New Insights Into the Role of Neutrophils in Lymphoma.

Abbreviations

antibody‐dependent cellular cytotoxicity

anaplastic large cell lymphoma

a proliferation‐inducing ligand

bone marrow

citrullinated histone H3

cutaneous T‐cell lymphoma

dendritic cells

diffuse large B‐cell lymphoma

extracellular matrix

epithelial‐mesenchymal transition

extranodal NK/T cell lymphoma

follicular lymphoma

granulocyte colony‐stimulating factor

Hodgkin lymphoma

hematopoietic stem cells

low‐density neutrophils

lymph nodes

mucosa‐associated lymphoid tissue

mycosis fungoides

matrix metalloproteinases

myeloperoxidase

neutrophil elastase

neutrophil extracellular trap

neutrophil‐to‐lymphocyte ratio

nodular sclerosis classical Hodgkin lymphoma

peripheral blood

peripheral blood mononuclear cells

polymorphonuclear myeloid‐derived suppressor cells

peripheral T‐cell lymphoma

rituximab plus cyclophosphamide, doxorubicin, vincristine and prednisone

reactive oxygen species

secondary lymphoid organs

tumor‐associated neutrophils

tissue factor

tumor microenvironment

tissue‐resident neutrophils

Introduction

Neutrophils are the first immune cells to arrive at sites of inflammation [ 1 ] and protect the host through phagocytosis, degranulation, reactive oxygen species (ROS) generation, recruitment of other immune cells, and neutrophil extracellular traps (NETs) formation/NETosis [ 2 , 3 ]. In humans, neutrophils account for 50%–70% of circulating immune cells, whereas in mice, they represent 10%–25% [ 2 , 4 , 5 , 6 ]. Immune protection relies on the infiltration of neutrophils into the challenged tissues.

Neutrophils have long been characterized as short‐lived effector cells with minimal infiltration into healthy tissues under physiological conditions. Conventional studies estimated their circulating half‐life at less than 24 h under steady‐state conditions [ 7 , 8 , 9 ]. However, in vivo labeling techniques have revealed a subset of neutrophils with extended lifespans exceeding 90 h [ 10 ], though this remains controversial [ 11 ]. It is universally acknowledged that stress signals (e.g., cytokines, hypoxia, or pathogen exposure) enhance neutrophils survival in circulation and tissues. Recent advances have highlighted the functional heterogeneity of neutrophils, challenging the traditional view of them as a homogeneous, terminally differentiated population. Single‐cell RNA sequencing, spatial transcriptomics, and maturity‐resolved surface marker profiling have uncovered distinct neutrophil subsets across tissues [ 12 , 13 , 14 ]. Seminal work in mice reveals that neutrophils constitutively traffic through healthy organs, including bone marrow (BM), spleen, lung, lymph nodes (LNs), white adipose tissue, skeletal muscle, skin, and intestinal mucosa, in a regulated manner [ 12 , 15 ]. While tissue‐resident macrophages are widely recognized as a central regulator of tissue homeostasis, emerging evidence now points to the existence of tissue‐resident neutrophils (TRNs), a specialized subpopulation that orchestrates analogous homeostatic functions within specific niches [ 16 ]. However, the concept of TRNs remains both novel and controversial. Recently, He et al. [ 17 ] systematically reviewed the tissue‐resident immune cells and characterized TRNs as tissue‐infiltrating neutrophils that acquire distinct tissue‐specific phenotypes and exhibit prolonged tissue residency. Most critically, we contend that the defining biological feature is their ability to extravasate into interstitial spaces under steady‐state conditions. However, key gaps persist in our understanding of their developmental pathways, immunophenotypic signatures, and mechanistic roles in tissue physiology.

Emerging insights into neutrophil biology have unveiled their multifaceted roles in tumor pathophysiology, as highlighted in comprehensive reviews [ 18 , 19 , 20 , 21 , 22 , 23 , 24 ]. While current evidence predominantly derives from solid tumor research, the functional contributions of neutrophils to lymphoma remain enigmatic, despite the shared ontogeny between lymphoma cells with neutrophils in BM, spleen, and LNs. This knowledge gap originates from two fundamental research limitations. First, the field has long suffered from systematic underestimation of neutrophils' pathological significance. Second, recent findings indicate that neutrophils display complex, context‐dependent functional plasticity throughout tumor progression, ranging from tumor‐promoting to suppressive roles depending on microenvironmental cues [ 25 , 26 ]. Neutrophils engage in multifaceted crosstalk with malignant lymphocytes and stromal elements, forming dynamic tumor‐immune networks that defy simple characterization. These complexities are further exacerbated by technical limitations in modeling the spatiotemporal dynamics of neutrophil‐lymphoma interactions.

Lymphoma is a group of lymphoid neoplasms originating from B, T or NK cells, spreading its course to lymphoid organs, LNs, spleen, and frequently disseminating to extranodal sites. Despite remarkable advances in lymphoma immunotherapy, including monoclonal antibodies, immune checkpoint inhibitors, and CAR‐T cell therapy, a substantial proportion of patients develop resistance, primarily driven by a suppressive tumor microenvironment (TME) [ 27 , 28 , 29 , 30 ]. Emerging evidence now positions tumor‐associated neutrophils (TANs) as pivotal orchestrators of tumor progression through multifaceted immunosuppressive mechanisms, and thus elevated TANs as a compelling therapeutic target in next‐generation cancer immunotherapy development [ 21 , 24 , 25 , 26 ]. This clinical potential is further underscored by the long‐established prognostic value of the neutrophil‐to‐lymphocyte ratio (NLR), a biomarker first linked to lymphoma outcomes over 15 years ago [ 31 ]. Given the unique phenotypic profiles of neutrophils in lymphoid tissues, targeting TANs may represent a promising therapeutic strategy to overcome immunosuppression in lymphoma. This review systematically synthesizes current evidence on the roles of neutrophils in lymphoid tissues homeostasis and lymphoma pathology, and the translational opportunities of TANs‐directed therapies.

