Next Article in Journal
GISTs with NTRK Gene Fusions: A Clinicopathological, Immunophenotypic, and Molecular Study
Next Article in Special Issue
Immunotherapy for Triple-Negative Breast Cancer: Combination Strategies to Improve Outcome
Previous Article in Journal
CRAC and SK Channels: Their Molecular Mechanisms Associated with Cancer Cell Development
Previous Article in Special Issue
Natural Blockers of PD-1/PD-L1 Interaction for the Immunotherapy of Triple-Negative Breast Cancer-Brain Metastasis
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Mechanisms and Strategies to Overcome PD-1/PD-L1 Blockade Resistance in Triple-Negative Breast Cancer

1
West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, Chengdu 610041, China
2
State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Collaborative Innovation Center for Biotherapy, Chengdu 610041, China
*
Author to whom correspondence should be addressed.
Cancers 2023, 15(1), 104; https://doi.org/10.3390/cancers15010104
Submission received: 29 November 2022 / Revised: 20 December 2022 / Accepted: 21 December 2022 / Published: 23 December 2022
(This article belongs to the Special Issue Immunotherapy of Triple-Negative Breast Cancer)

Abstract

:

Simple Summary

Breast cancer is the most prevalent malignancy in women. With the improvement of medical treatment, breast cancer has become one of the solid tumors with the best curative effect. However, triple-negative breast cancer is not sensitive to conventional treatment due to its high invasiveness, resulting in a poorer prognosis than other types. The antibodies of programmed death receptor 1 and its ligands represent a new option as immunotherapy for patients with triple negative breast cancer. However, some recent clinical data suggest that a large proportion of patients exhibit primary or acquired resistance to treatment with programmed death receptor antibodies. In this review, we discuss the mechanisms that lead to resistance and also summarize potential strategies to overcome the resistance, improving the therapeutic efficacy of programmed death receptor 1 and its ligand-based antibodies in triple negative breast cancer.

Abstract

Triple-negative breast cancer (TNBC) is characterized by a high rate of systemic metastasis, insensitivity to conventional treatment and susceptibility to drug resistance, resulting in a poor patient prognosis. The immune checkpoint inhibitors (ICIs) represented by antibodies of programmed death receptor 1 (PD-1) and programmed death receptor ligand 1 (PD-L1) have provided new therapeutic options for TNBC. However, the efficacy of PD-1/PD-L1 blockade monotherapy is suboptimal immune response, which may be caused by reduced antigen presentation, immunosuppressive tumor microenvironment, interplay with other immune checkpoints and aberrant activation of oncological signaling in tumor cells. Therefore, to improve the sensitivity of TNBC to ICIs, suitable patients are selected based on reliable predictive markers and treated with a combination of ICIs with other therapies such as chemotherapy, radiotherapy, targeted therapy, oncologic virus and neoantigen-based therapies. This review discusses the current mechanisms underlying the resistance of TNBC to PD-1/PD-L1 inhibitors, the potential biomarkers for predicting the efficacy of anti-PD-1/PD-L1 immunotherapy and recent advances in the combination therapies to increase response rates, the depth of remission and the durability of the benefit of TNBC to ICIs.

1. Introduction

According to the latest data from the International Agency for Research on Cancer of the World Health Organization, breast cancer has replaced lung cancer as the most prevalent malignancy worldwide [1]. Breast cancer is classified into four molecular types based on the expression of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER-2) and Ki-67 in breast cancer. Among them, triple negative breast cancer (TNBC) is characterized by negative ER, PR and HER-2, accounting for 10–20% [2]. Compared with other subtypes of breast cancer, TNBC is more aggressive, with a higher risk of recurrence and a poorer prognosis. Traditional breast cancer treatments include chemotherapy, endocrine therapy and targeted therapy. However, TNBC is unsuitable for endocrine and targeted therapy due to the lack of corresponding targets [3]. TNBC also has an unsatisfactory response to chemotherapy. Patients with advanced TNBC experience early onset of drug resistance during chemotherapy, with a median progression-free survival (PFS) of only 3–6 months and a median overall survival (OS) of only 10–13 months [4]. In recent years, the emergence of immune checkpoint inhibitors (ICIs) is radically altering our conceptions of cancer treatment. Targeting the PD-1/PD-L1 axis with ICIs yields significant anti-tumor activity and may provide long-term survival benefits, particularly for patients with TNBC [5,6]. For PD-L1-positive TNBC patients, treatment with atezolizumab in combination with nab-paclitaxel prolonged median overall survival by 10 months compared to chemotherapy alone [7].
Programmed death receptor 1 (PD-1) is a member of the CD28 superfamily that is expressed mainly in activated T-lymphocytes and myeloid cells, functioning as a crucial immunosuppressive molecule [8,9]. The PD-1 mainly consists of an extracellular immunoglobulin variable region (IgV), a hydrophobic transmembrane region and an intracellular region [10]. The tail of the intracellular region has an immunoreceptor tyrosine-based inhibitory motif (ITIM) and an immunoreceptor tyrosine-based switch motif (ITSM). PD-1 is an essential immune checkpoint receptor for activated T cells and plays a critical role in immunosuppression control. Binding to its ligand programmed death ligand-1 (PD-L1) induces the phosphorylation of tyrosine in ITSM of PD-1, which dephosphorylates downstream protein kinases Syk and PI3K, inhibiting the transcription and translation of genes and cellular factors required for T cell activation (Figure 1) [11,12]. Tumor cells can inhibit the killing function of T cells by high expression of PD-L1, thus contributing to immune escape. Tumor cells upregulate PD-L1 expression mainly through the following pathways: activation of EGFR, MAPK or PI3K-Akt pathway [13,14,15]; high expression of STAT3 and HIF-1 [16] alteration of PD-L1 at the genetic level, for example, the PD-L1 3′ untranslated region (3′ UTR) plays a negative regulatory role in PD-L1 expression, and loss of this gene fragment due to different structural variants correlates with increased PD-L1 expression in tumor cells [17,18]; and microRNA-based control of PD-L1 expression, for example, miR-513 overexpression can block IFN-γ-induced PD-L1 expression in bile duct cells [19,20]. The upregulated PD-L1 binds to PD-1 on the surface of tumor-specific CD8+ T cells, suppressing an anti-tumor immune response. In addition, elevated inflammatory factors such as IFN-γ in the tumor microenvironment (TME) can also induce PD-L1 and PD-L2 expression, resulting in “adaptive immune resistance” [21].
Immune checkpoint inhibitors (ICIs) have been developed to boost the immune killing of tumors by restoring the function of tumor infiltrating CD8+ T cells. ICIs, including PD-1 monoclonal antibody (pembrolizumab), PD-L1 monoclonal antibody (atezolizumab) and CTLA-4 monoclonal antibody (durvalumab), are commonly used in clinical [22,23,24]. These ICIs can restore or improve the patient’s anti-tumor immunity to kill tumor cells by overcoming tumor cell-mediated immune cell dysfunction. In recent years, ICI-based immunotherapy has made breakthroughs in treating melanoma and non-small cell lung cancer. In contrast, breast cancer immunotherapy has remained stagnant because breast cancer was previously considered an immunologically “cold tumor” with low immunogenicity [25,26]. TNBC is the most immunogenic subtype of breast cancer with higher levels of PD-L1 expression and tumor infiltrating lymphocytes (TILs) than other subtypes, suggesting that it is more likely to benefit from treatment with ICIs [27]. However, the limited effectiveness of TNBC to ICIs due to heterogeneity and immunosuppressive microenvironment must be overcome [7,28]. Therefore, it is vital to uncover the underlying mechanism of therapeutic resistance and partial hypo-responsiveness to effectively improve the clinical response rate of cancer patients to ICI treatment. This review summarizes the mechanisms of therapeutic resistance to ICIs in TNBC patients. It proposes potential solutions for overcoming ICI resistance, thereby providing theoretical support for enhancing its clinical anti-TNBC efficacy.

2. Resistance Mechanism of PD-1/PD-L1 Inhibit Therapies

Although ICI therapy has a successful anti-tumor effect in some patients, therapeutic resistance prevents ICIs from being used more widely in the clinical setting. ICI resistance’s complicated and varied mechanisms fall into the three following categories: primary, adaptive and acquired [29]. In contrast to primary resistance, in which tumors initially do not respond to ICIs, acquired resistance occurs after effective ICI treatment, leading to cancer progression or recurrence. Adaptive resistance refers to a tumor’s ability to evade immune attack despite the immune system can recognize it [30]. In this section, we discuss the current mechanisms of ICI resistance from the perspectives of antigen presentation, an immunosuppressive TME, the interplay of multiple immune checkpoints and the abnormal signaling pathways in tumors.

2.1. Disturbed Presentation of Tumor-Specific Antigens

The efficacy of ICIs on tumor cells depends on the killing effects of cytotoxic T lymphocytes (CTLs), which can target tumor-specific antigens (TSAs). The specific load and expression pattern of TSAs associated with the TMBs contribute to the different immunogenicity of tumors. Tumors with low or down-regulated TSAs can escape the immune system surveillance and develop tolerance in the body. Due to the lack of highly immunogenic TSAs to activate the TILs, low-immunogenic malignancies, like pancreatic cancer, have an inefficacy response to PD-1/PD-L1 antibodies [21,31]. However, the tumor cells with highly immunogenic antigens can selectively hide the antigens by reducing gene expression or deleting mutant alleles to avoid T cell-dependent cancer immunoediting [32,33,34]. Breast cancer has a substantially lower median TMB than melanoma and lung cancer, indicating that it is generally less immunogenic. The immunogenicity also varies between subtypes of breast cancer. In a study of 762 primary tumors, the mean mutational burden identified in ER tumors was more significant than in ER+ ones [35,36]. The whole exome sequencing (WES) on 3969 patients with primary or metastatic breast cancer revealed that only 5% (198 cases) had hypermutated genes. These hypermutated tumor subgroups, including TNBC, exhibited increased neoantigen burden and cytolytic activity [37]. Consistent with the reported disparities in mutational burden, a higher response rate of anti-PD-1 therapy in PD-L1-positive tumors is observed in TNBC than in ER+ breast cancer (18.5% vs. 12%) [38]. Although TNBC is the most immunogenic subtype of breast cancer, its response rate to ICIs remains poor. The immunogenicity may decrease during tumor progression due to reduced antigen expression and impaired antigen presentation [39].
Tumors can avoid T cell cytotoxicity by downregulating the antigen presentation by major histocompatibility complex (MHC) molecules [40,41]. In a study of 117 primary breast cancer tissue sections, more than half of the cases (19/32, 59%) in TNBC exhibited MHC-I deficiency, allowing tumor cells to evade the cytotoxic T cell-mediated immune response [42]. H3K27me3 alterations in TNBC reduce MHC-I transcription, which can be restored by epigenetic modulators, such as chidamide and pharmacological inhibitors of PRC2 subunits EZH2 or EED [43,44]. Moreover, the elevated MYC and MAL2 in TNBCs drive immune evasion by reducing MHC-I expression, resulting in resistance to ICI therapy [45,46]. In addition to MHC-I, short MHC-II antigen presentation contributes to ICI resistance. MHC-II expression in tumor cells was tightly related to increased TILs and interferon signaling in TNBC [47]. Compared to MHC-II-negative patients, pembrolizumab-treated TNBC patients with MHC-II expression had a more excellent pCR and better prognosis [48]. However, MHC-II on breast cancer cells provides selection pressure for LAG-3+ and FCRL6+ TILs, which antagonizes MHC-II expression and suppresses the antigen presentation, promoting adaptive resistance to anti-PD-1 treatment [49]. The alteration of other tumor antigen processing and presentation molecules, such as LMP and transporter for antigen presentation (TAP), can also result in ICI resistance [41,50].
Antigen presentation can also be impaired by the immunosuppressive TME, which results in resistance to ICIs. The aberrant differentiation of myeloid cells caused by the IL-10 released by TNBC reduces the number of dendritic cells (DCs) and increases the expression of PD-L1. Simultaneously, CD80 and CD86 cannot be activated due to the absence or low expression of co-stimulatory molecules in peripheral immature DCs, resulting in a decreased proportion of normal mature DCs and an increased immature DCs in peripheral blood. After infiltration into tumors, these immature DCs cannot generate an immune response due to their impaired antigen presentation function and inability to activate T cells, resulting in immune escape and resistance to ICIs [51,52,53].

2.2. Immunosuppressive TME

Numerous immune cells, stromal cells and cytokines are present in the TME of TNBC, which may affect the response of tumor cells to immunotherapy. Tumor-derived cytokines recruit more immunosuppressive cells into TME, which affect the efficacy of anti-PD-1/PD-L1 by suppressing T cell activity. Thus, the alteration of TME is a vital mechanism causing immunotherapy resistance [54].

2.2.1. Immunosuppressive Cells

The function of anti-tumor T cells is suppressed by various immunosuppressive cells found in the TME, such as Treg cells, marrow-derived suppressor cells (MDSCs), and tumor-associated macrophages (TAM) (Figure 2). Treg cells, characterized by the expression of Foxp3, CD25 and CD4, suppress the immune response of other immune cells, functioning as the primary controller of self-tolerance [55]. It has been demonstrated that a high abundance of Treg is significantly associated with a high level of PD-L1 in TNBC and results in low pCR with ICI treatment [56]. Patients with TNBC who have Treg cells in their TME have a worse prognosis, lower relapse-free survival rates and worse rates of overall survival [57,58]. Treg cells inhibit the proliferation of effector T cells by consuming the IL-2 and secreting immunosuppressive molecules like TGF-β, IL-35 and IL-10 [59,60]. The CTLA-4 on Treg cells binds to co-stimulatory molecules CD80 and CD86 on APCs to inhibit the secondary signaling, suppressing antigen presentation [61]. Treg can also directly destroy effector T cells and APCs by releasing perforin and granzyme [62]. Therefore, the Treg infiltration in TNBC inhibits T cells’ cell proliferation and function, leading to therapeutic resistance.
MDSCs, consisting of early myeloid cells, macrophages, immature granulocytes and DCs at different stages of differentiation, are a heterogeneous group of immature bone marrow cells with the capacity to control local immune responses [63]. In patients with TNBC, MDSCs may play a significant role as negative modulators of anti-tumor immunity [64]. TNBC patients have higher levels of MDSCs recruited by chemokines and cytokines produced from tumor cells, including IL-34, CXCL2 and CCL22 [65,66,67]. The recruitment of MDSCs at tumors hinders CTL infiltration and challenges the anti-tumor potentials of T cell-based immunotherapies. MDSCs result in resistance by inhibiting both the innate and adaptive immune response [68,69]. Additionally, MDSCs play a nonimmunologic role in promoting tumor progression by releasing prometastatic factors, including MMP9 and chitinase 3-like 1 [65]. In PD-1 monoclonal antibody-treated mice, reducing the MDSC recruitment by PI3K inhibitors achieves a combined inhibitory effect with PD-1 monoclonal antibody [70,71].
TAMs are differentiated monocytes recruited into the tumors by chemokines like CSF1 and CCL2 [72]. While M1 type macrophages destroy tumor cells and prevent pathogen infection, M2 type macrophages primarily promote tumor growth, invasion and metastasis [73]. A high density of M2 macrophages in TNBC promotes cancer cell proliferation and is associated with a greater risk of metastasis and a worse prognosis [73]. TNBC cells with BRCA1-IRIS-overexpression (IRISOE) can release high quantities of GM-CSF, which attracts macrophages to tumor cells and polarizes them to protumor M2 TAMs. This interplay of IRISOE cells and macrophages results in an immunosuppressive milieu in TNBC tumors that is conducive to the development of immune-evading TNBC [74]. M2 type TAM-mediated progression of TNBC can be stopped by blocking MAPK signaling with MEK inhibitors [75]. Additionally, TAMs have been demonstrated to directly and indirectly regulate the effect of anti-PD-1/PD-L1 on tumor cells by regulating the PD-1/PD-L1 expression, reducing the effector function of PD-1+ TILs, promoting PD-1+ Treg development and activity [76]. CSF-1R inhibitors are available to block macrophage CSF-1R and reduce the number of M2-type macrophages, ultimately increasing the response of tumor cells to PD-1 antibodies [77].

