Transcriptome sequencing of Hodgkin lymphoma Hodgkin and Reed-Sternberg cells reveals escape from NK cell recognition and an unfolded protein response

Transcriptome sequencing of Hodgkin lymphoma Hodgkin and Reed-Sternberg cells reveals escape from NK cell recognition and an unfolded protein response | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Transcriptome sequencing of Hodgkin lymphoma Hodgkin and Reed-Sternberg cells reveals escape from NK cell recognition and an unfolded protein response Ethel Cesarman, Mikhail Roshal, Isabella Kong, Wikum Dinalankara, and 17 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7957952/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Classic Hodgkin lymphoma (cHL) shares mutations with primary mediastinal B cell lymphoma (PMBL) but differs in histology, clinical behavior, and phenotype. To define transcriptional programs underlying these differences, we performed flow cytometric cell sorting and low-input RNA sequencing of Hodgkin and Reed-Sternberg (HRS) cells from eighteen primary tumors, paired intra-tumoral B cells, and four cHL cell lines, and compared them with RNA-sequencing data from 40 PMBL cases. Transcriptomic profiling revealed that HRS cells undergo abortive plasma cell differentiation with robust activation of the unfolded protein response (UPR), a feature shared with multiple myeloma but absent in diffuse large B cell lymphoma and PMBL. HRS cells also demonstrated profound immune evasion, including suppression of B cell identity genes and loss of natural killer cell recognition through downregulation of SLAM family ligands such as CD48. Comparative analysis with PMBL highlighted shared oncogenic programs and key distinctions: HRS cells exhibited greater loss of B cell identity, absence of GCB- and plasma cell markers, and unique upregulation of cytoskeletal and mitotic pathways consistent with their multinucleated morphology. These findings establish HRS cells as aberrantly differentiated GCB cells with partial plasmacytic features, UPR activation and distinct immune evasion strategies. Health sciences/Medical research Health sciences/Pathogenesis/Oncogenesis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION Hodgkin and Reed-Sternberg (HRS) cells, the malignant cells of classic Hodgkin lymphoma (cHL) are rare and embedded within a dense infiltrate of benign immune and stromal cells, with > 99% of bulk lymph node derived from non-neoplastic cells ( 1 ). This complicates isolation of tumor-specific nucleic acids, which requires enrichment of HRS cells. Limited availability of pure HRS cells has historically hindered comprehensive molecular characterization. Cultured cHL cell lines have served as surrogates, revealing distinct gene expression profiles from normal B cells and other B cell lymphomas, including recurrent CIITA gene fusions in a subset of cases ( 2 , 3 ). Studies of microdissected HRS cells identified chromosomal imbalances and transcriptional differences, notably downregulation of genes regulating cytokinesis and genomic stability, which may contribute to their multinucleated, genomically unstable phenotype ( 4 – 7 ). Our group previously performed whole exome and genome sequencing of purified HRS cells, identifying somatic mutations, indels and copy number alterations, and mapping the evolutionary timing of these events in pediatric and adult cHL ( 8 , 9 ). These analyses showed that some alterations arise before germinal center entry, while others occur early within the germinal center, but terminal HRS cells do not complete the full germinal center program, as evidenced by the absence of SBS9 mutational signature seen in other germinal center-derived lymphomas. Characterization of HRS DNA from cell lines, primary tissue (including from subsequent studies using flow-sorted HRS cells) and circulating tumor DNA revealed a spectrum of mutations overlapping with diffuse large B cell lymphomas (DLBCL) and primary mediastinal B cell lymphomas (PMBL) ( 10 – 21 ). Based on these findings, we hypothesized that the HRS transcriptome could explain at least some of the major differences between these related malignancies. To address this, we performed whole-transcriptome sequencing of HRS cells from primary cases, matched intra-tumoral B cells, and four HL cell lines, compared with 40 PMBL cases. Our analysis reveals that HRS cells exhibit abortive plasma cell differentiation with elevated unfolded protein response, alongside novel alterations in oncogenic, mitotic and immune evasion pathways, providing molecular insight into the unique biology of cHL. MATERIALS/SUBJECTS AND METHODS Tissue specimens Eighteen cHL cases underwent RNA sequencing, including cases previously reported for exome sequencing ( 8 ) and by Maura et al . ( 9 ) (Supplementary Table S1 ). Specimens originated from Weill Cornell Medical College, Mount Sinai Medical Center, Children’s Hospital of Los Angeles, Children’s Healthcare of Atlanta, Children’s Hospital of Philadelphia, Roswell Park Cancer Center, and Memorial Sloan Kettering Cancer Center. Case 1 from the prior study( 8 ) lacked residual material, and was excluded, though numbering was preserved for consistency. Seventeen cases ( 2 – 18 ) had paired intra-tumoral B cell cells, and one (case 19) did not. Cohort size was limited by availability of fresh-frozen viable cell suspensions and HRS cell recovery. Specimens were mechanically dissociated and cryopreserved after lymph node biopsy. Formalin-fixed paraffin-embedded (FFPE) biopsies were used for immunohistochemical validation. For comparison, we performed RNA sequencing on 40 PMBL cases, using tissue from FFPE blocks. All PBCL cases were obtained at Weill Cornell. All cHL and PMBL were deidentified and obtained with IRB approval. Immunohistochemistry IHC was performed on tissue sections (cases 2–10), a cHL microarray containing 16 additional cases and a PMBL TMA containing 50 cases. Immunohistochemical staining was done using the procedures and antibodies described in the Supplementary Methods. Cell Sorting HRS cells and intra-tumoral B cells were isolated from cHL tissues by FACS, as described ( 8 , 22 – 24 ). Briefly, thawed cell suspensions were washed in RPMI 1640/20% FBS containing DNase A, stained for 15 minutes on ice with an antibody panel CD64-FITC(22, Beckman Coulter (BC), Miami FL), CD30-PE (BerH83, Beckton-Dickinson (BD), San Jose, CA, RRID:AB_400238), CD5-ECD (BL1a, BC, RRID:AB_3678603), CD40-PE-Cy5.5 (custom conjugate, gift of Jonathan Fromm) or CD40-PerCP-eFluor 710 (1C10, Ebiosciences, San Diego, CA), CD20-PC7 (B9E9, BC), CD15-APC (HI98, BD, RRID:AB_10893192), CD45 APC-H7 (2D1,BD, RRID:AB_1645480) or CD45-Krome Orange (J.33, BC, RRID:AB_2888654), and CD95-Pacific Blue (DX2, Life Technologies, Grand Island, NY), resuspended in FACS buffer. Sorting was performed on a FACSAria (130µm nozzle, 12 psi) to separate HRS, B, and T cells. Sorted cells were collected in N-2-hydroxyethylpiperazine-N’-2-ethanesulfonic acid buffer solution containing 50% FBS. Flow cytometry NK cells were quantified in 43 cHL tumors and 10 reactive nodes using a panel including CD45, CD7, CD3 and CD56 ( 8 ). NK cells were defined as CD7 + CD56 + CD3 - mononuclear cells. Differences were assessed with two-tailed Student t-test (Excel, Microsoft, Bellevue, WA, RRID:SCR_016137). CD48 expression (clone TU145, BD, RRID:AB_396099) was analyzed on primary HRS cells was examined in 5 cases using a panel containing CD30, CD15, CD20, CD40, CD3, CD95, CD64, and CD45, as previously described ( 8 ). RNA Extraction, Library Construction and Next-Generation Sequencing cHL: Flow-sorted cHL cells were pelleted, washed and RNA extracted using Arcturus PicoPure RNA Isolation kit (KIT0204, Life Technologies, Carlsbad, CA) with RNAse-Free DNase (79254, Qiagen, Venlo, Netherlands) treatment. RNA quality and concentration were assessed with Bioanalyzer RNA Pico (5067 − 1513, Agilent, Santa Clara, CA). Libraries were prepared from 1-4ng total RNA using the SMARTer Ultra Low Input RNA Kit (Clontech, Mountain View, CA), followed by Illumina-compatible library construction with the KAPA LTP kit (KK8221, Woburn, MA). Libraries were sequenced on Illumina HiSeq in paired-end 101bp mode. Data are deposited in NCBI GEO (accession: GSE301492). PMBL : Total RNA was extracted from FFPE tissue sections using an in-house bead-based protocol. A 10% MCT solution (Nature’s Way coconut oil, NaOH) was prepared to generate a proteinase K mix for deparaffinization. Samples were incubated at 56C for 1 hour with intermittent shaking (30s at 1000rpm every 5 minutes). After incubation, the supernatant (RNA-containing fraction) and treated with DNase. RNA was subsequently purified using 0.8x SPRI beads (Agencourt AMPure XP Beads (Beckman Coulter, A63882) and eluted in nuclease-free water. Pooled RNA libraries were prepared using the KAPA Stranded RNA-Seq Kit library preparation kit (Roche 07962169001) and xGen Hybridization and Capture kit (IDT 1080577) in accordance with the manufacturer’s instructions. Differential Gene expression analysis Raw data were mapped to the human genome GRCh38 using HISAT2. FeatureCounts from the Rsubread package (version1.24.7) was used for read counting after which genes without a counts per million reads (CPM) in at least 3 samples were excluded from downstream analysis ( 25 ). Count data were normalized using the trimmed mean of M-values (TMM) method and differential gene expression analysis was performed using the limma-voom pipeline (limma version 3.40.6) ( 26 – 28 ). GSEA-4.3.2 was used for Gene set enrichment analysis (GSEA) ( 29 , 30 ). pheatmap and ggplot2 (version 3.2.1, RRID:SCR_014601) were used to plot the heatmap and cluster-specific trends ( 31 , 32 ). Comparative analyses of PMBL, ABC-DLBCL and GCB-DLBCL expression profiles used the dataset of Rosenwald et al. ( 12 ). Data