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AbstractObjectiveTo compare reflux symptoms, Zenker's diverticulum recurrence, and clinical outcomes in patients with and without a history of hiatal hernia who underwent Zenker's diverticulotomy (ZD).Study DesignSingle institution retrospective review.SettingTertiary care academic hospital.MethodsA retrospective review of patients with and without a history of hiatal hernia who underwent ZD via an open stapler, rigid endoscopic CO2 laser, stapler, or harmonic scalpel technique from January 2006 to December 2020 was performed. Data were abstracted for patient demographics, reflux symptoms, and rates of adverse events and symptomatic recurrence.ResultsA total of 426 patients were included in the study, 97 (22.8%) of which had a history of hiatal hernia. Eleven patients (11.3%) with a history of hiatal hernia had undergone Nissen fundoplication prior to ZD. Patients with a history of hiatal hernia showed less symptomatic improvement postoperatively. Significant differences were noted in the change in the Eating Assessment Tool (EAT‐10) (P < .01) and Reflux Symptom Index (RSI) (P = .03) where patients without a history of hiatal hernia improved more than hiatal hernia patients. Despite these differences in symptom relief, rates of postoperative complications and rates of recurrence did not significantly differ between groups. The median time to recurrence was similar for both groups.ConclusionPatients without a history of hiatal hernia had significantly larger improvements in EAT‐10 and RSI scores compared to patients with a history of hiatal hernia. However, these differences in scores may not represent clinically meaningful differences. There were no significant differences in postoperative adverse events or in recurrence of the Zenker's diverticulum between groups.

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.

Introduction: In recent years, multiple myeloma (MM) research has increasingly focused on unraveling the complex interactions between malignant plasma cells and their surrounding bone marrow microenvironment (BMME). To further elucidate these interactions, we developed a comprehensive single-cell atlas of the MM BMME, integrating both coding and noncoding (ncRNA) transcriptional profiles. By correlating these profiles with specific cytogenetic abnormalities in myeloma cells, we aim to uncover how ncRNAs regulate the phenotypic and functional states of myeloma cells and, consequently, shape the cellular landscape of the BMME. A detailed understanding of how the noncoding transcriptome affects the cellular components and immune landscape of the BMME is essential for advancing our knowledge of MM pathogenesis and identifying novel biomarkers and therapeutic targets. Methods: Our atlas was constructed using single-cell RNA sequencing data from 481 samples of CD138neg cells sorted from bone marrow aspirates of MM patients enrolled in the MMRF CoMMpass study. This dataset includes accompanying whole-genome sequencing and survival data, enabling correlative analysis between transcriptional profiles, cytogenetic abnormalities, and patient outcomes. To generate a combined coding and non-coding transcriptome, we developed an expanded human reference genome by systematically merging mRNA and ncRNA transcripts from the LncBook2.0 and GENECODEv42 reference genomes. The sequencing data was aligned to this expanded genome, followed by quality control processing, batch correction, clustering, and supervised analysis. Results: The resulting coding and non-coding atlas comprises over 1.9 million cells, spanning immune, plasma, and stromal compartments. Remarkably, ncRNAs constituted 46% of the associated genes, including 22,102 long ncRNAs (lncRNAs) and 3,112 small ncRNAs. Subclustering