From bone marrow to the tumor microenvironment: how neutrophil maturation shapes cancer immunity

From bone marrow to the tumor microenvironment: how neutrophil maturation shapes cancer immunity

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Tao Shi¹^,², Yiran Cai¹^,², Hanbing Wang¹^,², Jia Wei¹^,²

Cancer Biology & Medicine | 2025, 22(12) : 1431 - 1438

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Cancer Biology & Medicine | 2025, 22(12): 1431-1438

• PERSPECTIVE •

From bone marrow to the tumor microenvironment: how neutrophil maturation shapes cancer immunity

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Tao Shi¹^,², Yiran Cai¹^,², Hanbing Wang¹^,², Jia Wei¹^,²

Affiliations

¹Department of Oncology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China

²State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China

Published: 2025-12-15 doi: 10.20892/j.issn.2095-3941.2025.0547

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Cite this Article

Tao Shi, Yiran Cai, Hanbing Wang, Jia Wei. From bone marrow to the tumor microenvironment: how neutrophil maturation shapes cancer immunity[J]. Cancer Biology & Medicine, 2025 , 22 (12) : 1431 -1438 . DOI: 10.20892/j.issn.2095-3941.2025.0547

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Tumor-associated neutrophils (TANs) exhibit highly functional heterogeneity across cancers. Although TANs promote inflammatory responses and contribute to tumor clearance, they frequently undergo context-dependent reprogramming within the tumor microenvironment (TME) into highly immunosuppressive phenotypes that facilitate cancer dissemination and immunotherapy resistance^1,2. We contend that an underappreciated, upstream determinant of this divergence is the maturation stage of TANs^3,4. The developmental stage of TANs determines the migration patterns and constrains the functional capacity, and the developmental stage also constrains the extent of TME-driven re-education, together shaping pro- or anti-tumor outcomes^3–5. In this Perspective, we place maturation at the core of TAN biology and discuss current definitions for TAN developmental stages and the measurable markers that researchers and clinicians can use (Figure 1). In addition, spatial and temporal transitions in TAN maturation stages and the factors that govern these transitions are elucidated. We explain how maturation status shapes TAN function and articulate the key differences between mouse and human TAN maturation systems to highlight the value of human immune system (HIS) mouse models. Based on this framework, functional biomarkers and signatures of TAN maturation are introduced and we show how to embed them into patient stratification and longitudinal monitoring. Finally, we outline immunotherapy strategies targeting TAN maturation, selecting interventions guided by maturation markers to reinforce treatment benefits for cancer patients.

Definitions and lineage: the lack of a unified standard for TAN maturation

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Based on the current literature, there is no consensus on how to demarcate “immature,” “intermediate,” and “mature” TANs. Terminology often overlaps, obscuring distinctions in developmental states^3–7. Studies interchangeably invoke TANs, polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs), and low-density neutrophils (LDNs). Morphologic labels, such as band versus segmented nuclei, are applied with non-aligned gates and composite immunophenotypes differ across platforms and cohorts⁸. Phase assignment typically integrates nuclear morphology with markers in humans, including CD10, CD16, CD62L, C-X-C chemokine receptor 2 (CXCR2), and lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1) but the precise thresholds of expression and gating hierarchies vary between laboratories, which hinders a cross-study comparison⁴. CD101 is commonly used to distinguish immature from mature granulocytes in mice, often combined with Ly6G, CXCR2, and C-X-C chemokine receptor 4 (CXCR4)³, yet case-to-case mapping between CD101-defined murine states and human stages remains unsatisfactory. Methodologic variability adds further ambiguity. Specifically, density-gradient separation can artifactually partition LDN/high-density neutrophil (HDN) pools. Delayed processing or cryopreservation alters CD62L/CD10 and degranulation status and sorting itself can activate neutrophils, creating spurious “new” subpopulations^1,7,9. Single-cell RNA-seq (scRNA-seq) helps reveal a continuum of maturation status, however the sparse capture of surface proteins complicates the back-annotation of developmental phases and integration across datasets. To enable reproducible interpretation, we adopt practical working definitions. Neutrophils progress from promyelocytes (PMs), myelocytes (MCs), metamyelocytes (MMs), band/seg-competent (Band/SC), and finally to segmented neutrophils (Seg) in humans; MC/MM neutrophils are considered immature⁴. CD101⁻ denotes immature and CD101⁺ denotes mature TANs in mice, while the functional pattern to human stages could be more complex³. Finally, neutrophil development in the TME is unlikely to follow a strictly linear developmental trajectory⁵. Emergency granulopoiesis can accelerate output and skew lineage specification.

