A Comprehensive Exploration of Agents Targeting Tumor Microenvironment: Challenges and Future Perspectives

Abstract

The tumor microenvironment (TME) encompasses the complex and diverse surroundings in which tumors arise. Emerging insights highlight the TME's critical role in tumor development, progression, metastasis, and treatment response. Consequently, the TME has attracted significant research and clinical interest, leading to the identification of numerous novel therapeutic targets. Advances in molecular technologies now enable detailed genomic and transcriptional analysis of cancer cells and the TME and the integration of microenvironmental data to the tumor genomic landscape. This comprehensive review discusses current progress in targeting the TME for drug development, addressing associated challenges, strategies for modulating the pro-tumor microenvironment, and the discovery of new targets.

INTRODUCTION

The tumor microenvironment (TME) plays a crucial role in regulating the basic survival of tumor cells and supporting their functions.[1] The development and persistence of cancer—such as maintaining cell proliferation, evading apoptosis, stimulating angiogenesis, promoting invasion and metastasis, inciting tumor-promoting inflammation, and evading immune surveillance—are influenced, to varying degrees, by the complex interactions within the TME.[2] A significant portion of patients with metastatic disease will inevitably develop resistance to treatment following cancer therapy, and a comprehensive understanding of the dynamic changes occurring within the TME during tumor progression is essential for the development of targeted therapeutic approaches.[2,3] This resistance arises from a spectrum of biological mechanisms, encompassing DNA repair, genetic and epigenetic alterations, metabolic reprogramming, heightened angiogenesis, and modifications in the TME[2,3] (Figure 1). This comprehensive review was performed using the PubMed database, and articles approaching TME components were non-systematically pooled by the authors. We aimed to delve into the latest advancements in TME research, outline the obstacles and potential pathways for TME modulation, and provide new perspectives and potential breakthroughs in cancer therapy, particularly in overcoming treatment resistance associated with the TME.[4] In addition, we examined the literature covering the emerging technologies and the role of artificial intelligence in unraveling the complexities of the TME.

Figure 1.

The tumor microenvironment components. The tumor microenvironment is a complex network of diverse cells and secreted factors that serve as targets for anticancer treatments. It includes various cell types like cancer cells, immune cells (such as T and B lymphocytes, TAMs, DCs, NK cells, myeloid-derived suppressor cells, neutrophils, and eosinophils), stromal cells (like CAFs, pericytes, and mesenchymal stromal cells), as well as vascular networks and tissue-specific cells such as neurons and adipocytes. These cells release components like ECM, growth factors, cytokines, and EVs, crucial for communication within the TME and beyond. CAF: cancer-associated fibroblast; DC: dendritic cell; ECM: extracellular matrix; NK: natural killer; TAM: tumor-associated macrophage; TME: tumor microenvironment.

TARGETING TME COMPONENTS

Dendritic Cells

The engagement of the FMS-like receptor tyrosine kinase-3 (FLT3) with its ligand, FLT3L, plays a crucial role in regulating dendritic cells (DCs). When FLT3L is administered, it leads to the expansion of circulating DCs in vivo, followed by their migration to various tissues.[5] This process not only increases the number of DCs in the TME but also promotes DC maturation, enhancing the priming of antitumor T cells. Recombinant FLT3L, such as CDX-301, has been demonstrated to expand DCs and hematopoietic precursors in healthy human volunteers.[6] Although phase 1 and 2 trials (ClinicalTrials.gov ID: NCT00003431) have confirmed the immunogenicity and safety of CDX-301, its efficacy as a monotherapy in tumor remission remains to be established. A strategy combining radiation and CDX-301 is currently being studied in phase II trials for patients with advanced non–small cell lung cancer (NSCLC) (NCT04491084). In addition, a combination approach involving radiotherapy, FLT3L, and the costimulatory molecule CD40 is undergoing phase II trials in patients with lung cancer (NCT04491084).

Granulocyte-macrophage colony-stimulating factor (GM-CSF) regulates the development of myeloid cell types in response to stress, infections, and cancers. Imbalances in GM-CSF levels can either hinder or promote cancer progression, depending on factors like the amount of GM-CSF, cancer type, and tumor environment.[7] Treatments targeting granulocyte-macrophage colony-stimulating factor (GM-CSF) act as a booster of antitumor immunity by promoting the differentiation of DCs. Current clinical and preclinical approaches have evaluated treatments like GM-CSF monotherapy as well as GM-CSF combined with chemotherapy, monoclonal antibodies, or cancer vaccines.

DC vaccines involve loading DCs with tumor-associated antigens (TAAs) to trigger an immune response in patients, promoting the development of T cells for a targeted antitumor effect.[8] DCs are derived from CD34-positive precursor cells or monocytes and activated by Toll-like receptor (TLR) agonists and cytokines like interleukin 1 beta (IL-1β), interleukin 6 (IL-6), tumor necrosis factor alfa (TNF-α), and prostaglandin E2 (PGE2). This activation leads to their maturation into functional DCs. Mature DCs express major histocompatibility complex (MHC), costimulatory molecules, and cytokines, ultimately inducing a T helper 1 cells (Th1) immune response.[9] The effectiveness of inducing DC maturation is a critical determinant in the success or failure of DC vaccine treatments.[10]

Sipuleucel-T, a DC-based immunotherapy, for instance, comprises autologous peripheral blood mononuclear cells enriched for antigen-presenting cells, which are cultured ex vivo with recombinant PA2024 protein as a source of antigens to enhance their T lymphocyte activation properties. Following reinfusion into patients with asymptomatic prostate cancer with metastatic castration-resistant disease, this approach led to a modest median overall survival improvement of 4.1 months compared with placebo, resulting in United States Food and Drug Administration (FDA) approval for use in this setting.[11]

Recent progress in novel DC vaccination approaches holds significant promise, particularly in treating solid tumors. As an example, in individuals with melanoma, the combination of a high-dose systemic interferon alfa-2b (IFN-α2b) and a DC vaccine demonstrates a significant extension in both overall survival and progression-free survival compared with patients treated with the DC vaccine alone.[10] An overview of DC-based therapeutics in solid tumors is provided in Table 1.

Table 1.

