Role of tumor microenvironment composition and metabolism in lymphoid malignancies and therapeutic strategies

Literature search and selection criteria

This review systematically retrieved relevant studies on the TME and metabolic reprogramming in lymphoma published from the establishment of databases to April 2025 from PubMed. The search keywords included: lymphoma, tumor microenvironment, metabolic reprogramming, glucose metabolism, lipid metabolism, amino acid metabolism, tumor-associated macrophages, myeloid-derived suppressor cells, cancer-associated fibroblasts, and other related terms. Meanwhile, the reference lists of relevant reviews and high-quality studies were manually searched to supplement important literature not included in the databases.

Inclusion criteria

Study type: Basic experimental studies, clinical studies, meta-analyses, systematic reviews, and other original English studies with complete data and clear conclusions.

Research objects: Studies focusing on the functional mechanisms of TME components, metabolic abnormalities, and targeted therapeutic strategies in lymphoma.

Research content: Studies involving the regulatory roles of immune cells and non-immune components in the TME; studies on the association between abnormal glucose, amino acid (AA), lipid, and other core metabolic pathways and lymphoma occurrence, progression, drug resistance, and immune escape; studies on therapeutic strategies targeting TME components or metabolic abnormalities.

Literature quality: For basic experimental studies, those with clear grouping, sufficient sample size, and repeatable results were included; for clinical studies, those with complete patient information, clear outcome indicators, and rigorous follow-up were included; for meta-analyses/systematic reviews, those with standardized search strategies and strict inclusion/exclusion criteria were included.

Exclusion criteria

Duplicate published literature, literature with incomplete data, or literature from which core information cannot be extracted. Studies whose research objects are other hematological malignancies or solid tumors not related to lymphoma, and without extended analysis on lymphoma. Literature with unclear research design, lack of positive/negative controls, or unreliable experimental results; case reports, conference abstracts, and thesis literature with insufficient depth. Reviews were only used to sort out references and cite core conclusions, not for direct data extraction and analysis.

Literature screening and data extraction

Two researchers independently completed literature retrieval, initial screening of titles/abstracts, full-text re-screening, and data extraction. Disagreements were resolved through consultation with a third researcher. The core extracted information included: lymphoma subtype, research model (cell line/animal model/clinical sample), key research findings, regulatory molecules/targets, intervention measures (drugs/genetic manipulation), and experimental/clinical outcomes. Finally, a total of 147 literatures were included in this review.

Tumor-associated macrophages

TAMs are abundantly present in the TME of most cancer types and are typically associated with poor clinical prognosis in cancer patients. The known pro-tumorigenic effects of TAMs include stimulating pro-tumor inflammation, promoting the immune escape of cancer cells, facilitating angiogenic transformation, and accelerating the invasion and metastasis of tumor cells^1,4,5.

Key mechanisms driving TAM polarization

Macrophages exhibit two different polarization activation states, namely classically activated M1-type TAM (M1 TAMs) and alternatively activated M2-type TAM (M2 TAMs) ⁶ . M1 TAMs mainly exert pro-inflammatory, anti-bacterial, and antitumor functions by secreting pro-inflammatory cytokines, such as interleukin (IL)-1, IL-6, reactive oxygen species/reactive nitrogen species (ROS/RNS), and tumor necrosis factor (TNF)-α ⁷ . The TME often coerces them into adopting the M2 TAMs. This transition is frequently triggered by Th2-derived signals (IL-4, IL-13) and elevated CSF1R expression on macrophages, engaging critical signaling hubs, such as TLR4/NF-κB and IL-4/IL-13/STAT6 ⁸ . Once polarized, M2 TAMs secrete reparative factors—including Th2 cytokines (IL-4, IL-10, IL-13), matrix metalloproteinases (MMPs), and tumor growth factor (TGF)-β—that fuel tumor growth and suppress immunity via diverse signaling networks ³ .

Evidence in cancer and lymphoma

Specific chemokine axes act as potent drivers of this pro-tumorigenic reprogramming. For instance, CCL2, abundantly secreted by tumor cells, recruits monocytes via the CCL2/CCR2 axis; upon binding, CCR2 activates intracellular cascades (PI3K/AKT, MAPK/p38, JAK/STAT3) that accelerate tumor initiation and progression ⁹ . Similarly, in B-cell lymphoma, genetic alterations in CREBBP or EP300 reduce H3K27 acetylation, thereby unleashing the NOTCH pathway to upregulate CCL2/CSF1, which further promotes proliferation and M2 polarization ¹⁰ . The CCL3-CCR1 axis also plays a pivotal role: high CCR1 expression on monocytes, combined with tumor-derived CCL3, not only facilitates cell migration but actively skews macrophage programming toward the immunosuppressive M2 phenotype while inhibiting M1 responses, thus remodeling the TME ¹¹ .

Spatial heterogeneity and functional implications

The functional identity of TAMs (specifically CD163⁺ macrophages) is not uniform but varies significantly based on their spatial proximity to tumor cells. In tumor-rich areas (e.g. regions closely adjacent to tumor cells), CD163⁺ macrophages upregulate proteins related to apoptosis, DNA repair, and proliferation, including Bcl-2-interacting mediator of cell death (BIM), Bcl-2-associated agonist of cell death (BAD), and p53. In tumor-sparse areas (e.g. lymphoid tissues around the tumor), CD163⁺ macrophages exhibit higher levels of immunoregulatory proteins, such as VISTA and B7-H3, suggesting their active immunosuppressive function ¹² .

Key mechanism: TAMs drive immunosuppression and tumor growth

In peripheral T-cell lymphoma (PTCL), high GATA3 expression signals a poor prognosis by fostering a Th2-like environment rich in cytokines such as IL-4, IL-5, IL-10, and IL-13 ¹⁷ . These molecules act as architects of immune evasion, polarizing macrophages toward the pro-tumorigenic M2 phenotype ¹⁸ . Once established, M2 macrophages fuel angiogenesis via VEGF secretion while simultaneously engaging in an autocrine loop: they release IL-10 and TGF-to upregulate their own PD-L1 expression. This surface protein then binds to programmed cell death protein 1 (PD-1) on T-cells, effectively silencing their antitumor activity and creating a sanctuary for tumor cell survival (Figure 1).

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Figure 1.

Composition of the TME. TAMs inhibit the functions of tumor-infiltrating T-cells through their interactions with these T-cells. TAMs secrete various mediators that promote tumor progression. TAM, tumor-associated macrophage. (This figure was created by the authors using Microsoft PowerPoint 2019).

Evidence across lymphoma subtypes

A consistent narrative emerges across diverse lymphomas: abundant macrophage infiltration often heralds dismal outcomes.

T-cell lymphomas: In angioimmunoblastic T-cell lymphoma (AITL), a dominance of M2 macrophages closely tracks with poor prognosis. Similarly, in adult T-cell leukemia/lymphoma (ATLL), the presence of CD163⁺ TAMs serves as a stark indicator of unfavorable clinical trajectories ¹⁷ . Broadly, the density of CD163-positive macrophages inversely correlates with survival rates.

Follicular lymphoma (FL): Here, TAMs play a dual role. They can actively nurture FL B cells by crosslinking oligomannosylated B cell receptor (BCR) with Dendritic cell-specific intercellular adhesion molecule-3-grabbing non-integrin (DC-SIGN), triggering sustained, albeit weak, signaling that bolsters tumor growth. In contrast, TAMs can phagocytose tumor B cells. However, FL B cells express CD47 in large quantities, which inhibit the phagocytic and inflammatory functions of macrophages expressing signal regulatory protein α (SIRPα), allowing tumor cells to evade macrophage-mediated clearance and facilitating immune escape process ¹⁴ .

In Hodgkin’s lymphoma (HL), an increased quantity of TAMs often indicates poor patient prognosis. The interaction between HL cells and TAMs involves the regulation of various signaling pathways, including the Jak/STAT signaling pathway, and the effects of cytokines, such as IL13, which further influence tumor progression ¹⁹ . In classical HL (CHL), the presence of TAMs is associated with patient survival. In a study involving patients with CHL, the TAM-enriched TME phenotype remained consistent from diagnosis to early relapse biopsy, with significant enrichment of CD163-positive macrophages in early relapse samples, suggesting an association with CHL recurrence and prognosis ²⁰ .

Aggressive B-cell lymphomas: A meta-analysis demonstrated that a high density of M2 TAMs in the TME strongly predicts of poor prognosis in patients with diffuse large B-cell lymphoma (DLBCL) ²¹ . Similarly, in primary central nervous system lymphoma (PCNSL), an increased TAM levels are associated with shorter overall survival (OS) and progression-free survival (PFS). Increased TAMs levels may contribute to the poor prognosis of PCNSL^22,23.

Key mechanism: disrupting macrophage recruitment and survival

The CSF1R signaling pathway, activated by colony-stimulating factor 1 (CSF1), serves as a primary driver for TAM abundance and immunosuppressive activity. In mantle cell lymphoma (MCL), inhibiting this receptor eliminates CD163⁺ TAMs; specifically, the CSF1R inhibitor PLX3397 (pexidartinib) significantly reduces M2 TAMs viability. Furthermore, targeting the CCL2/CCR2 signaling axis offers a feasible immunological intervention, as CCR2 antagonists can reduce tumor growth and spread ²⁴ . Similarly, in MCL, immunofluorescence analysis revealed that the CCR1 inhibitor treatment group demonstrated a significant reduction in M2 TAMs and an increase in CD8⁺ T-cell infiltration, indicating that inhibition of CCR1 could reduce the CCL3-CCR1 paracrine signaling axis between the tumor and macrophages, thereby alleviating the tumor burden ¹¹ .

