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Clinicopathologic features and abnormal signaling pathways in plasmablastic lymphoma: a multicenter study in China

BMC Medicine volume 20, Article number: 483 (2022) Cite this article

Abstract

Background

Plasmablastic lymphoma (PBL) is a rare but aggressive B-cell lymphoma subtype with poor prognosis. Knowledge about the etiology, clinicopathologic and molecular features, and outcomes of PBL is limited. This study aimed to examine the clinicopathologic characteristics, therapeutic approaches, and clinical outcomes of PBL patients in a Chinese population.

Methods

A total of 102 PBL patients were recruited from three cancer centers. The pathologic features and clinical outcomes of 56 patients with available treatment details and follow-up data were reviewed and analyzed. RNA sequencing was performed in 6 PBL and 11 diffuse large B-cell lymphoma (DLBCL) patients.

Results

Most patients in our cohort were male (n = 36, 64.3%), and 35 patients presented with Ann Arbor stage I/II disease at diagnosis. All these patients showed negative findings for human immunodeficiency virus, and the vast majority of patients in our cohort were immunocompetent. Lymph nodes (n = 13, 23.2%) and gastrointestinal tract (n = 10, 17.9%) were the most commonly involved site at presentation. Post-treatment complete remission (CR) was the only prognostic factor affecting overall survival (OS) and progression-free survival (PFS) in the multivariate analysis. RNA-seq demonstrated that B-cell receptor (BCR), T-cell receptor (TCR), P53, calcium signaling, and Wnt signaling pathways were significantly downregulated in PBLs compared with GCB (or non-GCB) DLBCLs.

Conclusions

In this multicenter study in the Chinese population, PBL mainly occurred in immunocompetent individuals and most patients present with early-stage disease at diagnosis. Post-treatment CR was an important prognostic factor affecting OS and PFS. RNA-seq showed that the B-cell receptor (BCR), P53, calcium signaling, cell adhesion molecules, and Wnt signaling pathways significantly differed between PBL and GCB (or non-GCB) DLBCL, which provided theoretical basis for its pathogenesis and future treatment.

Peer Review reports

Background

Plasmablastic lymphoma (PBL) is a distinct and rare subtype of B-cell lymphoma that exhibits a plasmablastic morphology but shows a plasma cell-like immunophenotype [1, 2]. Previous studies have reported that PBL predominantly occurs in immunocompromised individuals, such as those with human immunodeficiency virus (HIV) infection, organ transplantation, and autoimmune diseases [1, 3]. Frequent Epstein-Barr virus (EBV) infection and MYC gene aberrations present in PBL patients are reported as adverse prognostic factors and may contribute to lymphomagenesis in these patients [4]. However, the exact pathogenesis of PBL remains largely unknown and requires further investigation.

Diagnosing PBL is sometimes challenging, as it shares some similar clinicopathological features with myeloma and diffuse large B-cell lymphoma (DLBCL). Although comparative genomic hybridization analysis has revealed that the genomic aberration profile of PBL seems to be more similar to that of DLBCL than plasma cell myeloma (PCM) [5], the prognosis of PBL was reported to be significantly worse than to that of DLBCL [6], with an estimated 2-year overall survival (OS) of < 50% [7, 8]. Therefore, a better understanding of the biology and pathophysiology of PBL may help in improving the survival outcomes.

As most studies on PBL were case reports and small case series, the pathogenesis, standard treatment approaches, and prognostic factors remain largely unknown. Furthermore, clinicopathological features and survival outcomes may vary across populations. Therefore, this study aimed to analyze the clinicopathologic characteristics, therapeutic approaches, and clinical outcomes of PBL patients in a Chinese population. In addition, RNA-sequencing was performed to identify the differences between PBL and DLBCL.

Methods

Patient group

All the patients diagnosed with PBL between January 2008 and October 2019 at the Fudan University Shanghai Cancer Center, Hunan Cancer Hospital, and the Second Xiangya Hospital were examined in this study. Most patients were referred to our institution for consultation after a biopsy was performed. Clinical data such as patients’ age, sex, HIV status, medical history, primary tumor site, Ann Arbor stage, therapies, and clinical outcomes were obtained from medical records. This study was performed in accordance with the Declaration of Helsinki and approved by the ethics committee of each participating medical center. All participants provided written informed consent.

The main immunohistochemical markers (CD20, CD79a, PAX-5, CD30, CD38, CD138, MUM1, and Ki67) were reviewed by two pathologists (Wan and Yu).

Statistical analysis

Progression-free survival (PFS) was calculated from the date of diagnosis to the date of disease progression, relapse, or death by any cause. OS was defined as the time from the date of initial diagnosis to the date of death or last contact. Using univariate analysis, the prognostic role of patient age, sex, disease stage, B symptoms, increased serum lactate dehydrogenase (LDH) level, Ki67, EBER, and patient complete remission (CR) status was evaluated. Prognostic factors (p < 0.05) were further examined using multivariate analysis with Cox regression. PFS and OS were estimated using the Kaplan–Meier method. Survival curves were compared using the log-rank test. Chi-square tests or Fisher’s precision probability tests was used to analyze the clinical differences in different patient groups. Statistical analysis was performed using GraphPad Prism (version 5, GraphPad Software) and R (version 3.5.1, R Foundation for Statistical Computing, Vienna, Austria). Statistical significance was set at P < 0.05.

