Skip to main content
Download PDF

Mechanisms of T-cell Depletion in Tumors and Advances in Clinical Research

Biological Procedures Online volume 27, Article number: 5 (2025) Cite this article

Abstract

T lymphocytes (T cells) are essential components of the adaptive immune system that play a vital role in identifying and eliminating infected and tumor cells. In tumor immunotherapy, T cells have emerged as a promising therapeutic strategy due to their high specificity, potent cytotoxic capability, long-lasting immune memory, and adaptability within immunotherapeutic approaches. However, tumors can evade the immune system by depleting T cells through various mechanisms, such as inhibitory receptor signaling, metabolic exhaustion, and physical barriers within the tumor microenvironment. This review provided an overview of the mechanisms underlying T-cell depletion in tumors and discussed recent advances in clinical research related to T-cell immunotherapy for tumors. It highlighted the need for in-depth studies on key issues such as indications, dosage, and sequencing of combined therapeutic strategies tailored to different patients and tumor types, providing practical guidance for individualized treatment. Future research on T-cell depletion would be necessary to uncover the fundamental mechanisms and laws of T-cell depletion, offering both theoretical insights and practical guidance for the selection and optimization of tumor immunotherapy. Furthermore, interdisciplinary, cross-disciplinary, and international collaborative innovations are necessary for developing more effective and safer treatments for tumor patients.

Introduction

T cells, also referred to as T lymphocytes, are vital components of the adaptive immune system, primarily responsible for identifying and eliminating infected and tumor cells. In tumor immunotherapy, T cells play an essential role due to their high specificity, potent cytotoxic capability, enduring immune memory, and adaptability within immunotherapies [1]. First, T cells have remarkable specificity. Each T cell possesses a unique T-cell receptor (TCR) on its surface, which specifically recognizes and binds to peptide-MHC molecules on antigen-presenting cells. This feature enables T cells to distinguish between self and non-self, allowing them to selectively target and attack abnormal peptides in tumor cells, effectively eliminating them [2]. Second, T cells have formidable killing capacity. Upon activation, T cells rapidly proliferate and secrete large quantities of cytokines, such as tumor necrosis factor (TNF) and interferon-gamma (IFN-γ), which enhance the antitumor activity of other immune cells [3]. Furthermore, T cells can directly destroy tumor cells by releasing effector molecules such as perforin and granzyme B [4]. In addition, T cells possess enduring immune memory. During the antitumor immune response, some T cells differentiate into memory T cells, which persist long after the tumor has been eradicated to maintain immune surveillance. If the tumor recurs or metastasizes, these memory T cells can be swiftly activated to resume their antitumor function, thereby enhancing the therapeutic impact and minimizing the likelihood of recurrence [5]. Lastly, T cells have versatility in immunotherapy. In recent years, significant clinical progress has been achieved with T-cell-based immunotherapies. For instance, immune checkpoint inhibitors (e.g., PD-1/PD-L1 and CTLA-4 inhibitors) can counteract tumor-suppressive effects on T cells, thereby reinvigorating their depleted function [6, 7].

T-cell depletion refers to the gradual decline in the proliferation, cytokine production, and cytotoxic effects of T cells during a sustained antitumor immune response, ultimately resulting in weakened antitumor immune function. The primary factors contributing to T-cell depletion include abnormal TCR signaling, the expression of immunosuppressive receptors, tumor microenvironmental factors, and metabolic dysregulation [8]. T-cell depletion has significant implications for tumor therapy. First, the accumulation of depleted T cells in tumor tissue undermines the efficacy of immunotherapy. This occurs because depleted T cells cannot fully exert their antitumor effects, leading to suboptimal therapeutic outcomes. Second, T-cell depletion is closely associated with tumor prognosis. Studies have demonstrated that a high abundance of severely depleted T cells in tumor tissue is inversely correlated with patient survival and treatment response [9]. Furthermore, T-cell depletion influences the selection of immunotherapeutic strategies. For instance, depleted T cells exhibit reduced responsiveness to immune checkpoint inhibitor therapy, necessitating alternative therapeutic approaches for these patients [10].

In this review, we introduced the basic concept and mechanisms of T-cell depletion, summarized the current progress in T-cell depletion within the fields of basic and clinical cancer research, and provided insights on potential developments in the future. This review aimed to provide valuable references for enhancing the understanding of the important role of T-cell depletion in the occurrence and development of tumors, both from clinical and fundamental perspectives.

Clinical Manifestations of T-cell Depletion

The clinical manifestations of T-cell depletion are influenced by various factors, including the type of tumor, the disease course, and the patient’s immune system status. Some potential clinical manifestations of T-cell depletion include the following: (1) Tumor progression and recurrence: Under normal conditions, a patient’s immune system can effectively control tumor progression. However, when T cells become depleted, they lose their ability to regulate tumor growth, leading to tumor progression and recurrence. This may result from the impaired antitumor function of depleted T cells and the immunosuppressive effects of other immune cells within the tumor microenvironment (TME), such as regulatory T cells and myeloid-derived suppressor cells (MDSCs) [11]. (2) Deterioration in the clinical course: T-cell depletion may lead to a worsening clinical trajectory, characterized by exacerbated symptoms, increased tumor burden, and reduced survival. This deterioration may be related to the diminished antitumor function of depleted T cells, immune surveillance evasion by tumor cells, and the influence of other immunosuppressive factors in the TME [12]. (3) Resistance to treatment: T-cell depletion may render patients resistant to oncological treatments such as chemotherapy, radiotherapy, and targeted therapies. Depleted T cells reduce the immune system’s response to tumors, thereby reducing the efficacy of these treatments. Additionally, T-cell depletion may be associated with an increased incidence of treatment-related side effects and toxicities [13]. (4) Differences in response to immunotherapy: T-cell depletion may influence a patient’s response to immunotherapy, such as PD-1/PD-L1 or cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) antibodies. Variations in T-cell- depletion between patients may lead to differences in immunotherapy efficacy. For example, some patients may achieve clinical remission with immunotherapy, while others may not benefit from the treatment. Therefore, the status of a patient’s T-cell depletion should be considered when selecting and evaluating immunotherapy regimens [14]. (5) Immune-related adverse events: Despite the significant efficacy of immunotherapy in oncology, it may also trigger immune-related adverse events (irAEs). These adverse events may be related to the status and functional recovery of depleted T cells. For example, immune checkpoint inhibitors may lead to functional recovery of depleted T cells but also activate autoimmune responses, resulting in tissue damage and organ dysfunction [15].