Input and Preprocessing and Methodology for Virus Identification The computational methods used for this analysis are presented in the Supplementary Methods section. RESULTS Distinct gene expression profiles of HRS cells compared to intra-tumoral B cells To examine the transcriptome of HRS cells, we conducted bulk-RNA sequencing on primary HRS cells from 18 cHL cases, including paired intra-tumoral non-neoplastic B cells from 17 cases and four cHL cell lines (KMH2, HDLM2, L1236, and L428). Cases were numbered 2–19, where 2 through 10 match those reported for exome sequencing ( 8 ) and 11–16 and 19 those reported for exome or full genome sequencing ( 9 ) ( Supplementary Table S1 ). Principal component analysis (PCA) and unsupervised clustering analysis revealed two distinct clusters, separating intra-tumoral B cells from both primary HRS cells and cHL cell lines (Fig. 1 A-B). Comparative analysis between HRS cells and intra-tumoral B cells identified 2144 upregulated genes (logFC ≥ 2; adjp ≤ 0.01) and 2451 downregulated genes (logFC≥-2; adjp ≤ 0.01) (Fig. 1 C, Supplementary Datatable S1 and S2 ). Based on these results, we defined the top 200 upregulated and top 200 downregulated genes ( Supplementary Datatable S3) . Similarly, we compared differentially expressed genes (DEGs) between HL cell lines and intra-tumoral B cells, as well as between primary HRS cells with HL cell lines ( Figure S1 A-B ). Although cHL cell lines and primary HRS cells clustered together in the PCA plot (Fig. 1 A), a substantial number of DEGs were observed between the two groups ( Figure S1 D ), indicating that in vitro cell lines only partially recapitulate the transcriptional landscape of primary HRS cells, potentially due to adaptation to culture conditions and loss of microenvironmental cues. Our results were compared with published Affymetrix array profiles of microdissected HRS cells (29 cases, 5 cell lines)( 6 ). Despite platform differences, gene-level fold changes were strongly concordant (Pearsons's coefficient 0.86; Spearman’s correlation 0.73), with only 20 genes showing discordant direction ( Figure S1 C-D , Supplementary Table S2 ). Compared to arrays, RNA-sequencing in this study provided greater sensitivity and dynamic range. HRS cells exhibit an unfolded protein response We first examined genes significantly upregulated in HRS cells compared to intra-tumoral B cells (logFC ≥ 2; adj-pvalue ≤ 0.01). Gene ontology analysis revealed enrichment of mitotic cell cycle, tube morphogenesis and cell development pathways (Fig. 2 A), consistent with previous reports linking abortive mitosis and incomplete cytokinesis to the multinucleated phenotype of HRS cells ( 33 , 34 ). GSEA further demonstrated enrichment of hallmark pathways dysregulated in cHL, including G2M checkpoint, IL2-STAT5 signaling, MYC targets, TNFa signaling via NFKB and inflammatory response (Fig. 2 B-C). Transcription factor target analysis highlighted over-representation of cHL-associated regulators, particularly E2F and NFKB family members (Fig. 2 D) ( 35 , 36 ). Together, these results validate our analytical approach and confirm that the transcriptional profile of HRS cells is consistent with established features of cHL. Beyond these expected findings, our analysis uncovered novel pathway enrichment in HRS cells. Specifically, GSEA revealed significant upregulation of the unfolded protein response (UPR), a pathway not previously associated with cHL (Fig. 2 B, 2 E-F). To assess whether UPR activation is unique to HRS cells, we evaluated UPR signature expression in DLBCL using established gene sets ( 11 , 12 , 17 , 18 ). Multiple myeloma (MM), a plasma cell malignancy characterized by strong UPR activity, was included as positive control. As expected, MM samples exhibited elevated UPR signature scores and increased expression of UPR-related genes ( Supplementary Figure S2 A-C ). In contrast, neither subtype of DLBCL, including activated B-cell (ABC) or germinal center B-cell (GCB), exhibited consistent evidence of UPR activation ( Supplementary Figure S2 B-D ). Among the top upregulated UPR genes, we identified PDIA6, an endoplasmic reticulum-localized disulfide isomerase essential for protein folding and prevention of aggregation through catalysis of disulfide bond formation and breakage (Fig. 2 F-G). Immunohistochemistry (IHC) for PDIA6 in cHL cases 2–10, as well as a tissue microarray of 16 additional cases, demonstrated strong and specific staining in HRS cells in all cases with minimal background in surrounding lymphoid cells (Fig. 2 H). Staining intensity was comparable to, or greater than, that observed in residual plasma cells, which are characterized by high UPR activity. Apart from plasma cells, which are easily recognized morphologically, PDIA6 expression was highly specific for HRS cells, indicating its potential as a sensitive and specific diagnostic marker for cHL. Downregulation of NK cell recognition pathways in HRS cells We next examined genes downregulated in HRS cells relative to intra-tumoral B cells (logFC≤-2; adj-pval ≤ 0.01). As expected, GSEA and GO analysis revealed suppression of immune regulatory pathways, including B cell receptor signaling, antigen processing and presentation, and B cell activation, processes known to be impaired in HRS cells (Fig. 3 A, Figure S3A-C ). Transcription factor target analysis further supported these findings, revealing reduced activity of key B cell regulators such as IRF8, PAX5 and POU2F2, consistent with the dedifferentiated phenotype of HRS cells ( Figure S3D ). Beyond these established findings, GSEA identified novel downregulated pathways, particularly those related to leukocyte activation and degranulation (Fig. 3 A). Cell type-specific signature analysis highlighted marked suppression of natural killer (NK) cell-mediated cytotoxicity, with consistent downregulation of genes involved in cytotoxicity, leukocyte-mediated killing and immune cell effector function (Fig. 3 B-D). Given the central role of the signaling lymphocytic activation molecule family (SLAMF) receptors in NK cell function, we examined their expression in HRS cells. Six of nine activating SLAM family receptors - SLAMF2 ( CD48 ), SLAMF3 ( LY9 ), SLAMF4 ( CD244 ), SLAMF5 ( CD84 ), SLAMF6 and SLAMF7 – were significantly downregulated on HRS cells (Fig. 3 E-F), suggesting that reduced expression of these ligands may contribute to NK cell evasion. Flow cytometry confirmed loss of CD48 (SLAMF2) in both cell lines and five primary cases (Fig. 3 G ) . In parallel, NK cell frequencies were significantly reduced in cHL tumors compared to reactive lymph nodes (median 0.6% vs. 1.4%, p < 0.01) (Fig. 3 H). Finally, IHC validated consistent loss of CD48 across all sequenced cases (cases 2–10) and 22 additional specimens (Fig. 3 I). Comparative transcriptomic analysis of cHL reveals key similarities to CD30 + B cells, and both normal and malignant plasma cells. We found that HRS cells exhibit upregulation of the UPR signaling, a hallmark of plasma cells, raising the question of which B cell subset they most closely resemble transcriptomically. Previous studies suggested that HRS cells may originate from CD30 + cells within the germinal center ( 7 ). To test this, we compared the published CD30 + B cell gene signature ( 7 ) to our HRS samples. Indeed, genes upregulated in CD30 + cells were significantly enriched (NES:2.21; p-val:0.000) ( Figure S4A ). To further examine relationships with other non-malignant B cell subsets, we analyzed the top 200 genes upregulated in HRS cells relative to intra-tumoral B cells across diverse B cell populations. Consistent with UPR signaling, the HRS signature was significantly enriched in bone marrow plasma cells (BMPCs), but not in tonsillar plasma cells, despite their shared plasma cell identity (Fig. 4 A). Cibersortx deconvolution further demonstrated that HRS cells exhibit a transcriptomic profile more like BMPCs and GCBs than other B cell subsets (Fig. 4 B-C, S4B). Given the overlap between HRS cells and plasma cell programs, we next examined HRS signature expression in MM. Genes upregulated in HRS relative to intra-tumoral B cells were significantly enriched in MM compared with GCBs (NES: 1.64; p = 0.002), while genes downregulated in HRS were negatively enriched in MM (NES: -2.45, p = 0.000) (Fig. 4 D). Virus discovery Having defined the transcriptional landscape of HRS cells and their relationship to plasma cells, we next asked whether known and unknown infectious agents contribute to cHL pathogenesis. To address this, we screened HRS cells (cases 2–9) and four cell lines using the Pandora( 37 ), and Virdetect pipeline ( 38 ). Epstein-Barr virus (EBV) was detected only in case 8, yielding 19 contigs (> 500bp, max 1829bp) with expression of LMP1 and LMP2 , consistent with latency II pattern ( Figure S5 ). The only other virus identified was bovine viral diarrheal virus (BVDV), detected in HRS cells of (cases 2–4) and B cells (cases 3 and 7), likely reflecting fetal calf serum contamination ( Supplementary Datatable S5 ). Low-stringency alignment of non-human contigs revealed no credible novel viral sequences, suggesting undiscovered viruses in cHL are either rare or highly divergent. Comparative transcriptomic analysis of cHL reveals key differences between cHL and PMBL Having established the transcriptional landscape of HRS cells and confirmed a limited contribution from viral infection, we next compared HRS gene expression profiles with PMBL to define shared and distinct molecular features between these related B cell malignancies. cHL and PMBL share clinical and pathological features, including GCB-cell origin and overlapping mutational landscapes ( 8 , 9 , 16 , 18 , 39 , 40 ). However, they exhibit distinct clinical behavior and histology, making a comparative analysis critical to understanding