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Insights into the tumor microenvironment of B cell lymphoma

Abstract

The standard therapies in lymphoma have predominantly focused on targeting tumor cells with less of a focus on the tumor microenvironment (TME), which plays a critical role in favoring tumor growth and survival. Such an approach may result in increasingly refractory disease with progressively reduced responses to subsequent treatments. To overcome this hurdle, targeting the TME has emerged as a new therapeutic strategy. The TME consists of T and B lymphocytes, tumor-associated macrophages (TAMs), myeloid-derived suppressor cells (MDSCs), cancer-associated fibroblasts (CAFs), and other components. Understanding the TME can lead to a comprehensive approach to managing lymphoma, resulting in therapeutic strategies that target not only cancer cells, but also the supportive environment and thereby ultimately improve survival of lymphoma patients. Here, we review the normal function of different components of the TME, the impact of their aberrant behavior in B cell lymphoma and the current TME-direct therapeutic avenues.

Introduction

The last two decades have seen numerous discoveries which have helped understand the biology of B cell lymphoma and lay the foundation for precision therapies. B cell lymphomas arise from the germinal center (GC), a dynamic structure that forms upon encounter of naïve B cells with a putative antigen [1], and may be secondary to i) genetic/epigenetic alterations in the GC B cells or ii) aberrant response of immune components of the microenvironment ultimately leading to lymphomagenesis [2]. Gene expression profiling (GEP) studies have divided diffuse large B cell lymphoma (DLBCL) - the most common B cell lymphoma - into two main subgroups based on the cell of origin (COO): the activated B cell (ABC) and the germinal center B cell (GCB) subtypes [3]. More recently, two additional molecular classifications have used whole exome sequencing (WES) and structural genomic abnormalities to further subdivide DLBCL into several genetically defined subgroups [4, 5]. An additional layer of complexity includes the immune cells that infiltrate the tumor. A landmark study performed on tumor biopsies from 95 untreated patients with follicular lymphoma (FL) - the second most frequent B cell lymphoma - demonstrated significant enrichment of genes associated with macrophages in patients with unfavorable outcomes whereas the expression signature was enriched for genes linked to T-cells in those with a favorable outcome [6]. Additionally, we reported the prognostic value of memory CD4+ T-cells, which play a critical role in immune surveillance, and designed a prognostic risk model (BioFLIPI) to improve the identification of high-risk patients [7]. Similarly, the prognostic relevance of TME in DLBCL has been uncovered in two recent studies which have further deconvoluted the TME in several ecosystems [8, 9]. Part of the reason for an unfavorable TME may be linked to the mutation of genes directly or indirectly involved in the control of antigen presentation, including CREBBP [10], EP300 [11], EZH2 [12], and others [13]. However, many additional mechanisms may come into play to shape the immune response against tumors [14]. Here, we dissect the function of different immune components of the TME (Table 1), the impact of their aberrant expression in B cell lymphoma and novel therapeutic avenues (Tables 2 and 3).

Table 1 Role and markers of the immune cells of the TME
Table 2 Clinical trials including agents targeting the immune cells of the TME in B cell lymphomas
Table 3 FDA-approved agents targeting the immune cells of the TME in B cell lymphomas

T follicular helper cells

T follicular helper (Tfh) cells commonly reside inside the lymph nodes, tonsils, and spleen. They are defined by the expression of cell surface markers CD4, CXCR5, PD1, and ICOS, their master regulator being B cell lymphoma (BCL) 6 [15]. Tfh cells play a critical role in the formation and maintenance of GCs. Also, Tfh cells engage GC B cells to promote clonal selection and affinity maturation so that high-affinity B cells can be selected to exit the GC reaction and undergo terminal differentiation towards plasma cells or memory cells [15]. This mechanism is mediated through interaction between the co-stimulatory molecule CD40-ligand on the Tfh cells with CD40 on the B cells (Fig. 1) [15]. On the contrary, T follicular regulatory (Tfr) cells limit the output of the GC reaction counterbalancing Tfh function [1]. Of note, Tfh cells can convert to Tfr cells through FOXP3 activation in the late germinal center [16]. Several studies have shown an increased expression of Tfh CD4+PD1+ICOS+ cells [17] and/or CD4+CXCR5+Foxp3- [18] cells in diagnostic samples of malignant lymphoid disease compared to healthy controls. The same expression decreased or returned to normal at the end of effective treatment, but it increased in progressive disease [17]. It is possible that Tfh cells may contribute to lymphoma B cell survival via production of sCD40L which activates NF-kB pathway and in turn up-regulates c-FLIP and Bcl-xL [19, 20]. Increased expression of lymphoma-infiltrating Tfh cells was associated with high levels of IL-6, IL-21 [21], IL-4 [22], and CXCL13 [9] (Fig. 1). Conversely blocking these cytokines resulted in reduced infiltration of Tfh cells [21]. Additionally, the crosstalk between lymphoma B cells and Tfh cells increases the release of CCL17 and CCL22, which induces the preferential migration of regulatory T cells (Treg) and IL-4 producing CD4+ T cells, stimulating more chemokine release thus creating an immune suppressive TME that promotes tumor survival and growth [23, 24]. Another study divided Tfh cells into Tfr-like subsets (CD4+CD25+CXCR5+) and Tfh CD25- subset (CD4+CD25-CXCR5+) [25]. The difference between these two groups was associated with the higher expression of Blimp1, Foxp3, IL-10, TGF-β, and lower levels of IL-21 in Tfr-like CD25+ cells compared to Tfh CD25- cells [25]. This discovery is intriguing as it demonstrates the plasticity of the immune response and implies the possibility to leverage this characteristic as a therapeutic tool. Novel insights on the role of Tfh cells in immune evasion can usher in the opportunity for unexplored therapeutic targets [26]. In particular, identification of genetic mutations, cell markers and cytokine/chemokine signaling that impact Tfh cell function will help in improving our knowledge of the causative events that induce and/or sustain tumor development and growth. Thus, targeting these regulators may be a new approach to interrupting T cell support of lymphoma cells, which may complement other therapeutic approaches.

Fig. 1
figure 1

Role of T follicular helper (Tfh) cells in the normal germinal center and in lymphomagenesis

T regulatory cells

Treg cells are CD4+ T cells expressing high CD25 (IL-2Rα) and FoxP3, and low or not CD127 (IL-7R α) [27, 28]. They suppress immune response activation and promote tolerance towards self-antigens to prevent autoimmunity [29]. However, their function can also suppress tumor immunity leading to immune escape [30]. Nevertheless, the significance of tumor-infiltrating Treg cells remains elusive due to their heterogeneity and their expression of both co-inhibitory and co-stimulatory receptors [31]. Specifically, some studies have shown that Treg FOXP3+ cells display a tumor-protective effect [32, 33] in FL [34] and DLBCL [34, 35] by suppressing T-cell proliferation and IFN-γ production [31, 36], while others found that Treg cells co-expressing activating markers such as CTLA4 [37] and TIGIT [38] result in an enhanced suppressive property and are associated with poor prognosis [39]. It is possible that the prognostic impact of Treg cells is dependent on disease context, however more clarity is still needed. Therefore, in-depth phenotypic and functional characterization of Treg cells is mandatory to identify novel targets for therapy and in turn improve patient survival. These data suggest that targeting Treg cells could be beneficial due to their antitumor immunity, however, it might also lead to unwanted immune-mediated toxicities.

In the last decade several immunomodulatory drugs (IMiDs) (e.g. lenalidomide) and targeting agents against B cell receptor (BCR) or intracellular kinases (e.g. BTK inhibitors and PI3K inhibitors) have been approved for hematologic malignancies [40]. Beside the tumor-specific effect, these molecules can also impact the immune components of the microenvironment (Fig. 2). For example, lenalidomide modulates Treg cells decreasing their suppressive function [41,42,43] and results in an enhanced anti-lymphoma activity. Similarly, PI3K inhibitors decrease the suppressive effect of Treg cells while enhancing CD8 T cell function [44,45,46]. The most recent therapeutic strategies targeting T cells include inhibition of checkpoint molecules such as PD1/PD-L1 and CTLA4 [47] or adoptive transfer of genetically engineered T cells [48]. Additional recently discovered immune checkpoint molecules that represent emerging targets for therapy are TIM3, LAG3 and TIGIT [49]. Blocking the negative T cell regulator CTLA4 reactivates immune response against the tumor in immunogenic cancers [50]. CTLA4 inhibition decreased Treg cells also in B cell lymphoma with a positive association of CD45RA-Treg ratio in responders vs non responders, however the antitumoral effects were quite modest [51]. PD1/PD-L1 inhibition prevents T cell exhaustion [52] and blocks the suppressive Treg activity [53]. Interestingly, inhibition of one checkpoint leads to compensatory increase of others. For example, blocking PD1 results in increase of LAG3 and CTLA4 [54]. On the contrary, combined inhibition of PD1 and LAG3 increased CD8 T cell cytotoxicity and decreased Treg cells [55]. Nevertheless, combination of two checkpoint blockades has shown modest activity in relapsed/refractory (R/R) B cell lymphoma [51, 56]. Similar to LAG3, TIM3 results in negative regulation of T cell response, ultimately leading to T cell exhaustion [57, 58], while its inhibition reduces tumor growth especially in combination with PD-1 blockade, but again the overall anti-tumor effect is modest [59]. TIGIT is also a negative regulator of T cells that can prevent immune response against tumor [60, 61]. As such it has attracted scientific attention as a novel target for therapy [62] and its use is under experimental evaluation. Given the tremendous potential of immune therapy, optimal methods to modulate Treg cells are needed in the future to achieve a balance between antitumor immunity and autoimmunity.

Fig. 2
figure 2

Drugs targeting T regulatory (Treg) cells

Effector CD8+ T cells

Naïve CD8+ T cells differentiate into cytotoxic effector CD8+ T cells when encountering a cognate antigen [63]. Once the antigen has been eliminated, they undergo apoptosis or differentiate into memory T cells [64]. However, CD8+ T cells may become exhausted in the face of persistent antigen stimulation in infections or autoimmunity [65]. In addition, during tumorigenesis cancer cells secrete inhibitory factors to generate an immune suppressive tumor environment, thus, despite their important role in eliminating tumor cells, CD8+ cytotoxic T cells often become exhausted and eventually fail to control tumor development and progression [65]. Anergic or exhausted CD8+ T cells are defined as CD8+ CD28- CD57+ T cells with a reduced proliferation and cytotoxic effect (loss of IL-2, TNF-α, and IFN-γ production) [66]. Differential expression level of CD5 distinguishes different T cell activation and effector function, as CD5high CD8+ T cells are more active and abundant in the TME compared to CD5low CD8+ T cells. Since CD5 expression inversely correlates with PD1 expression, targeting CD5 may increase PD1 levels, which in turn would maximize the effect of anti-PD1 checkpoint blockade [67]. CD8+ T cells are also characterized by a sustained expression of inhibitory receptors such as PD1, CTLA4, and LAG3 [68]. Several studies have shown a favorable correlation between increased numbers of effector CD8+ T cells and good outcomes in FL [69, 70]. Specifically, increase of PD1+ CD8+ T cells associated with a favorable outcome in FL patients, while reduction of the same was observed in transformation [71]. By contrast, expression of LAG3 defines a subset of PD1+ CD8+ T cells which correlates with poor outcome in FL [72]. In line with these data, inhibition of LAG3 increases the proliferation and effector function of CD8+ T cells [73], suggesting that these immune checkpoint inhibitors can potentially augment antitumor immunity. Currently, there are several clinical trials investigating the efficacy of anti-LAG3 inhibitors alone or in combination with other immunotherapy in hematologic malignancies (NCT04566978, NCT05039658, NCT02061761, NCT05255601).

Tumor-associated macrophages

Tumor-associated macrophages (TAMs) are one of the most critical immunosuppressive cell populations. TAMs suppress antitumor immunity and promote tumor progression by inhibiting the recruitment and activation of T cells via secreting cytokines, chemokines, and growth factors [74]. TAMs also serve as prominent metastasis promoters in the TME [75]. TAMs are classified into M1 and M2 phenotypes. In general, M1 macrophages are cytotoxic via secreting proinflammatory cytokines (e.g., IL-12, tumor necrosis factor-α, CXCL-10) and are considered anti-tumorigenic, while M2 macrophages are pro-tumorigenic via secreting anti-inflammatory cytokines (e.g., IL-10, IL-13, IL-4, matrix metalloproteinases) [75] (Fig. 3). A study by Taskinen et al. showed that high expression of CD68+ (M1 marker) TAMs was associated with adverse outcome in chemotherapy-treated FL patients (P = 0.026), but those patients had a favorable prognosis (progression free survival [PFS] was not reached, p = 0.006) and overall survival (p = 0.006) compared to the control group [76]. However, an increased number of TAMs, particularly CD68+ macrophages, was correlated with an increased likelihood of relapse after autologous hematopoietic stem-cell transplantation (P = 0.008) and shortened PFS (p = 0.03) in patients with classic Hodgkin’s lymphoma (HL) [77]. Along the same lines, elevated numbers of infiltrating CD163+ M2 macrophages were associated with increased angiogenic sprouting and poor prognosis in FL [78] and DLBCL [79]. Therefore, TAMs may exert either antitumor or protumor functions in different tumor types [80].

