IGHV1-69 BCRs with virus-neutralizing mutations show lymphoma-like transcriptomes in patients with chronic HCV infection

doi:10.21203/rs.3.rs-2719495/v1

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IGHV1-69 BCRs with virus-neutralizing mutations show lymphoma-like transcriptomes in patients with chronic HCV infection

https://doi.org/10.21203/rs.3.rs-2719495/v1

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Chronic hepatitis C virus (HCV) infection leads to a complex interplay with adaptive immune cells that may result in cryoglobulinemia or lymphoma. Although direct-acting antiviral (DAA) therapy has decreased the incidence of severe liver damage, its effect on extrahepatic HCV manifestations such as B cell dyscrasias is still unclear. Here, we used immunosequencing to analyze HCV imprinting on B cell receptor (BCR) repertoires in patients with chronic HCV mono-infection or a sustained virological response (SVR) after DAA therapy. The majority of patients had a B cell signature with high somatic hypermutation and richness. Convergence to specific immunoglobulin genes produced high-connectivity complementarity-determining region 3 (CDR3) networks. Interestingly, IGHV1-69 CDR1 and CDR3 mutations characterizing highly neutralizing HCV antibodies corresponded to recurrent point mutations found in clonotypic BCRs of high-grade lymphomas. These BCRs did not show autonomous signaling but a lower activation threshold. B cells carrying these point mutations showed a persisting oncogenic transcriptome signature with dysregulation in signaling nodes such as CARD11, MALT1, RelB, MAPK, and NFAT. Collectively, this study provides evidence that lymphoma-like cells may result from the anti-HCV immune response and may persist for years after SVR, leading to HCV-related B cell dyscrasias and increased lymphoma risk beyond viral elimination.

Biological sciences/Cancer/Haematological cancer/Lymphoma/Non-hodgkin lymphoma/B-cell lymphoma

Health sciences/Diseases/Infectious diseases

Health sciences/Risk factors

Biological sciences/Immunology/Lymphocytes/B cells

B cell receptor

HCV

lymphoma

HCV neutralizing antibodies

direct-acting antiviral drugs

The hepatitis C virus (HCV) is an enveloped virus containing single-stranded RNA which can cause chronic disease courses^{1, 2}. According to the WHO an estimated 58 million people have chronic hepatitis C virus infection worldwide, with about 1.5 million new infections occurring per year. Chronic HCV infection can lead to severe liver disease and result in liver cirrhosis with the risk of developing hepatocellular carcinoma and a variety of clinically important extrahepatic B cell dyscrasias such as mixed cryoglobulinemia or – rarely – lymphoma^{3, 4}. The chronic course of the disease is generally attributed to a number of host and viral factors^{5, 6}. Importantly, HCV RNA replicates inside infected host cells at high levels with a high mutation rate constantly generating quasispecies that evade efficient humoral and cellular immune responses⁷. Exhausted HCV-specific CD8⁺ T cells comprise memory-like and terminally exhausted subsets that are maintained even after viral elimination^{8, 9}. The complex interplay of HCV with the adaptive immune system is also showcased by the evident B cell dyscrasia observed in this disease. Type II mixed cryoglobulinemia results from the production of a monoclonal rheumatoid factor-like IgM autoantibody binding IgG by HCV B cells. These antibodies are found in up to 50% of patients with chronic HCV, but the circulating immune complexes result in clinically detectable symptomatic arthritis and vasculitis in only 5–10% of patients¹⁰. Analysis of these antibodies revealed similar sequences, often favoring the use of specific immunoglobulin heavy chain variable genes (IGHV) such as IGHV1‐69, IGHV3-23, IGHV3-7, and IGHV4-59¹¹. Interestingly, many HCV-dependent or –independent non-Hodgkin lymphomas use the same IGHV genes in their clonotypic B cell receptor (BCR)¹¹. Therefore, chronic active BCR-mediated clonal selection was hypothesized to cause both the expansion of autoreactive B cells and drive lymphomagenesis at least in some patients with HCV¹¹. Yet, it remains unclear whether the BCR expressed by the lymphoma cell directly (cross-)reacts with HCV antigens, what consequences may arise from such an interaction or if the mechanisms underlying clonal B cell selection may be more indirect^{12, 13}.