Therapeutic relevance: reprogramming phenotype and enhancing phagocytosis

What strategies exist to switch TAMs from a pro-tumor (M2) to an antitumor (M1) state or boost their engulfment capabilities? PI3Kγ is an important promoting factor for immunosuppression. Inhibiting PI3Kγ could promote TAM polarization toward the M1 phenotype, enhance immune response, and inhibit tumor growth and metastasis. PI3Kγ-specific inhibitors, such as IPI-549, are particularly applicable for tumors with high M2 TAM infiltration^25,26. TGF-β, an important immunosuppressive and metastasis-promoting factor, drives M2 polarization and tumor progression ²⁷ . Thus, inhibiting the TGF-β signaling pathway can help enhance immune cell activity. Similarly, the VEGF/VEGFR axis contributes to tumor angiogenesis and immune regulation by recruiting and polarizing TAMs and impairing T-cell function. Combination anti-VEGF therapies with ICIs can remodel the TME and enhance immunotherapy efficacy ²⁸ . In preclinical models of DLBCL, anti-CD47 antibodies can reduce tumor burden and when combined with rituximab, demonstrate a synergistic effect in promoting macrophage-mediated phagocytosis of lymphoma cells ²⁹ . In cutaneous T-cell lymphoma (CTCL), anti-PD-L1 and lenalidomide promote the repolarization of M2 TAMs to M1 phenotypes, as evidenced by the upregulation of M1 markers, such as CD80; the downregulation of CD163, PD-1, and PD-L1; changes in cytokine/chemokine expression; and inhibition of JAK/STAT and NF-κB signaling pathway. Their combination can inhibit M2 TAM migration by downregulating chemokines and their receptors, enhance phagocytic activity of M2 TAMs, and promote T-cell proliferation, thereby enhancing antitumor immunity ³⁰ .

Epigenetic drugs: therapeutic landscape and immune regulatory mechanisms

Various epigenetic drugs, such as DNA methyltransferase inhibitors (DNMTi), histone deacetylase inhibitors (HDACi), BET inhibitors, and EZH2 inhibitors, have been approved by the U.S. Food and Drug Administration (FDA) or are in clinical trials for treating hematological malignancies and solid tumors ¹⁰ . Tucidinostat (chidamide), a novel subtype-selective HDACi targeting class I HDAC1, HDAC2, HDAC3, and class IIb HDAC10, has been approved for treating relapsed/refractory PTCL ³¹ .

The level of histone acetylation is determined by the dynamic equilibrium between histone acetyltransferases (HATs) and histone deacetylases (HDACs). HATs add acetyl groups to lysine residues of histones, whereas HDACs remove them ³² . Specifically, HDAC2 inhibitors can induce IL28A and IL28B expression, stimulate STAT1, and upregulate genes involved in double-stranded RNA pathogen recognition receptors and Major Histocompatibility Complex class (MHC) I class antigen presentation, potentially increasing immune cell infiltration in the TME and enhancing response to PD-1 blockade ³³ . Furthermore, Nguyen et al. ³⁴ reported that HDAC3 selectively binds to activating transcription factor 3 (ATF3) in a deacetylase activity-dependent manner, thereby inhibiting TLR signaling. Since ATF3 is a stress-induced transcription factor essential for regulating immune responses and maintaining normal host defense mechanisms, its inhibition via HDAC3 enhances NK cell cytotoxicity against lymphoma cells and simultaneously upregulates the expression of chemokines, such as CXCL12, among which CXCL12 and CXCL10 most effectively recruit NK cell^35,36. EZH2 inhibitors can enhance the immunogenicity of lymphoma, promote T-cell function, and improve the therapeutic efficacy of T-cell immunotherapy on lymphoma, providing a new strategy for improving immunotherapy outcomes in patients with B-cell lymphoma ³⁷ .

Preclinical data illustrate considerable potential in overcoming immunotherapy resistance in B-cell lymphoma ³² . For instance, the HDACi OKI-179 could inhibit the growth of G1XP lymphoma cells, induce cell cycle arrest (stopping cells at the G0/G1 phase and reducing the proportion of cells in S phase), and induce apoptosis (increasing the production of cleaved caspase-3). OKI-179 upregulated PD-L1 expression in both the G1XP and OCI-Ly7 lymphoma cells, with a dose-dependent effect observed specifically in G1XP lymphoma cells ³⁸ . Meanwhile, per preclinical studies in mice, HDACi can enhance the efficacy of ICIs in treating various cancer types, including hepatocellular carcinoma and lymphoma^38,39.

Ongoing clinical trials are evaluating the synergistic effects of combining epigenetic-targeting agents with ICIs. For instance, the combination of DNMTi with drugs, such as anti-PD-1 and anti-PD-L1 could enhance the antitumor immune response and improve immunotherapy efficacy ⁴⁰ . While these findings highlight promising therapeutic relevance, further investigation is needed to fully define the optimal targets and address remaining uncertainties regarding long-term outcomes and patient selection. Table 1 shows the therapeutic strategies targeting TAMs in the TME.

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Table 1.

Therapeutic strategies targeting TAMs in the TME.

Target	Lymphoma subtype	Agent/drug	Stage of research/progress	Key findings	Ref.
CSF1/CSF1R axis	B-cell lymphoma (e.g. FL, DLBCL)	CSF1R inhibitors (e.g., PLX3397, BLZ945)	Preclinical/early clinical	Genetic loss of CREBBP/EP300 unleashes NOTCH signaling to upregulate CSF1, driving M2-TAM polarization and tumor progression. Targeting CSF1R aims to deplete or reprogram pro-tumorigenic TAMs.	Yang et al. 10
CCL2/CCR2 axis	B-cell lymphoma	CCR2 antagonists/CCL2 neutralizing antibodies	Preclinical	Tumor-derived CCL2 recruits monocytes via CCR2, activating PI3K/AKT/MAPK pathways that promote tumor initiation and M2 polarization. Blocking this axis may inhibit monocyte recruitment and TAM-mediated immunosuppression.	Xu et al. 9
CD47/SIRPα “Don’t Eat Me” signal	Follicular lymphoma (FL)	CD47 blocking antibodies (e.g. magrolimab)	Clinical Trials (Phase I/II)	FL B-cells overexpress CD47, which engages SIRPα on macrophages to inhibit phagocytosis, enabling immune escape. Blocking CD47 enhances macrophage-mediated tumor cell clearance (phagocytosis).	Laurent et al. 14
PD-L1/PD-1 immune checkpoint	Natural killer/T-cell lymphoma (NKTCL), peripheral T-cell lymphoma (PTCL)	PD-1/PD-L1 inhibitors (e.g. pembrolizumab, nivolumab)	Clinical trials/approved in other cancers	TAMs express PD-L1 and interact directly with CD8+ T-cells (PD-1+) in the TME, suppressing T-cell function. In PTCL, M2-TAM-derived IL-10/TGF-β upregulates their own PD-L1, silencing antitumor T-cells.	Xiang et al. 13 Li et al. 15 Boutilier and Elsawa 18
EZH2 (epigenetic regulator)	Lymphomas with EZH2 mutations or antigen presentation defects (e.g. FL)	EZH2 inhibitors (e.g. tazemetostat)	Approved for FL/clinical trials in combinations	EZH2 inhibition reverses MHC class I/II and antigen-processing gene (e.g. TAP1, LMP2) suppression, restoring antigen presentation. This can enhance the efficacy of subsequent immune therapies (e.g. checkpoint inhibitors, CAR-T).	(Based on prior conv. and 10 mechanism)
CSF1/CSF1R	Mantle cell lymphoma (MCL)	PLX3397 (pexidartinib)	Preclinical	Inhibiting CSF1R eliminates CD163+ TAMs and significantly reduces M2 TAM viability.	Ng et al. 24
CCL2/CCR2	Lymphoma (general)	CCR2 antagonists	Preclinical	Blocking this axis can reduce tumor growth and spread by disrupting monocyte recruitment.	Ng et al. 24
CCL3/CCR1	Mantle cell lymphoma (MCL)	CCR1 inhibitor	Preclinical	Inhibition reduces M2 TAMs and increases CD8+ T-cell infiltration, alleviating tumor burden by disrupting tumor-macrophage paracrine signaling.	Le et al. 11
PI3Kγ	Tumors with high M2 TAM infiltration	IPI-549	Preclinical/early clinical	PI3Kγ inhibition reprograms TAMs toward the M1 phenotype, enhances immune response, and inhibits tumor growth and metastasis.	Kaneda et al. 25 De Henau et al. 26
TGF-β	Lymphoma (general)	TGF-β pathway inhibitors	Preclinical	Inhibiting this pathway can counteract M2 polarization and tumor progression, helping to enhance immune cell activity.	Batlle and Massagué 27
VEGF/VEGFR	Lymphoma (general)	Anti-VEGF therapies (e.g. bevacizumab)	Clinical trials (combinations)	Combined with Immune Checkpoint Inhibitors (ICIs), anti-VEGF therapy can remodel the TME and enhance immunotherapy efficacy.	Chamseddine et al. 28
CD47	Diffuse large B-cell lymphoma (DLBCL)	Anti-CD47 antibodies	Preclinical	Promotes macrophage-mediated phagocytosis of lymphoma cells. Synergistic effect observed when combined with rituximab.	Chao et al. 29
PD-L1 and Immunomodulation	Cutaneous T-cell lymphoma (CTCL)	Anti-PD-L1 + lenalidomide	Preclinical	Combination promotes repolarization of M2 to M1 TAMs (↑CD80, ↓CD163/PD-L1), enhances phagocytosis, inhibits M2 migration, and promotes T-cell proliferation.	Han et al. 30
HDAC (Class I/IIb)	Relapsed/Refractory PTCL	Tucidinostat (chidamide)	Approved (China for r/r PTCL)	A subtype-selective HDAC inhibitor approved for the treatment of relapsed/refractory Peripheral T-Cell Lymphoma.	Pahl et al. 31
HDAC2	Lymphoma (general)	HDAC2 inhibitors	Preclinical	Can induce IL28A/B, stimulate STAT1, and upregulate genes involved in pathogen recognition and MHC I antigen presentation, potentially enhancing response to PD-1 blockade.	Gao et al. 33
HDAC3	Lymphoma (general)	HDAC3 inhibitors	Preclinical	Inhibition enhances NK cell cytotoxicity against lymphoma cells and upregulates chemokines (e.g. CXCL12, CXCL10) that recruit NK cells to the TME.	Ku and Cheng 35 Zhu et al. 36
EZH2	B-cell lymphoma	EZH2 inhibitors (e.g. tazemetostat)	Approved (FL)/clinical trials	Enhances lymphoma immunogenicity, promotes T-cell function, and improves the efficacy of T-cell-based immunotherapies.	Isshiki et al. 37
HDAC (Pan)	Lymphoma (e.g. G1XP model)	OKI-179	Preclinical	Inhibits lymphoma cell growth, induces cell cycle arrest and apoptosis. Upregulates PD-L1 expression in lymphoma cells.	Wang et al. 38
HDACi + ICI	Various cancers (incl. lymphoma)	HDACi + anti-PD-1/PD-L1	Preclinical/clinical trials	Preclinical studies show HDAC inhibitors can enhance the efficacy of Immune Checkpoint Inhibitors. Clinical trials are ongoing to evaluate these combinations.	Wang et al. 38 Llopiz et al. 39
DNMTi + ICI	Various cancers	DNMTi + anti-PD-1/PD-L1	Clinical trials	Combination therapies are being evaluated to enhance antitumor immune response and improve immunotherapy efficacy.	Ling et al. 40

