Citations

Abstract Objective We hypothesized that a set of immunohistochemistry (IHC) stains could be used to distinguish Burkitt lymphoma (BL), the quintessential B-cell lymphoma with a germinal center B-cell (GCB) dark zone (DZ) expression signature, from diffuse large B-cell lymphoma, not otherwise specified (DLBCL, NOS). This might also be applicable to high-grade B-cell lymphomas (HGBCLs) with MYC and BCL2 rearrangements (double-hit lymphomas [DHLs]) and triple-hit lymphomas (THLs). Methods A 5-marker IHC algorithm was designed from gene lists that distinguish physiologic DZ from light zone GCBs. Results In training and validation cohorts, we distinguished BL from DLBCL, NOS with high sensitivity and specificity. Because DHLs/THLs are enriched for the gene expression DZ signature (DZsig), we evaluated 19 DHLs/THLs and 4 HGBCLs, NOS. Most (83%) cases were IHC DZ. The NanoString DLBCL90 assay was performed on 34 cases to correlate IHC DZ results with the molecular DZsig. The IHC DZ call was significantly associated with the DZsig (P = .0011). The sensitivity and specificity of IHC to recognize DZsig+ cases among DLBCL, NOS and DHLs with BCL2 rearrangements/THLs were 91% and 100%, respectively. Conclusions The IHC DZ algorithm can support a diagnosis of BL and identifies MYC-BCL2 DHLs/THLs with a molecular DZsig.

Abstract Background and Aims Truncating variants in the TTN gene (TTNtv) are the most common genetic cause of dilated cardiomyopathy (DCM) but also occur as incidental findings in the general population. This study investigated factors associated with the clinical manifestation of TTNtv. Methods An international multicentre retrospective observational study was performed in families with TTNtv-related DCM. Shared frailty models were used to estimate associations of variant characteristics with lifetime risk of DCM, and logistic regression to estimate odds ratios (ORs) for individual-level clinical risk factor profiles (cardiac conditions, cardiovascular comorbidities, lifestyle) and DCM. Results A total of 3158 subjects in 1043 families with TTNtv-related DCM were studied. TTNtv-positive subjects were 21-fold more likely to develop DCM [OR, 21.21; 95% confidence interval (CI), 14.80–30.39]. Disease onset was earlier in males, but was similar for TTNtv of different types and locations. The presence of clinical risk factors was associated with earlier DCM onset (OR, 3.41; 95% CI, 2.06–5.64), with a prior history of atrial fibrillation having a two-fold increased odds of DCM (OR, 2.05; 95% CI, 1.27–3.32). The prevalence of clinical risk factors increased with age; however, the strength of the DCM association was greatest for young-onset (<30 years) disease (OR, 4.75; 95% CI, 2.35–9.60). Administration of beta-adrenergic receptor or renin-angiotensin system-blocking drugs prior to overt DCM was associated with 87% reduced odds of DCM (OR, .13; 95% CI, .08–.23). Conclusions Disease onset in TTNtv-associated familial DCM is dependent on individual patient context and is potentially modifiable by risk factor management and prophylactic therapeutic intervention.

Abstract Molecular characterization of high-grade B-cell lymphoma, not otherwise specified (HGBCL-NOS), is hindered by its rarity, evolving definition, and poor diagnostic reproducibility. To address this challenge, we analyzed 92 HGBCL-NOS tumors collected across Lymphoma/Leukemia Molecular Profiling Project sites. Leveraging comparison cohorts of diffuse large B-cell lymphoma, NOS (DLBCL-NOS) and Burkitt lymphoma (BL), and molecular frameworks described in these entities, our analysis revealed a heterogenous molecular landscape, reminiscent of DLBCL-NOS but with an enrichment of BL features. By cell-of-origin classification, 59% were germinal center B-cell–like (GCB), and 25% were activated B-cell–like (ABC). LymphGen, a genetic classifier for DLBCL-NOS, assigned a genetic subtype to 34% of HGBCL-NOS. Although classification rate was lower than in DLBCL-NOS (66%), assigned subtypes spanned the spectrum of LymphGen classes, including 31% of ABCs classified as MCD. Features differentiating HGBCL-NOS from DLBCL-NOS included MYC rearrangement (47% vs 6%); dark zone signature (DZsig) expression (45% vs 7%); and more frequent mutation of ID3, MYC, CCND3, and TP53, all common to BL. A genetic classifier that differentiates DLBCL-NOS from BL classified 53% of DZsig+ tumors as BL-like, and those classified as DLBCL-like were frequently BCL2-rearranged. Among DZsig− GCB tumors, 95% were DLBCL-like. Centralized pathology review reclassified almost half of tumors as DLBCL-NOS but did not identify a more homogenous HGBCL-NOS population, with no difference in features between confirmed and reclassified tumors. In conclusion, molecular testing enables a subset of HGBCL-NOS to be assigned to established categories. Based on rarity and diagnostic challenges, broader inclusion of HGBCL-NOS should be considered in biomarker-driven DLBCL trials.