Dendritic-cell–based therapeutics in solid tumors

Target and Drug Combination or Vaccine Type	Therapeutic Strategy	Type of Cancer	ClinicalTrials.gov ID
FLT3L THERAPIES
	FLT3L in treating patients with metastatic colorectal cancer	Metastatic colorectal cancer	NCT00003431[117]
	CD40 agonist antibody (CDX-1140) alone vs. combination with recombinant FLT3L (CDX-301) vs. combination with pembrolizumab vs. combination with chemotherapy	Multiple cancer types	NCT03329950[118]
	FLT3L (CDX-301) with CD40 agonist antibody (CDX-1140) and stereotactic radiotherapy vs. stereotactic radiotherapy alone	Non-small cell lung cancer	NCT04491084[119]
	CDX-1401 and Poly-ICLC vaccine therapy with or without CDX-301 in treating patients with stage IIB-IV melanoma	Stage IIB-IV melanoma	NCT02129075[120]
	Dose escalation of adenovirus gene transfer that drives direct tumor killing and FLT3L expression	Malignant glioma and glioblastoma multiforme	NCT01811992[121]
	Recombinant FLT3L alone or with melanoma-associated peptides	Stage IV melanoma, stage IV renal cell cancer, recurrent renal cell cancer and recurrent melanoma	NCT00019396[122]
GM-CSF THERAPIES
Monotherapy	GM-CSF monotherapy	Prostate cancer; ovarian cancer; kidney cancer; colon and rectal cancer	NCT00908141[123] NCT00157573[124] NCT00006483[125]
GM-CSF with chemotherapy	GM-CSF + different chemotherapy	Colon and rectal cancer	NCT00257322 [126]
	GM-CSF + docetaxel GM-CSF + mitoxantrone	Prostate cancer	NCT00488982[127] NCT00477087 [128]
GM-CSF with monoclonal antibody	Leukine (sargramostim) + herceptin	Breast cancer	NCT00429104[129]
	Leukine (sargramostim) + edrecolomab	Colorectal cancer	NCT00002664[130]
	GM-CSF + nivolumab + ipilimumab	Metastatic cutaneous melanoma	NCT02339571[131]
	PSA/IL-2/GM-CSF (complete vaccine)	Prostate cancer	NCT02058680[132] NCT00140374[133] NCT00799110[134] NCT01479244[135] NCT00448409[136]
	GVAX/ vaccine (GM-CSF secreting prostate cancer vaccine) GM-CSF + dendritic cell/tumor fusion vaccine	Prostate cancer	NCT00003002[137]
	Leukine (sargramostim) + NeuVaxTM vaccine (E75 synthetic peptide combined with GM-CSF)	Ovarian cancer Primary peritoneal cancer Fallopian tube cancer	NCT03645148[138]
	GM-CSF + TroVax/ (vaccinia virus encoding the human oncofetal antigen 5T4)	Breast cancer with low to intermediate HER2 expression	NCT01789099[139]
	Leukine (sargramostim) + HER-2/neu peptide vaccine	Prostate cancer Breast cancer Lung cancer	NCT04382664[140]
	Leukine (sargramostim) + iNeo Vac P01 (peptide vaccine)	Ovarian cancer Pancreatic cancer	NCT04040231[141]
	GM-CSF + UV1 synthetic peptide vaccine	Non–small cell lung cancer	NCT03600350[142]
GM-CSF with cancer vaccines and monoclonal antibody	GM-CSF + UV1 vaccine + ipilimumab + nivolumab	Melanoma Lung cancer	NCT04382664[140]
	Leukine (sargramostim) + galinpepimut-S (WT1 peptide vaccine) + nivolumab	Mesothelioma Pleural mesothelioma Wilms tumor	NCT04300244[143] NCT04040231[144]
	Leukine (sargramostim) + pTVG-HP (plasmid DNA vaccine) + nivolumab	Prostate cancer	NCT03600350[142]
DENDRITIC CELL VACCINES
Conventional MoDC-based	Sipuleucel-T and ipilimumab	Advanced prostate cancer	NCT01832870[145]
Conventional MoDC-based	Combining sipuleucel-T (SipT) and ipilimumab (Ipi)	Metastatic castration-resistant prostate cancer (mCRPC)	NCT01804465[146]
Conventional MoDC-based	Glycosylated recombinant human interleukin-7 (CYT107) after vaccine therapy	mCRPC	NCT01881867[147]
Conventional MoDC-based	Sipuleucel-T or placebo	mCRPC	NCT00065442[11]
Biomaterial-based	WDVAX vaccine	Metastatic melanoma	NCT01753089[148]
mRNA-based	mRNA electroporated autologous dendritic cells	Stage III/IV melanoma	NCT01676779[149]
DCsEV-based	tumor antigen-loaded dendritic cell-derived exosomes	Non–small cell lung cancer	NCT01159288[150]

CD40: cluster of differentiation 40; CYT107: glycosylated recombinant human interleukin-7; DCsEV: dendritic cell-derived exosomes; FLT3L: fms-like tyrosine kinase 3 ligand; GM-CSF: granulocyte-macrophage colony-stimulating factor; MHC: major histocompatibility complex; NCT: national clinical trial; PGE2: prostaglandin E2; SipT: sipuleucel-T; Th1: T helper 1; TLR: toll-like receptor; VEGF: vascular endothelial growth factor; VEGFR: vascular endothelial growth factor receptor; WT1: wilms' tumor 1; MoDC: monocyte derived dendritic cells; mRNA: messenger RNA; WDVAX: poly(lactic-co-glycolic acid-based scaffold vaccine.