Neutrophils Life Cycle

The life cycle of neutrophils (Figure 1 ) begins with the granulopoiesis in BM, where they undergo progressive maturation before being released into the circulation under circadian control [ 15 , 32 ]. In the vasculature, neutrophils exist in either a freely circulating pool or a marginated pool that adheres to the endothelium. Marginated neutrophils serve as a rapidly deployable reservoir for inflammatory responses, which traffic into BM, liver, spleen, and more controversially, in the lungs [ 2 , 9 , 33 ]. Although it is currently unknown why and how neutrophils persist in these organs, the phenomenon of multiorgan infiltration in the steady‐state is a conserved feature across species [ 2 , 15 ]. A specific subset, termed tissue‐resident neutrophils (TRNs), can extravasate into the interstitium of lymphoid organs under steady‐state conditions [ 15 , 34 ]. Following a short half‐life, senescent neutrophils are primarily cleared by macrophages in the BM, spleen, and liver [ 5 , 35 ]. Notably, neutrophils can undergo reverse migration (rM), reentering the circulation after tissue infiltration; under pathological conditions [ 36 ], convincing evidence for this process in the physiological state is lacking [ 37 ].

Under pathologic situation, emergency granulopoiesis and extramedullary hematopoiesis can occur, often accompanied by the appearance of banded neutrophils in the peripheral blood (“left shift”) [ 38 , 39 , 40 ]. At sites of inflammation, neutrophils deploy effector functions including phagocytosis, degranulation, and NETosis, with their lifespan prolonged by pro‐survival signals [ 2 , 3 ]. Postresolution, neutrophil clearance is mediated by macrophages or, alternatively, via rM [ 36 , 37 ]. Accumulating evidence from real‐time in vivo imaging has substantiated rM, a process that appears to exert dual effects: promoting the resolution of local inflammation while potentially disseminating inflammatory mediators systemically [ 37 , 41 , 42 ]. Although the precise molecular mechanisms remain incompletely defined, rM is characterized as an adaptive response dependent on vascular permeability and chemotactic gradients [ 43 , 44 ], with rM neutrophils displaying a distinct ICAM‐1 high CXCR1 low immunophenotype [ 45 ]. Emerging hypotheses suggest that rM‐experienced neutrophils may reenter the BM and contribute to immunological memory, aligning with recent discoveries implicating neutrophils in trained immunity [ 46 , 47 ].

Neutrophils in Lymphoid Organs Under Physiological Conditions

Lymphoid organs, including thymus, BM, spleen, LNs, and other lymphoid tissues, support distinct stages of the neutrophil life cycle, from production and storage to clearance and immune modulation (Figure 1 ). Within BM, neutrophils undergo a developmental journey from production to maturity. The resulting mature neutrophils contribute to hematopoietic stem cell (HSC) retention and support the quiescence of myeloid‐biased HSCs [ 13 , 48 , 49 ]. The BM also serves as the dominant site for steady‐state neutrophil clearance, with approximately 33% of aged neutrophils undergoing CXCR4‐dependent homing to BM, where they execute programmed apoptosis and are phagocytosed by macrophages [ 50 , 51 , 52 ]. Senescent neutrophils may disrupt hematopoietic niches via protease release, triggering progenitor egress, although the mechanisms underlying physiological neutrophil turnover remain incompletely defined [ 50 ].

In the spleen, neutrophils localize predominantly to the extravascular marginal zone and red pulp, as revealed by multiphoton and light‐sheet microscopy [ 15 , 53 ]. Traditionally, the vascular system of the spleen is considered a main site of the marginated pool. Splenic TRNs in the marginal zone exhibit a distinct phenotype (CD15 int/low CD16 int/low ICAM‐1 low CD11b high ), form NET‐like structures, and support B cell maturation and antibody production through B cell‐activating factor (BAFF), a proliferation‐inducing ligand (APRIL), and IL‐21 [ 53 ]. Under steady conditions, the spleen may eliminate approximately 30% senescent neutrophils [ 51 , 52 ], highlighting its role in systemic neutrophil homeostasis.

In LNs, neutrophils mainly reside in the interfollicular zones and the floor of subcapsular sinus under physiological conditions, where they closely associate with T cells and express CXCR4 and MHC II at higher levels than circulating neutrophils [ 34 ]. LN neutrophils exhibit unique spatial and phenotypic features. Unlike neutrophils in lung and liver [ 15 ], the majority of neutrophils in LNs are TRNs, present in the interstitial, outside the vascular [ 34 ]. In contrast to spleen TRNs, LN TRNs seldom localize to B cell follicles. These cells participate in immune surveillance by shuttling peripheral antigens to LNs and [ 34 ], under inflammatory conditions, can recruit additional neutrophils to establish a self‐reinforcing loop [ 54 ].

Aging drives notable remodeling of neutrophil populations in lymphoid organs. In aged mice, neutrophils accumulate in both BM and secondary lymphoid organs (SLOs), exhibiting prolonged survival, hypersegmented nuclei, and a pro‐inflammatory phenotype (F4/80 neg CD11b pos Ly6G pos SSC hi ) with elevated TNFα secretion [ 55 ]. Notably, splenic TRNs infiltrate white pulp regions and establish direct contacts with T/B cells, a feature mechanistically linked to age‐related autoimmunity [ 55 ]. Despite the well‐recognized increase in lymphoma incidence with age, the potential links between aging‐related TRN remodeling in SLOs and disease pathogenesis remain unexplored [ 56 ].

Collectively, emerging evidence reveals that neutrophils, particularly TRNs in SLOs, exhibit tissue‐specific immunophenotypes and functional diversity under steady‐state conditions [ 15 , 34 , 57 , 58 ]. These findings challenge traditional views of neutrophils as short‐lived, nonspecific effectors, revealing their spatiotemporal dynamics and immunoregulatory potential within lymphoid microenvironments and pointing to new directions for future research.