2.2.2. Cytokines

Chemokines and cytokines are another class of modulators in immunotherapy resistance via recruiting the immunosuppressive and regulating the expression of PD-1/PDL-1 in the TME. Elevated TGF-β results in the poor prognosis of TNBC by inducing EMT in tumor cells, recruiting immunosuppressive cells and suppressing CD8+ T cell function [78]. TGF-β has also been found to induce the expression of PD-L1 to promote tumor escape [76]. The TGF-β inhibitor tranilast enhances the anti-tumor effect of immunotherapy by improving the hypoxic environment [79]. The pro-inflammatory cytokine IL-6 released by TNBC cells induces the production of CCL5 and VEGF in lymphatic endothelial cells (LEC), promoting TNBC lymph node metastasis and angiogenesis [80,81,82]. Blocking the IL-6/CCR5 or VEGF signaling can prevent TNBC from metastasis and enhance the inhibitory effect of ICIs on TNBC by upregulating PD-L1 [81]. The levels of tumor-derived IL-18 is significantly correlated with poor survival in TNBC patients. IL-18 in TME of TNBC increases the number of immunosuppressive NK cells and induces PD-1 expression in NK cell subsets, resulting in resistance to ICIs [83,84]. Additionally, the increased expression of guanylate binding protein 5 (GBP5) and deletion of the tumor suppressor transcription factor Elf5 activate the IFN-γ signaling pathway (Figure 3) and promote PD-L1 expression, causing immunotherapy resistance in TNBC [85,86].

2.2.3. T Cell Exhaustion

Additional factors in TME like hypoxia can cause T cell exhaustion and increase the resistance to immunotherapy (Figure 4). During prolonged exposure to cognate antigens, the upregulated PD-1 expression on T cell surfaces leads to T cell exhaustion, a phenotype characterized by loss of proliferation and cytolytic function, followed by deficiencies in cytokine production. Hypoxia causes dysfunction and terminal exhaustion of human T cells via the epigenetic suppression of immune effector genes [87,88]. The exhausted CD8+ T cells with intermediate PD-1 expression can be restored to viability by blocking the PD-1 pathway. However, anti-PD-1 therapy cannot reverse the dysfunctional state of T cells with a high level of PD-1 [89,90]. Reversing the T cell dysfunction using HIF1α/HDAC1/EZH2 inhibitors can overcome the resistance to PD-1 blockade [87].

2.3. Compensatory Upregulation of Alternative Immune Checkpoints

Along with PD-1, a variety of immune inhibitory checkpoints, including TIM-3, LAG3, and T cell immune globulin and ITIM structure domain proteins (TIGIT), are highly expressed and linked to T cell function, which also affect the effectiveness of ICIs (Figure 5) [91,92,93].
An immunosuppressive checkpoint protein known as TIM3 (CD366, HAVCR2) is expressed on the surface of activated T cells, NK cells, and monocytes. TIM-3 inhibits cytotoxic T cell activity upon binding to ligands including phosphatidylserine, CEACAM-1, galactin-9, thereby suppressing anti-tumor immunity and promoting tumor escape, and these ligands are members of the h-galactoside-binding protein family that are overexpressed by TNBC cells [94,95,96,97]. In the presence of TNBC cells (MDA-MB-231 and MDA-MB-468), the use of anti-PD-1 monoclonal antibodies causes a compensatory increase in TIM-3 on the surface of CD4+ T cells, resulting in a suppressive signal and leads to effector T cell depletion [98]. Early clinical trials using anti-TIM-3 have described an overall acceptable safety profile and initial indications of anticancer activity [99]. Clinical trials are currently investigating whether inhibitors of TIM-3 combined with anti-PD-1/PD-L1 inhibitors can improve efficacy while reducing side effects [28].
The LAG-3 (CD223) is expressed after antigenic stimulation of T cells to prevent their overactivation, maintaining autoimmune tolerance [100]. The persistent LAG-3 expression in response to prolonged antigenic stimulation is associated with exhausted CD8+ TILs with a decrease in cytokine secretion and cytolytic activity [101]. A significant positive correlation has been found between the expression of LAG-3 and PD-L1 in TNBC patients [102]. Moreover, blocking PD-1 or PD-L1 in TNBC results in compensatory upregulation of LAG-3 in CD4+ T cells [98,103]. A synergistic blockade of PD-1 and LAG-3 in preclinical mouse models exhibits good responsiveness [101]. In a clinical trial, the combination of the anti-LAG-3 antibody leramilimab, the anti-PD-1 antibody spartalizumab and carboplatin had the best rate of remission in patients with advanced TNBC (ORR 32.4%), albeit with successively increased side effects [104]. Therefore, dual inhibition of LAG-3 and PD-1 is feasible for the combination treatment of TNBC in the future.
High levels of TIGIT and its ligand PVR (poliovirus receptor, CD155) are significantly associated with low overall survival and recurrence-free survival of patients with breast cancers [105]. TIGIT is a type I transmembrane protein with an Ig-like variable extracellular structural domain expressed on memory T cells, regulatory T cells and NK cells [106,107,108]. After binding to PVR, TIGIT inhibits immune response through its cytoplasmic immunoglobulin tail tyrosine-like (ITT) phosphorylation motif and ITIM, resulting in resistance in ICI therapy [109]. Dual blocking of TIGIT and PD-1 inhibits tumor growth in a mouse model of breast cancer [110].

2.4. Abnormal Signaling Transduction in Tumor Cells

Aberrant oncogenic signaling pathways have been found to have a substantial impact on both the stimulation of immunological escape in TNBC cells and the formation of immunosuppressive TME [111]. The activation of the MAPK signaling pathway in TNBC induces the production of VEGF and IL-8, which inhibit T cell recruitment and activity [112,113]. The Ras/MAPK pathway can also suppress antigen presentation by inhibiting MHC molecule expression, which helps TNBC cells escape the immune system. A stronger anti-tumor immune response has also been observed in animal models of breast cancer when MEK inhibitors are combined with PD-1/PD-L1 antibodies [113]. In TNBC patients treated with anti-PD-1/PD-L1, alterations in PTEN have been found to be significantly associated with worse ORR and shorter PFS and OS [114]. PTEN gene deletion is linked to reduced T cell infiltration at the tumor site, reduced T cell expansion after tumor resection and poorer efficacy of PD-1 inhibitor therapy in patients with malignant melanoma [115]. Similarly, according to the Cancer Genome Atlas (TCGA) data, 35% of basal-like tumors (mostly TNBC) exhibit PTEN gene deletion, which is associated with activated PI3K signaling, decreased expression of INF-γ and granzyme B, decreased infiltration of CD8+ T cell, and also upregulated PD-L1 expression [116,117,118]. The WNT signaling pathway is another potential oncogenic pathway that modulates the immune response. Tumors with high β-catenin expression have low numbers of CD103+ DCs in the TME, resulting in impaired antigen delivery and presentation, which in turn affects T cell infiltration and immune response in the microenvironment [119]. TNBC stem cells also constitutively upregulate PD-L1 through the activated WNT signaling pathway [120].

3. Biomarkers for Predicting the Efficacy of Anti-PD-1/PD-L1 Immunotherapy

PD-1/PD-L1 antibodies could restore pre-existing tumor-specific T cells by reducing the inhibitory effect of an active PD-1/PD-L1 axis. Therefore, the efficacy of PD-1/PD-L1 therapy is dependent upon the activity of tumor-reactive T lymphocytes in eradicating tumors, which is associated with the levels of PD-L1 expression, tumor mutational burden (TMB) and microsatellite instability (MSI), TILs and mismatch repair deficiencies. Using these indicators, it is critical to select TNBC patients who are more likely to respond to ICIs.

3.1. PD-L1 Expression Level

The PD-L1 expression levels on tumor cells and immune cells are the primary determinant of ICI response. Therefore, it is a significant biomarker for predicting the efficacy of PD-1/PD-L1 inhibitors in solid tumors, including non-small cell lung cancer (NSCLC), gastric cancer, esophageal cancer, uroepithelial cancer and cervical cancer [121,122]. A study on 654 different tumor specimens found that TNBC had higher PD-L1 expression than other breast cancer subtypes. Similarly, TNBC accounted for 59% of breast tumors with high levels of PD-L1 expression, supporting the feasibility of PD-L1 serving as a biomarker for predicting the ICI efficacy in TNBC [122,123,124]. TNBC patients with high PD-L1 expression are more likely to benefit from PD-1/PD-L1 blockade therapy [125]. Large clinical trials have confirmed that PD-L1-positive patients benefit from ICI therapy using several criteria, such as the combined positive score (CPS) in KEYNOTE-355 and the percentage of TILs in IMpassion130 [126,127]. However, some PD-L1-negative patients still respond to ICIs, which complicates the issue of PD-L1 as an exclusionary predictive biomarker [128]. This inconsistency of results can be partially attributed to the PD-L1 expression on non-tumor cells in the TME, which can promote immune escape of tumors [129]. Additionally, patients with negative biomarkers respond when intersecting biological pathways are activated without the presence of a specific biomarker [122]. In summary, although it is not the only consideration when deciding whether to administer an ICI, PD-L1 expression is one of the important predictors of whether patients will benefit from them.

3.2. TILs

TNBC subtype is associated with the highest TILs levels. TILs are the lymphocytes that aggregate in the tumor tissue or surrounding stroma, which might predict the efficacy of immunotherapy in epithelial tumors [130,131]. It has been shown that TIL levels were higher in TNBC (30%) than that in HER2-positive breast cancer (19%) and luminal breast cancer (13%). Consistently, TNBC usually has greater genetic instability, leading to high TMB and a robust anti-tumor immune response, implying that this subtype is more immunogenic [132]. Rich TILs were highly related to improved survival outcomes in early TNBC, making them a powerful immunotherapy prognostic factor for this subtype [133]. In the IMassion130 clinical study treating advanced or metastatic TNBC with atezolizumab and nab-paclitaxel, PFS and OS were significantly higher in patients with both abundant TILs and high PD-L1 expression [134]. Similarly, high levels of TILs and PD-L1 are also positively associated with pathologic complete remission and overall remission rates in TNBC patients receiving pembrolizumab and chemotherapy in the KEYNOTE-173 study [135]. Collectively, the TILs constitute a potential criterion for selecting patients who will benefit from ICI therapy.

3.3. TMB and MSI

DNA damage is a common phenomenon during biological evolution, which induces mutations that drive carcinogenesis and cancer recurrence. The total amount of somatic mutations, termed TMB, is another predictor of the anti-tumor efficacy of ICIs [136]. Tumor cells with non-synonymous mutations can generate neoantigens that are recognized by T cells as non-self antigenic epitopes, initiating the immunological clearance of tumor cells. The increased production of neoantigens due to a higher level of TMB elicits a stronger tumor-specific immune response [137]. It has been demonstrated that patients with high levels of TMB in melanoma, lung cancer and colorectal cancer respond better to ICIs, increasing their chances of survival [21,138,139,140]. Accordingly, breast cancer patients with high TMB (≥10 mut/Mb) may benefit from ICIs regardless of the mutational process [37,141]. A phase II multicenter trial of nivolumab plus ipilimumab for metastatic HER2-negative breast cancer with high TMB has been conducted to elucidate the impact of high TMB [114]. The median TMB for TNBC was 2.630 mut/Mb, with a prevalence of 5% mutation. Clinical studies suggest that TNBC patients with a high TMB have a longer PSF after being treated with ICIs. Therefore, TMB is one feature of TNBC that can predict response to ICI therapy.
MSI, a unique molecular alteration and hyper-mutable phenotype, is the result of a dysfunctional DNA mismatch repair (MMR) system in cancers. MSI-high (MSI-H) also elevates the mutation burden of tumor-associated genes and the generation of neoantigens, boosting anti-tumor immunity [142,143,144]. However, according to a study in 12,821 different tumor samples from The Cancer Genome Atlas, MMR deficiency was less prevalent in breast cancer with only 1.53% of MSI rates [145]. Furthermore, the expression of the MMR protein MLH1 in TNBC was negatively correlated with PD-L1 expression in stromal immune cells [146]. The higher amounts of tumor-specific antigens induced by MMR gene mutations, which in turn increases the anti-tumor immune response, may account for the greater therapeutic effect of ICIs in MMR-deficient tumors compared to non-MMR-deficient cancers [147]. Similar to this, higher TMB levels lead to increased neoantigen production in TNBC, which may make PD-1/PD-L1 inhibitors more effective [148]. Therefore, MSI might be combined with TMB as a candidate predictor for ICI treatment in TNBC patients [149].

3.4. Driver Gene Mutation

An increasing number of studies have shown that the gain-of-function of oncogenes suppressed anti-tumor immune response by regulating the expression of immune checkpoints. TNBCs with aberrant activation of MYC are resistant to ICI therapy [45]. MYC increases PD-L1 and CD47 expression by directly binding to their promoters [150,151,152]. Mucin 1 (MUC1) elevates PD-L1 transcription by recruiting MYC and NF-κB to the PD-L1 promoter, contributing to immune escape in TNBC [153]. Nuclear AURKA induces PD-L1 expression via an MYC-dependent pathway to mediate an immune evasion of TNBC, while the downregulation of AURKA leads to increased CD8+ T cell infiltration and activation in vivo [154]. Although MYC promotes PD-L1 expression that seems to be a beneficial factor for ICI treatment, it also plays a key role in the regulation of energy metabolism, invasion and angiogenesis, thereby promoting tumor progression [155]. Moreover, it has been observed that THZ1, an inhibitor of the CDK7-p38α-MYC axis, can recruit CD8+ T cells to enhance the anti-PD-1 therapeutic effect in a Lewis murine lung cancer model [156]. Therefore, the aberrant activation of oncogenic MYC causes a poor response to ICIs, providing a predictor and target for ICIs in TNBC.
Additionally, mutations in tumor suppressor genes (TSGs) are also related to the immune response of TNBC. A recent genetic study of TNBC patients revealed that those with mutant TP53 and wild-type PIK3CA have higher levels of immune suppressor cells and molecules in their TME. It is expected that patients with this genotype will respond better to immunotherapy [157]. Patients with PD-1 blockade-resistant TNBC have elevated levels of oncogenic LINK-A, which facilitates the K48-polyubiquitination-mediated degradation of the antigen peptide-loading complex (PLC) and intrinsic tumor suppressors Rb and p53, leading to reduced antigen presentation and tumor-specific immune response [158]. Another study employing next-generation sequencing (NGS) on nine patients with primary TNBC has found that patients with heterozygous loss of PTEN have higher PD-L1 expression levels in TILs, suggesting that patients with PTEN mutations may respond better to ICIs [159]. Additionally, the expression of PPP2R2B, a powerful tumor suppressor that plays an important role in the anti-tumor immune response, is significantly downregulated in TNBC tissues compared to normal breast tissues, along with a suppressed T cell receptor signaling pathway, antigen processing and presentation signaling pathway. The involvement of downregulated PPP2R2B in immune evasion renders it a promising predictor for predicting immunotherapeutic response and guiding the treatment of TNBC [160].