The key mechanisms driving the expansion and function of MDSCs

MDSCs are classified into two main types: polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs), and monocytic myeloid-derived suppressor cells (M-MDSCs)^8,41. Under physiological conditions, immature myeloid cells (IMCs) can differentiate into mature monocytes, dendritic cells, and granulocytes. However, in pathological environments, the differentiation and maturation of IMCs are inhibited, leading to the expansion of MDSCs. Various factors in the TME, such as those secreted by tumor cells and extracellular signals, can promote the transformation of IMCs into MDSCs ²⁴ . Factors related to tumors, such as chronic inflammation, hypoxia, nutritional deficiency, and growth factors, such as granulocyte-macrophage colony-stimulating factor (GM-CSF), granulocyte colony-stimulating factor (G-CSF), and cytokines, including IL-6, TNF, and VEGF, jointly promote the generation of MDSCs^42,43. Once formed, MDSCs are recruited to the TME through CXCR2, CCR2, CCR5, and other chemokine receptors. PMN-MDSCs are mainly recruited by CXC chemokines, whereas M-MDSCs migrate depending on the CCL2-CCR2 axis ⁴² . Factors related to the immunosuppressive ability of MDSCs include arginase 1 (ARG1), inducible nitric oxide synthase (iNOS), TGF-β, IL-10, cyclooxygenase-2 (COX-2) and IDO. Notably, ARG1 starves T-cells of arginine—an AA essential for their activation—thereby halting T-cell proliferation and function^8,44.

Evidence linking MDSCs to cancer progression and lymphoma prognosis

As heterogeneous myeloid populations that swell within the TME, MDSCs act as architects of tumor immune evasion, angiogenesis, and metastasis, while also fostering resistance to cancer therapies ⁴² . In DLBCL, clinical data reveal a stark correlation: the higher the percentage of circulating M-MDSCs in the peripheral blood (PB), the later the stage of DLBCL, the higher the International Prognostic Index (IPI) score, and the worse the survival period ⁴⁵ . Furthermore, survivors of DLBCL bear lasting scars of chronic inflammation, characterized by persistent inhibitory MDSCs, sustained T-cell activation, and eventual T-cell depletion—signatures that endure for years post-therapy ⁴⁶ . The frequencies of MDSCs in both the bone marrow (BM) and PB of patients with DLBCL were elevated. Genes involved in the nitric oxide (NO) pathway, reactive oxygen process, cellular oxidative detoxification, heme signal transduction, and regulation of the autophagy pathway were significantly upregulated in BM-MDSCs ⁴⁷ .

The therapeutic implications and remaining questions

Targeting MDSCs has become a key strategy for improving the therapeutic effects of cancer treatments ⁴² . The unique molecular landscape of BM-MDSCs offers specific avenues for intervention; disrupting their oxidative stress or autophagy pathways could potentially dismantle the immunosuppressive microenvironment. Such approaches hold promise for boosting the success of CAR-T cell therapies and bispecific antibodies ⁴⁷ .

Mechanisms and targeting strategies of MDSC-mediated immunosuppression in lymphoma

In relapsed/refractory DLBCL (R/R DLBCL), MDSCs promote angiogenesis through VEGF, inhibit the maturation and function of NKs, and induce macrophage polarization to the M2 phenotype by secreting IL-10 and TGF-β to suppress the innate immune response ⁴⁸ . MDSCs survive in the TME through metabolic reprogramming and are adverse prognostic indicators of hematological malignancies. The adenosine triphosphate (ATP) and oxaloacetate metabolism induced by the β2-AR-STAT3 pathway is a key regulatory factor for mitochondrial adaptation in MDSCs ⁴⁹

In the in vivo EL4 lymphoma model, blocking β2-AR signaling, inhibiting mitochondrial electron transport chain, or reducing oxaloacetate production could enhance doxorubicin efficacy, promote MDSCs apoptosis, and reduce ROS (mROS) generation ⁴⁹ . These findings highlight metabolism-driven pathways as promising therapeutic leverage points.

Multiple approaches effectively neutralize MDSCs. HDACi not only reduces the number of MDSCs but also impairs their immunosuppressive function, thereby promoting a more immunologically active antitumor TME ⁵⁰ . The inhibition mechanism of MDSCs can be reversed using ARG1 and NOS2 inhibitors, phosphodiesterase-5 inhibitors, and bardoxolone methyl, thereby enhancing T-cell proliferation. Anti-GR1 antibodies, peptibodies, 17-DMAG, 5-fluorouracil, and anti-CD33 antibodies can be used to deplete MDSCs and restore T-cell immunity. Vitamins A, D3, and E induce MDSC differentiation. For instance, all-trans retinoic acid (ATRA) can improve immunotherapy efficacy. Antibodies against S100A8/S100A9, tasquinimod, zoledronic acid, and JAK2/STAT3 inhibitors can reduce the number of MDSCs^51,52.

The JAK inhibitor ruxolitinib exemplifies translational potential. The JAK inhibitor ruxolitinib can significantly reduce the percentage of PMN-MDSCs in the blood. Ruxolitinib also downregulates the expression of MDSC-related markers such as S100A8, S100A9, and CD163, thereby weakening their suppressive function. In the presence of ICIs, ruxolitinib regulates myeloid cells, enhances antitumor immune responses, and preserves T-cell function. In a phase I clinical trial of patients with R/R HL, the objective response rate (ORR) of combination treatment with ruxolitinib and nivolumab was 52% (10/19), and some patients achieved a complete metabolic response or partial remission. The disease control rate was relatively high, indicating that JAK inhibitors can enhance the therapeutic effect of ICIs on lymphoma. Combination therapy showed good efficacy in patients with HL and provides a new direction for overcoming immune treatment resistance ⁵³ . In CTCL, JAK inhibitors (e.g. momelotinib and ruxolitinib), alone or in combination with an HDACi (romidestat), exert significant antitumor effects on CTCL cell lines and can effectively reverse resistance in primary samples that are unresponsive to romidestat ⁵⁴ . Table 2 shows the therapeutic strategies targeting MDSCs in the TME.

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Table 2.

Therapeutic strategies targeting MDSCs in the TME.

Target/mechanism	Lymphoma subtype	Agent/intervention	Stage of research/progress	Key findings	Ref.
β2-AR-STAT3 signaling and mitochondrial metabolism	Lymphoma (EL4 model)	β2-AR signaling blockade; mitochondrial ETC inhibition	Preclinical	Blocking this pathway or inhibiting mitochondrial metabolism enhances doxorubicin efficacy, promotes MDSC apoptosis, and reduces mitochondrial ROS generation in an EL4 lymphoma model.	Daneshmandi et al. 49
JAK2/STAT3 signaling	Lymphoma (general)	JAK2/STAT3 inhibitors (e.g. ruxolitinib)	Preclinical/phase I clinical trial	Reduces PMN-MDSC percentage and downregulates S100A8/A9, CD163. Combined with ICIs (nivolumab), showed 52% ORR in R/R HL patients, enhancing antitumor immunity.	Lv et al. 51 Zak et al. 53
Histone deacetylase (HDAC)	Lymphoma (general)	HDAC inhibitors (HDACi)	Preclinical	Reduces MDSC numbers and impairs their immunosuppressive function, promoting a more immunologically active TME.	Sidiropoulos et al. 50
Arginase 1 (ARG1) and iNOS (NOS2)	Lymphoma (general)	ARG1 and NOS2 inhibitors	Preclinical	Reverses MDSC-mediated immunosuppression by blocking arginine depletion and NO production, thereby enhancing T-cell proliferation.	Lv et al. 51
General MDSC depletion	Lymphoma (general)	Anti-GR1 antibodies, 5-fluorouracil, anti-CD33 antibodies	Preclinical	These agents can deplete MDSCs and help restore T-cell immunity.	Lv et al. 51
MDSC differentiation	Lymphoma (general)	All-trans retinoic acid (ATRA; vitamin A derivative)	Preclinical	Induces MDSC differentiation into mature myeloid cells, thereby improving immunotherapy efficacy.	Lv et al. 51
S100A8/A9 proteins	Lymphoma (general)	Anti-S100A8/A9 antibodies, tasquinimod	Preclinical	Targeting these pro-inflammatory proteins can reduce the number of MDSCs.	Lv et al. 51
JAK inhibition	Cutaneous T-cell lymphoma (CTCL)	Momelotinib, ruxolitinib (±romidepsin)	Preclinical	JAK inhibitors alone or combined with HDACi exert significant antitumor effects on CTCL and can reverse resistance to romidepsin.	Cortes et al. 54

Key mechanisms: how CAFs drive tumor progression

Several different biomarkers are used to define CAFs, including but not limited to α-smooth muscle actin (α-SMA, also known as ACTC2), platelet-derived growth factor receptor α/β (PDGFRα/β), fibroblast-specific protein 1 (FSP-1, also known as S100A4), and fibroblast activation protein (FAP) ⁵⁵ . CAFs play crucial roles in tumorigenesis, metastasis, angiogenesis, immune evasion, and drug resistance. For instance, they influence tumor progression by secreting regulatory molecules and extracellular vesicles (EAs) and remodeling the ECM ¹ . Targeting the proline synthase PYCR1 (pyrroline-5-carboxylate reductase 1) in CAFs may inhibit the production of tumor-promoting extracellular matrix (TP-ECM) ⁵⁶ .

Evidence in cancer and lymphoma: chemoresistance and immune evasion

Beyond shaping the physical tumor environment, CAFs actively confer chemoresistance to malignant cells. They stimulate cancer cell survival by delivering exosomes, promoting the epithelial–mesenchymal transition (EMT) in cancer cells, and eliminating chemotherapeutic drugs. CAFs are also involved in immune evasion and resistance to immunotherapy ¹ . CAFs contribute to immune evasion by forming an immune barrier through the secretion of chemokines and TGF-β, which recruit and polarize TAMs. In addition, neovascularization in lymphoma acts as a functional barrier, facilitating immune tolerance ⁵⁷ . In FL, CAFs play a significant role in the TME. They express various chemokines, such as CXCL12, CCL19, CCL21, and CCL2, which affect the growth of tumor B cells, recruit immune cells, and regulate TAM functions ¹⁴ .