Neutrophils in Lymphoma

Currently, it is widely recognized that chronic inflammation is a significant hallmark of tumors [ 59 , 60 ] and affects all stages of tumor development as well as therapeutic effect [ 61 , 62 , 63 ]. The role of neutrophils in tumor biology is far be overlooked for their short lives and well‐defined role in innate immunity. Meanwhile, immune cells such as macrophages have overshadowed the role of neutrophils in cancers [ 64 ]. Fortunately, emerging evidence now reveals neutrophils' unexpected capacity for adaptive immune modulation [ 24 ]. Neutrophils are now recognized as crucial components of TME, exhibiting remarkable phenotypic plasticity and functional diversity [ 64 , 65 ].

As key inflammatory components of TME, neutrophils play pivotal roles in multiple oncological processes including tumorigenesis, disease progression, metastatic dissemination, immune modulation, and therapeutic responsiveness [ 22 , 25 , 66 ]. Neutrophils within TME are now designated TANs. TANs have a longer half‐life because the TME is enriched with pro‐survival chemokines, cytokines, and DAMPs [ 67 , 68 ]. Neutrophils can either promote or inhibit tumor growth depending on their polarization state, which is shaped by microenvironmental cues [ 65 , 67 ]. In 2009, Fridlender et al. first proposed to classify TANs into antitumor N1 and pro‐tumor N2 subsets, following the categorization model of tumor‐associated macrophages [ 69 ]. Type I interferons (IFNs) induce the polarization of TANs into N1 phenotype [ 70 , 71 ], while transforming growth factor‐beta (TGF‐β) can polarize neutrophils into a pro‐tumor N2 phenotype [ 69 , 70 ]. In mouse models, TGF‐β antagonists promote an increase in N1‐polarized TANs within TME and suppress tumor growth [ 69 ]. However, the N1/N2 dichotomy reflects functional states rather than discrete subsets, as no definitive markers currently distinguish these populations. Moreover, the migratory patterns, activation mechanisms, phenotypic switching, and spatiotemporal dynamics of N1 and N2 TANs during in vivo disease progression remain poorly characterized.

Advanced single‐cell analyses have identified specialized neutrophil subsets with stage‐specific functions across pathological spectra, from infection resolution to chronic inflammation and malignant transformation [ 5 , 19 , 67 , 72 ]. Alongside the successful application of immunotherapy in tumors, particularly in hematological malignancies, the immunosuppressive roles of neutrophils in TME have been demonstrated, which may lead to poor prognosis and a poor response to immunotherapeutic strategies [ 22 , 25 , 26 , 66 , 73 ]. Functionally, N2‐polarized TANs represent immunosuppressive neutrophils. This raises a critical question: what are the key distinctions and relationships between N2 TANs and polymorphonuclear myeloid‐derived suppressor cells (PMN‐MDSCs)? MDSCs are a heterogeneous population of myeloid cells that suppress immune responses. In mice, they are typically defined by coexpression of CD11b and Gr1, and divided into monocytic MDSCs (M‐MDSCs, CD11b + Ly6c + Ly6G − ) and PMN‐MDSCs (CD11b + Ly6G + Ly6c − ), whereas their phenotypic characterization in humans remains debated. Notably, markers currently used to identify human PMN‐MDSCs (CD1 − CD15 + CD66b + CD16 + CD11b + CD33 + HLA‐DR − ) largely overlap with those of conventional mature neutrophils (CD14 − CD15 + CD66b + CD16 + ) [ 26 , 65 , 74 ]. Thus, we propose that PMN‐MDSCs may represent a pathological subset of neutrophils, though this classification requires further validation and expert consensus.

To overcome immunotherapy resistance mediated by immunosuppressive TME, targeting TANs has emerged as a promising focus in contemporary tumor immunotherapy research [ 75 ]. While lymphoma immunotherapy has witnessed rapid advancements in recent years, clinical benefits remain limited to patient subgroups [ 28 ]. To optimize therapeutic outcomes, a systematic dissection of immunosuppressive networks orchestrated by TANs in lymphoma is imperative. Unlike most solid tumors, lymphoma‐infiltrating neutrophils can derive from both TRNs in lymphoid organs and BM‐recruited neutrophils. Similar to solid tumors, TANs in lymphoma also exhibit marked heterogeneity, and the PB NLR is associated with lymphoma progression and prognosis (Figure 2 ).

Neutrophil Infiltrating in Lymphoma

The earliest report of neutrophil infiltration in lymphoma was a 1995 case study describing ALK‐positive anaplastic large cell lymphoma (ALK+ ALCL) accompanied by neutrophil infiltration, which proposed that neutrophil infiltration could define a new subtype [ 76 ]. Recent studies have shown that neutrophil‐rich ALCL responds well to rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R‐CHOP) but tends to recur [ 77 , 78 ].

More extensive research has focused on B‐cell non‐Hodgkin lymphomas (B‐NHLs). In 2007, Huard and colleagues demonstrated that elevated neutrophil infiltration in lymphoma lesions, combined with high APRIL expression, correlated negatively with survival in patients with diffuse large B‐cell lymphoma (DLBCL) [ 79 ]. A decade later, the same research team further elucidated that CXCL‐8 + DLBCL facilitates the recruitment of neutrophils, which secrete the tumor‐promoting factor APRIL, thereby driving DLBCL progression [ 80 ]. Subsequently, using datasets GSE10846 , GSE32918 , GSE53786 , and GSE23501 , they identified Elane , a gene signature associated with TANs, as linked to poor prognosis in DLBCL patients treated with R‐CHOP [ 81 ]. More recently, a study focusing on macrophages revealed CD66 + neutrophils infiltrating lymphoma lesions are associated with poor prognosis in DLBCL patients, as shown by multiplex immunohistochemistry (IHC) [ 82 ]. Beyond DLBCL, elevated neutrophil infiltration has been observed in follicular lymphoma (FL) undergoing transformation and is associated with shorter transformation‐free survival and an immunosuppressive TME [ 83 ]. Even in indolent lymphomas such as low‐grade gastric mucosa‐associated lymphoid tissue (MALT) lymphoma, neutrophils' infiltration can negatively impact the efficacy of first‐line H. pylori eradication therapy [ 84 ], suggesting a role in modulating treatment response.