Blood Vessels

Hypoxia, a hallmark of the TME of various cancer types, can attenuate the efficacy of chemotherapy and radiotherapy, trigger the secretion of immune-suppressive cytokines, and promote the recruitment and proliferation of immune-regulatory cell population. [12–14] More recently, studies have been exploring the idea of vascular normalization. One of the notable advantages of vascular normalization is its potential for synergizing with other anticancer treatments, including chemotherapy, radiotherapy, and immunotherapy.[15–17] One classic example from clinical practice is the metastatic clear cell renal cell carcinoma (mRCC) treatment, in which combinations of anti-vascular endothelial growth factor (VEGF) agents with immune checkpoint inhibitors (ICIs) provide superior disease control than to single-agent VEGF-targeted therapies, signaling a shift in first-line treatment approaches.[18] Achieving vascular normalization poses certain challenges. The optimal dose of anti-angiogenic therapy and the timing of effective normalization, known as the “normalization window,” are tightly limited and vary between individuals, which presents obstacles to its clinical application.[19] Thus far, most of the mechanistic understanding regarding vessel normalization has been derived from inhibiting VEGF signaling pathways with moderate-to-low doses of monoclonal antibodies or small-molecule inhibitors targeting tyrosine kinase receptors (Table 2). However, given that VEGF is a critical survival factor for endothelial cells, sustained inhibition, even at low doses, ultimately results in vessel demise or the increased expression of alternative angiogenic factors.[20] Furthermore, the resistance to VEGF targeting regulated by immunosuppression suggests the involvement of additional regulators in tumor promotion through immunomodulation. These findings indicate that analyzing the immune profile within the altered TME could offer the potential for enhancing treatment efficacy through a combination of vessel-targeting and immunotherapy strategies.[21] Another potential mechanism that indirectly reduces the proliferation of endothelial cells is by acting on the mTOR/AP-1/VEGF pathway and consequently inhibiting angiogenesis.[22] In addition, the hypoxia-inducible factor (HIF)-2α inhibitor belzutifan recently demonstrated a significant clinical benefit among patients with mRCC previously treated with VEGF inhibitors and ICI.[23]

Table 2.

Agents targeting the vasculature currently in clinical use

Signaling	Targets	Drug
VEGF signaling	VEGF	Bevacizumab
	VEGFR	IMC-1121B (Ramucirumab)
	VEGFR	Sunitinib (Sutent)
	VEGFR	Sorafenib (Nexavat)
	VEGFR	Pazopanib (Votrient)
FGF signaling	FGFR	BMS-582664 (Brivanib)
PDGF signaling	PDGF	SU6668
EGFR signaling	EGFR	Cetuximab (Erbitux)
	EGFR	Panitumumab
	EGFR	Erlotinib
	EGFR	Gefitinib
mTOR signaling	mTOR	Everolimus

EGFR: epidermal growth factor receptor; FGF: fibroblast growth factor; mTOR: mammalian target of rapamycin; PDGF: platelet-derived growth factor; VEGF: vascular endothelial growth factor.

Macrophages

Experimental models have revealed that tumor cells could recruit and polarize macrophages to an M2-like phenotype, called tumor-associated macrophages (TAMs), through the secretion of specific chemokines such as the C–C motif chemokine family (CCL2, CCL3, and CCL5).[24–26] Then, these TAMs facilitate the acquisition of malignant traits by tumor cells, such as proliferation, angiogenesis, immune evasion, and metastasis.[27] Some studies have translated these experimental data to clinical settings, such as the observation of a statistically positive association of inferior survival with high tissue levels of CCL5 through microarray assay in patients with breast-localized phyllodes tumors.[26] Similar results were also demonstrated by Yang et al.,[24] who found a positive correlation between tumor colony-stimulating factor 1 receptor (CSF-1R), a tyrosine kinase transmembrane receptor involved in tissue macrophage maintenance, expression through immunohistochemistry, and more aggressive clinical and pathological tumoral features, besides inferior survival in a cohort of 268 patients with resected clear cell renal cell carcinoma.[28,29] Corroborating these findings, a meta-analysis involving 55 studies with a total of 8692 patients diagnosed with solid tumors also showed that an increase in the density of TAMs, identified through immunohistochemistry for CD68 in tumor samples, was associated with a decrease in overall survival (1.15-fold higher relative risk for mortality), which was more pronounced in breast, endometrial, prostate, bladder, ovary, and urothelial cancers.[30]

The previous analysis highlighted that the clinical benefit from some cytotoxic chemotherapy agents may derive in part from their actions on TAMs by reducing their tumoral population (e.g., structurally related marine-derived compounds trabectedin and lurbinectedin) or inducing phenotypic changes toward an M1 profile (e.g., the anti-metabolites gemcitabine and 5-fluorouracil).[31,32]

Aiming to deplete the TAM population, pexidartinib, a CSF1R inhibitor, was evaluated in a phase 2 dose extension study with a total of 23 patients harboring tenosynovial giant-cell tumors. From these, 12 had a partial response with a median duration of response above 8 months, and 7 had stable disease.[33] A posterior phase 3 trial has confirmed pexidartinib efficacy in this setting, resulting in its FDA approval. Although it was tolerable in most patients, a few cases of liver failure have resulted in a Boxed Warning with the FDA approval.[34] Other phase I trials have assessed CSF1R blocked (with antibodies or small molecules) in combination with cytotoxic agents or immunotherapy in different histologies, and efficacy studies are necessary.[35]

Blocking the chemokine-dependent recruitment of TAMs was assessed in phase 1 trials based on combination antibodies or small molecules with cytotoxic agents with modest tumor activity. Carlumab, an anti-CCL2 monoclonal antibody, presented mild efficacy (one partial response in 53 patients) in combination with cytotoxic standard chemotherapy in a phase 1b trial in individuals harboring solid tumors. Although a brief initial reduction in serum CCL2 was followed by its increase along chemotherapy treatments, non-distinct new adverse events regarding standard agents were related.[36] A CCL2 receptor blocker, PF-04136309, was analyzed for patients with metastatic ductal pancreatic cancer in combination with nab-paclitaxel and gemcitabine in the phase 1b study. Besides a non-increase in the objective response rate of 23.8%, a high incidence of pulmonary toxicity, one case with grade 4, was related.[37]

Despite this biological rationale and preclinical evidence, the combination of motolimod, a TLR8 agonist, to the EXTREME regimen (combination therapy using cetuximab antibody and platinum-based chemotherapy) in a randomized phase 2, double-blinded, placebo-controlled trial with patients diagnosed with recurrent/metastatic squamous cell carcinoma of the head and neck did not demonstrate the gain in progression-free survival or overall survival. Otherwise, a statistical benefit in these two endpoints was demonstrated in patients with human papilloma virus (HPV)–positive oropharyngeal cancer. The addition of motolimod was associated with a higher incidence of adverse events related to local injection reactions, acneiform eruptions, chills, and pyrexia.[38] Promising results were achieved with the combination of pembrolizumab and intratumoral vidutolimod, a TLR9 agonist, in a phase 1b study involving 44 patients with advanced melanoma who had never responded to previous anti-programmed cell death 1 (PD-1) therapy. This combination resulted in an objective response rate of 25% and a satisfactory safety profile.[39]

In a distinct mechanism of pattern recognition TLR activation, CD40 signaling can induce an epigenetic reprogramming to the end of polarizing macrophages toward proinflammatory and anti-tumoral phenotypes experimentally.[40] These findings were corroborated in a phase 2 trial of sotigalimab, a CD40 agonistic antibody, in combination with nivolumab that achieved an overall response rate of 15%, most of them lasting more than 18 months, in 38 patients with metastatic melanoma who had previously progressed on anti-PD1 therapy. In this trial, sotigalimab-related grade 3 adverse events were evidenced in 13% and have been represented as systemic inflammatory reactions.[41]

Despite the description of many mechanisms in vivo and in vitro justifying the pivotal role of TAMs in many steps of the natural history of tumors, the clinical diffuse use of therapies targeting many aspects of the biology of these cells still needs more clinical evidence of benefit, which could be achieved upon appropriate patient selection based on biomarkers in large clinical trials.