Fig. 3
figure 3

Macrophage polarization and specific cytokines release of M1 and M2 macrophages

Many clinical approaches targeting TAMs are still under investigation. Targeting the colony-stimulating factor-1 receptor (CSF1R) signaling pathway, which is essential for the recruitment, differentiation, and survival of TAMs, leads to their decrease in number and in immunosuppressive functions [81]. Targeting CSF1R caused abrogation of CD163+ TAMs in mantle cell lymphoma (MCL), irrespective of the sensitivity to BTK inhibitors [82]. PLX3397 (pexidartinib), a CSF1R inhibitor, significantly reduced the viability of M2 macrophages, but it did not affect M1 macrophages in FL [83]. Also, inhibition of CSF1-CSF1R axis improved the efficacy of other immunotherapies, such as PD-1 or CTLA-4 blockades [84]. Another promising target is CD47 which is overexpressed in several B cell lymphomas, including DLBCL, FL and MCL [85]. The interaction between CD47 and SIRPα prevents cancer cells from being phagocytosed by macrophages and dendritic cells [86]. Chao et al. reported that anti-CD47 antibody reduced lymphoma burden, and the combination with rituximab had a synergist effect on promoting phagocytosis of lymphoma cells [85]. Notably, anti-CD47 antibodies robustly inhibited the dissemination of disease to secondary sites [87]. This correlated with a benefit in prognosis as extranodal lymphomas generally associate with a reduced response to therapy and a worse prognosis. CCL2/CCR2 is another essential signaling axis implicated in activating and mobilizing TAMs from the bone marrow to the site of inflammation in the TME [88]. Targeting CCL2-CCR2 might be a feasible immune intervention for lymphoma treatment. A study showed that CREBBP/EP300 mutation in DLBCL patients had higher CCL2 expression, and tumor progression was induced by TAMs throughout the FBXW7-NOTCH-CCL2/CSF1 axis [88]. Accordingly, CCR2 antagonist decreased tumor growth and dissemination of DLBCL cells, and increased survival in xenograft models [89]. Another study showed that the combination of CCR2 and immune checkpoint inhibitors reduces tumor growth in cutaneous T-cell lymphomas [90]. Lastly, microRNAs (miRNA) are secreted from tumor cells and could induce the recruitment and reprogramming of TAMs [91]. Recent studies have shown that overexpression of specific miRNAs (e.g., miR-33, miR-130, and miR-155) decreases tumor progression by shifting TAM from M2 to M1 phenotype [92, 93].

Myeloid-derived suppressor cells

Myeloid-derived suppressor cells (MDSCs) are a heterogeneous group of immature myeloid cells (IMC) which is pathologically activated in many conditions, including autoimmunity, infectious diseases, obesity, and pregnancy [94]. In physiological conditions, IMCs differentiate into mature monocytes, dendritic cells, and granulocytes, however the differentiation and maturation of IMCs are blocked in a pathological environment, which leads to the expansion of MDSCs (Fig. 4) [95]. MDSCs are further divided into two major subsets: polymorphonuclear (PMN)-MDSCs and monocytic (M)-MDSCs. They can be differentiated from their normal counterparts by high arginase-1 (Arg-1) and nitric oxide synthase-2 (NOS-2) expression, and high and persistent level of reactive oxygen species (ROS) [94]. Also, PMN-MDSCs can be distinguished from neutrophils by their unique genomic profile [94], while M-MDSCs are different from TAMs based on their phenotype characterized by increased expression of F4/80 and M-CSF receptor, low expression of IRF8, low to intermediate expression of Ly6C and low or undetectable expression of S100A9 protein [94, 96]. MDSCs were shown to be higher at the time of diagnosis in Hodgkin and Non-Hodgkin lymphoma patients, especially in those with aggressive disease, compared to healthy control [97, 98]. Upregulated expression of MDSCs-related genes (e.g. ARG1, S100A12, and S100A8) was associated with inferior event-free survival compared to patients with low expression of these genes [99, 100]. Endoplasmic reticulum stress is the main regulator of the activation and suppressive function of MDSCs by promoting the expression of Arg-1 and NOS-2 [95]. Also, exosomes released by cancer cells accelerate the activation, expansion, and immunosuppression of MDSCs by transporting functional substances, such as miRNA, TGF- β, and PGE2 [95, 101].

Fig. 4
figure 4

Myeloid differentiation in physiologic and pathologic conditions

Promising therapeutic strategies are reducing MDSCs accumulation in the TME as well as inducing functional repolarization of these cells. However, a complete deletion of myeloid cells would not be feasible as it may cause severe adverse effects, such as bacterial infections. An example of such a strategy is phosphodiesterase-5 inhibitors (e.g. sildenafil) which reduce the immunosuppressive effect of MDSCs and enhance intratumoral T cell infiltration and activation through downregulation of Arg-1 and NOS-2 [102]. Antagomir, an antagonist of miR-30, showed to reduce MDSCs in B-cell lymphoma [103]. Histamine dihydrochloride (HDC) with IL-2 reduced MDSCs, but this anti-tumor mechanism is insufficiently understood [104]. The PI3Kδ/γ inhibitor RP6530 led to a significant inhibition of MDSCs and repolarized TAMs from M2 to M1-like phenotype in Hodgkin lymphoma (HL) in vitro and in vivo [105]. In the future, targeting MDSCs may be a crucial point to improve the efficacy of CAR-T cell therapy since it has been shown that MDSCs could inhibit CAR-T cell activation [106, 107].

Cancer-associated fibroblasts

Fibroblasts are resting mesenchymal cells in the connective tissue, which become activated during wound healing by growth factors, such as TGF-β, platelet derived growth factor (PDGF) and IL-6 [108]. Once activated, fibroblasts generate cytokines and chemokines, recruit immune cells, and synthesize an extracellular matrix (ECM). However, normal activated fibroblasts are different from cancer-associated fibroblasts (CAFs). CAFs exhibit enhanced migratory capacity, autocrine growth factor-induced signaling and increased levels of secretory molecules that enhance tumorigenesis (Fig. 5) [108]. This process might be a consequence of epigenetic changes promoting CAFs activation. Among the different molecular regulators released by CAFs, the CAF-derived stromal cell-derived factor 1 promotes tumor growth by inducing angiogenesis via the recruitment of endothelial progenitor cells into tumors [109]. CAFs also produce abundant VEGF, PDGFC, FGF2, osteopontin and secreted frizzled-related protein 2 to exacerbate the angiogenesis of neoplastic tissues [110]. Heat shock factor 1 (HSF1) may cause HSF1-driven pro-tumorigenic program in cancer cells [111]. Yes-associated protein 1 enhances stiffening of ECM, angiogenesis, and cancer cell invasion [112]. In general, CAFs promote an immune suppressive TME. The cytokines or chemokines secreted by CAFs may have direct or indirect implications for tumor immunity [110]. It is uncertain if CAFs are associated with immunosuppressive populations of B cells due to poorly defined markers for such cells [113]. Production of IL-4, IL-6, and IL-8 may induce immunosuppressive myeloid cell differentiation, while CXCL14 affects macrophages recruitment to the tumor. Additionally, CAFs modulate immunity through their acquisition of adhesion molecules (e.g., ICAM1), which serve as a docking platform for the immune cells [114].

Fig. 5
figure 5

Functions of cancer-associated fibroblasts (CAFs)

Lymphoma B cells can trigger mesenchymal stem cells (MSCs) differentiation into fibroblast reticular cells. Pandey et al. reported that stromal cells of FL-infiltrating lymph nodes and bone marrow overexpressed CXCL12, while IL-4-high FL-Tfh cells triggered CXCL12 upregulation [115], which further promotes FL B cell activation, migration and adhesion [115]. IL-8 promotes neutrophil survival, causing activation of stromal cells and promotion of malignant B-cell survival [116]. CCL2 is overexpressed by MSCs from FL bone marrow in comparison with those from healthy age-matched donors (HD-MSCs), and it is up-regulated in HD-MSCs after coculture with malignant B cells [117]. DLBCL stromal-1 gene signature is enriched in CAFs and its expression is inversely associated with DLBCL tumor stage. Thus, CAFs are hypothesized to aid in trapping malignant B cells in the lymph node preventing their spread to new anatomical locations. Among all the gene regulators, TGF-β is the main upstream regulator of the DLBCL stromal-1 gene signature [118]. TGF-β has been shown to cause apoptosis in mouse models of B cell lymphoma [119]. Although TGF-β could promote an immunosuppressive environment, it is also a potent negative regulator of B-cell survival, proliferation, activation, and differentiation [120].

Targeting CAFs could be a challenging task due to the lack of specific cell surface markers causing difficulty to precisely target CAFs without damaging the normal tissue. However, there are a few general approaches targeting CAFs: 1) targeting the chemokine and growth factor pathways to inhibit the activation of CAFs, 2) normalization of CAFs via all-transretinoic acid or calcipotriol, 3) depletion of CAFs by transgenic technologies or immunotherapies, 4) targeting CAF-derived ECM proteins and associated signaling to induce stromal depletion, 5) cellular therapies (such as oncolytic adenoviruses, TNF-related apoptosis-inducing ligand or type I interferon) [110].

Tumor-infiltrating natural killer cells

Natural killer (NK) cells are innate cytotoxic lymphocytes of the immune system, contributing to the prevention of infection and tumor growth [121]. NK cells can be divided into two subtypes: CD56dim CD16+ NK cells (a mature cytotoxic population) and CD56bright CD16- NK cells (an immature and mostly immunomodulatory population) [121]. For both populations the most important cell surface inhibitory receptors are i) the members’ killer cell immunoglobulin-like receptor (KIR) family and ii) the CD94/NKG2A heterodimer [122, 123]. In physiologic conditions, normal cells are spared by the NK cells due to the recognition of MHC Class I engaged with KIRs. By contrast, lack of “self-recognition” signals to the NK cells to attack abnormal cells, such as tumor cells which present downregulated antigen presentation molecules as immune evasion strategy (Fig. 6) [124].

Fig. 6
figure 6

Role of natural killer (NK) cells in physiologic and pathologic conditions

The role of NK cells in tumor immunosurveillance is well established [125, 126]. Importantly, NK cells seem to prevent development of tumors including B cell lymphoma [127, 128]. Recent evidence has shown that tumor infiltrating NK cells unleashed cytotoxic T cells, ultimately resulting in tumor eradication [129]. In line with the role of NK cells in suppressing malignancies, several studies have demonstrated a survival advantage of tumor infiltration by NK cells [129,130,131,132,133]. Even though a direct correlation may be less clear due to the frequent co-expression of T cells, these studies support a critical role of NK cells in promoting antitumor immune response. Tumor immune escape includes mechanisms that prevent NK cell activation or recruitment. For examples, suppressive cytokines (e.g. TGF- β) [134, 135] and prostaglandin [136, 137] clearly suppress NK cell activation. TGF- β also induces differentiation of Treg cells, which in turn suppress NK cells [138, 139]. Additional escape mechanisms include engagement of inhibitory receptors. Besides expressing NK-cell inhibitory receptors, NK cells also express other immune checkpoint molecules (e.g., PD1, TIM3, TIGIT, SIRP α) [140,141,142,143,144]. For example, increased expression of PD1 on NK cells was observed in several tumors [145,146,147,148], including HL and DLBCL [148]. By contrast, the inhibitory ligand PDL1 was found on tumor cells and macrophages, thus favoring the PD1/PDL1 interaction which limits the anti-tumor effect of NK cells. Recent studies have shown that PD1 blockades disrupt the suppressive PD1/PDL1 axis, reactivating NK cells with clinical implication [148]. Blockade of other immune checkpoint molecules has also shown encouraging potential for NK cell-based immunotherapy [124]. TIGIT was associated with NK cell exhaustion. On the contrary, TIGIT blockade antibodies restored anti-tumor activity [149]. Monalizumab, a humanized antibody against NKG2A, unleashes NK and T cells, thus promoting an enhanced tumor immunity [150]. STING agonists, such as cyclic dinucleotides, enhance NK cell fitness and anti-tumor effect [130, 151]. Another approach to amplify NK cell function against tumor is using “NK cell engagers”: bi- or tri-specific antibodies that bind NK and tumor cells [152, 153]. Furthermore, FDA has recently approved the first NK cell-based immunotherapy, NK-92, for clinical testing [154, 155]. Of note, NK cells provide a safer chimeric antigen receptor (CAR)-engineering platform compared to T cells [156]. Additionally, since they lack most of the KIRs, CAR-NK cells are less likely to become exhausted [157]. Several ongoing efforts have attempted to further potentiate and prolong NK-CAR potency by combining checkpoint inhibitor, cytokines and co-stimulatory signaling [157]. However, this promising off-the-shelf approach needs additional improvements to maximize its therapeutic efficacy.