3.5. TNBC Microenvironment Phenotypes

Each TNBC molecular subtype exhibits distinct TME profiles associated with multiple cell types, including fibroblasts, adipose and immune-inflammatory cells, and blood and lymphatic vascular networks [161]. The TNBC microenvironment phenotypes were classified into three heterogeneous clusters, including the “immune-desert” cluster with low immune cell infiltration, the “innate immune-inactivated” cluster with resting innate immune cells and nonimmune stromal cells infiltration, and the “immune-inflamed” cluster, with abundant adaptive and innate immune cells infiltration. These microenvironment clusters had significant prognostic efficacy [152]. Quiescent cancer cells (QCCs) in TNBC constitute immunotherapy-resistant reservoirs by orchestrating a local hypoxic immune-suppressive milieu that blocks T cell function. The microenvironment of HIF-α1-expressing tumor cells was similar to that of QCC, and the TME after knockout was rich in a large number of killer T cells, suggesting that the hypoxic environment caused by HIF-α1 may affect the efficacy of immunotherapy treatment results, which must be taken into account when predicting treatment outcomes [162]. BRCA1-IRIS-overexpressing (IRISOE) TNBC cells secrete high levels of GM-CSF in a HIF-α1- and NF-κB-dependent manner of recruiting macrophages to tumors. The recruited tumor-associated macrophages (TAMs) derived from peripheral blood monocytes in the TNBC microenvironment promote tumor growth and progression by directly and indirectly modulating PD-1/PD-L1 expression. Accordingly, IRISOE TNBC tumors had significantly few CD8+/PD-1+ cytotoxic T cells and more CD25+/FOXP3+ regulatory T cells [74,76]. It has also been found that baseline CD4+ levels in the peripheral blood of TNBC patients correlate significantly with PFS and OS, especially in those receiving immunotherapy in combination with chemotherapy. TNBC patients with higher CD4+/CD8+ ratios have better treatment responses [163].

4. Therapeutic Strategies for Immune Checkpoint PD-1/PD-L1 Inhibitor Resistance

As mentioned above, the effectiveness of PD-1/PD-L1 inhibitors alone is only observed in 10%–30% of tumor patients. The efficacy of the same therapy can vary greatly across patients, between different tumor sites in the same patient, and even between different regions of the same tumors due to the high heterogeneity of TNBC. Additionally, immune resistance also contributes to the inadequate response to ICIs. Therefore, it is necessary to combine anti-PD-1/PD-L1 inhibitors with conventional treatments, including chemotherapy, radiation and targeted therapy to reduce the resistance and improve the anti-tumor effect (Figure 6).

4.1. Combination with Chemotherapy

ICIs, along with chemotherapy, are currently the predominant combinatory anti-tumor therapy. Chemotherapeutic drugs can augment systemic tumor-specific immune responses by enhancing neoantigen release and presentation, stimulating DC production and maturation and inducing macrophages to secrete pro-inflammatory cytokines. In addition, chemotherapy can eliminate immunosuppressive MDSC and Treg, which increases the susceptibility of tumor cells to cytotoxic T cells and improves the efficacy of immunotherapy [164]. The efficacy of atezolizumab in combination with albumin-bound paclitaxel versus albumin-bound paclitaxel alone has been assessed in the IMpassion130 clinical trial that enrolled 902 advanced TNBC patients. According to the interim analysis, PFS improved by 1.7 months in the combination treatment group compared to the alone treatment group in the intention-to-treat (ITT) population and by 2.5 months in the PD-L1-positive subgroup [165,166]. The phase III clinical trial KEYNOTE-355 investigated the efficacy of pembrolizumab in combination with chemotherapy (paclitaxel, paclitaxel or gemcitabine plus carboplatin) for advanced TNBC. The median PFS was higher in the combination therapy group than in the chemotherapy group, including ITT, PD-L1 positive (CPS ≥ 1) and PD-L1 high expression subgroups (CPS ≥ 10) [167]. Therefore, combining the PD-L1 inhibitors and chemotherapy may have better efficacy in TNBC.

4.2. Combination with Radiotherapy

Radiation can remodel the immunological context of the TME by enhancing neoantigen expression and release, triggering the release of pro-inflammatory factors and increasing tumor-infiltrating immune cells [168]. With enhanced tumor-specific antigen release and elevated antigen presentation by DCs, irradiated tumors provide an ‘in situ tumor vaccine’ for the activation of tumor-specific T cells. In addition, radiotherapy-induced apoptotic tumor cells are phagocytosed by DCs and other APCs, the antigens of which can be presented by MHC-Ⅰ molecules and activate endogenous CD8+ T cells [169]. The ability of radiation to promote anti-tumor T cell activation is attracting clinical attention as ICI treatment progresses, and it has been demonstrated that it can overcome ICI resistance in mouse models [169]. In a study examining the combined effects of radiation and PD-L1 inhibitors in mouse models of breast and colon cancer, it has been found that combination therapy can effectively elicit CD8+ T cell responses, optimize the tumor immune microenvironment and control tumor growth [170]. Radiotherapy stimulates the release of CXCL16 from mouse breast cancer cells, which recruits CXCR-6-expressing T cells into TME. In a mouse model inoculated with 4T1 cells, radiotherapy combined with PD-1 antibody delayed tumor growth and inhibited the formation of lung metastases, resulting in increased survival [171,172]. In phase II clinical trial (TONIC), radiation treatment increased TIL and CD8+ T cells in the TME of TNBC, making the TME “hotter” and more susceptible to PD-1 inhibitors [173]. In another phase II clinical trial (Simon 2), an ORR of 33% has been achieved with pembrolizumab in combination with radiotherapy, compared to an ORR of 18.5% with monotherapy [174]. Radiotherapy combined with immunotherapy can enhance and sustain anti-tumor immune responses for both primary and metastatic tumors, but more research is needed to determine the best radiotherapy dose and fractionated irradiation modalities for triggering systemic anti-tumor immunity.

4.3. The Synergistic Effect of ICIs

Immune checkpoints, like CTLA-4 and PD-1, exert their functions in distinct ways and complement each other in the control of adaptive immune responses. PD-1 induces the exhaustion of peripheral T cells, whereas CTLA-4 mainly inhibits T cell activation in the early stages. Therefore, anti-CTLA-4 antibodies can enhance the therapeutic effects of anti-PD-1 antibodies [175,176]. The immunoreceptor TIGIT is a promising new target for cancer immunotherapy. By binding to CD155 on DCs, TIGIT triggers a signaling cascade response that decreases production and secretion of IL-12 and IL-10, contributing to the formation of immune-tolerant DCs [177]. In addition, TIGIT inhibits NK cell degranulation, cytokine production and NK cell-mediated cytotoxicity in CD155+ tumor cells. Interaction of TIGIT+ NK cells with MDSCs expressing CD155 reduces the phosphorylation of ZAP70/Syk and ERK1/2, decreasing the cytolytic capacity of NK cells [178]. The TIGIT/CD155 axis has been shown to mediate resistance to ICI, which may make TIGIT blockers potential candidates for the treatment of patients with immune resistance [179,180]. Given the regulatory role of the TIGIT pathway in T cell and NK cell-mediated tumor recognition, dual blockade of PD-1 and TIGIT effectively increases the expansion of tumor antigen-specific CD8+ T cells in vitro, promoting tumor rejection in a mouse model [181]. In mice injected with EMT6 breast cancer cells, it has been observed that the simultaneous blockade of TIGIT and PD-1 induces stronger anti-tumor immune effects and achieves a complete response (CR) [110]. In addition, there are combination therapies with LAG-3 inhibitors and IDO inhibitors, which are believed to bring new options for patients who are resistant to PD-1/PD-L1 inhibitors [182,183]. In phase I/II clinical trial (NCT02460224), LAG525 (an antibody against LAG-3) in combination with spartalizumab (an antibody against PD-1) has shown durable responses in solid tumors, including TNBC [184]. Combining IDO inhibitor Navoximod with an anti-PD-L1 monoclonal antibody more effectively activates CTLs cells in tumors and inhibits tumor growth [185]. A phase Ib clinical trial including 66 patients with different types of malignancies (including TNBC) showed that navoximod combined with atezolizumab upregulated the expression of IDO and PD-L1 on the surface of all types of tumor cells leading to partial remission in 9% of patients and stable disease in 17%, while PD-L1+ patients had a slightly higher response rate than PD-L1 patients [186].

4.4. Combination with Targeted Therapy

The TNBC with homologous recombination repair deficiency (HRD) is sensitive to PARP inhibitors, which leads to the accumulation of DNA single-strand breaks and double-strand breaks that need to be repaired by homologous recombination enzyme [187,188,189]. The application of PARP inhibitors in the context of BRCA mutations results in a synthetic lethal effect on TNBC cells via inhibiting DNA repair [190,191]. Notably, in a BRCA-mutant basal breast cancer exceptional long-term survivor, a striking tumor eradication was accompanied by a marked infiltration of immune cells containing CD8+ effector cells after PARP inhibitors [192]. The PARP inhibitor olaparib induces CD8+ T cell infiltration and activation by inducing the cGAS/STING-dependent pro-inflammatory cytokine production in tumor cells, providing a rationale for combining PARP inhibition with immunotherapies for the treatment of TNBC [193]. A phase I/II clinical trial (MEDIOLA trial) evaluated the efficacy of the PARP inhibitor Olaparib in combination with Durvalumab for the treatment of germline BRCA mutated metastatic breast cancer. The results showed that the median duration of remission was better in the 10 TNBC patients who received ICIs in combination with targeted therapy than with Olaparib alone [194]. Other clinical trials have evaluated the efficacy and safety of the PARP inhibitor Niraparib in combination with Pembrolizumab in patients with advanced TNBC. The combination therapy improved the ORR and DCR in patients with BRCA mutations compared to wild-type BRCA, resulting in significantly longer median PFS with tolerable overall adverse effects [195].
It has been found that the cyclin D-CDK4 complex reduces the stability of the PD-L1 protein. There is a consensus that the sensitivity of tumor cells to ICIs is related to the level of PD-L1 expression, thus, increasing the level and stability of PD-L1 in tumor cells may improve the therapeutic effect of ICIs. The cyclin D-CDK4/6 increases the level of transcription factor E2F and phosphorylation of the retinoblastoma (Rb), thereby triggering the cell cycle from pre-DNA synthesis (G1 phase) to DNA replication (S1 phase) [196]. The normal expression of the Rb gene is key to the effectiveness of CDK4/6 inhibitors in treating breast cancer. The study confirmed that Rb+ is more common in TNBC patients lacking BRCA1 mutation and the expression level of androgen receptor (AR) is positively correlated with the level of Rb expression, therefore, TNBC patients expressing Rb gene or AR+ TNBC patients may be sensitive to CDK4/6 inhibitors [197]. This might be because the cancer cells lacking the Rb gene could express PD-L1 at higher levels. The CDK inhibitor Palbociclib in combination with the PD-1 monoclonal antibody regimen significantly delays tumor progression and improves OS in TNBC patients [198]. Abemaciclib, a selective CDK4/6 inhibitor, reduces tumor cell growth primarily through an Rb gene-dependent mechanism, and clinical trials of abemaciclib in combination with pembrolizumab for TNBC are ongoing [199].
The receptor tyrosine kinase EGFR is overexpressed in 36%-89% of TNBC patients, which promotes cell proliferation, differentiation and migration [200,201,202,203]. In the early stage of breast cancer, EGFR overexpression is associated with reduced OS and DFS [204]. The EGFR inhibitor gefitinib enhances the efficacy of PD-1 monoclonal antibody by reducing the interaction between PD-L1 and PD-1, enhancing IL-2 expression in T cells, promoting the activation of CD8+ TILs and improving T cell-mediated tumor cell killing [205]. Consequently, gefitinib can reduce the survival rate of EGFR overexpressing cancer cells by reducing PD-L1 expression [206]. The potential of EGFR inhibitors for inducing anti-tumor immunity offers the feasibility of combining the EGFR-targeting therapies, including TKIs and CAR-T with ICIs in EGFR-overexpressed TNBC [207,208].
TNBCs with high levels of vascular endothelial growth factor (VEGF), a proangiogenic molecule produced by the tumors, are associated with a high risk of metastasis [209]). In the tumor immune microenvironment, VEGF-A can upregulate the expression of PD-1 and other immune checkpoints in CD8+ T cells, resulting in PD-1 inhibitor resistance [210]. While blocking the VEGF pathway can promote antigen-specific T cell migration, enhancing the effect of PD-L1 inhibitors like Atezolizumab [211]. Although there are few studies on TNBC, a combination of anti-angiogenic molecules with immunomodulators of inhibitory checkpoints may be a potential strategy for VEGF- producing TNBC.

4.5. Oncolytic Viruses

Oncolytic viruses are a class of viruses that have the ability of self-replication and can take advantage of the inactivation or defect of oncogenes in tumor cells, thus replicating in large numbers in tumor cells and causing lysis and death of tumor cells but normal cell death [212]. In the mouse in situ TNBC model and secondary transplantation tumor model, Maraba virus was found to not only have a strong anti-tumor effect on in situ TNBC but also prevent a recurrence. Systemic intravenous injection of Maraba virus was more effective than intratumoral injection [213]. Maraba virus not only effectively recruited immune cells through chemokines but also upregulated PD-L1 expression in breast cancer cells in 3 TNBC models, including 4T1, EMT6 and E0771 [214]. These results suggest that the efficacy of PD-1 inhibitors could be enhanced by oncolytic virus therapy.

4.6. Neoantigen-Based Immunotherapy

Recent advances in tumor immunotherapies, particularly neoantigen-based cancer vaccines and antibody-based therapies, have been widely studied in breast cancer due to their anti-tumor effects by stimulating an immune response [215]. The combination of ICIs and tumor vaccines will produce a stronger anti-tumor immune response by accelerating the initiation and activation of T cells and blocking the immunosuppressive pathway [216]. Currently, the combination of neoantigen-based tumor vaccines and ICIs are being studied in clinical trials, such as the Durvalumab and PVX-410 vaccine for stage II and III TNBC patients (NCT02826434) [217], and the Durvalumab and Vigil vaccine for metastatic breast cancer (NCT02725489) [218]. Bispecific antibodies are artificial antibodies containing two specific antigen-binding sites, which build a bridge between target cells and functional molecules to stimulate a directed immune response [219]. Due to their ability to target two different checkpoint molecules, bispecific antibodies provide a novel approach to delivering dual-drug ICIs in a single medication. These bispecific antibodies are predicted to be able to prevent the development of therapeutic resistance to existing immunotherapies [220]. Tebotelimab (MGD013) is such a bispecific tetravalent dual affinity re-targeting molecule (DART) that is designed to bind PD-1 and LAG-3. Tebotelimab is being tested in solid tumors and hematologic malignancies in combination with margetuximab, a monoclonal antibody against the Fc segment of HER2 [219,221]. According to preclinical studies, margetuximab exposure in the presence of tebotelimab leads to the upregulation of PD-1 and LAG-3, and enhances the lysis activity of immune cells. Early results from the clinical trial (NCT0321926) showed a tolerable safety profile and encouraging evidence of anti-tumor activity in patients with advanced HER2-positive cancers, including breast cancer, and preliminary evidence of clinical viability [222].