analysis of the major immune compartments (B lymphoid, myeloid, and NK and T lymphoid) yielded 70 subclusters, with ncRNAs representing 24-38% of the top 100 differentially expressed genes within each compartment. This underscores the significant role of ncRNAs in distinguishing immune subpopulations. Moreover, examining the association between specific cytogenetic abnormalities and the immune composition of the BMME, 30 subclusters were found to be differentially abundant (P &lt; 0.05) between cytogenetic abnormalities, supporting our hypothesis that myeloma cell genotypes significantly shape the immune microenvironment. For instance, patients with CCND1 amplification displayed an increase CD4+ central memory T cells with a decrease in CD8+ cytotoxic T cells. Similarly, patients with 1q21 gain exhibited an increase in TGFβ-stimulated monocytes, while a decrease in cytotoxic CD8+ T and CD56dim NK cells was observed in patients with 17p13 deletion. Next, examining which ncRNAs are associated with specific cytogenetic abnormalities, we identified 14 ncRNAs significantly differentially expressed across cytogenetic abnormalities. Increased expression of six of these ncRNAs were associated with poor overall survival both independently and in combination (P &lt; 0.05, HR = 3.7). Notably, three of these ncRNAs have documented roles in cancer progression but have not been previously studied in the context of MM. Subsequently stratifying patients based on their enrichment of these outcome-associated ncRNAs revealed even stronger associations with immune composition, including an increase in CD4+ regulatory T cells (P &lt; 0.05). This further supports our hypothesis that myeloma cell genotypes shape the BMME. Lastly, by constructing a gene regulatory network to predict the interactions between coding and noncoding RNAs, we illustrate the regulatory networks of ncRNAs modulating the phenotypes of myeloma and immune cell subpopulations. Conclusion: In summary, we present the first high-resolution transcriptomic atlas of the MM BMME, integrating both coding and noncoding RNAs. This study reveals distinct immune subpopulations associated with specific myeloma cell genotypes and highlights the central role of ncRNAs in modulating the phenotypic and functional states of both malignant and non-malignant cells in the MM BMME. Our findings emphasize the potential of ncRNAs as therapeutic targets and prognostic markers for MM, offering new avenues for research and clinical intervention.

Introduction: The primary analysis of the phase 3 ECHO trial (NCT02972840) demonstrated that acalabrutinib plus bendamustine-rituximab (ABR) significantly improved progression-free survival (PFS) vs placebo plus bendamustine-rituximab (PBR) in older patients (pts) with previously untreated mantle cell lymphoma (MCL) (Wang et al. EHA 2024, Abstract #LB3439). Here we present additional efficacy and safety results from the ECHO trial. Methods: Pts aged ≥65 years (y) with previously untreated MCL and ECOG PS ≤2 were randomly assigned 1:1 to receive ABR or PBR. Acalabrutinib (100 mg twice daily) or placebo was administered until progressive disease (PD) or unacceptable toxicity. Induction with BR was administered for 6 cycles followed by rituximab maintenance (A±R maintenance, cycles 7-30) in pts achieving a partial or complete response (PR or CR). Pts progressing on PBR could cross over to receive acalabrutinib monotherapy. PFS (primary endpoint) was assessed by independent review committee. Minimal residual disease (MRD) negativity rate (10-5) was assessed in peripheral blood (every 24 weeks [wks], at CR, and at PD) and bone marrow (at CR) by NGS-based ClonoSEQ assay (Adaptive Biotechnologies). Results: Among the 598 pts randomized to ABR or PBR (299 in each arm), high-risk