Rahman, Zaid Abdel

Multiple myeloma (MM) treatment outcomes in developing countries may be impacted by resource constraints. This systematic review and meta-analysis evaluated efficacy outcomes of MM treatments across developing regions. Comprehensive searches in five major databases identified 37 eligible studies from Asia, Africa, Latin America, and Eastern Europe. The Newcastle-Ottawa Scale was used to assess risk of bias. Newer novel agents including daratumumab, carfilzomib, and pomalidomide showed limited use across studies. For patients receiving autologous stem cell transplantation (ASCT), the pooled overall survival rate at longest follow-up (2.5-12.5 years) was 62% (95% CI: 48-75%), with high heterogeneity (I²=92%), while the progression-free survival rate at longest follow-up (3-8 years) was 44% (95% CI: 23-67%). Comparative analyses demonstrated ASCT was associated with significantly superior 5-year survival compared to conventional chemotherapy (RR: 1.59; 95% CI: 1.38-1.82). Bortezomib-based regimens showed better outcomes than thalidomide-based therapies (HR for overall survival (OS) at 4 years: 0.73; 95% CI: 0.53-1.0) and alkylating agent-based regimens (HR: 0.48; 95% CI: 0.28-0.83). Despite resource limitations, ASCT and certain novel agents are associated with improved survival outcomes for MM patients in developing countries. However, substantial heterogeneity in outcomes suggests variability in healthcare infrastructure, treatment accessibility, and clinical expertise across these regions.

Background: Ph-like ALL is a high-risk subset of B-lineage ALL that responds poorly to standard chemotherapy regimens. While allogeneic hematopoietic cell transplantation (HCT) is routinely recommended for patients with Ph-like ALL, large multicenter data addressing its role is limited. Here, we conducted a multicenter study to evaluate the role of HCT in adolescent and young adult (AYA) and adult patients (pts) with Ph-like ALL and compare their outcomes to pts with Ph-pos and Ph-neg (non-Ph-like) ALL. Methods: The study included pts (age ≥18) with B-lineage ALL who received HCT in first complete remission (CR1) at 3 academic centers (MD Anderson Cancer Center, City of Hope and Mayo Clinic) between 2006 and 2021. Pts were divided into 3 main subgroups: Ph-like, Ph-pos and Ph-neg ALL. Ph-like ALL cases were identified using cumulative data obtained by targeted RNA sequencing, conventional cytogenetics, FISH studies, whole genome chromosomal microarray and flow cytometry. Measurable residual disease (MRD) prior to HCT was measured using flow cytometry with a sensitivity of 0.01% for Ph-neg and Ph-like ALL, and with a PCR assay for BCR::ABL1 for Ph-pos ALL. MRD-negativity was defined as <0.01%. Predictors of relapse were evaluated in univariate and multivariate analysis using Fine-Gray sub-distribution hazard models considering non-relapse mortality (NRM) as a competing risk. Results: 673 patients were identified, 83 (12.3%) had Ph-like ALL, of which 73% had CRLF2-alterations. The remaining patients were classified either as Ph-pos (N=271, 40.3%) or Ph-neg ALL (N=319, 47.4%). Patients with Ph-like ALL were younger (median age 40 years vs 48 and 46 years for Ph-pos and Ph-neg ALL, respectively, p=0.01), more likely to be of Hispanic ethnicity (69% vs 32% and 48% for Ph-pos and Ph-neg ALL respectively, p<0.001). Patients with Ph-like ALL were also more likely to have induction failure (24% vs 2% and 11% for Ph-pos and Ph-neg ALL, respectively, p=0.001). A summary of pts characteristics for each subgroup can be found in Table 1. The median follow-up was 30, 52 and 48 months for patients with Ph-like, Ph-pos and Ph-neg ALL, respectively. In univariate analysis, 3-yr OS and PFS did not differ significantly (66% and 59% vs 59% and 54%, p=0.1) between patients with Ph-like and Ph-neg ALL, respectively. Similarly, the cumulative incidence of relapse was comparable between patients with Ph-like and Ph-neg ALL (22% vs 20%, respectively, p=0.7). In contrast, the 3-yr OS (75%, p<0.001) and PFS (70%, p=0.001) were significantly higher and relapse rate significantly lower (12%, p=0.003) in pts with Ph-pos ALL compared with Ph-like or Ph-neg ALL (Figure 1). The inferior survival in patients with Ph-like and Ph-neg ALL was likely attributable to higher relapse rates (22% and 20% vs 12%, respectively, p=0.003) compared to Ph-pos ALL. Finally, the 3-yr NRM rate in patients with Ph-like ALL was comparable (20% vs 18% and 23%, respectively, p>0.1) to Ph-pos and Ph-neg ALL. We confirmed that the relapse rate in patients with Ph-like ALL was comparable to the rate in pts with Ph-neg ALL (HR=1.02, 95% CI 0.6-1.8, p=0.9) on multivariate analysis (MVA). Ph-pos ALL was associated with a significantly lower relapse rate compared with Ph-neg ALL (HR=0.4, 95% CI 0.3-0.7, p<0.001). MRD positivity prior to allo-HCT was the only additional significant predictor for relapse on MVA (HR=2.9, 95% CI 1.8-4.7, p<0.001). Conclusions: HCT appears to overcome the poor prognosis of patients with Ph-like ALL. Despite higher induction failure rates, patients with Ph-like ALL undergoing HCT in CR1 had similar outcomes to other Ph-neg ALL subsets. The impact of effective salvage therapy leading to MRD-negativity in CR1 in this group is under investigation and will be reported. Further studies are needed to assess the impact of different Ph-like alterations on HCT outcomes. Outcomes for patients with Ph-pos ALL are significantly better than other groups, likely due to the use of TKIs pre- and post-HCT.

Context.— Unlike B-cell acute lymphoblastic leukemia/lymphoma (ALL/LBL), there have been few therapeutic advances in T-cell ALL (T-ALL)/LBL, an aggressive ALL/LBL subtype. Objective.— To perform a focused tissue array study to elucidate tumor markers of therapeutic potential in T-ALL/LBL. Design.— Using immunohistochemistry, we evaluated expression of leukemic antigens of interest, specifically CC-chemokine receptor 4 (CCR4), among others, on available remnant diagnostic material, including tumor tissue slides obtained from formalin-fixed, paraffin-embedded preserved tissues. Results.— Our analysis identified, for the first time, expression of CCR4 in T-ALL/LBL in 11 of 27 cases (40.7%) and confirmed common expression of BCL2, CD38, and CD47, as reported previously. We also identified the expression of CD123 in 4 of 26 cases (15.4%), whereas BCL6 and PDL1 were expressed in a small number of T-ALL/LBL cases. The potential novel target CCR4 was significantly more common in the Pre/Pro-T immunophenotypic subtype, 6 of 9 (66.7%, P = .01). No additional differences in clinical and epidemiologic variables were noted among positive or negative CCR4 cases. Conclusions.— These findings support preclinical and clinical testing of therapies targeting CCR4, CD47, BCL2, CD38, and CD123 in T-ALL/LBL, and may help guide the development of targeted clinical trials in T-ALL/LBL, a rare disease in urgent need of novel therapies.

Abstract Extramedullary disease in acute myeloid leukemia (AML), also known as myeloid sarcoma (MS), is an uncommon presentation of de novo AML. We analyzed medical records of patients in the Mayo Clinic database spanning between 1996 and 2021 who were diagnosed with de novo extramedullary AML. Survival outcomes were analyzed using Kaplan-Meier and Cox-proportional hazard models for univariate and multivariate analysis, respectively. With a median follow-up of 20.7 months, 83 patients with de novo MS were identified; 49 presented with synchronous MS and 34 with isolated MS. Next generation sequencing (NGS) revealed RTK-RAS pathway mutations in 44% of patients. Median overall survival (OS) was 25.3 months and 17.8 months in isolated and synchronous MS, respectively (p = 0.49). Variables associated with improved OS on univariate analysis included treatment with intensive chemotherapy (p < 0.001), normal or favorable risk karyotype (p = 0.001), age less than 60 years (p = 0.001), and a complete response to treatment at extramedullary sites (p < 0.0001). On multivariate analysis, normal or favorable risk karyotype (p = 0.001), age less than 60 (p = 0.01), and a complete extramedullary response (p = 0.001) were associated with improved OS. Localized therapy did not provide added survival benefit in isolated MS. Genomic stratification, age, and extramedullary site response are predictive of survival outcomes.

