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Introduction: Primary diffuse large B-cell lymphoma (DLBCL) of the central nervous system (CNS), traditionally referred to as primary CNS lymphoma (PCNSL), is a rare type of primary large B-cell lymphoma of immune-privileged sites with significantly poorer prognosis than systemic DLBCL. Genetic profiles of PCNSL were widely studied, whereas the tumor microenvironment has not been well characterized. Patients and Methods: A series of molecular analyses were performed using DLBCL FFPE tissues collected by the International Lymphoma Consortium. First, multiplex fluorescent immunohistochemistry (mfIHC) using antibodies for CD20, PAX5, CD3, CD4, CD8, FOXP3, CD45RO, CD68, CD56, PD-1, PD-L1, PD-L2, and CTLA-4 was performed on PCNSL tissues from 121 immunocompetent patients and de novo systemic DLBCL tissues from 405 patients. Digital quantification results for 405 patients with EBV-negative systemic DLBCL or primary testicular (PT) DLBCL have been reported previously. The preliminary mfIHC results of PCNSL will be presented. Second, mfIHC for multiple B cell biomarkers, CD3, CD4, CD8, CD68, CD163, CD11c, and CD31 were performed for 10 PCNSL validation cases, 24 PT-DLBCL and 451 systemic DLBCL tissues (unpublished). Third, RNA samples were extracted and sequenced for the targeted 1408 cancer-associated genes, successfully in 142 PCNSL cases, including 102 cases evaluated by either of these two mfIHC panels and additional 40 PCNSL cases, Results: First, in the first large mfIHC cohort, PCNSLs compared with de novo systemic nodal or extranodal DLBCL had significantly higher mean/median CD56+ cell densities whereas lower T cell densities (consistent with the immune privilege), as well as lower CD45RO+, PD-1+, and FOXP3+ percentages in T cells whereas higher CD4¯CD8¯ double-negative percentages in T cells. Prognostic analysis in the PCNSL cohort showed that high CD56+ cell densities and high CD45RO+CD8+ T cell densities were associated with significantly poorer and better patient survival, respectively, which are opposite to their prognostic effects in systemic DLBCL as previously reported. Twelve patients had very high PD-L1 expression in B cells and significantly poorer survival in the PCNSL cohort. Second, as validation, the 10 PCNSL cases in the second mfIHC study showed significantly less T cells than systemic DLBCL and PT-DLBCL cases, and low CD8 T cell densities and having low percentage of CD8 T cells adjacent to tumor cells were associated with significantly poorer survival. Immunofluorescence landscapeand spatial analysisrevealed significant differences in immune privilege between PCNSL and PT-DLBCL. Third, gene expression profiling analysis by targeted RNA-seq identified 282 significantly differentially expressed genes between PCNSL and systemic DLBCL, referred to as the PCNSL signature. Unsupervised clustering analysis divided the PCNSL cohort into two clusters, which had no significant difference in MYD88 mutation frequencies analyzed at the mRNA level. Importantly, the cluster with higher expression of many neural glial genes in the PCNSL signature had significantly poorer survival, which remained significant in multivariate analysis adjusting for clinical factors and/or treatments, two PCNSL subcohorts (as training and validation cohorts), and methotrexate-treated patients. NCAM1 (Neural Cell Adhesion Molecule 1, encoding CD56) was among the upregulated PCNSL signature genes, explaining the poorer prognosis associated with higher CD56+ cell densities in PCNSL by the mfIHC analysis. Summary: Our studies represent the largest immunophenotypic and gene expression profiling studies currently in PCNSL, a rare type of primary DLBCL of immune-privileged sites. Multiplex immunofluorescence revealed the immune landscape in PCNSL in comparison with systemic and testicular DLBCL, and identified prognostic immune biomarkers. Targeted RNA-seq identified a PCNSL gene signature enriched with neuronal-glial genes and showing significant prognostic effect in PCNSL. These novel findings in the PCNSL microenvironment warrant further studies.