Specifically, CXCL12 is a key factor that regulates the migration of lymphoma cells from blood to lymphoid tissues. It binds to its receptor, CXCR4, and activates downstream signaling pathways, promoting cell survival, metastasis, and chemotherapy resistance. CXCL12 also interacts with 2-arachidonoyl glycerol (2-AG) to regulate lymphoma cell chemotaxis. In chronic lymphocytic leukemia (CLL), 2-AG and CXCL12 jointly increase cell migration. In MCL cells, chemotaxis was reduced after combined treatment in most samples ⁵⁸ . The efficacy of immunotherapy relies on the accumulation of antigen-specific CD8⁺ T-cells within tumors, a process governed by the CXCL12-CXCR4 axis via tumor-associated lymphatic vessels. Consequently, inhibiting CXCL12/CXCR4 signaling can boost the population of functional CD8⁺ T-cells inside tumors, improving tumor control ⁵⁹ .

Therapeutic relevance: targeting exosomes and signaling axes

Exosomes (small extracellular vesicles, sEVs) are potential biomarkers for monitoring and exploring tumor development mechanisms. Exosomes enter the TME by carrying the CD98hc protein, promoting tumor cell proliferation and invasion and chemotherapy resistance (i.e. resistance to panitumumab), leading to disease progression. Inhibiting exosome generation can block this process and enhance the efficacy of chemotherapy, providing a new strategy for overcoming drug resistance ⁶⁰ . Some studies highlighted that exosomes derived from DLBCL can promote tumor progression by transferring GP130 to macrophages, activating STAT3 signaling, and polarizing macrophages toward a tumor-promoting M2-like phenotype. Using exosomes in the TME and macrophages as therapeutic targets provides a new direction for precise clinical treatment of DLBCL ⁴⁰ .

Exosomes modulate antitumor immunity and serve as therapeutic vehicles

Tumor-derived exosomes (TDEs) secreted by lymphoma cells carry PD-L1 and bind to PD-1 on the surface of T-cells, inducing T-cell apoptosis or functional exhaustion, and weakening the antitumor effect of CAR-T cells. In DLBCL, the level of PD-L1 in TDEs positively correlates with disease progression, and blocking the PD-L1 pathway reverses immunosuppression. Conversely, chimeric antigen receptor (CAR) exosomes are derived from CAR-T cells, carrying the same CAR as the parent cell and containing cytotoxic molecules, such as granzyme B and perforin, which can directly kill lymphoma cells expressing the corresponding antigen ⁶¹ . Leveraging the tumor-homing behavior of cancer cells, researchers have prepared activated macrophage-tumor chimeric exosomes (aMT-exos) that can accumulate in lymph nodes and tumors, activate immune responses, improve the TME, and effectively inhibit primary tumors, tumor metastasis, and postoperative tumor recurrence. This provides a new strategy for personalized immunotherapy ⁶² .

The role of the ECM in tumor progression and immune evasion

The ECM can be divided into the basement membrane and the interstitial matrix ⁶³ . ECM serves as a supporting framework for tumor cells, creating a specific survival environment ⁶⁴ . Abnormal degradation and deposition are associated with tumor progression and can affect the function of immune cells ⁶³ . In HL, tumor and stromal cells can modify ECM properties ⁶⁵ . The remodeling of ECM alters its physical properties and composition, creating favorable conditions for tumor cell migration. Circulating tumor cells (CTCs) upregulate the expression of certain ECM proteins, which support their survival, enable evasion of immune clearance, and facilitate formation of metastatic foci ⁶⁴ (Figure 1). Table 3 shows the therapeutic strategies targeting CAFs and ECM in the TME.

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Table 3.

Therapeutic strategies targeting CAFs and ECM in the TME.

Target/mechanism	Lymphoma subtype	Agent/intervention	Stage of research/progress	Key findings	Ref.
PYCR1 in CAFs	Lymphoma (General)	PYCR1 inhibitors	Preclinical	Targeting proline synthase PYCR1 in CAFs may inhibit the production of tumor-promoting extracellular matrix (TP-ECM).	Liu et al. 56
CXCL12/CXCR4 axis	Follicular lymphoma (FL), chronic lymphocytic leukemia (CLL), mantle cell lymphoma (MCL)	CXCR4 antagonists (e.g. plerixafor)	Preclinical/clinical trials	CXCL12 from CAFs promotes lymphoma cell survival, metastasis, and chemoresistance. Inhibiting this axis can boost intratumoral functional CD8+ T-cells and improve tumor control.	Laurent et al. 14 Merrien et al. 58 Steele et al. 59
Exosome generation/uptake	Lymphoma (general)	Exosome generation inhibitors	Preclinical	Inhibiting exosome generation can block exosome-mediated promotion of tumor proliferation, invasion, and chemotherapy resistance (e.g. to panitumumab).	Liao et al. 60
Exosomal GP130/STAT3 Axis (in macrophages)	Diffuse large B-cell lymphoma (DLBCL)	Agents targeting exosomal GP130 transfer	Preclinical	DLBCL-derived exosomes transfer GP130 to macrophages, activating STAT3 and polarizing them to a pro-tumor M2-like phenotype. Targeting this axis provides a new therapeutic direction.	Ling et al. 40
Exosomal PD-L1	DLBCL	PD-1/PD-L1 blockade	Preclinical	Tumor-derived exosomes (TDEs) carry PD-L1, inducing T-cell exhaustion. Blocking this pathway reverses immunosuppression, and PD-L1 level in TDEs correlates with disease progression.	Wang et al. 61
CAR exosomes	Lymphoma (general)	Exosomes derived from CAR-T cells	Preclinical	CAR exosomes carry cytotoxic molecules (granzyme B, perforin) and can directly kill antigen-expressing lymphoma cells, offering a cell-free immunotherapy strategy.	Wang et al. 61
Engineered macrophage-tumor exosomes	Lymphoma (general)	Activated macrophage-tumor chimeric exosomes (aMT-exos)	Preclinical	aMT-exos home to lymph nodes/tumors, activate immune responses, remodel the TME, and inhibit primary tumor growth, metastasis, and recurrence.	Wang et al. 62
ECM remodeling	Lymphoma (general)	Integrin inhibitors, LOX inhibitors	Preclinical	Targeting ECM proteins (e.g. upregulated by circulating tumor cells) or enzymes that remodel ECM (e.g. lysyl oxidase) may hinder tumor cell survival, immune evasion, and metastasis.	Winkler et al. 64

Genetic alterations shaping the TME

Genetic characteristics play a decisive role in shaping the TME of lymphoma, particularly genetic abnormalities associated with antigen presentation. These abnormalities act like hidden barriers, aiding tumor cells in evading immune surveillance. Specifically, mutations or deletions in the β2-microglobulin (B2M) gene impair the assembly of MHC class I molecules, thereby preventing effective presentation of tumor antigens and allowing cancer cells to evade recognition by CD8⁺ T-cells. Meanwhile, mutations in the CD58 gene disrupt its critical interaction with CD2, inhibiting T-cell activation signaling. These two types of genetic events collectively reveal the frequent immune escape mechanisms in DLBCL and contribute to the formation of an ‘immune-desert’ cold TME ⁶⁶ . Furthermore, abnormalities in epigenetic regulators, such as EZH2 mutations or CREBBP/EP300 deletions, suppress the expression of MHC molecules and antigen-processing-related genes (e.g. TAP1, LMP2) through histone modifications ⁶⁷ . These early genetic alterations are closely associated with the impaired antigen-presenting function observed in FL precursor cells^67,68.

At a broader level, driver genetic alterations (such as MYC proto-oncogene (MYC) amplification and TP53 mutation) not only regulate the secretion of chemokines to suppress dendritic cell maturation and T-cell infiltration but also promote the recruitment of M2-type TAMs and MDSCs, thereby reinforcing the immunosuppressive barrier^69,70. Meanwhile, chromosomal deletions or translocations (e.g. 9p24.1 amplification) can lead to abnormal amplification of immune checkpoint molecules (e.g. PD-L1) or sustained activation of immune-activating pathways (e.g. NF-κB), further reshaping the immunosuppressive microenvironment ⁷¹ .

Targeted therapies directed against these genetic markers hold great clinical potential. For instance, EZH2 inhibitors can reverse MHC expression defects and restore antigen-presenting function, thereby enhancing the tumor-recognition capacity of ICIs or CAR-T cells—a strategy that has been established as an important therapeutic target for improving immune recognition ⁷² . Therefore, for lymphoma patients with B2M mutations, exploring combination therapies of “epigenetic modulators ⁺ tumor vaccine ⁺ PD-1 inhibitors” holds promise in compensating for the defect in antigen presentation and transforming the cold TME into a hot, immune-active battlefield.

Key mechanism: lactic acid reshapes the immune landscape

Tumor cells undergo aerobic glycolysis to produce lactic acid, which is subsequently transported out of the cells to the extracellular environment through the activation of monocarboxylate transporters on the cell membrane (especially MCT4), leading to acidification of the TME ⁸⁰ . Lactic acid activates the mTOR pathway, thereby phosphorylating the transcription factor TFEB and inhibiting its nuclear translocation, which, in turn, suppresses the expression of vacuolar ATPase subunit (ATP6Vod2) in TAMs. Inhibition of ATP6Vod2 mediates lysosomal degradation of hypoxia-inducible factor 2-α (HIF-2α) and program TAMs in the TME as immunocytes promoting tumor growth ⁸⁰ (Figure 2) Gpr132 (a G protein-coupled receptor) recognizes lactic acid on TAMs and also promotes the polarization of TAMs toward the M2 phenotype. Moreover, the expression of Gpr132 is inhibited by the peroxisome proliferator-activated receptor (PPARγ) transcription factor ⁷³ . Beyond myeloid reprogramming, lactic acid also inhibits the functions of T-cells and NKs, while promoting the proliferation and activity of immunosuppressive cells, such as Tregs and MDSCs, thereby facilitating tumor immune evasion^81,82.

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Figure 2.

Lactic acid produced by aerobic glycolysis of tumor cells is transported out of the cells by MCT4, thereby promoting TAMs polarization to M2 phenotype. (This figure was created by the authors using Microsoft PowerPoint 2019).