e19002 Background: Extramedullary disease in acute myeloid leukemia (AML), also known as myeloid sarcoma (MS), is an uncommon presentation of de novo AML. Clinicopathologic characteristics and optimal treatment strategies of de novo MS remain unclear in both isolated MS without bone marrow (BM) involvement and synchronous MS with BM involvement. Methods: In a single-site retrospective study, medical records of patients with de novo extramedullary AML who received oncological care at any Mayo Clinic site between 1996 and 2021 were analyzed. Using BlueSky Statistics software, survival outcomes were analyzed using Kaplan-Meier and Cox-proportional hazard models for univariate and multivariate analysis, respectively. Results: 83 patients with de novo MS were identified; 49 (59%) presented with synchronous MS and 34 (41%) exhibited isolated MS. Median age at diagnosis was 56 years (range, 17-89); 63% were male. Next-generation sequencing of the blood +/- BM revealed abnormalities in 24/27 (88%) analyzed patients; aberrations included mutations in RTK-RAS pathways (12/27), NPM1 (10/27), TET2 (6/27), and IDH2 (4/27). Median length of follow-up was 1.73 years (95% CI; 0.03-3.0); 53 patients (64%) had expired. Median event free survival was 0.64 years and 0.61 years in isolated and synchronous MS, respectively (p = 0.5). Median overall survival (mOS) in isolated and synchronous MS was 2.1 years and 1.5 years, respectively (p = 0.5). Induction treatment with intensive chemotherapy (IC) was administered in 70 patients (84%). IC regimens included 7+3, MEC, CLAG-M, and hyper-CVAD. Variables associated with improved survival in both groups included treatment with IC +/- allogenic stem cell transplant (alloSCT) (p < 0.001), normal or favorable risk karyotype (p = 0.001), and age less than 60 (p = 0.001). Localized therapy (LT) did not provide an added survival benefit. Patients with synchronous MS were more likely to relapse in the BM and blood than isolated MS (p = 0.02). Conclusions: Enriched with RTK-RAS mutations, de novo MS remains an aggressive form of AML, particularly in patients with intermediate or high-risk genomics or those with skin, soft tissue, or lymphatic involvement. IC should be employed with consideration of alloSCT in eligible patients, particularly in synchronous MS due to a heightened risk for medullary and leukemic relapse.[Table: see text]

AbstractGilteritinib is approved for the treatment of relapsed/refractory (R/R) acute myeloid leukemia (AML) with an FLT3‐mutation (FLT3mut+). However, the gilteritinib phase 3 ADMIRAL study (Perl et al NEJM 2019) was conducted prior to widespread adoption of either midostaurin as a component of standard intensive induction and consolidation or posttransplant FLT3 inhibitor maintenance. We performed a retrospective analysis using data from 11 US centers and where we identified 113 patients who received gilteritinib alone or as combination therapy for the treatment of R/R FLT3mut+ AML. The composite complete remission (CR) rate (CRc, defined as CR + CRi + CR with incomplete platelet recovery [CRp]) was 48.7% (n = 55). The CRc rate after treatment with gilteritinib in patients who were treated with only prior 7+3 and midostaurin with or without consolidation was 58% with a median survival of 7.8 months. Survival was longest in patients who obtained a CR, particularly a cMRD (clinical minimal or measurable residual disease) negative response; this remained significant after censoring at the time of stem cell transplant. The mitogen‐activated protein kinase pathway activating mutations that are known for gilteritinib resistance (NRAS, KRAS, and PTPN11) had lower CRc (35% vs. 60.5%) and lower median overall survival than patients' whose leukemia did not express these mutations (4.9 months vs. 7.8 months) (HR 2.4; 95% CI 1. 5.4) p value <.01.