In Hodgkin lymphoma (HL), evidence is scarcer. A seminal study in classical HL reported neutrophil infiltration and neutrophil extracellular trap (NET) formation specifically in 75% of nodular sclerosis subtype (NS‐cHL) cases, where it was spatially associated with fibrosis [ 85 ]. Unfortunately, this study is a retrospective cross‐sectional analysis that only observed the relationship between NETs and lymph node fibrosis, without further summarizing their association with prognosis. A recent case report of gastric HL with marked neutrophil infiltration and neutrophilic leukocytosis described a refractory clinical course with early relapse, hinting at a possible adverse role [ 86 ]. The primary studies investigating neutrophil infiltration in lymphoma lesions are summarized in Table 1 .

Mechanistic insights into the pro‐tumorigenic functions of neutrophils in lymphomagenesis and progression have primarily emerged from murine models. In 2019, Tan et al. [ 88 ] developed a Becn1 ΔM mouse model, specifically knocking out Beclin‐1 in myeloid cells, and observed that 20%–40% of these mice spontaneously developed B‐cell lymphomas, with B‐lymphoma cells colocalizing with neutrophils [ 88 ]. The interaction between neutrophils and B cells was found to activate the IL‐21/STAT3/IRF1 and CD40L/ERK signaling pathways, upregulate PD‐L1 expression, and suppress CD8 + T cell function, thereby promoting the initiation and progression of B‐cell lymphoma [ 88 ]. These findings collectively suggest that neutrophils may play a critical role in influencing B‐lymphocyte maturation and inducing lymphomagenesis. In murine models of lymphoma secondary to autoimmune disease, a pro‐tumorigenic neutrophil subset with B‐cell helper phenotypes has been identified infiltrating lymphoma lesions, with a propensity for NET extrusion [ 89 ]. In peripheral T‐cell lymphoma (PTCL) mouse models, pathological lesions in the spleen, LNs, lungs, and skin show extensive neutrophil infiltration [ 90 ]. CD4 + T cells and neutrophils synergistically accelerate disease progression through the secretion of IFN‐γ and IL‐6, while depletion of neutrophils or downregulation of IL‐6 promotes disease remission and improves survival rates in lymphoma‐bearing mice [ 90 ]. In Dalton lymphoma mice model, a model of T‐cell lymphoma, neutrophils infiltrate in vital organs including liver, lungs, spleen, kidney, LNs and peritoneum and contribute to lymphoma progression [ 91 ]. Tinospora cordifolia suppresses neutrophil infiltration and hyperactivation, exerting both preventive and therapeutic effects against cancer progression [ 92 ]. A notable contradiction arose in a Burkitt lymphoma SRG mouse xenograft model, in which neutrophil depletion markedly attenuated the therapeutic efficacy of the combined regimen of rituximab and anti‐SIRPα antibody, while the combination therapy exhibited no measurable impact on neutrophil/macrophage infiltration but effectively enhanced their phagocytic capacity to suppress tumor growth [ 93 ]. This finding underscores the context‐dependent duality of neutrophil functions.

In summary, although neutrophil infiltration is consistently associated with unfavorable clinical features across various lymphomas, research on TANs in lymphoid malignancies remains nascent compared to solid tumors. Current studies are largely confined to documenting their presence and gross correlation with outcomes. A significant knowledge gap exists regarding the phenotypic and functional heterogeneity of lymphoma‐infiltrating neutrophils and the precise mechanisms governing their recruitment and multifaceted roles within the unique lymphoid TME.

Circulating Neutrophils in Lymphoma Patients

While investigations into circulating neutrophil alterations in lymphoma patients are also limited, some phenotypic characterizations have been attempted (Table 2 ). In patients with cutaneous T‐cell lymphoma (CTCL), activated neutrophils displaying a hypodense phenotype, characterized by elevated CD11b and CD66b expression alongside reduced CD62L levels, are detectable in PB, even at early disease stages, and have been shown to promote lymphoma progression [ 99 ]. In DLBCL, an increase in CD11b + CD16 + neutrophils was observed, whereas no such increase was found in HL or FL, although this finding was based on a limited cohort (6 DLBCL, 5 HL, and 5 FL cases) [ 105 ]. More recently, a study in Africa proposed that chronic malaria exposure remodels the neutrophil compartment in children, skewing it toward an aged phenotype (CD62L −/+ CD184 + ) and away from a mature phenotype (CD11b + CD62L + CD182 + CD184 − ), thereby potentially contributing to Burkitt lymphomagenesis. Consistent with this finding, children diagnosed with Burkitt lymphoma exhibited a significant expansion of immature neutrophils (CD10 − ) linked to malaria exposure [ 106 ].