Evidence in lymphoma and metabolic competition

Clinical observations confirm that serum lactic acid levels increase progressively in patients with lymphoma ⁸³ . The high glucose uptake and metabolism of tumor cells may lead to an insufficient glucose supply for immune cells, affecting their functions and weakening the body’s antitumor immune response^81,82. In a high glucose environment, lactic acid could inhibit the function of conventional T-cells, but Tregs are resistant to the equivalent concentration of lactic acid in tumors. Their inhibitory functions and proliferation remain unaffected. Treatment with the PEPCK inhibitor 3MP revealed that lactic acid uptake and oxidation, along with upstream gluconeogenic reactions involving PEP, play important roles in the proliferation and inhibition of Tregs ⁸⁴ . In DLBCL, the high-grade malignant B-cell subpopulation exhibits enhanced glycolytic activity. In DLBCL tissues with high glycolytic metabolism, the abundance of interferon (IFN)-TAMs (CD68⁺CXCL10⁺PD-L1⁺) increases, whereas the infiltration of CD8⁺ T-cells decreases, indicating an immunosuppressive microenvironment ⁸⁵ .

Key mechanisms: the metabolic engine and feedback loops

HK has four isoenzymes, namely HK1, HK2, HK3, and HK4. HK1 is typically widely expressed, whereas HK2 is expressed only in adipocytes, bones, and cardiac muscles ⁹¹ . The expression of HK2 is increased in tumors, and its enhanced activity can promote glucose uptake and phosphorylation, providing more energy and synthetic raw materials for tumor cells, thereby promoting tumor cell proliferation^81,92. HIF-1α can upregulate HK2 expression, which promotes glucose conversion into glucose-6-phosphate (G-6-P), thereby enhancing glycolytic flux. Meanwhile, the accumulation of a large amount of glycolytic intermediates can increase the level and activity of HIF-1α, forming a positive feedback loop, which further promotes aerobic glycolysis and maintains the survival and proliferation of tumor cells ⁹³ . Beyond metabolism, HK2 exhibits non-classical functions, such as binding to mitochondrial pore proteins to inhibit apoptosis and directly maintaining tumor cell stemness^94,95.

Evidence in lymphoma: dysregulation and prognostic value

In the context of lymphoma, HK2 serves not only as an important marker related to metabolic function but also holds potential prognostic value^81,92. In PCNSL, the activity of HK2 increases, resulting in higher glycolytic activity of this tumor compared to normal lymphoid tissues ⁹³ . Specifically, patients with PCNSL exhibiting normal immune function and positive Epstein–Barr virus (EBV) status activate the RelA/p65-HK2 signaling axis through different mechanisms, driving glycolysis and promoting tumor progression ⁹⁶ . Similarly, in DLBCL, HK2 showed significantly high expression. Knockdown of HK2 can reduce tumor growth ⁹⁷ . Conversely, HK3 shows a different pattern; mainly found in hematopoietic cells, it is upregulated during terminal differentiation in certain acute myeloid leukemia (AML) models. However, unlike HK2, HK3 deletion in AML cell lines does not alter basal glycolytic activity, suggesting a divergent role in metabolic regulation ⁹⁸ .

Therapeutic relevance: targeting the axis

The dependency of tumors on HK2 offers promising therapeutic avenues. Knockdown of HK2 effectively curtails tumor growth in DLBCL ⁹⁷ . Per another study, high HK2 expression is closely related to intracerebral tumor progression of PCNSL. Knockdown of RelA/p65 or inhibition of the NF-κB pathway (such as BAY11-7082) significantly reduced HK2 levels and inhibited tumor cell growth ⁹⁶ . In AML, while HK2 knockout diminishes glycolytic capacity, the deletion of HK3 significantly enhanced the sensitivity of AML cell lines to cell death induced by ATRA. During the ATRA-induced differentiation process, HK3-deficient (HK3-null) AML cells exhibited an accumulation of ROS and DNA damage ⁹⁸ . Studies revealed that a novel isomerase isoform of hexokinase domain containing 1 (HKDC1) is involved in glucose homeostasis and tumor development. HKDC1 exhibits high sequence similarity with the other four HK isoforms, with only the last eight C-terminal AAs showing differences. In SNK6 cells, overexpression of HKDC1 promotes cell proliferation, while knockdown of HKDC1 inhibits cell proliferation and increases cell apoptosis, indicating that HKDC1 plays a dominant role in the growth of extranodal natural killer/T-cell lymphoma (ENKTL) ⁹⁹ . Critically, ablating HKDC1 can inhibit tumor sphere formation (clusters of cancer cells), cell migration, and cancer cell invasion, as well as reduce the expression of stem cell markers, such as ABCG2, Oct4, Sox2, CD13, and CD133. Re-expression of HKDC1 rescued these phenotypes, indicating that its crucial role in promoting cancer cell proliferation, stem cell maintenance, and tumor growth ¹⁰⁰ .

Key mechanism: PFKP drives tumor aggression

PFK1, a key rate-limiting enzyme in the glycolytic process, exists in three tissue-specific isoenzymes: muscle type (PFKM), liver type (PFKL), and platelet type (PFKP). PFKP is highly expressed in various malignant tumors, including breast cancer, hepatocellular carcinoma, prostate cancer, glioblastoma, and leukemia. Its high expression positively correlates with tumor progression ¹⁰⁶ . PFKP Y64 phosphorylation promotes glycolysis in EGFR-activated enhanced tumor cells in a β-catenin transcriptional activation-dependent manner. It also enhances β-catenin S552 phosphorylation mediated by AKT, thereby promoting its nuclear translocation and downstream gene expression and ultimately promoting the proliferation, migration and invasion of tumor cells ¹⁰⁷ .

Evidence in cancer and lymphoma: metastasis and metabolic reprogramming

Beyond local growth, PFKP plays an important role in tumor metastasis. CXCR4 is crucial for the migration of normal hematopoietic stem cells, progenitor cells, and lymphocytes and is implicated in the metastasis of leukemia and cancer cells. Nuclear PFKP promotes CXCR4 expression, thereby enhancing the migration of T-cell acute lymphoblastic leukemia (T-ALL) cells ¹⁰⁸ . Moreover, in T-cell lymphoma, deletion of the Pdcd1 gene encoding PD-1 leads to the upregulation of PFK-1 and other key glycolytic enzymes, including HK-2, aldolase A, and enolase 1. This enhances glucose uptake and metabolism in tumor cells, thereby increasing energy carrier production, supporting rapid proliferation and malignant transformation, and ultimately promoting tumor progression ¹⁰⁹ . In addition to the key enzymes involved in glycolysis, the expression of glycogen synthase kinase 3 (GSK-3) is increased in DLBCL cell lines and is associated with enhanced cell survival and proliferation. Inhibiting GSK3 can reduce the proliferation of lymphoma cells ⁹⁷ .

Therapeutic relevance: targeting glycolytic branch pathways

In addition to glucose oxidation through glycolysis, which generates acetyl-CoA and lactic acid, glycolytic branch pathways also play a role in tumor growth and adaptation. These branch pathways transfer glucose carbon flux from glycolytic processes at various levels to several anabolic pathways, including the PPP, glycogen synthesis, HBP, and SBP. The metabolites produced by these pathways can be utilized in various metabolic processes, enabling tumor metabolic reprogramming with special flexibility ⁷⁷ . PPP plays a significant role in lymphoma cells. CLL cells divert large amounts of glucose flux into the PPP. Moreover, PPP protects B-ALL cells from oxidative stress. Transcription factors, such as PAX5 and IKZF1 negatively regulate the expression of the key PPP enzyme G6PD, thereby influencing the metabolic state of tumor cells. Meanwhile, SBP has been identified as a key metabolic node regulating the proliferation of malignant B cells ¹¹⁰ . Its activity is upregulated during B-cell activation and germinal center reaction. In human germinal center B-cell lymphomas, the key enzymes Phosphoglycerate dehydrogenase (PHGDH) and PSAT1 in SBP are overexpressed. Importantly, pharmacological inhibition of PHGDH effectively suppresses lymphoma cell proliferation, highlighting a promising therapeutic avenue ⁷⁷ .

Key mechanisms: transcriptional regulators and transporters drive tumor metabolism

Members of the PRDM family (including PRDI-BF1 and RIZ homologous domains) are sequence-specific transcriptional regulators that are often dysregulated in cancer. PRDM15 regulates the transcription of key genes in lymphoma cells and is involved in two metabolic pathways that are crucial for the survival of tumor cells: the PI3K/AKT/mTOR signaling pathway (InsR and Igf1R) and glycolysis (Pkm, Pfkp, and Eno3). Deletion of PRDM15 leads to downregulation of the transcription of these genes, thereby affecting the activity of metabolic pathways ¹¹¹ . In terms of metabolic regulation, oncogenic HSP90 simultaneously supports glycolysis and mitochondrial respiration. In lymphoma cells, oncogenic HSP90 more effectively utilizes the metabolites required for synthesizing macromolecules, which is conducive to maintaining cellular biosynthetic activity. The inhibition of oncogenic HSP90 reduces glucose uptake and lactate secretion in DLBCL cells, impairs glycolytic function, and increases glycolytic reserves. It also reduces glutamine (Gln)-induced mitochondrial oxygen consumption, thereby lowering basal oxygen consumption rate and respiratory parameters ¹¹² .

Evidence in cancer: the role of GLUT proteins in tumor progression

Glucose transporter (GLUT) is responsible for transporting glucose into the cells. Among them, GLUT1, GLUT3, and GLUT4 are overexpressed in various tumors. Oncogenes such as c-MYC, KRAS, and YAP can upregulate the expression GLUT1, promoting glucose uptake by tumor cells. P53, a tumor suppressor protein, inhibits the transcription of GLUT1, GLUT3, and GLUT4. P53 inactivation leads to an increase in GLUT3 expression, thereby increasing the rate of tumor glycolysis (Figure 2) ⁹² . GLUT1 is widely expressed in various tumor cells, and its overexpression increases glucose uptake and promotes tumor cell growth and proliferation ¹¹³ . Single-cell RNA sequencing (scRNA-seq) and other techniques have revealed that GLUT1 is highly expressed specifically in M2 TAMs, indicating their strong capacity for glucose uptake. In M2 TAMs, an increase in glucose utilization increases the level of OGT-catalyzed cleavage of tissue proteinase B by lysosomes (cathespin B O-GlcNAcylation), thereby increasing the mature form of tissue proteinase B and promoting cancer metastasis and chemotherapy resistance ¹¹⁴ . Studies have shown that CAR-T cells overexpressing GLUT1 exhibit stronger metabolic adaptability in vivo, characterized by the simultaneous upregulation of genes related to glycolysis and mitochondrial respiration and an increased ability to utilize glucose. Moreover, GLUT1 overexpression helps maintain the memory phenotype of CAR-T cells ¹¹⁵ .