the transcriptional programs underlying both their commonalities and differences. To delineate the transcriptional programs distinguishing these entities, we compared the transcriptomes of HRS cells, intra-tumoral B cells and 40 PMBL samples. Unsupervised clustering positioned PMBL samples between intra-tumoral B cells and HRS cells, (Fig. 5 A). As the sequencing of HRS and PMBL cases was performed independently, we compared expression using log fold-change (logFC) of HRS vs intra-tumoral B cells relative to mean PMBL expression. This identified four major categories: 1523 genes upregulated in HRS and highly expressed in PMBL samples; 1585 genes downregulated in HRS and lowly expressed in PMBL; 2131 genes upregulated in HRS but lowly expressed in PMBL; and 2193 genes downregulated in HRS but highly expressed in PMBL (Fig. 5 B). Among the top 20 genes downregulated in HRS but highly expressed in PMBL were LMO2, a GCB-associated gene, and TNFRFS17 (encoding BCMA), a plasma cell marker. IHC confirmed robust expression of BCMA and LMO2 in PMBL cases (BCMA 37/45, LMO2 41/41), but absence in HRS cells from cHL biopsies (BCMA 0/17; LMO2 0/15) (Fig. 5 C ). GO analysis of genes downregulated in HRS but highly expressed in PMBL highlighted BCR signaling, immune regulation, leukocyte activation and cytokine signaling pathways (Fig. 5 D). ssGSEA analysis corroborated immune activation in both malignancies, but at significantly lower levels in HRS. Consistent with our earlier finding that HRS cells suppress NK-mediated cytotoxicity via downregulation of SLAMF receptors, we observed broad downregulation of NK cytotoxicity genes in HRS compared with PMBL (Fig. 5 F). Except for SLAMF4 (CD244), which is expressed at low levels in PMBL, all other SLAMF receptors (CD48, CD84, LY9, SLAMF6 and SLAMF7) are highly expressed in PMBL (Fig. 5 G). IHC for CD48 validated these results: in PMBL, 36 cases showed strong positivity (in > 50% of the tumor cells), 6 cases showed partial positivity (5–50% of tumor cells) and 2 cases were negative. In contrast, in 22 cHL cases were negative for CD48 expression in HRS cells (Fig. 5 H). Conversely, genes upregulated in HRS but lowly expressed in PMBL were enriched for developmental and microtubule cytoskeletal pathways (Fig. 5 I). ssGSEA analysis confirmed a significant enrichment of microtubule cytoskeleton organization in HRS relative to PMBL (Fig. 5 J), consistent with their aberrant mitotic progression and characteristic multinucleated morphology, which is largely absent in PMBL. DISCUSSION We present the first RNA sequencing dataset of HRS cells isolated from primary cases of cHL, providing an integrated view of their transcriptional programs relative to intra-tumoral B cells, other B cell malignancies and plasma cell populations. Our transcriptomic analysis reveals that HRS shares greater similarity with plasma cells than with mature B cells and exhibits features reminiscent of plasma cell malignancies such as MM. While prior studies have established a GCB cell origin for cHL, supported by the presence of ongoing somatic hypermutation ( 41 – 44 ), our findings provide molecular evidence for partial plasmacytic differentiation, extending prior immunohistochemical observations of abortive plasma cell features in HRS cells ( 45 , 46 ). HRS cells show widespread downregulation of B cell identity genes, including BCR components and transcription factors such as PAX5 and IRF8. At the same time, they display features of incomplete plasma cell differentiation, including expression of IRF4/MUM1, but relatively low levels of PRDM1/BLIMP1 and absence of CD138 in most cases, although exceptions have been reported ( 47 , 48 ). This imbalance likely explains the paradox of robust UPR activation despite the absence of immunoglobulin production. Comparison with MM further underscores the aberrant plasmacytic features of HRS cells. Like MM, HRS cells show strong UPR activation, including overexpression of XBP1, ATF6 and other UPR components ( 49 ). However, unlike MM, HRS cells fail to undergo full plasma cell maturation, lacking consistent CD138 expression and immunoglobulin secretion. Thus, cHL appears locked in a non-productive, partially plasmacytic state. While plasma cell differentiation in MM is tightly coupled to BLIMP1 activity, in cHL UPR activation appears to arise through alternative mechanisms, possibly linked to FOXO1 downregulation ( 23 , 50 ). Among UPR genes, PDIA6 was consistently overexpressed and highly specific to HRS cells and plasma cells within cHL biopsies, suggesting a potential role as a diagnostic marker. These findings support a model in which HRS cells aberrantly exit the germinal center through an abortive plasma cell differentiation program further compromised by failure to express immunoglobulin. Consistent with this, HRS cells show greater transcriptional similarity to BMPCs than to tonsil plasma cells, aligning with the notion that BMPCs arise from cells that have transited through the germinal center ( 51 ). Interestingly, the dissociation we previously reported between the canonical AID signature and SBS9 signature in cHL, where AID is present but SBS9 is absent, was again observed here ( 9 ). Although SBS9 was initially attributed to non-canonical AID activity, recent studies link it to replicative stress in GCB cells ( 52 ). Such dissociation, though rarely seen in B cell lymphomas, occurs in a subset of MM cases with MAF rearrangements ( 53 ), suggesting that cHL and certain MM subsets may share aberrant GC exit mechanisms. Our comparative transcriptomic analysis highlights both shared and divergent features between cHL and PMBL. Both malignancies activate proliferative and oncogenic pathways, but HRS cells are distinguished by a more profound loss of B cell identity, absence of GCB-associated genes such as LMO2 and enrichment for cytoskeletal and mitotic programs consistent with their multinucleated morphology. Unlike PMBL, HRS cells do not express LMO2 nor BCMA, reinforcing the notion that the two tumors diverge at the level of differentiation despite overlapping mutational landscapes. Furthermore, HRS cells display unique enrichment of neuronal and cytoskeletal gene programs, reflecting possible lineage infidelity or aberrant differentiation processes not observed in other B cell malignancies. Our dataset also refines the immune evasion strategies of HRS cells. In addition to impaired antigen presentation through B2M mutations ( 8 ), overexpression of checkpoint ligands (PDL1, PDL2 and TIM3), and secretion of immunosuppressive cytokines, we identify a novel mechanism - loss of NK cell-mediated cytotoxicity. Specifically, downregulation of multiple SLAM family ligands, including CD48, was observed in both primary HRS cells and cell lines and validated at the protein level. This suppression coincided with significantly reduced NK cell infiltration in cHL tumors compared with reactive lymph nodes, suggesting spatial exclusion of NK cells as an additional immune evasion strategy. Taken together with frequent loss of MHC class I, these findings indicate that HRS cells evade both T cell and NK cell mediated surveillance, offering a more comprehensive view of their immune escape repertoire. This finding has therapeutic implications, as CAR-NK strategies are now entering clinical development. Finally, we investigated the possibility of viral involvement in cHL pathogenesis beyond EBV. Our unbiased viral search revealed no novel viral sequences, and EBV transcripts were detected only in known EBV-positive cases ( 54 – 56 ). This is consistent with the prevailing model in which EBV contributes to cHL pathogenesis through NFKB activation in a subset of cases, while EBV-negative disease relies on somatic alterations, such as mutations in TNFAIP3 (A20), to activate similar pathways ( 8 , 9 , 57 ). Thus, EBV positive tumors rely on viral oncogenic programs, whereas EBV-negative tumors acquire genetic lesions to converge on similar signaling outcomes. In summary, our findings refine the molecular identity of HRS cells as aberrantly differentiated GCB-derived cells with plasmacytic features, robust UPR activation, and unique immune evasion strategies. The distinction from PMBL underscores the divergent transcriptional trajectories of related B cell lymphomas, while transcriptomic similarities to MM highlight a shared yet incomplete plasmacytic program. The identification of UPR activation and NK cell evasion as defining features of HRS cells points to potential diagnostic markers and novel therapeutic vulnerabilities in cHL. Declarations ACKNOWLEDGEMENTS This project was supported by the Department of Pathology and Laboratory Medicine of Weill Cornell Medicine and its Center for Translational Pathology. It was funded in part by NIH grant R01-CA068939 to EC. JR was partially funded by the Tri-I Training Program in Computational Biology and Medicine (5T32GM083937). MR and JR were supported by MSK Cancer Center Support Grant/Core Grant (P30 CA008748). AUTHORSHIP CONTRIBUTIONS EC, MR, and LGR conceived of the experiments, advised on every aspect, conducted validation experiments and wrote the manuscript; MR and JR sorted primary cases, optimized and constructed libraries. JR, IYK, WD, FW, SZ, BB, and AC analyzed data with LM, OE, and RR. JB, SIP, AEK, MJO, NG, MSL, MJB contributed patient samples. All authors reviewed the manuscript. 