Abstract Background: trALL is an important secondary primary malignancy (SPM) that has recently been appreciated. While patients (pts) with MM have an 8%-17% risk of developing an SPM while on lenalidomide (R) maintenance following autologous stem cell transplant (ASCT), trALL has been rarely observed. Little is known about the characteristics of trALL in pts with MM compared to pts who had other malignancies prior to the development of trALL. We define tALL as any prior exposure to cytotoxic chemotherapy and/or radiation for another malignancy, and herein, we report a comparative analysis of characteristics and outcomes of pts with trALL with and without MM from the Mayo Clinic Cancer Center (MCCC). Methods: We performed a systematic search in the 3-site MCCC registry and included all pts diagnosed and received at least 1 cycle of ALL-directed therapy and/or underwent allogeneic transplantation (AlloHCT) for ALL between 2007-2020. All cases of trALL in this series are B-ALL. Comparisons of characteristics between trALL patients with and without MM were made using a Wilcoxon rank sum test (continuous variables) or Fisher's exact test (categorical variables). Time-to-event variables were compared using unadjusted Cox proportional hazards regression models. Results: 70 trALL pts (14 MM [20%], 56 non-MM [80%]) were identified during the study period. The median age at trALL diagnosis was 63.9 (range 47-71) for MM pts and 63.1 (range 18.2-84) for non-MM pts. Median follow-up from trALL diagnosis was 1.42 years (range 0.02-10.6 years). The most common prior non-MM malignancies among tALL pts were breast (28.6%), lymphoma (17.9%), myeloid (17.9%), and GU/GYN (14.3%). Amongst the 14 MM pts, 100% (n=10) had ISS-I disease, 8 (57%) had IgG K MM, 1 (n=10) had high risk cytogenetics, 8 (57.1%) received R-based induction , 4 (28.6%) received CyBorD induction, 4(28.6%) received VRD induction, 3 (21.4%) received RD induction. 10 (71.4%) pts were actively on R when they developed trALL, 8 (57.1%) pts received prior ASCT. The median time to develop trALL following ASCT for MM was 46.3 months (m), (95% CI 20.4-67.6), 12 (85.7%) pts received R maintenance with a median duration of 53m (95% CI 16.9-121). The median time to develop trALL after initiation of R maintenance was 61.2m (95% CI 16.9-123.4). The most common trALL induction regimen received was HyperCVAD which was used in 71.4% of MM pts and 51.8% of non-MM pts. In comparison to non-MM pts, MM patients had a significantly lower WBC at diagnosis (Median: 2.0 vs. 5.8, P=0.005),no t(9;22) BCR/ABL1 cytogenetics (0.0% vs. 35.7%, P=0.008), a higher frequency of hypodiploid/near-triploid (Ho-Tri) cytogenetics (42.9% vs. 12.5%, P=0.009), and a lower frequency of prior radiation therapy (7.1% vs. 44.6%, P=0.012). MM pts had a higher frequency of AlloHCT for trALL (71.4% vs. 42.9%, P=0.075) and were more commonly in complete response (CR) at transplant (100.0% vs. 70.8%, P=0.078). No trALL in MM pts were Ph-like ALL. There was a statistically significant difference in time to development of trALL between previous malignancy locations (P=0.018), with GU/GYN (Median: 9 years) having the longest time and myeloid (Median: 3 years) having the shortest time; MM was 6 years. In the overall pt cohort, 56 (80%) pts achieved a complete response after induction and 60% (n=25) were minimal residual disease (MRD)+ after induction. Pts with MM had a significantly lower likelihood of being MRD+ after induction (OR=0.09, P=0.015). Overall, 24.3% of pts relapsed after induction therapy for trALL; 39 (55.5%) died after trALL diagnosis including 43% (n=35) who died after AlloHCT. Although pts with MM tended to have better outcomes compared to non-MM trALL pts in terms of overall survival after trALL diagnosis (Figure 1A), survival after AlloHCT (Figure 1B), relapse rate after trALL diagnosis and non-relapse mortality after AlloHCT, none of these findings were statistically significant in this small cohort (Figure 1C). Conclusion: trALL is a unique SPM that can occur in