Methods for Evaluating T-cell Depletion

At present, the evaluation of T-cell depletion mainly includes the following methods: (1) Histopathological examination: The distribution, number, and subtype of depleted T cells in tumor tissues can be directly observed through immunohistochemical staining (IHC) and immunofluorescence staining. For example, in a study by Rizvi et al. (2015), IHC was used to quantify PD-1+ T cells in non-small cell lung cancer (NSCLC) samples, and found that higher densities of these exhausted T cells were associated with improved responses to PD-1 blockade therapy [16]. Additionally, using multiplex immunofluorescence, Tumeh et al. (2014) demonstrated the spatial relationship between exhausted T cells and PD-L1-expressing tumor cells in melanoma, providing insights into the TME that predict responsiveness to immunotherapy [17]. These approaches offer a comprehensive assessment of the tumor immune landscape, enhancing our understanding of T-cell dynamics across different TME. (2) Flow cytometry: Flow cytometry facilitates multiparametric detection and quantification of surface markers and functional molecules of depleted T cells. For instance, Pauken et al. (2016) used flow cytometry to identify co-expression patterns of inhibitory receptors, such as PD-1, CTLA-4, and T-cell immunoglobulin and mucin domain-containing protein 3 (TIM-3) on CD8(+) T cells in chronic viral infections and cancer, highlighting the heterogeneous nature of T-cell exhaustion [18]. In another study, Darvin et al. (2018) used flow cytometry to assess the expression of activation markers (CD25, CD69) and cytokine production (IFN-γ, TNF-α, IL-2) in T cells derived from breast cancer patients. This study correlated these immunological profiles with clinical outcomes and therapeutic responses [19]. Additionally, functional assays, such as proliferation assays and cytotoxicity assays, were performed to evaluate the impaired effector functions of exhausted T cells, providing a detailed understanding of the biological impairments associated with T-cell exhaustion. (3) Gene expression profiling: Through RNA sequencing, microarrays, and real-time quantitative PCR, the gene expression profile of depleted T cells can be comprehensively and thoroughly analyzed. For example, Wherry et al. (2007) used gene expression profiling to characterize exhausted T cells in chronic viral infections, identifying key transcription factors and inhibitory receptors that define the exhausted phenotype [20]. Similarly, Gajewski et al. (2018) performed RNA sequencing on T cells isolated from hepatocellular carcinoma (HCC) patients, identifying gene signatures associated with T-cell exhaustion that correlated with poor prognosis and resistance to immunotherapy [21]. Real-time quantitative polymerase chain reaction was also used in these studies to validate the expression levels of critical genes identified through high-throughput methods, ensuring the reliability and reproducibility of the findings. Collectively, these approaches not only elucidate the molecular characteristics and signaling pathways of T cell depletion but also identify potential biomarkers for prognosis and therapeutic response. (4) Epigenetic and noncoding RNA analysis: In recent years, the role of epigenetic modifications and noncoding RNAs in regulating T-cell depletion has garned increasing attention. For instance, Julia A. Belk et al. (2022) investigated DNA methylation patterns in exhausted T cells from melanoma patients, identifying specific methylation markers associated with T-cell dysfunction and resistance to PD-1 blockade [22]. Similarly, histone modification analysis in a colorectal cancer model by Rashmi J. Rao et al. (2024) revealed altered chromatin states associated with the expression of inhibitory receptors, providing insights into the epigenetic regulation of T-cell exhaustion [23]. Additionally, microRNA (miRNA) profiling has uncovered regulatory networks involving noncoding RNAs that modulate T-cell activity. In a study by Meng Zhang et al. (2020) demonstrated thatmiRNA-5119 was downregulated in exhausted T cells in gastric cancer, and its restoration improved T-cell function and anti-tumor activity [24]. These epigenetic and noncoding RNA analyses not only elucidate the regulatory mechanisms underlying T-cell depletion but also offer potential biomarkers for guiding the selection and optimization of tumor immunotherapy strategies.

Mechanisms of T-cell Depletion

T-cell depletion is a multifaceted process involving numerous mechanisms and molecular pathways. The primary mechanisms of T-cell depletion are shown below.

Abnormal TCR Signaling

TCR signaling is crucial for T-cell activation and function (Fig. 1). In depleted T cells, TCR signaling pathways are impaired. For instance, reduced phosphorylation levels of the TCR-CD3 complex obstruct the activation of downstream signaling molecules, such as ZAP70, LAT, PLCγ1, and PKCθ [25]. Additionally, the expression of signal transduction suppressor molecules, including SHP1, SHP2, and CBL-B, is increased in depleted T cells, further impeding TCR signaling [26]. These abnormalities in TCR signaling affect T-cell activation, proliferation, and differentiation, leading to diminished antitumor capabilities.

Fig. 1
figure 1

The primary mechanism of T-cell depletion. This figure illustrates the main mechanisms behind T-cell depletion, including disrupted T-cell receptor (TCR) signaling and the effects of immunosuppressive factors within the tumor microenvironment

Full size image

TCR stimulation plays a crucial role in the development, homeostasis, proliferation, cell death, cytokine production, and differentiation of T cells [27]. Based on existing research, Liang et al. concluded that TCRs specifically recognize antigen peptides presented by major histocompatibility complex (MHC) molecules on the surface of antigen-presenting cells and convert extracellular recognition signals into intracellular signals. By inducing the activation of tyrosine kinases adjacent to TCRs, these receptors promote the assembly of signaling complexes, activate downstream signaling pathways such as MAPK, PKC, and calcium ion pathways, and finally activates the corresponding transformation. The transcription factors regulate the expression of effector protein molecules and completes the activation of T cells [28]. Zhang et al. demonstrated that regulating early TCR signaling promotes T-cell activation both in vivo and in vitro [29]. Murine models with attenuated TCR signaling strength have shown that TCR signaling functions as a regulatory feedback mechanism for T-cell homeostasis and differentiation in different cytokine environments, such as IL-2-mediated regulatory T-cell (Treg) development, IL-7-mediated naïve CD8(+) T-cell homeostasis, and IL-4-induced innate memory CD8(+) T-cell development [30].

Abnormal TCR signaling is a fundamental barrier to effective T-cell responses within the TME. Therapeutic interventions aimed at restoring proper TCR signaling could potentially rejuvenate exhausted T cells. For example, targeting inhibitory molecules such as SHP2 with specific inhibitors has shown promise in restoring TCR signaling and enhancing T-cell function [31]. However, these strategies must be carefully balanced to avoid unintended overactivation of T cells, which could result in autoimmune side effects.

Tumor Microenvironmental Factors

The TME is rich in immunosuppressive factors that negatively impact T-cell function (Fig. 2). Immunosuppressive cells, including Tregs and MDSCs, secrete cytokines like TGF-β, IL-10, and indoleamine-2,3-dioxygenase (IDO), which inhibit T-cell activation, proliferation, and cytokine production [32]. Moreover, tumor cells can express ligands such as PD-L1, FasL, and PDL2, which directly inhibit T-cell activity) [33]. Metabolic challenges within the TME, including hypoxia, lactate accumulation, and competition for energy-metabolizing substances, further suppress T-cell function [34].