5. Conclusions and Perspective

The appearance of immunotherapy has led to a paradigm shift in the treatment of numerous tumors, including breast cancer. ICIs, represented by PD-1/PD-L1 inhibitors, can effectively improve the prognosis of TNBC patients by overcoming the immunosuppressive TME and restoring the recognition and killing effects of immune cells on cancer cells. Clinical trials with PD-1/PD-L1 inhibitors in TNBC are currently being conducted, however, while promising results have been achieved, several pressing issues have also been revealed. The benefit of ICI monotherapy is limited, with ORRs ranging from 5% to 23%, and even many PD-L1-positive populations do not respond to it. We discussed the resistance mechanisms to ICI treatment, including altered expression and presentation of tumor antigens, synergistic effects of multiple immune checkpoints, the suppressive effect of TME and aberrant activation of oncogenic signaling in tumor cells.
Additionally, multiple mechanisms intertwine and crosstalk in the population, with dynamic counterbalances that affect the physiological and pathological regulation of tumors and immune cells. Therefore, it is not clinically meaningful to find and modulate the resistance targets merely, and even the resistance can be re-established quickly, which cannot completely solve the ICI resistance situation. Screening people who can benefit from ICI therapy based on the predictors, such as PD-L1 expression, TIL assessment and TMB detection, is also one of the means to address the current drug resistance situation. More importantly, the combination of chemotherapy, radiotherapy and targeted therapy will also improve the response rate of TNBC patients to ICIs, but their effectiveness and safety need to be confirmed. In addition, we need to focus on how to minimize the incidence of immune-related adverse events, how to maximize the efficacy and safety of ICI, the dose tolerated by patients and the optimal duration of dosing, all of which need to be addressed by conducting more clinical trials.

Author Contributions

X.C., L.F., Y.H. and Y.W. wrote the manuscript and made the figures, X.C. organized the tables, N.X. conceived, designed and edited the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by grants from National Key R&D Program of China (2020YFA0509400), Guangdong Basic and Applied Basic Research Foundation (2019B030302012), the National Natural Science Foundation of China (81821002, 82130082, 81790251, 81972665, 8226100505), 1·3·5 project for disciplines of excellence, West China Hospital, Sichuan University (ZYGD22007 and ZYJC21004).

Acknowledgments

BioRender was used to create the figures.

Conflicts of Interest

The authors declare no competing interests.