Background: Positron emission tomography (PET) scan is the imaging modality of choice for initial staging and response assessment of follicular lymphoma (FL). Quantitative parameters such as standardized uptake value (SUV) have been investigated as putative prognosticators in FL, with high baseline SUVmax predicting aggressive disease. To date, there is no data to guide treatment choices in patients (pts) with high SUVmax but with no documented evidence of histologic transformation (HT). Specifically, it remains unclear whether anthracycline-containing regimens, such as R-CHOP, are more beneficial than R-Bendamustine (BR) in these pts. Therefore, we aimed to compare the efficacy of frontline R-CHOP and BR in newly diagnosed FL pts based on the SUVmax at baseline PET (bPET). Patients and Methods: Pts with newly diagnosed, biopsy-proven FL1-2 and FL3A who had a bPET scan and who received either first-line R-CHOP or BR within 6 months of diagnosis between 2002 and 2022 were evaluated. Analysis was restricted to pts with age < 70 years to reduce confounding of age with treatment selection. Cohorts included were the FOLL12 (n=562, Luminari et al JCO 2022) and the R-chemotherapy arm of the RELEVANCE (n=216, Morschhauser et al NEJM 2018) clinical trials, the prospectively enrolled Molecular Epidemiology Resource (MER) and the Lymphoma Epidemiology of Outcomes (LEO) cohorts (n=288) and a retrospective cohort from 13 Australian centers (n=219). Choice of chemotherapy regimen was per treating physician. Maintenance was per protocol (FOLL12/RELEVANCE) or per treating physician (MER/LEO/Australia). Event-free survival (EFS) and overall survival (OS) were defined as time from treatment initiation to progression, relapse, retreatment or death; both were censored at 72 months due to varying follow-up across cohorts. SUVmax was grouped by tertile within each cohort to account for potential differences in SUVmax distributions and patient populations across cohorts. Kaplan Meier curves and multivariable Cox models cohort-stratified and adjusted for clinical factors (FLIPI, ECOG PS, age, grade 3A) were used to evaluate outcomes. Results: The median age at diagnosis was 57 years (IQR 49-64). 651 (51%) pts were treated with R-CHOP and 634 (49%) with BR. Within the study cohorts, there was a prevalence of cases receiving BR compared to R-CHOP in the Australian (90% vs 10%) and MER/LEO (68% vs 32%) cohorts, while the opposite was observed in the RELEVANCE (16% vs 84%) and FOLL12 (37% vs 63; p<0.001) trials. Pts receiving R-CHOP were slightly younger (median 56 vs 58 years, p=0.005), more frequently had grade 3A (17% vs 7%, p<0.001), elevated LDH (27% vs 22%, p=0.029), bulky disease > 7 cm (44% vs 37%, p=0.019), lower ECOG PS (PS >1 7% vs 13%, p<0.001), and higher rate of high risk FLIPI (37% vs 30%, p=0.005). Baseline SUVmax was slightly lower in R-CHOP (median 10.7, IQR 7.9-14.9) vs BR (median 11.0, IQR 8.2-14.2) treated pts (p=0.0045). At a median follow-up of 56 months (range, 1-72 months), 415 pts (32%) had an event and 103 (8%) died. Higher SUVmax was not associated with EFS (middle tertile HR=0.96, 95% CI 0.76-1.22; upper tertile HR=0.86, 95% CI 0.68-1.09; p=0.45) or OS (middle tertile HR=1.28, 95% CI 0.80-2.05; upper tertile HR=0.97, 95% CI 0.59-1.59; p=0.44) in multivariable models stratified on cohort and adjusted for treatment and clinical factors. We then compared outcomes by treatment within tertiles of SUVmax. In multivariable models, R-CHOP had modestly inferior EFS to BR in low (HR=1.27, 95% CI 0.84-1.93) and middle tertiles (HR=1.49, 95% CI 0.99-2.25), and modestly superior OS to BR in low (HR=0.59, 95% CI 0.23-1.47) and middle (HR=0.79, 95% CI 0.37-1.71) tertiles. Both EFS (HR=1.06, 95% CI 0.71-1.58) and OS (HR=1.02, 95% CI 0.45-2.30) for R-CHOP were similar to BR in the highest tertile. No comparisons identified a statistically significant benefit for either therapy in multivariable models when evaluating SUVmax tertile subsets. Conclusions: In this large multicenter study of newly diagnosed FL pts with bPET who received frontline immunochemotherapy, higher baseline SUVmax was not associated with inferior outcomes after adjusting for treatment and clinical factors. Within the caveats of retrospective studies and confounding of treatment selection, these data provide no clear insights for SUVmax-based therapy selection in first-line follicular lymphoma pts treated with immunochemotherapy.

Background: The Optimized Hemophagocytic Lymphohistiocytosis (HLH) Inflammatory (OHI, Zoref-Lorenz et al, Blood, 2022) index, defined by the combined elevation in serum soluble CD25 (sCD25) and ferritin, has emerged as a promising prognostic tool for patients with newly diagnosed hematologic malignancies, demonstrating superior performance in predicting 500-day mortality compared to HLH-2004 criteria. However, previous studies were retrospective, with a substantial proportion (65%) of patients suspected clinically to have HLH. We evaluated the performance of the OHI index in an unselected, prospective cohort of newly diagnosed diffuse large B-cell lymphoma (DLBCL) patients. Methods: We analyzed the predictive utility of the OHI index in 331 newly diagnosed DLBCL patients enrolled from 2002-2015 in the prospective Iowa/Mayo Molecular Epidemiology Resource cohort. Ferritin and sCD25 levels were quantified in pre-treatment serum samples using R&D ELISA kits. OHI values were also optimized based on 500-day mortality in the cohort using receiver operating curve analysis with internal validation. Patients were classified as OHI+ using the original and newly optimized thresholds for sCD25 and ferritin. The primary endpoint was 500-day survival, and the secondary endpoints were event-free survival (EFS) at 24 months (EFS24), EFS, and overall survival (OS). The predictive capability of the OHI index was evaluated using logistic regression to determine odds ratios (OR) and 95% confidence