Fig. 2
figure 2

Common methods used to evaluate T-cell depletion and key therapeutic strategies to overcome T-cell depletion. This figure summarizes common methods used to assess T-cell depletion, such as flow cytometry, histopathological examination, and gene expression profiling. It also highlights some of the key therapeutic strategies to counteract T-cell depletion, including chimeric antigen receptor T (CAR-T) cell therapy, tumor vaccines, and combination therapies, all of which are critical for cancer immunotherapy

Full size image

T cells must substantially increase nutrient uptake to generate an appropriate immune response, and failure to obtain sufficient nutrients or engage in the proper metabolic pathways can alter or prevent effector T-cell differentiation and function. Inhibitory receptors present in the TME can inhibit T-cell metabolism and alter T-cell signaling, either directly or through the release of extracellular vesicles, such as exosomes [35]. Scharping et al. found that T cells showed persistent loss of mitochondrial function and mass when infiltrating murine and human tumors. This effect was specific to the TME, not merely caused by activation; besides, they also validated that the TME repressed T-cell mitochondrial biogenesis to drive intratumoral T-cell metabolic insufficiency and dysfunction [36]. In turn, Treg depletion also alters the TME. Zhang et al. found that Treg depletion in a mouse model accelerated the occurrence of pancreatic cancer by modifying the TME; Meanwhile, unexpected crosstalk with fibroblasts caused the differentiation of inflammatory fibroblast subsets, driving myeloid infiltration through CCR1. These findings suggest a potential new therapeutic approach to alleviate immunosuppression in pancreatic cancer [37].

The immunosuppressive TME plays a pivotal role in promoting T-cell exhaustion and depletion. Modifying the TME through strategies such as inhibiting immunosuppressive cytokines or depleting Tregs and MDSCs has demonstrated potential in enhancing T-cell function. For instance, using IDO inhibitors or TGF-β blockers can restore T-cell activity and improve antitumor responses. Additionally, metabolic reprogramming of the TME to restore nutrient availability for T cells has emerged as a promising avenue for enhancing antitumor immunity. However, these strategies require careful optimization to avoid disruption of normal physiological processes while ensuring the selective targeting of tumor-associated immunosuppressive factors.

Metabolic Disorder

Metabolic competition between tumor cells and T cells leads to an insufficient nutrient supply, resulting in T-cell depletion (Fig. 2). Tumor cells consume large amounts of amino acids, glucose, and other energy-metabolizing substances, disrupting T-cell metabolism. In a hypoxic environment, tumor cells produce substantial lactic acid through lactic acid fermentation, acidifying the microenvironment and further suppressing T-cell function [38]. Additionally, tumor cells can deplete tryptophan through the expression of IDO, affecting T-cell proliferation and differentiation [39]. These metabolic disorders not only impact the energy supply for T cells but also interfere with signaling and gene expression, leading to T-cell dysfunction.

Sosnowska et al. found that inhibition of arginase modulated the T-cell response in the TME of lung carcinoma. In advanced tumors, systemic concentrations of ʟ-arginine decrease to levels that impair the proliferation of antigen-specific T cells. Systemic or myeloid-specific arginase 1 deletion improves antigen-induced proliferation of adoptively transferred T cells and inhibits tumor growth [40]. Cheng et al. reported that tumors depleted of fumarate hydratase (FH) inhibited functional CD8 + T-cell activation, expansion, and efficacy. Mechanistically, FH depletion leads to fumarate accumulation in tumor interstitial fluid. Increased fumarate can directly succinate ZAP70 at C96 and C102 and abrogate its activity in infiltrating CD8 + T cells, thereby suppressing CD8 + T-cell activation. These findings suggested that fumarate accumulation is a metabolic barrier to CD8 + T-cell antitumor function [41]. ʟ-arginine deprivation also suppresses T-cell responses in tumors. Fletcher et al. found that a pegylated form of the catabolic enzyme arginase I blocked proliferation and cell cycle progression in normal activated T cells without triggering apoptosis or impairing T-cell activation [42]. Tumor-induced glucose restriction in ovarian cancer results in the downregulation of methyltransferase EZH2 expression in T cells, leading to T-cell dysfunction through the Notch signaling pathway. This dysregulation has been found to be associated with poor clinical prognosis [43].

Metabolic dysregulation within the TME is a significant contributor to T-cell exhaustion. The high metabolic demands of tumor cells create a competitive environment that limits the availability of essential nutrients for T cells, impairing their function and survival. Therapeutic approaches targeting metabolic pathways, such as inhibiting IDO or arginase, have shown promise in restoring T-cell functionality and enhancing antitumor immunity. Additionally, strategies aimed at supplementing or optimizing nutrient availability for T cells, such as metabolic reprogramming or the use of metabolic inhibitors, could mitigate the effects of metabolic competition. However, these interventions must be precisely targeted to avoid unintended consequences on normal cellular metabolism and ensure the selective enhancement of T-cell responses within the TME.

Transcription Factors and Epigenetic Regulation

Transcription factors and epigenetic regulation play essential roles in T-cell depletion. In depleted T cells, the expression and activity of key transcription factors (e.g., NFAT, T-bet, Eomes, and Blimp-1) are modulated, leading to diminished antitumor immune function. Concurrently, epigenetic modifications (e.g., DNA methylation, histone modifications, and miRNA regulation) contribute to the generation and maintenance of depleted T cells. For example, DNA demethylation of the promoter regions of immunosuppressive receptor genes, such as PD-1 and TIM-3, in depleted T cells results in the upregulation of their expression [44]. Histone modifications (e.g., acetylation and methylation), as well as miRNA regulation (e.g., miR-199a-5p), also play a role in the epigenetic regulation of depleted T cells [45, 46].

Chihara et al. found that the transcription factor MAF, which induced TGF-β and IL-6 production, was overexpressed in depleted CD8 + T cells [47]. Zheng et al. found that depleted CD8 + T cells and the high expression of the layilin gene in Tregs inhibited the function of CD8 + T cells in HCC tumor tissues, as identified through single-cell sequencing [48]. Seo et al. showed that TOX and TOX2 were highly induced in CD8 + CAR + PD-1high TIM3high (“exhausted”) tumor-infiltrating lymphocytes (CAR TILs) in a CAR T-cell model. CAR TILs deficient in both TOX and TOX2 (Tox DKO) were more effective than wild-type (WT), TOX-deficient, or TOX2-deficient CAR TILs in suppressing tumor growth and prolonging the survival of tumor-bearing mice. These findings suggest that TOX and Nr4a transcription factors are critical for the transcriptional program of CD8 + T-cell exhaustion downstream of NFAT [49]. Similarly, Chen et al. found that Nr4a triple knockout CAR TILs displayed phenotypes and gene expression profiles characteristic of CD8 + effector T cells. Chromatin regions uniquely accessible in Nr4a triple knockout CAR TILs, compared to WT, were enriched for binding motifs of NF-κB and AP-1, which were transcription factors involved in the activation of T cells. These data highlight the important role of NR4A transcription factors in T-cell hyporesponsiveness [50]. Belk et al. used CRISPR screens in murine and human tumor models to demonstrate that perturbation of the INO80 and BAF chromatin remodeling complexes improved T-cell persistence in tumors. In vivo Perturb-seq identified distinct transcriptional roles of each complex. Depletion of canonical BAF complex members, such as Arid1a, maintained the effector program and the downregulation of exhaustion-related genes in tumor-infiltrating T cells. These findings not only highlighted key genetic regulators of T-cell depletion but also demonstrated that the regulation of epigenetic states could enhance T-cell responses in cancer immunotherapy [51].