Alternative trajectories can emerge under the influence of systemic cytokines and within tumors tissue-specific cues may impose “stage stalling” or conversion. These realities underscore the importance of maturation-aware measurement and interpretation and emphasize the link between TAN maturation and function.

In addition, the terminology describing neutrophil populations in tumors has often been used inconsistently across studies. Herein we adopt the following distinctions: TANs refer broadly to all neutrophils found within or adjacent to tumor tissues, regardless of phenotype or density; PMN-MDSCs represent a functionally defined subset of neutrophil-lineage cells with immunosuppressive activity and are typically identified in the circulation or tumor sites by T-cell inhibitory properties; and LDNs are defined operationally based on the co-sedimentation with mononuclear cells after density-gradient centrifugation and may include both immature and activated neutrophils, encompassing but not limited to PMN-MDSCs. Recognizing these distinctions avoids conflating developmental, functional, and methodologic definitions when interpreting neutrophil heterogeneity in cancer.

Spatiotemporal evolution and regulatory factors of TAN maturation

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Neutrophil maturation in cancer proceeds along a recognizable spatiotemporal trajectory from bone marrow (BM) to circulation, to primary and pre-metastatic sites, and ultimately to established metastases, yet the composition of states at each waypoint is plastic and stage-dependent. First, early during tumorigenesis systemic cytokines, such as granulocyte-/granulocyte-macrophage colony-stimulating factor (G-/GM-CSF), interleukin-6 (IL-6), and interleukin-1β (IL-1β), accelerate emergency granulopoiesis and shorten neutrophil residence in the BM, resulting in premature mobilization of immature and intermediate neutrophils^10,11. These populations accumulate within the low-density blood fraction (often labeled LDN/PMN-MDSC) and preferentially enter tumor-draining vasculature and tissues, where the populations are predisposed to suppress T-cell function, support angiogenesis, and remodel the extracellular matrix¹².

Second, recruitment and positioning of TANs are controlled by chemokine and retention axes that intersect with the developmental stage^6,13. CXCR2–ligand programs (CXCL1/2/5/8) promote egress of neutrophils from the BM and recruitment into inflamed tumor sites, whereas the CXCR4–CXCL12 axis favors retention and “return-to-marrow” signaling. Less mature cells frequently exhibit heightened responsiveness to CXCR2 cues and distinct adhesion profiles, including altered CD62L and β2-integrin expression, which bias trafficking toward tumors. With increasing tumor burden, the proportion of immature TANs is typically elevated in blood and tissue and neutrophil influx into pre-metastatic niches, such as lung, liver, and bone, preparing those sites for cancer cell seeding.