Today, chronic HCV is treatable via direct-acting antiviral (DAA) therapy administered over several weeks¹. The introduction of DAA treatment has largely transformed our ability to encounter the global threat caused by HCV. Nevertheless, while greatly reducing the burden of severe liver damage and its clinical consequences, the effect of viral elimination on extrahepatic manifestations of HCV such as the accompanying B cell dyscrasia remains to be defined.

Here, we dissect HCV imprinting of B cell repertoires in patients with chronic HCV mono-infection and HCV patients with a sustained virological response (SVR) after HCV therapy. We show that complementarity-determining region 1 (CDR1) and CDR3 mutations characterizing highly neutralizing HCV antibodies correspond to recurrent point mutations found in the clonotypic BCRs of HCV-unrelated high-grade lymphomas. Using single-cell sequencing, we demonstrate that these point mutations confer a persisting oncogenic signature on B cells that can be interpreted as mechanistic basis for HCV-related B cell dyscrasias and that highlights the elevated lymphoma risk in these patients even years after HCV cure.

Biological samples

Peripheral blood of 42 HCV patients (30 with chronic HVC, 29 with SVR; 7 paired samples with matched time points) was collected in CPT tubes (BD, Germany) between 2010 and 2019 during routine clinical monitoring at the University Medical Center Hamburg-Eppendorf. As a control, the blood of twelve healthy donors (HD) without any hematological abnormalities was collected (University Medical Center Halle). Written informed consent was obtained from each patient and healthy individual included for the use of their biological material as approved by the respective ethics Commission Hamburg (Ethikkommission der Ärztekammer Hamburg, project number PV4081, Ethikkommission Halle 2020-039 and 2014/75. PBMC were isolated by density gradient centrifugation and cryopreserved in liquid nitrogen.

The subcohort of patients with chronic HCV has previously been published as control group in a report on autoimmune liver diseases¹⁴.

Next-generation immunosequencing and data processing

Immunosequencing of B cell repertoires was performed as described¹⁴. In brief, V(D)J rearranged IGH loci were amplified from 500 ng of blood or tissue-derived genomic DNA using a multiplex PCR, pooled at 4 nM and quality-assessed on a 2100 Bioanalyzer (Agilent Technologies). Sequencing was performed on an Illumina MiSeq (paired-end, 2 x 301 cycles, v3 chemistry). Rearranged IGH loci were annotated using MiXCR v3.0.13¹⁵ and the IMGT 202011-3.sv6 IGH library as reference. Non-productive reads and sequences with less than 2 counts were discarded. Each unique CDR3 was considered a clone. All Samples were normalized to a read depth of 30,000. Broad repertoire metrics (clonality, diversity, richness) were analyzed as previously described¹⁶. IGHV genes were regarded as somatically hypermutated if they showed < 98% identity to the germline sequence. PCA of V-J Gene combinations, their contributions, and the Pillai p value were calculated using R package ade4.

Network connectivity analysis

Network connectivity was calculated with the imnet tool (https://github.com/rokroskar/imnet) and visualized as petri dish plots with R library igraph¹⁷. Sequences were calculated as connected if they differed in a maximum of three positions (Levenshtein distance ≤ 3). Connectivity index β was calculated by dividing the number of links by the number of sequences. Data analysis and plotting was performed using R version (v4.1.2).

Sequence alignment of IGHV1-69

Raw reads were aligned to germline sequences using igblast¹⁸. Sequences were filtered for productive and complete IGHV1-69 VDJ regions. An amino acid position was counted as mutated referring to the germline sequence if the amino acid was not present in this position in any of the germline alleles IGHV1-69*01 – IGHV1-69*20.