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Additional Declarations There is NO conflict of interest to disclose. Supplementary Files SupplementaryDatatablesBCG.xlsx Supplemental datatables RNAseqsupplementalmethodstablesandfiguresforBCGFinal.docx Supplemental methods and figures Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: revise 16 Jan, 2026 Review # 2 received at journal 20 Dec, 2025 Reviewer # 2 agreed at journal 12 Dec, 2025 Reviewer # 1 agreed at journal 24 Nov, 2025 Reviewers invited by journal 03 Nov, 2025 Editor assigned by journal 27 Oct, 2025 Submission checks completed at journal 27 Oct, 2025 First submitted to journal 26 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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14:50:31","extension":"xml","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":139604,"visible":true,"origin":"","legend":"","description":"","filename":"25BCJ12750structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7957952/v1/35579050e36fdd113f5634c3.xml"},{"id":95845703,"identity":"8d7b539c-0940-4b8e-a6a6-12c7c748ac12","added_by":"auto","created_at":"2025-11-13 14:50:31","extension":"html","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":155214,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7957952/v1/e0858eca93d4ade568967847.html"},{"id":95845681,"identity":"e1c5127d-195d-4ac9-9f3d-8dae171bcfa4","added_by":"auto","created_at":"2025-11-13 14:50:30","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1837853,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistinct gene expression profiles of HRS cells compared to intra-tumoral B cells.\u003c/strong\u003e (\u003cstrong\u003eA\u003c/strong\u003e) Principal component analysis (PCA) of gene expression profiles from HRS cell populations from 18 primary cHL cases (red) and intratumoral B cells from 17 primary cHL cases (blue) and four HL cell lines (KMH2, HDLM2, L1236, and L428) (green). (\u003cstrong\u003eB\u003c/strong\u003e) Unsupervised hierarchical clustering of the differentially expressed genes between HRS and intra-tumoral B cells. Colors in \u003cstrong\u003eB\u003c/strong\u003erepresents relative expression: red indicates higher and blue indicates lower expression relative to the gene’s mean. (\u003cstrong\u003eC\u003c/strong\u003e) Volcano plot for genes that are differentially regulated between HRS and intratumoral B cells.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7957952/v1/80902093ec045e73a3b8ec74.png"},{"id":95845684,"identity":"eed223e3-c66e-4bda-816d-e7f8dd9a1364","added_by":"auto","created_at":"2025-11-13 14:50:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":5239617,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eUpregulation of the unfolded protein response (UPR) in HRS cells. \u0026nbsp;(A) \u003c/strong\u003eGene ontology analysis for genes that are significantly upregulated in HRS in comparison to intra-tumoral B cells (logFC≥2; adj-pval≤0.05). (\u003cstrong\u003eB\u003c/strong\u003e) Ten Hallmark pathways identified by GSEA for genes that are differentially regulated between HRS and intra-tumoral B cells. (\u003cstrong\u003eC\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eGSEA of NFKB signaling pathway. (\u003cstrong\u003eD\u003c/strong\u003e) Transcription factor target over-representation analysis was performed using ChIP-X Enrichment Analysis version 3 (ChEA3) for genes that are upregulated in HRS in comparison to intra-tumoral B cells (adj-p≤0.001, logFC≥2.32). (\u003cstrong\u003eE\u003c/strong\u003e) GSEA for the unfolded protein response (Broad Institute MSigDB: HALLMARK_UNFOLDED_PROTEIN_RESPONSE) comparing HRS cells to intra-tumoral B cells. (\u003cstrong\u003eF\u003c/strong\u003e) Heatmap of differentially regulated UPR genes between HRS and intra-tumoral B cells (adjp≤0.05; logFC ≥ 1 or logFC ≤ -1) based on UPR gene signature in \u003cstrong\u003eB\u003c/strong\u003e. Colors represent relative expression: red indicates higher and blue indicates lower expression relative to the gene’s mean. (\u003cstrong\u003eG\u003c/strong\u003e) Transcript expression of PDIA6 in intra-tumoral B cells (gray) and HRS cells (blue), with adjusted-p value determined using limma-voom. (\u003cstrong\u003eH\u003c/strong\u003e) Immunohistochemistry for PDIA6 in two representative cHL cases. Original magnification: 60X.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7957952/v1/3eec05db03c26dd36ee8ca01.png"},{"id":95845682,"identity":"aed59d20-cd0c-45f8-ab6a-aed952e1a891","added_by":"auto","created_at":"2025-11-13 14:50:30","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2442524,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDownregulation of NK cell recognition pathways in HRS cells. \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e) 15 downregulated biological processes identified between HRS and intra-tumoral B cells.\u003cstrong\u003e \u003c/strong\u003eGSEA for (\u003cstrong\u003eB\u003c/strong\u003e) KEGG natural killer cell mediated cytotoxicity, (\u003cstrong\u003eC)\u003c/strong\u003e GOBP Leukocyte mediated cytotoxicity and (\u003cstrong\u003eD\u003c/strong\u003e) GOBP Cell killing pathways comparing HRS to intra-tumoral B cells. NES represents normalized enrichment score. (\u003cstrong\u003eE\u003c/strong\u003e) Heatmap displaying differential expression of SLAMF receptors in HRS vs intra-tumoral B cells (adjp≤0.001, logFC≤-1).Colors represent relative expression: red indicates higher and blue indicates lower expression relative to the gene’s mean. \u003cstrong\u003e(F) \u003c/strong\u003eNormalized expression of SLAMF receptor expression for HRS and intra-tumoral B cells. \u0026nbsp;\u003cstrong\u003e(G) \u003c/strong\u003eFlow cytometry analysis of CD48 expression on CD30+ HRS cells (red) compared to CD30- cells in a primary cHL specimen.\u003cstrong\u003e (H) \u003c/strong\u003eFlow cytometry quantification of NK cell proportions in cHL (N=48) and normal lymph nodes (N=10) samples.\u003cstrong\u003e (I) \u003c/strong\u003eImmunohistochemistry for CD48 across two representative cHL cases. Original magnification: 60X.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7957952/v1/3445b1bc6f743e5ac0a883fb.png"},{"id":96240264,"identity":"f064ad39-d490-4367-bead-87c0fbcd35de","added_by":"auto","created_at":"2025-11-19 07:08:43","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1133973,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparative transcriptomic analysis of HRS cells suggests a germinal center-derived origin and similarities to plasma cell lineages.\u003c/strong\u003e (\u003cstrong\u003eA\u003c/strong\u003e) ssGSEA analysis of the HRS signature (top 200 upregulated in HRS vs intra-tumoral B cells) across different B cell subsets (BMPC: bone marrow plasma cells; CB: centroblasts; CC: centrocytes; GCB: germinal center B cells; Memory: memory B cells; Naïve: naïve B cells; TPC: tonsil plasma cells). * Indicates statistical significance of the HRS signature enrichment compared to the background distribution generated from 100 random gene signatures. (\u003cstrong\u003eB\u003c/strong\u003e) Cibersortx analysis estimating the contribution of bone marrow plasma cells (BMPC), germinal center B cells (GCB) and naïve B cells signatures in HRS cells, intra-tumoral B cells and HL cell lines. (\u003cstrong\u003eC\u003c/strong\u003e) Estimated abundance of BMPC signature in HRS cells, intra-tumoral B cells and HL cell lines. (\u003cstrong\u003eD\u003c/strong\u003e) GSEA for top 200 upregulated and downregulated genes in HRS vs intra-tumoral B cells in multiple myeloma (MM) samples. NES in \u003cstrong\u003eE\u003c/strong\u003e represents normalized enrichment score.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7957952/v1/82521723fc84a750ec29bad7.png"},{"id":95845690,"identity":"6dfb7350-a01d-4c52-81f0-92f795c8b7fb","added_by":"auto","created_at":"2025-11-13 14:50:31","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":9001207,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparative transcriptomic analysis of HRS cells and primary mediastinal B-cell lymphoma (PMBL). \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e) MDS plot of Top 1000 DEGs for primary HRS, intra-tumoral B cells and PMBL cells. (\u003cstrong\u003eB\u003c/strong\u003e) Scatter plot for logFC expression between HRS and intra-tumoral B vs mean PMBL expression. Purple: downregulated in HRS vs intra-tumoral B, highly expressed in PMBL, with and LMO2 and BCMA (TNFRSF17) highlighted in red boxes. Red: upregulated in HRS vs intra-tumoral B, highly expression in PMBL. Blue: downregulated in HRS vs intra-tumoral B, lowly expressed in PMBL. Orange: upregulated in HRS intra-tumoral B, lowly expressed in PMBL. Top 20 discordant genes in each direction are labeled. (\u003cstrong\u003eC\u003c/strong\u003e) IHC for LMO2 (cytoplasmic, top panels) and BCMA (nuclear, bottom panels) for cHL and PMBL tumors. HRS cells are depicted by red arrows. Cases were those included in a tissue microarray and only considered evaluable among the cHL cases if internal non-tumoral positive control cells were present. (\u003cstrong\u003eD\u003c/strong\u003e) GO analysis of genes downregulated in HRS vs intra-tumoral B cells but highly expressed in PMBL. ssGSEA analysis of (\u003cstrong\u003eE\u003c/strong\u003e) immune activation and (\u003cstrong\u003eF\u003c/strong\u003e) NK-mediated cytotoxicity for HRS and PMBL samples. (\u003cstrong\u003eG\u003c/strong\u003e) Scatter plot of logFC between HRS and intra-tumoral B versus mean PMBL expression, highlighting SLAMF receptor family genes. (\u003cstrong\u003eH\u003c/strong\u003e) IHC for CD48 (cytoplasmic) for cHL and PMBL tumors. HRS cells are depicted by red arrows. (\u003cstrong\u003eI\u003c/strong\u003e) GO analysis of genes upregulated in HRS vs intra-tumoral B cells but lowly expressed in PMBL. (\u003cstrong\u003eJ\u003c/strong\u003e) ssGSEA analysis of microtubule cytoskeleton organization for HRS and PMBL samples. Original magnification for \u003cstrong\u003eC\u003c/strong\u003eand \u003cstrong\u003eH\u003c/strong\u003e was 60x.