Abstract Introduction: Monitoring minimal residual disease (MRD) is critical in multiple myeloma (MM) to predict outcomes and guide therapy. Traditional bone marrow (BM) aspirates for MRD detection are invasive and limited by sample quality. We therefore explored cell-free DNA (cfDNA) fragmentation as a less invasive alternative for MRD detection. Methods: We performed 30-40X whole-genome sequencing (WGS) on peripheral blood cfDNA from 45 MM patients, collecting baseline (n = 45) and follow-up samples (n = 98) from eight Canadian sites (M4 and IMMAGINE studies) and one U.S. site (SPORE study), plus 25 healthy controls. Samples were collected post-induction therapy (n = 13), 100 days post-autologous stem cell transplantation (ACST, n = 36), and during maintenance therapy (n = 49). Multiparameter flow cytometry (MFC) MRD testing was conducted on 77 samples. We evaluated insert size metrics and MM-specific chromatin accessibility (from Ordoñez et al., 2020) using Griffin (described in Doebley et al., 2022). Results: Baseline samples had a higher proportion of short fragments (20-150 bp) than follow-up samples (p = 0.0037) and healthy controls (p = 0.019). A fragment score (FS) based on weighted fragment distribution (per Vessies et al., 2022) was highest at baseline (mean = -0.384), followed by MRD-positive (mean = -0.495) and MRD-negative (mean = -0.550) samples. MRD-negative FS was lower than baseline samples (p < 0.001) but higher than healthy controls (mean = -0.639; p = 0.016). Baseline samples had lower coverage at MM-specific chromatin regions than MRD timepoints (p < 0.05; baseline mean = 0.982; MRD-positive = 0.989; MRD-negative = 0.994; healthy = 0.993), suggesting higher transcriptional activity pre-treatment. MRD-negative samples had higher coverage than MRD-positive cases (p < 0.01). Using logistic regression, we assessed the predictive performance of FS and coverage at MM-specific sites. FS alone achieved an AUC of 0.632 (sensitivity [SN] 39.4%, specificity [SP] 92.1%, accuracy [AC] 67.6%). Coverage yielded an AUC of 0.681 (SN 75.8%, SP 60.5%, AC 67.6%). Combining FS and coverage at MM sites improved performance (AUC = 0.734; SN 48.5%, SP 92.1%, AC 71.8%). We next evaluated whether adjusting the BM tumor cell percentage cutoff by MFC could improve performance. At 0.017% (1 in 5, 789 cells) for MRD positivity, the combined model’s accuracy reached 83% with an AUC of 0.757 (SN 17%, SP 97%). Conclusions: cfDNA fragmentomic analysis achieved high specificity (92-97%) in detecting MRD, providing a less invasive alternative to facilitate serial monitoring. While sensitivity remains an area for improvement, the high specificity of cfDNA makes it valuable for confirming MRD negativity and reducing invasive procedures. Future efforts aim to enhance sensitivity by integrating additional fragmentomic features. Citation Format: Dor D. Abelman, Jenna Eagles, Aimee Wong, Saumil Shah, Stephanie Pedersen, Stephenie Prokopec, David S. Scott, Sarah Bridges, Darrell White, Irwindeep Sandhu, Kevin Song, Esteban Braggio, Alli Murugesan, Anthony Reiman, Suzanne Trudel, Trevor J. Pugh. Tumor-independent monitoring of minimal residual disease in multiple myeloma using cfDNA fragmentomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3250.