Compared with conventional neutrophils, research in lymphoma has focused more extensively on PMN‐MDSCs. Higher frequencies of PMN‐MDSCs (defined as Lin − CD33 + CD11b + CD123 low HLA‐DR − ) have been observed in patients with newly diagnosed DLBCL than in healthy controls, although this increase was not associated with patient prognosis [ 94 ]. Similarly, elevated levels of PMN‐MDSCs (CD33 + CD11b + HLA‐DR − CD15 + ) were found in patients with extranodal NK/T‐cell lymphoma (ENKL), but also showed no prognostic association [ 100 ]. In HL patients, circulating Lin − CD11b + CD33 + HLA‐DR − CD14 − PMN‐MDSCs were elevated and were significantly higher in patients who failed to achieve complete remission; however, overall levels did not show a statistically significant correlation with prognosis [ 104 ]. Conversely, a separate study reported that PMN‐MDSCs (CD66b + CD33 + HLA‐DR − ) were increased in the peripheral blood mononuclear cells (PBMCs) of patients with both HL and B‐NHL, correlated with greater biological aggressiveness and poor prognosis, and were predominantly composed of mature, activated CD11b + CD16 + low‐density neutrophils (LDNs) [ 103 ]. An immature neutrophil population exhibiting a CD10 − CD14 − CD45 + HLA‐DR − phenotype was significantly elevated in patients with NHL and may correlate with disease progression and inferior outcomes [ 95 , 102 , 107 , 108 ]. In DLBCL, patients with high levels of PMN‐MDSCs (CD11b + CD33 + HLA‐DR low/− CD124 + CD15 + ) were more likely to have the nongerminal center B‐cell‐like (non‐GCB) subtype, and persistence in high‐risk patients may predict early relapse [ 96 ]. CD11b + CD15 + PMN‐MDSCs were significantly elevated in NHL patients compared with those with lymphadenitis and were identified as an independent prognostic factor [ 101 ]. Furthermore, CD11b + CD14 − CD15 + PMN‐MDSCs were significantly elevated in patients with mycosis fungoides (MF) and correlated with inferior outcomes [ 98 ]. In contrast, one study found that PMN‐MDSCs defined as CD11b + CD33 + HLA‐DR low/− CD14 − CD15 + showed no significant increase in PB of DLBCL patients compared with healthy controls [ 97 ]. Notably, M‐MDSCs (CD14 + HLA‐DR low/− ) have a more consistent definition across studies and are consistently reported to be increased in lymphoma patients, where they correlate with poor prognosis [ 109 ].

The substantial heterogeneity in phenotypic definitions of PMN‐MDSCs across studies, using markers such as CD11b, CD33, CD15, CD66b, and CD16, likely contributes to the variability in reported prognostic correlations. CD11b and CD33 are nonspecific, as they are expressed not only on PMN‐MDSCs but also on NK cells and all myeloid lineage cells. Similarly, CD15 and CD66b are present on eosinophils and mature neutrophils, whereas CD16 is expressed on NK cells, monocytes, and mature neutrophils. Notably, all of these markers are also found on TANs. Given that current marker panels cannot reliably distinguish PMN‐MDSCs from the broader TAN population, we propose that classifying PMN‐MDSCs as a functionally distinct, immunosuppressive subset of TANs may provide a more coherent and productive framework for investigating tumor‐mediated immunosuppression and developing targeted therapeutic strategies [ 26 , 65 , 74 ].

Although neutrophil phenotypic heterogeneity in the PB of lymphoma patients has been documented, clinical investigations continue to prioritize the NLR, a clinically accessible metric of systemic inflammation derived from complete blood counts. The NLR has emerged as a promising prognostic biomarker in oncology because of its simplicity and clinical availability. An elevated NLR is a well‐validated poor prognostic factor across diverse solid tumors, including carcinomas of the pancreas, colorectum, urothelium, nasopharynx, stomach, breast, endometrium, and liver, as well as soft tissue sarcomas [ 110 ].

The prognostic utility of NLR in lymphoma was first suggested in 2010 by Porrata et al. [ 31 ], who proposed it as a simple, inexpensive, and standardized factor for assessing outcomes in patients with DLBCL treated with R‐CHOP. Subsequent studies have demonstrated that elevated NLR at diagnosis correlates with poor prognosis in patients with DLBCL [ 111 ], HL [ 112 , 113 ], early‐stage cHL [ 114 ], primary central nervous system lymphoma (PCNSL) [ 115 ], pediatric HL [ 116 ], MF [ 117 ], extranodal NK‐T cell lymphoma [ 118 ], T‐lymphoblastic lymphoma [ 119 ], and HIV‐associated lymphoma [ 120 ]. Notably, NLR also exhibits diagnostic value in identifying lymphoma among patients with asymptomatic lymphadenopathy [ 121 ]. However, conflicting evidence exists, with some studies reporting no significant association between NLR and outcomes in patients with mycosis fungoides [ 122 ], and HIV‐associated NHL [ 123 ]. While the NLR is a simple and effective prognostic marker, future models should integrate multiple parameters to enhance predictive accuracy and guide personalized treatment strategies.

Given that both lymphoma pathophysiology and immuno‐chemotherapy can profoundly alter immune homeostasis, investigating posttreatment inflammatory indices may offer additional prognostic and therapeutic insights. However, such studies remain limited. Tan et al. [ 124 ] observed that elevated NLR following ABVD therapy was associated with worse outcomes in HL patients. In contrast, a high poststeroid NLR correlated with a better prognosis in PCNSLs patients [ 125 ]. In DLBCL, a pretreatment NLR ≥ 3 predicts poor prognosis, whereas a reduction in posttreatment NLR to < 3 after R‐CHOP treatment correlates with improved survival [ 126 ]. Paradoxically, preclinical studies suggest a complex role for neutrophils in therapy: rituximab was less effective in a B‐cell lymphoma SCID mouse model in the absence of neutrophils [ 127 ], and administration of granulocyte colony‐stimulating factor (G‐CSF) or granulocyte‐macrophage CSF (GM‐CSF) may enhance the antitumor effects of rituximab by expanding CD11b high CD18 high circulating neutrophils [ 128 ]. These findings underscore the dual and context‐dependent role of neutrophils in lymphoma biology and treatment response.

In the era of immunotherapy, refining posttreatment prognostic scoring systems and optimizing therapeutic strategies remain imperative. Integrating the NLR with phenotypic characterization of circulating neutrophils could yield a novel prognostic framework with enhanced clinical utility. However, such integration entails considerable complexity. Even under physiological conditions, neutrophil phenotypes are influenced by multiple host factors, including sex, age, and circadian rhythms. For example, blood sampling at different time points reveals dynamic shifts in subsets enriched in younger neutrophils (e.g., CXCR2 + CXCR4 − CD62L + ) versus aged neutrophils (e.g., CXCR2 − CXCR4 + CD62L − ). Current consensus proposes that steady‐state circulating mature neutrophils exhibit conserved phenotypes: LCS − cKit − Ly6C low CD11b + Ly6G hi CXCR2 + CXCR4 − (in mice) and CD15 + CD66b + CD11b + CD49d − CD101 + CD16 hi CD10 + (in human) [ 129 ]. Pathological states further amplify this heterogeneity. Most importantly, recent single‐cell sequencing studies demonstrate only partial phenotypic overlap between circulating neutrophils and TANs within the TME [ 130 ]. Thus, even combinatorial assessment of NLR and circulating neutrophil phenotypes cannot serve as a direct proxy for TAN biology.