T Cells

Immune checkpoint inhibitors

ICIs are a cancer treatment strategy that enhances T-cell responses within the TME. Certain molecules in the co-stimulatory pathway send inhibitory signals to activated T cells, regulating the strength of the immune response and functioning as “checkpoint” molecules.[42] The most recognized T-cell checkpoint molecules are cytotoxic T lymphocyte antigen 4 (CTLA4) and PD-1. Research advancements on these checkpoint molecules have led to the development of T-cell targeting antibodies that exhibit high efficacy across various cancers.[1] Two of the most evolving checkpoint inhibition approaches widely used in the past decade involve blocking the PD-1/PD-L1 and CTLA-4 pathways.[42] Other targets, including inhibitory receptors such as T-cell immunoglobulin and mucin 3 (Tim-3), V-domain immunoglobulin suppressor of T-cell activation (VISTA), T-cell immunoreceptor with immunoglobulin and ITIM domain (TIGIT), and lymphocyte activation gene 3 (Lag-3), as well as activating molecules like OX40 (CD134) and glucocorticoid-induced TNFR-related protein (GITR), are currently under investigation.[42,43]

Cellular therapy

Tumor-infiltrating lymphocytes (TILs) are a specific type of immune cell known as T cells. These cells identify and attack antigens on the surface of cancer cells, penetrating solid tumors to destroy them. When a tumor is surgically removed from a patient, tissue samples are sent to a lab where TILs are extracted and cultivated over 3 weeks, allowing them to multiply into billions of cells. Before reinfusing the TILs into the patient, the individual undergoes chemotherapy and receives IL-2, an immune-stimulating chemical. This treatment temporarily depletes existing immune cells, creating space for the newly introduced TILs.[44]

Patients diagnosed with stage IIIC or IV melanoma, who had experienced disease progression following treatment with checkpoint inhibitors or BRAF/MEK targeted therapy (for those harboring BRAF V600 mutations), underwent extraction and ex vivo expansion of tumor tissue-derived T cells via a controlled manufacturing process (Lifileucel). Following nonmyeloablative lymphodepleting cytotoxic treatment, autologous reinjection of Lifileucel was administered, followed by up to six doses of IL-2. Encouraging outcomes from this single-arm trial, including an overall response rate of 31.5% (with a recommended dosing range of 7.5-72 × 10⁹ viable cells) and a median duration of response not yet reached, led to its FDA-accelerated approval for these refractory patients.[45] Also, the combination of TILs and ICIs is being evaluated in a phase I clinical trial (NCT05576077).

CAR T cell

The T-cell receptor (TCR) can be engineered to recognize a specific antigen and augment a targeted immune response. Building on this strategy, chimeric antigen receptor (CAR) T cells have been developed, revolutionizing the treatment landscape for certain refractory tumors.[46] Supported by compelling clinical trial data, CD19-targeted and B cell maturation antigen-targeted CAR T cells have received FDA approval for the treatment of patients with B cell lymphoma,[47] B cell acute lymphoblastic leukemia,[48] and multiple myeloma,[49] respectively, who have relapsed or progressed following prior therapies. These approaches have demonstrated elevated rates of complete and durable responses in either these or the other hematological malignancies.[50,51]

Regarding solid tumors, CAR T-cell trials have shown promising albeit less robust preliminary outcomes in neoplasms with historically poor prognoses and resistance to conventional treatments. A phase I/II clinical trial (NCT00902044) demonstrated encouraging outcomes using HER2 CAR T cells in the treatment of 19 patients with HER2-positive sarcomas, including 16 osteosarcomas, one primitive neuroectodermal tumor, one Ewing sarcoma, and one protofibroblastic small round cell tumor.[51]

IL-13Rα2 is significantly expressed in glioblastoma (GBM) tumor cells but rarely found in normal brain cells, making it a compelling target for CAR T-cell therapy in glioblastoma. In a study by Brown and colleagues[52] (NCT02208362), multi-dose treatment with IL-13Rα2-CAR T cells led to complete tumor regression for almost 8 months in a patient with disseminated glioblastoma. Another target in GBM tumors, epidermal growth factor receptor (EGFR), was examined in a phase I clinical trial in which 10 patients with recurrent EGFRvIII+ glioblastoma were treated with EGFRvIII engineered CAR T-cells (NCT02209376).[53] This study demonstrated an antitumor effect with a median overall survival (OS) of approximately 8 months in all patients. Other CAR T-cell targets in solid tumor include MUC1, CD133, MSLN, CEA, and GD2.[54] However, these CAR-T trials frequently report high incidences of inflammatory reactions, highlighting the need for comprehensive support from specialized teams to manage these cases.[55]

Recently, CAR natural killer (NK) cells and CAR-macrophages (CAR-M) have been introduced as alternatives or complements to CAR T-cell therapy for solid tumors. CAR NK cells might be a favorable substitute for CAR T cells because they do not require human leukocyte antigen (HLA) compatibility and have limited toxicity.[54] However, like CAR T cells, CAR NK cells face challenges such as migration to the tumor site, persistence in the immunosuppressive TME, and transduction.[54] Regarding CAR-M, several limitations are associated with their bioengineering, storage, expansion, persistence in the TME, and toxicity.[54]

Regulatory T cells

In the TME, regulatory T cells (Tregs) play multiple roles, particularly in suppressing T-cell activation.[56] Currently, there is no dedicated Treg-targeted therapy in oncology. However, research indicates that Tregs can also express the membrane receptors CTLA-4, PD-1, LAG3, and TIGIT,[56] which could be targetable with ICIs.[57]