Third, after recruitment into the TME, tissue-derived factors reshape the composition and trajectories of neutrophil maturation states^5,14,15. Hypoxia and acidosis, lactate transport through monocarboxylate transporter 1/monocarboxylate transporter 4 (MCT1/MCT4), transforming growth factor-β (TGF-β), interleukin-10 (IL-10), vascular endothelial growth factor (VEGF), eicosanoid, complement signaling, neutrophil extracellular traps (NETs), endoplasmic reticulum-stress/unfolded protein response (ER-stress/UPR) and lipid-peroxidation pathways collectively influence stage allocation, residence time, and transition probabilities along the myelopoietic axis of TANs. These factors can stabilize TANs in intermediate stages across primary and metastatic sites, prolong persistence, delay terminal segmentation, or even induce stage reversal (“rollback”) toward immature-like phenotypes. Our recent work provided an example of TAN modulation in bone metastases. The Dickkopf-related protein 1 (DKK1)-cytoskeleton-associated protein 4 (CKAP4) pathway is linked to reversion of maturity markers and extended longevity of immature-like states of TANs, whereas DKK1 blockade restores maturity-associated features (e.g., increased CD101⁺ fractions in metastases)³. Other bone-TME derived factors, such as osteopontin or TGF-β, also have the potential to reprogram TAN maturation stages^16,17. In other contexts, type-I interferon or Toll-like receptor (TLR) ligation appears to stabilize later maturation signatures and limit the expansion of immature-like pools, highlighting that maturation can be dynamically regulated by local and systemic signals upon tumor infiltration^18,19. However, we refer to “immature-like” neutrophils as populations that exhibit some transcriptional features associated with immaturity, such as reduced CD101 expression or partial segmentation, but are more closely linked to immunosuppressive and tumor-promoting functions rather than strict developmental immaturity. This distinction emphasizes that “immature-like” describes a functional reprogramming state within the tumor microenvironment rather than a fixed stage along the canonical maturation trajectory. Direct evidence is still lacking to determine whether TME-induced immature-like neutrophils are truly equivalent to immature neutrophils resident in the BM or whether TME-induced immature-like neutrophils undergo a full transition into classically defined immature states in developmental terms.

Some studies challenge the notion that TAN maturation follows a simple linear developmental trajectory. Tumors can recruit mature neutrophils under some conditions (e.g., infection-like inflammation or antibody exposure), so the incoming pool is not uniformly immature⁵. The LDN label is not equivalent to developmental immaturity because activation, degranulation, or handling artifacts can alter buoyant density independent of lineage stage. Aging phenotypes, such as CXCR4^hi CD62L^lo, may mimic some features of immature neutrophils yet are developmentally distinct¹³. Single-cell atlases consistently reveal continuous trajectories rather than discrete stages and maturation can be reversible under organ-specific cues, as described in bone metastases²⁰. These considerations support maturation-resolved study designs, such as standardized reporting that separates developmental stage from activation or aging status and longitudinal sampling across blood and tissue, including metastatic niches, to determine whether tumor-derived factors truly redirect TAN stage composition.

Coupling between TAN maturation and function

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Most studies converge on a broad association between developmental stage and behavior^3,4,13. Immature and intermediate neutrophils (operationally defined as human MC/MM or murine CD101⁻) are frequently linked to pro-tumor functions, including T-cell suppression, angiogenesis, extracellular-matrix remodeling, and metastatic facilitation. In contrast, mature neutrophils (human segmented cells/murine CD101⁺) are more commonly associated with anti-tumor potential through a respiratory burst, degranulation, NET formation, chemokine orchestration, antigen presentation capacity, and antibody/complement-dependent mechanisms. However, there are also some studies claiming the opposite point^5,6,10. For example, mature TANs can acquire suppressive features in multiple myeloma¹⁰, while immature neutrophils recruited into the brain TME can polarize into a “hybrid” dendritic-like phenotype to help tumor regression⁶. This functional shift of mature TANs in multiple myeloma is largely driven by pro-inflammatory stromal factors within the TME, whereas tumor-derived factors in brain tumors promote the differentiation of immature neutrophils into hybrid dendritic-like cells. These examples illustrate that heterogeneity of the TME can lead neutrophils at similar maturation stages to adopt distinct functional programs.

A second line of evidence suggests that neutrophil function can be programmed at different points along the differentiation path⁴. Human data indicate that bone-marrow-derived intermediate stages (MC/MM) can harbor intrinsic immunosuppressive programs and extended survival, implying that at least part of bone marrow neutrophils acquires pro-tumor phenotype before being recruited into the TME. Other studies, however, emphasized post-recruitment education. When neutrophils arrive at the TME, local metabolic and cytokine cues can direct the neutrophils toward either pro- or anti-tumor phenotypes irrespective of the initial stage. For example, Ng et al. reported that immature and mature neutrophils can be recruited into the pancreatic TME and are then educated by tumor cells to have pro-angiogenic function and promote tumor progression⁵. In addition, some situations happen in clinical settings, such as infection-like inflammation or opsonizing antibody therapy, can recruit functionally competent mature neutrophils to tumors^18,19,21. Taken all the current studies into consideration, we think that both sides contribute to the TAN state. Maturation establishes the baseline constraints (migration routes, available effector modules, and susceptibility to reprogramming), while TME signals modulate and determine the functional heterogeneity of TANs.