intervals (CI) for 500-day mortality and EFS24, as well as Cox regression to calculate hazard ratios (HR) and 95% CIs for EFS and OS. Results: The median age at diagnosis of the 331 patients was 63.5 years (interquartile range, 54.5-74), and 168 (51%) were male. Using the original thresholds (sCD25 3,900 U/mL and ferritin 1,000 ng/mL), 4.2% of patients were OHI+, with a more than 5-fold higher 500-day mortality risk compared to OHI- patients (OR=5.6; CI 1.6-17, p<0.001). After optimizing thresholds for sCD25 (2,400 U/mL) and ferritin (250 ng/mL) to predict 500-day mortality, 23.6% were OHI+ and the OHI+ group had a 9-fold higher 500-day mortality risk (OR=9.2; CI 4.0-24, p<0.001), with 31% mortality in the OHI+ vs 5% in the OHI- group. OHI+ patients exhibited more B-symptoms (35% vs 20%, p=0.027), elevated LDH levels (76% vs 34%, p<0.001), poorer performance status (Eastern Cooperative Oncology Group 2+: 38% vs 12%, p<0.001), and more advanced stage disease (Stage IV: 57% vs 38%, p<0.001), although the frequency of a high International Prognostic Index (IPI) was not statistically different between the groups (IPI 3-5: 44% vs 36%, p=0.28). After adjusting for age and IPI, OHI+ remained a strong predictor of 500-day mortality (OR=5.0; CI 1.9-13, p=0.001). Further adjustment for the cell of origin did not impact the results. The association of OHI+ status with 500-day mortality was similar in IPI 0-2 (OR=5.8; CI 1.2-29, p=0.033) and 3-5 (OR=6.8; CI 0.6-73, p=0.11). OHI+ patients were also more likely to not achieve EFS24 (45% vs 13%), with a 3-fold greater risk after adjusting for age and IPI (OR=3.2; CI 1.5-6.5, p=0.0018). The OHI index also retained its predictive ability over longer-term follow-up (median 9.8 years for living patients) for both OS (HR=2.0; CI 1.0-4.0, p=0.040) and EFS (HR=2.2; CI 1.1-4.3, p=0.030) after adjusting for age and IPI. Cytokine profiling using multiplex ELISA identified elevated inflammatory markers in OHI+ patients, underscoring the role of systemic inflammation in prognosis. The distribution of cytokines was significantly different between the groups, with consistently higher means in the OHI+ vs OHI- group, including IL1a (1,628 vs 759 pg/ml, p=0.008), CCL2 (1,020 vs 724 pg/ml, p=0.028), CXCL10 (165 vs 53 pg/ml, p<0.0001), and CXCL9 (380 vs 150 pg/ml, p<0.0001). Conclusions: While the original OHI index for prediction of 500-day mortality was validated in this unselected cohort of newly diagnosed DLBCL patients, optimization of the OHI thresholds identified a larger OHI+ group (24%), enhanced the identification of hyperinflammation, improved predictive ability for early (500-day) mortality, and predicted EFS24 status and long-term OS. This underscores the clinical relevance of the OHI index, supports the need to evaluate disease-specific thresholds, and suggests its potential for use in routine management and as enrollment criteria in clinical trials for novel therapies.

Background: Indolent non-Hodgkin lymphomas (iNHL) are incurable and disproportionately affect adults age >65 in whom frailty and functional impairment can impact disease management. The Vulnerable Elders Survey (VES-13) is a 13-item screening tool that incorporates age, self-rated health, physical function limitations, and functional disabilities to identify vulnerable older community-dwelling adults. Adults with a VES-13 score of >3 have a fourfold increased risk of death or functional decline over 2 years as compared to adults with a score <3 (Saliba et al, JAGS 2001). Our team previously showed that VES-13 >3 was associated with a higher risk of 1-year mortality in NHL (OR 3.26, 95% CI 2.15-4.96, Fama et al, ASH 2019), including in adults age <65. In this study, we determined whether VES-13 scores >3 were associated with quality of life (QOL) changes in adults with iNHL across the age spectrum. Methods: We used the Lymphoma Epidemiology of Outcomes (LEO) Cohort Study to identify adults enrolled from 2015-2020 with grade 1-3A follicular and marginal zone lymphoma (FL, MZL) who completed the VES-13 at enrollment and QOL surveys at enrollment and follow-up. The LEO Cohort Study enrolls participants within 6 months of diagnosis and collects information on disease status, QOL, health behaviors, and patient-reported functional assessment. For this analysis we included QOL measured using the Functional Assessment of Cancer Therapy-General (FACT-G) at years 1 and 2 post-enrollment. The FACT-G total score was the sum of 4 subscales (range): physical (PWB, 0-28), social/family (SFWB, 0-28), emotional (EWB, 0-24), and functional (FWB, 0-28) well-being. A higher FACT-G total score (range 0-108) indicated better overall QOL. VES-13 scores ranged from 0 (lowest risk for death or decline) to 10+ (highest risk). Generalized linear mixed models evaluated changes in QOL from baseline based on VES-13 score >3 (vulnerable) vs <3 (non-vulnerable), within groups by age at enrollment >65 and <65. Results: Our study included 1,186 participants: 42% age >65, 54% female, 84% non-Hispanic White, 10% Hispanic, 3.3% Black, and 1.4% Asian/Pacific Islander. Most (68%) were diagnosed with FL. FLIPI was high risk for 20%, and MALT-IPI was high risk for 23%. In the VES-13 <3 group, the mean (SD) baseline FACT-G total score was 86.5 (12.0), PWB 21.0 (3.5), SFWB 24.3 (4.3), EWB 18.8 (3.7), and FWB 22.3 (4.9). In the VES-13 >3 group, the mean (SD) baseline FACT-G total score was 70.4 (16.5), PWB 15.4 (5.6), SFWB 22.3 (5.5), EWB 17.5 (4.5), and FWB 15.3 (6.4); all significantly lower than the VES-13 >3 group (all p<0.01). In adults <65, 63 (9%) had a VES-13 >3, which was associated with a significant improvement from baseline in PWB at years 1 and 2 when compared to VES-13 <3 (changes in baseline PWB were 2.1, 2.9 for VES-13 >3 vs 0.2, 0.1 for VES-13 <3, all p<0.05). Similarly, we observed improvement in FWB from baseline at years 1 and 2 in the VES-13 >3 vs <3 group (2.4, 2.9 vs 0.4, -0.1, respectively