Several strategies have been proposed to boost antitumor immunity, including depleting Tregs in the TME using kinase inhibitors, low-dose cyclophosphamide, and anti-CD25 antibodies. For example, sunitinib has shown effectiveness in renal cell carcinoma,[58] and metronomic cyclophosphamide has shown promise in patients with breast cancer.[59] In addition, targeting co-stimulatory signals like OX40, GITR, ICOS, and TNFR2, as well as blocking inhibitory cytokines derived from Tregs, such as IL-10, IL-35, and transforming growth factor (TGF)-β, can further diminish Treg suppressive functions within the TME.[60–64]

T-cell bispecific antibodies

A significant obstacle to the effectiveness of T-cell-based immunotherapy is the inadequate infiltration of T cells into the TME. To tackle this issue, T-cell engaging bispecific antibodies (bsAbs) have been developed. These bsAbs are engineered to bind simultaneously to an antigen on tumor cells and a surface molecule on T cells, thereby combining the specificity of two antibodies into a single molecule to efficiently redirect T cells to the tumor cells.[65]

One example involves targeting the CD3 chain of the TCR, due to its invariant nature, while the other arm targets tumor cell antigens like CD19, which is specifically expressed in hematologic malignancies. This approach led to the development and FDA approval of blinatumomab, a CD19/CD3 bsAb, for treating B-cell precursor acute lymphoblastic leukemia.[66] Currently, a more complex design of trispecific antibodies targeting CD3 and CD137 using a dual-specific Fab is also being tested among solid tumors expressing CLDN-6 (NCT05735366).

The bispecific T-cell engager (BiTE), a bsAb lacking an Fc domain, comprises variable regions from an antitumor cell antigen and an anti-CD3 antibody, connected by a short linker. The epidermal growth factor receptor variant III (EGFRvIII), often overexpressed in glioblastoma, is another target for BiTEs. An early clinical study involving EG-FRvIII-specific BiTEs, including AMG 596, has been conducted in patients with recurrent glioblastoma.[67]

Also, Tebentafusp is a distinctive BiTE. It connects an affinity-enhanced TCR that targets the glycoprotein-100 (gp100)–HLA–A02 complex found on melanoma cells with an anti-CD3 chain. Tebentafusp showed a significant improvement in OS for patients with metastatic uveal melanoma, resulting in its approval in 2022.[68]

B Cells

Recent evidence indicates that tumor-infiltrating B lymphocytes (TIL-Bs), including B cells and plasma cells, are important and versatile players in antitumor immune responses.[69,70] In numerous cancers, TIL-Bs have demonstrated significant prognostic value and are emerging as crucial predictors of responses to ICIs.[69,70] In addition, TIL-Bs are involved in various other lympho-myeloid aggregates and engage in complex interactions with the tumor stroma, underscoring their multifaceted role in the TME.[69]

In a mice study, the development of immunosuppressive and effector B-cell responses within pancreatic ductal adenocarcinoma (PDAC) was examined using a multifaceted approach that included genetically engineered models, B-cell profiling, and functional assays.[70] The findings reveal that IL-35+ B cells inversely correlate with plasma cell frequency in PDAC. Through transcriptional profiling of naive B cells, it was discovered that IL-35 production by B cells induces a unique transcriptional state in naive B cells, inhibiting plasma cell differentiation by maintaining high levels of the B cell lineage-defining transcription factors Pax5 and Bcl6. Furthermore, targeting Bcl6 in naive B cells significantly increased the presence of intratumoral plasma cells and overcame resistance to immunotherapy, resulting in tumor growth control.[70] This study suggests that the transcriptional reprogramming of naive B cells can be a strategic target to modulate the balance between effector and regulatory B cell functions, enhancing tumor immunity in PDAC.[70]

In another study with PDAC, resistance to systemic treatment with stimulator of interferon gene (STING) agonists was partly due to the expansion of immunosuppressive B cells that hinder NK cell function.[71] Although previous research has shown that the STING-triggered IFN response is crucial for antitumor NK cell activity, this study presents a novel scenario in which systemic delivery of STING agonists suppresses NK cell-mediated antitumor responses via B cell-derived IL-35. This suppression mechanism explains why systemic delivery of STING agonists is less effective than intratumoral delivery.[71] By blocking B cell-specific IL-35 during 2'3'-cyclic GMP-AMP treatment, this negative regulatory circuit can be disrupted, offering a potential strategy to enhance tumor control. However, numerous challenges must be addressed when translating the immune capabilities of B cells into effective tumor immunotherapies.

Cancer-Associated Fibroblasts

Cancer-associated fibroblasts (CAFs) are a pivotal element within the TME, exerting control and influence on tumor behavior through comprehensive interactions with both tumor and stromal compartments.[72]

Transcriptomic analysis based on single-cell RNA-sequencing has revealed that a combination of biomarkers is capable of discriminating CAF subsets across different cancer types. CAFs were categorized using a presumed functional naming system such as myofibroblastic (myCAF), inflammatory (iCAF), antigen-presenting (apCAF), matrix, cycling (cCAF), or developmental (dCAF).[73,74] Importantly, CAF subsets are not invariable categories but can transition between each other through specific signaling pathways. This characteristic provides a rationale for inducing CAF phenotypic switching as a strategy in the development of anticancer therapy.

MyCAFs are found adjacent to tumor foci, where they are activated by direct contact with neoplastic cells.[75] They are distinguished by high expression of α-smooth muscle actin (αSMA) and low expression of IL-6. Conversely, iCAFs are found at a greater distance from tumor cells and are activated by cancer cell-derived factors such as IL-1 and TNF-α.[76] They are characterized by low expression of αSMA and high expression of IL-6. These two subtypes, myCAFs and iCAFs, are considered mutually exclusive.[77] There is evidence of conversion between iCAFs and myCAFs via TGF-β or IL-6 signaling pathways.[78]

Recently, apCAFs, a new subset of CAFs expressing major histocompatibility complex-II molecules was discovered proposing an immunomodulatory role of CAFs. In recent integrative analyses involving multiple single-cell RNA-sequencing studies and comprehensive lineage tracing assays, it has been identified that antigen-presenting CAFs (apCAFs) originate from mesothelial cells.[79] Throughout the progression of pancreatic cancer, mesothelial cells undergo a phenotypic transformation into apCAFs. This transformation involves a downregulation of mesothelial characteristics and an acquisition of fibroblastic features, a process driven by the cytokines IL-1 and TGF-β. Significantly, apCAFs have the capability to engage and reprogram naive CD4+ T cells into regulatory Tregs in a response that is specific to antigens.[79] Moreover, the application of a monoclonal antibody targeting the cell marker mesothelin has been shown to effectively inhibit the mesothelial-to-apCAF transition and the subsequent induction of Tregs by apCAFs.[80] Collectively, these findings highlight the potential role of mesothelial cells in promoting immune evasion during pancreatic cancer and offer valuable perspectives on potential strategies to enhance treatment efficacy.