Immunohistochemistry (IHC) and in situ hybridization for EBV-encoded RNA

Hematoxylin and eosin staining and IHC studies were performed on formalin-fixed and paraffin-embedded tissue sections using standard methods. Primary antibodies against CD20, CD79a, PAX-5, CD38, CD138, and MUM1 (Ventana Medical Systems, USA) were applied on a BenchMark XT automated immunostainer (Ventana Medical Systems) with Cell Conditioning heat retrieval solution (Ventana Medical Systems). Appropriate internal controls (lymphocytes) and external controls (tonsils) were also included in each section. The morphology and IHC results were reviewed by two pathologists (Wan and Yu).

Detection of EBV-encoded small RNA (EBER)-1/2 was performed with proper controls using an ISH kit (Triplex International Bioscience, China) following the manufacturer’s instructions.

RNA-sequencing

RNA was extracted using the AllPrep Kit (Qiagen). Sequencing libraries for RNA-sequencing were prepared using TruSeq RNA Library Prep Kit V2 (Illumina). Paired-end 100 bp read sequencing was performed on a HiSeq 2500 system using Illumina TruSeq V3 chemistry. Paired-end reads were mapped to the human genome (NCBI build 37) by the gapped aligner STAR 2.4.117, using the two-pass method and parameters recommended by the NCI Genomic Data Commons (GDC) 18. The alignment file was used to calculate the raw digital gene expression values by HTseqcount software 0.7.219, using the intersection-nonempty model, which were further analyzed to provide digital gene expression values. The alignment file was also used for variant calling by VarScan2 with selection based on variant read count ≥ 3 and variant read frequency ≥ 0.1.

Reverse-transcriptase quantitative PCR (RT-qPCR)

RT-qPCR was performed as previously described [9, 10]. RNA was extracted from paraffin-embedded tissue using the AllPrep Kit, according to the manufacturer’s instructions (Qiagen, San Diego, CA, USA). cDNA was synthesized with the Reverse Transcriptase Kit (Takara, # RR036A). Then, qPCR was performed using SYBR Green according to a standard protocol (Takara, #RR420A). Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) served as internal control. The primer sequences are provided in Additional file 1: Table S1.

Results

Patient characteristics

A total of 102 patients were diagnosed with PBL at our three cancer centers and the clinical characteristics are summarized in Additional file 1: Table S2.Treatment details and follow-up data were available for 56 patients and the clinicopathologic parameters, treatment, and survival outcome of these patients have been listed in Table 1. Of the 56 patients, most patients were male (n = 36, 64.3%), with a median age of 55.0 (range 10–79) years. PBL occurred at various sites, with the lymph nodes (n = 13, 23.2%) and gastrointestinal tract (n = 10, 17.9%) being the most commonly involved locations, followed by the oral cavity (n = 9, 16.1%). Most patients (n = 35) presented with Ann Arbor stage I/II disease at diagnosis. Elevated LDH level (17/41, 41.5%) and B symptoms (22/49, 44.9%) were observed in less than half of the patients. All these patients showed negative findings for HIV, and immunosuppression (immune-related disease, post transplantation, and current or previous malignancy) was noted in only 4 patients [scleroderma (n = 2) and organ transplantation (n = 2)].

Table 1 Clinicopathologic characteristics of the 56 PBL patients with available follow-up data in our study
Full size table

Immunoblastic-like morphology and plasmacytic immunophenotypes were observed in patients with PBL (Fig. 1A–D). Plasma cell markers CD38 (Fig. 1A), CD138 (Fig. 1B), and MUM1 (Fig. 1C) were ubiquitously expressed in PBL patients, with positive rates of 90.3%, 69.0%, and 95.4%, respectively, for the entire cohort (Table 1). CD30 was positive in 23.8% of the tested patients (n = 42). All the patients showed negative findings for CD20, CD79a, and PAX-5. The Ki-67 expression was relatively high in our study, with a median value of 80% and a wide range between 40% and 100%. EBER expression was observed in 50% of the tested patients (n = 20). MYC expression was assessed in 14 patients, and 10 patients showed positive findings.

