Hsi, Eric D.

Background TP53 mutational status ( TP53 ms) is prognostically important in myeloid neoplasms. Immunohistochemistry (IHC) of p53 has been used as a surrogate for TP53 mutations, with faster results than next-generation sequencing (NGS) and cytogenetic analysis. Given the challenges posed by heterogeneous p53 IHC expression, this study aims to evaluate the interobserver interpretation of p53 stain as a surrogate marker for TP53m . Methods Fifty-three bone marrow (BM) specimens previously diagnosed as myeloid neoplasms or nonneoplastic BM specimens with available concurrent TP53ms were evaluated. p53 IHC staining was performed on all 53 core biopsy or clot sections. TP53 mutation was found in 24 cases ( TP53 m). Twenty-nine specimens were TP53 wild-type and served as the control group. Six hematopathologists (HPs) blinded to the diagnosis and TP53 m independently scored the p53 staining pattern of the biopsies/clot sections for overall staining percentage (OSP) and staining intensity (dark staining percentage as a percentage of total cells (DCP)). Results The intraclass correlation was excellent for OSP (0.927) and good for DCP (0.848). For OSP, a cutoff of 30% resulted in sensitivity of 83.3%, specificity of 89.7%, PPV of 87.0%, and NPV of 86.7%. For DCP, a cutoff of 10% achieved sensitivity of 87.5%, specificity of 96.6%, PPV of 95.4%, and NPV of 90.3%. Additionally, DCP significantly correlated with the VAF of TP53 m (R = 0.469, p = 0.028). Conclusion High inter-rater reliability for OSP and DCP supports integrating p53 IHC into bone marrow evaluations for rapid TP53 m assessment. With superior specificity and predictive values, DCP proves to be a more reliable diagnostic marker for TP53 mutations. While this approach shows promise for myeloid neoplasms, further validation is needed to overcome challenges and expand its clinical utility for tailored treatment strategies.

Abstract Germinal center (GC)-derived lymphomas arise within a specialized immune ecosystem, yet whether malignant cells direct its remodeling remains unclear. Integrating genomic, transcriptomic, spatial, and functional analyses across follicular lymphoma and diffuse large B-cell lymphoma, we define a developmental framework linking malignant B-cell differentiation state to tumor microenvironment (TME) organization. Rather than segregating by histology, lymphomas align along a shared differentiation continuum in which proliferative dark zone (DZ) states associate with immune-depleted TMEs, whereas post-GC/memory B-cell (MBC) states drive inflamed but immunosuppressed TMEs. Spatial profiling reveals collapse of GC architecture and emergence of suppressive myeloid niches along this trajectory. Single-cell lineage reconstruction uncovers a DZ-to-MBC developmental axis underlying lymphoma evolution. Genetic reprogramming in vivo demonstrates that malignant differentiation state is sufficient to instruct TME remodeling. Collectively, these findings establish malignant differentiation state as a causal determinant of immune architecture across GC-derived lymphomas and identify lineage-directed immune reprogramming as a potential therapeutic strategy.

Large B-cell lymphoma with IRF4 rearrangement (LBCL-IRF4) predominantly affects children and young adults (CAYA) and presents as localized disease with excellent prognosis. Although most tumors harbor IRF4 rearrangements (IRF4-R), the existence of cryptic rearrangements has been suggested. Whether IRF4-R LBCL in adults represents the same biological entity remains unclear. To address this question, 35 CAYA patients diagnosed with LBCL-IRF4 and 7 adult (>40-year-old) LBCL with IRF4-R were investigated by an integrative molecular approach. Targeted sequencing structural variant analysis (SV-NGS) confirmed the IRF4-R in 84% of investigated cases. In CAYA, an enrichment (55% vs 29% in adults) of translocations involving IGH, with a breakpoint cluster 3' to IRF4 (EXOC2) was observed, including a cryptic insertion of IGHM-IGHJ5 into IRF4 locus. Novel translocations, IRF4::MIR142 in two CAYA (7%) and IRF4::BATF in one adult, were discovered. Whole-exome sequencing analysis identified unreported mutations in LBCL-IRF4 as YY1 and ZC3H12A (11% each). The high incidence of mutations affecting the B-cell receptor/NF-KB pathways in LBCL-IRF4 was confirmed in cases with diffuse component only. None of the CAYA tumors were classified by LymphGen tool. Adult IRF4-R LBCL showed higher levels of genetic complexity and a distinct mutational profile with mutations on KMT2D and DTX1 (43% each), and MYD88-L265P (29%), and were predicted as EZB or MCD (29% each). These differential genetic features were in line with different clinical presentations (extranodal involvement and advanced stage). In conclusion, IRF4-R architecture and mutational profile differ according to age, supporting that not all cases should be classified as LBCL-IRF4.