Further insights into CAF dynamics were provided by tracking CAF subpopulations throughout breast tumor progression in mice.[81] A transcriptional shift from immunoregulatory activities toward functions related to wound healing and antigen presentation as the tumor progresses was observed.[81] Comparable findings from melanoma models in mice showed that three specific CAF subclusters—S1, S2, and S3—vary in abundance through different stages of tumor growth, with the S3 subpopulation, characterized by high levels of Acta2, becoming dominant in later stages.[82] These findings, primarily derived from correlative analyses using single-cell RNA-sequencing and immunostaining, suggest that CAF subsets not only have distinct origins but also specialized functions. However, these observations are based on transcriptional profiles and in vitro studies, which may not fully capture their in vivo roles.[82]

Targeting CAFs has encountered significant challenges. One major issue is the absence of specific surface markers for CAFs, making their direct depletion difficult without harming normal tissue.[83] To address this, strategies involve targeting critical signals and effectors in CAFs, such as chemokine and growth factor pathways, to inhibit their activation and function. Molecules like all-trans retinoic acid (ATRA) or calcipotriol can normalize CAFs and induce an inactive phenotype. Additionally, CAF-based or mesenchymal stem cell (MSC)-based therapies can be used to deliver anticancer agents, including oncolytic adenoviruses, TNF-related apoptosis-inducing ligand (TRAIL), or type I IFN. Targeting CAF-derived extracellular matrix (ECM) proteins and associated signaling can induce stromal depletion. Direct depletion of CAFs can also be achieved using transgenic technologies or immunotherapies. Key targets and technologies include CAR, FAP (fibroblast activation protein), FGF2 (fibroblast growth factor 2), GPR77 (G protein-coupled receptor 77), IL-6, IL-6R (IL-6 receptor), mAb (monoclonal antibody), MMP (matrix metalloproteinase), MDSC (myeloid-derived suppressor cell), NK, PD-1, PDGFR, SDF1 (stromal-derived factor 1), SMO (smoothened), TAM, and Treg.[83]

Agents targeting FAP-α, CXCR4/CXCL12, HGF, PDGF, TGF-β, and hyaluronan signaling in CAFs are being studied in preclinical and clinical trials for breast cancer, chronic myelogenous leukemia, gastrointestinal stromal tumor, and melanoma.[84,85] Especially, TGF-R β is a promising target for pancreatic and colorectal tumors and is being evaluated in a myriad of phase I clinical trials (NCT06199466, NCT03436563, NCT05836324). Also, activating the Notch1 signaling pathway in CAFs inhibits melanoma cell growth in culture and in a xenograft mouse model.[86] In addition, vaccination against FAP-α, primarily expressed on CAFs, effectively suppressed B16/F10 melanoma development in mice.[87,88]

The multi-receptor somatostatin analogue pasireotide (SOM230; Novartis) has been used to inhibit the mTOR–4E-BP1 pathway responsible for protein synthesis in α-SMA+ CAFs, which highly express the somatostatin receptor SST1. In a murine xenograft model of PDAC, treatment with SOM230 reduced CAF-secreted molecules, including IL-6, thereby overcoming CAF-induced cancer cell resistance to chemotherapy (gemcitabine). Further research on the CAF-targeting effects of SOM230 could elucidate its anti-metastatic potential in pancreatic cancers.[89–91]

Extracellular Matrix

Beyond offering structural support, the ECM acts as a dynamic entity that influences cellular behaviors and undergoes remodeling, a common feature in tumors marked by increased collagen synthesis and deposition. This process, often accompanied by the expression of remodeling enzymes such as MMPs, lysyl oxidase (LOX), lysyl oxidase-like proteins (LOXLs), and WNT1-inducible signaling pathway proteins (WISPs), is crucial for the progression of cancer.[91]

Consequently, the ECM serves as a robust barrier that promotes tumor survival and progression. However, this barrier also presents vulnerabilities that can be exploited by anticancer therapies, thereby serving as a strategic entry point for therapeutic interventions. For instance, treatments that aim to normalize ECM stiffness have shown promise in various cancers. Techniques such as photothermal depletion of CAFs have been effective in reducing ECM stiffness in desmoplastic cholangiocarcinoma, thereby impacting the tumor's physical environment.[92] Similarly, therapies that target ECM stiffness to inhibit angiogenesis have been explored in liver metastasis.[93] These approaches indicate that reducing ECM stiffness is a promising approach for effective treatment. Conversely, strategies that increase ECM stiffness, such as cholesterol depletion treatments, have been found to enhance the effectiveness of T-cell immunotherapy by altering the tumor's biomechanical properties.[94]

There is also an application involving the ECM to enhance the effectiveness of CAR T therapy, facilitating easier penetration into solid tumors. This approach leverages modifications to the ECM, aiming to reduce its density or stiffness, thereby allowing CAR T cells to infiltrate and target cancer cells more effectively. To address this, reengineered CAR T cells that overexpress heparinase have been developed.[95] Heparinase can break down ECM components and enhance T-cell infiltration into the tumor, significantly impeding tumor growth. Additionally, a recent therapeutic approach combines an oncolytic adenovirus that delivers decorin with CAR T cells targeting carbonic anhydrase IX (CAIX).[96] This strategy has been shown to remodel the ECM and boost immune responses in cancer, demonstrating the potential for innovative combination therapies to overcome challenges in treating solid tumors.[96]

STRATEGIES: TRANSFORMING “COLD” TUMORS INTO “HOT”

“Hot tumors” are characterized by a TME rich in TILs, PD-L1 overexpression, genomic instability, and preexisting antitumor immune responses.[97] “Cold tumors” lack inflammation and exhibit a deficiency in T cells both within the tumor and along its periphery, resulting in a low immunoscore.[97] They also show inadequate T-cell priming, characterized by low tumor mutational burden, impaired antigen presentation, and inherent resistance to T-cell–mediated killing[97] (Figure 2). Variable tumors are tumors in a variable state between cold and hot ones.