Fig. 1
figure 1

Representative case of plasmablastic lymphoma. A–C CD38, CD138, and MUM1 were positive by immunohistochemistry (× 400). D Neoplastic cells have plasmablastic morphology, with a prominent nucleolus and moderate amount of cytoplasm

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Treatment

Treatment modalities in our cohort were as follows: 50 (89.3%) received chemotherapy alone, 2 received radiotherapy combined with chemotherapy, 2 (3.6%) received surgery and adjuvant chemotherapy, and 2 (3.6%) with localized disease (thyroidectomy for thyroid involvement and hemicolectomy for right hemi-colon involvement) received curative surgical resection alone. The chemotherapy regimens used are listed in Table 1. CHOP or CHOP-like chemotherapy was the most common regimen used in 43 patients. Bortezomib combined with chemotherapy, including PAD (bortezomib, doxorubicin, and dexamethasone), CHOP, and BADT (bortezomib, doxorubicin, dexamethasone, and lenalidomide), was used as first-line treatment in 4 patients. Other chemotherapy regimens, such as DA-EPOCH, GDP (gemcitabine, cisplatin, and dexamethasone), and GEMOX (gemcitabine and oxaliplatin), were used in seven cases.

Response to treatment

In our cohort, 44.6% (n = 25) of the patients achieved CR after treatment, 30.4% (n = 17) achieved PR, 1.8% (n = 1) SD, and 23.2% (n = 13) showed PD. When combined with chemotherapy, bortezomib did not improve the CR rate compared to the CHOP group (p > 0.05). The two patients with localized disease achieved durable CR after surgery alone.

Clinical outcome and prognosis parameters

The median follow-up duration was 23.0 (range, 1–130) months. At the last follow-up, 22 (39.3%) PBL patients died. The 2-year PFS and OS rates in our cohort were 59.4% and 65.1%, respectively (Fig. 2A, B).

Fig. 2
figure 2

A, B Progression-free survival (PFS) and overall survival (OS) of all patients. C, D Comparison of progression-free survival (PFS) and overall survival (OS) between patients with stage I/II and III/IV disease

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Prognostic factors determined by univariate and multivariate analyses are summarized in Table 2. Univariate analysis revealed that achievement of a CR (p = 0.001) was an adverse prognostic factor affecting PFS, which was not associated with other clinical parameters such as clinical stage (Fig. 2C). Clinical stage (p = 0.02) (Fig. 2D), serum LDH level (p = 0.03), and CR (p = 0.001) after treatment were important prognostic factors of OS, as revealed by univariate analysis. In the multivariate analysis, achievement of CR remained the only significant factor affecting OS and PFS.

Table 2 Univariate and multivariate analysis of prognostic factors for survivals (by Cox regression)
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RNA-sequencing results and validation by RT-qPCR

RNA-seq was performed in 6 PBL and 11 DLBCL cases. No difference was found between the PBL and DLBCL patients in gender, age, primary sites, and disease stage (Additional file 1: Table S3). As shown in Fig. 3A, a clustered heat map exhibits the profiling of the differentially expressed genes (DEGs) between PBL and DLBCL. Red blocks represent the overexpressed genes, while the blue blocks represent the lowly expressing genes. The heat map clustering showed that the gene expression pattern of PBL was distinguished from DLBCL. Compared with DLBCL, a total of 1507 DEGs were identified in the PBL group, including 1049 upregulated and 458 downregulated genes. The upregulated or downregulated genes are represented in a volcano plot (Fig. 3B).

Fig. 3
figure 3

Expression profiles. A Hierarchical clustering and heat map of DEGs between PBL and DLBCL. Red blocks represent the overexpressed genes, while the blue blocks represent the lowly expressing genes. B Volcano plot of DEGs (FDR < 0.05) between PBL and DLBCL. C Significantly downregulated pathways in PBL compared to DLBCL. D, E Upregulation and downregulation of DEGs of BCR and TCR signaling pathways in PBLs compared to DLBCL. F Significantly upregulated pathways in PBL compared to DLBCL. G–I Upregulation and downregulation of DEGs of cell adhesion molecules, calcium, and Wnt signaling pathways in PBLs compared to DLBC

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Biological pathways and themes underlying the malignancy-specific gene expression patterns were identified. KEGG showed that some important pathways were downregulated in PBL compared to DLBCL, including BCR and TCR signaling pathways (Fig. 3C). Many BCR signaling pathway genes were significantly (FDR = 0.001, hypergeometric test) expressed at lower levels in PBLs than in DLBCLs. Individual BCR signaling genes (CD22, CD72, CD19, CR2, NFATC1, BLNK, CD79N, CARD11, SYK, NFKBIE, and VAV2) and TCR signaling genes were repressed by two-fold or more on average in PBLs (Fig. 3D, E). Compared with that noted in DLBCL, many biological pathways were upregulated in PBL, such as cell adhesion molecules, calcium, and Wnt signaling pathways (Fig. 3F–I). Cell adhesion genes (SDC1, ITGA8, CDH15, CLDN18, ITGB8, OCLN, and NLGN1) were higher in PBLs.