baseline characteristics included high-risk simplified MIPI score in 24.1% and 24.4%, blastoid histology in 8.7% and 6.7%, pleomorphic histology in 5.0% and 6.0%, centrally tested Ki-67 ≥30% in 46.5% and 49.2%, and known TP53 mutation in 7.4% and 9.7%, respectively. PFS hazard ratios (HRs) for subgroups were 0.78 (95% confidence interval [CI] 0.51-1.19) in pts with high-risk simplified MIPI score, 0.68 (95% CI 0.29-1.58) in pts with blastoid histology, 0.64 (95% CI 0.25-1.66) in pts with pleomorphic histology, 0.69 (95% CI 0.49-0.98) in pts with Ki-67 ≥30%, and 0.88 (95% CI 0.42-1.78) in pts with known TP53 mutation. In the ABR arm, median PFS was 22.2 months (mo) among pts who discontinued acalabrutinib during induction for reasons other than PD or death, 29.4 mo in pts who discontinued acalabrutinib during A±R maintenance (cycles 7-30) for reasons other than PD or death, and not reached in pts who received acalabrutinib for 31 cycles or more. Among evaluable patients who were MRD negative at the end of induction (24 wks), the rate of conversion to MRD positive during maintenance was lower in the ABR arm (5.85%; n=11/188) than in the PBR arm (15%; n=26/171). Conversely, among evaluable pts who were MRD positive at the end of induction (24 wks), 37.5% (n=3/8) in the ABR arm and 20% (n=3/15) in the PBR arm converted to MRD negative during maintenance. Overall rates of AEs were similar in each arm during induction, but were higher in ABR during A±R maintenance (cycles 7-30) and more so in the monotherapy phase (cycle 31+). Grade ≥3 TEAEs (ABR vs PBR) were 70.0% vs 68.7% during induction, 64.9% vs 62.9% during A±R maintenance (cycles 7-30), and 57.0% vs 45.3% during monotherapy (cycle 31+). Similarly, rates of TEAEs leading to discontinuation of acalabrutinib/placebo were 8.1% vs 8.8% during induction, 23.9% vs 19.0% during A±R maintenance (cycles 7-30), and 25.9% vs 13.7% during monotherapy (cycle 31+). Exposure-adjusted incidence rates per 100 person-years reduced the difference between ABR and PBR for clinically relevant TEAE rates (32.6 vs 29.3 for grade ≥3 serious TEAEs; 4.2 vs 4.0 for grade 5 TEAEs; 15.5 vs 12.4 for TEAEs leading to acalabrutinib/placebo discontinuation), possibly due to longer median exposure to acalabrutinib (28.6 vs 24.6 mo). Conclusion: Acalabrutinib in combination with BR provides a significant PFS benefit in pts with previously untreated MCL, including those with high-risk features. Furthermore, the addition of acalabrutinib to BR provided a greater PFS effect among pts in the ABR arm with the longest exposure to acalabrutinib. The PFS improvement may be partially driven by the contribution of acalabrutinib to sustained MRD-negative status and deepened responses after the end of induction. ABR provides this clinical benefit without excess toxicity as shown by attenuated differences between arms in exposure-adjusted incidence rates, suggesting that higher AE rates in the ABR arm are likely due in part to the longer duration of acalabrutinib treatment vs placebo. These data emphasize the benefits of acalabrutinib in frontline MCL treatment in high-risk pts and the additional benefit of continuous therapy.

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.