References

  1. Sung, H.; Ferlay, J.; Siegel, R.L.; Laversanne, M.; Soerjomataram, I.; Jemal, A.; Bray, F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA A Cancer J. Clin. 2021, 71, 209–249. [Google Scholar] [CrossRef] [PubMed]
  2. Jiang, Y.Z.; Ma, D.; Suo, C.; Shi, J.; Xue, M.; Hu, X.; Xiao, Y.; Yu, K.D.; Liu, Y.R.; Yu, Y.; et al. Genomic and Transcriptomic Landscape of Triple-Negative Breast Cancers: Subtypes and Treatment Strategies. Cancer Cell 2019, 35, 428–440. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Cho, B.; Han, Y.; Lian, M.; Colditz, G.A.; Weber, J.D.; Ma, C.; Liu, Y. Evaluation of Racial/Ethnic Differences in Treatment and Mortality among Women with Triple-Negative Breast Cancer. JAMA Oncol. 2021, 7, 1016–1023. [Google Scholar] [CrossRef] [PubMed]
  4. Rossi, L.; Mazzara, C.; Pagani, O. Diagnosis and Treatment of Breast Cancer in Young Women. Curr. Treat. Options Oncol. 2019, 20, 86. [Google Scholar] [CrossRef] [PubMed]
  5. Planes-Laine, G.; Rochigneux, P.; Bertucci, F.; Chrétien, A.S.; Viens, P.; Sabatier, R.; Gonçalves, A. PD-1/PD-L1 Targeting in Breast Cancer: The First Clinical Evidences Are Emerging. A Literature Review. Cancers 2019, 11, 1033. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Hartkopf, A.D.; Taran, F.A.; Wallwiener, M.; Walter, C.B.; Krämer, B.; Grischke, E.M.; Brucker, S.Y. PD-1 and PD-L1 Immune Checkpoint Blockade to Treat Breast Cancer. Breast Care 2016, 11, 385–390. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  7. Schmid, P.; Adams, S.; Rugo, H.S.; Schneeweiss, A.; Barrios, C.H.; Iwata, H.; Diéras, V.; Hegg, R.; Im, S.A.; Shaw Wright, G.; et al. Atezolizumab and Nab-Paclitaxel in Advanced Triple-Negative Breast Cancer. N. Engl. J. Med. 2018, 379, 2108–2121. [Google Scholar] [CrossRef]
  8. Ishida, Y.; Agata, Y.; Shibahara, K.; Honjo, T. Induced expression of PD-1, a novel member of the immunoglobulin gene superfamily, upon programmed cell death. EMBO J. 1992, 11, 3887–3895. [Google Scholar] [CrossRef] [PubMed]
  9. Ahmadzadeh, M.; Johnson, L.A.; Heemskerk, B.; Wunderlich, J.R.; Dudley, M.E.; White, D.E.; Rosenberg, S.A. Tumor antigen-specific CD8 T cells infiltrating the tumor express high levels of PD-1 and are functionally impaired. Blood 2009, 114, 1537–1544. [Google Scholar] [CrossRef]
  10. Neel, B.G.; Gu, H.; Pao, L. The ′Shp′ing news: SH2 domain-containing tyrosine phosphatases in cell signaling. Trends Biochem. Sci. 2003, 28, 284–293. [Google Scholar] [CrossRef] [PubMed]
  11. Ribas, A.; Wolchok, J.D. Cancer immunotherapy using checkpoint blockade. Science 2018, 359, 1350–1355. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Okazaki, T.; Maeda, A.; Nishimura, H.; Kurosaki, T.; Honjo, T. PD-1 immunoreceptor inhibits B cell receptor-mediated signaling by recruiting src homology 2-domain-containing tyrosine phosphatase 2 to phosphotyrosine. Proc. Natl. Acad. Sci. USA 2001, 98, 13866–13871. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Zhao, R.; Song, Y.; Wang, Y.; Huang, Y.; Li, Z.; Cui, Y.; Yi, M.; Xia, L.; Zhuang, W.; Wu, X.; et al. PD-1/PD-L1 blockade rescue exhausted CD8+ T cells in gastrointestinal stromal tumours via the PI3K/Akt/mTOR signalling pathway. Cell Prolif. 2019, 52, e12571. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Stutvoet, T.S.; Kol, A.; de Vries, E.G.; de Bruyn, M.; Fehrmann, R.S.; Terwisscha van Scheltinga, A.G.; de Jong, S. MAPK pathway activity plays a key role in PD-L1 expression of lung adenocarcinoma cells. J. Pathol. 2019, 249, 52–64. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Doi, T.; Ishikawa, T.; Okayama, T.; Oka, K.; Mizushima, K.; Yasuda, T.; Sakamoto, N.; Katada, K.; Kamada, K.; Uchiyama, K.; et al. The JAK/STAT pathway is involved in the upregulation of PD-L1 expression in pancreatic cancer cell lines. Oncol. Rep. 2017, 37, 1545–1554. [Google Scholar] [CrossRef] [Green Version]
  16. Shurin, M.R.; Umansky, V. Cross-talk between HIF and PD-1/PD-L1 pathways in carcinogenesis and therapy. J. Clin. Investig. 2022, 132, e159473. [Google Scholar] [CrossRef]
  17. Kataoka, K.; Shiraishi, Y.; Takeda, Y.; Sakata, S.; Matsumoto, M.; Nagano, S.; Maeda, T.; Nagata, Y.; Kitanaka, A.; Mizuno, S.; et al. Aberrant PD-L1 expression through 3′-UTR disruption in multiple cancers. Nature 2016, 534, 402–406. [Google Scholar] [CrossRef]
  18. Green, M.R.; Monti, S.; Rodig, S.J.; Juszczynski, P.; Currie, T.; O’Donnell, E.; Chapuy, B.; Takeyama, K.; Neuberg, D.; Golub, T.R.; et al. Integrative analysis reveals selective 9p24.1 amplification, increased PD-1 ligand expression, and further induction via JAK2 in nodular sclerosing Hodgkin lymphoma and primary mediastinal large B-cell lymphoma. Blood 2010, 116, 3268–3277. [Google Scholar] [CrossRef] [Green Version]
  19. Bayraktar, R.; Van Roosbroeck, K. miR-155 in cancer drug resistance and as target for miRNA-based therapeutics. Cancer Metastasis Rev. 2018, 37, 33–44. [Google Scholar] [CrossRef]
  20. Gong, A.Y.; Zhou, R.; Hu, G.; Li, X.; Splinter, P.L.; O’Hara, S.P.; LaRusso, N.F.; Soukup, G.A.; Dong, H.; Chen, X.M. MicroRNA-513 regulates B7-H1 translation and is involved in IFN-gamma-induced B7-H1 expression in cholangiocytes. J. Immunol. 2009, 182, 1325–1333. [Google Scholar] [CrossRef]
  21. Rizvi, N.A.; Hellmann, M.D.; Snyder, A.; Kvistborg, P.; Makarov, V.; Havel, J.J.; Lee, W.; Yuan, J.; Wong, P.; Ho, T.S.; et al. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science 2015, 348, 124–128. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. André, T.; Shiu, K.K.; Kim, T.W.; Jensen, B.V.; Jensen, L.H.; Punt, C.; Smith, D.; Garcia-Carbonero, R.; Benavides, M.; Gibbs, P.; et al. Pembrolizumab in Microsatellite-Instability-High Advanced Colorectal Cancer. N. Engl. J. Med. 2020, 383, 2207–2218. [Google Scholar] [CrossRef] [PubMed]
  23. Kwapisz, D. Pembrolizumab and atezolizumab in triple-negative breast cancer. Cancer Immunol. Immunother. 2021, 70, 607–617. [Google Scholar] [CrossRef]
  24. Loibl, S.; Untch, M.; Burchardi, N.; Huober, J.; Sinn, B.V.; Blohmer, J.U.; Grischke, E.M.; Furlanetto, J.; Tesch, H.; Hanusch, C.; et al. A randomised phase II study investigating durvalumab in addition to an anthracycline taxane-based neoadjuvant therapy in early triple-negative breast cancer: Clinical results and biomarker analysis of GeparNuevo study. Ann. Oncol. Off. J. Eur. Soc. Med. Oncol. 2019, 30, 1279–1288. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Bense, R.D.; Sotiriou, C.; Piccart-Gebhart, M.J.; Haanen, J.; van Vugt, M.; de Vries, E.G.E.; Schröder, C.P.; Fehrmann, R.S.N. Relevance of Tumor-Infiltrating Immune Cell Composition and Functionality for Disease Outcome in Breast Cancer. J. Natl. Cancer Inst. 2017, 109, 372–380. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Loi, S.; Sirtaine, N.; Piette, F.; Salgado, R.; Viale, G.; Van Eenoo, F.; Rouas, G.; Francis, P.; Crown, J.P.; Hitre, E.; et al. Prognostic and predictive value of tumor-infiltrating lymphocytes in a phase III randomized adjuvant breast cancer trial in node-positive breast cancer comparing the addition of docetaxel to doxorubicin with doxorubicin-based chemotherapy: BIG 02-98. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 2013, 31, 860–867. [Google Scholar] [CrossRef] [PubMed]
  27. Liu, Z.; Jiang, Z.; Gao, Y.; Wang, L.; Chen, C.; Wang, X. TP53 Mutations Promote Immunogenic Activity in Breast Cancer. J. Oncol. 2019, 2019, 5952836. [Google Scholar] [CrossRef] [Green Version]
  28. Andrews, L.P.; Yano, H.; Vignali, D.A.A. Inhibitory receptors and ligands beyond PD-1, PD-L1 and CTLA-4: Breakthroughs or backups. Nat. Immunol. 2019, 20, 1425–1434. [Google Scholar] [CrossRef]
  29. Sharma, P.; Hu-Lieskovan, S.; Wargo, J.A.; Ribas, A. Primary, Adaptive, and Acquired Resistance to Cancer Immunotherapy. Cell 2017, 168, 707–723. [Google Scholar] [CrossRef] [Green Version]
  30. Kim, T.K.; Vandsemb, E.N.; Herbst, R.S.; Chen, L. Adaptive immune resistance at the tumour site: Mechanisms and therapeutic opportunities. Nat. Rev. Drug Discov. 2022, 21, 529–540. [Google Scholar] [CrossRef]
  31. Patel, S.A.; Minn, A.J. Combination Cancer Therapy with Immune Checkpoint Blockade: Mechanisms and Strategies. Immunity 2018, 48, 417–433. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Matsushita, H.; Vesely, M.D.; Koboldt, D.C.; Rickert, C.G.; Uppaluri, R.; Magrini, V.J.; Arthur, C.D.; White, J.M.; Chen, Y.S.; Shea, L.K.; et al. Cancer exome analysis reveals a T-cell-dependent mechanism of cancer immunoediting. Nature 2012, 482, 400–404. [Google Scholar] [CrossRef] [Green Version]
  33. Verdegaal, E.M.; de Miranda, N.F.; Visser, M.; Harryvan, T.; van Buuren, M.M.; Andersen, R.S.; Hadrup, S.R.; van der Minne, C.E.; Schotte, R.; Spits, H.; et al. Neoantigen landscape dynamics during human melanoma-T cell interactions. Nature 2016, 536, 91–95. [Google Scholar] [CrossRef] [PubMed]
  34. Anagnostou, V.; Smith, K.N.; Forde, P.M.; Niknafs, N.; Bhattacharya, R.; White, J.; Zhang, T.; Adleff, V.; Phallen, J.; Wali, N.; et al. Evolution of Neoantigen Landscape during Immune Checkpoint Blockade in Non-Small Cell Lung Cancer. Cancer Discov. 2017, 7, 264–276. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Vogelstein, B.; Papadopoulos, N.; Velculescu, V.E.; Zhou, S.; Diaz, L.A., Jr.; Kinzler, K.W. Cancer genome landscapes. Science 2013, 339, 1546–1558. [Google Scholar] [CrossRef] [PubMed]
  36. Haricharan, S.; Bainbridge, M.N.; Scheet, P.; Brown, P.H. Somatic mutation load of estrogen receptor-positive breast tumors predicts overall survival: An analysis of genome sequence data. Breast Cancer Res. Treat. 2014, 146, 211–220. [Google Scholar] [CrossRef] [Green Version]
  37. Barroso-Sousa, R.; Jain, E.; Cohen, O.; Kim, D.; Buendia-Buendia, J.; Winer, E.; Lin, N.; Tolaney, S.M.; Wagle, N. Prevalence and mutational determinants of high tumor mutation burden in breast cancer. Ann. Oncol. Off. J. Eur. Soc. Med. Oncol. 2020, 31, 387–394. [Google Scholar] [CrossRef] [Green Version]
  38. Rugo, H.; Delord, J.-P.; Im, S.-A.; Ott, P.; Piha-Paul, S.; Bedard, P.; Sachdev, J.; Le Tourneau, C.; van Brummelen, E.; Varga, A.; et al. Abstract S5-07: Preliminary efficacy and safety of pembrolizumab (MK-3475) in patients with PD-L1–positive, estrogen receptor-positive (ER+)/HER2-negative advanced breast cancer enrolled in KEYNOTE-028. Cancer Res. 2016, 76, S5. [Google Scholar] [CrossRef]
  39. Li, Z.; Qiu, Y.; Lu, W.; Jiang, Y.; Wang, J. Immunotherapeutic interventions of Triple Negative Breast Cancer. J. Transl. Med. 2018, 16, 147. [Google Scholar] [CrossRef] [Green Version]
  40. Zhao, M.Z.; Sun, Y.; Jiang, X.F.; Liu, L.; Liu, L.; Sun, L.X. Promotion on NLRC5 upregulating MHC-I expression by IFN-γ in MHC-I-deficient breast cancer cells. Immunol. Res. 2019, 67, 497–504. [Google Scholar] [CrossRef]
  41. Vitale, M.; Rezzani, R.; Rodella, L.; Zauli, G.; Grigolato, P.; Cadei, M.; Hicklin, D.J.; Ferrone, S. HLA class I antigen and transporter associated with antigen processing (TAP1 and TAP2) down-regulation in high-grade primary breast carcinoma lesions. Cancer Res. 1998, 58, 737–742. [Google Scholar] [PubMed]
  42. Dusenbery, A.C.; Maniaci, J.L.; Hillerson, N.D.; Dill, E.A.; Bullock, T.N.; Mills, A.M. MHC Class I Loss in Triple-negative Breast Cancer: A Potential Barrier to PD-1/PD-L1 Checkpoint Inhibitors. Am. J. Surg. Pathol. 2021, 45, 701–707. [Google Scholar] [CrossRef] [PubMed]
  43. Lehmann, B.D.; Colaprico, A.; Silva, T.C.; Chen, J.; An, H.; Ban, Y.; Huang, H.; Wang, L.; James, J.L.; Balko, J.M.; et al. Multi-omics analysis identifies therapeutic vulnerabilities in triple-negative breast cancer subtypes. Nat. Commun. 2021, 12, 6276. [Google Scholar] [CrossRef] [PubMed]
  44. Tu, K.; Yu, Y.; Wang, Y.; Yang, T.; Hu, Q.; Qin, X.; Tu, J.; Yang, C.; Kong, L.; Zhang, Z. Combination of Chidamide-Mediated Epigenetic Modulation with Immunotherapy: Boosting Tumor Immunogenicity and Response to PD-1/PD-L1 Blockade. ACS Appl. Mater. Interfaces 2021, 13, 39003–39017. [Google Scholar] [CrossRef]
  45. Lee, J.V.; Housley, F.; Yau, C.; Nakagawa, R.; Winkler, J.; Anttila, J.M.; Munne, P.M.; Savelius, M.; Houlahan, K.E.; Van de Mark, D.; et al. Combinatorial immunotherapies overcome MYC-driven immune evasion in triple negative breast cancer. Nat. Commun. 2022, 13, 3671. [Google Scholar] [CrossRef]
  46. Fang, Y.; Wang, L.; Wan, C.; Sun, Y.; Van der Jeught, K.; Zhou, Z.; Dong, T.; So, K.M.; Yu, T.; Li, Y.; et al. MAL2 drives immune evasion in breast cancer by suppressing tumor antigen presentation. J. Clin. Investig. 2021, 131, e140837. [Google Scholar] [CrossRef]
  47. Park, I.A.; Hwang, S.H.; Song, I.H.; Heo, S.H.; Kim, Y.A.; Bang, W.S.; Park, H.S.; Lee, M.; Gong, G.; Lee, H.J. Expression of the MHC class II in triple-negative breast cancer is associated with tumor-infiltrating lymphocytes and interferon signaling. PLoS ONE 2017, 12, e0182786. [Google Scholar] [CrossRef] [Green Version]
  48. Gonzalez-Ericsson, P.I.; Wulfkhule, J.D.; Gallagher, R.I.; Sun, X.; Axelrod, M.L.; Sheng, Q.; Luo, N.; Gomez, H.; Sanchez, V.; Sanders, M.; et al. Tumor-Specific Major Histocompatibility-II Expression Predicts Benefit to Anti-PD-1/L1 Therapy in Patients With HER2-Negative Primary Breast Cancer. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2021, 27, 5299–5306. [Google Scholar] [CrossRef]
  49. Johnson, D.B.; Nixon, M.J.; Wang, Y.; Wang, D.Y.; Castellanos, E.; Estrada, M.V.; Ericsson-Gonzalez, P.I.; Cote, C.H.; Salgado, R.; Sanchez, V.; et al. Tumor-specific MHC-II expression drives a unique pattern of resistance to immunotherapy via LAG-3/FCRL6 engagement. JCI Insight 2018, 3, e120360. [Google Scholar] [CrossRef] [Green Version]
  50. Wang, Z.; Wu, X. Study and analysis of antitumor resistance mechanism of PD1/PD-L1 immune checkpoint blocker. Cancer Med. 2020, 9, 8086–8121. [Google Scholar] [CrossRef]
  51. Martín-Gayo, E.; Sierra-Filardi, E.; Corbí, A.L.; Toribio, M.L. Plasmacytoid dendritic cells resident in human thymus drive natural Treg cell development. Blood 2010, 115, 5366–5375. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Li, X.; Du, H.; Zhan, S.; Liu, W.; Wang, Z.; Lan, J.; PuYang, L.; Wan, Y.; Qu, Q.; Wang, S.; et al. The interaction between the soluble programmed death ligand-1 (sPD-L1) and PD-1(+) regulator B cells mediates immunosuppression in triple-negative breast cancer. Front. Immunol. 2022, 13, 830606. [Google Scholar] [CrossRef] [PubMed]