The microenvironment difference introduces a third dimension because TANs in comparable or similar maturation stages can exhibit different functional profiles at different sites. Organ-specific TMEs differ in hypoxia, acidosis, stromal and vascular architecture, microbial or damage-associated signals, and dominant cytokine pathways, all resulting in the heterogeneity of TAN development and function¹⁵. Our own study involving bone TME provides an example. Local signaling through the DKK1–CKAP4–Chitinase-3-like protein 3 (CHI3L3) axis can promote immature-like, long-lived programs even among neutrophils that initially entered as mature, whereas disruption of this axis restores maturity-associated features and improves overall anti-tumor immunity³. By contrast, the lung and liver niches may differ in how chemokine, lipid, and complement signals influence neutrophil behavior, thus producing alternative endpoints from comparable developmental inputs of TANs²². Collectively, these observations suggested that maturation may define the permissible range of plasticity, while site-specific context selects the functional endpoint of TANs, a working hypothesis that highlights the need for biomarkers and interventions tailored to both stage composition and anatomic niche of tumors. This working hypothesis requires further experimental validation.

In addition, we acknowledge that the functional heterogeneity of TANs can also result from activation-induced or metabolically driven reprogramming, rather than from developmental differences alone. To clarify these distinctions, we propose three mechanistically separable but overlapping processes that contribute to TAN functional heterogeneity: (i) development difference, which establishes the baseline effector potential along the maturation continuum; (ii) activation-state shifts, in which cytokines, such as TGF-β or type I interferons, reorient mature TANs toward suppressive or inflammatory profiles; and (iii) metabolic adaptation, in which environmental cues, like lactate accumulation or hypoxia, modify signaling and effector outputs. Recognizing that these processes as distinct yet interconnected helps prevent the simple conflation between maturation-dependent diversity and functional heterogeneity of TANs.

Species differences and the necessity of human-centric models for TAN research

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Direct extrapolation from mice-to-humans is fraught for TAN maturation. In human tumors intermediate stages, which are classically defined as myelocytes and metamyelocytes (MC/MM), are often disproportionately abundant, display prolonged survival, and harbor potent immunosuppressive programs⁴. However, these features are not consistently recapitulated by murine heuristics that rely on CD101 as a binary maturity gate. Marker relationships are also non-isomorphic. Human phase assignments integrate nuclear morphology with markers, such as CD10/CD16/CXCR2/LOX-1, and when informative, CD63/Galectin-3 to enrich MC/MM, whereas murine studies predominantly use Ly6G/CXCR2 combined with CD101 to distinguish immature from mature⁴. As a result, CD101⁻ or CD101⁺ TANs in mice do not directly correspond to CD10⁻ or CD10⁺ TANs in humans and functional equivalence should not be assumed. Moreover, this gap is further compounded by technical limitations. Many surface determinants are sparsely captured by scRNA-seq, which complicates phase back-annotation and cross-species alignment.

Two methodologic principles help bridge this gap. First, a bulk-first strategy prospectively sorting human stages, generating bulk transcriptomes to derive stage-associated gene sets, and subsequently projecting those onto single-cell datasets yields more stable human phase calls than de novo scRNA clustering. Second, human-centric experimental systems are essential for mechanistic and translational research. Human immune system (HIS) mice with neutrophil reconstitution (e.g., NCG-HIS Gfil^−/− mice used in our study) can recapitulate the survival and immunosuppressive features of human MC&MM neutrophils⁴. Tumor organoids or precision-cut slices co-cultured with autologous blood preserve patient-specific gradients and cell-to-cell crosstalk and micro-physiologic “tumor-on-chip” platforms allow controlled hypoxia/acidosis and flow¹⁵. Furthermore, these models should also mimic the dynamics of human TAN development, which can finally increase clinical relevance, enable maturation-aware patient stratification, and provide standardized platforms to develop therapeutic interventions targeting TANs for cancer treatment.