Innate lymphoid cells

Innate lymphoid cells (ILCs) belong to the adaptive immune system and have a similar phenotype and function of T cells but differ from them for the lack of antigen receptors and clonal selection and expansion after stimulation [158]. ILCs are relatively rare (≤ 1% lymphocytes in mucosal tissues) [159] and can be distinguished in three main subsets: 1) type 1 ILCs include ILC1s and conventional NK cells [160, 161], express Tbx21, produce IFN-γ, and contribute to anti-viral and Th1 immunity [162]; 2) type 2 ILCs express Gata3, ROR α, TCF1 and Notch [163, 164], produce Th2 cell-associated cytokines (IL-4, IL-5, IL-9 and IL-13), and contribute to respond to Helminths infections and allergic diseases [165]; 3) type 3 ILCs express ROR γ t, present a different expression of T-bet [161, 166,167,168], produce IL-17A and IL-22, and participate in the homeostasis and mucosal defense and preservation of memory CD4 T cells [164, 169]. Notably, ILCs have a remarkable plasticity that allows them to acquire features of another ILCs subtype as required by changes in the TME. For examples, NK cells can switch to ILC1-like cells upon increase of TGF- β [135]. The existence of a continuous conversion from NK cells to ILC1s and vice versa is also plausible [170, 171]. Similarly, IL-12 has been shown to induce differentiation of ILC2s into ILC1 [172, 173] and ILC3s into ILC1s [173, 174]. ILCs also regulate tumor surveillance through a dynamic crosstalk with different immune components of the TME. Among ILCs, NK cells are the most active population as previously described. ILC2s can suppress immune response against tumor through IL-13-mediated enhancement of MDSCs expansion [174], alternatively they favor anti-tumor immunity through IL-5-mediated cooperation with DCs [175, 176]. ILC2s may potentiate the suppressive function of Treg through release of the growth factor AREG [177], or limit T cell activation through production of Arg1 [178]. ILC3s favor chronic inflammation, which in turn may promote tumor initiation [179, 180]. A group of ILC3s produce IL-17 and IL-22 [181, 182], which have been associated with poor prognosis in cancer patients [183, 184]. Collectively, these studies support the interplay between ILCs and the immune cells of the TME, which influence both innate and adaptive immune response against tumor. Future studies may be directed to investigating strategy blocking ILCs-myeloid or ILCs-Treg axes as a promising therapeutic strategy.

Lymphomas of the immune-privileged sites

The lymphomas of the immune-privileged sites include those arising from the central nervous system (PCNSL) and testes (PTL) [185]. Unlike other lymphomas, PCNSL and PTL are invisible to the immune system and have a suppression of anti-tumor T-cell response. Typically, they are localized diseases at presentation, even though they may be disseminated within the compartment (CNS-CNS, testis-testis) and between the compartments (CNS to testis) but rarely systemically, and have a poor prognosis [186, 187]. Constitutive activation of NF-kB via BCR (e.g. CD79B mutation) and toll-like receptor (e.g. MYD88 L265P mutation) is the canonical oncogenic pathway [188,189,190]. They share genetic features with classical ABC-DLBCL as well as with the recently defined molecular clusters MCD and C5 [4, 5]. However, the precise relationship between these classes remains to be elucidated. They present a high prevalence of genetic mutations causing loss of MHC class I and II expression [189, 191, 192]. Additionally, structural alterations at 9p24.1, which is the PD-L1 and PD-L2 locus, increase the abundance of transcriptional and translational expression of PD-L1 and PD-L2, further reinforcing immune evasion [189]. The predominant immune components of TME in these diseases are CD8+ cytotoxic T cells with a direct correlation between their number and outcome. Macrophages are also frequently identified, being an increased M1/M2 ratio associated with a better survival. Of note, PD1 and TIM3 appear to be concomitantly upregulated in CD8+ cytotoxic T cells and M2 macrophages with prognostic implications [193, 194]. However, further investigation is required to uncover the immune landscape of these diseases. The specific features of the lymphomas of the immune-privileged sites impact on treatment option. Especially, NF-kB/BTK inhibition has shown promise, with ibrutinib-based therapy being at the forefront of clinical investigation [195,196,197]. Additionally, checkpoint inhibition (e.g. nivolumab/pembrolizumab) has had an emerging role in the therapeutic armory [198].

Conclusion

The crosstalk between malignant B cells and immune cells in the lymphoma TME is highly complicated and might be affected by often interconnected intrinsic and/or extrinsic mechanisms which ultimately can lead to immune escape. This notion suggests the need to adopt a more comprehensive therapeutic strategy that does not limit its focus to tumor cells but that considers a global approach including the TME. Targeting the TME has long been considered a promising strategy, but much more work is needed to identify novel prognostic and predictive targets. Stratification of the patients for precision medicine as well as monitoring of immune response remain unmet clinical needs. Several advancements have been made towards this direction, such as the recent development of liquid biopsy that monitors circulating tumor DNA and immune components [199] or immune-imaging tools [200,201,202] to assess the efficacy of immunotherapy. The horizon of B cell lymphoma allows for a glimpse of a therapeutic strategy that considers the tumor in its whole, and maybe such an approach might be able to overcome the current clinical hurdles and rescue the still high therapeutic failures.

Availability of data and materials

Not applicable.

Abbreviations

GC:

Germinal center

GEP:

Gene expression profiling

DLBCL:

Diffuse large B cell lymphoma

COO:

Cell of origin

ABC:

Activated B cell

GCB:

Germinal center B cell

WES:

Whole exome sequencing

FL:

Follicular lymphoma

Tfh:

T follicular helper

BCL6:

B cell lymphoma 6

Tfr:

T follicular regulatory

IMiDs:

Immunomodulatory drugs

TAMs:

Tumor-associated macrophages

PFS:

Progression free survival

CSF1R:

Colony-stimulating factor-1 receptor

miRNA:

microRNAs

MDSCs:

Myeloid-derived suppressor cells

IMC:

Immature myeloid cells

PMN:

Polymorphonuclear

Arg-1:

Arginase-1

NOS-2:

Nitric oxide synthase-2

PDGF:

Platelet derived growth factor

ECM:

Extracellular matrix

CAFs:

Cancer-associated fibroblasts

HSF1:

Heat shock factor 1

HD-MSCs:

Healthy age-matched donors

HL:

Hodgkin lymphoma

NK:

Natural killer

CAR:

Chimeric antigen receptor

ILC:

Innate lymphoid cells

PCNSL:

Primary central nervous system lymphoma

PTL:

Primary testis lymphoma

BCR:

B cell receptor

References

  1. Mesin L, Ersching J, Victora GD. Germinal center B cell dynamics. Immunity. 2016;45:471–82 http://www.ncbi.nlm.nih.gov/pubmed/27653600.

    Article  CAS  Google Scholar 

  2. Basso K, Dalla-Favera R. Germinal centres and B cell lymphomagenesis. Nat Rev Immunol. 2015;15:172–84 https://pubmed.ncbi.nlm.nih.gov/25712152/.

    Article  CAS  Google Scholar 

  3. Alizadeh AA, Eisen MB, Davis RE, Ma C, Lossos IS, Rosenwald A, et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature. 2000;403:503–11 http://www.ncbi.nlm.nih.gov/pubmed/10676951.

    Article  CAS  Google Scholar 

  4. Chapuy B, Stewart C, Dunford AJ, Kim J, Kamburov A, Redd RA, et al. Molecular subtypes of diffuse large B cell lymphoma are associated with distinct pathogenic mechanisms and outcomes. Nat Med. 2018;24:679–90 http://www.ncbi.nlm.nih.gov/pubmed/29713087.

    Article  CAS  Google Scholar 

  5. Schmitz R, Wright GW, Huang DW, Johnson CA, Phelan JD, Wang JQ, et al. Genetics and pathogenesis of diffuse large B-cell lymphoma. N Engl J Med. 2018;378:1396–407 http://www.ncbi.nlm.nih.gov/pubmed/29641966.

    Article  CAS  Google Scholar 

  6. Dave SS, Wright G, Tan B, Rosenwald A, Gascoyne RD, Chan WC, et al. Prediction of survival in follicular lymphoma based on molecular features of tumor-infiltrating immune cells. N Engl J Med. 2004;351:2159–69 http://www.nejm.org/doi/abs/10.1056/NEJMoa041869.

    Article  CAS  Google Scholar 

  7. Mondello P, Fama A, Larson MC, Feldman AL, Villasboas JC, Yang ZZ, et al. Lack of intrafollicular memory CD4 + T cells is predictive of early clinical failure in newly diagnosed follicular lymphoma. Blood Cancer J. 2021;11:130 https://pubmed.ncbi.nlm.nih.gov/34267181/.

    Article  Google Scholar 

  8. Kotlov N, Bagaev A, Revuelta MV, Phillip JM, Cacciapuoti MT, Antysheva Z, et al. Clinical and biological subtypes of B-cell lymphoma revealed by microenvironmental signatures. Cancer Discov. 2021;11:1468–89 https://pubmed.ncbi.nlm.nih.gov/33541860/.

    Article  CAS  Google Scholar 

  9. Steen CB, Luca BA, Esfahani MS, Azizi A, Sworder BJ, Nabet BY, et al. The landscape of tumor cell states and ecosystems in diffuse large B cell lymphoma. Cancer Cell. 2021;39(10):1422–37 http://www.cell.com/article/S1535610821004517/fulltext Elsevier.

    Article  CAS  Google Scholar 

  10. Mondello P, Tadros S, Teater M, Fontan L, Chang AY, Jain N, et al. Selective inhibition of HDAC3 targets synthetic vulnerabilities and activates immune surveillance in lymphoma. Cancer Discov. 2020;10:440–59 http://cancerdiscovery.aacrjournals.org/lookup/doi/10.1158/2159-8290.CD-19-0116.

    Article  CAS  Google Scholar 

  11. Meyer SN, Scuoppo C, Vlasevska S, Bal E, Holmes AB, Holloman M, et al. Unique and shared epigenetic programs of the CREBBP and EP300 acetyltransferases in germinal center B cells reveal targetable dependencies in lymphoma. Immunity Cell Press. 2019;51:535–547.e9.

    CAS  Google Scholar 

  12. Ennishi D, Takata K, Béguelin W, Duns G, Mottok A, Farinha P, et al. Molecular and genetic characterization of MHC deficiency identifies ezh2 as therapeutic target for enhancing immune recognition. Cancer Discov. 2019;9:546–63 https://pubmed.ncbi.nlm.nih.gov/30705065/.

    Article  Google Scholar 

  13. Mondello P, Ansell SM, Nowakowski GS. Immune epigenetic crosstalk between malignant B cells and the tumor microenvironment in B cell lymphoma. Front Genet. 2022;13:826594 https://pubmed.ncbi.nlm.nih.gov/35237302/.

    Article  CAS  Google Scholar 

  14. Mondello P, Ansell SM. PHOENIX rises: genomic-based therapies for diffuse large B cell lymphoma. Cancer Cell. 2021;39:1570–2 https://pubmed.ncbi.nlm.nih.gov/34739842/.

    Article  CAS  Google Scholar 

  15. Crotty S. T follicular helper cell differentiation, function, and roles in disease. Immunity. 2014;41:529–42 https://pubmed.ncbi.nlm.nih.gov/25367570/.

    Article  CAS  Google Scholar 

  16. Jacobsen JT, Hu W, Castro TBR, Solem S, Galante A, Lin Z, et al. Expression of Foxp3 by T follicular helper cells in end-stage germinal centers. Science. 2021;373:eabe5146 https://pubmed.ncbi.nlm.nih.gov/34437125/.

    Article  CAS  Google Scholar 

  17. Zhou DM, Xu YX, Zhang LY, Sun Y, Wang ZY, Yuan YQ, et al. The role of follicular T helper cells in patients with malignant lymphoid disease. Hematology. 2017;22:412–8 https://pubmed.ncbi.nlm.nih.gov/28281408/.

    Article  CAS  Google Scholar 

  18. Cha Z, Gu H, Zang Y, Wang Z, Li J, Huang W, et al. The prevalence and function of CD4+CXCR5+Foxp3+ follicular regulatory T cells in diffuse large B cell lymphoma. Int Immunopharmacol. 2018;61:132–9 https://pubmed.ncbi.nlm.nih.gov/29870918/.

    Article  CAS  Google Scholar 

  19. Mintz MA, Cyster JG. T follicular helper cells in germinal center B cell selection and lymphomagenesis. Immunol Rev. 2020;296:48–61 https://pubmed.ncbi.nlm.nih.gov/32412663.