  53. Deng, X.X.; Jiao, Y.N.; Hao, H.F.; Xue, D.; Bai, C.C.; Han, S.Y. Taraxacum mongolicum extract inhibited malignant phenotype of triple-negative breast cancer cells in tumor-associated macrophages microenvironment through suppressing IL-10/STAT3/PD-L1 signaling pathways. J. Ethnopharmacol. 2021, 274, 113978. [Google Scholar] [CrossRef] [PubMed]
  54. Kondou, R.; Iizuka, A.; Nonomura, C.; Miyata, H.; Ashizawa, T.; Nagashima, T.; Ohshima, K.; Urakami, K.; Kusuhara, M.; Yamaguchi, K.; et al. Classification of tumor microenvironment immune types based on immune response-associated gene expression. Int. J. Oncol. 2019, 54, 219–228. [Google Scholar] [CrossRef] [Green Version]
  55. Sakaguchi, S.; Yamaguchi, T.; Nomura, T.; Ono, M. Regulatory T cells and immune tolerance. Cell 2008, 133, 775–787. [Google Scholar] [CrossRef] [Green Version]
  56. Oshi, M.; Asaoka, M.; Tokumaru, Y.; Angarita, F.A.; Yan, L.; Matsuyama, R.; Zsiros, E.; Ishikawa, T.; Endo, I.; Takabe, K. Abundance of Regulatory T Cell (Treg) as a Predictive Biomarker for Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer. Cancers 2020, 12, 3038. [Google Scholar] [CrossRef]
  57. Bohling, S.D.; Allison, K.H. Immunosuppressive regulatory T cells are associated with aggressive breast cancer phenotypes: A potential therapeutic target. Mod. Pathol. Off. J. U. S. Can. Acad. Pathol. Inc. 2008, 21, 1527–1532. [Google Scholar] [CrossRef] [Green Version]
  58. Ohara, M.; Yamaguchi, Y.; Matsuura, K.; Murakami, S.; Arihiro, K.; Okada, M. Possible involvement of regulatory T cells in tumor onset and progression in primary breast cancer. Cancer Immunol. Immunother. 2009, 58, 441–447. [Google Scholar] [CrossRef] [Green Version]
  59. Chinen, T.; Kannan, A.K.; Levine, A.G.; Fan, X.; Klein, U.; Zheng, Y.; Gasteiger, G.; Feng, Y.; Fontenot, J.D.; Rudensky, A.Y. An essential role for the IL-2 receptor in T(reg) cell function. Nat. Immunol. 2016, 17, 1322–1333. [Google Scholar] [CrossRef]
  60. Taylor, A.; Verhagen, J.; Blaser, K.; Akdis, M.; Akdis, C.A. Mechanisms of immune suppression by interleukin-10 and transforming growth factor-beta: The role of T regulatory cells. Immunology 2006, 117, 433–442. [Google Scholar] [CrossRef]
  61. Sade-Feldman, M.; Jiao, Y.J.; Chen, J.H.; Rooney, M.S.; Barzily-Rokni, M.; Eliane, J.P.; Bjorgaard, S.L.; Hammond, M.R.; Vitzthum, H.; Blackmon, S.M.; et al. Resistance to checkpoint blockade therapy through inactivation of antigen presentation. Nat. Commun. 2017, 8, 1136. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  62. Liu, L.; Cheng, X.; Yang, H.; Lian, S.; Jiang, Y.; Liang, J.; Chen, X.; Mo, S.; Shi, Y.; Zhao, S.; et al. BCL-2 expression promotes immunosuppression in chronic lymphocytic leukemia by enhancing regulatory T cell differentiation and cytotoxic T cell exhaustion. Mol. Cancer 2022, 21, 59. [Google Scholar] [CrossRef] [PubMed]
  63. Condamine, T.; Kumar, V.; Ramachandran, I.R.; Youn, J.I.; Celis, E.; Finnberg, N.; El-Deiry, W.S.; Winograd, R.; Vonderheide, R.H.; English, N.R.; et al. ER stress regulates myeloid-derived suppressor cell fate through TRAIL-R-mediated apoptosis. J. Clin. Investig. 2014, 124, 2626–2639. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  64. Li, W.; Tanikawa, T.; Kryczek, I.; Xia, H.; Li, G.; Wu, K.; Wei, S.; Zhao, L.; Vatan, L.; Wen, B.; et al. Aerobic Glycolysis Controls Myeloid-Derived Suppressor Cells and Tumor Immunity via a Specific CEBPB Isoform in Triple-Negative Breast Cancer. Cell Metab. 2018, 28, 87–103.e106. [Google Scholar] [CrossRef] [Green Version]
  65. Kumar, S.; Wilkes, D.W.; Samuel, N.; Blanco, M.A.; Nayak, A.; Alicea-Torres, K.; Gluck, C.; Sinha, S.; Gabrilovich, D.; Chakrabarti, R. ΔNp63-driven recruitment of myeloid-derived suppressor cells promotes metastasis in triple-negative breast cancer. J. Clin. Investig. 2018, 128, 5095–5109. [Google Scholar] [CrossRef] [Green Version]
  66. Yu, B.; Luo, F.; Sun, B.; Liu, W.; Shi, Q.; Cheng, S.Y.; Chen, C.; Chen, G.; Li, Y.; Feng, H. KAT6A Acetylation of SMAD3 Regulates Myeloid-Derived Suppressor Cell Recruitment, Metastasis, and Immunotherapy in Triple-Negative Breast Cancer. Adv. Sci. 2022, 9, e2105793. [Google Scholar] [CrossRef]
  67. Kajihara, N.; Kobayashi, T.; Otsuka, R.; Nio-Kobayashi, J.; Oshino, T.; Takahashi, M.; Imanishi, S.; Hashimoto, A.; Wada, H.; Seino, K.I. Tumor-derived interleukin-34 creates an immunosuppressive and chemoresistant tumor microenvironment by modulating myeloid-derived suppressor cells in triple-negative breast cancer. Cancer Immunol. Immunother. 2022. Available online: https://link.springer.com/article/10.1007/s00262-022-03293-3 (accessed on 14 September 2022). [CrossRef]
  68. Parihar, R.; Rivas, C.; Huynh, M.; Omer, B.; Lapteva, N.; Metelitsa, L.S.; Gottschalk, S.M.; Rooney, C.M. NK Cells Expressing a Chimeric Activating Receptor Eliminate MDSCs and Rescue Impaired CAR-T Cell Activity against Solid Tumors. Cancer Immunol. Res. 2019, 7, 363–375. [Google Scholar] [CrossRef]
  69. Wu, J.; Wang, Z.T.; Wang, Q. Effect of Expression Level Changes of M-MDSC to Related Immune Function in Patients with Primary ITP. Zhongguo Shi Yan Xue Ye Xue Za Zhi 2021, 29, 581–585. [Google Scholar] [CrossRef]
  70. Rico, L.G.; Aguilar Hernández, A.; Ward, M.D.; Bradford, J.A.; Juncà, J.; Rosell, R.; Petriz, J. Unmasking the expression of PD-L1 in Myeloid Derived Suppressor Cells: A case study in lung cancer to discover new drugs with specific on-target efficacy. Transl. Oncol. 2021, 14, 100969. [Google Scholar] [CrossRef]
  71. Wu, J.; Zhao, X.; Sun, Q.; Jiang, Y.; Zhang, W.; Luo, J.; Li, Y. Synergic effect of PD-1 blockade and endostar on the PI3K/AKT/mTOR-mediated autophagy and angiogenesis in Lewis lung carcinoma mouse model. Biomed. Pharmacother. 2020, 125, 109746. [Google Scholar] [CrossRef] [PubMed]
  72. Ngambenjawong, C.; Gustafson, H.H.; Pun, S.H. Progress in tumor-associated macrophage (TAM)-targeted therapeutics. Adv. Drug Deliv. Rev. 2017, 114, 206–221. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  73. Wu, K.; Lin, K.; Li, X.; Yuan, X.; Xu, P.; Ni, P.; Xu, D. Redefining Tumor-Associated Macrophage Subpopulations and Functions in the Tumor Microenvironment. Front. Immunol. 2020, 11, 1731. [Google Scholar] [CrossRef] [PubMed]
  74. Sami, E.; Paul, B.T.; Koziol, J.A.; ElShamy, W.M. The Immunosuppressive Microenvironment in BRCA1-IRIS-Overexpressing TNBC Tumors Is Induced by Bidirectional Interaction with Tumor-Associated Macrophages. Cancer Res. 2020, 80, 1102–1117. [Google Scholar] [CrossRef] [Green Version]
  75. Zhang, Q.; Le, K.; Xu, M.; Zhou, J.; Xiao, Y.; Yang, W.; Jiang, Y.; Xi, Z.; Huang, T. Combined MEK inhibition and tumor-associated macrophages depletion suppresses tumor growth in a triple-negative breast cancer mouse model. Int. Immunopharmacol. 2019, 76, 105864. [Google Scholar] [CrossRef]
  76. Santoni, M.; Romagnoli, E.; Saladino, T.; Foghini, L.; Guarino, S.; Capponi, M.; Giannini, M.; Cognigni, P.D.; Ferrara, G.; Battelli, N. Triple negative breast cancer: Key role of Tumor-Associated Macrophages in regulating the activity of anti-PD-1/PD-L1 agents. Biochim. Et Biophys. Acta. Rev. Cancer. 2018, 1869, 78–84. [Google Scholar] [CrossRef]
  77. Li, M.; Li, M.; Yang, Y.; Liu, Y.; Xie, H.; Yu, Q.; Tian, L.; Tang, X.; Ren, K.; Li, J.; et al. Remodeling tumor immune microenvironment via targeted blockade of PI3K-γ and CSF-1/CSF-1R pathways in tumor associated macrophages for pancreatic cancer therapy. J. Control. Release Off. J. Control. Release Soc. 2020, 321, 23–35. [Google Scholar] [CrossRef]
  78. Lin, R.L.; Zhao, L.J. Mechanistic basis and clinical relevance of the role of transforming growth factor-β in cancer. Cancer Biol. Med. 2015, 12, 385–393. [Google Scholar] [CrossRef]
  79. Panagi, M.; Voutouri, C.; Mpekris, F.; Papageorgis, P.; Martin, M.R.; Martin, J.D.; Demetriou, P.; Pierides, C.; Polydorou, C.; Stylianou, A.; et al. TGF-β inhibition combined with cytotoxic nanomedicine normalizes triple negative breast cancer microenvironment towards anti-tumor immunity. Theranostics 2020, 10, 1910–1922. [Google Scholar] [CrossRef]
  80. Hartman, Z.C.; Poage, G.M.; den Hollander, P.; Tsimelzon, A.; Hill, J.; Panupinthu, N.; Zhang, Y.; Mazumdar, A.; Hilsenbeck, S.G.; Mills, G.B.; et al. Growth of triple-negative breast cancer cells relies upon coordinate autocrine expression of the proinflammatory cytokines IL-6 and IL-8. Cancer Res. 2013, 73, 3470–3480. [Google Scholar] [CrossRef]
  81. Lee, E.; Fertig, E.J.; Jin, K.; Sukumar, S.; Pandey, N.B.; Popel, A.S. Breast cancer cells condition lymphatic endothelial cells within pre-metastatic niches to promote metastasis. Nat. Commun. 2014, 5, 4715. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  82. Hudis, C.A.; Gianni, L. Triple-negative breast cancer: An unmet medical need. Oncologist 2011, 16 (Suppl. 1), 1–11. [Google Scholar] [CrossRef] [Green Version]
  83. Wawrocki, S.; Druszczynska, M.; Kowalewicz-Kulbat, M.; Rudnicka, W. Interleukin 18 (IL-18) as a target for immune intervention. Acta Biochim. Pol. 2016, 63, 59–63. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  84. Fabbi, M.; Carbotti, G.; Ferrini, S. Context-dependent role of IL-18 in cancer biology and counter-regulation by IL-18BP. J. Leukoc. Biol. 2015, 97, 665–675. [Google Scholar] [CrossRef] [PubMed]
  85. Cheng, S.W.; Chen, P.C.; Lin, M.H.; Ger, T.R.; Chiu, H.W.; Lin, Y.F. GBP5 Repression Suppresses the Metastatic Potential and PD-L1 Expression in Triple-Negative Breast Cancer. Biomedicines 2021, 9, 371. [Google Scholar] [CrossRef]
  86. Singh, S.; Kumar, S.; Srivastava, R.K.; Nandi, A.; Thacker, G.; Murali, H.; Kim, S.; Baldeon, M.; Tobias, J.; Blanco, M.A.; et al. Loss of ELF5-FBXW7 stabilizes IFNGR1 to promote the growth and metastasis of triple-negative breast cancer through interferon-γ signalling. Nat. Cell Biol. 2020, 22, 591–602. [Google Scholar] [CrossRef]
  87. Ma, S.; Zhao, Y.; Lee, W.C.; Ong, L.T.; Lee, P.L.; Jiang, Z.; Oguz, G.; Niu, Z.; Liu, M.; Goh, J.Y.; et al. Hypoxia induces HIF1α-dependent epigenetic vulnerability in triple negative breast cancer to confer immune effector dysfunction and resistance to anti-PD-1 immunotherapy. Nat. Commun. 2022, 13, 4118. [Google Scholar] [CrossRef]
  88. Wherry, E.J. T cell exhaustion. Nat. Immunol. 2011, 12, 492–499. [Google Scholar] [CrossRef]
  89. Ngiow, S.F.; Young, A.; Jacquelot, N.; Yamazaki, T.; Enot, D.; Zitvogel, L.; Smyth, M.J. A Threshold Level of Intratumor CD8+ T-cell PD1 Expression Dictates Therapeutic Response to Anti-PD1. Cancer Res. 2015, 75, 3800–3811. [Google Scholar] [CrossRef] [Green Version]
  90. Blackburn, S.D.; Shin, H.; Freeman, G.J.; Wherry, E.J. Selective expansion of a subset of exhausted CD8 T cells by alphaPD-L1 blockade. Proc. Natl. Acad. Sci. USA 2008, 105, 15016–15021. [Google Scholar] [CrossRef]
  91. Thommen, D.S.; Schreiner, J.; Müller, P.; Herzig, P.; Roller, A.; Belousov, A.; Umana, P.; Pisa, P.; Klein, C.; Bacac, M.; et al. Progression of Lung Cancer Is Associated with Increased Dysfunction of T Cells Defined by Coexpression of Multiple Inhibitory Receptors. Cancer Immunol. Res. 2015, 3, 1344–1355. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  92. Koyama, S.; Akbay, E.A.; Li, Y.Y.; Herter-Sprie, G.S.; Buczkowski, K.A.; Richards, W.G.; Gandhi, L.; Redig, A.J.; Rodig, S.J.; Asahina, H.; et al. Adaptive resistance to therapeutic PD-1 blockade is associated with upregulation of alternative immune checkpoints. Nat. Commun. 2016, 7, 10501. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  93. Curdy, N.; Lanvin, O.; Laurent, C.; Fournié, J.J.; Franchini, D.M. Regulatory Mechanisms of Inhibitory Immune Checkpoint Receptors Expression. Trends Cell Biol. 2019, 29, 777–790. [Google Scholar] [CrossRef] [PubMed]
  94. Gao, X.; Zhu, Y.; Li, G.; Huang, H.; Zhang, G.; Wang, F.; Sun, J.; Yang, Q.; Zhang, X.; Lu, B. TIM-3 expression characterizes regulatory T cells in tumor tissues and is associated with lung cancer progression. PLoS ONE 2012, 7, e30676. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  95. Wolf, Y.; Anderson, A.C.; Kuchroo, V.K. TIM3 comes of age as an inhibitory receptor. Nat. Rev. Immunol. 2020, 20, 173–185. [Google Scholar] [CrossRef] [PubMed]
  96. de Mingo Pulido, Á.; Gardner, A.; Hiebler, S.; Soliman, H.; Rugo, H.S.; Krummel, M.F.; Coussens, L.M.; Ruffell, B. TIM-3 Regulates CD103(+) Dendritic Cell Function and Response to Chemotherapy in Breast Cancer. Cancer Cell 2018, 33, 60–74.e66. [Google Scholar] [CrossRef] [Green Version]
  97. Sabatos-Peyton, C.A.; Nevin, J.; Brock, A.; Venable, J.D.; Tan, D.J.; Kassam, N.; Xu, F.; Taraszka, J.; Wesemann, L.; Pertel, T.; et al. Blockade of Tim-3 binding to phosphatidylserine and CEACAM1 is a shared feature of anti-Tim-3 antibodies that have functional efficacy. Oncoimmunology 2018, 7, e1385690. [Google Scholar] [CrossRef] [Green Version]
  98. Saleh, R.; Toor, S.M.; Khalaf, S.; Elkord, E. Breast Cancer Cells and PD-1/PD-L1 Blockade Upregulate the Expression of PD-1, CTLA-4, TIM-3 and LAG-3 Immune Checkpoints in CD4(+) T Cells. Vaccines 2019, 7, 149. [Google Scholar] [CrossRef] [Green Version]
  99. Corti, C.; Nicolò, E.; Curigliano, G. Novel immune targets for the treatment of triple-negative breast cancer. Expert Opin. Ther. Targets 2021, 25, 815–834. [Google Scholar] [CrossRef]
  100. Workman, C.J.; Rice, D.S.; Dugger, K.J.; Kurschner, C.; Vignali, D.A. Phenotypic analysis of the murine CD4-related glycoprotein, CD223 (LAG-3). Eur. J. Immunol. 2002, 32, 2255–2263. [Google Scholar] [CrossRef]
  101. Woo, S.R.; Turnis, M.E.; Goldberg, M.V.; Bankoti, J.; Selby, M.; Nirschl, C.J.; Bettini, M.L.; Gravano, D.M.; Vogel, P.; Liu, C.L.; et al. Immune inhibitory molecules LAG-3 and PD-1 synergistically regulate T-cell function to promote tumoral immune escape. Cancer Res. 2012, 72, 917–927. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  102. Stovgaard, E.S.; Kümler, I.; List-Jensen, K.; Roslind, A.; Christensen, I.J.; Høgdall, E.; Nielsen, D.; Balslev, E. Prognostic and Clinicopathologic Associations of LAG-3 Expression in Triple-negative Breast Cancer. Appl. Immunohistochem. Mol. Morphol. AIMM 2022, 30, 62–71. [Google Scholar] [CrossRef] [PubMed]
  103. Heimes, A.S.; Almstedt, K.; Krajnak, S.; Runkel, A.; Droste, A.; Schwab, R.; Stewen, K.; Lebrecht, A.; Battista, M.J.; Brenner, W.; et al. Prognostic Impact of LAG-3 mRNA Expression in Early Breast Cancer. Biomedicines 2022, 10, 2656. [Google Scholar] [CrossRef] [PubMed]