all p<0.05). The VES-13 >3 group had a decline in their EWB at 1 year vs the VES <3 group (-0.5 vs 1.2, respectively, p=0.003). At year 2, total FACT-G improved from baseline in the VES-13 >3 group (5.6 for VES-13 >3 vs -0.5 for VES-13 <3, p=0.002). SFWB changes from baseline did not differ between groups. In adults >65, 83 (17%) had a VES-13 >3, which was associated with a significant improvement from baseline PWB (1.3, 1.5 for VES-13 >3 vs. 0.1, -0.1 for VES-13 <3), FWB (3.3, 2.2 for VES-13 >3 vs. 0.5, 0.1 for VES-13 <3), and total FACT-G score (5.2, 3.4 for VES-13 >3 vs. 1.0, -0.4 for VES-13 <3) when compared to VES-13 <3 at years 1 and 2 (all p<0.05). SFWB and EWB changes from baseline did not differ between groups. While there was improvement from baseline PWB and FWB in the VES-13 >3 group, QOL scores across all subscales remained below the VES-13 <3 group in the study period for both age groups. Statistical significance was maintained in models adjusted for baseline characteristics, including initial treatment strategy (observation, systemic, vs local) for both age groups. Conclusion: Although the vulnerable group reported worse QOL throughout the study period compared to the non-vulnerable group, survivors in the vulnerable group saw greater improvement in their physical and functional well-being at 1- and 2-years post-diagnosis. Additional analyses are underway to identify drivers of improvement in physical and functional well-being in vulnerable adults diagnosed with iNHL.

Background: Hypomethylating agent (HMA) and venetoclax (VEN) therapy is a standard of care frontline treatment of acute myeloid leukemia (AML) amongst patients (pts) ineligible for intensive therapy. Despite its convenient flat dose, oral nature, and static excretion irrespective of body weight (wt), VEN has a large, variable volume of distribution and extensive protein binding (Yang, Molecules, 2022). Body mass index (BMI) is a more accurate, albeit imperfect, indicator of body fat that has not been evaluated as an independent predictor of differential VEN exposures and clinical outcomes. We sought to evaluate this possibility amongst pts treated with frontline HMA+VEN in a multi-center, real-world, retrospective study. Methods: We conducted a multi-center, retrospective study through four US academic centers in the Consortium on Myeloid Malignancies and Neoplastic Diseases (COMMAND). 368 pts treated with frontline HMA+VEN from 6/2016-8/2023were evaluated based on BMI within 30 days of induction. Responses were defined by European LeukemiaNet (ELN) 2022 criteria. Pearson's chi-squared test and Wilcoxon rank-sum test were used for comparison between groups. The Kaplan-Meier method and multivariable Cox regression model were applied to overall survival (OS). Continuous variables were summarized as a median with interquartile range (IQR), and categorical variables were reported as a frequency (percentage). Results: The median age was 75 (IQR: 70-79) years, 58% were male, and 76% were white. 107 (29%) had a normal BMI of 18-25 kg/m2, 141 (38%) were overweight (BMI 25-30 kg/m2), and 120 (33%) were obese (BMI >30 kg/m2). There were no significant differences in baseline pt-, disease-, and treatment-specific factors when comparing pts with normal wt to BMI >25.The cohort was enriched for complex karyotype and TP53-mutated disease (27% and 32%, respectively), with 73% categorized as adverse risk by ELN 2022. There was no difference in 30-, 60-, and 90-day mortality rates (6-8%, 14-18%, 19-29%, respectively) by BMI group. Complete remission (CR/CRi) rate was 50% overall and was not impacted by BMI (41%, normal wt; 55%, overweight; 52%, obese) (p=0.10). Overall response rate (ORR) (CR/CRi/MLFS) was 59% overall and differed by BMI groups (50%, normal wt; 66%, overweight; 58%, obese) (p= 0.047). The median OS was 6.6 months for normal wt, 13.7 months for overweight, and 8.3 months for obese pts, and not significantly different when comparing normal to overweight (p=0.052) or obese pts (p=0.756). In multivariable analysis, the effect of BMI varied by the composite remission rate used. Overweight was borderline significantly associated with higher likelihood of achieving CR compared to normal wt (odds ratio [OR] 1.98, 95% confidence interval [CI] 0.99-4.03; p=.056), whereas obesity was not (OR 1.78, CI 0.86-3.74; p=.13). Other co-variates with a significant association with achieving CR included diagnosis of secondary AML (sAML) (OR 0.37, CI 0.18-0.74; p=.006) and presence of IDH (OR 2.81, CI 1.30-6.15; p=.009), ASXL (OR 0.39, CI 0.15-0.96; p=.046), TET2 (OR 2.43, CI 1.17-5.09; p=.02), and DNMT3A (OR 2.37, CI 1.19-4.78; p=.02) mutations. There was a trend towards higher likelihood of achieving CR/CRi for both overweight (OR 1.74, CI 0.92-3.32; p=.09) and obese pts (OR 1.88, CI 0.96-3.74; p=.07). Diagnosis of sAML and presence of TET2, ASXL, and DNMT3A mutations no longer had a significant association with achieving CR/CRi, while IDH mutations maintained an association (p=.01). None of these variables demonstrated a significant impact on ORR (inclusive of MLFS) except overweight (OR: 1.99, CI 1.06-3.80; p=.03) and sAML vs de novo (OR: 0.53, CI 0.29-0.99; p=.047). In multivariable logistic regression, higher ECOG score was associated with risk of early mortality within 60 (p=.01) and 90 (p=.01) days, but not 30 days. sAML vs de novo associated with higher 90-day mortality, presence of NPM and TP53 mutation associated with higher 30-day mortality, and cytogenetic risk associated with higher 60- and 90-day mortality. Conclusions: This multi-center, real-world study demonstrates that BMI may not have a linear effect on response to frontline HMA+VEN, with some indication of negative impact at both lower and higher BMI categories. However, additional dedicated studies are needed to determine if differences in BMI is associated with altered drug exposure as an explanation for these differences.