Diffuse large B-cell lymphoma (DLBCL), the most common type of lymphoma, arises from various pathogenic mechanisms including gene translocations and fusions. Detection of gene rearrangements using fluorescence in situ hybridization (FISH) is a standard practice for DLBCL diagnosis and guides treatment decisions. High-throughput chromosome conformation capture (Hi-C) DNA sequencing is a next-generation sequencing-based technology to identify genome-wide rearrangements using a single assay. In this study, Hi-C sequencing was performed using FFPE tissues from 159 patients with DLBCL, and identified 746 cancer genes at or proximal to the rearrangement breakpoints with a total of 1903 occurrences. Focusing on clinically important rearrangements, Hi-C detected 102 rearrangements of MYC, BCL2, and/or BCL6 in 92 patients and revealed the fusion partners, including 25 rearrangements missed by FISH. Causes of FISH negative results included FISH-cryptic breakpoints, complex or faint FISH signals, low percentage of FISH positivity, and issues related to tissue fixation. Moreover, in 20 patients (12.6%), Hi-C sequencing detected 22 rearrangements characteristic of other lymphoma types, including CCND1 rearrangements that could lead to reclassification as mantle cell lymphoma. Survival analysis for genome-wide rearrangements using machine learning models identified MYC, PD-L1, CCND1, BCL2, NTRK1/PRCC, RRAS, and FANCE rearrangements with significant prognostic effects in the DLBCL cohort. In conclusion, Hi-C sequencing detects gene rearrangements crucial for diagnosis in an unbiased and molecular manner and showed high sensitivity and specificity in our study. These advantages of Hi-C sequencing offer help to improve the workflow of clinical pathology laboratories, diagnostic precision, and treatment of large B-cell lymphoma.