  104. Schöffski, P.; Tan, D.S.W.; Martín, M.; Ochoa-de-Olza, M.; Sarantopoulos, J.; Carvajal, R.D.; Kyi, C.; Esaki, T.; Prawira, A.; Akerley, W.; et al. Phase I/II study of the LAG-3 inhibitor ieramilimab (LAG525) ± anti-PD-1 spartalizumab (PDR001) in patients with advanced malignancies. J. Immunother. Cancer 2022, 10, e003776. [Google Scholar] [CrossRef] [PubMed]
  105. Stamm, H.; Oliveira-Ferrer, L.; Grossjohann, E.M.; Muschhammer, J.; Thaden, V.; Brauneck, F.; Kischel, R.; Müller, V.; Bokemeyer, C.; Fiedler, W.; et al. Targeting the TIGIT-PVR immune checkpoint axis as novel therapeutic option in breast cancer. Oncoimmunology 2019, 8, e1674605. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  106. Yu, X.; Harden, K.; Gonzalez, L.C.; Francesco, M.; Chiang, E.; Irving, B.; Tom, I.; Ivelja, S.; Refino, C.J.; Clark, H.; et al. The surface protein TIGIT suppresses T cell activation by promoting the generation of mature immunoregulatory dendritic cells. Nat. Immunol. 2009, 10, 48–57. [Google Scholar] [CrossRef] [PubMed]
  107. Stanietsky, N.; Simic, H.; Arapovic, J.; Toporik, A.; Levy, O.; Novik, A.; Levine, Z.; Beiman, M.; Dassa, L.; Achdout, H.; et al. The interaction of TIGIT with PVR and PVRL2 inhibits human NK cell cytotoxicity. Proc. Natl. Acad. Sci. USA 2009, 106, 17858–17863. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  108. Pauken, K.E.; Wherry, E.J. TIGIT and CD226: Tipping the balance between costimulatory and coinhibitory molecules to augment the cancer immunotherapy toolkit. Cancer Cell 2014, 26, 785–787. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  109. Dougall, W.C.; Kurtulus, S.; Smyth, M.J.; Anderson, A.C. TIGIT and CD96: New checkpoint receptor targets for cancer immunotherapy. Immunol. Rev. 2017, 276, 112–120. [Google Scholar] [CrossRef]
  110. Johnston, R.J.; Comps-Agrar, L.; Hackney, J.; Yu, X.; Huseni, M.; Yang, Y.; Park, S.; Javinal, V.; Chiu, H.; Irving, B.; et al. The immunoreceptor TIGIT regulates antitumor and antiviral CD8(+) T cell effector function. Cancer Cell 2014, 26, 923–937. [Google Scholar] [CrossRef]
  111. Yang, L.; Li, A.; Lei, Q.; Zhang, Y. Tumor-intrinsic signaling pathways: Key roles in the regulation of the immunosuppressive tumor microenvironment. J. Hematol. Oncol. 2019, 12, 125. [Google Scholar] [CrossRef] [PubMed]
  112. Liu, C.; Peng, W.; Xu, C.; Lou, Y.; Zhang, M.; Wargo, J.A.; Chen, J.Q.; Li, H.S.; Watowich, S.S.; Yang, Y.; et al. BRAF inhibition increases tumor infiltration by T cells and enhances the antitumor activity of adoptive immunotherapy in mice. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2013, 19, 393–403. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  113. Loi, S.; Dushyanthen, S.; Beavis, P.A.; Salgado, R.; Denkert, C.; Savas, P.; Combs, S.; Rimm, D.L.; Giltnane, J.M.; Estrada, M.V.; et al. RAS/MAPK Activation Is Associated with Reduced Tumor-Infiltrating Lymphocytes in Triple-Negative Breast Cancer: Therapeutic Cooperation Between MEK and PD-1/PD-L1 Immune Checkpoint Inhibitors. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2016, 22, 1499–1509. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  114. Barroso-Sousa, R.; Keenan, T.E.; Pernas, S.; Exman, P.; Jain, E.; Garrido-Castro, A.C.; Hughes, M.; Bychkovsky, B.; Umeton, R.; Files, J.L.; et al. Tumor Mutational Burden and PTEN Alterations as Molecular Correlates of Response to PD-1/L1 Blockade in Metastatic Triple-Negative Breast Cancer. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2020, 26, 2565–2572. [Google Scholar] [CrossRef] [PubMed]
  115. Atefi, M.; Avramis, E.; Lassen, A.; Wong, D.J.; Robert, L.; Foulad, D.; Cerniglia, M.; Titz, B.; Chodon, T.; Graeber, T.G.; et al. Effects of MAPK and PI3K pathways on PD-L1 expression in melanoma. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2014, 20, 3446–3457. [Google Scholar] [CrossRef] [Green Version]
  116. Keniry, M.; Parsons, R. The role of PTEN signaling perturbations in cancer and in targeted therapy. Oncogene 2008, 27, 5477–5485. [Google Scholar] [CrossRef] [Green Version]
  117. Peng, W.; Chen, J.Q.; Liu, C.; Malu, S.; Creasy, C.; Tetzlaff, M.T.; Xu, C.; McKenzie, J.A.; Zhang, C.; Liang, X.; et al. Loss of PTEN Promotes Resistance to T Cell-Mediated Immunotherapy. Cancer Discov. 2016, 6, 202–216. [Google Scholar] [CrossRef] [Green Version]
  118. Mittendorf, E.A.; Philips, A.V.; Meric-Bernstam, F.; Qiao, N.; Wu, Y.; Harrington, S.; Su, X.; Wang, Y.; Gonzalez-Angulo, A.M.; Akcakanat, A.; et al. PD-L1 expression in triple-negative breast cancer. Cancer Immunol. Res. 2014, 2, 361–370. [Google Scholar] [CrossRef] [Green Version]
  119. Spranger, S.; Bao, R.; Gajewski, T.F. Melanoma-intrinsic β-catenin signalling prevents anti-tumour immunity. Nature 2015, 523, 231–235. [Google Scholar] [CrossRef]
  120. Castagnoli, L.; Cancila, V.; Cordoba-Romero, S.L.; Faraci, S.; Talarico, G.; Belmonte, B.; Iorio, M.V.; Milani, M.; Volpari, T.; Chiodoni, C.; et al. WNT signaling modulates PD-L1 expression in the stem cell compartment of triple-negative breast cancer. Oncogene 2019, 38, 4047–4060. [Google Scholar] [CrossRef]
  121. Gibney, G.T.; Weiner, L.M.; Atkins, M.B. Predictive biomarkers for checkpoint inhibitor-based immunotherapy. Lancet Oncol. 2016, 17, e542–e551. [Google Scholar] [CrossRef] [Green Version]
  122. Patel, S.P.; Kurzrock, R. PD-L1 Expression as a Predictive Biomarker in Cancer Immunotherapy. Mol. Cancer Ther. 2015, 14, 847–856. [Google Scholar] [CrossRef] [Green Version]
  123. Thompson, R.H.; Kuntz, S.M.; Leibovich, B.C.; Dong, H.; Lohse, C.M.; Webster, W.S.; Sengupta, S.; Frank, I.; Parker, A.S.; Zincke, H.; et al. Tumor B7-H1 is associated with poor prognosis in renal cell carcinoma patients with long-term follow-up. Cancer Res. 2006, 66, 3381–3385. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  124. Hino, R.; Kabashima, K.; Kato, Y.; Yagi, H.; Nakamura, M.; Honjo, T.; Okazaki, T.; Tokura, Y. Tumor cell expression of programmed cell death-1 ligand 1 is a prognostic factor for malignant melanoma. Cancer 2010, 116, 1757–1766. [Google Scholar] [CrossRef] [PubMed]
  125. Lin, H.; Wei, S.; Hurt, E.M.; Green, M.D.; Zhao, L.; Vatan, L.; Szeliga, W.; Herbst, R.; Harms, P.W.; Fecher, L.A.; et al. Host expression of PD-L1 determines efficacy of PD-L1 pathway blockade-mediated tumor regression. J. Clin. Investig. 2018, 128, 805–815. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  126. Rugo, H.S.; Loi, S.; Adams, S.; Schmid, P.; Schneeweiss, A.; Barrios, C.H.; Iwata, H.; Diéras, V.; Winer, E.P.; Kockx, M.M.; et al. PD-L1 Immunohistochemistry Assay Comparison in Atezolizumab Plus nab-Paclitaxel-Treated Advanced Triple-Negative Breast Cancer. J. Natl. Cancer Inst. 2021, 113, 1733–1743. [Google Scholar] [CrossRef]
  127. Büttner, R.; Gosney, J.R.; Skov, B.G.; Adam, J.; Motoi, N.; Bloom, K.J.; Dietel, M.; Longshore, J.W.; López-Ríos, F.; Penault-Llorca, F.; et al. Programmed Death-Ligand 1 Immunohistochemistry Testing: A Review of Analytical Assays and Clinical Implementation in Non-Small-Cell Lung Cancer. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 2017, 35, 3867–3876. [Google Scholar] [CrossRef]
  128. Chae, Y.K.; Pan, A.; Davis, A.A.; Raparia, K.; Mohindra, N.A.; Matsangou, M.; Giles, F.J. Biomarkers for PD-1/PD-L1 Blockade Therapy in Non-Small-cell Lung Cancer: Is PD-L1 Expression a Good Marker for Patient Selection? Clin. Lung Cancer 2016, 17, 350–361. [Google Scholar] [CrossRef]
  129. Zouein, J.; Kesrouani, C.; Kourie, H.R. PD-L1 expression as a predictive biomarker for immune checkpoint inhibitors: Between a dream and a nightmare. Immunotherapy 2021, 13, 1053–1065. [Google Scholar] [CrossRef]
  130. Arora, S.; Velichinskii, R.; Lesh, R.W.; Ali, U.; Kubiak, M.; Bansal, P.; Borghaei, H.; Edelman, M.J.; Boumber, Y. Existing and Emerging Biomarkers for Immune Checkpoint Immunotherapy in Solid Tumors. Adv. Ther. 2019, 36, 2638–2678. [Google Scholar] [CrossRef]
  131. Hamada, T.; Soong, T.R.; Masugi, Y.; Kosumi, K.; Nowak, J.A.; da Silva, A.; Mu, X.J.; Twombly, T.S.; Koh, H.; Yang, J.; et al. TIME (Tumor Immunity in the MicroEnvironment) classification based on tumor CD274 (PD-L1) expression status and tumor-infiltrating lymphocytes in colorectal carcinomas. Oncoimmunology 2018, 7, e1442999. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  132. Denkert, C.; von Minckwitz, G.; Darb-Esfahani, S.; Lederer, B.; Heppner, B.I.; Weber, K.E.; Budczies, J.; Huober, J.; Klauschen, F.; Furlanetto, J.; et al. Tumour-infiltrating lymphocytes and prognosis in different subtypes of breast cancer: A pooled analysis of 3771 patients treated with neoadjuvant therapy. Lancet Oncol. 2018, 19, 40–50. [Google Scholar] [CrossRef] [PubMed]
  133. Ibrahim, E.M.; Al-Foheidi, M.E.; Al-Mansour, M.M.; Kazkaz, G.A. The prognostic value of tumor-infiltrating lymphocytes in triple-negative breast cancer: A meta-analysis. Breast Cancer Res. Treat. 2014, 148, 467–476. [Google Scholar] [CrossRef] [PubMed]
  134. Emens, L.A.; Molinero, L.; Loi, S.; Rugo, H.S.; Schneeweiss, A.; Diéras, V.; Iwata, H.; Barrios, C.H.; Nechaeva, M.; Nguyen-Duc, A.; et al. Atezolizumab and nab-Paclitaxel in Advanced Triple-Negative Breast Cancer: Biomarker Evaluation of the IMpassion130 Study. J. Natl. Cancer Inst. 2021, 113, 1005–1016. [Google Scholar] [CrossRef]
  135. Schmid, P.; Salgado, R.; Park, Y.H.; Muñoz-Couselo, E.; Kim, S.B.; Sohn, J.; Im, S.A.; Foukakis, T.; Kuemmel, S.; Dent, R.; et al. Pembrolizumab plus chemotherapy as neoadjuvant treatment of high-risk, early-stage triple-negative breast cancer: Results from the phase 1b open-label, multicohort KEYNOTE-173 study. Ann. Oncol. Off. J. Eur. Soc. Med. Oncol. 2020, 31, 569–581. [Google Scholar] [CrossRef]
  136. Yarchoan, M.; Albacker, L.A.; Hopkins, A.C.; Montesion, M.; Murugesan, K.; Vithayathil, T.T.; Zaidi, N.; Azad, N.S.; Laheru, D.A.; Frampton, G.M.; et al. PD-L1 expression and tumor mutational burden are independent biomarkers in most cancers. JCI Insight 2019, 4, e126908. [Google Scholar] [CrossRef] [Green Version]
  137. Goodman, A.M.; Kato, S.; Bazhenova, L.; Patel, S.P.; Frampton, G.M.; Miller, V.; Stephens, P.J.; Daniels, G.A.; Kurzrock, R. Tumor Mutational Burden as an Independent Predictor of Response to Immunotherapy in Diverse Cancers. Mol. Cancer Ther. 2017, 16, 2598–2608. [Google Scholar] [CrossRef] [Green Version]
  138. Hellmann, M.D.; Ciuleanu, T.E.; Pluzanski, A.; Lee, J.S.; Otterson, G.A.; Audigier-Valette, C.; Minenza, E.; Linardou, H.; Burgers, S.; Salman, P.; et al. Nivolumab plus Ipilimumab in Lung Cancer with a High Tumor Mutational Burden. N. Engl. J. Med. 2018, 378, 2093–2104. [Google Scholar] [CrossRef]
  139. Van Allen, E.M.; Miao, D.; Schilling, B.; Shukla, S.A.; Blank, C.; Zimmer, L.; Sucker, A.; Hillen, U.; Foppen, M.H.G.; Goldinger, S.M.; et al. Genomic correlates of response to CTLA-4 blockade in metastatic melanoma. Science 2015, 350, 207–211. [Google Scholar] [CrossRef] [Green Version]
  140. Voutsadakis, I.A. High Tumor Mutation Burden and Other Immunotherapy Response Predictors in Breast Cancers: Associations and Therapeutic Opportunities. Target. Oncol. 2020, 15, 127–138. [Google Scholar] [CrossRef]
  141. Subbiah, V.; Solit, D.B.; Chan, T.A.; Kurzrock, R. The FDA approval of pembrolizumab for adult and pediatric patients with tumor mutational burden (TMB) ≥10: A decision centered on empowering patients and their physicians. Ann. Oncol. Off. J. Eur. Soc. Med. Oncol. 2020, 31, 1115–1118. [Google Scholar] [CrossRef] [PubMed]
  142. Lin, A.; Zhang, J.; Luo, P. Crosstalk Between the MSI Status and Tumor Microenvironment in Colorectal Cancer. Front. Immunol. 2020, 11, 2039. [Google Scholar] [CrossRef] [PubMed]
  143. Pellat, A.; Netter, J.; Perkins, G.; Cohen, R.; Coulet, F.; Parc, Y.; Svrcek, M.; Duval, A.; André, T. Lynch syndrome: What is new? Bull. Du Cancer 2019, 106, 647–655. [Google Scholar] [CrossRef] [PubMed]
  144. Baretti, M.; Le, D.T. DNA mismatch repair in cancer. Pharmacol. Ther. 2018, 189, 45–62. [Google Scholar] [CrossRef]
  145. Zhao, P.; Li, L.; Jiang, X.; Li, Q. Mismatch repair deficiency/microsatellite instability-high as a predictor for anti-PD-1/PD-L1 immunotherapy efficacy. J. Hematol. Oncol. 2019, 12, 54. [Google Scholar] [CrossRef]
  146. Horimoto, Y.; Thinzar Hlaing, M.; Saeki, H.; Kitano, S.; Nakai, K.; Sasaki, R.; Kurisaki-Arakawa, A.; Arakawa, A.; Otsuji, N.; Matsuoka, S.; et al. Microsatellite instability and mismatch repair protein expressions in lymphocyte-predominant breast cancer. Cancer Sci. 2020, 111, 2647–2654. [Google Scholar] [CrossRef]
  147. Xu, Y.; Fu, Y.; Zhu, B.; Wang, J.; Zhang, B. Predictive Biomarkers of Immune Checkpoint Inhibitors-Related Toxicities. Front. Immunol. 2020, 11, 2023. [Google Scholar] [CrossRef]
  148. Li, Y.; Wang, J.; Wu, L.; Li, X.; Zhang, X.; Zhang, G.; Xu, S.; Sun, S.; Jiao, S. Diversity of Dominant Peripheral T Cell Receptor Clone and Soluble Immune Checkpoint Proteins Associated With Clinical Outcomes Following Immune Checkpoint Inhibitor Treatment in Advanced Cancers. Front. Immunol. 2021, 12, 649343. [Google Scholar] [CrossRef]
  149. Kurata, K.; Kubo, M.; Kai, M.; Mori, H.; Kawaji, H.; Kaneshiro, K.; Yamada, M.; Nishimura, R.; Osako, T.; Arima, N.; et al. Microsatellite instability in Japanese female patients with triple-negative breast cancer. Breast Cancer 2020, 27, 490–498. [Google Scholar] [CrossRef] [Green Version]
  150. Casey, S.C.; Tong, L.; Li, Y.; Do, R.; Walz, S.; Fitzgerald, K.N.; Gouw, A.M.; Baylot, V.; Gütgemann, I.; Eilers, M.; et al. MYC regulates the antitumor immune response through CD47 and PD-L1. Science 2016, 352, 227–231. [Google Scholar] [CrossRef]
  151. Zimmerli, D.; Brambillasca, C.S.; Talens, F.; Bhin, J.; Linstra, R.; Romanens, L.; Bhattacharya, A.; Joosten, S.E.P.; Da Silva, A.M.; Padrao, N.; et al. MYC promotes immune-suppression in triple-negative breast cancer via inhibition of interferon signaling. Nat. Commun. 2022, 13, 6579. [Google Scholar] [CrossRef] [PubMed]
  152. Xiao, Y.; Ma, D.; Zhao, S.; Suo, C.; Shi, J.; Xue, M.Z.; Ruan, M.; Wang, H.; Zhao, J.; Li, Q.; et al. Multi-Omics Profiling Reveals Distinct Microenvironment Characterization and Suggests Immune Escape Mechanisms of Triple-Negative Breast Cancer. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2019, 25, 5002–5014. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  153. Maeda, T.; Hiraki, M.; Jin, C.; Rajabi, H.; Tagde, A.; Alam, M.; Bouillez, A.; Hu, X.; Suzuki, Y.; Miyo, M.; et al. MUC1-C Induces PD-L1 and Immune Evasion in Triple-Negative Breast Cancer. Cancer Res. 2018, 78, 205–215. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  154. Sun, S.; Zhou, W.; Li, X.; Peng, F.; Yan, M.; Zhan, Y.; An, F.; Li, X.; Liu, Y.; Liu, Q.; et al. Nuclear Aurora kinase A triggers programmed death-ligand 1-mediated immune suppression by activating MYC transcription in triple-negative breast cancer. Cancer Commun. 2021, 41, 851–866. [Google Scholar] [CrossRef] [PubMed]