    Article  CAS  Google Scholar 

  20. Travert M, Ame-Thomas P, Pangault C, Morizot A, Micheau O, Semana G, et al. CD40 ligand protects from TRAIL-induced apoptosis in follicular lymphomas through NF-κB activation and up-regulation of c-FLIP and Bcl-xL. J Immunol. 2008;181:1001–11 https://www.jimmunol.org/content/181/2/1001.

    Article  CAS  Google Scholar 

  21. Brady MT, Hilchey SP, Hyrien O, Spence SA, Bernstein SH. Mesenchymal stromal cells support the viability and differentiation of follicular lymphoma-infiltrating follicular helper T-cells. PLoS One. 2014;9:e97597 https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0097597.

    Article  Google Scholar 

  22. Calvo KR, Dabir B, Kovach A, Devor C, Bandle R, Bond A, et al. IL-4 protein expression and basal activation of Erk in vivo in follicular lymphoma. Blood. 2008;112:3818–26 https://pubmed.ncbi.nlm.nih.gov/18682601/.

    Article  CAS  Google Scholar 

  23. Rawal S, Chu F, Zhang M, Park HJ, Nattamai D, Kannan S, et al. Cross talk between follicular Th cells and tumor cells in human follicular lymphoma promotes immune evasion in the tumor microenvironment. J Immunol. 2013;190:6681–93 http://www.jimmunol.org/cgi/doi/10.4049/jimmunol.1201363.

    Article  CAS  Google Scholar 

  24. Pangault C, Amé-Thomas P, Ruminy P, Rossille D, Caron G, Baia M, et al. Follicular lymphoma cell niche: identification of a preeminent IL-4-dependent T(FH)-B cell axis. Leukemia. 2010;24:2080–9 http://www.nature.com/articles/leu2010223.

    Article  CAS  Google Scholar 

  25. Ma X, Zha J, He J, Chen L, Huang J, Wu W, et al. T follicular helper cell-mediated IL-21 production suppresses FOXP3 expression of T follicular regulatory-like cells in diffuse large B cell lymphoma patients. Hum Immunol. 2020;81:452–9 https://pubmed.ncbi.nlm.nih.gov/32534760/.

    Article  CAS  Google Scholar 

  26. Han G, Deng Q, Marques-Piubelli ML, Dai E, Dang M, Ma MCJ, et al. Follicular lymphoma microenvironment characteristics associated with tumor cell mutations and MHC class II expression. Blood Cancer Discov. 2022;3:428–43 https://aacrjournals.org/bloodcancerdiscov/article/3/5/428/708353/Follicular-Lymphoma-Microenvironment.

    Article  CAS  Google Scholar 

  27. Chaudhry A, Rudensky AY. Control of inflammation by integration of environmental cues by regulatory T cells. J Clin Invest. 2013;123:939–44 https://pubmed.ncbi.nlm.nih.gov/23454755/.

    Article  CAS  Google Scholar 

  28. Fontenot JD, Gavin MA, Rudensky AY. Foxp3 programs the development and function of CD4+CD25+ regulatory T cells. Nat Immunol. 2003;4:986–92 https://pubmed.ncbi.nlm.nih.gov/12612578/.

    Article  Google Scholar 

  29. Josefowicz SZ, Lu LF, Rudensky AY. Regulatory T cells: mechanisms of differentiation and function. Annu Rev Immunol. 2012;30:531–64.

    Article  CAS  Google Scholar 

  30. Facciabene A, Motz GT, Coukos G. T-regulatory cells: key players in tumor immune escape and angiogenesis. Cancer Res. 2012;72:2162–71 https://aacrjournals.org/cancerres/article/72/9/2162/584187/T-Regulatory-Cells-Key-Players-in-Tumor-Immune.

    Article  CAS  Google Scholar 

  31. Yang ZZ, Novak AJ, Stenson MJ, Witzig TE, Ansell SM. Intratumoral CD4+CD25+ regulatory T-cell-mediated suppression of infiltrating CD4+ T cells in B-cell non-Hodgkin lymphoma. Blood. 2006;107:3639–46 https://pubmed.ncbi.nlm.nih.gov/16403912/.

    Article  CAS  Google Scholar 

  32. Carreras J, Lopez-Guillermo A, Fox BC, Colomo L, Martinez A, Roncador G, et al. High numbers of tumor-infiltrating FOXP3-positive regulatory T cells are associated with improved overall survival in follicular lymphoma. Blood. 2006;108:2957–64 http://www.bloodjournal.org/cgi/doi/10.1182/blood-2006-04-018218.

    Article  CAS  Google Scholar 

  33. Wahlin BE, Aggarwal M, Montes-Moreno S, Gonzalez LF, Roncador G, Sanchez-Verde L, et al. A unifying microenvironment model in follicular lymphoma: outcome is predicted by programmed death-1-positive, regulatory, cytotoxic, and helper T cells and macrophages. Clin Cancer Res. 2010;16:637–50 https://aacrjournals.org/clincancerres/article/16/2/637/75610/A-Unifying-Microenvironment-Model-in-Follicular.

    Article  CAS  Google Scholar 

  34. Tzankov A, Meier C, Hirschmann P, Went P, Pileri SA, Dirnhofer S. Correlation of high numbers of intratumoral FOXP3+ regulatory T cells with improved survival in germinal center-like diffuse large B-cell lymphoma, follicular lymphoma and classical Hodgkin’s lymphoma. Haematologica. 2008;93:193–200 https://pubmed.ncbi.nlm.nih.gov/18223287/.

    Article  CAS  Google Scholar 

  35. Lee NR, Song EK, Jang KY, Choi HN, Moon WS, Kwon K, et al. Prognostic impact of tumor infiltrating FOXP3 positive regulatory T cells in diffuse large B-cell lymphoma at diagnosis. Leuk Lymphoma. 2008;49:247–56 https://pubmed.ncbi.nlm.nih.gov/18231910/.

    Article  CAS  Google Scholar 

  36. Yang ZZ, Novak AJ, Ziesmer SC, Witzig TE, Ansell SM. Attenuation of CD8+ T-cell function by CD4+CD25 + regulatory T cells in B-cell non-Hodgkin’s lymphoma. Cancer Res. 2006;66:10145–52 https://pubmed.ncbi.nlm.nih.gov/17047079/.

    Article  CAS  Google Scholar 

  37. Nakayama S, Yokote T, Akioka T, Hiraoka N, Nishiwaki U, Miyoshi T, et al. Infiltration of effector regulatory T cells predicts poor prognosis of diffuse large B-cell lymphoma, not otherwise specified. Blood Adv. 2017;1:486–93 https://ashpublications.org/bloodadvances/article/1/8/486/15602/Infiltration-of-effector-regulatory-T-cells.

    Article  CAS  Google Scholar 

  38. Yang ZZ, Kim HJ, Wu H, Jalali S, Tang X, Krull JE, et al. TIGIT expression is associated with T-cell suppression and exhaustion and predicts clinical outcome and anti-PD-1 response in follicular lymphoma. Clin Cancer Res. 2020;26:5217–31 https://pubmed.ncbi.nlm.nih.gov/32631956/.

    Article  Google Scholar 

  39. Tang X, Yang Z-Z, Kim HJ, Anagnostou T, Yu Y, Wu X, et al. Phenotype, function, and clinical significance of CD26+ and CD161+Tregs in splenic marginal zone lymphoma. Clin Cancer Res. 2022;28:4322–35 https://pubmed.ncbi.nlm.nih.gov/35686915/.

    Article  CAS  Google Scholar 

  40. Profitós-Pelejà N, Santos JC, Marín-Niebla A, Roué G, Ribeiro ML. Regulation of B-cell receptor signaling and its therapeutic relevance in aggressive B-cell lymphomas. Cancers (Basel). 2022;14:860 https://pubmed.ncbi.nlm.nih.gov/35205606/.

    Article  Google Scholar 

  41. Ramsay AG, Clear AJ, Kelly G, Fatah R, Matthews J, MacDougall F, et al. Follicular lymphoma cells induce T-cell immunologic synapse dysfunction that can be repaired with lenalidomide: implications for the tumor microenvironment and immunotherapy. Blood. 2009;114:4713–20 https://pubmed.ncbi.nlm.nih.gov/19786615/.

    Article  CAS  Google Scholar 

  42. Pandiyan P, Younes SA, Ribeiro SP, Talla A, McDonald D, Bhaskaran N, et al. Mucosal regulatory T cells and T helper 17 cells in HIV-associated immune activation. Front Immunol. 2016;7:228 https://pubmed.ncbi.nlm.nih.gov/27379092/.

    Article  Google Scholar 

  43. Grygorowicz MA, Borycka IS, Nowak E, Paszkiewicz-Kozik E, Rymkiewicz G, Błachnio K, et al. Lenalidomide potentiates CD4+CD25+Treg-related suppression of lymphoma B-cell proliferation. Clin Exp Med. 2017;17:193–207 https://pubmed.ncbi.nlm.nih.gov/26961690/.

    Article  CAS  Google Scholar 

  44. Tarantelli C, Argnani L, Zinzani PL, Bertoni F. PI3Kδ Inhibitors as Immunomodulatory Agents for the Treatment of Lymphoma Patients. Cancers (Basel). 2021;13:5535 /pmc/articles/PMC8582887.

    Article  CAS  Google Scholar 

  45. Carnevalli LS, Sinclair C, Taylor MA, Gutierrez PM, Langdon S, Coenen-Stass AML, et al. PI3Kα/δ inhibition promotes anti-tumor immunity through direct enhancement of effector CD8+ T-cell activity 11 medical and health sciences 1107 immunology. J Immunother Cancer. 2018;6:1–14 https://jitc.biomedcentral.com/articles/10.1186/s40425-018-0457-0.

    Google Scholar 

  46. Jin H, Zhou Y, Wang L. The mechanism of rapamycin in promoting asthmatic regulatory T cell differentiation and function. Zhejiang Da Xue Xue Bao Yi Xue Ban. 2021;50:621–6 https://pubmed.ncbi.nlm.nih.gov/34986526/.

    Google Scholar 

  47. Fife BT, Bluestone JA. Control of peripheral T-cell tolerance and autoimmunity via the CTLA-4 and PD-1 pathways. Immunol Rev. 2008;224:166–82 https://pubmed.ncbi.nlm.nih.gov/18759926/.

    Article  CAS  Google Scholar 

  48. Larson RC, Maus M, v. Recent advances and discoveries in the mechanisms and functions of CAR T cells. Nat Rev Cancer. 2021;21:145–61 https://pubmed.ncbi.nlm.nih.gov/18759926.

    Article  CAS  Google Scholar 

  49. Bejarano L, Jordāo MJC, Joyce JA. Therapeutic targeting of the tumor microenvironment. Cancer Discov. 2021;11:933–59 https://pubmed.ncbi.nlm.nih.gov/33811125/.

    Article  CAS  Google Scholar 

  50. Sobhani N, Tardiel-Cyril DR, Davtyan A, Generali D, Roudi R, Li Y. CTLA-4 in regulatory T cells for cancer immunotherapy. Cancers (Basel). 2021;13:1440 https://pubmed.ncbi.nlm.nih.gov/33809974/.

    Article  CAS  Google Scholar 

  51. Tuscano JM, Maverakis E, Groshen S, Tsao-Wei D, Luxardi G, Merleev AA, et al. A phase I study of the combination of rituximab and ipilimumab in patients with relapsed/ refractory B-cell lymphoma. Clin Cancer Res. 2019;25:7004–13 https://pubmed.ncbi.nlm.nih.gov/31481504/.

    Article  CAS  Google Scholar 

  52. Wei SC, Levine JH, Cogdill AP, Zhao Y, Anang NAAS, Andrews MC, et al. Distinct cellular mechanisms underlie anti-CTLA-4 and anti-PD-1 checkpoint blockade. Cell. 2017;170:1120–33 https://pubmed.ncbi.nlm.nih.gov/28803728/.

    Article  CAS  Google Scholar 

  53. Gong J, Chehrazi-Raffle A, Reddi S, Salgia R. Development of PD-1 and PD-L1 inhibitors as a form of cancer immunotherapy: a comprehensive review of registration trials and future considerations. J Immunother Cancer. 2018;6:8 https://pubmed.ncbi.nlm.nih.gov/28803728/.

    Article  Google Scholar 

  54. Huang RY, Francois A, McGray AR, Miliotto A, Odunsi K. Compensatory upregulation of PD-1, LAG-3, and CTLA-4 limits the efficacy of single-agent checkpoint blockade in metastatic ovarian cancer. Oncoimmunology. 2017;6:e1249561 https://pubmed.ncbi.nlm.nih.gov/28197366/.