Background: FL3B is the least common among FL subtypes, accounting for 5-10% of cases. Almost half of FL3B tumors have concurrent diffuse large B cell lymphoma (DLBCL) in the diagnostic tissue biopsy, while FL3B rarely coexists with FL1-2 or FL3A. Several lines of evidence suggest that FL3B displays distinct biological and clinical characteristics resembling aggressive DLBCL rather than the indolent FL1-3A. Accordingly, DLBCL anthracycline-containing regimens, such as R-CHOP, are the mainstay of therapy for FL3B with or without coexisting DLBCL. However, while some studies show that R-CHOP therapy in FL3B was associated with 5-year overall survival (OS) rate of 54%, others report outcomes comparable to FL3A with 79-90% survival. Additional controversy involves the clinical implication of pure FL3B (FL3Bp) vs FL3B with concurrent DLBCL (FL3Bc). Thus, it remains unclear if FL3B clinically resembles DLBCL or lower-grade FL and whether FL3Bp has a different prognosis from FL3Bc. To address these questions, we performed a pooled study of two large prospective multicenter study cohorts to compare the clinical characteristics and outcomes of newly diagnosed FL3B with FL1-2, FL3A and DLBCL patients, all of whom were uniformly treated with frontline R-CHOP. Patients and Methods: Weevaluated 469 newly diagnosed patients with FL1-2 (n=216), FL3A (n=170) and FL3B (n=83) who received R-CHOP within 6 months of diagnosis and 739 de novo DLBCL (GCB n=455 and non-GCB n=284) who were prospectively enrolled into the Molecular Epidemiology Resource (MER) and the Lymphoma Epidemiology of Outcomes (LEO) cohorts between 2002 and 2021. FL3B cases were designated as FL3Bc and FL3Bp based on the presence or absence of coexisting DLBCL, respectively. Histologic diagnosis was determined by an expert pathologist at each participating center and centrally reviewed. Event free survival (EFS) and OS were defined as time from diagnosis to progression, relapse, retreatment or death, and early progression defined as failing to achieve EFS at 24 months (EFS24). Associations between clinical features and EFS or OS were evaluated using Kaplan Meier curves and Cox proportional hazards models unadjusted and adjusted for age and FLIPI (comparisons with FL1-2 and FL3A) or IPI (comparisons with DLBCL). Results: The median age was 61 years (range, 18-94 years). Among FL3B patients, 21 (25%) had FL3Bc and 62 (75%) FL3Bp. Baseline characteristics and outcomes were broadly similar between the two FL3B subtypes. We then compared all FL3B patients to those with lower-grade FL. Patients with FL3B showed similar clinical features to those with FL1-2 and FL3A, with exception for a lower tumor burden. After R-CHOP, FL1-2 patients had an inferior EFS (HR 2.13 95%CI 1.31-3.46) than those with FL3B, whereas there was no difference compared to FL3A. OS was similar across all FL grades. Although FL1-2 patients failed to achieve EFS24 more frequently than FL3B and FL3A (34% vs 18% and 15%, p<0.001), FL3B patients who did fail EFS24 had almost three folds higher risk of subsequent mortality (HR 2.84 95%CI 1.35-6.01) than other FLs. At 5-year follow-up, FL3B patients had twice the risk of relapse with an aggressive subtype (i.e., DLBCL, high-grade B-cell lymphoma) than those with FL1-2 and FL3A, who instead often recurred with indolent disease (i.e., FL1-2, FL3A; p<0.001). We further compared FL3B patients to those with DLBCL classified based on cell-of-origin into GCB and non-GCB subtypes. At diagnosis, patients with FL3B had more favorable clinical features than those with GCB and non-GCB DLBCL. Compared to FL3B, patients with non-GCB DLBCL had an inferior EFS (HR 1.73 95%CI 1.07-2.79) and OS (HR 2.04 95%CI 1.11-3.75), while those with GCB DLBCL did not show a significant difference in EFS (HR 1.41 95%CI 0.88-2.25) or OS (HR 1.69, 95%CI 0.93-3.06) likely due to insufficient statistical power. Patients with FL3B failed EFS24 less frequently than patients with GCB or non-GCB DLBCL (17% vs 25% and 32%; p=0.01). Among patients who failed EFS24, those with FL3B had a similar subsequent OS as both GCB (HR 1.41 95%CI 0.73-2.72) and non-GCB DLBCL (HR 1.27 95%CI 0.65-2.47). Conclusions: We report that FL3Bp and FL3Bc appear clinically similar. While most FL3B patients have a prognosis comparable to FL1-2 and FL3A, 18% exhibit aggressive behavior with poor outcome reminiscent of DLBCL. Future studies with a larger population will be needed to confirm our findings.