Abstract Introduction: Diffuse large B-cell lymphoma (DLBCL) is the most common type of malignant lymphoma. Previous studies have shown that DLBCL cells are susceptible to GPX4 (Glutathione peroxidase 4)-regulated ferroptosis, an iron-dependent type of programmed cell death characterized by increased reactive oxygen species and excessive lipid peroxidation. In addition to GPX4, FSP1 (Ferroptosis suppressor protein 1, previously known as AIFM2) is a glutathione-independent repressor of ferroptosis that has shown prognostic significance in solid tumors. In this study, we aimed to reveal the significance of GPX4 and FSP1 in DLBCL. Patients and Methods: We performed immunohistochemistry (IHC) for GPX4 and FSP1 in a large cohorts of patients with de novo DLBCL, and evaluated their cytoplasmic and nuclear expression. Prognostic analysis was performed for FSP1 and GPX4 expression in patients treated with rituximab (R)-CHOP or CHOP chemotherapy, respective of TP53 mutation status, as p53 regulates ferroptosis and TP53 mutation is associated with poorer prognosis in DLBCL. Results: FSP1 expression with a ≥10% cutoff was positive in 42.3% of DLBCL cases. Patients with TP53 mutations had a non-significant trend of higher mean FSP1 expression than those with wild-type (Wt) TP53 (P=0.11). Prognostic analysis revealed that cytoplasmic FSP1+ expression was associated with significantly poorer overall survival and progression-free survival in Wt-TP53 DLBCLs treated with R-CHOP (P=0.016 and P=0.003, respectively), and only showed non-significant unfavorable trends in TP53 mutated DLBCLs and patients treated with CHOP. In contrast, GPX4 expression did not show a significant unfavorable prognostic effect in DLBCL, and in fact, was associated with a non-significant trend of better survival. Previously we have quantified immune cell abundance and PD-1/PD-L1 expression in the tumor microenvironment of the study cohort using multiplex fluorescent IHC. Correlative analysis found that FSP1+ patients had significantly higher mean and median abundance of CD68+ cells (both M1 and M2 macrophages) and CD11c+ cells than FSP1- patients. Further analysis in Wt-TP53 and mutated TP53 subcohorts found that only in the TP53 mutated DLBCL subcohort, FSP1 expression was associated with significantly higher mean and median CD163-CD68+ (M1) and overall CD68+ macrophages, whereas in the Wt-TP53 DLBCL subcohort, FSP1 expression was associated with significantly higher median (but not mean) CD163+CD68+ (M2) macrophages and CD11c+ cells. Summary: Cytoplasmic FSP1 expression but not GPX4 had significantly adverse prognostic effect in patients with Wt-TP53 DLBCL treated with standard immunochemotherapy. Our results also suggest that in addition to ferroptosis regulation, macrophage abundance was relevant for the prognostic effects of FSP1 expression. Citation Format: Beibei Lyu, Zijun Xu-Monette, Xiaoxian X. Zhao, Eric D. Hsi, Ming Chen, Carlo Visco, Alexandar Tzankov, Karen Dybkaer, Mu-En Wang, Chang Wang, Qingyan Au, Harry Nunns, Zenggang Pan, Benjamin Parsons, Santiago Montes-Moreno, Fenghuang Zhan, Michael B. Møller, Leon Bernal-Mizrachi, Youli Zu, Shanxiang Zhang, Weina Chen, Govind Bhagat, Yong Li, KEN H. YOUNG. Expression of the ferroptosis suppressor FSP1 but not GPX4 shows significant adverse prognostic effect in diffuse large B-cell lymphoma with wild-type TP53 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4661.

ABSTRACT Background Despite histologic remission (HR) being important in management of ulcerative colitis, the impact of endoscopic sampling on newer scoring systems remains uncertain. This study examines the outcome of applying PICaSSO Histologic Remission Index (PHRI) scoring on biopsies collected during routine clinical care and investigates the impact of endoscopic sampling variation on PHRI scoring and HR status. Methods A retrospective survey of UC endoscopic biopsies ( N = 128, 559 bites, 1–13 bites/biopsy) was evaluated using standard H&E stain and myeloperoxidase (MPO) immunohistochemistry to aid neutrophil identification. Convolutional neural networks (CNN), trained on colonic tissue architecture and cytomorphology features, were deployed alongside pathologist interpretations. In silico modeling of bite‐derived virtual biopsies ( N = 19,760) was investigated to determine the impact of sampling variation on PHRI scores and compared with ground truth clinical samples. Results PHRI MPO scoring displayed improved sensitivity and specificity for identifying neutrophils, compared with PHRI H&E . CNN‐derived PHRI scoring was most accurate for chronic active and chronic active with ulceration categories, with greatest variability observed in chronic inactive biopsies. Virtual patient biopsies comprised of < 5 endoscopic bites were impacted most by sampling permutations. Limited variability in PHRI scores was observed in samples consisting of ≥ 5 bites. Conclusions HR status (PHRI = 0) determination was slightly impacted by sampling. Biopsies consisting of < 5 endoscopic bites exhibited the most variability. Conservative sampling of 5–7 endoscopic bites may produce more accurate assessments of microscopic heterogeneity in clinical studies employing quantitative histologic measurements to assess disease activity and remission. Additionally, incorporating MPO increased the sensitivity and specificity of detecting active inflammation for PHRI scoring.