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7957952/v1/bd38144828cf67eaab0e3f94.png"},{"id":96708085,"identity":"51542e51-12c0-49f6-97fc-5e218c49e51d","added_by":"auto","created_at":"2025-11-25 09:56:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":19554473,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7957952/v1/2b8bdd9e-c6b9-4365-8932-5adb2fb4bc18.pdf"},{"id":95845687,"identity":"312ab684-e2d0-4b9e-b075-86090137d6ab","added_by":"auto","created_at":"2025-11-13 14:50:30","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":7745274,"visible":true,"origin":"","legend":"Supplemental datatables","description":"","filename":"SupplementaryDatatablesBCG.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7957952/v1/d7912fb1f984dfa5fda500de.xlsx"},{"id":96240511,"identity":"5edbdaae-79ae-4f1d-8d28-b3b62b62d534","added_by":"auto","created_at":"2025-11-19 07:09:01","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":31710648,"visible":true,"origin":"","legend":"Supplemental methods and figures","description":"","filename":"RNAseqsupplementalmethodstablesandfiguresforBCGFinal.docx","url":"https://assets-eu.researchsquare.com/files/rs-7957952/v1/df79bf8df1679d82a4c07116.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"Transcriptome sequencing of Hodgkin lymphoma Hodgkin and Reed-Sternberg cells reveals escape from NK cell recognition and an unfolded protein response","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eHodgkin and Reed-Sternberg (HRS) cells, the malignant cells of classic Hodgkin lymphoma (cHL) are rare and embedded within a dense infiltrate of benign immune and stromal cells, with \u0026gt;\u0026thinsp;99% of bulk lymph node derived from non-neoplastic cells (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). This complicates isolation of tumor-specific nucleic acids, which requires enrichment of HRS cells. Limited availability of pure HRS cells has historically hindered comprehensive molecular characterization. Cultured cHL cell lines have served as surrogates, revealing distinct gene expression profiles from normal B cells and other B cell lymphomas, including recurrent CIITA gene fusions in a subset of cases (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Studies of microdissected HRS cells identified chromosomal imbalances and transcriptional differences, notably downregulation of genes regulating cytokinesis and genomic stability, which may contribute to their multinucleated, genomically unstable phenotype (\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOur group previously performed whole exome and genome sequencing of purified HRS cells, identifying somatic mutations, indels and copy number alterations, and mapping the evolutionary timing of these events in pediatric and adult cHL (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). These analyses showed that some alterations arise before germinal center entry, while others occur early within the germinal center, but terminal HRS cells do not complete the full germinal center program, as evidenced by the absence of SBS9 mutational signature seen in other germinal center-derived lymphomas. Characterization of HRS DNA from cell lines, primary tissue (including from subsequent studies using flow-sorted HRS cells) and circulating tumor DNA revealed a spectrum of mutations overlapping with diffuse large B cell lymphomas (DLBCL) and primary mediastinal B cell lymphomas (PMBL) (\u003cspan additionalcitationids=\"CR11 CR12 CR13 CR14 CR15 CR16 CR17 CR18 CR19 CR20\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBased on these findings, we hypothesized that the HRS transcriptome could explain at least some of the major differences between these related malignancies. To address this, we performed whole-transcriptome sequencing of HRS cells from primary cases, matched intra-tumoral B cells, and four HL cell lines, compared with 40 PMBL cases. Our analysis reveals that HRS cells exhibit abortive plasma cell differentiation with elevated unfolded protein response, alongside novel alterations in oncogenic, mitotic and immune evasion pathways, providing molecular insight into the unique biology of cHL.\u003c/p\u003e"},{"header":"MATERIALS/SUBJECTS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eTissue specimens\u003c/h2\u003e\u003cp\u003eEighteen cHL cases underwent RNA sequencing, including cases previously reported for exome sequencing (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) and by Maura \u003cem\u003eet al\u003c/em\u003e. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Specimens originated from Weill Cornell Medical College, Mount Sinai Medical Center, Children\u0026rsquo;s Hospital of Los Angeles, Children\u0026rsquo;s Healthcare of Atlanta, Children\u0026rsquo;s Hospital of Philadelphia, Roswell Park Cancer Center, and Memorial Sloan Kettering Cancer Center. Case 1 from the prior study(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) lacked residual material, and was excluded, though numbering was preserved for consistency. Seventeen cases (\u003cspan additionalcitationids=\"CR3 CR4 CR5 CR6 CR7 CR8 CR9 CR10 CR11 CR12 CR13 CR14 CR15 CR16 CR17\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) had paired intra-tumoral B cell cells, and one (case 19) did not. Cohort size was limited by availability of fresh-frozen viable cell suspensions and HRS cell recovery. Specimens were mechanically dissociated and cryopreserved after lymph node biopsy. Formalin-fixed paraffin-embedded (FFPE) biopsies were used for immunohistochemical validation. For comparison, we performed RNA sequencing on 40 PMBL cases, using tissue from FFPE blocks. All PBCL cases were obtained at Weill Cornell. All cHL and PMBL were deidentified and obtained with IRB approval.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eImmunohistochemistry\u003c/h3\u003e\n\u003cp\u003eIHC was performed on tissue sections (cases 2\u0026ndash;10), a cHL microarray containing 16 additional cases and a PMBL TMA containing 50 cases. Immunohistochemical staining was done using the procedures and antibodies described in the Supplementary Methods.\u003c/p\u003e\n\u003ch3\u003eCell Sorting\u003c/h3\u003e\n\u003cp\u003eHRS cells and intra-tumoral B cells were isolated from cHL tissues by FACS, as described (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Briefly, thawed cell suspensions were washed in RPMI 1640/20% FBS containing DNase A, stained for 15 minutes on ice with an antibody panel CD64-FITC(22, Beckman Coulter (BC), Miami FL), CD30-PE (BerH83, Beckton-Dickinson (BD), San Jose, CA, RRID:AB_400238), CD5-ECD (BL1a, BC, RRID:AB_3678603), CD40-PE-Cy5.5 (custom conjugate, gift of Jonathan Fromm) or CD40-PerCP-eFluor 710 (1C10, Ebiosciences, San Diego, CA), CD20-PC7 (B9E9, BC), CD15-APC (HI98, BD, RRID:AB_10893192), CD45 APC-H7 (2D1,BD, RRID:AB_1645480) or CD45-Krome Orange (J.33, BC, RRID:AB_2888654), and CD95-Pacific Blue (DX2, Life Technologies, Grand Island, NY), resuspended in FACS buffer. Sorting was performed on a FACSAria (130\u0026micro;m nozzle, 12 psi) to separate HRS, B, and T cells. Sorted cells were collected in N-2-hydroxyethylpiperazine-N\u0026rsquo;-2-ethanesulfonic acid buffer solution containing 50% FBS.\u003c/p\u003e\n\u003ch3\u003eFlow cytometry\u003c/h3\u003e\n\u003cp\u003eNK cells were quantified in 43 cHL tumors and 10 reactive nodes using a panel including CD45, CD7, CD3 and CD56 (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). NK cells were defined as CD7\u003csup\u003e+\u003c/sup\u003eCD56\u003csup\u003e+\u003c/sup\u003eCD3\u003csup\u003e-\u003c/sup\u003e mononuclear cells. Differences were assessed with two-tailed Student t-test (Excel, Microsoft, Bellevue, WA, RRID:SCR_016137). CD48 expression (clone TU145, BD, RRID:AB_396099) was analyzed on primary HRS cells was examined in 5 cases using a panel containing CD30, CD15, CD20, CD40, CD3, CD95, CD64, and CD45, as previously described (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eRNA Extraction, Library Construction and Next-Generation Sequencing\u003c/h3\u003e\n\u003cp\u003ecHL: Flow-sorted cHL cells were pelleted, washed and RNA extracted using Arcturus PicoPure RNA Isolation kit (KIT0204, Life Technologies, Carlsbad, CA) with RNAse-Free DNase (79254, Qiagen, Venlo, Netherlands) treatment. RNA quality and concentration were assessed with Bioanalyzer RNA Pico (5067\u0026thinsp;\u0026minus;\u0026thinsp;1513, Agilent, Santa Clara, CA). Libraries were prepared from 1-4ng total RNA using the SMARTer Ultra Low Input RNA Kit (Clontech, Mountain View, CA), followed by Illumina-compatible library construction with the KAPA LTP kit (KK8221, Woburn, MA). Libraries were sequenced on Illumina HiSeq in paired-end 101bp mode. Data are deposited in NCBI GEO (accession: GSE301492).\u003c/p\u003e\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003ePMBL\u003c/span\u003e: Total RNA was extracted from FFPE tissue sections using an in-house bead-based protocol. A 10% MCT solution (Nature\u0026rsquo;s Way coconut oil, NaOH) was prepared to generate a proteinase K mix for deparaffinization. Samples were incubated at 56C for 1 hour with intermittent shaking (30s at 1000rpm every 5 minutes). After incubation, the supernatant (RNA-containing fraction) and treated with DNase. RNA was subsequently purified using 0.8x SPRI beads (Agencourt AMPure XP Beads (Beckman Coulter, A63882) and eluted in nuclease-free water. Pooled RNA libraries were prepared using the KAPA Stranded RNA-Seq Kit library preparation kit (Roche 07962169001) and xGen Hybridization and Capture kit (IDT 1080577) in accordance with the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eDifferential Gene expression analysis\u003c/h2\u003e\u003cp\u003eRaw data were mapped to the human genome GRCh38 using HISAT2. FeatureCounts from the Rsubread package (version1.24.7) was used for read counting after which genes without a counts per million reads (CPM) in at least 3 samples were excluded from downstream analysis (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Count data were normalized using the trimmed mean of M-values (TMM) method and differential gene expression analysis was performed using the limma-voom pipeline (limma version 3.40.6) (\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). GSEA-4.3.2 was used for Gene set enrichment analysis (GSEA) (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). pheatmap and ggplot2 (version 3.2.1, RRID:SCR_014601) were used to plot the heatmap and cluster-specific trends (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Comparative analyses of PMBL, ABC-DLBCL and GCB-DLBCL expression profiles used the dataset of Rosenwald \u003cem\u003eet al.