Therapeutic relevance and targets: exploit metabolic vulnerabilities

Based on the high glucose uptake characteristics of tumor cells, positron emission tomography (PET) imaging with 18F-labeled fluorodeoxyglucose (FDG) can be used to detect glucose uptake by tumor tissues. This method can be used for tumor diagnosis and monitoring therapeutic responses ¹¹⁶ . Various therapeutic strategies and drugs targeting glucose metabolism have been developed based on abnormal glucose metabolism in tumor cells. For instance, inhibitors of GLUTs (e.g. STF-31 and BAY-876) and key enzymes involved in glycolysis (e.g. 3-bromopyruvate, HK2, and LDHA inhibitors) have been studied and applied in tumor treatment ⁸¹ . Table 4 shows the therapeutic strategies targeting glucose metabolism in the TME.

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Table 4.

Therapeutic strategies targeting glucose metabolism in the TME.

Target/mechanism	Lymphoma subtype	Agent/intervention	Stage of research/progress	Key findings	Ref.
Lactate efflux (MCT4)	Lymphoma (general)	Monocarboxylate transporter (MCT4) inhibitors	Preclinical	Inhibiting lactate export could prevent TME acidification and block lactate-mediated reprogramming of TAMs toward a pro-tumor M2 phenotype via the mTOR-TFEB-ATP6V0d2 axis.	Xia et al. 80
Lactate sensing (Gpr132)	Lymphoma (general)	GPR132 antagonists	Preclinical	Blocking the lactate receptor GPR132 on TAMs may prevent their polarization to the immunosuppressive M2 phenotype.	Wan et al. 73
Gluconeogenesis in Tregs (PEPCK)	Lymphoma (general)	PEPCK inhibitors (e.g. 3-mercaptopicolinic acid, 3MP)	Preclinical	Inhibiting PEPCK disrupts lactic acid uptake and oxidation in Tregs, impairing their proliferation and immunosuppressive function, which are resistant to lactate in the TME.	Watson et al. 84
HIF-1α	Lymphoma (general), Hodgkin’s lymphoma (HL)	HIF-1α inhibitors	Preclinical/under clinical evaluation	HIF-1α drives glycolysis, VEGF secretion, M2-TAM polarization, and lymphoma cell migration via the CXCR4/AKT/mTOR axis. Targeting it may disrupt these pro-tumor pathways.	Wan et al. 73 Zhao et al. 88 Nakashima et al. 89 Jin et al. 90
Hexokinase 2 (HK2)	DLBCL, PCNSL	HK2 knockdown/NF-κB pathway inhibitors (e.g. BAY11-7082)	Preclinical	HK2 is overexpressed and critical for glycolysis. Its knockdown inhibits tumor growth in DLBCL. In PCNSL, inhibiting the RelA/p65 (NF-κB)-HK2 axis reduces HK2 levels and curbs tumor growth.	Tateishi et al. 96 Jalali and Ansell 97
Hexokinase domain containing 1 (HKDC1)	Extranodal NK/T-cell lymphoma (ENKTL)	HKDC1 knockdown	Preclinical	HKDC1 promotes ENKTL cell proliferation, stemness, and tumor growth. Ablating HKDC1 inhibits cancer stem cell properties, migration, and invasion.	Chen et al. 99 Liu et al. 100
SMYD3/PKM2 Axis	Diffuse large B-cell lymphoma (DLBCL)	SMYD3 inhibitors	Preclinical	Lysine methyltransferase SMYD3 promotes PKM2 transcription via H3K4me3, facilitating DLBCL cell proliferation and aerobic glycolysis. SMYD3 overexpression correlates with poor prognosis and chemoresistance, making it a potential therapeutic target.	Tian et al. 105
Glycogen synthase kinase 3 (GSK3)	DLBCL	GSK3 inhibitors	Preclinical	GSK3 expression is increased in DLBCL and associated with enhanced cell survival/proliferation. Inhibition of GSK3 can reduce lymphoma cell proliferation.	Jalali and Ansell 97
Serine biosynthetic pathway (SBP)/PHGDH	Germinal center B-cell lymphomas	PHGDH inhibitors	Preclinical	Key SBP enzymes PHGDH and PSAT1 are overexpressed. Pharmacological inhibition of PHGDH effectively suppresses lymphoma cell proliferation, highlighting a promising therapeutic avenue.	Simon-Molas et al. 77
PRDM15 transcriptional network	Lymphoma (general)	PRDM15 targeting	Preclinical	PRDM15 regulates transcription of key genes in the PI3K/AKT/mTOR pathway (InsR, Igf1R) and glycolysis (Pkm, Pfkp). Its deletion downregulates these pathways, affecting tumor cell survival.	Mzoughi et al. 111
Oncogenic HSP90	DLBCL	HSP90 inhibitors	Preclinical	Oncogenic HSP90 supports both glycolysis and mitochondrial respiration in lymphoma cells. Its inhibition reduces glucose uptake, lactate secretion, and impairs mitochondrial respiration in DLBCL cells.	Calvo-Vidal et al. 112
Glucose transporters (GLUT1/3/4)	Lymphoma (general)	GLUT inhibitors (e.g. STF-31, BAY-876)	Preclinical	GLUT1/3/4 are overexpressed in tumors. Inhibitors targeting these transporters aim to reduce glucose uptake, a critical vulnerability of tumor cells.	Stine et al. 81 Yadav et al. 92
GLUT1 in CAR-T Cells	Lymphoma (general)	CAR-T cells overexpressing GLUT1	Preclinical	GLUT1 overexpression enhances metabolic fitness of CAR-T cells in vivo, upregulating both glycolysis and mitochondrial respiration genes, and helps maintain a memory phenotype.	Shi et al. 115
Glycolytic key enzymes (e.g. HK2, LDHA)	Lymphoma (general)	Enzyme inhibitors (e.g. 3-bromopyruvate)	Preclinical	Various inhibitors targeting rate-limiting glycolytic enzymes (Hexokinase, Lactate Dehydrogenase A) have been studied to disrupt the Warburg effect in tumor treatment.	Stine et al. 81
Pentose phosphate pathway (PPP)/G6PD	B-cell acute lymphoblastic leukemia (B-ALL), CLL	Modulation of PPP flux	Preclinical	PPP is crucial for lymphoma cell redox balance. Transcription factors PAX5/IKZF1 negatively regulate the key PPP enzyme G6PD, influencing the metabolic state of tumor cells.	D’Avola et al. 110

Key mechanism: tumors hijack arginine metabolism

Arginine is required for tumor growth. Arginine synthesized intracellularly is largely derived from the urea cycle. Ornithine and citrulline are converted into arginine by the catalytic activities of ornithine transcarbamylase (OTC), argininosuccinate synthetase-1 (ASS-1), and argininosuccinate lyase. Notably, tumor cells significantly increase their consumption of arginine ⁷³ .

Evidence in cancer and lymphoma

In various tumors, the transcription of ASS-1 is suppressed, resulting in the dependence of tumor cells on exogenous arginine ¹¹⁷ . Notably, PTCL exhibits arginine auxotrophy and relies on the arginine transporter SLC3A2 for arginine uptake from the environment to sustain proliferation and escape immune surveillance ¹¹⁹ . Similarly, in lymphoma cells, increased arginase activity results in a significant decrease in plasma arginine levels ¹²⁰ . Among them, elevated level of arginase-1 leads to the decomposition of L-arginine into urea and L-ornithine, as reported in many cancers ⁷³ . This makes lymphoma cells highly dependent on extracellular arginine and arginine transporters to maintain biological functions, such as proliferation, survival, and protein synthesis ¹²⁰ . Furthermore, in PTCL, arginine promotes tumor progression by promoting the synthesis of new RNA and enhancing OXPHOS ¹¹⁹ . In lymphoma, the arginine deprivation-mediated immunosuppressive TME mainly functions through two enzymes: nitric oxide synthase (NOS) and arginase. Both are conducive to the immune escape of cancer cells. Hematopoietic system malignant cells, MDSCs, and TAMs express NOS2 and/or arginase, deprive the TME of arginine, and inhibit T-cell proliferation and cytotoxicity ¹²⁰ . Moreover, arginine metabolism helps maintain the immunosuppressive function of MDSCs ¹²¹ .

Therapeutic relevance and targets

Arginine deprivation therapy could be used for treating related tumors highlighting the potential therapeutic value of arginase inhibitors. Moreover, protein arginine methyltransferases (PRMTs) are associated with tumor stem cell characteristics, and their inhibition suppresses tumor cell proliferation and induces apoptosis ¹¹⁷ . Promisingly, Quinacrine, when used in combination with HDACi, showed synergistic antitumor effects both in vitro and in vivo, providing a new combined strategy for the treatment of PTCL ¹¹⁹ .

Key mechanisms of Gln metabolism

Gln is one of the most abundant AA and participates in various cellular metabolic processes. After entering the cells through AATs, such as ASCT2, it is metabolized into glutamate and ammonium by enzymes, such as glutaminase (GLS) and ultimately converted into lactic acid and ATP^93,117. Gln can also be converted into glutathione to maintain the redox balance within the cells ⁷³ . Tumor cells have a high demand for Gln, and their metabolism is regulated by various oncogenes and tumor suppressor genes, such as c-MYC and P53 ¹²² . MYC could induce the transcription of AATs, such as Asct2 (SLC1A5) and LAT1 (SLC7A5), thereby upregulating the expression of AATs in MYC-expressing B cells and increasing AA uptake ¹²³ . MYC can also upregulate the expression of GLS1, while P53 promotes mitochondrial respiration and TCA activity by upregulating the expression of GLS-2, thereby regulating the redox balance and proliferation of cells ⁹³ . Furthermore, SLC7A5 exchanges Gln and leucine to activate the MTORC1 pathway, which is a crucial regulatory factor for cell growth in hematological malignancies ¹²⁴ .