    Article  Google Scholar 

  55. Huang RY, Eppolito C, Lele S, Shrikant P, Matsuzaki J, Odunsi K. LAG3 and PD1 co-inhibitory molecules collaborate to limit CD8+ T cell signaling and dampen antitumor immunity in a murine ovarian cancer model. Oncotarget. 2015;6:27359–77 https://pubmed.ncbi.nlm.nih.gov/26318293/.

    Article  Google Scholar 

  56. Ansell SM, Hurvitz SA, Koenig PA, LaPlant BR, Kabat BF, Fernando D, et al. Phase I study of ipilimumab, an anti-CTLA-4 monoclonal antibody, in patients with relapsed and refractory B-cell non-Hodgkin lymphoma. Clin Cancer Res. 2009;15:6446–53 https://pubmed.ncbi.nlm.nih.gov/19808874/.

    Article  CAS  Google Scholar 

  57. Zhu C, Anderson AC, Schubart A, Xiong H, Imitola J, Khoury SJ, et al. The Tim-3 ligand galectin-9 negatively regulates T helper type 1 immunity. Nat Immunol. 2005;6:1245–53 https://pubmed.ncbi.nlm.nih.gov/16286920/.

    Article  CAS  Google Scholar 

  58. Kang CW, Dutta A, Chang LY, Mahalingam J, Lin YC, Chiang JM, et al. Apoptosis of tumor infiltrating effector TIM-3+CD8+ T cells in colon cancer. Sci Rep. 2015;5:15659 https://pubmed.ncbi.nlm.nih.gov/26493689/.

    Article  CAS  Google Scholar 

  59. Hahn AW, Gill DM, Pal SK, Agarwal N. The future of immune checkpoint cancer therapy after PD-1 and CTLA-4. Immunotherapy. 2017;9:681–92 https://pubmed.ncbi.nlm.nih.gov/28653573/.

    Article  CAS  Google Scholar 

  60. Yu X, Harden K, Gonzalez LC, Francesco M, Chiang E, Irving B, et al. The surface protein TIGIT suppresses T cell activation by promoting the generation of mature immunoregulatory dendritic cells. Nat Immunol. 2009;10:48–57 https://pubmed.ncbi.nlm.nih.gov/19011627.

    Article  CAS  Google Scholar 

  61. Johnston RJ, Comps-Agrar L, Hackney J, Yu X, Huseni M, Yang Y, et al. The Immunoreceptor TIGIT regulates antitumor and antiviral CD8+ T cell effector function. Cancer Cell. 2014;26:923–37 https://pubmed.ncbi.nlm.nih.gov/25465800/.

    Article  CAS  Google Scholar 

  62. Harjunpää H, Guillerey C. TIGIT as an emerging immune checkpoint. Clin Exp Immunol. 2020;200:108–19 https://pubmed.ncbi.nlm.nih.gov/31828774/.

    Article  Google Scholar 

  63. Kaech SM, Ahmed R. Memory CD8+ T cell differentiation: initial antigen encounter triggers a developmental program in naïve cells. Nat Immunol. 2001;2:415–22 https://pubmed.ncbi.nlm.nih.gov/11323695/.

    Article  CAS  Google Scholar 

  64. Youngblood B, Hale JS, Kissick HT, Ahn E, Xu X, Wieland A, et al. Effector CD8 T cells dedifferentiate into long-lived memory cells. Nature. 2017;552:404–9 https://pubmed.ncbi.nlm.nih.gov/29236683/.

    Article  CAS  Google Scholar 

  65. Collier JL, Weiss SA, Pauken KE, Sen DR, Sharpe AH. Not-so-opposite ends of the spectrum: CD8+ T cell dysfunction across chronic infection, cancer and autoimmunity. Nat Immunol. 2021;22:809–19 https://pubmed.ncbi.nlm.nih.gov/34140679/.

    Article  CAS  Google Scholar 

  66. Strioga M, Pasukoniene V, Characiejus D. CD8+ CD28- and CD8+ CD57+ T cells and their role in health and disease. Immunology. 2011;134:17–32 http://www.ncbi.nlm.nih.gov/pubmed/21711350.

    Article  CAS  Google Scholar 

  67. Alotaibi F, Vincent M, Min WP, Koropatnick J. Reduced CD5 on CD8+ T cells in tumors but not lymphoid organs is associated with increased activation and effector function. Front Immunol. 2021;11:584937 https://pubmed.ncbi.nlm.nih.gov/33584650/.

    Article  Google Scholar 

  68. Blank CU, Haining WN, Held W, Hogan PG, Kallies A, Lugli E, et al. Defining ‘T cell exhaustion’. Nat Rev Immunol. 2019;19:665–74 https://pubmed.ncbi.nlm.nih.gov/31570879/.

    Article  CAS  Google Scholar 

  69. Wahlin BE, Sander B, Christensson B, Kimby E. CD8+ T-cell content in diagnostic lymph nodes measured by flow cytometry is a predictor of survival in follicular lymphoma. Clin Cancer Res. 2007;13:338–97 https://pubmed.ncbi.nlm.nih.gov/17255259/.

    Article  Google Scholar 

  70. Alvaro T, Lejeune M, Salvadó M-T, Lopez C, Jaén J, Bosch R, et al. Immunohistochemical patterns of reactive microenvironment are associated with clinicobiologic behavior in follicular lymphoma patients. J Clin Oncol. 2006;24:5350–7 http://ascopubs.org/doi/10.1200/JCO.2006.06.4766.

    Article  Google Scholar 

  71. Carreras J, Lopez-Guillermo A, Roncador G, Villamor N, Colomo L, Martinez A, et al. High numbers of tumor-infiltrating programmed cell death 1-positive regulatory lymphocytes are associated with improved overall survival in follicular lymphoma. J Clin Oncol. 2009;27:1470–6 http://ascopubs.org/doi/10.1200/JCO.2008.18.0513.

    Article  Google Scholar 

  72. Yang ZZ, Kim HJ, Villasboas JC, Chen YP, Price-Troska TP, Jalali S, et al. Expression of LAG-3 defines exhaustion of intratumoral PD-1 + T cells and correlates with poor outcome in follicular lymphoma. Oncotarget. 2017;8:61425–39 https://pubmed.ncbi.nlm.nih.gov/28977875/.

    Article  Google Scholar 

  73. Grosso JF, Kelleher CC, Harris TJ, Maris CH, Hipkiss EL, de Marzo A, et al. LAG-3 regulates CD8+ T cell accumulation and effector function in murine self- and tumor-tolerance systems. J Clin Investig. 2007;117:3383–92 https://pubmed.ncbi.nlm.nih.gov/17932562/.

    Article  CAS  Google Scholar 

  74. Pathria P, Louis TL, Varner JA. Targeting tumor-associated macrophages in Cancer. Trends Immunol. 2019;40:310–27 https://pubmed.ncbi.nlm.nih.gov/30890304.

    Article  CAS  Google Scholar 

  75. Lin Y, Xu J, Lan H. Tumor-associated macrophages in tumor metastasis: biological roles and clinical therapeutic applications. J Hematol Oncol. 2019;12:76 https://pubmed.ncbi.nlm.nih.gov/31300030/.

    Article  Google Scholar 

  76. Taskinen M, Karjalainen-Lindsberg M-L, Nyman H, Eerola L-M, Leppä S. A high tumor-associated macrophage content predicts favorable outcome in follicular lymphoma patients treated with rituximab and cyclophosphamide-doxorubicin-vincristine-prednisone. Clin Cancer Res. 2007;13:5784–9 http://clincancerres.aacrjournals.org/cgi/doi/10.1158/1078-0432.CCR-07-0778.

    Article  CAS  Google Scholar 

  77. Steidl C, Lee T, Shah SP, Farinha P, Han G, Nayar T, et al. Tumor-associated macrophages and survival in classic Hodgkin’s lymphoma. N Engl J Med. 2010;362:875–85 https://pubmed.ncbi.nlm.nih.gov/20220182/.

    Article  CAS  Google Scholar 

  78. Clear AJ, Lee AM, Calaminici M, Ramsay AG, Morris KJ, Hallam S, et al. Increased angiogenic sprouting in poor prognosis FL is associated with elevated numbers of CD163+ macrophages within the immediate sprouting microenvironment. Blood. 2010;115:5053–6 https://pubmed.ncbi.nlm.nih.gov/20375314/.

    Article  CAS  Google Scholar 

  79. Shen L, Li H, Shi Y, Wang D, Gong J, Xun J, et al. M2 tumour-associated macrophages contribute to tumour progression via legumain remodelling the extracellular matrix in diffuse large B cell lymphoma. Sci Rep. 2016;6:30347 https://pubmed.ncbi.nlm.nih.gov/27464733/.

    Article  CAS  Google Scholar 

  80. Wu K, Lin K, Li X, Yuan X, Xu P, Ni P, et al. Redefining tumor-associated macrophage subpopulations and functions in the tumor microenvironment. Front Immunol. 2020;11:1731.

    Article  CAS  Google Scholar 

  81. Petty AJ, Yang Y. Tumor-associated macrophages in hematologic malignancies: new insights and targeted therapies. Cells. 2019;8:1526 https://pubmed.ncbi.nlm.nih.gov/32849616/.

    Article  CAS  Google Scholar 

  82. Papin A, Tessoulin B, Bellanger C, Moreau A, le Bris Y, Maisonneuve H, et al. CSF1R and BTK inhibitions as novel strategies to disrupt the dialog between mantle cell lymphoma and macrophages. Leukemia. 2019;33(2442):2453 https://pubmed.ncbi.nlm.nih.gov/30940906/.

    Google Scholar 

  83. Valero JG, Matas-Céspedes A, Arenas F, Rodriguez V, Carreras J, Serrat N, et al. The receptor of the colony-stimulating factor-1 (CSF-1R) is a novel prognostic factor and therapeutic target in follicular lymphoma. Leukemia. 2021;35:2635–49 https://pubmed.ncbi.nlm.nih.gov/33731849/.

    Article  CAS  Google Scholar 

  84. DeNardo DG, Ruffell B. Macrophages as regulators of tumour immunity and immunotherapy. Nat Rev Immunol. 2019;19:369–82 https://pubmed.ncbi.nlm.nih.gov/30718830/.

    Article  CAS  Google Scholar 

  85. Chao MP, Alizadeh AA, Tang C, Myklebust JH, Varghese B, Gill S, et al. Anti-CD47 antibody synergizes with rituximab to promote phagocytosis and eradicate non-Hodgkin lymphoma. Cell. 2010;142:699–713 https://linkinghub.elsevier.com/retrieve/pii/S0092867410008925.

    Article  CAS  Google Scholar 

  86. Eladl E, Tremblay-Lemay R, Rastgoo N, Musani R, Chen W, Liu A, et al. Role of CD47 in hematological malignancies. J Hematol Oncol. 2020;13:96 https://pubmed.ncbi.nlm.nih.gov/32677994/.

    Article  Google Scholar 

  87. Chao MP, Tang C, Pachynski RK, Chin R, Majeti R, Weissman IL. Extranodal dissemination of non-Hodgkin lymphoma requires CD47 and is inhibited by anti-CD47 antibody therapy. Blood. 2011;118:4890–901 https://ashpublications.org/blood/article/118/18/4890/29362/Extranodal-dissemination-of-nonHodgkin-lymphoma.

    Article  CAS  Google Scholar 

  88. Huang YH, Cai K, Xu PP, Wang L, Huang CX, Fang Y, et al. CREBBP/EP300 mutations promoted tumor progression in diffuse large B-cell lymphoma through altering tumor-associated macrophage polarization via FBXW7-NOTCH-CCL2/CSF1 axis. Signal Transduct Target Ther. 2021;6:10 https://pubmed.ncbi.nlm.nih.gov/33431788/.

    Article  CAS  Google Scholar 

  89. Yan-Li L, Hu Q-Q, Wen Z-F, Li Q, Zhai Z-M. CCR2 expression promotes diffuse large B lymphoma cell survival and invasion. Lab Investig. Lab Invest. 2022;102:1377–88. https://pubmed.ncbi.nlm.nih.gov/35851856/.

  90. Wu X, Singh R, Hsu DK, Zhou Y, Yu S, Han D, et al. A small molecule CCR2 antagonist depletes tumor macrophages and synergizes with anti–PD-1 in a murine model of cutaneous T-cell lymphoma (CTCL). J Investig Dermatol. 2020;140:1390–400 https://pubmed.ncbi.nlm.nih.gov/31945344/.

    Article  CAS  Google Scholar 

  91. Ludwig N, Rubenich DS, Zaręba Ł, Siewiera J, Pieper J, Braganhol E, et al. Potential roles of tumor cell-and stroma cell-derived small extracellular vesicles in promoting a pro-angiogenic tumor microenvironment. Cancers (Basel). 2020;12:3599 https://pubmed.ncbi.nlm.nih.gov/33276428/.