Cloning and cellular expression of IGHV1-69 BCR

For expression of selected BCRs, heavy chain (HC) and light chain (LC) sequences (Supplementary Table 1) were synthesized via GeneArt (Thermo Fisher). HCs encompassed the completely rearranged VDJ sequence without the constant region. HCs were cloned in-frame to the adjacent murine µ constant chain in the pMIZCC vector via XhoI and PshAI. LC encompassed the respective kappa or lambda constant region and were cloned into pMIZYN via XhoI and EcoRI. For the production of viral supernatant, Phoenix-eco cells were seeded at 0.5*10⁶ cells/well in 6 well plates 24 hours before transfection. For transfection, 1 µg of DNA was used along with 3 µg PEI MAX® (Polysciences 24765-100) per well. The DNA mix consisted of three plasmids in a 1:1:1 ratio (plasmid containing the human variable light and constant chain, the heavy chain human variable region fused to murine µ constant region and the pKAT packaging plasmid to increase virus production). Viral supernatant was collected after 48 hours of incubation at 37°C, filtered through a 0.45 µm filter and concentrated using the Lenti-X™ Concentrator (Clontech 631231) overnight. Transductions were performed by resuspending 2.5*10⁵ TKO cells in TKO medium containing 10 µg/ml polybrene (Merck Millipore TR-1003-G) and viral supernatant followed by 3h spinoculation at 37°C and 300 x g.

Calcium signaling

For calcium flux measurements, 1.5*10⁶ TKO cells were loaded with Indo-1 AM (ThermoFisher I1223) using Pluronic F-127 (Invitrogen P3000MP) and stimulated with either 2 µM 4-OHT (Merck H7904) for measuring of autonomous signaling capabilities by induction of SLP65-ERT2 or 2 µM 4-OHT + 10 µg/ml anti-IgM (Sigma-Aldrich AP500 Goat Anti-Mouse IgM) for BCR crosslinking. As a loading control to achieve maximum cytosolic calcium levels, 4 µg/ml Ionomycin (StemCell Technology 73722) were added. All measurements were performed at 37°C using a custom 3D-printed tube holder connected to a water pump and heating unit on a BD LSR Fortessa flow cytometer.

Single-cell RNA and BCR sequencing

To enrich B cells for single-cell analyses, we FACS-sorted CD19⁺ cells (CD19-PECy7, clone J3-119, Beckman Coulter) from cryopreserved PBMC of 4 HCV and processed on a 10X Chromium Controller (10X Genomics, Pleasanton, CA, USA). Single-cell libraries were generated using the Next GEM Single Cell 5' Kit v2 and Chromium Single Cell Human BCR Amplification kits according to the manufacturer´s instructions. The libraries were sequenced on an Illumina NovaSeq 6000 system (S4 flow cell) with 150 base pairs and paired-end configurations. Filtered reads were aligned and the barcodes were counted with cellranger count pipeline (v 5.0.1). HCV and previously published healthy samples¹⁹ were integrated in R (v 4.2.1) using package Seurat (v 4.1.1)²⁰. Integration anchors were calculated using the function FindIntegrationAnchors and datasets were integrated with IntegrateData to one object. After scaling, PCA and UMAP calculations were performed on 20 dimensions. Clusters that were not covered by each individual were discarded. B cell clusters were assigned according to subset markers found with function FindAllMarkers and selected B cell population marker genes. Genes IGHV, IGKV, IGLV were eliminated from genelists. Fastq files from V(D)J libraries were analyzed with cellranger vdj pipeline, and the filtered results were integrated with GEX Data with package scRepertoire (v 1.4.0). Gene module scores were calculated in Seurat with the function AddModuleScore. For further analysis, we structured the dataset using the function subset, to obtain only HCV with mutant IGHV1-69 and all HD cells. We used package SCISSORS (v.1.2) to wrap results from PHATE²¹ into the Seurat object. After RunPHATE was performed on 20 principal components and euclidean distance, a DimPlot was generated on PHATE reduction. Differentially expressed genes were detected with the function FindSpecificMarkers and visualized with the package EnhancedVolcano (v 1.14.0). Upregulated genes were used as input for pathway analysis with package enrichR (v.3.0).