pts with MM. It is associated with Ho-Tri cytogenetics and is BCR/ABL1 negative. The majority of MM pts that developed trALL had undergone prior ASCT and were on R maintenance when they developed trALL. Despite being more likely to have adverse cytogenetics features, MM-associated trALL has similar survival compared to non-MM-associated trALL which speaks to the poor survival outcomes of this SPM. Further research on trALL in MM pts is merited. Figure 1 Figure 1. Disclosures Litzow: Amgen: Research Funding; Pluristem: Research Funding; AbbVie: Research Funding; Actinium: Research Funding; Astellas: Research Funding; Omeros: Other: Advisory Board; Jazz: Other: Advisory Board; Biosight: Other: Data monitoring committee. Bergsagel: Janssen: Consultancy. Fonseca: Scientific Advisory Board: Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; Caris Life Sciences: Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy; Patent: Prognosticaton of myeloma via FISH: Patents & Royalties; Bayer: Consultancy; Takeda: Consultancy; Celgene: Consultancy; Amgen: Consultancy; BMS: Consultancy; Mayo Clinic in Arizona: Current Employment; Juno: Consultancy; Kite: Consultancy; Aduro: Consultancy; OncoTracker: Consultancy, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy; Novartis: Consultancy; Merck: Consultancy; Sanofi: Consultancy; Pharmacyclics: Consultancy; Janssen: Consultancy. Dispenzieri: Takeda: Research Funding; Alnylam: Research Funding; Pfizer: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy; Janssen: Consultancy, Research Funding. Murthy: CRISPR Therapeutics: Research Funding. Ailawadhi: GSK: Consultancy, Research Funding; Sanofi: Consultancy; Pharmacyclics: Consultancy, Research Funding; Takeda: Consultancy; Medimmune: Research Funding; Xencor: Research Funding; Genentech: Consultancy; Janssen: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Cellectar: Research Funding; Beigene: Consultancy; BMS: Consultancy, Research Funding; AbbVie: Consultancy; Karyopharm: Consultancy; Ascentage: Research Funding. Foran: actinium: Research Funding; taiho: Honoraria; bms: Honoraria; servier: Honoraria; pfizer: Honoraria; novartis: Honoraria; OncLive: Honoraria; abbvie: Research Funding; boehringer ingelheim: Research Funding; takeda: Research Funding; trillium: Research Funding; aptose: Research Funding; revolution medicine: Honoraria; syros: Honoraria; sanofi aventis: Honoraria; certara: Honoraria; gamida: Honoraria; kura: Research Funding; h3bioscience: Research Funding; aprea: Research Funding; sellas: Research Funding; stemline: Research Funding.

Abstract TMB is used to guide PD-1-directed immunotherapy in solid tumor Oncology. However, it has not been systematically studied in AML, where the focus has been on cytogenetic risk and individual driver gene mutations (GM's). TMB contribution to AML epidemiology is also uncertain. We therefore studied its association with epidemiologic risk factors; driver GM's and somatic mutations (SM's) in AML risk genes which we recently demonstrated (ABCB1; CYP1A1; CYP2B6; EPHX1; ERCC1,2,& 5; MEFV; MTRR; and TERT); clinical and cytogenetic features; and outcome after therapy in the MCAEC, a highly annotated clinical epidemiology cohort of consecutive AML pts [Finn, Cancer Epidemiol 39:1084, 2015]. Methods: We obtained somatic leukemia DNA from remnant diagnostic cytogenetic pellets in 98 MCAEC patients (pts), as previously described [Foran, Blood (2017) 130:570a]. Whole exome sequencing (WES) was performed at depth of ~100 million paired end 100bp reads using Agilent SureSelectXT Human All Exon V5 + UTRs target enrichment kit. Reads were mapped to human genome build hg19 using BWA-MEM. Single nucleotide variants (SNVs) and small INDELs were identified using Mayo Clinic (MC) analytic pipeline GenomeGPS 4.0.1 following Broad GATK variant discovery best practices of alignment, realignment and recalibration, and multi-sample joint genotyping; and filtered using both germline whole exome and genome sequencing of ~1200 MC Biobank samples and public germline