Evidence in lymphoma and the TME

In the TME, Gln metabolism affects the functions of immune cells, and tumor cells compete with immune cells for Gln uptake. Inhibiting Gln metabolism promotes the differentiation of CD4⁺Th1 cells and CD8⁺ T-cells, and inhibits Th17 cell differentiation. Gln metabolism-related inhibitors can regulate T-cell function and enhance antitumor immunity ¹²⁵ . In Burkitt’s lymphoma (BL), high expression of SLC1A5 and SLC7A5 promotes disease progression, with their expression being dependent on Gln availability. Their upregulation is triggered by the abnormal activation of MYC in BL, thereby promoting cell dependence on Gln for growth and survival ¹²⁰ . In MYC-induced BL cell lines, Gln is metabolized through TCA under hypoxic conditions. Inhibition of this process can effectively suppress tumor progression. In DLBCL, the transcription factor NRF2 (NFE2L2) correlates with advanced clinical stages and IPI scores, driving metabolic reprogramming that heightens reliance on the Gln pathway and susceptibility to GLS inhibition ¹²⁶ . Similarly, in MCL, resistance to ibrutinib is linked to Gln dependence and the necessity of the transporter ASCT2, where elevated GLS expression fuels both proliferation and drug resistance ¹²⁷ . In CLL, Gln uptake underpins resistance to venetoclax (VEN) induced by CD40/BCR stimulation, highlighting AA metabolism as a central pillar of resistance mechanisms across these malignancies ¹²⁸ .

Therapeutic relevance and emerging targets

Targeting the Gln metabolic axis offers a promising strategy to overcome therapeutic resistance and inhibit lymphoma growth. The GLS inhibitors, BPTES and CB-839, can inhibit the proliferation of lymphoma cells, and CB-839 can impair glutathione production ⁹³ . In MCL, the highly specific GLS inhibitor, taregenastat (CB-839), inhibits the growth of MCL cells and simultaneously enhances the efficacy of ibrutinib and venetoclax(VEN) in vitro and in vivo ¹²⁷ . Likewise, in CLL, the Gln transporter inhibitor V9302 mitigates VEN resistance by blocking Gln uptake, effectively re-sensitizing cells to treatment ¹²⁸ .

The central role of Trp in biology

Trp is a fundamental component of protein synthesis and serves as a precursor for many important biological molecules. Its metabolic pathways include the serotonin and kynurenine (Kyn) pathways. These metabolites play significant roles in immune regulation, neurotransmission, and cell growth ¹²⁹ .

Tumors exploit Trp metabolism to evade immunity

Trp can be rapidly internalized by tumor cells through the cell membrane. Most solid tumors express high levels of indoleamine 2,3-dioxygenase (IDO1) and tryptophan 2,3-dioxygenase (TDO2), which are the two main dioxygenases involved in the decomposition of Trp into Kyn. Trp-deficiency syndrome (TDS) is caused by the metabolism and utilization of Trp by tumor cells in the TME ⁷³ . In lymphoma, IDO1 ⁺ tumor cells catalyze the degradation of Trp through IDO1, resulting in the reduction of Trp in the TME and the accumulation of metabolites, such as Kyn. This promotes immune tolerance in tumor cells and protects them from immune attacks ¹²⁰ .

Although some viewpoints suggest that cancer cells compete with T-cells for glucose, resulting in immunosuppression, some studies have found that glucose levels are not universally limited in the TME. Cells in the TME continue to have the ability to increase glucose uptake when Gln uptake is restricted. This indicates that intrinsic cellular programs play a significant role in regulating glucose uptake by immune and cancer cells, rather than being merely a matter of nutritional competition ¹¹⁶ . Table 5 shows the therapeutic strategies targeting AA metabolism in the TME.

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Table 5.

Therapeutic strategies targeting AA metabolism in the TME.

Target/pathway	Lymphoma subtype	Agent/intervention	Stage of research/progress	Key findings	Ref.
Arginine deprivation/ASS-1 deficiency	Peripheral T-cell lymphoma (PTCL) and other ASS-1 deficient tumors	Arginine deprivation therapy; arginase inhibitors	Preclinical/early clinical	PTCL exhibits arginine auxotrophy and relies on the SLC3A2 transporter for uptake. Arginine deprivation therapy and arginase inhibition aim to exploit this metabolic vulnerability.	Ling et al. 117 Ren et al. 119 Liao et al. 120
Protein arginine methyltransferases (PRMTs)	Lymphoma (general)	PRMT inhibitors	Preclinical	PRMTs are associated with tumor stem cell characteristics. Their inhibition suppresses tumor cell proliferation and induces apoptosis.	Ling et al. 117
Glutaminase (GLS)	Mantle cell lymphoma (MCL)	Taregenastat (CB-839)	Preclinical	The GLS inhibitor CB-839 inhibits MCL cell growth and enhances the efficacy of ibrutinib and venetoclax (VEN) in vitro and in vivo.	Li et al. 127
Glutaminase (GLS)	DLBCL and other lymphomas	GLS inhibitors (BPTES, CB-839)	Preclinical	GLS inhibitors (e.g. BPTES, CB-839) can inhibit lymphoma cell proliferation. CB-839 also impairs glutathione production.	Pi et al. 93
Glutamine transporter ASCT2 (SLC1A5)	Mantle cell lymphoma (MCL)	ASCT2 targeting	Preclinical	Resistance to ibrutinib in MCL is linked to glutamine dependence and the necessity of the ASCT2 transporter.1	Li et al. 127
Glutamine transporter	Chronic lymphocytic leukemia (CLL)	V9302	Preclinical	The glutamine transporter inhibitor V9302 mitigates venetoclax (VEN) resistance by blocking Gln uptake, re-sensitizing cells to treatment.	Chen et al. 128
Amino acid metabolism (ASNS, ASS1, SLC1A5, PHGDH)	T-cell acute lymphoblastic leukemia (T-ALL)	Inhibitors of key metabolic genes	Preclinical	Inhibiting key AA metabolic genes (e.g. ASNS, ASS1, SLC1A5, PHGDH) suppresses mTORC1 activity and enhances sensitivity to FGFR1 inhibitors, suggesting a strategy to overcome drug resistance.	Zhang et al. 118
IDO1 (indoleamine 2,3-dioxygenase 1)	Lymphoma (general)	IDO1 inhibitors (e.g. epacadostat, INCB024360)	Clinical trials (phase I/II, largely discontinued)	IDO1+ tumor cells deplete tryptophan and produce kynurenine in the TME, promoting T-cell dysfunction and immune tolerance. Inhibition aims to restore tryptophan levels and block immunosuppressive metabolite production.	Wan et al. 73 Liao et al. 120
TDO2 (tryptophan 2,3-dioxygenase 2)	Lymphoma (general)	TDO2 inhibitors	Preclinical	Similar to IDO1, TDO2 catalyzes the first step of the kynurenine pathway. Targeting TDO2 is proposed as an alternative or complementary strategy to IDO1 inhibition for reversing Trp metabolism-mediated immunosuppression.	Wan et al. 73
Kynurenine receptor (AhR)	Lymphoma (general)	Aryl hydrocarbon receptor (AhR) antagonists	Preclinical	The oncometabolite kynurenine activates the AhR transcription factor in immune cells, directly inducing a regulatory T-cell (Treg) phenotype and suppressing effector T-cell function. Blocking AhR signaling aims to counteract this effect.	(Mechanism implied by Liao et al. 120 , Yan et al. 129 )
Dual IDO1/TDO2 inhibition	Lymphoma (general)	Dual IDO1/TDO2 inhibitors	Preclinical/Early Clinical	Concurrent inhibition of both key Trp-catabolizing enzymes may provide a more comprehensive blockade of the kynurenine pathway, potentially overcoming compensatory mechanisms and single-agent resistance.	(Rationale based on Wan et al. 73 )

Key mechanisms of cholesterol metabolism

Cholesterol is a fundamental component of most cell membranes (including the plasma membrane) and its supply is crucial for cell proliferation. Cells obtain cholesterol either through de novo synthesis or by taking up cholesterol-containing lipoproteins via low-density lipoprotein receptors (LDLRs) ¹³⁷ . In the cholesterol synthesis pathway, 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) and SCAP (sterol regulatory element-binding protein-activated cleavage-activating protein) are the key rate-limiting enzymes ¹³⁰ . Cellular cholesterol metabolism is mainly regulated by two key transcription factors, SREBP2 and liver X receptor (LXR). SREBP2 transcribes genes involved in cholesterol biosynthesis and uptake, thereby increasing cellular cholesterol levels. LXR transcribes genes involved in cholesterol efflux and inhibits cholesterol uptake, thereby reducing cellular cholesterol levels ¹³⁸ . Furthermore, cholesterol modulates membrane fluidity and the formation of lipid rafts via the mevalonate pathway, structures that are vital for tumor cell signal transduction, protein interactions, and immune surveillance ⁹³ .

Evidence in cancer and lymphoma progression

Dysregulated cholesterol metabolism acts as a catalyst for malignancy. HMGCR is upregulated in various cancers. Its overexpression promotes cancer cell growth and migration, while its knockdown inhibits tumor occurrence ¹³⁰ . Cholesterol accumulation in the TME is necessary for triggering T-cell exhaustion ¹³⁹ . High cholesterol levels can disrupt the lipid metabolic network within T-cells, thereby exerting an inhibitory effect on immunity ⁸⁰ . Cholesterol impairs T-cell function by inducing expression of genes associated with T-cell exhaustion, downregulating the T-cell receptor (TCR) pathway and triggering endoplasmic reticulum stress. The increase in cholesterol efflux from macrophages via C1QB induces the upregulation of immune checkpoints (PD-1, LAG-3, and TIM-3) and T-cell exhaustion by simultaneously activating XBP1/ER stress and inhibiting the TCR signaling pathway, thereby suppressing the antitumor activity of T-cells^139,140. The exhaustion of CD8⁺ T-cells caused by immunosuppressive TME is a major obstacle affecting the efficacy of immunotherapy. CD8 T-cell exhaustion has been reported in various hematological malignancies, including AML, ALL, CLL, MM, and lymphoma ¹⁴⁰ . In lymphoma specifically, metabolic dysregulation correlates with progression. In DLBCL, SOX9 promotes cholesterol synthesis by upregulating the expression of DHCR24. Knockdown of SOX9 increases apoptosis, while simultaneously downregulating the expression of the anti-apoptotic proteins Bcl-xL, Mcl-1 and Bcl-2, and upregulating the expression of the pro-apoptotic proteins Bad and Bax. A high-cholesterol environment can inhibit apoptosis, and the inhibition of cholesterol synthesis can induce apoptosis ¹⁴¹ . For anaplastic large cell lymphoma (ALCL), a classic study has demonstrated that squalene metabolism serves as a key regulatory node in tumor progression: ALCL cells exhibit abnormally elevated squalene accumulation via FDFT1 activation, which not only scavenges lipid peroxides to enhance oxidative stress resistance but also suppresses ferroptosis through the GPX4/ACSL4 axis. In addition, squalene metabolites can potentiate STAT3 signaling to facilitate tumor cell proliferation and immune evasion ¹⁴² .