NETs in Lymphoma

TANs release NET‐derived products into PB through NETosis, which show potential as novel biomarkers for tumor diagnosis and prognosis [ 131 , 132 , 133 ]. NETs are web‐like filamentous extracellular structures composed of DNA, histones, and cytotoxic granule‐derived proteins, including neutrophil elastase (NE), myeloperoxidase (MPO), citrullinated histone H3 (CitH3), MMPs, tissue factor (TF), and cathepsin G [ 18 , 23 , 131 , 132 ]. These structures are released by neutrophils in response to pathogens or sterile stress, and their compositional complexity underpins functional diversity [ 134 , 135 , 136 ]. NETs immobilize and trap pathogens, facilitating host defense and contributing to immune homeostasis [ 132 ]. Initially identified in infection studies in 2004 [ 137 ], NETs were later shown to be induced by chronic inflammation‐driven neutrophil activation [ 131 , 132 ]. Their role in oncology emerged in 2010 when NETs were first reported to promote lung cancer progression [ 138 ]. Subsequent investigations into chronic inflammation‐mediated remodeling of the TME have further accelerated NETs research.

Current evidence indicates that in solid malignancies, NETs engage in bidirectional crosstalk with cancer cells to reshape cancer biology, and exhibit context‐dependent dual functions (pro‐tumor and antitumor) [ 18 , 131 , 132 , 139 ]. The pro‐tumor roles of NETs have garnered significant research focus. NETs favor tumor cell proliferation, metastasis through extracellular matrix (ECM) remodeling, angiogenesis induction, epithelial‐mesenchymal transition (EMT) promotion, cancer‐associated thrombosis, and immunosuppressive TME modulation [ 18 , 23 , 140 ]. Moreover, NETs can capture circulating tumor cells (CTCs) and promote their colonization [ 141 , 142 ]. It is worth noting that NETs have also been implicated in postoperative infection‐related metastasis and occurrence [ 143 , 144 ]. Critically, elevated circulating NET biomarkers correlate with poor prognosis across multiple cancers [ 145 ].

Paradoxically, NETs can exert antitumor functions via direct cytotoxicity against malignant cells and immune activation [ 139 , 146 , 147 , 148 ]. They mitigate inflammation by degrading cytokines and chemokines, and coordinate the resolution of sterile cancer‐related inflammation. NETs derived from N1‐polarized TANs may mediate antitumor effects [ 149 ]. Emerging evidence indicates that NETs exhibit subset‐specific compositional heterogeneity [ 135 ]. The complexity of NETs is further highlighted by their tumor‐type‐specific functions. For instance, elevated NET levels correlated with improved survival in prostate cancer, esophageal cancer, skin cancer, sarcoma, breast cancer, and colon cancer; conversely, higher NET levels are associated with poorer survival in pancreatic cancer, lung squamous cell carcinoma, glioblastoma, low‐grade glioma, ovarian cancer, gastric cancer, and bladder cancer [ 150 ].

Cancer cells influence neutrophil activity, maturation, and fate. Tumor‐derived mediators (e.g., G‐CSF, IL‐8, CXCL1/2, cathepsin C, and Toll‐like receptor ligands), hypoxia in TME, tumor‐activated fibroblasts, and platelets collectively drive NETosis [ 18 ]. Moreover, NETs interact with stromal and immune components in the TME, including endothelial cells, fibroblasts, erythrocytes, T/B/NK cells, DCs, and macrophages, to modulate tumor progression [ 136 ]. Given the structural and functional complexity of NETs, their precise mechanisms in tumorigenesis and their therapeutic potential in cancer treatment require further elucidation.

Emerging evidence implicates NETs in the pathogenesis of lymphoma, although this field remains in its early stages. Lymphoid tissues possess unique immunological architectures in which innate and adaptive immune cells are densely packed. Unlike solid tumors, lymphoma cells evolve within preexisting immune‐rich environments, including developing lymphocytes, tissue‐resident myeloid cells, and chronic inflammatory infiltrates (e.g., neutrophils, macrophages, DCs). The lymphoma‐TME interaction drives continuous remodeling of lymphoid architecture and function through quantitative, spatial, and phenotypic alterations of all the immune cell populations. Notably, TRNs in lymphoid tissues exhibit distinct phenotypes and functions compared with their peripheral counterparts, suggesting potentially more complex and unique roles for NETs in lymphoma pathogenesis.

Compelling preclinical and clinical data demonstrate neutrophil infiltration in lymphoma microenvironments with NET‐mediated tumor promotion [ 85 , 89 ]. Notably, NETs were observed in a subset of TANs and exhibit focal distribution patterns in NS cHL nodes. In contrast, no significant NETs accumulation is detected in marginal zone (MC cHL), lymphocyte‐rich (LR cHL), lymphocyte‐depleted (LD cHL), and nodular lymphocyte‐predominant HL (NLPHL) when compared with reactive lymphadenopathy [ 85 ]. Mechanistic studies reveal that NETs may drive DLBCL progression via TLR9 activation. Elevated NET levels in plasma and tumor specimens predict adverse clinical outcomes in patients with DLBCL [ 87 ]. Concurrently, emerging studies are interrogating the associations between NET components and lymphoma biology. For example, NE, MPO, MMP8, and MMP9, key constituents of NETs, have been implicated in lymphoma progression [ 91 ]. Particularly, MMP9 overexpression in NHL patients correlates with poor prognosis and advanced disease [ 151 , 152 , 153 ]. Recently, high‐throughput gene expression microarray analysis identified an 8‐gene NET signature ( PARVB, LYZ, PPARGC1A, HIF1A, SPP1, CDH1, S100A9, CXCL2 ) as a novel prognostic biomarker in DLBCL, where high expression of this signature correlates with inferior survival outcomes [ 154 ].