Statistical analysis

To test for the difference in the mean connectivity in B cell networks we used the two-tailed Mann-Whitney test using GraphPad Prism 8.3.1 (GraphPad Software, La Jolla, CA, USA).

HCV B cell repertoires show a high richness and somatic hypermutation independently of disease activity

We performed peripheral blood next-generation IGHV-D-J sequencing to determine general immune repertoire metrics in a real-world cohort of chronic HCV patients. Table 1 summarizes the demographic, clinical, and serological characteristics of all included patients. Clonality, diversity, and richness were calculated for each repertoire since these parameters robustly define the general repertoire architecture. Figure 1A-C summarizes the repertoire features of patients with chronic HCV infection and in patients with SVR after DAA treatment (and interferon treatment) as well as healthy controls. We found substantially increased B cell richness in HCV B cell repertoires independently of disease activity and viral clearance. Moreover, B cells from HCV patients showed, regardless of the clinical status, extensive rates of somatic hypermutation as compared to healthy controls (Fig. 1D). This increase persisted in individuals with SVR (Fig. 1D). In line with prior studies^{22, 23}, B cells from HCV patients had longer heavy-chain CDR3s independent of clinical status (Fig. 1E). This overrepresentation was especially characteristic of IGHV1-69-encoded BCRs, which are known for their broad HCV reactivity²².

Table 1

Characteristics of cohorts
		Healthy individuals	HCV patients
Nb of individuals Nb of samples		12 12	52 59
Sex
	Female Male	9 3	33 19
Age median (range)		44y (26–86)	55.5y (26–79)
Viremia (IU/mL)			22–50 Mio IU/mL
Genotype
	GT1 GT2 GT3 GT4 GT5 GT6		43.8% 9.4% 37.5% 3.1% 3.1% 3.1%
Frequency of cryoglobulinemia			3.3%
Treatment	Ledipasvir/Sofosbuvir Sofosbuvir/Velpatasvir Glecaprevir/Pibrentasvir Velpatasvir/Sofosbuvir Peginterferonalfa/Ribavirin Elbasvir/Grazoprevir Ombitasvir/Paritaprevir/Ritonavir Ombitasvir/Paritaprevir/Ritonavir/Dasabuvir Sofosbuvir/Ribavirin Sofosbuvir/Velpatasvir/Voxilaprevir		20.69% 20.69% 17.24% 13.78% 10.35% 3.45% 3.45% 3.45% 3.45% 3.45%

B cells are biased towards the usage of IGHV1-69 and IGHV4-59 rearrangements

Interestingly, despite our bulk B cell sequencing approach in a cohort without obvious clinical autoimmunity or cryoglobulinemia, we were able to statistically show repertoire skewing towards a specific IGHV-D-J gene usage regardless of clinical status (Fig. 1F). Compared to healthy controls, this skewing mainly derived from the increased usage of defined IGHV1-69 and IGHV4-59 rearrangements in HCV patients similar to previous findings in lymphomas and HCV-associated autoreactive B cell clones (Fig. 1G)^{11, 23}. This finding suggested systematic expansion of B cells with potential autoreactive or even lymphoma-like properties in patients with HCV.