\u003c/em\u003e (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eData Input and Preprocessing and Methodology for Virus Identification\u003c/h3\u003e\n\u003cp\u003eThe computational methods used for this analysis are presented in the Supplementary Methods section.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eDistinct gene expression profiles of HRS cells compared to intra-tumoral B cells\u003c/h2\u003e\u003cp\u003eTo examine the transcriptome of HRS cells, we conducted bulk-RNA sequencing on primary HRS cells from 18 cHL cases, including paired intra-tumoral non-neoplastic B cells from 17 cases and four cHL cell lines (KMH2, HDLM2, L1236, and L428). Cases were numbered 2\u0026ndash;19, where 2 through 10 match those reported for exome sequencing (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) and 11\u0026ndash;16 and 19 those reported for exome or full genome sequencing (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) (\u003cb\u003eSupplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). Principal component analysis (PCA) and unsupervised clustering analysis revealed two distinct clusters, separating intra-tumoral B cells from both primary HRS cells and cHL cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA-B).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eComparative analysis between HRS cells and intra-tumoral B cells identified 2144 upregulated genes (logFC\u0026thinsp;\u0026ge;\u0026thinsp;2; adjp\u0026thinsp;\u0026le;\u0026thinsp;0.01) and 2451 downregulated genes (logFC\u0026ge;-2; adjp\u0026thinsp;\u0026le;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC, \u003cb\u003eSupplementary Datatable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e and S2\u003c/b\u003e). Based on these results, we defined the top 200 upregulated and top 200 downregulated genes (\u003cb\u003eSupplementary Datatable S3)\u003c/b\u003e. Similarly, we compared differentially expressed genes (DEGs) between HL cell lines and intra-tumoral B cells, as well as between primary HRS cells with HL cell lines (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA-B\u003c/b\u003e). Although cHL cell lines and primary HRS cells clustered together in the PCA plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), a substantial number of DEGs were observed between the two groups (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eD\u003c/b\u003e), indicating that in vitro cell lines only partially recapitulate the transcriptional landscape of primary HRS cells, potentially due to adaptation to culture conditions and loss of microenvironmental cues.\u003c/p\u003e\u003cp\u003eOur results were compared with published Affymetrix array profiles of microdissected HRS cells (29 cases, 5 cell lines)(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Despite platform differences, gene-level fold changes were strongly concordant (Pearsons's coefficient 0.86; Spearman\u0026rsquo;s correlation 0.73), with only 20 genes showing discordant direction (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eC-D\u003c/b\u003e, \u003cb\u003eSupplementary Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e\u003c/b\u003e). Compared to arrays, RNA-sequencing in this study provided greater sensitivity and dynamic range.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eHRS cells exhibit an unfolded protein response\u003c/h2\u003e\u003cp\u003eWe first examined genes significantly upregulated in HRS cells compared to intra-tumoral B cells (logFC\u0026thinsp;\u0026ge;\u0026thinsp;2; adj-pvalue\u0026thinsp;\u0026le;\u0026thinsp;0.01). Gene ontology analysis revealed enrichment of mitotic cell cycle, tube morphogenesis and cell development pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), consistent with previous reports linking abortive mitosis and incomplete cytokinesis to the multinucleated phenotype of HRS cells (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). GSEA further demonstrated enrichment of hallmark pathways dysregulated in cHL, including G2M checkpoint, IL2-STAT5 signaling, MYC targets, TNFa signaling via NFKB and inflammatory response (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB-C). Transcription factor target analysis highlighted over-representation of cHL-associated regulators, particularly E2F and NFKB family members (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD) (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Together, these results validate our analytical approach and confirm that the transcriptional profile of HRS cells is consistent with established features of cHL.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eBeyond these expected findings, our analysis uncovered novel pathway enrichment in HRS cells. Specifically, GSEA revealed significant upregulation of the unfolded protein response (UPR), a pathway not previously associated with cHL (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE-F). To assess whether UPR activation is unique to HRS cells, we evaluated UPR signature expression in DLBCL using established gene sets (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Multiple myeloma (MM), a plasma cell malignancy characterized by strong UPR activity, was included as positive control. As expected, MM samples exhibited elevated UPR signature scores and increased expression of UPR-related genes (\u003cb\u003eSupplementary Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eA-C\u003c/b\u003e). In contrast, neither subtype of DLBCL, including activated B-cell (ABC) or germinal center B-cell (GCB), exhibited consistent evidence of UPR activation (\u003cb\u003eSupplementary Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eB-D\u003c/b\u003e).\u003c/p\u003e\u003cp\u003eAmong the top upregulated UPR genes, we identified PDIA6, an endoplasmic reticulum-localized disulfide isomerase essential for protein folding and prevention of aggregation through catalysis of disulfide bond formation and breakage (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF-G). Immunohistochemistry (IHC) for PDIA6 in cHL cases 2\u0026ndash;10, as well as a tissue microarray of 16 additional cases, demonstrated strong and specific staining in HRS cells in all cases with minimal background in surrounding lymphoid cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH). Staining intensity was comparable to, or greater than, that observed in residual plasma cells, which are characterized by high UPR activity. Apart from plasma cells, which are easily recognized morphologically, PDIA6 expression was highly specific for HRS cells, indicating its potential as a sensitive and specific diagnostic marker for cHL.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eDownregulation of NK cell recognition pathways in HRS cells\u003c/h2\u003e\u003cp\u003eWe next examined genes downregulated in HRS cells relative to intra-tumoral B cells (logFC\u0026le;-2; adj-pval\u0026thinsp;\u0026le;\u0026thinsp;0.01). As expected, GSEA and GO analysis revealed suppression of immune regulatory pathways, including B cell receptor signaling, antigen processing and presentation, and B cell activation, processes known to be impaired in HRS cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, \u003cb\u003eFigure S3A-C\u003c/b\u003e). Transcription factor target analysis further supported these findings, revealing reduced activity of key B cell regulators such as IRF8, PAX5 and POU2F2, consistent with the dedifferentiated phenotype of HRS cells (\u003cb\u003eFigure S3D\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eBeyond these established findings, GSEA identified novel downregulated pathways, particularly those related to leukocyte activation and degranulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Cell type-specific signature analysis highlighted marked suppression of natural killer (NK) cell-mediated cytotoxicity, with consistent downregulation of genes involved in cytotoxicity, leukocyte-mediated killing and immune cell effector function (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB-D).\u003c/p\u003e\u003cp\u003eGiven the central role of the signaling lymphocytic activation molecule family (SLAMF) receptors in NK cell function, we examined their expression in HRS cells. Six of nine activating SLAM family receptors - \u003cem\u003eSLAMF2\u003c/em\u003e (\u003cem\u003eCD48\u003c/em\u003e), \u003cem\u003eSLAMF3\u003c/em\u003e (\u003cem\u003eLY9\u003c/em\u003e), \u003cem\u003eSLAMF4\u003c/em\u003e (\u003cem\u003eCD244\u003c/em\u003e), \u003cem\u003eSLAMF5\u003c/em\u003e (\u003cem\u003eCD84\u003c/em\u003e), \u003cem\u003eSLAMF6\u003c/em\u003e and \u003cem\u003eSLAMF7\u003c/em\u003e \u0026ndash; were significantly downregulated on HRS cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE-F), suggesting that reduced expression of these ligands may contribute to NK cell evasion. Flow cytometry confirmed loss of CD48 (SLAMF2) in both cell lines and five primary cases (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG\u003cb\u003e)\u003c/b\u003e. In parallel, NK cell frequencies were significantly reduced in cHL tumors compared to reactive lymph nodes (median 0.6% vs. 1.4%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eH). Finally, IHC validated consistent loss of CD48 across all sequenced cases (cases 2\u0026ndash;10) and 22 additional specimens (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eI).