variant databases of 1000 genome project, 6500 individuals in exome sequencing project, and HapMap phase 3. Remaining variants were annotated using ANNOVAR, and functional variants of non-synonymous, truncating, frame-shift, and splice-sites were used in the statistical association analyses. TMB was defined as the number of functional mutations per Mb of coding region, heterozygous or homozygous. TMB associations with epidemiologic risk, clinical characteristics, and SM's in AML risk genes (listed above) or driver GM's (occurring in 5 or more pts: ASXL1, BCOR, CEBPA, DNMT3A, FLT3, IDH2, KRAS, MLL2-5, NF1, NPM1, NRAS, PHF6, RUNX1, SF3B1, STAG2, TET2, TP53, U2AF1) were evaluated using linear regression models; a rank transformation of TMB was utilized due to its skewed distribution. Multivariable analysis (MVA) models were adjusted for variables with p-value &lt;0.05 in unadjusted analysis. Regression coefficients ("β") were estimated, interpreted as change in mean TMB rank for specified variables or characteristic. Associations with outcomes were examined using logistic regression or Cox proportional hazards regression models. All statistical tests were two-sided (version 3.6.2; R Foundation for Statistical Computing, Vienna, Austria). Results Median age at AML diagnosis was 70 yrs (Range: 19-94 yrs), and 67 pts were male. Cytogenetic risk group was favorable (7%), intermediate-normal (46%) or abnormal (20%), and poor risk (27%). 40/61 pts (66%) achieved complete remission (CR). With a median follow-up of 8.0 months (Range: 0.1 - 186), 80 pts (82%) died and 20 (20%) underwent allogeneic transplantation (AlloBMT). Median TMB was 18.2 (Range: 15.0-70.1). In MVA, significant associations with increased TMB were observed in pts with history of prior immunosuppressive therapy or solid organ transplantation (β=19.48, P=0.015), and with FLT3 (β=21.12, P=0.015), MLL2 (β=20.91, P=0.001), and MLL3 (β=11.31, P=0.031) GM's. A borderline association was observed for U2AF1 (β=16.14, P=0.057). TMB was also associated with SM's in TERT (β=25.13, P=0.028); a borderline association with SM's in ABCB1 was not confirmed in MVA (β=-17.98, P=0.069). Additionally, cytogenetic risk group was associated with TMB in MVA (P=0.005), being highest in intermediate-normal and lowest in poor risk groups. Body Mass Index was inversely associated with TMB (unadjusted β=-16.99, P=0.005), but unconfirmed in MVA (β=-8.29, P=0.12). There was no association with CR (OR=0.93, P=0.46), use of (HR=0.96, P=0.64) or relapse risk (HR=1.00, P=0.98) following AlloBMT, or survival (HR=0.97, P=0.56) (Figure). Conclusions Measurement of TMB is feasible in this AML epidemiologic cohort, and we observed important associations with AML risk factors, risk gene SM's, cytogenetic risk group, and driver GM's. We acknowledge the relatively small sample size and possibility of type II error, and therefore these observations require validation in a large prospective cohort which is planned. Figure 1 Figure 1. Disclosures Foran: OncLive: Honoraria; certara: Honoraria; actinium: Research Funding; boehringer ingelheim: Research Funding; novartis: Honoraria; abbvie: Research Funding; servier: Honoraria; taiho: Honoraria; pfizer: Honoraria; revolution medicine: Honoraria; gamida: Honoraria; takeda: Research Funding; sanofi aventis: Honoraria; trillium: Research Funding; syros: Honoraria; aptose: Research Funding; bms: Honoraria; kura: Research Funding; h3bioscience: Research Funding; aprea: Research Funding; sellas: Research Funding; stemline: Research Funding. Murthy: CRISPR Therapeutics: Research Funding. Finn: Jazz: Consultancy, Speakers Bureau; BMS: Consultancy, Speakers Bureau; BeiGene: Consultancy, Speakers Bureau; ADC Therapeutics: Consultancy, Speakers Bureau. Badar: Pfizer Hematology-Oncology: Membership on an entity's Board of Directors or advisory committees. Cerhan: Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; Genentech: Research Funding; NanoString: Research Funding; Regeneron Genetics Center: Other: Research Collaboration.