Sequence connectivity analysis shows convergent recombination to stereotyped CDR3 sequences in HCV that persist beyond successful treatment

Next, we set out to calculate B cell network connectivity to detect potential stereotypic CDR3 patterns characteristic of non-Hodgkin lymphomas and autoreactive B cells. This analysis is exemplarily visualized as petri-dish plots for repertoires of patients 1, 2, and 3 (Fig. 2A). Overall, quantitative analysis of CDR3 sequences showed substantially higher connectivity within the B cell repertoires of HCV patients with chronic disease and SVR as compared to those of healthy controls (HDs) (Fig. 2B). We noticed more than a doubling in the number of subnetworks in chronic HCV and SVR compared to HDs (mean of 42 and 46 versus 17; Fig. 2C), a higher percentage of connected sequences (mean of 5.9 and 5.1 versus 2.7%, Fig. 2D), and larger networks in chronic HCV and SVR compared to HDs (mean largest subnetworks 14.7 and 11.4 versus 5 nodes; Fig. 2E).

When we calculated the biggest subnetwork for IGHV gene usage per individual, we found that in many cases the most frequently used IGHV gene belonged to one of the gene families responsible for skewing. Yet, within individual subnetworks of similar CDR3 sequences, a variety of IGHV gene families was typically present (exemplarily shown in Fig. 2F). This argued strongly in favor of B cell maturation trajectories characterized by convergent IGHV-D-J recombination towards specific stereotyped CDR3 sequences. Of note, high B cell connectivity persisted even years after HCV cure suggesting substantial longevity of this repertoire imprint (Fig. 2A).

Specific IGHV1-69 point mutations defining HCV elite-neutralizing antibodies correspond to recurrent IGHV1-69 point mutations found in HCV-unrelated lymphomas

Specific point mutations within the variable regions of IGHV1-69-encoded antibodies with E2 specificity have been shown to define HCV elite-neutralizers²². Our HCV dataset contained a high mutation frequency at some of these CDR1 and CDR3 hotspots within the IGHV1-69 gene both in patients with chronic HCV and in those with SVR even though these patients were not selected for HCV neutralization capacity (Fig. 3A). Of the previously described hotspot positions, especially positions IGHV1-69-S31 and IGHV1-69-R87 were heavily mutated in our HCV cohort (> 4 times more often than in healthy individuals). With our bulk sequencing approach, we did, however, not detect an increased mutational frequency at position IGHV1-69-S30, which has also been reported to be important for elite neutralization²². We aligned two of the most prominent HCV-specific hotspots from our dataset – IGHV1-69-S31 and IGHV1-69-R87 – with the clonotypic sequences from 24 IGHV1-69⁺ diffuse large B cell lymphomas (DLBCL)²⁴. Intriguingly, we noticed a similar mutational frequency and an overlapping spectrum of mutations at these positions in the HCV-derived and lymphoma-derived BCRs (Fig. 3A). Given that these DLBCL cases were unrelated to HCV, we reasoned that these mutations – while mediating efficient HCV neutralization during an infection – may also have oncogenic potential beyond the context of HCV.

We determined the mutational frequencies at the IGHV1-69-S31 and –R87 positions in samples acquired at the chronic HCV stage and after DAA treatment in all patients with matched blood samples. The median time between DAA treatment and blood sampling was 447 days. In the majority of HCV patients, the mutant clone persisted beyond HCV cure and did not trend towards decrement (Fig. 3B).

We wished to track the imprinting of the B cell repertoire by HCV over time from early infection phases to later time points. Unfortunately, none of the patients in our cohort had pre-infection blood samples available since all patients had been first diagnosed at the stage of chronic HCV infection. To approach this question, we longitudinally analyzed bone marrow B cells from a patient with chronic HCV infection who underwent an allogeneic stem cell transplant for myeloid leukemia. We found two classical HCV hotspot mutations in this patient (IGHV1-69-N30 and IGHV1-69-T31). When tracking these mutant sequences over time, we observed high mutational frequencies in the peritransplant period reflecting residual recipient-derived B lineage cells (Fig. 3C). This was followed by a dramatic decrease in mutational frequencies a few months after allogeneic stem cell transplant reflecting the expansion of HCV-naïve donor-derived B lineage cells. Over two years, the mutational frequencies in HCV-specific hotspot regions of IGHV1-69 increased substantially (Fig. 3C). After viral elimination by DAA therapy, these clones showed again a moderate drop but were not eliminated from the repertoire (Fig. 3C).