Moreover, while scRNA-seq has significantly advanced our understanding of TAN heterogeneity, scRNA-seq faces inherent limitations in accurately defining maturation stages due to transient transcriptional signatures and dropout effects. Emerging multi-omics approaches, such as CITE-seq (simultaneous measurement of transcripts and surface proteins) and scATAC-seq (chromatin accessibility profiling) offer complementary layers of information. Integrating these modalities, together with spatial transcriptomics, may enable the development of cross-platform maturation indices, allowing more reproducible and mechanistically informative annotation of neutrophil developmental states in future studies.

Clinical stratification and biomarkers based on TAN maturation status

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A TAN maturation-informed clinical workflow should begin with peripheral blood triage, proceed with tissue confirmation, and incorporate longitudinal tracking^1,4,7. We propose a maturation-aware neutrophil-to-lymphocyte ratio (NLR) for blood-based assessment that augments the NLR with a minimal 6–8-color flow panel [CD66b, CD15, CD16, CD10, LOX-1, and CXCR2 (± viability; optional CD63/Galectin-3 to enrich human MC/MM)]. The primary readout is the proportion of CD10⁻/LOX-1⁺ and/or CD63/Gal-3-high cells within CD66b⁺ neutrophils, reported alongside NLR and CXCR2 mean fluorescence intensity (MFI) as a proxy for trafficking competence. Thresholds require disease- and cohort-specific calibration but reporting these three quantities (NLR, immature fraction, and CXCR2) facilitates standardized communication across clinical trials. For tissue-based assessment, A pragmatic approach is multiplex immunohistochemistry (IHC)/immunofluorescence (IF) to quantify neutrophil burden and maturation balance for tissue-based assessment [e.g., CD66b, myeloperoxidase (MPO), CD10, CXCR2, ± programmed death-ligand 1 (PD-L1)]. DKK1 should be included (serum/tumor) as a directional cue and its downstream activity in bone metastasis, (e.g., the huChil3⁺ neu score) should be assessed³. Where feasible, bulk-derived maturation signatures should be projected onto spatial or single-cell transcriptomes to validate phase composition in situ. Longitudinal sampling at baseline, in the early on-treatment phase (e.g., weeks 2–4), and at post-treatment/progression stage should all be considered to capture the maturation drift. Moreover, rigorous quality control strategies are essential, including avoidance of density-gradient artifacts for decision-making, minimizing processing delays, and pre-specifying gating hierarchies. By embedding this compact workflow, TAN maturation evaluation can be integrated into early-phase studies to enable patient stratification for optimal immunotherapy response. At present, however, these proposals remain theoretical frameworks and direct clinical evidence demonstrating prognostic or therapeutic guidance based on TAN maturation is still lacking.

Treatment strategies targeting TAN maturation

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Therapies that target TAN maturation operate on three fronts: (1) induce maturation or redirect lineage fate in immature/intermediate neutrophils⁴; (2) block the recruitment of immature cells into tumors^6,13; and (3) shield mature programs from the TME-driven rollback into immature-like suppressive states³. First, inducing maturation or redirecting lineage fate in immature/intermediate neutrophils offers a direct strategy to curtail suppressive pools at their source. Rather than broadly suppressing granulopoiesis, interventions should specifically promote pro- or trans-differentiation of human MC/MM-like stages. Examples include Fms-like tyrosine kinase 3 ligand (Flt3L)-driven re-direction of MC/MM toward monocyte lineages (“de-suppress and replace”) and targeted modulation of lineage-skewing checkpoints identified during development, such as ER-stress/UPR nodes or epigenetic regulators, to slow premature egress and drive cells toward terminal segmentation. These approaches should be paired with maturation-resolved readouts (e.g., decreasing CD10⁻/LOX-1⁺ or CD63/Gal-3⁺ fractions in blood when feasible and increasing maturity markers in tissue) to confirm that the compartment is genuinely shifting toward non-suppressive states.