    Article  CAS  Google Scholar 

  92. Poles WA, Nishi EE, de Oliveira MB, Eugênio AIP, de Andrade TA, Campos AHFM, et al. Targeting the polarization of tumor-associated macrophages and modulating mir-155 expression might be a new approach to treat diffuse large B-cell lymphoma of the elderly. Cancer Immunol Immunother. 2019;68:269–82 https://pubmed.ncbi.nlm.nih.gov/30430204/.

    Article  CAS  Google Scholar 

  93. Moradi-Chaleshtori M, Bandehpour M, Soudi S, Mohammadi-Yeganeh S, Hashemi SM. In vitro and in vivo evaluation of anti-tumoral effect of M1 phenotype induction in macrophages by miR-130 and miR-33 containing exosomes. Cancer Immunol Immunother. 2021;70:1323–39 https://pubmed.ncbi.nlm.nih.gov/33140190/.

    Article  CAS  Google Scholar 

  94. Gabrilovich DI, Bronte V, Chen SH, Colombo MP, Ochoa A, Ostrand-Rosenberg S, et al. The terminology issue for myeloid-derived suppressor cells. Cancer Res. 2007;67:425 https://aacrjournals.org/cancerres/article/67/1/425/532949/The-Terminology-Issue-for-Myeloid-Derived.

    Article  CAS  Google Scholar 

  95. Tian X, Shen H, Li Z, Wang T, Wang S. Tumor-derived exosomes, myeloid-derived suppressor cells, and tumor microenvironment. J Hematol Oncol. 2019;12:84 https://pubmed.ncbi.nlm.nih.gov/31438991/.

    Article  Google Scholar 

  96. Kumar V, Patel S, Tcyganov E, Gabrilovich DI. The nature of myeloid-derived suppressor cells in the tumor microenvironment. Trends Immunol. 2016;37:208–20 https://pubmed.ncbi.nlm.nih.gov/26858199/.

    Article  CAS  Google Scholar 

  97. Romano A, Parrinello NL, Vetro C, Forte S, Chiarenza A, Figuera A, et al. Circulating myeloid-derived suppressor cells correlate with clinical outcome in Hodgkin lymphoma patients treated up-front with a risk-adapted strategy. Br J Haematol. 2015;168:689–700 https://pubmed.ncbi.nlm.nih.gov/25376846/.

    Article  CAS  Google Scholar 

  98. Marini O, Spina C, Mimiola E, Cassaro A, Malerba G, Todeschini G, et al. Identification of granulocytic myeloid-derived suppressor cells (G-MDSCs) in the peripheral blood of Hodgkin and non-Hodgkin lymphoma patients. Oncotarget. 2016;7:27676–88 https://pubmed.ncbi.nlm.nih.gov/27050283/.

    Article  Google Scholar 

  99. Azzaoui I, Uhel F, Rossille D, Pangault C, Dulong J, le Priol J, et al. T-cell defect in diffuse large B-cell lymphomas involves expansion of myeloid-derived suppressor cells. Blood. 2016;128:1081–92 https://pubmed.ncbi.nlm.nih.gov/27338100/.

    Article  CAS  Google Scholar 

  100. Tadmor T, Fell R, Polliack A, Attias D. Absolute monocytosis at diagnosis correlates with survival in diffuse large B-cell lymphoma-possible link with monocytic myeloid-derived suppressor cells. Hematol Oncol. 2013;31:65–71 https://pubmed.ncbi.nlm.nih.gov/22714941/.

    Article  Google Scholar 

  101. Ren WH, Zhang XR, Li WB, Feng Q, Feng HJ, Tong Y, et al. Exosomal miRNA-107 induces myeloid-derived suppressor cell expansion in gastric cancer. Cancer Manag Res. 2019;11:4023–40 https://pubmed.ncbi.nlm.nih.gov/31190980/.

    Article  CAS  Google Scholar 

  102. Serafini P, Meckel K, Kelso M, Noonan K, Califano J, Koch W, et al. Phosphodiesterase-5 inhibition augments endogenous antitumor immunity by reducing myeloid-derived suppressor cell function. J Exp Med. 2006;203:2691–702 https://pubmed.ncbi.nlm.nih.gov/17101732/.

    Article  CAS  Google Scholar 

  103. Xu Z, Ji J, Xu J, Li D, Shi G, Liu F, et al. MiR-30a increases MDSC differentiation and immunosuppressive function by targeting SOCS3 in mice with B-cell lymphoma. FEBS J. 2017;284:2410–24 https://pubmed.ncbi.nlm.nih.gov/28605567/.

    Article  CAS  Google Scholar 

  104. Grauers Wiktorin H, Nilsson MS, Kiffin R, Sander FE, Lenox B, Rydström A, et al. Histamine targets myeloid-derived suppressor cells and improves the anti-tumor efficacy of PD-1/PD-L1 checkpoint blockade. Cancer Immunol Immunother. 2019;68:163–74 https://pubmed.ncbi.nlm.nih.gov/30315349.

    Article  CAS  Google Scholar 

  105. Locatelli SL, Careddu G, Serio S, Consonni FM, Maeda A, Viswanadha S, et al. Targeting cancer cells and tumor microenvironment in preclinical and clinical models of Hodgkin lymphoma using the dual PI3Kd/G inhibitor RP6530. Clin Cancer Res. 2019;25:1098–112 https://pubmed.ncbi.nlm.nih.gov/30352904/.

    Article  CAS  Google Scholar 

  106. Cherkassky L, Morello A, Villena-Vargas J, Feng Y, Dimitrov DS, Jones DR, et al. Human CAR T cells with cell-intrinsic PD-1 checkpoint blockade resist tumor-mediated inhibition. J Clin Investig. 2016;126:3130–44 https://pubmed.ncbi.nlm.nih.gov/27454297/.

    Article  Google Scholar 

  107. Burga RA, Thorn M, Point GR, Guha P, Nguyen CT, Licata LA, et al. Liver myeloid-derived suppressor cells expand in response to liver metastases in mice and inhibit the anti-tumor efficacy of anti-CEA CAR-T. Cancer Immunol Immunother. 2015;64:817–29 https://pubmed.ncbi.nlm.nih.gov/25850344/.

    Article  CAS  Google Scholar 

  108. Kalluri R. The biology and function of fibroblasts in cancer. Nat Rev Cancer. 2016;16:582–98 https://pubmed.ncbi.nlm.nih.gov/27550820.

    Article  CAS  Google Scholar 

  109. Orimo A, Gupta PB, Sgroi DC, Arenzana-Seisdedos F, Delaunay T, Naeem R, et al. Stromal fibroblasts present in invasive human breast carcinomas promote tumor growth and angiogenesis through elevated SDF-1/CXCL12 secretion. Cell. 2005;121:335–48 https://pubmed.ncbi.nlm.nih.gov/15882617/.

    Article  CAS  Google Scholar 

  110. Chen X, Song E. Turning foes to friends: targeting cancer-associated fibroblasts. Nat Rev Drug Discov. 2019;18:99–115 https://pubmed.ncbi.nlm.nih.gov/30470818/.

    Article  CAS  Google Scholar 

  111. Scherz-Shouval R, Santagata S, Mendillo ML, Sholl LM, Ben-Aharon I, Beck AH, et al. The reprogramming of tumor stroma by HSF1 is a potent enabler of malignancy. Cell. 2014;158:564–78 https://pubmed.ncbi.nlm.nih.gov/25083868/.

    Article  CAS  Google Scholar 

  112. Calvo F, Ege N, Grande-Garcia A, Hooper S, Jenkins RP, Chaudhry SI, et al. Mechanotransduction and YAP-dependent matrix remodelling is required for the generation and maintenance of cancer-associated fibroblasts. Nat Cell Biol. 2013;15:637–46 https://pubmed.ncbi.nlm.nih.gov/23708000/.

    Article  CAS  Google Scholar 

  113. Sarvaria A, Madrigal JA, Saudemont A. B cell regulation in cancer and anti-tumor immunity. Cell Mol Immunol. 2017;14:662–74 https://pubmed.ncbi.nlm.nih.gov/28626234/.

    Article  CAS  Google Scholar 

  114. Powell DW, Mifflin RC, Valentich JD, Crowe SE, Saada JI, West AB. Myofibroblasts. I. Paracrine cells important in health and disease. Am J Physiol Cell Physiol. 1999;277:C1–9.

    Article  CAS  Google Scholar 

  115. Pandey S, Mourcin F, Marchand T, Nayar S, Guirriec M, Pangault C, et al. IL-4/CXCL12 loop is a key regulator of lymphoid stroma function in follicular lymphoma. Blood. 2017;129:2507–18 https://pubmed.ncbi.nlm.nih.gov/28202459/.

    Article  CAS  Google Scholar 

  116. Grégoire M, Guilloton F, Pangault C, Mourcin F, Sok P, Latour M, et al. Neutrophils trigger a NF-ΚB dependent polarization of tumorsupportive stromal cells in germinal center B-cell lymphomas. Oncotarget. 2015;6:16471–87 https://pubmed.ncbi.nlm.nih.gov/26158216/.

    Article  Google Scholar 

  117. Guilloton F, Caron G, Ménard C, Pangault C, Amé-Thomas P, Dulong J, et al. Mesenchymal stromal cells orchestrate follicular lymphoma cell niche through the CCL2-dependent recruitment and polarization of monocytes. Blood. 2012;119:2556–67 http://ashpublications.org/blood/article-pdf/119/11/2556/1350217/zh801112002556.pdf.

    Article  CAS  Google Scholar 

  118. Haro M, Orsulic S. A paradoxical correlation of cancer-associated fibroblasts with survival outcomes in B-cell lymphomas and carcinomas. Front Cell Dev Biol. 2018;6:98 https://pubmed.ncbi.nlm.nih.gov/30211161/.

    Article  Google Scholar 

  119. Stelling A, Hashwah H, Bertram K, Manz MG, Tzankov A, Müller A. The tumor suppressive TGF-b/SMAD1/S1PR2 signaling axis is recurrently inactivated in diffuse large B-cell lymphoma. Blood. 2018;131:2235–46 https://pubmed.ncbi.nlm.nih.gov/29615404/.

    Article  CAS  Google Scholar 

  120. Sanjabi S, Oh SA, Li MO. Regulation of the immune response by TGF-β: from conception to autoimmunity and infection. Cold Spring Harb Perspect Biol. 2017;9:a0222236 https://pubmed.ncbi.nlm.nih.gov/28108486.

    Article  Google Scholar 

  121. Vivier E, Tomasello E, Baratin M, Walzer T, Ugolini S. Functions of natural killer cells. Nat Immunol. 2008;9:503–10 https://pubmed.ncbi.nlm.nih.gov/18425107/.

    Article  CAS  Google Scholar 

  122. Harel-Bellan A, Quillet A, Marchiol C, DeMars R, Tursz T, Fradelizi D. Natural killer susceptibility of human cells may be regulated by genes in the HLA region on chromosome 6. Proc Natl Acad Sci U S A. 1986;83:5688–92 https://pubmed.ncbi.nlm.nih.gov/2426704/.

    Article  CAS  Google Scholar 

  123. McWilliams EM, Mele JM, Cheney C, Timmerman EA, Fiazuddin F, Strattan EJ, et al. Therapeutic CD94/NKG2A blockade improves natural killer cell dysfunction in chronic lymphocytic leukemia. Oncoimmunology. 2016;5:e1226720 https://pubmed.ncbi.nlm.nih.gov/27853650/.

    Article  Google Scholar 

  124. Wolf NK, Kissiov DU, Raulet DH. Roles of natural killer cells in immunity to cancer, and applications to immunotherapy. Nat Rev Immun. 2022:1–16 https://www.nature.com/articles/s41577-022-00732-1.

  125. Kärre K, Ljunggren HG, Piontek G, Kiessling R. Selective rejection of H-2-deficient lymphoma variants suggests alternative immune defence strategy. Nature. 1986;319:675–8 https://pubmed.ncbi.nlm.nih.gov/3951539/.

    Article  Google Scholar 

  126. Seaman WE, Sleisenger M, Eriksson E, Koo GC. Depletion of natural killer cells in mice by monoclonal antibody to NK-1.1. Reduction in host defense against malignancy without loss of cellular or humoral immunity. J Immunol. 1987;138:4539–44.

    CAS  Google Scholar 

  127. Street SEA, Hayakawa Y, Zhan Y, Lew AM, MacGregor D, Jamieson AM, et al. Innate immune surveillance of spontaneous B cell lymphomas by natural killer cells and γδ T cells. J Exp Med. 2004;199:879–84 https://pubmed.ncbi.nlm.nih.gov/15007091/.

    Article  CAS  Google Scholar 

  128. Smyth MJ, Crowe NY, Godfrey DI. NK cells and NKT cells collaborate in host protection from methylcholanthrene-induced fibrosarcoma. Int Immunol. 2001;13:459–63 https://pubmed.ncbi.nlm.nih.gov/11282985/.