HCV B cells show lymphoma-like transcriptomes at single-cell resolution

The finding of overlapping mutational patterns in HCV-neutralizing antibody/BCR sequences and HCV-unrelated lymphoma BCRs suggested that these mutations may confer oncogenic properties to the antigen receptor.

Since some of the BCRs used by DLBCL cells show autonomous signaling capacity, we wished to rule out that the HCV-induced hotspot mutations created similar antigen-independent signaling patterns. To this end, we cloned combinations of two DLBCL-derived IGHV1-69 rearrangements ²⁴ that carried HCV-typical hotspot mutations (IGHV1-69-N30/T31 or IGHV1-69-N31) along with two matching light chain sequences for expression in TKO cells (BCR1-4, Supplementary Table 1), a murine triple knock-out cell line that can be induced to express the BCR downstream signaling machinery upon 4-OHT challenge. In addition, the CDR1 sequences of these four BCRs were reverted to the germline CDR1 and expressed in TKO cells (Supplementary Table 1). While all of the BCRs showed anti-IgM-induced Ca²⁺ influx, none of the tested BCRs did show autonomous signaling capacity no matter if the original mutant CDR1 or the germline-reverted CDR1 were expressed (Fig. 4A). We noticed, however, that BCR1, a receptor with two CDR1 hotspot mutations (IGHV1-69-N30/T31), had a slightly higher response to IgM ligation compared to the germline-reverted CDR1 (Fig. 4A). Together, this data suggested that basic receptor functionality was preserved or even increased in IGHV1-69 variants carrying HCV hotspot mutations, but no autonomous signaling was induced.

Next, we asked whether B cells from chronic HCV patients carrying such hotspot mutations showed specific transcriptome signatures. To look at this at single-cell resolution, we subjected sorted HCV and healthy donor B cells to combined single-cell RNA and BCR VDJ sequencing. We compared B cells from two HDs with those from two patients with chronic HCV and another two with SVR. The two HCV patients with SVR had received their DAA treatment 406 and 420 days before blood sampling for this study. Figure 4B shows the UMAP projection of an integrated PBMC dataset from the two healthy donors, two patients with chronic HCV and two patients with SVR (HD: 4456 cells; chronic HCV: 2406 cells, HCV SVR: 1615 cells). The distribution of B cell subpopulations shifted from patients with chronic HCV to healthy donors (Fig. 4B and C). HCV patients with SVR showed an intermediate distribution of B cell subpopulations between chronic HCV and HDs (Fig. 4B and C). Consistent with the strong somatic hypermutation observed by repertoire deep sequencing, HCV patients showed more antigen-experienced B cell subsets including a considerable amount of cells in the mature activated compartment with a plasma(blast)-like signature (loss of MS4A1, PTPRC) (Fig. 4B-D). In addition, we observed the HCV-specific expansion of two clusters characterized by the expression of T-bet (TBX21) and other positive and negative key markers of atypical B cells^{25, 26} in HCV patients (Fig. 4B-D). While one of these clusters (T-bet⁺1) was expanded in chronic HCV and SVR, the other (T-bet⁺2) was mainly expanded in chronic HCV and was characterized by TNF receptor (TNFRSF1B) expression and high levels of FCLR3 and FCRL5 (Fig. 4B and C). We also noted a pronounced signature of BCR-mediated proliferation and MAPK activity in HCV (Fig. 4E).