Transcription factors and epigenetic modifications are critical regulators of T-cell exhaustion. Targeting these factors offers a promising strategy to reverse exhaustion and restore T-cell functionality. For instance, inhibiting transcription factors like MAF or TOX can mitigate the immunosuppressive programs within exhausted T cells, thereby enhancing their antitumor activity [52, 53]. Additionally, epigenetic therapies that modify DNA methylation or histone acetylation states can reactivate silenced genes involved in T-cell activation and effector functions [54, 55]. These approaches not only rejuvenate exhausted T cells but also provide a foundation for developing combination therapies that integrate transcriptional and epigenetic modulation with other immunotherapeutic strategies.

Cytokine Signaling

Cytokine signaling is crucial for T-cell regulation during immune responses. In depleted T cells, key cytokine signaling pathways are suppressed. For instance, the IL-2/STAT5 signaling pathway, vital for T-cell proliferation and survival, is impaired in depleted T cells, presenting with the decreased IL-2 production and STAT5 phosphorylation level [56]. Additionally, inhibitory cytokines such as TGF-β and IL-10 negatively regulate depleted T cells, further impairing their function [57].

Lu et al. found that suppression of the MondoA-TXNIP axis promoted glucose uptake and glycolysis and induced hyperglycolytic Th17-like Tregs. This process facilitated Th17 inflammation, promoted IL-17 A-induced CD8 + T-cell exhaustion, and drove colorectal carcinogenesis [58]. Fitzgerald et al. found that the infiltration of NK and CD8 + T cells could be enhanced by adjusting the CXCR3 axis, thereby improving anti-PD1 efficacy in murine models of pancreatic ductal adenocarcinoma [59]. Deng et al. showed that LILRB4, an immunoreceptor tyrosine-based inhibition motif-containing receptor and a marker of monocytic leukemia, suppressed T-cell activity and supported tumor cell infiltration into tissues through a signaling pathway involving APOE, LILRB4, SHP-2, uPAR, and ARG1 in acute myeloid leukemia cells [60]. Saka et al. used transcriptomics, mass cytometry, and epigenomics and revealed the critical role of thymocyte selection-associated high mobility group box protein (TOX) genes and TOX-associated pathways in driving T-cell exhaustion during chronic infections and cancer [61]. The MAPK pathway, consisting of ERK, JNK, p38 MAPK, and ERK 5 branches, controls the expression of transcription factors, cytokines, and cytokine receptors that activate T-cell function [62]. Zhao et al. found that the activation of the MAPK/ERK pathway promoted functional T-cell differentiation, promoted T-cell killing activity, and enhanced antitumor effects [63].

Cytokine signaling plays a dual role in T-cell regulation, balancing activation and inhibition. Enhancing positive cytokine pathways, such as IL-2/STAT5, while inhibiting negative pathways mediated by TGF-β and IL-10, can rejuvenate exhausted T cells and restore their antitumor functions. For example, disrupting the MondoA-TXNIP axis or adjusting the CXCR3 axis can enhance T-cell metabolism and infiltration, respectively, thereby improving the efficacy of immune checkpoint inhibitors like anti-PD1 therapies [58, 64]. Additionally, targeting inhibitory receptors such as LILRB4 can alleviate T-cell suppression and promote effective antitumor responses [65]. Moreover, activating the MAPK/ERK pathway has been shown to enhance T-cell differentiation and effector functions, further boosting antitumor immunity [66]. These findings highlight the potential of modulating cytokine signaling pathways to overcome T-cell exhaustion and improve cancer immunotherapy outcomes.

T-cell depletion in the TME is orchestrated by a complex interplay of aberrant TCR signaling, immunosuppressive TME factors, metabolic disturbances, transcriptional and epigenetic dysregulation, and impaired cytokine signaling. Together, these mechanisms collectively contribute to the exhaustion and functional impairment of T cells, undermining the efficacy of antitumor immune responses. A comprehensive understanding and targeted intervention of these pathways are essential for developing effective immunotherapies that can overcome T-cell depletion and restore robust antitumor immunity. Future research should focus on integrating multiple therapeutic strategies to address the multifactorial nature of T-cell exhaustion, thereby enhancing the overall effectiveness of cancer immunotherapy.

Therapeutic Strategies for Overcoming T-cell Depletion

Therapeutic strategies to overcome T-cell present an important area of research in tumor immunotherapy. These strategies focus on enhancing the activity, antitumor effect, and persistence of T cells to improve the overall efficacy and broaden the applicability of immunotherapy. The following table summarizes the main therapeutic strategies to address T-cell depletion (Table 1):

Table 1 Therapeutic strategies to overcome T-cell depletion
Full size table

The future of overcoming T-cell depletion in cancer immunotherapy is promising, with evolving strategies poised to transform clinical outcomes. CAR-T-cell therapy is expected to expand beyond hematologic malignancies, with next-generation CAR-T cells targeting solid tumors and enhanced through combination with immune checkpoint inhibitors to counteract TME suppression. Tumor vaccines, especially neoantigen-based and RNA vaccines, offer a personalized approach to activate the immune system, with improved efficacy when combined with checkpoint inhibitors. Combination therapies, integrating CAR-T, tumor vaccines, and immune checkpoint inhibitors, will become a cornerstone in treating cancer, addressing immune suppression and exhaustion through synergistic effects. These approaches are expected to offer more effective and less toxic treatments, facilitating personalized and durable responses. By addressing challenges such as treatment resistance and disease relapse, they hold the potential to significantly advance and transform cancer care. As research progresses, these therapies may significantly improve survival rates and quality of life for patients with both solid and hematologic cancers.

Conclusion

Malignant tumors represent a major medical challenge and are the second leading cause of death worldwide. T cells play a crucial role in improving the efficacy of current tumor immunotherapies. T-cell depletion is a state of diminished function characterized by the progressive loss of T-cell effector function and self-renewal ability. It is considered a major resistance mechanism to tumor cell immunotherapy. Despite the advances in current research, the molecular mechanisms of T-cell depletion are still not fully elucidated. Future studies should explore the signaling pathways, metabolic pathways, transcriptional regulation, epigenetics, and other multilevel mechanisms in T cell depletion.