Background: Anaplastic large cell lymphomas (ALCLs) represent a heterogeneous group of T-cell lymphomas that currently are classified by the presence or absence of ALK tyrosine kinase (TK) fusion genes (ALK+ or ALK−) and clinical presentation (systemic, cutaneous, or breast implant-associated). Two overarching molecular types of ALCL recently were discovered, defined by the presence (Type I) or absence (Type II) of a gene expression signature highly enriched for JAK-STAT3 activation. Fusions involving non-ALK TK genes occur in some ALK− cases, but the fusion landscape of ALCL remains incompletely characterized. Methods: Expert consensus pathology review was conducted in the Lymphoma/Leukemia Molecular Profiling Project (LLMPP). RNAseq was performed and fusions were identified using FusionCatcher. Here, we focused on recurrent in-frame coding fusions. Previously unreported fusions were validated by RT-PCR. Type I/II was assigned using a previously validated gene expression-based model. Genes with adjusted (adj) P<0.05 were considered differentially expressed. Overall survival (OS) was assessed for systemic ALCL, when available. Results: We evaluated 379 ALCLs (229M/150F; mean age, 56 y). Of 199 candidate fusions (excluding reciprocal events), 28 were recurrent and passed quality metrics. At least 1 of these 28 fusions was present in 150 cases (40%). ALK fusions were present in 106 ALK+ ALCLs (all Type I; P<0.0001). Of these, NPM1::ALK was seen in 68/106 (64%). Alternate partners (X::ALK) included ATIC (N=24) and CTLC, COL1A2, MSN, MYH9, RNF213, SATB1, TFH, TPM3, and TRAF1 (1-3 cases each). X::ALK was associated with older age (mean, 52 y) than NPM1::ALK (32 y; P<0.0001) and showed relative overexpression of 49 genes, including multiple activators of small GTPases such as CGNL1 (FC, 5.6; Padj=2.4×10-6), SRGAP1, ALS2, DOCK1, and NCKAP1. ALK expression was similar in cases with NPM1::ALK and X::ALK and there was no significant difference in OS. Non-ALK TK fusions were seen in 17/273 ALK− cases (6%), including TYK2 (N=9); JAK2 (N=6); and ROS1 (N=2). All were Type I ALCLs (P<0.0001). ALK− cases with non-ALK TK fusions overexpressed 38 genes compared to ALK− cases without TK fusions, including cytokines involved in the IL17 signaling pathway such as CXCL6 (FC, 12.5; Padj=4.2×10-3), CXCL1, and CSF3. We then assessed the relationship between ALK− cases with non-ALK TK fusions and ALK+ cases by separately comparing each subset to ALK− cases without TK fusions. FC values for ALK− cases with non-ALK TK fusions were significantly correlated with FC values for ALK+ ALCLs over the set of expressed genes (R=0.54; P<0.0001). At a median follow-up of 32 months, 0/4 systemic ALCL patients with non-ALK TK fusions had died, while 30% of those with ALK− ALCL without TK fusions had died, but this was not statistically significant (P=0.26). The other 13 ALK− cases with non-ALK TK fusions were either localized ALCLs or did not have outcome data available. Of 20 TP63 fusions, 17 (85%) were TBL1XR1::TP63 and 3 were X::TP63. As previously reported, TP63 fusions were associated with poor OS (median OS, 10 months; not reached for other ALK− ALCLs; P=0.007). Four ALCLs had a novel NCL::UBTF fusion involving genes encoding the nucleolar proteins nucleolin and nucleolar (upstream binding) transcription factor-1. Four cases each had PARG::BMS1 and TNK1::GPS2 (the latter seen only in Type I ALCLs). Conclusions: This large consortium-based analysis of coding fusions further elucidates the molecular distinction between Type I and Type II ALCLs. Both ALK and non-ALK TK fusions were seen exclusively in Type I ALCLs, which we have shown previously are enriched for JAK-STAT3 pathway genes and correlate strongly with pSTAT3Y705 positivity by immunohistochemistry. These fusions were not identified in Type II ALCLs, which previous data suggest are associated with epigenetic alterations. ALK+ ALCLs with NPM1::ALK and X::ALK showed differences in gene expression, suggesting biological differences. Furthermore, ALCLs with non-ALK TK fusions shared gene expression features with ALK+ ALCL. Clinical fusion detection could enhance molecular classification of Type I and Type II ALCLs and may guide precision therapy.