The gene expression profiles of the germinal center subtype (GCB) and non-germinal center subtype (non-GCB) DLBCL were further analyzed, retrospectively. The heat map clustering and volcano plot demonstrated that the gene profiling was different between PBL and GCB-DLBCL (Additional file 1: Fig. S1, A-B). Compared with GCB-DLBCL, no elevated important pathways in PBL were observed by KEGG, while BCR and P53 signaling pathway was significantly downregulated in PBL (Additional file 1: Fig. S1, C-F). The profiling of the different expressed genes and pathways between non-GCB DLBCL and PBL were also identified (Additional file 1: Fig. S2, A-B). KEGG showed that some important biological pathways were significantly upregulated (Additional file 1: Fig. S2, C) and downregulated (Additional file 1: Fig. S2, D) in PBL compared to non-GCB-DLBCL. BCR, TCR, Jak-Stat, and TLR signaling pathways were significantly downregulated in PBL and the detailed downregulated genes were shown in Additional file 1: Fig. S2(E–H).

To further confirm the results, RT-qPCR analysis and IHC were performed to validate the DEGs from the RNA-seq data. Gene expression data were selectively validated by real-time PCR for some candidate genes, which were chosen based on the differential fold change between DLBCLs and PBLs. RT-qPCR results showed that the mRNA expression of CD19 (BCR signaling pathway), CD22 (BCR signaling pathway), and CD72 (BCR signaling pathway) was relatively lower in PBL than in DLBCL (Fig. 4A–C), while the expression of SDC1 (Cell adhesion molecule), CHRM3 (calcium signaling pathway), and HTR2C (calcium signaling pathway) was relatively higher in PBL than in DLBCL (Fig. 4D–F). In addition, IHC result demonstrated that the expression of BCR signaling genes (CD19 and CD22) were relatively lower in PBL compared to DLBCL (Fig. 4G, H). The RT-qPCR and IHC results highly correlated with the array data, indicating that the RNA-seq data was reliable and accurate.

Fig. 4
figure 4

Validation of DEGs by RT-qPCR and immunohistochemistry. A–C The qRT-PCR results showed that the mRNA expression of CD19, CD22, and CD72 were relatively lower in PBL than in DLBCL. D–F The RT-qPCR results showed that the expression of SDC1, CHRM3, and HTR2C were relatively higher in PBL were relatively lower in PBL than in DLBCL. G, H The expression of CD19 and CD22 detected by IHC. Magnification, x200

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Discussion

PBL is a rare type of non-Hodgkin lymphoma with overlapping features of B-cell lymphoma and plasma cell neoplasms [11]. It is characterized by male predominance, frequent involvement of the oral cavity, and an aggressive disease course, with a high rate of HIV and EBV infection [1, 3]. The exact pathogenesis, standard treatment strategies, and prognostic factors have not yet been defined. This study examined the clinicopathological characteristics, molecular features, and clinical outcomes of PBL in Chinese population.

We found that the clinicopathologic features, such as patient immune status, lesion location, and clinical outcome, were different between Chinese and Western populations. Many studies have confirmed that PBL mainly affects immunocompromised individuals, such as those with HIV infection or other autoimmune diseases [1,2,3, 8, 11]. Patients in our study group were HIV-negative, and most cases were immunocompetent, consistent with the findings of a review of 60 Chinese PBL patients [12]. In addition, the most involved sites in our study were the lymph nodes and gastrointestinal tract, followed by the oral cavity, which differed from the findings of previous research that reported that PBL commonly involved the oral cavity and other extra nodal sites in patients with immunodeficiency in Europe [1, 3, 8]. Similar to previous findings [1, 3, 7], plasma cell markers (CD38, CD138, and MUM1) were commonly expressed in our patients.

There is no optimal therapeutic approach for PBL. Although CHOP was the most commonly used regimen and patients achieved an overall response rate of approximately 60–70% after treatment, the NCCN guidelines demonstrated that it is inadequate therapy and recommends a more intensive regimen, including hyper-CVAD, CODOX-M/IVAC, and DA-EPOCH [13]. Previous studies have shown no apparent survival benefit of intensive chemotherapy over CHOP regimens in PBL patients [14, 15]. The prognosis of PBL remains poor, with a median OS of 6–32 months [1, 7, 8]. However, the survival outcome of our cohort was relatively longer, with 2-year PFS and OS of 62.7% and 65.2%, respectively. More than half of the patients in our cohort were at an early stage of disease and this may partly explain the prognosis.

Some important prognostic factors, such as disease stage, serum LDH level, EBV status, and CR status, have been identified in PBL [1, 2]. In our study, clinical stage, LDH level, EBV status, patient CR status, and IPI were significant prognostic factors in the univariate analysis, consistent with the findings of other studies [1, 2]. However, only CR status remained a significant independent factor in the multivariate analysis [1]. Many studies have reported that CR after treatment is associated with better outcomes in PBL patients, suggesting that CR is one of the strongest prognostic factors.

The chronic activation of the B cell receptor (BCR) and various downstream signals has been reported to be important for the survival of B cell lymphoma [16, 17]. In recent years, BCR signaling has emerged as an established target in lymphoma, and BCR inhibitors have achieved clinical effects in B-cell lymphoma [18, 19]. In our study, BCR signal was downregulated in PBL compared to DLBCL, which was consistent with the findings of a previous study [20], indicating that the BCR signal was not central to the pathogenesis of PBL and that PBL was distinct from DLBCL.