In clinical practice, single therapeutic strategies are often insufficient to overcome T-cell depletion and achieve optimal outcomes. Therefore, future research must focus on developing combination therapeutic strategies that target multiple pathways involved in T-cell depletion to enhance tumor immunotherapy. It can be achieved by combining immune checkpoint inhibitors, CAR-T-cell therapy, TCR engineering, tumor vaccines, immunometabolic modulation, TME improvement, and research on drug resistance mechanisms. In addition, in-depth studies on key issues such as indications, dosages, and sequencing of these combination strategies across different patient populations and tumor types are needed, to help provide practical guidance for personalized treatment approaches.

In conclusion, this review offered a comprehensive overview of the current advancements in research on T-cell depletion, emphasizing its clinical manifestations, evaluation methods, mechanisms, and therapeutic strategies. Additionally, this review also proposed potential future research directions for advancing clinical applications and enhancing the fundamental understanding of the important role of T-cell depletion in tumor occurrence and development.

Data Availability

No datasets were generated or analysed during the current study.

References

  1. Choi Y, Shi Y, Haymaker CL, Naing A, Ciliberto G, Hajjar J. T-cell agonists in cancer immunotherapy. J Immunother Cancer 2020, 8(2).

  2. He J, Xiong X, Yang H, Li D, Liu X, Li S, Liao S, Chen S, Wen X, Yu K, et al. Defined tumor antigen-specific T cells potentiate personalized TCR-T cell therapy and prediction of immunotherapy response. Cell Res. 2022;32(6):530–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Shaw DM, Merien F, Braakhuis A, Dulson D. T-cells and their cytokine production: the anti-inflammatory and immunosuppressive effects of strenuous exercise. Cytokine. 2018;104:136–42.

    Article  CAS  PubMed  Google Scholar 

  4. Cao X, Cai SF, Fehniger TA, Song J, Collins LI, Piwnica-Worms DR, Ley TJ. Granzyme B and perforin are important for regulatory T cell-mediated suppression of tumor clearance. Immunity. 2007;27(4):635–46.

    Article  CAS  PubMed  Google Scholar 

  5. Corrado M, Pearce EL. Targeting memory T cell metabolism to improve immunity. J Clin Investig. 2022;132(1).

  6. Pu Y, Ji Q. Tumor-Associated macrophages regulate PD-1/PD-L1 immunosuppression. Front Immunol. 2022;13:874589.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Kong F, Wang C, Zhang J, Wang X, Sun B, Xiao X, Zhang H, Song Y, Jia Y. Chinese herbal medicines for prostate cancer therapy: from experimental research to clinical practice. Chin Herb Med. 2023;15(4):485–95.

    PubMed  PubMed Central  Google Scholar 

  8. Aoki H, Ueha S, Shichino S, Ogiwara H, Shitara K, Shimomura M, Suzuki T, Nakatsura T, Yamashita M, Kitano S, et al. Transient depletion of CD4(+) cells induces remodeling of the TCR repertoire in gastrointestinal Cancer. Cancer Immunol Res. 2021;9(6):624–36.

    Article  CAS  PubMed  Google Scholar 

  9. Kong F, Wang C, Zhao L, Liao D, Wang X, Sun B, Yang P, Jia Y. Traditional Chinese medicines for non-small cell lung cancer: therapies and mechanisms. Chin Herb Med. 2023;15(4):509–15.

    PubMed  PubMed Central  Google Scholar 

  10. Lu J, Wu J, Mao L, Xu H, Wang S. Revisiting PD-1/PD-L pathway in T and B cell response: beyond immunosuppression. Cytokine Growth Factor Rev. 2022;67:58–65.

    Article  CAS  PubMed  Google Scholar 

  11. Delgoffe GM, Xu C, Mackall CL, Green MR, Gottschalk S, Speiser DE, Zehn D, Beavis PA. The role of exhaustion in CAR T cell therapy. Cancer Cell. 2021;39(7):885–8.

    Article  CAS  PubMed  Google Scholar 

  12. Park JA, Wang L, Cheung NV. Modulating tumor infiltrating myeloid cells to enhance bispecific antibody-driven T cell infiltration and anti-tumor response. J Hematol Oncol. 2021;14(1):142.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Dong PY, Liang SL, Li L, Liu J, Zhang XF. Lotus root polysaccharide inhibits the growth of ovarian cancer cells by blocking the cell cycle. Tradit Med Res. 2023;8(8):44.

    Article  Google Scholar 

  14. Hong MMY, Maleki Vareki S. Addressing the Elephant in the immunotherapy room: Effector T-Cell Priming versus Depletion of Regulatory T-Cells by Anti-CTLA-4 therapy. Cancers. 2022;14(6).

  15. Zhang W, Cui N, Ye J, Yang B, Sun Y, Kuang H. Curcumin’s prevention of inflammation-driven early gastric cancer and its molecular mechanism. Chin Herb Med. 2022;14(2):244–53.

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Rizvi NA, Hellmann MD, Snyder A, Kvistborg P, Makarov V, Havel JJ, Lee W, Yuan J, Wong P, Ho TS, et al. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Sci (New York NY). 2015;348(6230):124–8.

    Article  CAS  Google Scholar 

  17. Tumeh PC, Harview CL, Yearley JH, Shintaku IP, Taylor EJ, Robert L, Chmielowski B, Spasic M, Henry G, Ciobanu V, et al. PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature. 2014;515(7528):568–71.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Pauken KE, Sammons MA, Odorizzi PM, Manne S, Godec J, Khan O, Drake AM, Chen Z, Sen DR, Kurachi M, et al. Epigenetic stability of exhausted T cells limits durability of reinvigoration by PD-1 blockade. Volume 354. New York, NY): Science; 2016. pp. 1160–5. 6316.

    Google Scholar 

  19. Li Z, Hao E, Cao R, Lin S, Zou L, Huang T, Du Z, Hou X, Deng J. Analysis on internal mechanism of zedoary turmeric in treatment of liver cancer based on pharmacodynamic substances and pharmacodynamic groups. Chin Herb Med. 2022;14(4):479–93.

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Wherry EJ, Ha SJ, Kaech SM, Haining WN, Sarkar S, Kalia V, Subramaniam S, Blattman JN, Barber DL, Ahmed R. Molecular signature of CD8 + T cell exhaustion during chronic viral infection. Immunity. 2007;27(4):670–84.