Background: A donor search prognosis score based on HLA type and race/ethnicity can classify patients into 3 groups based on the likelihood of finding an HLA-matched (8/8) unrelated donor (MUD): Very Likely (44% of the population), Likely (41%) and Very Unlikely (15%). Previous studies showed that >90% of Very Likely, 26% of Likely and <10% of Very Unlikely patients used a MUD for their hematopoietic cell transplants (HCT), with the rest using other donor sources (mismatched unrelated donor, cord blood, or haploidentical relative). For some patients, prolonged efforts to identify a MUD might be futile and delay HCT, leading to increased morbidity, greater chance for relapse and disease resistance, and worse HCT outcomes. BMT CTN 1702 (NCT03904134) was the first national study to track the entire donor search identification process. Designed as a biologic assignment study, the goal was to estimate and compare overall survival between two arms: patients who are Very Likely to find a MUD versus those who are Very Unlikely to find a MUD. It tested whether provision of a donor search prognosis score to centers could prevent prolonged futile searches for the Very Unlikely group and improve their transplant rates and outcomes, compared to the Very Likely group. Methods: Eligible diagnoses included acute leukemia, myelodysplastic syndromes, lymphoma, acquired aplastic anemia and sickle cell disease. Patients could be consented at any time after diagnosis until an unrelated donor search was started. Consented patients became evaluable only after it was determined that no appropriate HLA-identical siblings were available. The primary endpoint was survival time after the patient was declared evaluable, regardless of whether HCT occurred, and was compared between the Very Unlikely and Very Likely groups. The target enrollment was 1732 evaluable patients. Because this was a biologic assignment trial and not a randomized trial, formal comparisons of overall survival between the Very Likely and Very Unlikely groups were done using a covariate-adjusted Cox proportional hazards model. The following covariates were a priori specified for adjustment in the model, according to the statistical analysis plan: sex, age, Karnofsky Performance Score (KPS), race/ethnicity, disease, disease status, and interval from consent to evaluability. Results: 1751 evaluable patients were enrolled at 47 centers: 44% female, median age 59.4 years (range 0.6-81.3 years), 73% were non-Hispanic White, 10% Hispanic White, 8% Black, 5% Asian/Native Hawaiian/Pacific Islander, 0.5% American Indian/Alaska Native. Among the evaluable patients, 1181 received a HCT, 827 died, and 924 are still alive with or without HCT, with a median of 25 months of follow up (range=6-54 months [mos], inter-quartile range [IQR]=25-34 mos). The distribution was: 958 Very Likely, 517 Less Likely, and 276 Very Unlikely. Individuals in the Very Unlikely group were younger and were less likely to be non-Hispanic White. The unadjusted cumulative incidences of undergoing HCT by 6 mos and 2 years [yrs], in the Very Unlikely group were 51% and 61% vs. 60% and 69% in the Very Likely Group; after adjustment, there was not a significant difference in the likelihood of undergoing HCT (Dehn et al, submitted). There was no difference in median time from evaluability to HCT: 3.4 mos Very Unlikely and 3.3 mos Very Likely. Unadjusted survival rates from the time of evaluability for the Very Unlikely and the Very Likely groups were: 6 mos (85% vs 84%), 1 yr (69% vs. 69%) and 2 yrs (55% vs. 56%). In the multivariate Cox model, there was no significant difference in the risk of death (HR = 1.07 for Very Unlikely vs. Very Likely, 95% confidence interval 0.86-1.33, p=0.56) adjusting for significant clinical covariates: age, KPS, disease status, and time from consent to evaluability were all significantly associated with overall survival. There was no significant center effect and no interaction between donor search prognosis group and clinical covariates. Conclusion: In this large multicenter BMT CTN study, using the donor selection strategy described, there was no difference in adjusted time to HCT or survival for patients Very Likely versus Very Unlikely to find an 8/8 MUD. These results suggest that patients Very Unlikely to identify a MUD should proceed to HCT using the best available alternative donor rather than delaying HCT to try to identify a MUD.

Introduction: Acute myeloid leukemia (AML) has been considered by many to be an oncologic emergency often leading to hospital admission for expeditious evaluation and treatment. Previous studies reported that time from diagnosis to treatment (TDT) does not impact outcomes (Sekeres, Blood, 2009), (Bertoli, Blood, 2013), (Rollig, Blood, 2020), however these analyses were restricted to intensively treated and/or non-United States (US) patients (pts). We report on a multi-center, retrospective analysis of TDT in adults with newly diagnosed AML receiving Hypomethylating agent (HMA) + venetoclax (Ven) using real-world data from the COMMAND. Methods: Eight US academic medical centers with AML expertise performed a review of adult pts within their center treated with HMA+Ven for newly diagnosed AML. TDT was defined as days from diagnosis of AML to initiation of treatment with HMA+Ven. Cytoreduction with hydroxyurea or leukapheresis was included to control for the effects of severity of presentation on TDT. The primary outcome was impact of TDT on overall survival (OS) (defined as date of diagnosis to date of death). TDT was treated continuously for time-to-event analyses. Secondary outcomes included measurable residual disease (MRD) by flow cytometric analysis (sensitivity <0.1%), complete response (CR), complete response with incomplete count recovery (CRi), defined by European LeukemiaNet (ELN) 2022 Guidelines (Dohner, Blood,2022), and early mortality (death within 30 and 60 days of initiation of HMA+Ven). Pre-planned subgroup analyses included those based on disease biology (FLT3 ITD, IDH1/2, TP53 mutation, ELN 2022 risk), HMA used (azacitidine vs decitabine) and age (<75 vs ≥75 years). For those analyses where TDT was significant in univariable analysis (P=0.1), multivariable analysis was conducted controlling for the following: ECOG performance status (PS), age, receipt of cytoreduction, ELN 2022 risk, and presence of individual pathogenic variants detected on broad myeloid gene next generation sequencing panels used at each institution. All analyses were conducted by a