\u003c/p\u003e\u003cp\u003e\u003cb\u003eComparative transcriptomic analysis of cHL reveals key similarities to CD30\u003c/b\u003e\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e \u003cb\u003eB cells, and both normal and malignant plasma cells.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe found that HRS cells exhibit upregulation of the UPR signaling, a hallmark of plasma cells, raising the question of which B cell subset they most closely resemble transcriptomically. Previous studies suggested that HRS cells may originate from CD30\u003csup\u003e+\u003c/sup\u003e cells within the germinal center (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). To test this, we compared the published CD30\u003csup\u003e+\u003c/sup\u003e B cell gene signature (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) to our HRS samples. Indeed, genes upregulated in CD30\u003csup\u003e+\u003c/sup\u003e cells were significantly enriched (NES:2.21; p-val:0.000) (\u003cb\u003eFigure S4A\u003c/b\u003e). To further examine relationships with other non-malignant B cell subsets, we analyzed the top 200 genes upregulated in HRS cells relative to intra-tumoral B cells across diverse B cell populations. Consistent with UPR signaling, the HRS signature was significantly enriched in bone marrow plasma cells (BMPCs), but not in tonsillar plasma cells, despite their shared plasma cell identity (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Cibersortx deconvolution further demonstrated that HRS cells exhibit a transcriptomic profile more like BMPCs and GCBs than other B cell subsets (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB-C, S4B).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eGiven the overlap between HRS cells and plasma cell programs, we next examined HRS signature expression in MM. Genes upregulated in HRS relative to intra-tumoral B cells were significantly enriched in MM compared with GCBs (NES: 1.64; p\u0026thinsp;=\u0026thinsp;0.002), while genes downregulated in HRS were negatively enriched in MM (NES: -2.45, p\u0026thinsp;=\u0026thinsp;0.000) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eVirus discovery\u003c/h2\u003e\u003cp\u003eHaving defined the transcriptional landscape of HRS cells and their relationship to plasma cells, we next asked whether known and unknown infectious agents contribute to cHL pathogenesis. To address this, we screened HRS cells (cases 2\u0026ndash;9) and four cell lines using the Pandora(\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e), and Virdetect pipeline (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Epstein-Barr virus (EBV) was detected only in case 8, yielding 19 contigs (\u0026gt;\u0026thinsp;500bp, max 1829bp) with expression of \u003cem\u003eLMP1\u003c/em\u003e and \u003cem\u003eLMP2\u003c/em\u003e, consistent with latency II pattern (\u003cb\u003eFigure S5\u003c/b\u003e). The only other virus identified was bovine viral diarrheal virus (BVDV), detected in HRS cells of (cases 2\u0026ndash;4) and B cells (cases 3 and 7), likely reflecting fetal calf serum contamination (\u003cb\u003eSupplementary Datatable S5\u003c/b\u003e). Low-stringency alignment of non-human contigs revealed no credible novel viral sequences, suggesting undiscovered viruses in cHL are either rare or highly divergent.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eComparative transcriptomic analysis of cHL reveals key differences between cHL and PMBL\u003c/h2\u003e\u003cp\u003eHaving established the transcriptional landscape of HRS cells and confirmed a limited contribution from viral infection, we next compared HRS gene expression profiles with PMBL to define shared and distinct molecular features between these related B cell malignancies. cHL and PMBL share clinical and pathological features, including GCB-cell origin and overlapping mutational landscapes (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). However, they exhibit distinct clinical behavior and histology, making a comparative analysis critical to understanding the transcriptional programs underlying both their commonalities and differences.\u003c/p\u003e\u003cp\u003eTo delineate the transcriptional programs distinguishing these entities, we compared the transcriptomes of HRS cells, intra-tumoral B cells and 40 PMBL samples. Unsupervised clustering positioned PMBL samples between intra-tumoral B cells and HRS cells, (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). As the sequencing of HRS and PMBL cases was performed independently, we compared expression using log fold-change (logFC) of HRS vs intra-tumoral B cells relative to mean PMBL expression. This identified four major categories: 1523 genes upregulated in HRS and highly expressed in PMBL samples; 1585 genes downregulated in HRS and lowly expressed in PMBL; 2131 genes upregulated in HRS but lowly expressed in PMBL; and 2193 genes downregulated in HRS but highly expressed in PMBL (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Among the top 20 genes downregulated in HRS but highly expressed in PMBL were LMO2, a GCB-associated gene, and \u003cem\u003eTNFRFS17\u003c/em\u003e (encoding BCMA), a plasma cell marker. IHC confirmed robust expression of BCMA and LMO2 in PMBL cases (BCMA 37/45, LMO2 41/41), but absence in HRS cells from cHL biopsies (BCMA 0/17; LMO2 0/15) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eGO analysis of genes downregulated in HRS but highly expressed in PMBL highlighted BCR signaling, immune regulation, leukocyte activation and cytokine signaling pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). ssGSEA analysis corroborated immune activation in both malignancies, but at significantly lower levels in HRS. Consistent with our earlier finding that HRS cells suppress NK-mediated cytotoxicity via downregulation of SLAMF receptors, we observed broad downregulation of NK cytotoxicity genes in HRS compared with PMBL (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF). Except for SLAMF4 (CD244), which is expressed at low levels in PMBL, all other SLAMF receptors (CD48, CD84, LY9, SLAMF6 and SLAMF7) are highly expressed in PMBL (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG). IHC for CD48 validated these results: in PMBL, 36 cases showed strong positivity (in \u0026gt;\u0026thinsp;50% of the tumor cells), 6 cases showed partial positivity (5\u0026ndash;50% of tumor cells) and 2 cases were negative. In contrast, in 22 cHL cases were negative for CD48 expression in HRS cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH).\u003c/p\u003e\u003cp\u003eConversely, genes upregulated in HRS but lowly expressed in PMBL were enriched for developmental and microtubule cytoskeletal pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eI). ssGSEA analysis confirmed a significant enrichment of microtubule cytoskeleton organization in HRS relative to PMBL (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eJ), consistent with their aberrant mitotic progression and characteristic multinucleated morphology, which is largely absent in PMBL.\u003c/p\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eWe present the first RNA sequencing dataset of HRS cells isolated from primary cases of cHL, providing an integrated view of their transcriptional programs relative to intra-tumoral B cells, other B cell malignancies and plasma cell populations. Our transcriptomic analysis reveals that HRS shares greater similarity with plasma cells than with mature B cells and exhibits features reminiscent of plasma cell malignancies such as MM. While prior studies have established a GCB cell origin for cHL, supported by the presence of ongoing somatic hypermutation (\u003cspan additionalcitationids=\"CR42 CR43\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e), our findings provide molecular evidence for partial plasmacytic differentiation, extending prior immunohistochemical observations of abortive plasma cell features in HRS cells (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHRS cells show widespread downregulation of B cell identity genes, including BCR components and transcription factors such as PAX5 and IRF8. At the same time, they display features of incomplete plasma cell differentiation, including expression of IRF4/MUM1, but relatively low levels of PRDM1/BLIMP1 and absence of CD138 in most cases, although exceptions have been reported (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). This imbalance likely explains the paradox of robust UPR activation despite the absence of immunoglobulin production. Comparison with MM further underscores the aberrant plasmacytic features of HRS cells. Like MM, HRS cells show strong UPR activation, including overexpression of XBP1, ATF6 and other UPR components (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). However, unlike MM, HRS cells fail to undergo full plasma cell maturation, lacking consistent CD138 expression and immunoglobulin secretion. Thus, cHL appears locked in a non-productive, partially plasmacytic state. While plasma cell differentiation in MM is tightly coupled to BLIMP1 activity, in cHL UPR activation appears to arise through alternative mechanisms, possibly linked to FOXO1 downregulation (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e). Among UPR genes, PDIA6 was consistently overexpressed and highly specific to HRS cells and plasma cells within cHL biopsies, suggesting a potential role as a diagnostic marker.