    Article  CAS  PubMed  Google Scholar 

  21. Gajewski TF, Schreiber H, Fu YX. Innate and adaptive immune cells in the tumor microenvironment. Nat Immunol. 2013;14(10):1014–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Belk JA, Daniel B, Satpathy AT. Epigenetic regulation of T cell exhaustion. Nat Immunol. 2022;23(6):848–60.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Rao RJ, Yang J, Jiang S, El-Khoury W, Hafeez N, Okawa S, Tai YY, Tang Y, Al Aaraj Y, Sembrat J et al. Post-transcriptional regulation of IFI16 promotes inflammatory endothelial pathophenotypes observed in pulmonary arterial hypertension. bioRxiv: the preprint server for biology. 2024.

  24. Zhang M, Shi Y, Zhang Y, Wang Y, Alotaibi F, Qiu L, Wang H, Peng S, Liu Y, Li Q, et al. miRNA-5119 regulates immune checkpoints in dendritic cells to enhance breast cancer immunotherapy. Cancer Immunol Immunotherapy: CII. 2020;69(6):951–67.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. van Ham M, Teich R, Philipsen L, Niemz J, Amsberg N, Wissing J, Nimtz M, Gröbe L, Kliche S, Thiel N, et al. TCR signalling network organization at the immunological synapses of murine regulatory T cells. Eur J Immunol. 2017;47(12):2043–58.

    Article  PubMed  Google Scholar 

  26. Peng DH, Rodriguez BL, Diao L, Chen L, Wang J, Byers LA, Wei Y, Chapman HA, Yamauchi M, Behrens C, et al. Collagen promotes anti-PD-1/PD-L1 resistance in cancer through LAIR1-dependent CD8(+) T cell exhaustion. Nat Commun. 2020;11(1):4520.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Solomon I, Amann M, Goubier A, Arce Vargas F, Zervas D, Qing C, Henry JY, Ghorani E, Akarca AU, Marafioti T, et al. CD25-T(reg)-depleting antibodies preserving IL-2 signaling on effector T cells enhance effector activation and antitumor immunity. Nat cancer. 2020;1(12):1153–66.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Liang G, Feng G, Chen H, Li L, Hu J, Zhou C, Li J, Shen H, Wu F, Tao C, et al. Changes in the TCR repertoire of T-cell subsets during culture of cytokine-induced killer cells. FEBS Lett. 2022;596(20):2696–705.

    Article  CAS  PubMed  Google Scholar 

  29. Zhang X, Lao M, Xu J, Duan Y, Yang H, Li M, Ying H, He L, Sun K, Guo C et al. Combination cancer immunotherapy targeting TNFR2 and PD-1/PD-L1 signaling reduces immunosuppressive effects in the microenvironment of pancreatic tumors. J Immunother Cancer. 2022;10(3).

  30. Choi H, Cho SY, Schwartz RH, Choi K. Dual effects of Sprouty1 on TCR signaling depending on the differentiation state of the T-cell. Journal of Immunology (Baltimore, Md: 1950). 2006;176(10):6034–6045.

  31. Ai L, Xu A, Xu J. Roles of PD-1/PD-L1 pathway: signaling, Cancer, and Beyond. Advances in experimental medicine and biology. 2020;1248:33–59.

  32. Gu J, Zhou J, Chen Q, Xu X, Gao J, Li X, Shao Q, Zhou B, Zhou H, Wei S, et al. Tumor metabolite lactate promotes tumorigenesis by modulating MOESIN lactylation and enhancing TGF-β signaling in regulatory T cells. Cell Rep. 2022;39(12):110986.

    Article  CAS  PubMed  Google Scholar 

  33. Celada LJ, Rotsinger JE, Young A, Shaginurova G, Shelton D, Hawkins C, Drake WP. Programmed Death-1 inhibition of phosphatidylinositol 3-Kinase/AKT/Mechanistic target of Rapamycin Signaling impairs sarcoidosis CD4(+) T cell proliferation. Am J Respir Cell Mol Biol. 2017;56(1):74–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Li N, Kang Y, Wang L, Huff S, Tang R, Hui H, Agrawal K, Gonzalez GM, Wang Y, Patel SP, et al. ALKBH5 regulates anti-PD-1 therapy response by modulating lactate and suppressive immune cell accumulation in tumor microenvironment. Proc Natl Acad Sci USA. 2020;117(33):20159–70.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Yue M, Hu S, Sun H, Tuo B, Jia B, Chen C, Wang W, Liu J, Liu Y, Sun Z, et al. Extracellular vesicles remodel tumor environment for cancer immunotherapy. Mol Cancer. 2023;22(1):203.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Scharping NE, Menk AV, Moreci RS, Whetstone RD, Dadey RE, Watkins SC, Ferris RL, Delgoffe GM. The Tumor Microenvironment represses T cell mitochondrial Biogenesis to Drive Intratumoral T Cell metabolic insufficiency and dysfunction. Immunity. 2016;45(2):374–88.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Zhai J, Song Z, Chang H, Wang Y, Han N, Liu Z, Yin J. He-Wei Granule enhances anti-tumor activity of cyclophosphamide by changing tumor microenvironment. Chin Herb Med. 2021;14(1):79–89.

    PubMed  PubMed Central  Google Scholar 

  38. Guram K, Kim SS, Wu V, Sanders PD, Patel S, Schoenberger SP, Cohen EEW, Chen SY, Sharabi AB. A threshold model for T-Cell activation in the era of checkpoint blockade immunotherapy. Front Immunol. 2019;10:491.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Wherry EJ, Kurachi M. Molecular and cellular insights into T cell exhaustion. Nat Rev Immunol. 2015;15(8):486–99.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Sosnowska A, Chlebowska-Tuz J, Matryba P, Pilch Z, Greig A, Wolny A, Grzywa TM, Rydzynska Z, Sokolowska O, Rygiel TP, et al. Inhibition of arginase modulates T-cell response in the tumor microenvironment of lung carcinoma. Oncoimmunology. 2021;10(1):1956143.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Cheng J, Yan J, Liu Y, Shi J, Wang H, Zhou H, Zhou Y, Zhang T, Zhao L, Meng X, et al. Cancer-cell-derived fumarate suppresses the anti-tumor capacity of CD8(+) T cells in the tumor microenvironment. Cell Metabol. 2023;35(6):961–e978910.

    Article  CAS  Google Scholar 

  42. Fletcher M, Ramirez ME, Sierra RA, Raber P, Thevenot P, Al-Khami AA, Sanchez-Pino D, Hernandez C, Wyczechowska DD, Ochoa AC, et al. l-Arginine depletion blunts antitumor T-cell responses by inducing myeloid-derived suppressor cells. Cancer Res. 2015;75(2):275–83.

