Citations

Abstract Triple-Negative Breast Cancer (TNBC) presents a significant clinical challenge due to its heterogeneity and lack of targeted treatment options, with chemotherapy and immunotherapy combinations currently serving as the main therapeutic strategy. Efforts to address TNBC heterogeneity have largely focused on classifying intrinsic cancer subtypes based on differential tumor mRNA expression, a strategy that has proven effective in hormone receptor-positive breast cancers but has yet to yield a clinically useful predictor of survival or treatment response in TNBC. We hypothesize that both the intrinsic characteristics of TNBC and the surrounding immune microenvironment influence treatment outcomes and that immune cell infiltration affects TNBC subtype classification and response variability. To explore this hypothesis, we compared the predictive and prognostic capabilities of cancer subtype-based (TNBC-type) gene signatures and immune cell deconvolution methods (CIBERSORT) within the same TNBC datasets. We found that immune cell abundance outperformed TNBC subtype-signatures and multicellular immune cell aggregates showed the highest performance of all. More specifically, aggregate immune cells associated with tertiary lymphoid structures and tumor associated macrophages/monocytes demonstrated statistically significant predictive value. These findings were confirmed in an independent cohort of 67 TNBC patients treated with neoadjuvant chemotherapy. Further, single-cell RNA sequencing analysis revealed that the predictive power of cancer-subtype could be partially explained by immune- and stromal features. Examination of single-cell resolution spatial transcriptomic data confirmed presence of TLS-like, TAM- and cancer-stromal niches within TNBC biopsy samples that were associated with treatment response. Overall, our results highlight that immune cell aggregates, which capture the spatial organization of the TME, outperform cell-type specific gene signatures in predicting TNBC outcomes. Our novel approach provides a robust framework for interpreting spatial relationships in bulk RNA-seq data, offering a pathway for reconciling past data with current advancements in spatial profiling technologies. This work paves the way for future studies to leverage the multi-cellular complexity of TNBC, enhancing diagnostic precision and facilitating the development of therapies that strategically modulate the tumor microenvironment for improved anti-cancer responses.

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 Background: Pyroptosis is a form of programmed cell death characterized by cleavage of gasdermin (GSDM) family proteins that form pores in the plasma membrane, cell rupture, and release of pro-inflammatory cytokines. Its pro-inflammatory potential has garnered significant research attention in recent years but has not been studied in lymphoma. Patients and Methods: We performed immunohistochemistry for cleaved GSDMD (n-terminal) in two large cohorts of diffuse large B-cell lymphoma (DLBCL) with multiplex fluorescent IHC (mfIHC) data, and analyzed for prognostic and immune impact. Results: Cleaved GSDMD was frequently expressed in DLBCL, and only the cytoplasmic (versus nuclear) form of expression correlated with significantly better patient survival in two DLBCL cohorts. To understand the expression at the single-cell level, we examined mfIHC results, which revealed that GSDMD+cells were tumor or immune cells, and varied in Ki-67, BCL2, and MYC expression. Cases with cytoplasmic cleaved GSDMD expression had higher mean and median levels of CD38+ (activated) M1 macrophages in two cohorts and lower PD-1/PD-L1 expression, as well as phenotypes of cognate interactions between live activated M1 macrophages, DLBCL cells, and T cells in spatially resolved immune landscape by mfIHC. In contrast, phagocytosis of pyroptotic lymphoma cells by M2 macrophages and cell death of T cells were observed in cases with predominantly nuclear form of cleaved GSDMD expression. Bulk gene expression profiling analysis identified a large proportion of RNA genes upregulated in DLBCLs with cytoplasmic cleaved GSDMD expression, and deconvolution analysis found decreased frequency of the “Inflammatory” lymphoma microenvironment (LME) subtype, increased frequency of cell states and ecotypes with favorable prognostic associations, and decreased frequency of T cell exhaustion states. Summary: Analysis of pyroptosis-inducing cleaved GSDMD (n-terminal) expression in a large number of DLBCL patients revealed dinstinctive cytoplasmic and nuclear expression patterns in live and pyroptotic cells associated with different prognostic and immune effects. Cytoplasmic cleaved GSDMD expression is a marker of cognate interactions between live cells (e.g., activated M1 macrophages) associated with adaptive responses and favorable prognostic effects, whereas nuclear cleaved GSDMD expression is associated with immunosuppressive mechanisms, including T cell death and phagocytosis by M2 macrophages.