Challenges and unresolved issues in metabolic adaptation

While the interplay between MYC, lipid metabolism, and oxidative stress resistance is increasingly clear, further inquiry is needed to fully elucidate how varying microenvironmental constraints influence these pathways across different lymphoma subtypes. Understanding the precise thresholds at which metabolic inhibition becomes lethal to tumor cells, versus when it might trigger compensatory survival mechanisms, remains an open question crucial for optimizing therapeutic strategies. Table 6 shows the therapeutic strategies targeting lipid metabolism in the TME.

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Table 6.

Therapeutic strategies targeting lipid metabolism in the TME.

Target/pathway	Lymphoma subtype	Agent/intervention	Stage of research/progress	Key findings	Ref.
Fatty acid synthase (FASN)	Diffuse large B-cell lymphoma (DLBCL)	FASN inhibitors	Preclinical	FASN is highly expressed in DLBCL. Inhibition of FASN activity significantly declines tumor growth and increases apoptosis. Targeting the ZDHHC21/FASN axis represents a potential therapeutic strategy.	Liu et al. 133
Fatty acid synthase (FASN) and SREBP	Cutaneous T-cell lymphoma (CTCL)	Combined FASN and SREBP inhibitors	Preclinical	FASN is highly expressed in CTCL and regulates malignant cell proliferation/survival. Its expression is regulated by SREBP1/2. Combined inhibition of FASN and SREBP holds potential for treating CTCL.	Chi et al. 134
Stearoyl-CoA desaturase 1 (SCD1)	Various cancers (potential in lymphoma)	SCD1 inhibitors	Preclinical	Inhibiting SCD1 induces the accumulation of saturated fatty acids and endoplasmic reticulum stress, leading to cancer cell apoptosis and ferroptosis. It is a therapeutic target for various tumors.	Bian et al. 130 Terry and Hay 135
Cholesterol synthesis (HMGCR) and uptake	Acute lymphoblastic leukemia (ALL), chronic lymphocytic leukemia (CLL), lymphoma (general)	Statins (HMGCR inhibitors); SCARB1/LDLR targeting	Preclinical	Statins inhibit cholesterol synthesis, suppress cell proliferation, induce apoptosis, and enhance chemotherapy efficacy in ALL/CLL models. Targeting cholesterol uptake receptors (e.g. SCARB1) also affects lymphoma cell survival.	Pi et al 93 Lee et al. 143
Cholesterol metabolism transcription factors (SREBP2, LXR)	Lymphoma (general)	SREBP2 inhibitors; LXR agonists	Preclinical	Regulating the activity of key cholesterol metabolism transcription factors (SREBP2 for synthesis/uptake, LXR for efflux) affects the survival and proliferation of lymphoma cells.	Yan et al. 138 Lee et al. 143
Squalene metabolism/FDFT1	Anaplastic large-cell lymphoma (ALCL)	FDFT1 inhibitors combined with ferroptosis inducers (e.g. ML162, RSL3)	Preclinical	ALCL cells exhibit elevated squalene accumulation via FDFT1, which scavenges lipid peroxides and suppresses ferroptosis. Combined inhibition of FDFT1 and induction of ferroptosis synergistically suppresses ALCL growth.	Garcia-Bermudez et al. 142
MYC-driven lipid synthesis	Burkitt lymphoma (BL), DLBCL	Inhibitors of fatty acid synthesis or phosphocholine synthesis (e.g. targeting PCYT1A)	Preclinical	MYC induces SREBP1 to drive fatty acid synthesis in BL and activates PCYT1A for phosphocholine synthesis in DLBCL. Inhibition of these lipid synthesis pathways impairs MYC-dependent lymphoma growth.	Stahl et al. 144
Fatty acid oxidation/CPT1	Burkitt lymphoma (BL) and other MYC-driven lymphomas	CPT1 inhibitors	Preclinical	MYC upregulates fatty acid synthesis and enhances fatty acid oxidation (FAO) to meet energy demands. Inhibition of the key FAO enzyme CPT1 exerts cytotoxicity in cancer cells.	Lee et al. 143
PRMT5	Mantle cell lymphoma (MCL)	PRMT5 inhibitors	Preclinical	High PRMT5 expression promotes MCL progression by activating MYC-driven lipid metabolic reprogramming, inducing SREBP1/2 and FASN expression. Inhibition targets this oncogenic axis.	Liang et al. 145
PI3K/AKT pathway	DLBCL, mantle cell lymphoma (MCL)	PI3K/AKT pathway inhibitors	Preclinical/Clinical Trials	Mutations in PI3K or PTEN lead to increased PIP3 levels, hyperactivating AKT and promoting cancer cell survival/proliferation. Targeting this pathway is a key therapeutic strategy.	Lee et al. 143
CAMKIIδ	Diffuse large B-cell lymphoma (DLBCL)	CAMKIIδ inhibitors	Preclinical	High CAMKIIδ expression correlates with poor prognosis in DLBCL. Its absence inhibits lipolysis, leading to insufficient energy supply and suppression of tumor growth.	Zhang et al. 146

Linking TME metabolism and cell therapy – mechanisms, challenges, and future directions

This review systematically elaborates on the reprogramming of glucose, AA, and lipid metabolism within the TME and its profound impact on the function of immune components (e.g. T-cells, macrophages, MDSCs). These metabolic features are not only drivers of tumor progression but also critical determinants of the success or failure of novel cell-based therapies, including chimeric antigen receptor T-cell (CAR-T) therapy. Notably, the TME is classified into hot and cold phenotypes based on immune characteristics, intersecting with metabolic reprogramming to shape therapeutic responses. Hot tumors have a TME rich in tumor-infiltrating lymphocytes (TILs), PD-L1 overexpression, genomic instability, and preexisting antitumor immunity, making them favorable for and responsive to ICIs alone. In contrast, cold tumors exhibit a low inflammatory signature, absent intratumoral CD8⁺ T-cells, a low immunoscore, and no effective endogenous antitumor response, rendering ICIs alone ineffective. Treating cold tumors requires combination therapies to recruit immune cells and convert them into hot tumors for immunotherapy to work ¹⁴⁷ . Integrating TME metabolic mechanisms with cell therapy strategies, on the basis of distinguishing hot and cold TME phenotypes, represents a core approach to overcoming current therapeutic bottlenecks and developing next-generation treatments.

Metabolic reprogramming in the TME creates a nutrient-scarce, metabolically hostile niche that directly impairs the function and persistence of adoptively transferred cells (e.g. CAR-T cells, NK cells) ¹¹⁵ . Tumor cells and stromal components compete fiercely for glucose, Gln, and arginine, leading to nutrient depletion and metabolic exhaustion of therapeutic cells^73,120. For instance, the Warburg effect-driven lactic acid accumulation in the TME not only acidifies the extracellular environment to inhibit T-cell proliferation and cytotoxicity but also polarizes TAMs toward the M2 phenotype, forming a feedforward loop of immunosuppression ⁷³ . Conversely, metabolic reprogramming of TME components also presents actionable targets to enhance cell therapy. For example, inhibiting glycolytic enzymes (HK2, PFKP) or glutaminase (GLS) in tumor cells can alleviate metabolic competition, improving the metabolic fitness of therapeutic cells^97,108,127. Targeting cholesterol metabolism—such as suppressing squalene accumulation in ALCL or using statins to disrupt lipid raft formation—can reverse T-cell exhaustion and enhance CAR-T cell infiltration^138,142.

The immune landscape of the TME is a key determinant of cell therapy success. TAMs, MDSCs, and CAFs collectively create an immunosuppressive barrier that attenuates the activity of therapeutic cells. M2-polarized TAMs express PD-L1, IDO, and IL-4I1, which directly inhibit T-cell function or induce T-cell exhaustion through ligand-receptor interactions (e.g. PD-L1/PD-1) and metabolic remodeling (e.g. Trp catabolism)^7,73. MDSCs further reinforce immunosuppression by secreting ARG1 and iNOS^41,120. These interactions contribute significantly to cell therapy resistance. In R/R DLBCL, MDSCs induce M2 macrophage polarization and inhibit NK cell maturation, reducing the efficacy of CAR-T therapy^48,49. However, targeting these immune components can sensitize lymphoid malignancies to cell therapy. For example, combining CAR-T cells with CSF1R inhibitors (to deplete M2 TAMs) or JAK inhibitors (to reduce MDSC abundance) has shown synergistic antitumor effects in preclinical models^11,53. Similarly, anti-CD47 antibodies enhance the phagocytic activity of TAMs, promoting the clearance of lymphoma cells and improving the persistence of therapeutic cells^5,14.

Beyond conventional CAR-T, emerging cell therapies are actively exploring the proactive utilization of metabolic pathways. M2-type TAMs are a major immunosuppressive and metabolically competitive component in the TME. Engineering CAR-M (macrophages) to skew toward a pro-inflammatory M1 phenotype, or concurrently knocking out immunosuppressive metabolic enzymes (e.g. ARG1), holds promise for transforming them from “accomplices” into “allies,” directly reshaping the metabolic and immune landscape of the TME. Future CAR designs may incorporate sensor modules responsive to specific TME metabolites (e.g. high potassium, low glucose, high lactate). This would allow for precise regulation or enhancement of CAR-T cell activation or function within the immunosuppressive metabolic milieu, enabling a more intelligent and adaptive response.

Despite the promising outlook, this field faces multiple challenges, which are further complicated by the heterogeneity of hot and cold TME phenotypes: metabolic dependencies may vary significantly across different lymphoma subtypes and even within the same tumor, and the metabolic characteristics of hot and cold TMEs add an additional layer of complexity to this heterogeneity. Tumor cells possess metabolic plasticity, potentially rapidly activating alternative pathways when one pathway is blocked, leading to the failure of single-target metabolic strategies. The metabolic state of the TME is dynamic, changing with disease progression, post-treatment, and across different anatomical sites. Determining the optimal timing and sequence for combining metabolic interventions with cell therapy requires further in-depth exploration. Metabolic modulators, while inhibiting tumor and immunosuppressive cells, may also have unforeseen negative effects on the CAR-T cells themselves.