Figure 2.

Cold and hot tumor environment and strategies to turn cold tumors into hot tumors. The primary cellular components and molecular interactions influencing the cold tumor phenotype and the hot tumor phenotype are delineated below. Key abbreviations include the following: NK (natural killer cells), DCs (dendritic cells), pDC (plasmacytoid dendritic cells), M2 (type 2 macrophages), MDSC (myeloid-derived suppressor cells), T eff (effector T cells), T reg (regulatory T cells), TCR (T-cell receptor), MHC (major histocompatibility complex), CTLA-4 (cytotoxic T-lymphocyte-associated protein 4), LAG3 (lymphocyte activation gene-3), PD-1 (programmed cell death-1), and PD-L1 (programmed cell death-ligand 1). On the second table of the figures, we can see an overview of potential strategies to transform cold tumors into hot ones, along with their mechanisms of action, enhancing therapeutic outcomes when combined with immunotherapy.

It is generally accepted that checkpoint inhibitors alone are more effective against “hot tumors” whereas having no benefit in treating “cold tumors” or “variable” tumors, which require a combination of other therapies to recruit immune cells to the tumor tissue to warm it up. Using combination therapies with immunotherapy approach stands as a pivotal method in addressing cold tumors such as chemotherapy, targeted therapy, radiation therapy, dual immunotherapy, oncolytic viruses, cancer vaccines, cytokines, cytotoxic chemotherapy, modulation of microbiome, radiation therapy, and other clinically viable combination techniques[98] (Figure 3). We discuss some of these therapies in the following sections.

Figure 3.

Mechanisms of action of therapies in TME. Summary of experimental and clinical interventions targeting tumoral stromal components. Tumor development is associated with intrinsic extracellular matrix modifications and cellular components that foster neoplastic progression. Tumor cells can induce pro-tumoral phenotypic changes in macrophages, fibroblasts, and lymphocytes by releasing soluble mediators (depicted as small colored circles). Tumors also release pro-angiogenic factors to guide the migration of vascular cells that form new branched vessels. Several strategies have been developed to disrupt tumor-stromal interactions and enhance immune cell-mediated tumoral attack:

¹Activating DCs with CG-CSF, CD40, and FLT3 agonists to enhance antigen presentation. Another strategy involves administering DC vaccines or a pool of autologous mononuclear cells presenting antigens extracted from tumors and enhanced in vitro (Sipuleucel).

²Augment anti-tumoral cytotoxic lymphocyte activities by introducing CAR T cells or an autologous pool of polyclonal lymphocytes extracted from tumors and enhanced in vitro (Lifileucel).

³Suppression of Treg cell activities using sunitinib, checkpoint inhibitors, or cyclo-phosphamide treatments.

⁴Inhibition of CAFs using mesothelin antibodies in experimental models.

⁵Inhibition of the angiogenic process at various stages by targeting soluble mediators with anti-VEGF agents, blocking their receptors with multi-tyrosine kinase inhibitors, or perturbing downstream signaling using mTOR inhibitors.

⁶Manipulate macrophage polarization toward a proinflammatory and anti-tumoral phenotype by administering TLR-8/9 agonists, CD40 agonists, or CSFR1 inhibitors.

CSFR-1: colony-stimulating factor-1 receptor; CAFs: cancer-associated fibroblasts; CAR T cell: chimeric antigen receptor T cells; DCs: dendritic cells; CG-CSF: granulocyte-macrophage colony-stimulating factor; CSF-1R: colony-stimulating factor-1 receptor; CTLs: CD8 positive cytotoxic T lymphocytes; EGF: epidermal growth factor; FGF: fibroblast growth factor;FLT3: FMS-like receptor tyrosine kinase-3; M1: macrophages type 1; M2: macrophages type 2; PDGF: platelet-derived growth factor; Treg: T regulatory cells; TLR-8/9: Toll-like receptors 8 and 9; VEGF: vascular endothelial growth factor.

Therapeutic Vaccines

The idea of a vaccine is to use tumor-specific antigens to activate antigen-specific T cells and establish antitumor immune memory.[99] This would induce influx of cytokine-producing CD8+ T cells and of intratumoral macrophages. Neoantigen-targeted vaccines show promise in activating long-lasting T-cell responses. Neoantigen quality is determined by various factors, including its dissimilarity to the wild-type amino acid sequence, its distribution among subclonal populations, its ability to be processed and presented on MHC molecules, and the affinity of the TCR for the neoantigen, among others.[100]

T-cell Receptor-Based Therapies and Adoptive T-cell Therapies

TCR-based therapy treatments are another evolving immunotherapy approach for inducing higher-quality T cells and directing them to the TME in immune-resistant solid tumors. Bispecific antibodies and engineered T cells redirect endogenous T cells to recognize and kill cancer cells.[101] Adoptive cell therapy, including CAR T cells, harnesses a patient's T cells to target cancer-specific antigens.

Oncolytic Viruses

Oncolytic viruses (OVs) are specially engineered viruses that selectively replicate within tumor cells and are considered promising cancer treatments.[89] A key area of interest with OVs is their ability to cause tumor cells to burst and die through replication, a process called lytic cell death. This type of cell death is highly immunogenic and can transform immunologically inactive, or “cold,” tumors into active, or “hot,” ones.[102] Tumors treated with OVs have shown a rise in the infiltration of CD8+ T cells and an increase in tumor-specific CD8+ T cells throughout the body. The potential synergy between OVs and ICIs is as a possible new approach to treating stubborn, immunologically cold tumors.[102]

Radiation Therapy

Radiation therapy can modify the TME to trigger an anticancer immune response by inducing an immunologic form of cell death.[103] This type of cell death can activate the patient's immune system to attack cancer cells even outside the radiation field, leading to what is known as the abscopal effect—where tumors distant from the irradiated area also regress.[104] Incorporating radiation into ICI regimens is an area of active investigation, with mixed results across different cancer types. For instance, the S1806 trial is evaluating the addition of atezolizumab to chemoradiation in patients with muscle-invasive bladder cancer, aiming to determine if this combination can enhance outcomes.[105] Similarly, the NIVES and RADVAX trials explored the use of radiotherapy combined with nivolumab alone or combined with ipilimumab in mRCC, offering insights into the potential benefits and challenges of this approach.[106,107]