Introduction: HIV-associated diffuse large B-cell lymphoma (HIV-DLBCL) is a significant complication in HIV-positive individuals, presenting unique clinical challenges and a poorer prognosis compared to patients with de novo DLBCL. Epstein-Barr Virus (EBV) status is a critical factor influencing the pathogenesis, clinical behavior, and therapeutic responses in these lymphomas. Plasmablastic lymphomas (PBL) have shared some overlapping genomic abnormalities with HIV-DLBCL including MYC rearrangements. This study aims to elucidate the differences in the genetic profiles and pathway activations between EBV(+) and EBV(-) HIV-DLBCL through comprehensive genomic profiling. Methods: Cases of DLBCL were identified in patients living with HIV from a multi-institute cooperative group. Cases of Burkitt lymphoma and PBL were excluded. We performed whole exome sequencing (WES) on 106 tumors of HIV-DLBCL and RNA sequencing on 39 tumors and mapped the reads to hg38 reference genome using BWA and STAR, respectively. EBV status of cases was determined by in situ hybridization and/or reads mapped on EBV genome in sequencing data. Somatic mutations were identified using variant callers (Strelka2, Mutect2) with WES data. For those mutated genes in COSMIC, allele frequency cutoff was set at 0.03. Mutations with an artifact score larger than 0.7 in SOBDetector and those located in segmental duplications were further removed. They were annotated with Ensembl Variant Effect Predictor, manually checked, and plotted with maftools. RNAseq read counts aligned to each gene were obtained by featureCounts and DEseq2 was used for differential expression (DE) analysis between EBV positive and negative groups. Pathway analysis with the DE genes was performed using GSEA. FISH analysis was performed using MYC, BCL2, and BCL6 break-apart probes. Results: There were 41 cases of EBV(+) HIV-DLBCL and 65 cases of EBV(-) HIV-DLBCL. FISH of EBV(+) HIV-DLBCL identified 42% (3/7) with MYC rearrangement (MYCr), none with BCL2 rearrangements (BCL2r) (0/6), and 33% (2/6) positive for BCL6 rearrangement (BCL6r) with 1 tumor having a MYCr/BCL6r. For EBV(-) HIV-DLBCL, there were 35% with a MYCr (6/17), 18% with BCL2r (2/11), and 27% with a BCL6r (3/11) with 2 tumors with MYCr/BCL6r, and 1 tumor with MYCr/BCL2r/BCL6r. The most frequent mutations seen in EBV(+) HIV-DLBCL were STAT3 (32%), DDX3X (22%), and TP53 (15%). For EBV(-) HIV-DLBCL, the most frequent mutations were KMT2D (25%), TP53 (23%), GNA13 (22%), and TET2 (22%). Pathways that were most commonly associated with EBV(+) HIV-DLBCL were JAK/STAT (42%) (STAT3, JAK1) and NF-kB (39%)(DDX3X, TNFAIP3) while EBV(-) HIV-DLBCL was associated with epigenetic modifiers (62%)(KMT2D, TET2, EP300), JAK/STAT (45%)(SOCS1, JAK3) and PI3K/mTOR (40%)(GNA13, MTOR). Significant disparities between EBV(+) and EBV(-) were KMT2D (24% vs 50%, P=0.0025), TET2 (10% vs 26%, P=0.008), SOCS1 (29% vs 39%, P=0.04), DDX3X (15% vs 5%, P=0.03), and GNA13 (5% vs 24%, P=0.001). RAS mutations (KRAS, NRAS) were infrequent in HIV-DLBCL (EBV(+), 12%; EBV(-), 6%), in contrast to prior studies of PBL. Gene expression profiling showed enrichment of MYC targets, oxidative phosphorylation, and the mTORC pathway in EBV(+) as compared to EBV(-) HIV-DLBCL. Conclusion: EBV(+) HIV-DLBCL show a distinct mutational profile compared to EBV(-) HIV-DLBCL, with EBV(+) cases showing frequent mutations with STAT3 and DDX3X in contrast to EBV(-) cases with frequent mutations associated with epigenetic modification pathways (KMT2D, TET2). These genetic profiles underscore the need for tailored therapeutic approaches depending on EBV status. Although the analysis is limited and requires confirmation in a larger cohort, this is the largest study at present evaluating these tumors.

