS) is defined as clonal hematopoiesis in the absence of a hematologic neoplasm, along with unexplained cytopenia. While several studies have identified risk factors and developed scores to predict progression to overt myeloid neoplasms, the clinical and molecular features during the progression process remain poorly understood. Aim: Evaluate the clinical and clonal characteristics of patients with CCUS, with a focus on the longitudinal evolution of clonal and clinical parameters over time. Methods: After IRB approval, we retrospectively reviewed charts of patients with unexplained cytopenia (2015-2024), recording data at the time of CCUS diagnosis (WHO 2022 diagnostic criteria) and at time of follow-up bone marrow biopsy after diagnosis. Follow-up CBC and karyotype data were recorded for patients who had repeat bone marrow biopsies (n= 111), while follow-up clonal parameters and risk scores were calculated for those who underwent repeat NGS (n= 74). A reduction or expansion in clone size was defined as a change exceeding 5% (CE5%), or change exceeding 10% (CE10%) from the baseline value. Overall survival (OS) was calculated from diagnosis to last follow-up. For statistical analysis, we used BlueSky Statistics V10.3.1. Results: 214 CCUS patients (median age 73, 68% males) were included. At baseline, 30% of patients had abnormal cytogenetics, with del (20q) being the most common one (8%; n= 18), followed by trisomy 8 (6%; n= 13), and loss of chromosome Y (5%; n= 10). The median number of mutations was 2 (range, 1-5), with the most common mutations TET2 (38%), SRSF2 (21.5%), ASXL1 (21%), ZRSR2 (18.5%), DNMT3A (9.5%), and U2AF1 (9%). Most patients had high risk CHRS (60%), followed by intermediate (30%), and low risk (10%). On the other hand, 41% had high risk CCRS, 29% had intermediate risk, and 30% had low risk. After a median follow-up of 46 months, 62 patients died (median OS not reached). A decrease in the white blood cell (WBC) count from the time of diagnosis to follow-up was more frequently seen among CCUS patients who progressed to MN (70% vs 50%, p= 0.04), however, changes in hemoglobin and platelets did not differ between those who progressed and those who did not (p&gt; 0.05). Although the frequency of abnormal karyotypes at diagnosis was similar between patients who eventually progressed (28%) and those who did not (31%) (p= 0.6), 4 (2%) patients with initially normal karyotypes acquired chromosomal abnormalities during follow-up, and all progressed to MDS. Among the 74 patients who had follow-up NGS, 31% acquired new mutations, clonal expansion of pre-existing mutations were seen in 54% using CE5% and 19% per CE10%, and 16% developed new variants of uncertain significance (VUS). Acquiring new pathogenic mutations was similar in patients who progressed to MN compared to those who did not progress (34% vs 28%, p= 0.6). On the other hand, clonal expansion was significantly more observed in patients who progressed compared to those who did not, using both CE5% (73% vs 31%, p = &lt;0.001) and CE10% (27% vs 9%, p= 0.03). At follow-up, ASXL1 was the most commonly acquired mutation among patients who did not progress (4 cases), followed by TET2 (2 cases), and U2AF1, GATA2, DNMT3A, SF3B1, ZRSR2, TP53, and CBL (1 case each). On the other hand, SRSF2, SETBP1, CBL, JAK2, TET2, and RUNX1 were more frequently acquired among those who progressed to myeloid neoplasms (each appeared in 2 patients). When recalculating CCRS, CHRS, IPSS-M, and IPSS-R at follow-up for patients who had repeat NGS, there was no significant difference in score changes - either upward or downward - between those who progressed and those who did not (p&gt; 0.05). Conclusion: In CCUS patients who progressed to myeloid neoplasms, WBC decline, clonal expansion (more frequent), and evolving chromosomal aberrations (less frequent) were observed, supporting the value of longitudinal genomic and clinical monitoring in CCUS.

Abstract Background: Flow cytometry (FC) is widely utilized for the identification of measurable residual disease (MRD) in multiple myeloma (MM), providing an essential laboratory indicator for prognostic assessment and therapeutic management. Unfortunately, the high level of expertise required, long manual analysis time, and complexity of FC data files currently limit the offering of this testing to selected reference laboratories. Methods: We developed an artificial intelligence (AI) pipeline to automatically enhance unaltered FC files, minimizing the expertise and manual analysis time needed to detect MM MRD using the 2-tube Euroflow Consortium Panel (Cytognos). Raw FC files corresponding to 150 MRD-positive bone marrow samples (MRD &lt; 5%, median = 0.0022%), and 39 MRD-negative samples were processed through our CCADDAS (Clustering and Classification of All events, Dimensionality reduction, Downsampling and Aberrancy Scaling) pipeline, deployed on a custom clinical-grade cloud environment (Biolegend). Automated processing steps included elimination of acquisition errors (FlowCut), state-of-the-art clustering (PARC), cluster-informed and density-based downsampling with preservation of low-event subsets, dimensionality reduction (UMAP), and cluster-based anomaly detection compared to negative controls (29 bone marrow aspirates). In addition, a deep neural network (DNN) trained on expert-defined subpopulations from negative controls was included for automatic gating of normal subsets (Tensorflow v2). AI-enhanced data files were analyzed using a general-purpose flow cytometry analysis software (Kaluza v 2.3, Beckman Coulter), and %MRD estimates were compared to reported results based on traditional expert analysis of original FC files. Results: Cluster-informed downsampling reduced the number of cells to be manually analyzed from 4.1 million to 196,761 cells per tube, on average (95% cellularity reduction); resulting in a smaller FC data file (from 203.2 MB to 20.5 MB; 90% data reduction). Importantly, low-level MRD events were adequately preserved after downsampling (median 88% and 77% retention, for 0.01-0.001% MRD and &lt; 0.001% MRD, respectively). True number of events were accurately estimated on gated subsets using an “upsampling factor” parameter [observed # events x mean (upsampling factor)]. Gating of normal subsets was completely automated using a DNN classifier parameter. In 96% of positive cases, MRD was rapidly identified as immunoglobulin light chain-restricted plasma cells on a single pre-calculated UMAP plot (tube 2), after dual coloring for kappa and lambda. On the remainder 4% of positive cases, MRD was easily segregated from benign plasma cells using the AI-generated “aberrancy scale” parameter or other strategies. The use of AI-enhanced files reduced manual analysis time from 15.05 minutes (SD = 6.84) to 1.29 minutes (SD = 0.90) per case, on average (p &lt; 0.0001) (91% reduction of manual analysis time). MM MRD was detected in all positive cases above limit of detection for our assay (≥0.0002%), with excellent quantitative correlation with conventional analysis on original FC files (linear regression slope = 0.9841, P &lt; 0.0001). Conclusion: We introduce a largely unsupervised AI pipeline that transforms raw MM MRD FC data from the Euroflow Consortium panel into a markedly smaller, AI-annotated and software-agnostic FC file, including comparison to normal controls. This CCADDAS pipeline simplifies and accelerates detection of MM MRD in clinical diagnostics, reducing the number of cells analyzed by 95% and manual analysis time by 91%, without impacting test performance. Moreover, CCADDAS can be utilized for any laboratory-developed MM MRD assay, and its small-sized export is compatible with any clinical FC software, computing platform, and analysis strategy. Adoption of CCADDAS is likely to facilitate the implementation of MM MRD FC analysis by more clinical laboratories.