    Article  CAS  PubMed  Google Scholar 

  43. Wen Y, Hou Y, Yi X, Sun S, Guo J, He X, Li T, Cai J, Wang Z. EZH2 activates CHK1 signaling to promote ovarian cancer chemoresistance by maintaining the properties of cancer stem cells. Theranostics. 2021;11(4):1795–813.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Liu M, Li Z, Yao W, Zeng X, Wang L, Cheng J, Ma B, Zhang R, Min W, Wang H. IDO inhibitor synergized with radiotherapy to delay tumor growth by reversing T cell exhaustion. Mol Med Rep. 2020;21(1):445–53.

    CAS  PubMed  Google Scholar 

  45. Liu L, Wang A, Liu X, Han S, Sun Y, Zhang J, Guo L, Zhang Y. Blocking TIGIT/CD155 signalling reverses CD8(+) T cell exhaustion and enhances the antitumor activity in cervical cancer. J Translational Med. 2022;20(1):280.

    Article  CAS  Google Scholar 

  46. He L, Fan Y, Zhang Y, Tu T, Zhang Q, Yuan F, Cheng C. Single-cell transcriptomic analysis reveals circadian rhythm disruption associated with poor prognosis and drug-resistance in lung adenocarcinoma. J Pineal Res. 2022;73(1):e12803.

    Article  CAS  PubMed  Google Scholar 

  47. Chihara N, Madi A, Kondo T, Zhang H, Acharya N, Singer M, Nyman J, Marjanovic ND, Kowalczyk MS, Wang C, et al. Induction and transcriptional regulation of the co-inhibitory gene module in T cells. Nature. 2018;558(7710):454–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Zheng C, Zheng L, Yoo JK, Guo H, Zhang Y, Guo X, Kang B, Hu R, Huang JY, Zhang Q, et al. Landscape of infiltrating T cells in Liver Cancer revealed by single-cell sequencing. Cell. 2017;169(7):1342–e13561316.

    Article  CAS  PubMed  Google Scholar 

  49. Seo H, Chen J, González-Avalos E, Samaniego-Castruita D, Das A, Wang YH, López-Moyado IF, Georges RO, Zhang W, Onodera A, et al. TOX and TOX2 transcription factors cooperate with NR4A transcription factors to impose CD8(+) T cell exhaustion. Proc Natl Acad Sci USA. 2019;116(25):12410–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Chen J, López-Moyado IF, Seo H, Lio CJ, Hempleman LJ, Sekiya T, Yoshimura A, Scott-Browne JP, Rao A. NR4A transcription factors limit CAR T cell function in solid tumours. Nature. 2019;567(7749):530–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Belk JA, Yao W, Ly N, Freitas KA, Chen YT, Shi Q, Valencia AM, Shifrut E, Kale N, Yost KE, et al. Genome-wide CRISPR screens of T cell exhaustion identify chromatin remodeling factors that limit T cell persistence. Cancer Cell. 2022;40(7):768–e786767.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Verdeil G. MAF drives CD8(+) T-cell exhaustion. Oncoimmunology. 2016;5(2):e1082707.

    Article  PubMed  Google Scholar 

  53. Khan O, Giles JR, McDonald S, Manne S, Ngiow SF, Patel KP, Werner MT, Huang AC, Alexander KA, Wu JE, et al. TOX transcriptionally and epigenetically programs CD8(+) T cell exhaustion. Nature. 2019;571(7764):211–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Amabile A, Migliara A, Capasso P, Biffi M, Cittaro D, Naldini L, Lombardo A. Inheritable silencing of endogenous genes by hit-and-run targeted epigenetic editing. Cell. 2016;167(1):219–e232214.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Lei M, Chen N, Xu Y, Gong Q, Gao J. Lithocarpus Polystachyus (Sweet Tea) water extract promotes human hepatocytes HL7702 proliferation through activation of HGF/AKT/ERK signaling pathway. Chin Herb Med. 2022;14(4):576–82.

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Jones DM, Read KA, Oestreich KJ. Dynamic roles for IL-2-STAT5 signaling in effector and regulatory CD4(+) T cell Populations. Journal of immunology (Baltimore, Md: 1950). 2020;205(7):1721–1730.

  57. Rosser EC, Mauri C. Regulatory B cells: origin, phenotype, and function. Immunity. 2015;42(4):607–12.

    Article  CAS  PubMed  Google Scholar 

  58. Lu Y, Li Y, Liu Q, Tian N, Du P, Zhu F, Han Y, Liu X, Liu X, Peng X, et al. MondoA-Thioredoxin-interacting protein Axis maintains Regulatory T-Cell identity and function in Colorectal Cancer Microenvironment. Gastroenterology. 2021;161(2):575–e591516.

    Article  CAS  PubMed  Google Scholar 

  59. Fitzgerald AA, Wang S, Agarwal V, Marcisak EF, Zuo A, Jablonski SA, Loth M, Fertig EJ, MacDougall J, Zhukovsky E et al. DPP inhibition alters the CXCR3 axis and enhances NK and CD8 + T cell infiltration to improve anti-PD1 efficacy in murine models of pancreatic ductal adenocarcinoma. J Immunother Cancer. 2021;9(11).

  60. Deng M, Gui X, Kim J, Xie L, Chen W, Li Z, He L, Chen Y, Chen H, Luo W, et al. LILRB4 signalling in leukaemia cells mediates T cell suppression and tumour infiltration. Nature. 2018;562(7728):605–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Saka D, Gökalp M, Piyade B, Cevik NC, Arik Sever E, Unutmaz D, Ceyhan GO, Demir IE, Asimgil H. Mechanisms of T-Cell exhaustion in pancreatic Cancer. Cancers. 2020;12(8).

  62. Wachsmann TLA, Wouters AK, Remst DFG, Hagedoorn RS, Meeuwsen MH, van Diest E, Leusen J, Kuball J, Falkenburg JHF, Heemskerk MHM. Comparing CAR and TCR engineered T cell performance as a function of tumor cell exposure. Oncoimmunology. 2022;11(1):2033528.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Zhao MF, Qu XJ, Qu JL, Jiang YH, Zhang Y, Hou KZ, Deng H, Liu YP. The role of E3 ubiquitin ligase cbl proteins in interleukin-2-induced Jurkat T-cell activation. Biomed Res Int. 2013;2013:430861.

    Article  PubMed  PubMed Central  Google Scholar 

  64. Levings MK, Bacchetta R, Schulz U, Roncarolo MG. The role of IL-10 and TGF-beta in the differentiation and effector function of T regulatory cells. Int Arch Allergy Immunol. 2002;129(4):263–76.

    Article  CAS  PubMed  Google Scholar 

  65. Li Z, Deng M, Huang F, Jin C, Sun S, Chen H, Liu X, He L, Sadek AH, Zhang CC. LILRB4 ITIMs mediate the T cell suppression and infiltration of acute myeloid leukemia cells. Cell Mol Immunol. 2020;17(3):272–82.