Second, blocking the recruitment of immature neutrophils into tumors facilitates source control by limiting continual replenishment. Targeting the CXCR4 axis functions as a pharmacologic “gate”, reducing egress and chemotaxis of CXCR4⁺ neutrophils, which is usually composed of suppressive PMN-MDSC/immature-like cells as well as some mature effectors in the context of cancer. Stage bias can be further reinforced by combing CXCR4 blockade with upstream interventions that shrink immature pools (e.g., modulating excessive G/GM-CSF, IL-6, or IL-1β without compromising safety). In addition to CXCR4, additional neutrophil-included interventions are under evaluation. CXCR1/2 antagonism (e.g., small-molecule inhibitors or IL-8 neutralization) aims to curtail chemotaxis and intratumoral accumulation of tumor-promoting neutrophils, thereby improving T-cell access and function. Modulating the colony-stimulating factor 1/colony-stimulating factor 1 receptor (CSF1/CSF1R) axis, which is classically used to reprogram macrophage-rich TMEs, can also reshape cytokine networks that favor immature-like TAN programs. Finally, NETs-targeting strategies [e.g., DNase-based degradation of extracellular DNA scaffolds, peptidyl arginine deiminase 4 (PAD4) inhibition to prevent chromatin decondensation and neutrophil elastase inhibition to limit protease-mediated conditioning] are being explored to mitigate pro-metastatic niches and restore antitumor immunity. Incorporating these modalities with maturation-aware pharmacodynamics will be helpful to develop more effective TAN-targeting strategies.

Third, protecting mature TANs from TME re-education can address the “rollback” in which mature neutrophils revert into immature-like, long-lived, suppressive states. This can be approached through organ-specific circuits. Neutralizing DKK1 or intercepting downstream CKAP4-PI3K/AKT-STAT6 signaling in bone metastases can prevent maturation reversal and reduces persistence of immature-like phenotypes, while restoring maturity-associated features, such as higher CD101⁺ proportions in mice. More broadly, suppressive imprinting can be prevented by intervening in the signals that mediate maturity reversion, including buffering lactate/acidosis (MCT1/MCT4 inhibition), restraining TGF-β/IL-10 and prostaglandin E₂/cyclooxygenase-2 (PGE₂/COX-2) programs, and curbing complement- or NET-driven conditioning. These “shielding” interventions are site-aware and selected according to the dominant re-educators specific to each tumor niche, which also needs longitudinal assays to ensure maturity maintenance rather than non-specific depletion. Taken together, promoting maturation, blocking influx, and shielding from functional rollback provide a cohesive, maturation-centered strategy that can be integrated with standard anticancer immunotherapies while maintaining host defense. However, most evidence remains preclinical, which requires prospective validation.

Recent clinical studies have started to explore neutrophil-targeting interventions in cancer therapy. CXCR1/2 antagonists, such as SX-682 (NCT03161431 and NCT04574583) and ladarixin (NCT05815173) are being tested either alone or combined with immune checkpoint blockade in melanoma, pancreatic cancer, and head and neck cancer. These trials aim to reduce tumor-promoting neutrophil infiltration and enhance antitumor T-cell activity. In addition, blockade of neutrophil-associated cytokine pathways, including IL-8 [e.g., the anti-IL-8 antibody BMS-986253 (NCT04050462)] and TGF-β signaling [e.g., vactosertib (NCT03732274)] is under clinical investigation for the potential to mitigate neutrophil recruitment and suppress polarization within the TME. Although most of these trials are still in early clinical phases, they provide translational proof-of-concept that the pharmacological modulation of neutrophil trafficking or maturation can synergize with immunotherapy and improve clinical outcomes.