Furthermore, chemotherapy‐induced NETs release may exacerbate hypercoagulability in malignant lymphoma through leukocyte activation cascades [ 155 ]. Hypercoagulability promotes tumor‐associated thrombosis, thereby accelerating cancer progression [ 140 ]. However, the aforementioned research on NETs detection primarily relies on CitH3 as a biomarker, which lacks ideal specificity because it is expressed in cancer cells and is absent in certain NET subtypes owing to divergent NETosis mechanisms [ 156 ]. There are currently no standardized protocols for NETs quantification despite advancing methodologies [ 140 , 156 , 157 , 158 ]. Moreover, only a subset of neutrophils undergo NETosis. The immunological specificity and complexity of lymphoma TME necessitate further exploration of the TAN subpopulations that drive NETs formation, as well as the development of standardized detection methods for lymphoma‐associated NETs.

Compared with solid tumors, research on NETs in hematological malignancies is still in its early stages. The unique phenotypic plasticity of TRNs within lymphoid tissues and their potential role in shaping the TME warrant urgent mechanistic investigation. Elucidating NET‐mediated immunomodulatory pathways could reveal novel therapeutic vulnerabilities in lymphoma pathogenesis.

Targeting TANs in Lymphoma

Given the tumor‐promoting properties of TANs, strategies targeting these cells have emerged as a research priority [ 21 , 24 , 159 , 160 ]. Current approaches encompass 5 major categories: (1) Inhibition of neutrophil recruitment via CXCR receptor blockage and IL‐8 signaling disruption; (2) Prevention of pro‐tumor polarization through TGF‐β signaling inhibition, metabolic reprogramming interventions, and immune checkpoint pathway modulation; (3) Suppression of neutrophil expansion by G‐CSF neutralization; (4) Targeting NETs; (5) Neutralization of neutrophil‐derived mediators, such as NE, MMPs, MPO, and ROS. Comprehensive strategies have recently have reviewed in depth [ 24 , 66 , 161 , 162 , 163 ].

The established role of NETs as pathogenic drivers in various diseases positions them as promising therapeutic targets, particularly for advanced and metastatic cancers. Current NET‐targeting strategies primarily fall into two categories: (1) Inhibition of NETs formation [ 156 ] via targeting upstream inflammatory mediators (CXCR1/2, IL‐8, IL‐17) [ 164 ], PAD4 inhibitors [ 165 ], NE inhibitors [ 166 ], GSDMD inhibitors [ 167 ], anticitrullinated protein antibodies [ 168 ], traditional Chinese medicine formulations [ 169 ]; (2) Disruption of existing NETs via DNA inhibitors [ 170 ] and heparin [ 171 ] to degradation or destabilization of NETs. Given NETs' physiological role in infection control, therapeutic NETs inhibition in chemotherapy‐induced neutropenic patients may potentially compromise antimicrobial defenses, necessitating careful risk–benefit evaluation in immunocompromised populations.

Despite ongoing clinical trials exploring TAN‐targeting strategies in solid tumors, significant challenges persist. The TME dynamically regulates neutrophil plasticity, driving polarization from antitumor N1 phenotypes to pro‐tumor N2 phenotypes [ 65 , 69 , 163 ]. Notably, neutrophils spanning a continuum from antitumor to pro‐tumor functional states may coexist within distinct TME niches. While neutrophil‐mediated tumor suppression primarily involves cytotoxic molecule secretion (hydrogen peroxide, nitric oxide, MPO, NE, MMPs, ROS) and immune modulation through NETs formation, antibody‐dependent cellular cytotoxicity (ADCC), and T cell/macrophage activation [ 161 , 163 , 172 , 173 , 174 , 175 , 176 , 177 , 178 ], these mechanisms are frequently coopted by tumors to support progression [ 24 , 26 , 64 , 66 , 163 , 179 ]. For instance, IL‐8 overexpression in malignancies promotes epithelial‐mesenchymal transition, angiogenesis, and myeloid‐derived suppressor cell recruitment, yet IL‐8‐activated neutrophils may differentiate into CD74 high SiglecF low subsets associated with enhanced antitumor immunity and improved responses to immune checkpoint blockade (ICB)‐chemotherapy combinations in lung cancer [ 180 ]. This functional duality poses significant therapeutic challenges. While neutrophil depletion suppresses carcinogenesis in experimental models [ 90 ], it concurrently elevates infection risks and may trigger extramedullary granulopoiesis [ 181 ]; Conversely, G‐CSF administration in lymphoma therapy not only counteracts chemotherapy‐induced leukopenia but also enhances CD20 antibody‐mediated ADCC [ 182 ]. G‐CSF may increase the number of neutrophils and induced the expression of FcγRI (CD64) on the circulating neutrophils, thereby enhancing ADCC activity and potentiating antitumor responses in patients with FL [ 183 ]. Notably, neutrophils mediate mostly trogocytosis rather than phagocytosis of anti‐CD20‐opsonized CLL B cells [ 184 ].

Although G‐CSF can enhance the rituximab‐mediated ADCC, current treatment guidelines consistently emphasize its primary role as supportive care for chemoimmunotherapy‐induced neutropenia [ 185 , 186 ]. The chief goal of its administration is to maintain chemotherapy dose intensity, and its prophylactic use hinges on a careful assessment of neutropenia risk. Even therapeutic application must adhere to strict indications, as inappropriate use may cause harm [ 185 , 186 ]. Beyond stimulating hematopoiesis, G‐CSF can also promote extramedullary hematopoiesis, leading to the release of immature neutrophils. It can also activate and reprogram neutrophils, contributing to NET release [ 187 ]. These processes may, in turn, drive pro‐tumorigenic neutrophilia and immunosuppression, potentially compromising the antitumor efficacy of chemotherapy [ 188 ], thereby adding complexity and potential risk to treatment management. Furthermore, the administration of exogenous G‐CSF may interfere with the prognostic value of established biomarkers such as the NLR and circulating NET markers. Although antagonists of G‐CSF or G‐CSF receptor have demonstrated antitumor effects in some solid tumor animal models [ 189 , 190 ], whether they confer clinical benefit in lymphoma patients requires further investigation.