    Article  CAS  Google Scholar 

  129. Bonavita E, Bromley CP, Jonsson G, Pelly VS, Sahoo S, Walwyn-Brown K, et al. Antagonistic inflammatory phenotypes dictate tumor fate and response to immune checkpoint blockade. Immunity. 2020;53:1215–29 https://pubmed.ncbi.nlm.nih.gov/33220234/.

    Article  CAS  Google Scholar 

  130. Marcus A, Mao AJ, Lensink-Vasan M, Wang LA, Vance RE, Raulet DH. Tumor-derived cGAMP triggers a STING-mediated interferon response in non-tumor cells to activate the NK cell response. Immunity. 2018;49:754–63 https://pubmed.ncbi.nlm.nih.gov/30332631/.

    Article  CAS  Google Scholar 

  131. Varn FS, Wang Y, Mullins DW, Fiering S, Cheng C. Systematic pan-cancer analysis reveals immune cell interactions in the tumor microenvironment. Cancer Res. 2017;77:1271–82 https://pubmed.ncbi.nlm.nih.gov/28126714/.

    Article  CAS  Google Scholar 

  132. Cózar B, Greppi M, Carpentier S, Narni-Mancinelli E, Chiossone L, Vivier E. Tumor-infiltrating natural killer cells. Cancer Discov. 2021;11:34–44 https://pubmed.ncbi.nlm.nih.gov/33277307/.

    Article  Google Scholar 

  133. Cursons J, Souza-Fonseca-Guimaraes F, Foroutan M, Anderson A, Hollande F, Hediyeh-Zadeh S, et al. A gene signature predicting natural killer cell infiltration and improved survival in melanoma patients. Cancer Immunol Res. 2019;7:1162–74.

    Article  CAS  Google Scholar 

  134. Castriconi R, Cantoni C, della Chiesa M, Vitale M, Marcenaro E, Conte R, et al. Transforming growth factor β1 inhibits expression of NKP30 and NKG2d receptors: consequences for the NK-mediated killing of dendritic cells. Proc Natl Acad Sci U S A. 2003;100:4120–5 https://pubmed.ncbi.nlm.nih.gov/12646700/.

    Article  CAS  Google Scholar 

  135. Gao Y, Souza-Fonseca-Guimaraes F, Bald T, Ng SS, Young A, Ngiow SF, et al. Tumor immunoevasion by the conversion of effector NK cells into type 1 innate lymphoid cells. Nat Immunol. 2017;18:1004–15 https://pubmed.ncbi.nlm.nih.gov/28759001/.

    Article  CAS  Google Scholar 

  136. Zelenay S, van der Veen AG, Böttcher JP, Snelgrove KJ, Rogers N, Acton SE, et al. Cyclooxygenase-dependent tumor growth through evasion of immunity. Cell. 2015;162:1257–70.

    Article  CAS  Google Scholar 

  137. Young A, Ngiow SF, Gao Y, Patch AM, Barkauskas DS, Messaoudene M, et al. A2AR adenosine signaling suppresses natural killer cell maturation in the tumor microenvironment. Cancer Res. 2018;78:1003–16 https://pubmed.ncbi.nlm.nih.gov/29229601/.

    Article  CAS  Google Scholar 

  138. Ghiringhelli F, Ménard C, Martin F, Zitvogel L. The role of regulatory T cells in the control of natural killer cells: relevance during tumor progression. Immunol Rev. 2006;214:229–38 https://pubmed.ncbi.nlm.nih.gov/17100888/.

    Article  CAS  Google Scholar 

  139. Kerdiles Y, Ugolini S, Vivier E. T cell regulation of natural killer cells. J Exp Med. 2013;210:1065–8 https://pubmed.ncbi.nlm.nih.gov/23733834/.

    Article  CAS  Google Scholar 

  140. Stanietsky N, Simic H, Arapovic J, Toporik A, Levy O, Novik A, et al. The interaction of TIGIT with PVR and PVRL2 inhibits human NK cell cytotoxicity. Proc Natl Acad Sci U S A. 2009;106:17858–63 https://pubmed.ncbi.nlm.nih.gov/19815499/.

    Article  CAS  Google Scholar 

  141. Chan CJ, Martinet L, Gilfillan S, Souza-Fonseca-Guimaraes F, Chow MT, Town L, et al. The receptors CD96 and CD226 oppose each other in the regulation of natural killer cell functions. Nat Immunol. 2014;15:531–8 https://pubmed.ncbi.nlm.nih.gov/24658051/.

    Article  Google Scholar 

  142. Hsu J, Hodgins JJ, Marathe M, Nicolai CJ, Bourgeois-Daigneault MC, Trevino TN, et al. Contribution of NK cells to immunotherapy mediated by PD-1/PD-L1 blockade. J Clin Investig. 2018;128:4654–68 https://pubmed.ncbi.nlm.nih.gov/30198904/.

    Article  Google Scholar 

  143. Concha-Benavente F, Kansy B, Moskovitz J, Moy J, Chandran U, Ferris RL. PD-L1 mediates dysfunction in activated PD-1 þ NK cells in head and neck cancer patients. Cancer Immunol Res. 2018;6:1548–60 https://pubmed.ncbi.nlm.nih.gov/30282672/.

    Article  CAS  Google Scholar 

  144. Deuse T, Hu X, Agbor-Enoh S, Jang MK, Alawi M, Saygi C, et al. The SIRPα-CD47 immune checkpoint in NK cells. J Exp Med. 2021;218:e20200839 https://pubmed.ncbi.nlm.nih.gov/33416832/.

    Article  CAS  Google Scholar 

  145. Benson DM, Bakan CE, Mishra A, Hofmeister CC, Efebera Y, Becknell B, et al. The PD-1/PD-L1 axis modulates the natural killer cell versus multiple myeloma effect: a therapeutic target for CT-011, a novel monoclonal anti-PD-1 antibody. Blood. 2010;116:2286–94 https://pubmed.ncbi.nlm.nih.gov/20460501/.

    Article  CAS  Google Scholar 

  146. Beldi-Ferchiou A, Lambert M, Dogniaux S, Vély F, Vivier E, Olive D, et al. PD-1 mediates functional exhaustion of activated NK cells in patients with Kaposi sarcoma. Oncotarget. 2016;7:72961–77 https://pubmed.ncbi.nlm.nih.gov/27662664/.

    Article  Google Scholar 

  147. Liu Y, Cheng Y, Xu Y, Wang Z, Du X, Li C, et al. Increased expression of programmed cell death protein 1 on NK cells inhibits NK-cell-mediated anti-tumor function and indicates poor prognosis in digestive cancers. Oncogene. 2017;36:6143–53 https://pubmed.ncbi.nlm.nih.gov/28692048/.

    Article  CAS  Google Scholar 

  148. Vari F, Arpon D, Keane C, Hertzberg MS, Talaulikar D, Jain S, et al. Immune evasion via PD-1/PD-L1 on NK cells and monocyte/macrophages is more prominent in Hodgkin lymphoma than DLBCL. Blood. 2018;131:1809–19 https://pubmed.ncbi.nlm.nih.gov/29449276/.

    Article  CAS  Google Scholar 

  149. Zhang Q, Bi J, Zheng X, Chen Y, Wang H, Wu W, et al. Blockade of the checkpoint receptor TIGIT prevents NK cell exhaustion and elicits potent anti-tumor immunity. Nat Immunol. 2018;19:723–32 https://pubmed.ncbi.nlm.nih.gov/29915296/.

    Article  CAS  Google Scholar 

  150. André P, Denis C, Soulas C, Bourbon-Caillet C, Lopez J, Arnoux T, et al. Anti-NKG2A mAb is a checkpoint inhibitor that promotes anti-tumor immunity by unleashing both T and NK cells. Cell. 2018;175:1731–43 https://pubmed.ncbi.nlm.nih.gov/30503213/.

    Article  Google Scholar 

  151. McWhirter SM, Barbalat R, Monroe KM, Fontana MF, Hyodo M, Joncker NT, et al. A host type I interferon response is induced by cytosolic sensing of the bacterial second messenger cyclic-di-GMP. J Exp Med. 2009;206:1899–911 https://pubmed.ncbi.nlm.nih.gov/19652017/.

    Article  CAS  Google Scholar 

  152. Gauthier L, Morel A, Anceriz N, Rossi B, Blanchard-Alvarez A, Grondin G, et al. Multifunctional natural killer cell engagers targeting NKp46 trigger protective tumor immunity. Cell. 2019;177:1701–13 https://pubmed.ncbi.nlm.nih.gov/31155232/.

    Article  CAS  Google Scholar 

  153. Sarhan D, Brandt L, Felices M, Guldevall K, Lenvik T, Hinderlie P, et al. 161533 TriKE stimulates NK-cell function to overcome myeloid-derived suppressor cells in MDS. Blood Adv. 2018;2:1459–60 https://pubmed.ncbi.nlm.nih.gov/29941459/.

    Article  CAS  Google Scholar 

  154. Chang YH, Connolly J, Shimasaki N, Mimura K, Kono K, Campana D. A chimeric receptor with NKG2D specificity enhances natural killer cell activation and killing of tumor cells. Cancer Res. 2013;73:1777–86 https://pubmed.ncbi.nlm.nih.gov/23302231/.

    Article  CAS  Google Scholar 

  155. Parihar R, Rivas C, Huynh M, Omer B, Lapteva N, Metelitsa LS, et al. NK cells expressing a chimeric activating receptor eliminate MDSCs and rescue impaired CAR-T cell activity against solid tumors. Cancer. Immunol Res. 2019;7:363–75 https://pubmed.ncbi.nlm.nih.gov/30651290/.

    CAS  Google Scholar 

  156. Klingemann H. Are natural killer cells superior CAR drivers? Oncoimmunology. 2014;3:e28147 https://pubmed.ncbi.nlm.nih.gov/25340009/.

    Article  Google Scholar 

  157. Laskowski TJ, Biederstädt A, Rezvani K. Natural killer cells in antitumour adoptive cell immunotherapy. Nat Rev Cancer. 2022;22:557–75 https://www.nature.com/articles/s41568-022-00491-0.

    Article  CAS  Google Scholar 

  158. Eberl G, Colonna M, Santo JPD, McKenzie ANJ. Innate lymphoid cells: a new paradigm in immunology. Science. 2015;348:aaa6566 https://pubmed.ncbi.nlm.nih.gov/25999512/.

    Article  Google Scholar 

  159. Tait Wojno ED, Beamer CA. Isolation and identification of innate lymphoid cells (ILCs) for immunotoxicity testing. Methods Mol Biol. 2018;1803:353–70 https://pubmed.ncbi.nlm.nih.gov/29882149/.

    Article  Google Scholar 

  160. Diefenbach A, Colonna M, Koyasu S. Development, differentiation, and diversity of innate lymphoid cells. Immunity. 2014;41:354–65 https://pubmed.ncbi.nlm.nih.gov/25238093/.

    Article  CAS  Google Scholar 

  161. McKenzie ANJ, Spits H, Eberl G. Innate lymphoid cells in inflammation and immunity. Immunity. 2014;41:366–74 https://pubmed.ncbi.nlm.nih.gov/25238094/.

    Article  CAS  Google Scholar 

  162. Bernink JH, Peters CP, Munneke M, te Velde AA, Meijer SL, Weijer K, et al. Human type 1 innate lymphoid cells accumulate in inflamed mucosal tissues. Nat Immunol. 2013;14(14):221–9 https://pubmed.ncbi.nlm.nih.gov/23334791/.

    Article  CAS  Google Scholar 

  163. Mackay LK, Kallies A. Transcriptional regulation of tissue-resident lymphocytes. Trends Immunol. 2017;38:94–103 https://pubmed.ncbi.nlm.nih.gov/27939451/.

    Article  CAS  Google Scholar 

  164. Tait Wojno ED, Artis D. Emerging concepts and future challenges in innate lymphoid cell biology. J Exp Med. 2016;213:2229–48 https://pubmed.ncbi.nlm.nih.gov/27811053/.

    Article  Google Scholar 

  165. Licona-Limón P, Kim LK, Palm NW, Flavell RA. TH2, allergy and group 2 innate lymphoid cells. Nat Immunol. 2013;14:536–42 https://pubmed.ncbi.nlm.nih.gov/23685824/.

    Article  Google Scholar 

  166. Hwang YY, McKenzie ANJ. Innate lymphoid cells in immunity and disease. Adv Exp Med Biol. 2013;785:9–26 https://pubmed.ncbi.nlm.nih.gov/23456833/.

    Article  CAS  Google Scholar 

  167. Huntington ND, Carpentier S, Vivier E, Belz GT. Innate lymphoid cells: parallel checkpoints and coordinate interactions with T cells. Curr Opin Immunol. 2016;38:86–93 https://pubmed.ncbi.nlm.nih.gov/26736074/.