Patients with chronic HCV and with SVR showed high numbers of IGHV1-69 expressing B cells (Fig. 4F), many of which with mutations characteristic of HCV-neutralizing antibodies (Fig. 4G). The percentage of those cells in the repertoire was similar in patients with chronic HCV and those with SVR (Fig.s 4F + G). We performed PHATE analysis to study the transcriptomes of HCV patient-derived B cells carrying IGHV1-69 with HCV-typical hotspot mutations. This analysis showed a clear separation of this class of B cells from healthy donor B cells, while there were no significant differences between patients with chronic HCV and those with SVR (Fig. 4H). Differentially regulated genes were enriched for classical lymphoma driver genes downstream of the BCR including MALT1 and CARD11 (Fig. 4I). Broader pathway analysis showed that also other parts of this signaling cascade were deregulated such as the calcineurin-NFAT axis as well as other pathways known to synergize with BCR signaling such as the toll-like receptor axis (Fig. 4J).

Lymphomas are characterized by the uncontrolled growth of clonal lymphocytes. Risk factors include age, family history, autoimmune disease, immunosuppression, exposure to chemicals or radiation, genetic risk factors, and specific bacterial or viral infections. While some viruses, such as EBV, HHV-8, and HTLV-1 can directly transform lymphocytes, the B cell dyscrasias and B cell lymphomas arising in patients chronically infected with HCV have long been suspected to be driven by chronic immune stimulation: Either indirectly by a chronic inflammatory environment such as in Helicobacter-driven lymphomas or more directly through chronic stimulation of the BCR pathway by HCV antigens^{3, 11–13}. Yet, the exact pathophysiological phenomena underlying the association of HCV and lymphomas remained unclear.

In our work, we characterized the peripheral blood B cell architecture of patients with chronic HCV that – clinically – did not suffer from B cell dyscrasias such as cryoglobulinemia or lymphoma. We found a characteristic HCV fingerprint essentially consisting of lymphoma-like immunoglobulin gene usage, high somatic hypermutation, and stereotypic CDR3 motifs. Unexpectedly, this fingerprint persisted in the majority of patients even years after successful HCV therapy. Moreover, we pinpointed mutations of serine 31 within the CDR1 of the IGHV1-69 gene that had recently been identified to facilitate broad neutralization of antibodies against HCV E2²². While serine 31 mutations have been reported in small cohorts of HCV-associated lymphomas (3/8 patients with S31T and 1/8 patients with S31N in²⁷; 1/3 with S31T and 1/3 with S31N in²⁸) we show that this residue is also frequently mutated in HCV-unrelated high-grade lymphomas.

It has been widely recognized over the past decade that the antigen receptor with its specific configuration is a powerful tumor promotor in lymphoma. Major revelations were the discovery of preferentially used immunoglobulin genes (e.g. IGHV4-34, IGHV4-59, or IGHV1-69) to the extent of virtually identical “stereotyped” receptor configurations^{13, 29–35}, their reactivity with self-antigens^{29, 36–41}, their autonomous signaling capacity through BCR-internal epitopes^{40, 42} as well as the clinical success of a wealth of new therapies interfering with antigen receptor signaling. Through these studies, it became clear that lymphoma BCRs harbor recurrent sequence motifs that are rare or even completely absent in healthy lymphocytes e.g. the chronic lymphocytic leukemia-specific light chain point mutation IGLV3-21^R11043–48. The acquisition of enhancing IGHV1-69 “HCV-neutralizing” hotspot mutations during infection that are at the same time recurrent aberrations in BCRs of HCV-unrelated DLBCLs do add a whole new perspective on the potential risks underlying anti-viral immune responses. Our data suggest that in the case of HCV, broad virus neutralization may come at the cost of generating BCR variants with oncogenic potential that mimic the chronic active BCR signaling phenotype characteristic for lymphomas. In line with this, we observed that HCV-derived B cells expressing IGHV1-69-encoded BCRs with CDR1 hotspot mutations upregulated classical lymphoma drivers downstream of the BCR and MYC as well as NF-κB, MAPK, and NFAT pathway components such as CARD11, MALT1, RelB, PIM3, KRAS, MAPK8IP3, and NFATC1. As a consequence, the persistence of expanded B cell networks may not simply be regarded as an uncleared BCR-centered “HCV scar”, but as the result of imprinted lymphoma-like BCR signaling maintaining the persistence of these clonal networks. This idea is substantiated by our PHATE analysis that identified these gene expression profiles in patients with chronic HCV and those with SVR.