Translating neutrophil‐targeting strategies into lymphoma treatment faces unique clinical constraints. Baseline neutropenia is common, particularly in patients with BM involvement or advanced‐stage disease, and therapy‐induced neutropenia frequently occurs after chemoimmunotherapy, radiation, or CAR‐T cell therapy. Consequently, prophylactic or therapeutic G‐CSF (and, to a lesser extent, GM‐CSF) is routinely used in lymphoma care to prevent febrile neutropenia and avoid treatment delays [ 185 , 186 ]. Any intervention that depletes neutrophils or broadly inhibits G‐CSF signaling therefore risks exacerbating neutropenia, increasing infectious complications, and limiting the delivery of dose‐intensive therapy. Notably, a study using a mouse lymphoma model suggested that co‐targeting gamma‐glutamyltransferase alongside G‐CSF could mitigate its pro‐tumorigenic and immunosuppressive effects without compromising bone marrow hematopoiesis [ 191 ]. Thus, balancing the risks of neutropenia against those of therapy‐induced pro‐tumorigenic neutrophilia remains a critical and ongoing challenge in the therapeutic landscape.

The development of TANs‐targeted therapies must achieve precise discrimination between pro‐tumor N2 phenotypes and antitumor N1 populations, representing a fundamental challenge in translational immuno‐oncology. Emerging therapeutic strategies are increasingly focused on exploiting the antitumor potential of neutrophils through two key approaches: (1) modulation of neutrophil effector mechanisms including ADCC potentiation, TGF‐β/Smad signaling inhibition, IFN pathway activation, and SIRT1‐mediated antigen presentation enhancement [ 147 , 160 , 180 , 192 ]; (2) development of engineered neutrophil platforms such as chimeric antigen receptor‐engineered neutrophils (CAR‐neutrophils) and neutrophil‐based drug delivery systems [ 163 ]. Recent work by Chang and colleagues revealed that neutrophil‐specific CAR engineering confers potent antitumor activity, as evidenced by improved survival outcomes in glioblastoma models [ 193 , 194 ]. These advances highlight the critical need for precise therapeutic strategies capable of selectively eliminating pro‐tumor TANs while preserving beneficial antitumor and immunomodulatory neutrophil functions. Fortunately, advances in single‐cell sequencing and omics technologies have enabled a more comprehensive understanding of the spatiotemporal heterogeneity of TANs, leading to their classification into eight subsets in humans: pro‐inflammatory, chemokine‐secreting, proangiogenic, transitional, IFN‐stimulated, antigen‐presenting, immunosuppressive (PMN‐MDSCs), and classical subtypes (for a comprehensive review, see Zhou et al. [ 195 ]). A recent study in BM of multiple myeloma identified three distinct CXCR2 + mature neutrophil subsets, TREM1 + CD10 + , RETN + LCN2 + , and TNFAIP3 + CXCL8 + , with immunosuppressive TREM1 + CD10 + neutrophils predominating in the TME [ 196 ]. These findings will facilitate the exploration of neutrophil subsets associated with lymphoma. Therefore, key challenges moving forward include: (1) deciphering context‐dependent neutrophils phenotypic heterogeneity; (2) designing TME‐specific delivery platforms; and (3) establishing predictive biomarkers for treatment response stratification.

Targeting TANs and NETs holds considerable therapeutic promise, especially in relapsed or refractory lymphomas. However, current knowledge of TAN subsets, their spatial distribution, and functional roles in lymphoma remains limited. Further research is critically needed to define the phenotypes and tissue localization of pro‐tumorigenic TANs in lymphomas. The clinical utility of such strategies would be substantially enhanced if cytokine‐based therapies or small‐molecule inhibitors could effectively reprogram pro‐tumor TANs toward antitumor N1‐polarized subsets.

Conclusions and Perspectives

Current limitations stem from our fragmented understanding of neutrophil biology and pathophysiology in lymphoid tissues and lymphoma. Due to the limited studies available, our current work provides only a brief summary of the relationship between PMN‐MDSCs and neutrophils or their respective roles in lymphoma immunity. The intrinsic biological properties of neutrophils, including their short half‐life and remarkable phenotypic plasticity under chronic stress, generate profound microenvironment‐driven functional diversity. Emerging evidence highlights their dynamic trafficking through lymphoid organs, where they undergo context‐specific functional reprogramming that could either restrain or promote lymphoma progression. The complex interplay between neutrophil dynamics and lymphoma pathogenesis warrants deeper investigation to develop effective therapeutic interventions that maximize clinical benefit while minimizing systemic toxicity.

To advance the field, the following key questions must be addressed:

Systematic mapping of neutrophil phenotypic and functional heterogeneity across lymphoma subtypes and tumor microenvironments.

Mechanistic dissection of TRN subsets throughout lymphomagenesis and disease evolution.

Microenvironmental determinants controlling the antitumor (N1) to pro‐tumor (N2) polarization switch in lymphoma niches.

Precision reprogramming strategies to restore antitumor neutrophil effector functions.

Mechanistic insights into lymphoma‐induced dysregulation of BM myelopoiesis and progenitor differentiation pathways.

Molecular definition of neutrophil‐mediated mechanisms facilitating BM infiltration and metastatic niche establishment.

Author Contributions

Ling Gu: conceptualization, methodology, funding acquisition, writing – original draft, writing – review and editing, project administration, visualization.

Funding

This work was supported by the National Nature Science Foundation of China (Grant No. 82241005) and Sichuan Science and Technology Program of China (Grant No. 2025ZNSFSC0540).

Ethics Statement

The author has nothing to report.

Consent

The author has nothing to report.

Conflicts of Interest

The author declares no conflicts of interest.

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

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Associated Data

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.