    Article  CAS  Google Scholar 

  168. Mjösberg J, Bernink J, Peters C, Spits H. Transcriptional control of innate lymphoid cells. Eur J Immunol. 2012;42:1916–23 https://pubmed.ncbi.nlm.nih.gov/22865043/.

    Article  Google Scholar 

  169. Klose CSN, Artis D. Innate lymphoid cells as regulators of immunity, inflammation and tissue homeostasis. Nat Immunol. 2016;17:765–74 https://pubmed.ncbi.nlm.nih.gov/27328006/.

    Article  CAS  Google Scholar 

  170. Klose CSN, Flach M, Möhle L, Rogell L, Hoyler T, Ebert K, et al. Differentiation of type 1 ILCs from a common progenitor to all helper-like innate lymphoid cell lineages. Cell. 2014;157:340–56 https://pubmed.ncbi.nlm.nih.gov/24725403/.

    Article  CAS  Google Scholar 

  171. Constantinides MG, McDonald BD, Verhoef PA, Bendelac A. A committed precursor to innate lymphoid cells. Nature. 2014;508:397–401 https://pubmed.ncbi.nlm.nih.gov/24509713/.

    Article  CAS  Google Scholar 

  172. Bal SM, Bernink JH, Nagasawa M, Groot J, Shikhagaie MM, Golebski K, et al. IL-1β, IL-4 and IL-12 control the fate of group 2 innate lymphoid cells in human airway inflammation in the lungs. Nat Immunol. 2016;17:636–45 https://pubmed.ncbi.nlm.nih.gov/27111145/.

    Article  CAS  Google Scholar 

  173. Ohne Y, Silver JS, Thompson-Snipes LA, Collet MA, Blanck JP, Cantarel BL, et al. IL-1 is a critical regulator of group 2 innate lymphoid cell function and plasticity. Nat Immunol. 2016;17:646–55 https://pubmed.ncbi.nlm.nih.gov/27111142/.

    Article  CAS  Google Scholar 

  174. Trabanelli S, Chevalier MF, Martinez-Usatorre A, Gomez-Cadena A, Salomé B, Lecciso M, et al. Tumour-derived PGD2 and NKp30-B7H6 engagement drives an immunosuppressive ILC2-MDSC axis. Nat Commun. 2017;8:593 https://pubmed.ncbi.nlm.nih.gov/28928446/.

    Article  Google Scholar 

  175. Ikutani M, Yanagibashi T, Ogasawara M, Tsuneyama K, Yamamoto S, Hattori Y, et al. Identification of innate IL-5–producing cells and their role in lung eosinophil regulation and antitumor immunity. J Immunol. 2012;188:703–13 https://pubmed.ncbi.nlm.nih.gov/22174445/.

    Article  CAS  Google Scholar 

  176. Saranchova I, Han J, Huang H, Fenninger F, Choi KB, Munro L, et al. Discovery of a metastatic immune escape mechanism initiated by the loss of expression of the tumour biomarker Interleukin-33. Sci Rep. 2016;6:30555 https://pubmed.ncbi.nlm.nih.gov/27619158/.

    Article  CAS  Google Scholar 

  177. Zaiss DMW, Gause WC, Osborne LC, Artis D. Emerging functions of amphiregulin in orchestrating immunity, inflammation, and tissue repair. Immunity. 2015;42:216–26 https://pubmed.ncbi.nlm.nih.gov/25692699/.

    Article  CAS  Google Scholar 

  178. Bando JK, Nussbaum JC, Liang H-E, Locksley RM. Type 2 innate lymphoid cells constitutively express arginase-I in the naïve and inflamed lung. J Leukoc Biol. 2013;94:877–84 https://pubmed.ncbi.nlm.nih.gov/23924659/.

    Article  CAS  Google Scholar 

  179. Fuchs A, Vermi W, Lee JS, Lonardi S, Gilfillan S, Newberry RD, et al. Intraepithelial type 1 innate lymphoid cells are a unique subset of il-12- and il-15-responsive ifn-γ-producing cells. Immunity. 2013;38:769–81 https://pubmed.ncbi.nlm.nih.gov/23453631/.

    Article  CAS  Google Scholar 

  180. Bernink JH, Krabbendam L, Germar K, de Jong E, Gronke K, Kofoed-Nielsen M, et al. Interleukin-12 and -23 control plasticity of Cd127+ group 1 and group 3 innate lymphoid cells in the intestinal Lamina Propria. Immunity. 2015;43:146–60.

    Article  CAS  Google Scholar 

  181. Pearson C, Thornton EE, McKenzie B, Schaupp AL, Huskens N, Griseri T, et al. ILC3 GM-CSF production and mobilisation orchestrate acute intestinal inflammation. Elife. 2016;5:e10066 https://pubmed.ncbi.nlm.nih.gov/26780670/.

    Article  Google Scholar 

  182. Griseri T, Arnold IC, Pearson C, Krausgruber T, Schiering C, Franchini F, et al. Granulocyte macrophage Colony-stimulating factor-activated eosinophils promote Interleukin-23 driven chronic colitis. Immunity. 2015;43:187–99 https://pubmed.ncbi.nlm.nih.gov/26200014/.

    Article  CAS  Google Scholar 

  183. Liu J, Duan Y, Cheng X, Chen X, Xie W, Long H, et al. IL-17 is associated with poor prognosis and promotes angiogenesis via stimulating VEGF production of cancer cells in colorectal carcinoma. Biochem Biophys Res Commun. 2011;407:348–54 https://pubmed.ncbi.nlm.nih.gov/21396350/.

    Article  CAS  Google Scholar 

  184. Tosolini M, Kirilovsky A, Mlecnik B, Fredriksen T, Mauger S, Bindea G, et al. Clinical impact of different classes of infiltrating T cytotoxic and helper cells (Th1, Th2, Treg, Th17) in patients with colorectal cancer. Cancer Res. 2011;71:1263–71 https://pubmed.ncbi.nlm.nih.gov/21303976/.

    Article  CAS  Google Scholar 

  185. King RL, Goodlad JR, Calaminici M, Dotlic S, Montes-Moreno S, Oschlies I, et al. Lymphomas arising in immune-privileged sites: insights into biology, diagnosis, and pathogenesis. Virchows Arch. 2020;476:647–65 https://pubmed.ncbi.nlm.nih.gov/31863183/.

    Article  Google Scholar 

  186. Kridel R, Telio D, Villa D, Sehn LH, Gerrie AS, Shenkier T, et al. Diffuse large B-cell lymphoma with testicular involvement: outcome and risk of CNS relapse in the rituximab era. Br J Haematol. 2017;176:210–21 https://pubmed.ncbi.nlm.nih.gov/27739058/.

    Article  CAS  Google Scholar 

  187. Bromberg JEC, Issa S, Bakunina K, Minnema MC, Seute T, Durian M, et al. Rituximab in patients with primary CNS lymphoma (HOVON 105/ALLG NHL 24): a randomised, open-label, phase 3 intergroup study. Lancet Oncol. 2019;20:216–28 http://www.ncbi.nlm.nih.gov/pubmed/30630772.

    Article  CAS  Google Scholar 

  188. Radke J, Ishaque N, Koll R, Gu Z, Schumann E, Sieverling L, et al. The genomic and transcriptional landscape of primary central nervous system lymphoma. Nat Commun. 2022;13:1–20 https://www.nature.com/articles/s41467-022-30050-y.

    Article  Google Scholar 

  189. Chapuy B, Roemer MGM, Stewart C, Tan Y, Abo RP, Zhang L, et al. Targetable genetic features of primary testicular and primary central nervous system lymphomas. Blood. 2016;127:869–81 http://www.bloodjournal.org/cgi/doi/10.1182/blood-2015-10-673236.

    Article  CAS  Google Scholar 

  190. Ngo VN, Young RM, Schmitz R, Jhavar S, Xiao W, Lim K-H, et al. Oncogenically active MYD88 mutations in human lymphoma. Nature. 2011;470:115–9 http://www.ncbi.nlm.nih.gov/pubmed/21179087.

    Article  CAS  Google Scholar 

  191. Challa-Malladi M, Lieu YK, Califano O, Holmes A, Bhagat G, Murty V v., et al. Combined genetic inactivation of Beta2-microglobulin and CD58 reveals frequent escape from immune recognition in diffuse large B-cell lymphoma. Cancer Cell 2011;20:728. /pmc/articles/PMC3660995/.

    Article  CAS  Google Scholar 

  192. Steidl C, Shah SP, Woolcock BW, Rui L, Kawahara M, Farinha P, et al. MHC class II transactivator CIITA is a recurrent gene fusion partner in lymphoid cancers. Nature. 2011;471:377–81 https://pubmed.ncbi.nlm.nih.gov/21368758/.

    Article  CAS  Google Scholar 

  193. Marcelis L, Antoranz A, Delsupehe AM, Biesemans P, Ferreiro JF, Debackere K, et al. In-depth characterization of the tumor microenvironment in central nervous system lymphoma reveals implications for immune-checkpoint therapy. Cancer Immunol Immunother. 2020;69:1751–66 https://pubmed.ncbi.nlm.nih.gov/32335702/.

    Article  CAS  Google Scholar 

  194. Guo J, Tang Q. Recent updates on chimeric antigen receptor T cell therapy for hepatocellular carcinoma. Cancer Gene Ther. 2021;28:1075–87 https://pubmed.ncbi.nlm.nih.gov/33500535/.

    Article  CAS  Google Scholar 

  195. Mondello P, Brea EJ, de Stanchina E, Toska E, Chang AY, Fennell M, et al. Panobinostat acts synergistically with ibrutinib in diffuse large B cell lymphoma cells with MyD88 L265 mutations. JCI Insight. 2017;2:e90196 http://www.ncbi.nlm.nih.gov/pubmed/28352655.

    Article  Google Scholar 

  196. Grommes C, Pastore A, Palaskas N, Tang SS, Campos C, Schartz D, et al. Ibrutinib unmasks critical role of Bruton tyrosine kinase in primary CNS lymphoma. Cancer Discov. 2017;7:1018–29 http://cancerdiscovery.aacrjournals.org/lookup/doi/10.1158/2159-8290.CD-17-0613.

    Article  CAS  Google Scholar 

  197. Lionakis MS, Dunleavy K, Roschewski M, Widemann BC, Butman JA, Schmitz R, et al. Inhibition of B cell receptor signaling by Ibrutinib in primary CNS lymphoma. Cancer Cell. 2017;31:833–843.e5 http://www.ncbi.nlm.nih.gov/pubmed/28552327.

    Article  CAS  Google Scholar 

  198. Mondello P, Mian M, Bertoni F. Primary central nervous system lymphoma: novel precision therapies. Crit Rev Oncol Hematol. 2019;141:139–45 http://www.ncbi.nlm.nih.gov/pubmed/31295667.

    Article  Google Scholar 

  199. Nabet BY, Esfahani MS, Moding EJ, Hamilton EG, Chabon JJ, Rizvi H, et al. Noninvasive early identification of therapeutic benefit from immune checkpoint inhibition. Cell. 2020;183:363–76 https://pubmed.ncbi.nlm.nih.gov/33007267/.

    Article  CAS  Google Scholar 

  200. Tavaré R, Escuin-Ordinas H, Mok S, McCracken MN, Zettlitz KA, Salazar FB, et al. An effective immuno-PET imaging method to monitor CD8-dependent responses to immunotherapy. Cancer Res. 2016;76:73–82 https://pubmed.ncbi.nlm.nih.gov/26573799/.

    Article  Google Scholar 

  201. Farwell MD, Gamache RF, Babazada H, Hellmann MD, Harding JJ, Korn R, et al. CD8-targeted PET imaging of tumor-infiltrating T cells in patients with Cancer: a phase i first-in-humans study of 89Zr-Df-IAB22M2C, a radiolabeled anti-CD8 Minibody. J Nucl Med. 2022;63:720–6 https://pubmed.ncbi.nlm.nih.gov/34413145/.

    CAS  Google Scholar 

  202. Gosmann D, Russelli L, Weber WA, Schwaiger M, Krackhardt AM, D’Alessandria C. Promise and challenges of clinical non-invasive T-cell tracking in the era of cancer immunotherapy. EJNMMI Res. 2022;12:5 https://pubmed.ncbi.nlm.nih.gov/35099641/.

    Article  CAS  Google Scholar 

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WLN and PM reviewed the literature, designed, and wrote the manuscript; SMA revised the paper. All the authors approved it.

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Ng, W.L., Ansell, S.M. & Mondello, P. Insights into the tumor microenvironment of B cell lymphoma. J Exp Clin Cancer Res 41, 362 (2022). https://doi.org/10.1186/s13046-022-02579-9

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Keywords

  • Tumor microenvironment
  • B-cell lymphoma
  • T cells
  • T follicular helper cells
  • T regulatory cells
  • Tumor-associated macrophages
  • Myeloid-derived suppressor cells
  • Cancer-associated fibroblasts