Introduction Peripheral T-cell lymphoma (PTCL) encompasses a heterogeneous group of clinically aggressive entities. ~30% of cases cannot be further classified and are designated as PTCL - not otherwise specified (NOS). We delineated two novel molecular subgroups among PTCL-NOS with distinct clinical and biological features: PTCL-GATA3 which is characterized by high expression of GATA3, a master regulator of T-helper-2-cell (TH2) differentiation, and its target genes (i.e., CCR4, IL4, IL13) and PTCL-TBX21 which is characterized by high expression of TBX21, a master regulator of TH1 differentiation, and its target genes (i.e., CXCR3, IFNG), with the GATA3 subtype showing significantly worse clinical outcomes (overall survival). Nonsense mutations in CCR4 are found predominately in PTCL-GATA3, often within the cytoplasmic domain and gain-of-function in nature. Methods Mutation and copy number data were generated from whole exome sequencing (TFH phenotype excluded following LLMPP pathology review; n = 153). Single nucleotide variants were determined using Mutect2 and Varsvan2 using in-house filtering. Copy number (CN) profiles were generated using CNVkit. Four CCR4 cytoplasmic domain mutants and controls (cytoplasmic domain knockout [CDKO], wild-type CCR4 overexpression (CCR4-WT), and empty vector [EV]) were transduced into healthy-donor CD4+ T cells (n = 2). Polarization studies were generated using TH1- or TH2-associated cytokine exposure. Surface plasmon resonance was used to determine the binding affinity of CCR4 proteins to CCL17 and CCL22. In silico docking studies were done through Schrödinger's BioLuminate. Antibody-dependent cell-mediated cytotoxicity (ADCC) assay was performed through co-incubation of NK92 (CD16 and CD56) and CCR4 edited primary CD4+ T-cells (stained with calcein AM) for 2 hours at a 5:1 NK:T cell ratio by 7-AAD flow cytometry. Results PTCL-GATA3 had a higher frequency of CN aberrations (e.g. TP53, PTEN CN loss) and a more aberrant genome (p &lt; 0.001) than PTCL-TBX21, including mutations with genes associated with DNA repair and damage (TP53, ATM) and T-cell differentiation (CCR4). CCR4 mutations were virtually mutually exclusive with TP53 mutations, and these cases showed higher CCR4 mRNA and protein expression than CCR4-WT cases (p &lt; 0.05). Primary CD4+ T-cells with ectopic expression of the CCR4 variants, especially CCR4-Q330X, did not require CD3/CD28 for proliferation, bypassing CD3/CD28 ligation for T-cell activation. In addition, proliferation rates were similar between TH2-conditional media and normal media, but proliferation and TBX21 expression in TH1-conditional media were inhibited, implying a novel role of CCR4 in T-cell receptor (TCR) activation and TH-differentiation. CCR4 variant proteins showed higher binding affinity for their natural ligands, CCL22 and CCL17, with mutants exhibiting tighter binding to both ligands (1.5- to 3-fold decrease in KD) by surface plasmon resonance and in silico modeling studies. The in silico models demonstrated mutant CCR4 bound mogamulizumab tighter than CCR4-WT, consistent with a higher ADCC-induced apoptosis rate, highest with CCR4-Q330X mutation. CCR4-Y331X exhibited a worse docking score compared to CCR4-WT and a lower ADCC-induced apoptosis rate. Conclusions Our findings reveal distinct genetic characterizations including aberrant TP53 and PI3K signaling and CCR4 mutations in PTCL-GATA3. These CCR4 mutations are shown to have a key role in PTCL-GATA3 pathogenesis by dysregulating TH-differentiation and aberrantly activating the TCR. CCR4 mutation promotes the TH2 phenotype by blocking TH1 differentiation. CCR4 mutant proteins demonstrated an increased binding affinity towards its known ligands, CCL17 and CCL22, and mogamulizumab, consistent with previous studies exhibiting mogamulizumab efficacy against CCR4 mutations. However, the most frequent CCR4 mutant, Y331X, showed worse binding compared to other CCR4 mutants or CCR4-WT, a mutation that showed Mogamulizumab-resistance in a prior CTCL study as well as in an in vitro ADCC assay. The results emphasize aberrant pathways implicated by genomic and clinical evaluation of two novel PTCL subtypes, as well as support the novel role of mutant CCR4 in enhancing T-cell lymphomagenesis and T-helper differentiation, highlighting multiple therapeutic targets.