One mechanistic explanation of how upstream IGHV1-69 hotspot mutations allow engaging in lymphoma-like signaling comes from the superior responses to IgM ligation for one of the lymphoma-derived BCRs with mutated CDR1. It is plausible, that specific mutation-induced steric changes in receptors of this family with their inherent propensity for autoreactivity lower the activation threshold for cross-reaction with self-antigens. This is also illustrated by the light chain dependency of this activation effect. Interestingly, this BCR not only carries two CDR1 hotspot mutations but also shares other characteristics with classical elite-neutralizing HCV antibodies, e.g. the long and hydrophobic CDR3, the hydrophobic CDR2 and the rather high mutation rate of 94% identity to germline²². The requirement for multiple BCR alterations in combination with proper light chain usage might contribute to the only moderately elevated lymphoma risk of HCV patients.

From a clinical perspective, the substantial longevity of the HCV-induced oncogenic imprints despite cessation of antigenic pressure may provide an explanation for the increased lymphoma risk even after HCV cure that has been suggested by some cohort studies. One of these studies showed that three of 431 DAA-treated patients were afterward diagnosed with high-grade non-Hodgkin lymphoma; the prevalence in this cohort was 696 per 100,000 - about 30 times higher compared with the general population⁴⁹. Also, El-Serag et al⁵⁰ demonstrated no impact of DAA treatment on non-Hodgkin lymphoma risk. Our finding of lymphoma-like B cell programs in the absence of HCV antigenic pressure may explain why viral elimination induces remissions only in selected lymphoma cases.

Together, this data contributes a new perspective on how anti-viral immune responses may foster lymphomagenesis and should raise our awareness of elevated lymphoma risk in successfully treated HCV patients in the DAA era.

Acknowledgements

The authors thank Robin A. Woost, Christoph Wosiek and Aline Patzschke for excellent technical assistance. We would also like to thank Alexander Navarrete-Santos and the cell sorting core facility at the Martin-Luther-University Halle-Wittenberg as well as Ghanem El Kassem and Michael Böttcher (Martin-Luther-University Halle-Wittenberg) for technical advice on single-cell sequencing. Financial support from the Deutsche Forschungsgemeinschaft (SFB841 and BI 1711/4-1 to MB) is acknowledged.

Author contributions

Study concept and design: MB, JW, CS, LP, EW; Acquisition of data: CS, ME, LP; Analysis and interpretation of data: CS, EW, MB, LS, RS; Drafting of the mansucript: MB, EW, CS; Critical revision of the manuscript for important intellectual content: JW, LP, ME, CA; Technical or material support: JW, CA, MK, JK; Obtained funding: MB; Study supervision: MB, JW.

Competing Interests

The authors disclose no potential conflicts of interest.

Data availability

The herein-reported single-cell RNA sequencing data set has been deposited at ArrayExpress under the ID E-MTAB-12502.

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There is NO conflict of interest to disclose.

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IGHV1-69 BCRs with virus-neutralizing mutations show lymphoma-like transcriptomes in patients with chronic HCV infection

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Abstract

Figures

Introduction

Methods

Biological samples

Next-generation immunosequencing and data processing

Network connectivity analysis

Sequence alignment of IGHV1-69

Cloning and cellular expression of IGHV1-69 BCR

Calcium signaling

Single-cell RNA and BCR sequencing

Statistical analysis

Results

HCV B cell repertoires show a high richness and somatic hypermutation independently of disease activity

B cells are biased towards the usage of IGHV1-69 and IGHV4-59 rearrangements

HCV B cells show lymphoma-like transcriptomes at single-cell resolution

Discussion

Declarations

Acknowledgements

Author contributions

Competing Interests

Data availability

References

Additional Declarations

Supplementary Files

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