Abstract Pyroptosis is a form of programmed cell death characterized by the cleavage of the gasdermin (GSDM) family proteins that form pores in the plasma membrane, cell rupture, and the release of proinflammatory cytokines. In this study, we performed immunohistochemistry for cleaved gasdermin D (GSDMD), gasdermin E (GSDME) N-terminus, and gasdermin C (GSDMC) in 2 different cohorts of diffuse large B-cell lymphoma (DLBCL) and analyzed the impact of GSDM expression on prognosis and immunity. The results showed frequent cleaved GSDMD (N-terminal) expression. Only cytoplasmic GSDMD N-terminal expression correlated with significantly better patient survival in the 2 cohorts. In contrast, GSDME was mainly expressed in the vascular endothelium, and correlated with significantly adverse prognostic effect. Correlating with the multiplex fluorescent immunohistochemistry results, we found that cytoplasmic GSDMD N-terminal expression was associated with increased CD38+ (activated) M1 macrophages in both cohorts, cognate interactions between live DLBCL cells and activated M1 macrophages (and T cells), and lower PD-1/PD-L1 expression in the analyzed cases. In contrast, T-cell pyroptosis, lymphoma cell-resistance to cell death, and phagocytosis by M2 macrophages were observed in tissues with predominantly nuclear GSDMD N-terminal expression. Bulk gene expression profiling and deconvolution analysis revealed associations of cytoplasmic GSDMD N-terminal expression with downregulation of “Don’t eat me”–signaling genes, upregulation of many RNA genes, decreased frequency of “inflammatory” lymphoma microenvironment subtype, increased frequencies of prognostically favorable cell states and ecotypes, and decreased frequency of T-cell exhaustion state. In summary, this study showed distinct cellular and subcellular patterns of 3 GSDM proteins and their associated immune response phenotypes and prognostic effects, with implications for novel therapeutic strategies for B-cell lymphoma.

Abstract Over the past decade, classification systems using high-throughput genetic data have been developed to identify molecular subtypes of DLBCL. Although not a primary goal, these classifiers were also proposed as prognostic factors in their respective publications. To date, however, no study has directly compared these classifiers' ability to predict overall (OS) and event-free survival (EFS) in the same cohort. Herein, we sought to systematically compare predictive performance, benchmarked against the IPI, of several current established molecular classifiers and evaluate if any add significant independent prognostic information beyond the IPI. WES (including paired germline filter) and RNAseq data from newly diagnosed DLBCL patients (N=432; 2018 WHO criteria) in the Mayo Clinic/University of Iowa Lymphoma Molecular Epidemiology Resource (MER) were available for analysis (WES n=112, RNAseq n=40, or both n=280). The number of cases able to be classified (including as unclassified) for each classifier was as follows: IPI (432, 100%), cell-of-origin (COO, by Hans algorithm; 346, 80.1%), refined COO (by gene expression with Dark Zone Signature; 320, 100%), Haematological Malignancy Research Network (HMRN; 349, 89.0%), B-cell state (320, 100%), Lymphoma Ecotype (320, 100%), Lymphoma Microenvironment (LME; 320, 100%), Tumor microenvironment (TME26; 320, 100%), SubLymE (312, 97.5%), LymphGen (358, 91.3%), and DLBclass (223, 58.2%). OS was defined as time from diagnosis to all-cause death while EFS was defined as time from diagnosis to disease progression, initiation of second-line treatment, or all-cause death. We calculated Harrell's c-statistics for each Cox proportional hazards model evaluating the discriminative performance of each classifier in predicting OS/EFS. Using bootstrap validation, we obtained optimism-corrected c-statistics, which we report in the results. We performed likelihood ratio tests (LRT) comparing a univariable Cox model with IPI alone and models including both IPI and a given classifier to assess if a classifier provided independent prognostic information beyond the IPI. All patients were treated with immunochemotherapy (IC) with curative intent, 247 (57%) were male, median age at diagnosis was 65 years (IQR 55-72 years), 390 (96%) were White, 209 (60%) had GCB subtype by Hans, 22 (5.1%) had MYC double-hit by FISH (MYC and BCL2 or BCL6), and 162 (37.9%) had an IPI ≥ 3. The median follow-up was 7.0 years, 167 (39%) experienced an event, and 137 (32%) died. In a univariable Cox model, the c-statistic for IPI predicting OS was 0.66 (95% confidence interval [CI] 0.61-0.70). All other classifiers had c-statistics of ≤0.56. The c-statistic for IPI predicting EFS was 0.64 (95% CI 0.60-0.69), and all other classifiers had c-statistics of ≤0.58. The univariate DLBclass results for OS and EFS were not significantly impacted when restricted to cases with confidence &gt;0.7 (n=136). In Cox models of IPI alone versus IPI plus an individual classifier, the only classifier that provided statistically significant, independent information for OS was TME26 (LRT p=0.02). Adjusting for IPI, patients who were TME26-negative had significantly inferior OS compared to TME26-positive cases (HR 1.63, 95% CI 1.07-2.47; p=0.02). For EFS, DLBclass (restricted to confidence &gt;0.7) added significant prognostic information beyond IPI (LRT p=0.02). This finding was largely driven by C5 subtype; relative to C1 subtype and adjusting for IPI, C5 subtype had significantly inferior EFS (HR 5.53, 95% CI 1.81-17.0; p=0.003). In summary, we compared prognostic performance of multiple DLBCL molecular classifiers with respect to OS and EFS in a single real-world, prospective cohort of newly diagnosed, IC-treated DLBCL. Our data supports two key findings: all classifiers had modest performance for prognosis, and none individually outperformed the IPI in predicting OS nor EFS. Second, only TME26 and DLBclass (confidence &gt;0.7) provided additional prognostic information beyond that captured by the IPI for OS and EFS, respectively. This finding suggests that the tumor immune microenvironment and characteristics of C5 DLBCLs (ABC-subtype, CD79B mutations) can potentially offer significant independent information for predicting survival and response to front-line immunochemotherapy. If replicated, these findings could inform risk-adapted treatment approaches and aid in identifying high-risk patients for enrollment in genomically-informed clinical trials.