The tumor suppressor gene TP53, which encodes the p53 transcription factor and then regulates many target genes in various cancers, was reported to be a barrier to tumor development [21,22,23,24,25]. Mutations in TP53 occurred in around 20% of DLBCLs and loss of P53 function could contribute to lymphomagenesis [25, 26]. In ABC-DLBCL, loss of P53 function could facilitate tumor progression by suppressing the pathogenic cooperation of IKK2ca-enforced canonical NF-kB [24]. Our results showed that P53 signaling pathway was significantly downregulated in PBL compared to GCB-DLBCL, indicating that inactivated P53 may contribute to lymphomagenesis in PBL and serve as a potential therapeutic target in the future.

The tumor microenvironment can interact with cancer cells and play a critical role in tumor development and drug resistance [27, 28]. Cell adhesion molecules (CAMs) can mediate interactions between tumor cells and stromal cells. Recent studies have reported that high expression of CAMs contributes to the activation of multiple signaling pathways and promotes the development of cancer in plasma cell neoplasms and lymphoma [27,28,29]. Targeting CAMs such as CD38 and CD138/SDC1 with monoclonal antibodies have achieved promising results in multiple myeloma [30, 31]. Daratumumab, a monoclonal antibody directed against CD38, was reported to be effective in advanced-stage large B-cell lymphoma (LBCL) with plasmablastic features [32]. In this study, four PBL patients achieved durable response (12–31 months and ongoing) after the treatment of daratumumab combined with DA-EPOCH [32]. Our results showed that the expression of CAMs was significantly higher in PBL than in DLBCL, suggesting that CAMs may play important roles in the development of PBL. In addition, CAMs may be potential therapeutic targets in PBL and require further investigation in the future.

Conclusions

The findings of our study demonstrated a higher frequency of primary extra nodal involvement and indicated that HIV status was different in Chinese PBL patients than that commonly underscored in the literature. Patients with early-stage disease and CR after treatment may have a favorable prognosis. BCR signaling was downregulated in PBL patients compared to DLBCL patients, indicating that this signaling may play a small role in PBL. The downregulated P53 signaling pathway may contribute to the lymphomagenesis in PBL and serve as a potential therapeutic target in the future. In addition, significant upregulation of cell adhesion genes was identified in PBL, and these CAMs may be potential therapeutic targets in the future. This study has several limitations. This study was retrospective and lacked a comparator group. Another shortcoming was that the treatment and follow-up data was missing in approximately half of the patients and may lead to a significant ascertainment bias in the outcome result. In addition, the sample size for RNA-sequencing was relatively small in our study. Additional large-scale, prospective, and international studies are needed to further identify the concrete pathogenesis and molecular features of PBL and improve the survival outcome of PBL.

Availability of data and materials

The datasets used and/or analyzed in this study are available from the corresponding author upon reasonable request.

Abbreviations

BCR:

B cell receptor

CAMs:

Cell adhesion molecules

CR:

Complete remission

DEGs:

Differentially expressed genes

DLBCL:

Diffuse large B-cell lymphoma

EBER:

EBV-encoded small RNA

EBV:

Epstein-Barr virus

GDC:

Genomic Data Commons

HIV:

Human immunodeficiency virus

IPI:

International prognostic index

LDH:

Lactate dehydrogenase

PBL:

Plasmablastic lymphoma

PCM:

Plasma cell myeloma

PFS:

Progression-free survival

ORR:

Overall response rate

OS:

Overall survival

RT-qPCR:

Reverse-transcriptase quantitative PCR

References

  1. Tchernonog E, Faurie P, Coppo P, Monjanel H, Bonnet A, Algarte Genin M, Mercier M, Dupuis J, Bijou F, Herbaux C, et al. Clinical characteristics and prognostic factors of plasmablastic lymphoma patients: analysis of 135 patients from the LYSA group. Ann Oncol. 2017;28(4):843–8.

    Article  CAS  Google Scholar 

  2. Loghavi S, Alayed K, Aladily TN, Zuo Z, Ng SB, Tang G, Hu S, Yin CC, Miranda RN, Medeiros LJ, et al. Stage, age, and EBV status impact outcomes of plasmablastic lymphoma patients: a clinicopathologic analysis of 61 patients. J Hematol Oncol. 2015;8:65.

    Article  Google Scholar 

  3. Morscio J, Dierickx D, Nijs J, Verhoef G, Bittoun E, Vanoeteren X, Wlodarska I, Sagaert X, Tousseyn T. Clinicopathologic comparison of plasmablastic lymphoma in HIV-positive, immunocompetent, and posttransplant patients: single-center series of 25 cases and meta-analysis of 277 reported cases. Am J Surg Pathol. 2014;38(7):875–86.