Conclusions and perspectives

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A maturation-centered framework clarifies an important axis of TAN heterogeneity but substantial challenges remain. First, there is still no unified standard to define TAN maturation stages across species and platforms and lineage architecture appears intrinsically complex. Second, maturation provides the initial constraints on neutrophil behavior, whereas the TME sets the endpoint phenotype and organ-specific factors can even redirect apparent stage. Third, whether maturation itself determines TAN function or merely constrains it continues to be debated and is context-dependent. Fourth, using maturation-related blood and tissue biomarkers with longitudinal monitoring in clinical practice could improve patient stratification and better guide immunotherapy decisions. Looking ahead, cross-species maturation staging maps, multicenter standard operating procedures (SOPs) for a robust “maturation index”, human-centered stage-resolved intervention studies, and spatial/longitudinal multi-omics analysis are needed to define organ-specific directional programs and validate the causality. These efforts can finally enable true precision and TAN maturation-guided immunotherapy for cancer patients.

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Appendix

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Year 2025 volume 22 Issue 12

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doi: 10.20892/j.issn.2095-3941.2025.0547

Receive Date：2025-09-14
Online Date：2026-04-03
Published：2025-12-15

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History

Received：2025-09-14
Accepted：2025-11-17

Affiliations

¹Department of Oncology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China

²State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China

Corresponding:

Correspondence to: Jia Wei, E-mail: jiawei99@nju.edu.cn

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表12种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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Figure 1 TAN maturation couples developmental stage to functional programs and guides treatment design. (A) Developmental staging of mouse or human TANs (precursor, immature, and mature stages). (B) Coupling between maturation and function. Immature/intermediate neutrophils preferentially display immunosuppressive and pro-tumor functions: immune suppression (ROS, NETs, and PGE₂); TME remodeling (neutrophil elastase, IL-1β, and S100A8/9); and direct tumor-promoting factors (EGF, HGF, and integrins). In contrast, mature neutrophils can support anti-tumor activity, including antigen-presenting-like features (CD86 and MHC-I/II), direct cytotoxicity (degranulation and NO), and immune activation (ISG, IL-12, and ADCC). (C) Modulation factors that shift TAN stage-function relationships. Pro-suppressive fields (hypoxia, lactate, DKK1, TGF-β/IL-10, PGE₂, C5a, and ER-stress) bias toward immature-like programs, whereas pro-activating inputs (type-I interferon and TLR ligation) favor mature effector states. Organ context imposes directionality: brain metastasis–associated TNF-α and ceruloplasmin; and bone metastasis-associated DKK1 can drive or stabilize immature-like phenotypes. (D) Treatment strategies focusing on TAN maturation. Strategies include (i) redirecting differentiation of immature TANs toward non-suppressive fates (e.g., Flt3L and ER-stress/epigenetic modulators), (ii) blocking tumoral recruitment of immature neutrophils (e.g., CXCR4 antagonists and peri-operative/neoadjuvant windows), and (iii) preventing conversion of mature cells into immature-like states (e.g., DKK1 inhibition targeting the DKK1–CKAP4 axis). ADCC, antibody-dependent cellular cytotoxicity; BD/SC, band/seg-competent; C5a, complement component 5a; CKAP4, cytoskeleton-associated protein 4; CSF-1, colony-stimulating factor 1; DKK1, Dickkopf-related protein 1; ER, endoplasmic reticulum; EGF, epidermal growth factor; Flt3, FMS-like tyrosine kinase 3; HGF, hepatocyte growth factor; IL-10, interleukin-10; IFN, interferon; IL-12, interleukin-12; ISG, interferon-stimulated genes; IL-1β, interleukin-1 beta; MC, myelocyte; MHC, major histocompatibility complex; MM, metamyelocyte; Neu, neutrophil; NETs, neutrophil extracellular traps; NE, neutrophil elastase; NO, nitric oxide; PM, promyelocyte; PGE2, prostaglandin E2; ROS, reactive oxygen species; S100A8/9, S100 calcium-binding proteins A8/A9; TME, tumor microenvironment; TGF-β, transforming growth factor beta; TLR, toll-like receptor; TNF, tumor necrosis factor.

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