central statistician using RStudio statistical package. Results: 488 pts were included in the analysis. Median age was 76 (interquartile range: 70-80) and the majority of pts had an ECOG PS of 0 or 1 (56%). Most pts (67.6%) had adverse risk with 9.4% and 18.6% of pts having favorable and intermediate risk disease by ELN 2022, respectfully. The most common mutations identified were TP53 (27.5%), IDH1/2 (19.3%), NPM1 (16.4%), DNMT3A (16.8%), ASXL1 (15.4%), and FLT3-ITD (13.7%). Twenty-eight percent of pts received cytoreduction prior to initiation of HMA+Ven. Azacitidine+Ven was the most common regimen utilized (53.9%). Median number of cycles of HMA+Ven was 3 (IQR: 1-6). MRD (-) CR, MRD (+) CR, and CRi was achieved in 21.5%, 10.5%, and 16.4% of pts after one cycle of HMA+Ven. Median OS for the cohort was 10.4 months (95% CI: 9.4-12.6). Median TDT for the cohort was 9 days (IQR: 5-17). In univariate Cox model, longer TDT was associated with improved OS (HR: 0.989, 95% CI: 0.981 to 0.998; p = 0.013). In multivariable analysis, longer TDT was still associated with improved OS (HR: 0.987; 95% CI: 0.973-0.999; p=0.049). TDT and presence of bZIP in-frame CEBPA mutations were the only factors associated with improved OS, while ECOG PS of 2 or 3-4, when compared to ECOG PS=0 (p=0.035 and 0.0002, respectively) and therapy-related AML (p=0.002), were associated with worse OS. Notably, ELN 2022 risk and IDH1/2 or NPM1 mutation status did not impact OS. Discussion: In this real-world, multi-center, US-based analysis of pts with newly diagnosed AML treated with HMA+Ven we show that longer TDT is associated with improved OS even when controlling for severity of presentation, ELN 2022 risk score, ECOG PS, and age. This finding is consistent with data in pts treated with 7+3. Similar to results published in an electronic medical record-based analysis out of Germany (Baden, Haemotologica, 2024) in pts treated with lower-intensity Ven regimens, our results show that pts with newly diagnosed AML eventually treated with HMA+Ven are best served with a complete appraisal of disease biology and treatment planning before initiation of induction therapy. Given the consistent negative impact of ECOG PS and the findings of our study, future consideration for potential patient optimization strategies to improve ECOG PS prior to therapy initiation are warranted.

Background. Study of myeloid neoplasms (MN) has been rapidly transformed by genome characterization. Gene mutations have been reported to influence disease phenotype and risk of disease progression, and the evaluation of mutational status can provide valuable insights to improve the decision-making process. In this international study, we evaluated the clinical impact of mutational screening in patients with CMML, which is characterized by significant clinical and genomic heterogeneity, including a substantial proportion of patients with poor outcomes and unmet needs. Currently, only limited molecular information has been incorporated into CMML classification and prognostication. Methods. We retrospectively collected 3182 CMML patients. We used MOSAIC, an AI-based framework for multimodal analysis in rare cancers (PMID: 38875514) to develop innovative, molecular-based tools for classification and prognostication. An independent validation of the results on 516 prospectively collected patients was performed. Results. Bayesian Networs and Hierarchical Dirichlet Processes were used to identify genomic associations and define a CMML molecular classification. We identified 11 clusters with distinct clinical and genomic features, including splicing machinery, signal transduction and tyrosine kinase pathways aberrations, and high-risk molecular signatures (i.e., AML-like and TP53 mutations). Up to 15% of patients showed clear genomic overlap with other MN. Importantly, extensive multi-color flow cytometry on T lymphocytes, NK and myeloid cells (BD FACSymphony A5 Cell Analyzer) revealed specific immunologic and inflammation signatures associated with molecular subgroups. We then integrated molecular and clinical information to build an international CMML Prognostic Scoring System (iCPSS). We assessed the performance of different statistical and AI-based methods; L1-penalized Cox Model resulted as the best performing method. Selected features included hematological parameters (WBC, Hb, PLT and marrow blasts), cytogenetic abnormalities, and mutations in 10 genes (ASXL1, DNMT3A, EZH2, NRAS, RUNX1, SETBP1, STAG2, TET2, TP53, U2AF1). By Bayesian thresholds optimization, we identified 5 risk classes (i.e., very-low, low, intermediate, high and very-high) with median overall survival (OS) ranging from 99 to 9 months (P<.001), and median leukemia-free survival (LFS) ranging from 210 to 18 months (P<.001). iCPSS provided better patient discrimination across all clinical endpoints compared to currently available prognostic tools, with a Concordance Index (CI) for OS of 0.75 versus 0.62-0.64, respectively. Notably, compared to available scoring systems, up to 40% of patients were reassigned to higher or lower risk classes by the iCPSS. External validation on an independent prospective cohort confirmed that the performance of iCPSS is superior to existing prognostic models (CI for OS 0.71 vs 0.54-0.61, respectively) To demonstrate the clinical utility of iCPSS, we focused on 753 patients who underwent allogeneic stem cell transplantation (HSCT). In multivariable analysis, iCPSS stratified the probability of OS post-HSCT (P<.001) and identified groups of patients with different probabilities of disease relapse, ranging from 9% to 62% (P<.001). We employed a clinical- and genomic-based decision support system (PMID: 38723212) to determine the optimal timing of HSCT. Preliminary analyses indicated that higher-risk patients according to iCPSS (i.e., intermediate, high, and very high) benefit from an immediate HSCT strategy. Lower-risk patients (i.e., very low and low) had life expectancy maximized with delayed HSCT. Modeling decision analysis using iCPSS compared to conventional scores, resulted in a change in transplantation policy for a significant proportion of patients (up to 25%). Conclusion. Molecular information significantly improves the classification of CMML patients, providing a basis for refining diagnostic boundaries with other MN and for a more rational inclusion of patients in clinical trials. The iCPSS demonstrated superior performance over currently available scoring systems and improved HSCT decision making process.