    Article  Google Scholar 

  4. Valera A, Balague O, Colomo L, Martinez A, Delabie J, Taddesse-Heath L, Jaffe ES, Campo E. IG/MYC rearrangements are the main cytogenetic alteration in plasmablastic lymphomas. Am J Surg Pathol. 2010;34(11):1686–94.

    Article  Google Scholar 

  5. Chang CC, Zhou X, Taylor JJ, Huang WT, Ren X, Monzon F, Feng Y, Rao PH, Lu XY, Fabio F, et al. Genomic profiling of plasmablastic lymphoma using array comparative genomic hybridization (aCGH): revealing significant overlapping genomic lesions with diffuse large B-cell lymphoma. J Hematol Oncol. 2009;2:47.

    Article  Google Scholar 

  6. Li JW, Shi D, Wan XC, Hu J, Su YF, Zeng YP, Hu ZJ, Yu BH, Zhang QL, Wei P, et al. Universal extracellular vesicles and PD-L1+ extracellular vesicles detected by single molecule array technology as circulating biomarkers for diffuse large B cell lymphoma. Oncoimmunol. 2021;10(1):1995166.

    Article  Google Scholar 

  7. Liu M, Liu B, Liu B, Wang Q, Ding L, Xia C, Dong L. Human immunodeficiency virus-negative plasmablastic lymphoma: a comprehensive analysis of 114 cases. Oncol Rep. 2015;33(4):1615–20.

    Article  CAS  Google Scholar 

  8. Castillo J, Pantanowitz L, Dezube BJ. HIV-associated plasmablastic lymphoma: lessons learned from 112 published cases. Am J Hematol. 2008;83(10):804–9.

    Article  Google Scholar 

  9. Liu Z, Cai Y, Yang Y, Li A, Bi R, Wang L, Shen X, Wang W, Jia Y, Yu B, et al. Activation of MET signaling by HDAC6 offers a rationale for a novel ricolinostat and crizotinib combinatorial therapeutic strategy in diffuse large B-cell lymphoma. J Pathol. 2018;246(2):141–53.

    Article  CAS  Google Scholar 

  10. Jia YJ, Liu ZB, Wang WG, Sun CB, Wei P, Yang YL, You MJ, Yu BH, Li XQ, Zhou XY. HDAC6 regulates microRNA-27b that suppresses proliferation, promotes apoptosis and target MET in diffuse large B-cell lymphoma. Leukemia. 2018;32(3):703–11.

    Article  CAS  Google Scholar 

  11. Castillo JJ, Bibas M, Miranda RN. The biology and treatment of plasmablastic lymphoma. Blood. 2015;125(15):2323–30.

    Article  CAS  Google Scholar 

  12. Han X, Duan M, Hu L, Zhou D, Zhang W. Plasmablastic lymphoma: Review of 60 Chinese cases and prognosis analysis. Med (Baltimore). 2017;96(9):e5981.

    Article  Google Scholar 

  13. Horwitz SM, Zelenetz AD, Gordon LI, Wierda WG, Abramson JS, Advani RH, Andreadis CB, Bartlett N, Byrd JC, Fayad LE, et al. NCCN Guidelines Insights: Non-Hodgkin’s Lymphomas, Version 3.2016. J Natl Compr Canc Netw. 2016;14(9):1067–79.

    Article  Google Scholar 

  14. Castillo JJ, Furman M, Beltran BE, Bibas M, Bower M, Chen W, Diez-Martin JL, Liu JJ, Miranda RN, Montoto S, et al. Human immunodeficiency virus-associated plasmablastic lymphoma: poor prognosis in the era of highly active antiretroviral therapy. Cancer. 2012;118(21):5270–7.

    Article  Google Scholar 

  15. Castillo JJ, Winer ES, Stachurski D, Perez K, Jabbour M, Milani C, Colvin G, Butera JN. Prognostic factors in chemotherapy-treated patients with HIV-associated Plasmablastic lymphoma. Oncologist. 2010;15(3):293–9.

    Article  CAS  Google Scholar 

  16. Davis RE, Ngo VN, Lenz G, Tolar P, Young RM, Romesser PB, Kohlhammer H, Lamy L, Zhao H, Yang Y, et al. Chronic active B-cell-receptor signalling in diffuse large B-cell lymphoma. Nature. 2010;463(7277):88–92.

    Article  CAS  Google Scholar 

  17. Young RM, Phelan JD, Wilson WH, Staudt LM. Pathogenic B-cell receptor signaling in lymphoid malignancies: new insights to improve treatment. Immunol Rev. 2019;291(1):190–213.

    Article  CAS  Google Scholar 

  18. Younes A, Brody J, Carpio C, Lopez-Guillermo A, Ben-Yehuda D, Ferhanoglu B, Nagler A, Ozcan M, Avivi I, Bosch F, et al. Safety and activity of ibrutinib in combination with nivolumab in patients with relapsed non-Hodgkin lymphoma or chronic lymphocytic leukaemia: a phase 1/2a study. Lancet Haematol. 2019;6(2):e67–78.