Cytotoxic Chemotherapy

The effectiveness of cytotoxic chemotherapy in combating tumors partially relies on the immune system. It can reconfigure immune tolerance by eliminating immunosuppressive cells such as Tregs within the TME.[108] In addition, chemotherapy can induce cellular necrosis, a type of cell death that is more immunogenic than apoptosis. This process leads to the release of inflammatory signals like IL-8, TNF-α, and High Mobility Group Box Protein 1 (HMGB1), which further stimulate the immune response against the tumor.[109]

Targeted Therapies

VEGF is known to regulate the growth of vascular endothelial cells and contribute to immunosuppression. Research indicates that blocking VEGF pathways can enhance immune responses. Clinical studies have demonstrated that combining PD-L1 monoclonal antibodies with VEGF inhibitors yields synergistic effects, showing promise in treating various types of tumors.[110] Specifically, using PD-L1 inhibitors together with VEGFR2 inhibitors has been effective in reducing PD-1 and PD-L1 expression levels, increasing TILs, reducing Tregs and MDSCs, and inhibiting tumor growth.[110,111]

FUTURE PERSPECTIVES—DECODING THE TME WITH NEW TECHNOLOGIES

Spatial Technologies and Artificial Intelligence

Some available artificial intelligence (AI) approaches, such as deep/machine learning algorithms, could be configured to predict genomic and/or transcriptomic profiles based on digitized hematoxylin and eosin (H&E)-stained tumor slides after a previous training step with a certain accuracy. In a similar manner, the stroma components and their spatial distribution could be characterized from digitized slides, and this information would be used for prognostic and predictive purposes.[112] Lim et al.[113] demonstrated that the Lunit SCOPE IO, a deep learning machine tool based on convolutional neural network architecture, effectively distinguished between individuals experiencing disease recurrence and those without evidence of disease. This discrimination was based on lower stromal TIL density (mean of 630.2/mm²) for the former and higher stromal TIL density (mean of 1021.3/mm³) for the latter, in a retrospective analysis of 289 patients with stage II-III colon cancer who had undergone surgery followed by adjuvant therapy.[113]

Another retrospective study assessed the prognostic value of a trained deep-learning convolutional neural network–based algorithm for determining the tumor-stroma ratio (TRS) in H&E-stained slides (representing the most invasive element of the tumor) from patients with localized colorectal cancer.[114] This AI approach could predict differences in OS according to low (TRS < 48.8%) and high (TRS ≥ 48.8%) cutoffs. In the discovery cohort (499 patients), the median OS was 72 and 67 months (unadjusted hazard ratio of 1.79; 95% CI, 1.30–2.47; log-rank test P < 0.0010) for low and high-TRS patients, respectively. Similar findings were described in the validation cohort, with a median OS of 49 and 46 months (unadjusted HR of 2.21; 95% CI, 1.35–3.63; P = 0.002) for low and high-TRS patients, respectively. Additionally, the high-TRS cutoff was still an independent prognostic for inferior survival in a multivariate analysis in both the discovery (HR 1.72; 95% CI, 1.24–2.37; P = 0.001) and validation (2.08; 1.26–3.42; P = 0.004) cohorts.[114]

AI methodologies can also analyze cell-to-cell interactions from H&E-stained tumor slides to infer possible correlations with clinical features, as evidenced in a retrospective analysis of 2231 luminal human localized breast cancer slides through a supervised deep learning model. In this study, the authors evidenced a positive statistical association of adverse clinical features (e.g., positive lymph node status, Ki-67 ≥20%, tumor size ≥2 cm, and higher tumor grade) with a higher presence of TILs close to other stroma or tumor cells.[115]

Despite the emerging potential of AI tools for oncology research purposes in characterizing the TME regarding both component description and spatial distribution, most of the evidence in recent years has been focused on prognostic outcomes. Nevertheless, further studies are needed to assess their role in treatment prediction. Additionally, these strategies must undergo validation in other distinct scenarios, necessitating collaboration with multi-institutional datasets.

Nanotechnology

Nanoparticles (NPs), defined as materials smaller than 100 nm, exhibit unique properties due to their surface characteristics and small size. The key application of these nanomaterials is serving as a drug delivery system (DDS) that enables the precise delivery of therapeutic agents to specific cells and tissue environments. These DDSs enhance the effectiveness of the drug, minimize side effects, and improve both pharmacokinetics and bioavailability.[116] As a result, nanomaterial-based DDSs are emerging as innovative therapeutic modalities for a variety of cancers, owing to their ability to navigate biological barriers and optimize drug distribution. For example, in the treatment of melanoma, various nanomaterials such as liposomes, nanostructured lipid carriers (NLCs), solid lipid nanoparticles (SLNs), hydrogels, nanoemulsions, polymer micelles, and inorganic nanoparticles have been used to create nano-DDSs. These platforms offer several significant benefits, including targeted delivery to TAMs, modulation of T-cell responses, and enhancement of other immune responses.[116]

CONCLUSIONS

The complex development of tumors mirrors dynamic changes in the TME, which are pivotal in promoting tumor growth and metastasis. Although targeting specific components of the TME—such as the ECM, vasculature, and both non-immune and immune cells—presents valuable therapeutic opportunities, focusing on these elements individually may not yield comprehensive and lasting therapeutic outcomes.

The success of immunotherapy in treating cancer stems from advancements in understanding the critical mechanisms of T-cell activation and suppression. Emerging therapies, including CAR T, CAR NK, and CAR-M cells, show promise in treating solid tumors. However, clinical trials often struggle to demonstrate effective results due to both innate and acquired resistance in patients.

Exploring TME targets, such as the modulation of tumor vasculature in combination with immunotherapies, could help overcome these therapeutic challenges. A deeper understanding of the essential elements of the TME may drive the discovery and development of innovative treatments. Moreover, incorporating nanomedicine and AI into cancer research could offer novel approaches to targeting the TME.

Given the significant variability within the TME, integrating biomarker-driven patient selection in clinical trials is crucial. This approach is essential for effectively transitioning these strategies from the lab to clinical practice and ensuring their efficacy in cancer treatment.