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 Introduction: MYC+BCL2+ double expression (DE) is a biomarker for poor prognosis in diffuse large B-cell lymphoma (DLBCL), likely due to the cooperation between MYC and BCL2 oncoproteins in tumor cells. However, as generally MYC and BCL2 are separately assessed on two different slides by immunohistochemistry (IHC), MYC+ and BCL2+ results are from different cells. With the WHO-recommended cutoffs, ≥40% for MYC and ≥50% for BCL2 (sum &lt; 100%), there is chance that the so-called DE comes from non-overlapping regions of the tumor (not single-cell DE). Moreover, tumor expression scores based on morphology assessment often vary among pathologists. In this study, we performed fluorescent multiplex IHC (fmIHC) using a MultiOmyxTM immunofluorescence platform (NeoGenomics Laboratories, Inc.) to determine single-cell MYC and BCL2 co-expression for prognostic analysis in DLBCL. Patients and Methods: Co-expression of MYC, BCL2, and 11 immunophenotypic markers by fmIHC was digitally quantified for 547 patients with DLBCL. Percentage of cells with MYC/BCL2 double or single expression was calculated for various cell types. Prognostic analysis was performed for de novo DLBCL cases, including 108 patients treated CHOP chemotherapy, and 356 patients treated with rituximab (R)-CHOP. Results: First, although MYC and BCL2 were expressed in multiple cell types, the vast majority (&gt;90%) of MYC+BCL2+ DE cells were lymphoma cells. Frequencies of MYC and BCL2 co-expression were consistent with random distribution of independent MYC/BCL2 expression in positive cases. The activated B-cell-like subtype compared with the germinal center B-cell-like subtype had a significantly higher mean percentage of MYC+BCL2+ DE, but not single BCL2 or MYC expression, in PAX5+ cells. Second, in both the R-CHOP and CHOP cohorts, high percentages of DE in PAX5+ cells and in all DAPI+ cells were associated with significantly poorer survival of DLBCL patients. Very high percentage of single BCL2 expression in PAX5+ cells was also associated with poorer survival, however, only in a small number of patients in both cohorts. Only in the R-CHOP cohort, high single MYC expression in PAX5+ cells (in a significant proportion of the cohort) was associated with significantly poorer overall survival. In the R-CHOP cohort, eight cases had MYC/BCL2 double hit by FISH, including 3 cases with MYC/IGH fusions (DE) and 5 cases with MYC/non-IGH rearrangements (only one DE). The exclusion of these double hit cases did not impact the significance of DE and single MYC+ expression. Summary: True MYC+BCL2+ double protein expression at the single cell level is predominantly in lymphoma cells, and associated with significantly poor survival of DLBCL patients. Our results suggest high cutoffs for common MYC/BCL2 IHC to identify true double expressor lymphoma. Citation Format: Zijun Yidan Xu-Monette, Yong Li, Qingyan Au, Harry Nunns, Wenyu Shi, Alexandar Tzankov, Carlo Visco, Govind Bhagat, Eric Hsi, Xiaoxian X. Zhao, Karen Dybkaer, April Chiu, Wayne Tam, Youli Zu, Fredrick B. Hagemeister, Andrew Song, Michele Pellegrino, Heounjeong Go, Maurilio Ponzoni, Andrés Ferreri, Michael B. Møller, Benjamin Parsons, J. Han van Krieken, Miguel A. Piris, Jane N. Winter, Mingzhi Zhang, Bing Xu, Ken H. Young. Single-cell double expression of MYC and BCL2 proteins by fluorescent multiplex IHC is mainly in lymphoma cells with significant prognostic impact in large B-cell lymphoma while suggesting high cutoffs for routine IHC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6418.

Abstract Recent advances in the field of immuno‐oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high‐throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi‐marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

AbstractQuantifying tumor‐infiltrating lymphocytes (TILs) in breast cancer tumors is a challenging task for pathologists. With the advent of whole slide imaging that digitizes glass slides, it is possible to apply computational models to quantify TILs for pathologists. Development of computational models requires significant time, expertise, consensus, and investment. To reduce this burden, we are preparing a dataset for developers to validate their models and a proposal to the Medical Device Development Tool (MDDT) program in the Center for Devices and Radiological Health of the U.S. Food and Drug Administration (FDA). If the FDA qualifies the dataset for its submitted context of use, model developers can use it in a regulatory submission within the qualified context of use without additional documentation. Our dataset aims at reducing the regulatory burden placed on developers of models that estimate the density of TILs and will allow head‐to‐head comparison of multiple computational models on the same data. In this paper, we discuss the MDDT preparation and submission process, including the feedback we received from our initial interactions with the FDA and propose how a qualified MDDT validation dataset could be a mechanism for open, fair, and consistent measures of computational model performance. Our experiences will help the community understand what the FDA considers relevant and appropriate (from the perspective of the submitter), at the early stages of the MDDT submission process, for validating stromal TIL density estimation models and other potential computational models. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.