    Article  Google Scholar 

  19. Tam CS, Anderson MA, Pott C, Agarwal R, Handunnetti S, Hicks RJ, Burbury K, Turner G, Di Iulio J, Bressel M, et al. Ibrutinib plus venetoclax for the treatment of mantle-cell lymphoma. N Engl J Med. 2018;378(13):1211–23.

    Article  CAS  Google Scholar 

  20. Chapman J, Gentles AJ, Sujoy V, Vega F, Dumur CI, Blevins TL, Bernal-Mizrachi L, Mosunjac M, Pimentel A, Zhu D, et al. Gene expression analysis of plasmablastic lymphoma identifies downregulation of B-cell receptor signaling and additional unique transcriptional programs. Leukemia. 2015;29(11):2270–3.

    Article  CAS  Google Scholar 

  21. Klimovich B, Meyer L, Merle N, Neumann M, König AM, Ananikidis N, Keber CU, Elmshäuser S, Timofeev O, Stiewe T. Partial p53 reactivation is sufficient to induce cancer regression. J Exp Clin Cancer Res. 2022;41(1):80.

    Article  CAS  Google Scholar 

  22. Sun C, Li M, Zhang L, Sun F, Chen H, Xu Y, Lan Y, Zhang L, Lu S, Zhu J, et al. IDO1 plays a tumor-promoting role via MDM2-mediated suppression of the p53 pathway in diffuse large B-cell lymphoma. Cell Death Dis. 2022;13(6):572.

    Article  CAS  Google Scholar 

  23. Zhang G, Ren C, Li C, Wang Y, Chen B, Wen L, Jia M, Li K, Mok H, Cao L, et al. Distinct clinical and somatic mutational features of breast tumors with high-, low-, or non-expressing human epidermal growth factor receptor 2 status. BMC Med. 2022;20(1):142.

    Article  Google Scholar 

  24. Pascual M, Mena-Varas M, Robles EF, Garcia-Barchino M-J, Panizo C, Hervas-Stubbs S, Alignani D, Sagardoy A, Martinez-Ferrandis JI, Bunting KL, et al. PD-1/PD-L1 immune checkpoint and p53 loss facilitate tumor progression in activated B-cell diffuse large B-cell lymphomas. Blood. 2019;133(22):2401–12.

    Article  CAS  Google Scholar 

  25. Chapuy B, Stewart C, Dunford AJ, Kim J, Kamburov A, Redd RA, Lawrence MS, Roemer MGM, Li AJ, Ziepert M, et al. Molecular subtypes of diffuse large B cell lymphoma are associated with distinct pathogenic mechanisms and outcomes. Nat Med. 2018;24(5):679–90.

    Article  CAS  Google Scholar 

  26. Morin RD, Mendez-Lago M, Mungall AJ, Goya R, Mungall KL, Corbett RD, Johnson NA, Severson TM, Chiu R, Field M, et al. Frequent mutation of histone-modifying genes in non-Hodgkin lymphoma. Nature. 2011;476(7360):298–303.

    Article  CAS  Google Scholar 

  27. Gupta VA, Matulis SM, Conage-Pough JE, Nooka AK, Kaufman JL, Lonial S, Boise LH. Bone marrow microenvironment-derived signals induce Mcl-1 dependence in multiple myeloma. Blood. 2017;129(14):1969–79.

    Article  CAS  Google Scholar 

  28. Taniguchi M, Ueda Y, Matsushita M, Nagaya S, Hashizume C, Arai K, Kabayama K, Fukase K, Watanabe K, Wardhani LO, et al. Deficiency of sphingomyelin synthase 2 prolongs survival by the inhibition of lymphoma infiltration through ICAM-1 reduction. FASEB J. 2020;34(3):3838–54.

    Article  CAS  Google Scholar 

  29. Slomp A, Peperzak V. Role and regulation of pro-survival BCL-2 proteins in multiple myeloma. Front Oncol. 2018;8:533.

    Article  Google Scholar 

  30. Lokhorst HM, Plesner T, Laubach JP, Nahi H, Gimsing P, Hansson M, Minnema MC, Lassen U, Krejcik J, Palumbo A, et al. Targeting CD38 with daratumumab monotherapy in multiple myeloma. N Engl J Med. 2015;373(13):1207–19.

    Article  CAS  Google Scholar 

  31. Kelly KR, Siegel DS, Chanan-Khan AA, Somlo G, Heffner LT, Jagannath S, Zimmerman T, Munshi NC, Madan S, Mohrbacher A, et al. Indatuximab ravtansine (BT062) in combination with low-dose dexamethasone and lenalidomide or pomalidomide: clinical activity in patients with relapsed / refractory multiple myeloma. Blood. 2016;128:22.

    Article  Google Scholar 

  32. Ryu YK, Ricker EC, Soderquist CR, Francescone MA, Lipsky AH, Amengual JE. Targeting CD38 with daratumumab plus chemotherapy for patients with advanced-stage plasmablastoid large B-cell lymphoma. J Clin Med. 2022;11:16.