Background This study aims to characterize right ventricular dysfunction (RVD) in heart failure (HF) with preserved ejection fraction and understand the cumulative prognostic value of abnormal RV echocardiographic parameters in HF with preserved ejection fraction. Methods and Results Data from 809 patients in the PARAGON‐HF (Prospective Comparison of Angiotensin Receptor–Neprilysin Inhibitor With Angiotensin‐Receptor Blocker Global Outcomes in HF With Preserved Ejection Fraction) echocardiographic substudy (55% women, mean age 74±8 years) were analyzed. Correlates of RVD (defined as tricuspid annular plane systolic excursion <1.7 cm, fractional area change <35% or absolute RV free wall longitudinal strain <20%) were identified using multivariable logistic regression models. We further assessed the prognostic value of the number of abnormal RV parameters (0, 1, ≥2) on total HF hospitalizations (HFH) and cardiovascular death, total HFH, first HFH or cardiovascular death, all‐cause death, and cardiovascular death. RVD was identified in 461 (57%) patients. Correlates of RVD included older age, higher heart rate, atrial fibrillation/flutter, greater left ventricle wall thickness, higher N‐terminal pro‐B‐type natriuretic peptide levels, lower systolic blood pressure, and lower left ventricle absolute global longitudinal strain. These results were consistent across sexes, except atrial fibrillation/flutter and LV wall thickness, which were associated with a higher risk of RVD in men but not in women. Participants with ≥2 abnormal RV parameters had a significantly higher adjusted risk of total HFH and cardiovascular death (rate ratio, 2.13 [95% CI, 1.13–4.01]), first HFH or cardiovascular death, all‐cause death, and cardiovascular death. Conversely, an isolated abnormal RV parameter was not associated with a worse outcome. Conclusions RV measures may underestimate the burden of RVD in HF with preserved ejection fraction when considered in isolation. Clinicians should consider multiple dimensions to comprehensively assess RV function in patients with HF with preserved ejection fraction.

Abstract Aims To evaluate clinical outcomes, echocardiographic features, and the efficacy and safety of sacubitril/valsartan compared to valsartan across age groups in the PARAGON-HF trial. Methods and results A total of 4796 participants ≥50 years of age with chronic heart failure (HF) and left ventricular ejection fraction (LVEF) ≥45% were divided into three age groups: &lt;65 years (n = 825), 65–74 years (n = 1772), and ≥75 years (n = 2199). Echocardiograms of 1097 patients were analysed in a standardized fashion at a core imaging laboratory. The primary composite outcome was total HF hospitalizations and cardiovascular (CV) death. Older patients were more likely to experience primary composite outcomes (compared to patients &lt;65 years, adjusted rate ratio [aRR] for ≥75 years: 1.39, 95% confidence interval [CI] 1.21–1.61), total HF hospitalization (aRR 1.27, 95% CI 1.09–1.49), and CV death (adjusted hazard ratio [aHR] 2.04, 95% CI 1.44–2.87). Age did not modify the effect of sacubitril/valsartan compared to valsartan on primary composite endpoint (pinteraction = 0.79) in the overall population or in those with LVEF ≤57%. Older adults randomized to sacubitril/valsartan were more likely to develop hypotension compared to those receiving valsartan (pinteraction = 0.026). Older patients had smaller left ventricular chamber sizes, higher LVEF, and were more likely to have abnormal measures of diastolic function. Conclusion Older patients with HF with preserved ejection fraction had higher event rates than younger patients, more adverse events overall, and more hypotension when treated with sacubitril/valsartan; however, the treatment benefits of sacubitril/valsartan were retained in older patients.