\u003c/p\u003e\u003cp\u003eThese findings support a model in which HRS cells aberrantly exit the germinal center through an abortive plasma cell differentiation program further compromised by failure to express immunoglobulin. Consistent with this, HRS cells show greater transcriptional similarity to BMPCs than to tonsil plasma cells, aligning with the notion that BMPCs arise from cells that have transited through the germinal center (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). Interestingly, the dissociation we previously reported between the canonical AID signature and SBS9 signature in cHL, where AID is present but SBS9 is absent, was again observed here (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Although SBS9 was initially attributed to non-canonical AID activity, recent studies link it to replicative stress in GCB cells (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e). Such dissociation, though rarely seen in B cell lymphomas, occurs in a subset of MM cases with MAF rearrangements (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e), suggesting that cHL and certain MM subsets may share aberrant GC exit mechanisms.\u003c/p\u003e\u003cp\u003eOur comparative transcriptomic analysis highlights both shared and divergent features between cHL and PMBL. Both malignancies activate proliferative and oncogenic pathways, but HRS cells are distinguished by a more profound loss of B cell identity, absence of GCB-associated genes such as LMO2 and enrichment for cytoskeletal and mitotic programs consistent with their multinucleated morphology. Unlike PMBL, HRS cells do not express LMO2 nor BCMA, reinforcing the notion that the two tumors diverge at the level of differentiation despite overlapping mutational landscapes. Furthermore, HRS cells display unique enrichment of neuronal and cytoskeletal gene programs, reflecting possible lineage infidelity or aberrant differentiation processes not observed in other B cell malignancies.\u003c/p\u003e\u003cp\u003eOur dataset also refines the immune evasion strategies of HRS cells. In addition to impaired antigen presentation through B2M mutations (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), overexpression of checkpoint ligands (PDL1, PDL2 and TIM3), and secretion of immunosuppressive cytokines, we identify a novel mechanism - loss of NK cell-mediated cytotoxicity. Specifically, downregulation of multiple SLAM family ligands, including CD48, was observed in both primary HRS cells and cell lines and validated at the protein level. This suppression coincided with significantly reduced NK cell infiltration in cHL tumors compared with reactive lymph nodes, suggesting spatial exclusion of NK cells as an additional immune evasion strategy. Taken together with frequent loss of MHC class I, these findings indicate that HRS cells evade both T cell and NK cell mediated surveillance, offering a more comprehensive view of their immune escape repertoire. This finding has therapeutic implications, as CAR-NK strategies are now entering clinical development.\u003c/p\u003e\u003cp\u003eFinally, we investigated the possibility of viral involvement in cHL pathogenesis beyond EBV. Our unbiased viral search revealed no novel viral sequences, and EBV transcripts were detected only in known EBV-positive cases (\u003cspan additionalcitationids=\"CR55\" citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e). This is consistent with the prevailing model in which EBV contributes to cHL pathogenesis through NFKB activation in a subset of cases, while EBV-negative disease relies on somatic alterations, such as mutations in TNFAIP3 (A20), to activate similar pathways (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Thus, EBV positive tumors rely on viral oncogenic programs, whereas EBV-negative tumors acquire genetic lesions to converge on similar signaling outcomes.\u003c/p\u003e\u003cp\u003eIn summary, our findings refine the molecular identity of HRS cells as aberrantly differentiated GCB-derived cells with plasmacytic features, robust UPR activation, and unique immune evasion strategies. The distinction from PMBL underscores the divergent transcriptional trajectories of related B cell lymphomas, while transcriptomic similarities to MM highlight a shared yet incomplete plasmacytic program. The identification of UPR activation and NK cell evasion as defining features of HRS cells points to potential diagnostic markers and novel therapeutic vulnerabilities in cHL.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project was supported by the Department of Pathology and Laboratory Medicine of Weill Cornell Medicine and its Center for Translational Pathology. It was funded in part by NIH grant R01-CA068939 to EC. \u0026nbsp;JR was partially funded by the Tri-I Training Program in Computational Biology and Medicine (5T32GM083937). MR and JR were supported by MSK Cancer Center Support Grant/Core Grant (P30 CA008748).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAUTHORSHIP CONTRIBUTIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEC, MR, and LGR conceived of the experiments, advised on every aspect, conducted validation experiments and wrote the manuscript; MR and JR sorted primary cases, optimized and constructed libraries. JR, IYK, WD, FW, SZ, BB, and AC analyzed data with LM, OE, and RR. \u0026nbsp;JB, SIP, AEK, MJO, NG, MSL, MJB contributed patient samples. \u0026nbsp; All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDISCLOSURE OF CONFLICTS OF INTEREST\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe have no conflicts of interest to report.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eSwerdlow SH, Campo E, Harris NL, Jaffe ES, Pileri SA, Stein H, et al. WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues. 4th ed. 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Leuk Lymphoma. 2006;47(7):1315-21.\u003c/li\u003e\n \u003cli\u003eWilson KS, Freeland JM, Gallagher A, Cosby SL, Earle JA, Alexander FE, et al. Measles virus and classical Hodgkin lymphoma: no evidence for a direct association. Int J Cancer. 2007;121(2):442-7.\u003c/li\u003e\n \u003cli\u003eSchmitz R, Hansmann ML, Bohle V, Martin-Subero JI, Hartmann S, Mechtersheimer G, et al. TNFAIP3 (A20) is a tumor suppressor gene in Hodgkin lymphoma and primary mediastinal B cell lymphoma. J Exp Med. 2009;206(5):981-9.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"blood-cancer-journal","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"bcj","sideBox":"Learn more about [Blood Cancer Journal](http://www.nature.com/bcj/)","snPcode":"41408","submissionUrl":"https://mts-bcj.nature.com/cgi-bin/main.plex","title":"Blood Cancer Journal","twitterHandle":"@bloodcancerjnl","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7957952/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7957952/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Classic Hodgkin lymphoma (cHL) shares mutations with primary mediastinal B cell lymphoma (PMBL) but differs in histology, clinical behavior, and phenotype. To define transcriptional programs underlying these differences, we performed flow cytometric cell sorting and low-input RNA sequencing of Hodgkin and Reed-Sternberg (HRS) cells from eighteen primary tumors, paired intra-tumoral B cells, and four cHL cell lines, and compared them with RNA-sequencing data from 40 PMBL cases. Transcriptomic profiling revealed that HRS cells undergo abortive plasma cell differentiation with robust activation of the unfolded protein response (UPR), a feature shared with multiple myeloma but absent in diffuse large B cell lymphoma and PMBL. HRS cells also demonstrated profound immune evasion, including suppression of B cell identity genes and loss of natural killer cell recognition through downregulation of SLAM family ligands such as CD48. Comparative analysis with PMBL highlighted shared oncogenic programs and key distinctions: HRS cells exhibited greater loss of B cell identity, absence of GCB- and plasma cell markers, and unique upregulation of cytoskeletal and mitotic pathways consistent with their multinucleated morphology. These findings establish HRS cells as aberrantly differentiated GCB cells with partial plasmacytic features, UPR activation and distinct immune evasion strategies.","manuscriptTitle":"Transcriptome sequencing of Hodgkin lymphoma Hodgkin and Reed-Sternberg cells reveals escape from NK cell recognition and an unfolded protein response","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-13 14:50:26","doi":"10.21203/rs.3.rs-7957952/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2026-01-16T16:03:26+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-12-20T10:21:18+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-12-12T16:32:10+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-11-24T08:03:13+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-11-04T03:10:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-27T12:17:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-27T12:13:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Blood Cancer Journal","date":"2025-10-26T19:19:53+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"blood-cancer-journal","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"bcj","sideBox":"Learn more about [Blood Cancer Journal](http://www.nature.com/bcj/)","snPcode":"41408","submissionUrl":"https://mts-bcj.nature.com/cgi-bin/main.plex","title":"Blood Cancer Journal","twitterHandle":"@bloodcancerjnl","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5f7fe4b0-b18e-485a-b4eb-d08832bfce29","owner":[],"postedDate":"November 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":57379532,"name":"Health sciences/Medical research"},{"id":57379533,"name":"Health sciences/Pathogenesis/Oncogenesis"}],"tags":[],"updatedAt":"2026-03-31T09:43:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-13 14:50:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7957952","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7957952","identity":"rs-7957952","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}