    Article  PubMed  Google Scholar 

  66. Liu Y, Wang X, Liu Y, Yang J, Mao W, Feng C, Wu X, Chen X, Chen L, Dong P. N4-acetylcytidine-dependent GLMP mRNA stabilization by NAT10 promotes head and neck squamous cell carcinoma metastasis and remodels tumor microenvironment through MAPK/ERK signaling pathway. Cell Death Dis. 2023;14(11):712.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Hu Y, Zhou Y, Zhang M, Ge W, Li Y, Yang L, Wei G, Han L, Wang H, Yu S, et al. CRISPR/Cas9-Engineered Universal CD19/CD22 Dual-targeted CAR-T cell therapy for Relapsed/Refractory B-cell Acute Lymphoblastic Leukemia. Clin cancer Research: Official J Am Association Cancer Res. 2021;27(10):2764–72.

    Article  CAS  Google Scholar 

  68. Maciocia PM, Wawrzyniecka PA, Maciocia NC, Burley A, Karpanasamy T, Devereaux S, Hoekx M, O’Connor D, Leon T, Rapoz-D’Silva T, et al. Anti-CCR9 chimeric antigen receptor T cells for T-cell acute lymphoblastic leukemia. Blood. 2022;140(1):25–37.

    Article  CAS  PubMed  Google Scholar 

  69. Zhang C, Wang Z, Yang Z, Wang M, Li S, Li Y, Zhang R, Xiong Z, Wei Z, Shen J, et al. Phase I escalating-dose trial of CAR-T therapy targeting CEA(+) metastatic colorectal cancers. Mol Therapy: J Am Soc Gene Therapy. 2017;25(5):1248–58.

    Article  CAS  Google Scholar 

  70. McKay RR, Hafron JM, Ferro C, Wilfehrt HM, Fitch K, Flanders SC, Fabrizio MD, Schweizer MT. A Retrospective Observational Analysis of Overall Survival with Sipuleucel-T in Medicare Beneficiaries Treated for advanced prostate Cancer. Adv Therapy. 2020;37(12):4910–29.

    Article  Google Scholar 

  71. Kleemann J, Jäger M, Valesky E, Kippenberger S, Kaufmann R, Meissner M. Real-world experience of Talimogene Laherparepvec (T-VEC) in Old and Oldest-Old patients with Melanoma: a retrospective single Center Study. Cancer Manage Res. 2021;13:5699–709.

    Article  Google Scholar 

  72. Holl EK, McNamara MA, Healy P, Anand M, Concepcion RS, Breland CD, Dumbudze I, Tutrone R, Shore N, Armstrong AJ, et al. Prolonged PSA stabilization and overall survival following sipuleucel-T monotherapy in metastatic castration-resistant prostate cancer patients. Prostate Cancer Prostatic Dis. 2019;22(4):588–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Fazel M, AlRawashdh N, Alamer A, Curiel-Lewandrowski C, Abraham I. Is there still a role for talimogene laherparepvec (T-VEC) in advanced melanoma? An indirect efficacy comparison of T-VEC plus ipilimumab combination therapy versus T-VEC alone as salvage therapy in unresectable metastatic melanoma. Expert Opin Biol Ther. 2021;21(12):1647–53.

    Article  CAS  PubMed  Google Scholar 

  74. Yan Z, Cao J, Cheng H, Qiao J, Zhang H, Wang Y, Shi M, Lan J, Fei X, Jin L, et al. A combination of humanised anti-CD19 and anti-BCMA CAR T cells in patients with relapsed or refractory multiple myeloma: a single-arm, phase 2 trial. Lancet Haematol. 2019;6(10):e521–9.

    Article  PubMed  Google Scholar 

  75. Ajona D, Ortiz-Espinosa S, Moreno H, Lozano T, Pajares MJ, Agorreta J, Bértolo C, Lasarte JJ, Vicent S, Hoehlig K, et al. A combined PD-1/C5a blockade synergistically protects against Lung Cancer Growth and Metastasis. Cancer Discov. 2017;7(7):694–703.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Science Foundation of China (No. 82204805), the Key Project of the National Science Fund of Anhui Province (No. 2023AH050866), the Outstanding Young Teacher Project of Colleges and Universities of Anhui Province (No. YQYB2024030), and the Second Affiliated Hospital of Anhui University of Traditional Chinese Medicine “Xinglin Talents” cultivation plan project (No. 2023-0500-48-46).

Funding

This work was supported by the Key Project of the National Science Fund of Anhui Province (No. 2023AH050866), the Outstanding Young Teacher Project of Colleges and Universities of Anhui Province (No. YQYB2024030), and the Second Affiliated Hospital of Anhui University of Traditional Chinese Medicine “Xinglin Talents” cultivation plan project (No. 2023-0500-48-46,2023-0500-48-41).

Author information

Author notes

  1. Xiangfei Su, Mi Zhang and Hong Zhu contributed equally to this work.

Authors and Affiliations

  1. China Association of Chinese Medicine, Beijing, China

    Xiangfei Su

  2. Department of Pharmacy, The Second Affiliated Hospital of Anhui University of Chinese Medicine, No. 300, Shouchun Road, Hefei, Anhui, 230061, China

    Mi Zhang, Yuewei Xu, Li Wang & Ming Cai

  3. School of Pharmacy, Anhui University of Chinese Medicine, Hefei, Anhui, China

    Mi Zhang & Ming Cai

  4. Tongling People’s Hospital, Tongling, Anhui, China

    Hong Zhu

  5. Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, Anhui, China

    Jingwen Cai

  6. Anhui Provincial Children’s Hospital, Hefei, Anhui, China

    Zhen Wang

  7. Key Laboratory of Data Science and Innovation and Development of Traditional Chinese Medicine and Social Sciences of Anhui Province, Anhui University of Chinese Medicine, No. 350, Longzihu Road, Hefei, Anhui, 230012, China

    Chen Shen

Authors
  1. Xiangfei Su
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Mi Zhang
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Hong Zhu
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Jingwen Cai
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Zhen Wang
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Yuewei Xu
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Li Wang
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Chen Shen
    View author publications

    You can also search for this author inPubMed Google Scholar

  9. Ming Cai
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

X Su, M Zhang, and H Zhu drafted the manuscript, J Cai, Z Wang, Y Xu, and Li Wang revised the manuscript, C Shen and M Cai guidance for this work and revised the manuscript. The author(s) read and approved the final manuscript.

Corresponding authors

Correspondence to Chen Shen or Ming Cai.

Ethics declarations

Ethical Approval

Not applicable.

Consent for Publication

The manuscript has been approved for publication by all authors.

Competing Interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Su, X., Zhang, M., Zhu, H. et al. Mechanisms of T-cell Depletion in Tumors and Advances in Clinical Research. Biol Proced Online 27, 5 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12575-025-00265-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12575-025-00265-6

Keywords

Biological Procedures Online

ISSN: 1480-9222

Contact us