Abstract Background: Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma (NHL), accounting for approximately 30% of all NHL cases. DLBCL diagnosis relies on histologic examination, immunophenotyping, molecular and fluorescence in situ hybridization (FISH) analysis to differentiate it from similar NHL subtypes with overlapping morphological features, including more high-grade lymphomas like double-hit lymphoma. Because FISH is performed in a panel of single- or dual-target test format and analyzed through microscopy and manual image analysis, assessment of multiple target biomarkers can be cumbersome and expensive. As additional biomarkers for diagnosis, subtyping, prognosis, and therapeutic decision-making become available, target panels will become larger, posing additional challenges to clinical laboratories. Patients and Methods In this study, Hi-C sequencing of FFPE samples was performed to identify all genomic rearrangements by a single sequencing analysis for an unselected DLBCL case series of 159 patients, and the results were compared to FISH for the detection of clinically important variants. Results Hi-C sequencing showed superior performance compared to FISH: standard FISH for DLBCL includes testing for MYC, BCL2, and BCL6. Between FISH and Hi-C, these biomarkers were detected 105 times, of which, FISH detected 80/105 (76%) and Hi-C detected 102/105 (97%). The cohort included 4 double-hit lymphomas by FISH but Hi-C sequencing detected five. Besides DLBCL diagnostic biomarkers (MYC, BCL2, BCL6), many additional biomarkers were detected by Hi-C sequencing including variants not tested by FISH because the clinical suspicion was ambiguous and the relevant FISH probes were not used, and those not tested because the biomarkers were not thought to be common and, hence, left out of the FISH panel. In total, Hi-C sequencing detected additional biomarkers in 42 (26%) cases, including (1) variants targeted by FISH (i.e. MYC, BCL2, BCL6) but negative, (2) classification biomarkers for other lymphomas (CCND1, MALT, IRF4), and (3) those not tested because the biomarkers are not common and not included in the FISH panel. These additional biomarkers were supportive of suspected diagnosis of DLBCL versus double-hit lymphoma (24 cases), prompted reconsideration of a different diagnosis that may have led to different treatments (6 cases, e.g. mantle cell lymphoma), or biomarkers such as PDL1, ALK, and ATM which have implications for targeted therapies and/or inclusion in clinical trials (5 cases). Conclusion The Hi-C FFPE sequencing technology has the potential to improve the workflow of pathology labs for detection of a wide range of structural variants informing precision diagnosis and treatment for lymphomas.