Introduction Plasmablastic lymphoma (PBL) is a rare aggressive subtype of lymphoma. It is more common in HIV positive patients, and is often associated with Epstein-Barr virus (EBV) and MYC rearrangements. PBL is characterized by markers of plasmacytic differentiation including CD138 and MUM1/IRF4, and loss of B-cell markers such as CD20, which suggests a cell of origin similar to that of multiple myeloma (MM) or activated B-cell-like (ABC) diffuse large B-cell lymphoma (DLBCL). The standard of care for PBL is CHOP-based chemotherapy but this is frequently not curative. Other than EBV-negative status, which defines a high-risk group, no other biological features have been discovered that are associated with outcomes. Methods Here, we provide a comprehensive analysis of the genomic and transcriptomic landscape of PBL using a collection of 176 exomes and genomes (n=55 new, contributed by Lymphoma/Leukemia Molecular Profiling Project [LLMPP] sites and centrally reviewed by the LLMPP pathology panel [WHO 2016]; n=121 previously published [PMID: 33225311, 33951889, 34465776, 34714908]), 65 transcriptomes (n=44 new; n=21 published) and 37 in situ single cell transcriptomic profiles (CosMx Spatial Molecular Imager) from archival diagnostic tissue biopsies. Somatic mutations (SNVs/Indels) were identified using an ensemble of four variant callers (Strelka2, Lofreq, Mutect2, SAGE). Salmon and DESeq2 were used to identify differentially expressed genes. This multi-omics dataset was compared to other known B-cell malignancies including 92 MM, 238 Burkitt lymphomas (BL), and 208 DLBCLs. Cell segmentation of the CosMx data was performed using Baysor and downstream analyses were conducted using the Seurat workflow. For functional validation, cell viability assays (CellTiter-Glo Luminescent Assay) were conducted in the PBL cell line, PBL-1, and 4 control DLBCL cell lines. Results Within the cohort, 63% (106/169) of primary PBL cases were EBV-positive (EBV+) and 57% (82/144) harbored MYC rearrangements (MYC+). When stratifying patients by EBV and MYC rearrangement status, mutations in different genes were enriched in each group: STAT3 occurred in 55% (29/53) of EBV+/MYC+ PBLs; NOTCH1 in 19% (7/36) of EBV+/MYC-; MYC in 24% (6/25) and TP53 in 40% (10/25) of EBV-/MYC+ tumors; TET2 was mutated in 38% (9/24) and KRAS in 25% (6/24) of EBV-/MYC- PBLs. EBV-/MYC+ tumors represented a subgroup of patients with dismal outcomes. The 2-year overall survival (OS) of these patients was 22% compared to 61%, 78%, and 54% of EBV+/MYC+, EBV+/MYC-, and EBV-/MYC- PBL patients, respectively (log-rank test p-adj. &lt; 0.05). Consistent with previous studies, we observed recurrent mutations affecting JAK-STAT (STAT3, SOCS1, SOCS3, DUSP2) in 41% of cases and RAS-RAF (NRAS, KRAS, BRAF) signaling in 38% of all PBLs. In contrast to ABC-DLBCL, very few mutations occurred in the NF-κB signalling pathway. Accordingly, PBL showed marked downregulation of genes involved in B-cell receptor and NF-κB signaling. Consistent with the lack of reliance on these pathways, functional analyses in PBL-1 showed resistance to treatment to ibrutinib as well as PI3K- and MALT1-inhibitors. Moreover, constitutive expression of the IκBα super-repressor did not affect viability of PBL-1 cells. In situ single cell transcriptomic data analyses showed a sparse tumor microenvironment (TME) in PBL, with the primary non-malignant cell types being, on average, 10% macrophages, 7% NK/T cells, and 4% stromal cells of all represented cell types. EBV+/MYC+ tumors displayed a more abundant immune cell population with higher levels of macrophages (median 12%) and NK/T cells (median 9%), whereas EBV-/MYC- tumors were composed of the lowest levels of immune cells (median 4% macrophages and 1% NK/T cells). With respect to malignant cell phenotypes, we noted a novel population of SPP1-expressing cells that were enriched in EBV+/MYC+ tumors and a population of CD44-expressing cells that were enriched in EBV+/MYC- tumors. Conclusion Here we present novel subgroups of PBL with unique biology and clinical outcomes. We show that PBL does not rely on B-cell receptor signaling, instead relying on potentially targetable vulnerabilities in JAK-STAT, NOTCH, and RAS-RAF signaling according to EBV positivity and MYC rearrangement status. Lastly, we provide insight into the TME of PBL and demonstrate a novel population of SPP1 and CD44 expressing malignant cells in EBV+ tumors.

Our polyvinyl alcohol feedstock was prepared through carbic anhydride functionalization, UV curing during direct ink writing, and base treatment. The scaffold exhibited mechanical properties similar to pelvic floor tissue.