    Article  Google Scholar 

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Acknowledgements

Not applicable.

Funding

This study was supported by the National Natural Science Foundation of China (Grant No. 81470353, 81870155, 81700195), Innovation Group Project of Shanghai Municipal Health Commission (Grant No. 2019CXJQ03), Shanghai Science and Technology Development Fund (Grant No. 19MC1911000), Shanghai Municipal Key Clinical Specialty (Grant No. shslczdzk01301), Innovation Program of Shanghai Science and Technology Committee (Grant No. 20Z11900300), Clinical Research Plan of Shanghai Hospital Development Center (Grant No. SHDC2020CR3046B), Shanghai Science and Technology Development Fund (Grant No. 19MC1911000), and the Scientific Research Launch Project for new employees of the Second Xiangya Hospital of Central South University.

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Authors and Affiliations

  1. Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China

    Di Shi, Xiao-Chun Wan, Tian Tian, Jue Hu, Qun-Ling Zhang, Yi-Fan Su, Yu-Peng Zeng, Zi-Juan Hu, Bao-Hua Yu, Xiao-Qiu Li, Ping Wei & Xiao-Yan Zhou

  2. Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China

    Di Shi, Xiao-Chun Wan, Tian Tian, Jue Hu, Qun-Ling Zhang, Yi-Fan Su, Yu-Peng Zeng, Zi-Juan Hu, Bao-Hua Yu, Xiao-Qiu Li, Ping Wei & Xiao-Yan Zhou

  3. Institute of Pathology, Fudan University, Shanghai, 200032, China

    Di Shi, Xiao-Chun Wan, Tian Tian, Jue Hu, Qun-Ling Zhang, Yi-Fan Su, Yu-Peng Zeng, Zi-Juan Hu, Bao-Hua Yu, Xiao-Qiu Li, Ping Wei & Xiao-Yan Zhou

  4. GenePlus-Shenzhen, Shenzhen, 518000, People’s Republic of China

    Lin Gao

  5. Institute of Microbiology, Chinese Academy of Sciences, Beijing, 102199, China

    Lin Gao

  6. Department of Oncology, Hunan Cancer Hospital, Changsha, 410000, China

    Jin Li

  7. Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China

    Ji-Wei Li

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  1. Di Shi
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Contributions

DS, JWL, and XYZ participated in the research design and coordination and helped draft the manuscript. DS and JWL conducted the experiments. WXC and YBH reviewed the main immunohistochemical markers. DS, JWL, JL, TT, JH, QLZ, YFS, YPZ, ZJH, XQL, and PW contributed to clinical sample collection. LG, DS, and JWL performed the data analysis. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Ji-Wei Li or Xiao-Yan Zhou.

Ethics declarations

Ethics approval and consent to participate

The research protocol was performed in accordance with the Declaration of Helsinki and approved by Ethics Institutional Review Board (IRB) of Fudan University Shanghai Cancer Center (the approval number: 050432–4-2108), and informed consent was obtained from all participants included in the study in agreement with institutional guidelines.

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Informed consent for publication was obtained from all participants.

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The authors declare no competing interests.

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Supplementary Information

Additional file1. Table S1

: RT-qPCR primers. Table S2: Clinicopathologic characteristics of PBL patients in our study. Table S3: Clinicopathologic characteristics of PBL patients and DLBCL patients for RNA sequencing in our study. Fig. S1: Expression profiles. A. Hierarchical clustering and heat map of DEGs between PBL and GCB-DLBCL. Red blocks represent the overexpressed genes, while the blue blocks represent the lowly expressing genes. B. Volcano plot of DEGs (FDR < 0.05) between PBL and GCB-DLBCL. C. Significantly upregulated pathways in PBL compared to GCB-DLBCL. D. Significantly downregulated pathways in PBL compared to GCB-DLBCL. -F. Downregulation of DEGs of BCR E and P53 F signaling pathways in PBLs compared to GCB-DLBCL. Fig. S2: Expression profiles. A. Hierarchical clustering and heat map of DEGs between PBL and non-GCB-DLBCL. Red blocks represent the overexpressed genes, while the blue blocks represent the lowly expressing genes. B. Volcano plot of DEGs (FDR < 0.05) between PBL and non-GCB-DLBCL. C. Significantly upregulated pathways in PBL compared to non-GCB-DLBCL. D. Significantly downregulated pathways in PBL compared to GCB-DLBCL. E-H. Downregulation of DEGs of BCR E, TCR F, Jak-STAT G and TLR H signaling pathways in PBLs compared to GCB-DLBCL.

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Shi, D., Gao, L., Wan, XC. et al. Clinicopathologic features and abnormal signaling pathways in plasmablastic lymphoma: a multicenter study in China. BMC Med 20, 483 (2022). https://doi.org/10.1186/s12916-022-02683-9

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Keywords

BMC Medicine

ISSN: 1741-7015

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