Abstract Background: MCL is a B-cell non-Hodgkin lymphoma for which auto-HCT is often employed in first CR, based on non-randomized phase 2 trials, and a randomized trial (Dreyling et al, Blood 2005) conducted before the advent of more effective induction and maintenance regimens. The TRIANGLE trial (Dreyling et al, Lancet 2024) suggested that auto-HCT may not add benefit to more effective induction and maintenance regimens containing high-dose cytarabine, rituximab and BTK inhibitors. E4151 explored whether auto-HCT benefits pts achieving deep first remission, as measured by a highly sensitive immunoglobulin high throughput sequencing minimal residual disease (MRD) assay. Methods: EA4151 is a four arm trial conducted through the U.S. National Clinical Trials Network (NCTN) and Blood and Marrow Transplant Clinical Trials Network (BMT-CTN). Pts with MCL between the ages of 18 and 70 and in first remission were eligible. After induction, pts underwent PET/CT, bone marrow biopsy, and the clonoSEQ® MRD assay from peripheral blood. Pts in CR with uMRD at 1 in 10-6 sensitivity (uMRD6) were randomized 1:1 to Arm A (auto-HCT + 3 years of maintenance rituximab [MR]) or Arm B (3 years of MR alone), stratified by MIPI-c score and intensive vs non-intensive induction. Pts with either MRD-positive (MRD+) CR or MRD-indeterminate CR (Arm C and Arm D, respsectively) both received auto-HCT + 3 years of MR. Pts who were MRD+ pre-transplant had MRD repeated at day 100. Primary endpoint was to compare overall survival (OS) in Arms A and B, with secondary endpoints including progression-free survival (PFS). Primary analysis population included all randomized pts. As some pts refused their assigned treatment (N=65 [25.3%] for arm A and N=2 [0.8%] for arm B), a “treated as assigned” analysis was also performed. Stratified logrank test was used to compare survival distributions. P-values are two-sided. Results: From Aug 2017 to July 2024, 650 pts were assigned to a treatment arm with 257, 259, 49, and 85 pts enrolled on Arms A, B, C, and D, respectively. Pts were 79% male and 92% white race. Median age was 60 years (range 27-70). MIPI-c was low/low-intermediate (LI) in 63% and high/ high-intermediate (HI) in 37%. Induction was intensive (defined as high-dose cytarabine-containing) in 73% and non-intensive in 27%. A BTK inhibitor was given during induction in 7.2% of pts, and during maintenance in 0.3% of pts. The third pre-planned interim analysis was based on data as of 7/15/24, with median follow up of 2.7 years. The futility boundary was an OS hazard ratio (HR) of 0.984 for Arm A vs B. The estimated OS HR for Arm A vs B in all randomized (n=516) and pts treated as assigned (n=375) were 1.11 (CI 0.71-1.74, p=0.66) and 1.00 (CI 0.58-1.74, p=0.99), respectively and crossed the futility boundary. The 3 year (yr) OS for Arms A and B were 82.1% and 82.7% in all randomized pts, and 86.2% and 84.8% in pts treated as assigned. The estimated PFS HR for Arm A vs B in all randomized and pts treated as assigned were 1.05 (CI 0.71-1.56, p=0.79) and 0.95 (CI 0.59-1.54, p=0.84), respectively. The 3 yr PFS for Arms A and B were 76.6% and 77.4% in all randomized pts, and 81.5% and 80.4% in pts treated as assigned. For Arm C, 3 yr OS and PFS were 81.9% (CI 69.6-96.4%) and 76.9% (CI 64.4-91.7%), respectively. For Arm D, 3 yr OS and PFS were 85.1% (CI 76.0%-95.4%) and 73.4% (62.7-85.9%), respectively. For the MIPI-c low/LI group, 3 yr OS was 84.6% vs 85.7% for Arm A vs B (p=0.96), while in the MIPI-c high/HI group, 3 yr OS was 77.4% vs 77.6% for Arm A vs B (p=0.71). For the intensive induction group, 3 yr OS was 83.0% vs 86.2% for Arm A vs B (p=0.30), while in the non-intensive induction group, 3 yr OS was 79.5% vs 72.8% for Arm A vs B (p=0.48). Exploratory analysis of MRD+ pts (Arm C) showed that pts who converted to uMRD6 post auto-HCT (n=17) had 3 yr OS of 100% and PFS of 100%, whereas those who remained MRD+ (n=13) post auto-HCT had 3 yr OS of 63.6% and PFS of 48.8%. Causes of death (COD) in Arm A were 4.7% lymphoma, 5.1% COVID-19, and 5.0% other/unknown. COD in Arm B were 3.5% lymphoma, 6.6% COVID-19, and 4.6% other/unknown. In Sept 2024, the DSMC recommended termination of accrual and release of trial findings based on these results. Conclusion: In this interim analysis, in the era of highly effective induction and maintenance regimens, MCL pts in first CR with uMRD6 did not benefit from consolidative auto-HCT. Pts who remain MRD+ after induction may benefit from auto-HCT. Longer follow-up will be important to confirm these 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&lt;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&lt;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&lt;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&lt;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&lt;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.