  155. Hanahan, D.; Weinberg, R.A. Hallmarks of cancer: The next generation. Cell 2011, 144, 646–674. [Google Scholar] [CrossRef] [Green Version]
  156. Wang, J.; Zhang, R.; Lin, Z.; Zhang, S.; Chen, Y.; Tang, J.; Hong, J.; Zhou, X.; Zong, Y.; Xu, Y.; et al. CDK7 inhibitor THZ1 enhances antiPD-1 therapy efficacy via the p38α/MYC/PD-L1 signaling in non-small cell lung cancer. J. Hematol. Oncol. 2020, 13, 99. [Google Scholar] [CrossRef] [PubMed]
  157. Cheng, J.; Ding, X.; Xu, S.; Zhu, B.; Jia, Q. Gene expression profiling identified TP53(Mut)PIK3CA(Wild) as a potential biomarker for patients with triple-negative breast cancer treated with immune checkpoint inhibitors. Oncol. Lett. 2020, 19, 2817–2824. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  158. Hu, Q.; Ye, Y.; Chan, L.C.; Li, Y.; Liang, K.; Lin, A.; Egranov, S.D.; Zhang, Y.; Xia, W.; Gong, J.; et al. Oncogenic lncRNA downregulates cancer cell antigen presentation and intrinsic tumor suppression. Nat. Immunol. 2019, 20, 835–851. [Google Scholar] [CrossRef]
  159. Sasaki, R.; Horimoto, Y.; Yanai, Y.; Kurisaki-Arakawa, A.; Arakawa, A.; Nakai, K.; Saito, M.; Saito, T. Molecular Characteristics of Lymphocyte-predominant Triple-negative Breast Cancer. Anticancer Res. 2021, 41, 2133–2140. [Google Scholar] [CrossRef]
  160. Li, Z.; Li, Y.; Wang, X.; Yang, Q. PPP2R2B downregulation is associated with immune evasion and predicts poor clinical outcomes in triple-negative breast cancer. Cancer Cell Int. 2021, 21, 13. [Google Scholar] [CrossRef]
  161. Bareche, Y.; Buisseret, L.; Gruosso, T.; Girard, E.; Venet, D.; Dupont, F.; Desmedt, C.; Larsimont, D.; Park, M.; Rothé, F.; et al. Unraveling Triple-Negative Breast Cancer Tumor Microenvironment Heterogeneity: Towards an Optimized Treatment Approach. J. Natl. Cancer Inst. 2020, 112, 708–719. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  162. Baldominos, P.; Barbera-Mourelle, A.; Barreiro, O.; Huang, Y.; Wight, A.; Cho, J.W.; Zhao, X.; Estivill, G.; Adam, I.; Sanchez, X.; et al. Quiescent cancer cells resist T cell attack by forming an immunosuppressive niche. Cell 2022, 185, 1694–1708.e1619. [Google Scholar] [CrossRef] [PubMed]
  163. Li, M.; Xu, J.; Jiang, C.; Zhang, J.; Sun, T. Predictive and Prognostic Role of Peripheral Blood T-Cell Subsets in Triple-Negative Breast Cancer. Front. Oncol. 2022, 12, 842705. [Google Scholar] [CrossRef] [PubMed]
  164. Emens, L.A.; Middleton, G. The interplay of immunotherapy and chemotherapy: Harnessing potential synergies. Cancer Immunol. Res. 2015, 3, 436–443. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  165. Schmid, P.; Rugo, H.S.; Adams, S.; Schneeweiss, A.; Barrios, C.H.; Iwata, H.; Diéras, V.; Henschel, V.; Molinero, L.; Chui, S.Y.; et al. Atezolizumab plus nab-paclitaxel as first-line treatment for unresectable, locally advanced or metastatic triple-negative breast cancer (IMpassion130): Updated efficacy results from a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet Oncol. 2020, 21, 44–59. [Google Scholar] [CrossRef] [PubMed]
  166. Emens, L.A.; Adams, S.; Barrios, C.H.; Diéras, V.; Iwata, H.; Loi, S.; Rugo, H.S.; Schneeweiss, A.; Winer, E.P.; Patel, S.; et al. First-line atezolizumab plus nab-paclitaxel for unresectable, locally advanced, or metastatic triple-negative breast cancer: IMpassion130 final overall survival analysis. Ann. Oncol. Off. J. Eur. Soc. Med. Oncol. 2021, 32, 983–993. [Google Scholar] [CrossRef]
  167. Cortes, J.; Cescon, D.W.; Rugo, H.S.; Nowecki, Z.; Im, S.A.; Yusof, M.M.; Gallardo, C.; Lipatov, O.; Barrios, C.H.; Holgado, E.; et al. Pembrolizumab plus chemotherapy versus placebo plus chemotherapy for previously untreated locally recurrent inoperable or metastatic triple-negative breast cancer (KEYNOTE-355): A randomised, placebo-controlled, double-blind, phase 3 clinical trial. Lancet 2020, 396, 1817–1828. [Google Scholar] [CrossRef]
  168. Chang, J.Y.; Mehran, R.J.; Feng, L.; Verma, V.; Liao, Z.; Welsh, J.W.; Lin, S.H.; O’Reilly, M.S.; Jeter, M.D.; Balter, P.A.; et al. Stereotactic ablative radiotherapy for operable stage I non-small-cell lung cancer (revised STARS): Long-term results of a single-arm, prospective trial with prespecified comparison to surgery. Lancet Oncol. 2021, 22, 1448–1457. [Google Scholar] [CrossRef]
  169. Yeo, E.L.L.; Li, Y.Q.; Soo, K.C.; Wee, J.T.S.; Chua, M.L.K. Combinatorial strategies of radiotherapy and immunotherapy in nasopharyngeal carcinoma. Chin. Clin. Oncol. 2018, 7, 15. [Google Scholar] [CrossRef]
  170. Dewan, M.Z.; Galloway, A.E.; Kawashima, N.; Dewyngaert, J.K.; Babb, J.S.; Formenti, S.C.; Demaria, S. Fractionated but not single-dose radiotherapy induces an immune-mediated abscopal effect when combined with anti-CTLA-4 antibody. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2009, 15, 5379–5388. [Google Scholar] [CrossRef]
  171. Demaria, S.; Kawashima, N.; Yang, A.M.; Devitt, M.L.; Babb, J.S.; Allison, J.P.; Formenti, S.C. Immune-mediated inhibition of metastases after treatment with local radiation and CTLA-4 blockade in a mouse model of breast cancer. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2005, 11, 728–734. [Google Scholar] [CrossRef]
  172. Song, H.N.; Jin, H.; Kim, J.H.; Ha, I.B.; Kang, K.M.; Choi, H.S.; Jeong, H.J.; Kim, M.Y.; Kim, H.J.; Jeong, B.K. Abscopal Effect of Radiotherapy Enhanced with Immune Checkpoint Inhibitors of Triple Negative Breast Cancer in 4T1 Mammary Carcinoma Model. Int. J. Mol. Sci. 2021, 22, 10476. [Google Scholar] [CrossRef] [PubMed]
  173. Voorwerk, L.; Slagter, M.; Horlings, H.M.; Sikorska, K.; van de Vijver, K.K.; de Maaker, M.; Nederlof, I.; Kluin, R.J.C.; Warren, S.; Ong, S.; et al. Immune induction strategies in metastatic triple-negative breast cancer to enhance the sensitivity to PD-1 blockade: The TONIC trial. Nat. Med. 2019, 25, 920–928. [Google Scholar] [CrossRef] [PubMed]
  174. Ho, A.Y.; Barker, C.A.; Arnold, B.B.; Powell, S.N.; Hu, Z.I.; Gucalp, A.; Lebron-Zapata, L.; Wen, H.Y.; Kallman, C.; D’Agnolo, A.; et al. A phase 2 clinical trial assessing the efficacy and safety of pembrolizumab and radiotherapy in patients with metastatic triple-negative breast cancer. Cancer 2020, 126, 850–860. [Google Scholar] [CrossRef] [PubMed]
  175. Leighl, N.B.; Redman, M.W.; Rizvi, N.; Hirsch, F.R.; Mack, P.C.; Schwartz, L.H.; Wade, J.L.; Irvin, W.J.; Reddy, S.C.; Crawford, J.; et al. Phase II study of durvalumab plus tremelimumab as therapy for patients with previously treated anti-PD-1/PD-L1 resistant stage IV squamous cell lung cancer (Lung-MAP substudy S1400F, NCT03373760). J. Immunother. Cancer 2021, 9, e002973. [Google Scholar] [CrossRef] [PubMed]
  176. Rupp, T.; Genest, L.; Babin, D.; Legrand, C.; Hunault, M.; Froget, G.; Castagné, V. Anti-CTLA-4 and anti-PD-1 immunotherapies repress tumor progression in preclinical breast and colon model with independent regulatory T cells response. Transl. Oncol. 2022, 20, 101405. [Google Scholar] [CrossRef]
  177. Joller, N.; Hafler, J.P.; Brynedal, B.; Kassam, N.; Spoerl, S.; Levin, S.D.; Sharpe, A.H.; Kuchroo, V.K. Cutting edge: TIGIT has T cell-intrinsic inhibitory functions. J. Immunol. 2011, 186, 1338–1342. [Google Scholar] [CrossRef] [Green Version]
  178. Sarhan, D.; Cichocki, F.; Zhang, B.; Yingst, A.; Spellman, S.R.; Cooley, S.; Verneris, M.R.; Blazar, B.R.; Miller, J.S. Adaptive NK Cells with Low TIGIT Expression Are Inherently Resistant to Myeloid-Derived Suppressor Cells. Cancer Res. 2016, 76, 5696–5706. [Google Scholar] [CrossRef] [Green Version]
  179. Kawashima, S.; Inozume, T.; Kawazu, M.; Ueno, T.; Nagasaki, J.; Tanji, E.; Honobe, A.; Ohnuma, T.; Kawamura, T.; Umeda, Y.; et al. TIGIT/CD155 axis mediates resistance to immunotherapy in patients with melanoma with the inflamed tumor microenvironment. J. Immunother. Cancer 2021, 9, e003134. [Google Scholar] [CrossRef]
  180. Zhang, C.; Wang, Y.; Xun, X.; Wang, S.; Xiang, X.; Hu, S.; Cheng, Q.; Guo, J.; Li, Z.; Zhu, J. TIGIT Can Exert Immunosuppressive Effects on CD8+ T Cells by the CD155/TIGIT Signaling Pathway for Hepatocellular Carcinoma In Vitro. J. Immunother. 2020, 43, 236–243. [Google Scholar] [CrossRef]
  181. Chauvin, J.M.; Zarour, H.M. TIGIT in cancer immunotherapy. J. Immunother. Cancer 2020, 8, e000957. [Google Scholar] [CrossRef] [PubMed]
  182. Yang, R.; Sun, L.; Li, C.F.; Wang, Y.H.; Yao, J.; Li, H.; Yan, M.; Chang, W.C.; Hsu, J.M.; Cha, J.H.; et al. Galectin-9 interacts with PD-1 and TIM-3 to regulate T cell death and is a target for cancer immunotherapy. Nat. Commun. 2021, 12, 832. [Google Scholar] [CrossRef] [PubMed]
  183. Kjeldsen, J.W.; Lorentzen, C.L.; Martinenaite, E.; Ellebaek, E.; Donia, M.; Holmstroem, R.B.; Klausen, T.W.; Madsen, C.O.; Ahmed, S.M.; Weis-Banke, S.E.; et al. A phase 1/2 trial of an immune-modulatory vaccine against IDO/PD-L1 in combination with nivolumab in metastatic melanoma. Nat. Med. 2021, 27, 2212–2223. [Google Scholar] [CrossRef]
  184. Hong, D.S.; Schoffski, P.; Calvo, A.; Sarantopoulos, J.; Olza, M.O.D.; Carvajal, R.D.; Prawira, A.; Kyi, C.; Esaki, T.; Akerley, W.L.; et al. Phase I/II study of LAG525 ± spartalizumab (PDR001) in patients (pts) with advanced malignancies. J. Clin. Oncol. 2018, 36, 3012. [Google Scholar] [CrossRef]
  185. Spahn, J.; Peng, J.; Lorenzana, E.; Kan, D.; Hunsaker, T.; Segal, E.; Mautino, M.; Brincks, E.; Pirzkall, A.; Kelley, S.; et al. Improved anti-tumor immunity and efficacy upon combination of the IDO1 inhibitor GDC-0919 with anti-PD-l1 blockade versus anti-PD-l1 alone in preclinical tumor models. J. Immunother. Cancer 2015, 3, P303. [Google Scholar] [CrossRef] [Green Version]
  186. Jung, K.H.; LoRusso, P.; Burris, H.; Gordon, M.; Bang, Y.J.; Hellmann, M.D.; Cervantes, A.; Ochoa de Olza, M.; Marabelle, A.; Hodi, F.S.; et al. Phase I Study of the Indoleamine 2,3-Dioxygenase 1 (IDO1) Inhibitor Navoximod (GDC-0919) Administered with PD-L1 Inhibitor (Atezolizumab) in Advanced Solid Tumors. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2019, 25, 3220–3228. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  187. Bryant, H.E.; Schultz, N.; Thomas, H.D.; Parker, K.M.; Flower, D.; Lopez, E.; Kyle, S.; Meuth, M.; Curtin, N.J.; Helleday, T. Specific killing of BRCA2-deficient tumours with inhibitors of poly(ADP-ribose) polymerase. Nature 2005, 434, 913–917. [Google Scholar] [CrossRef]
  188. Farmer, H.; McCabe, N.; Lord, C.J.; Tutt, A.N.; Johnson, D.A.; Richardson, T.B.; Santarosa, M.; Dillon, K.J.; Hickson, I.; Knights, C.; et al. Targeting the DNA repair defect in BRCA mutant cells as a therapeutic strategy. Nature 2005, 434, 917–921. [Google Scholar] [CrossRef]
  189. Amé, J.C.; Spenlehauer, C.; de Murcia, G. The PARP superfamily. BioEssays News Rev. Mol. Cell. Dev. Biol. 2004, 26, 882–893. [Google Scholar] [CrossRef]
  190. Zatreanu, D.; Robinson, H.M.R.; Alkhatib, O.; Boursier, M.; Finch, H.; Geo, L.; Grande, D.; Grinkevich, V.; Heald, R.A.; Langdon, S.; et al. Polθ inhibitors elicit BRCA-gene synthetic lethality and target PARP inhibitor resistance. Nat. Commun. 2021, 12, 3636. [Google Scholar] [CrossRef]
  191. Garufi, G.; Palazzo, A.; Paris, I.; Orlandi, A.; Cassano, A.; Tortora, G.; Scambia, G.; Bria, E.; Carbognin, L. Neoadjuvant therapy for triple-negative breast cancer: Potential predictive biomarkers of activity and efficacy of platinum chemotherapy, PARP- and immune-checkpoint-inhibitors. Expert Opin. Pharmacother. 2020, 21, 687–699. [Google Scholar] [CrossRef] [PubMed]
  192. Labrie, M.; Li, A.; Creason, A.; Betts, C.; Keck, J.; Johnson, B.; Sivagnanam, S.; Boniface, C.; Ma, H.; Blucher, A.; et al. Multiomics analysis of serial PARP inhibitor treated metastatic TNBC inform on rational combination therapies. npj Precis. Oncol. 2021, 5, 92. [Google Scholar] [CrossRef] [PubMed]
  193. Pantelidou, C.; Sonzogni, O.; De Oliveria Taveira, M.; Mehta, A.K.; Kothari, A.; Wang, D.; Visal, T.; Li, M.K.; Pinto, J.; Castrillon, J.A.; et al. PARP Inhibitor Efficacy Depends on CD8(+) T-cell Recruitment via Intratumoral STING Pathway Activation in BRCA-Deficient Models of Triple-Negative Breast Cancer. Cancer Discov. 2019, 9, 722–737. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  194. Domchek, S.M.; Postel-Vinay, S.; Im, S.A.; Park, Y.H.; Delord, J.P.; Italiano, A.; Alexandre, J.; You, B.; Bastian, S.; Krebs, M.G.; et al. Olaparib and durvalumab in patients with germline BRCA-mutated metastatic breast cancer (MEDIOLA): An open-label, multicentre, phase 1/2, basket study. Lancet Oncol. 2020, 21, 1155–1164. [Google Scholar] [CrossRef]
  195. Vinayak, S.; Tolaney, S.M.; Schwartzberg, L.; Mita, M.; McCann, G.; Tan, A.R.; Wahner-Hendrickson, A.E.; Forero, A.; Anders, C.; Wulf, G.M.; et al. Open-label Clinical Trial of Niraparib Combined With Pembrolizumab for Treatment of Advanced or Metastatic Triple-Negative Breast Cancer. JAMA Oncol. 2019, 5, 1132–1140. [Google Scholar] [CrossRef] [Green Version]
  196. Knudsen, E.S.; Witkiewicz, A.K. The Strange Case of CDK4/6 Inhibitors: Mechanisms, Resistance, and Combination Strategies. Trends Cancer 2017, 3, 39–55. [Google Scholar] [CrossRef] [Green Version]
  197. Patel, J.M.; Goss, A.; Garber, J.E.; Torous, V.; Richardson, E.T.; Haviland, M.J.; Hacker, M.R.; Freeman, G.J.; Nalven, T.; Alexander, B.; et al. Retinoblastoma protein expression and its predictors in triple-negative breast cancer. npj Breast Cancer 2020, 6, 19. [Google Scholar] [CrossRef]
  198. Zhang, J.; Bu, X.; Wang, H.; Zhu, Y.; Geng, Y.; Nihira, N.T.; Tan, Y.; Ci, Y.; Wu, F.; Dai, X.; et al. Cyclin D-CDK4 kinase destabilizes PD-L1 via cullin 3-SPOP to control cancer immune surveillance. Nature 2018, 553, 91–95. [Google Scholar] [CrossRef] [Green Version]
  199. Tolba, M.F.; Omar, H.A. Immunotherapy, an evolving approach for the management of triple negative breast cancer: Converting non-responders to responders. Crit. Rev. Oncol. Hematol. 2018, 122, 202–207. [Google Scholar] [CrossRef]
  200. Maennling, A.E.; Tur, M.K.; Niebert, M.; Klockenbring, T.; Zeppernick, F.; Gattenlöhner, S.; Meinhold-Heerlein, I.; Hussain, A.F. Molecular Targeting Therapy against EGFR Family in Breast Cancer: Progress and Future Potentials. Cancers 2019, 11, 1826. [Google Scholar] [CrossRef]
  201. Changavi, A.A.; Shashikala, A.; Ramji, A.S. Epidermal Growth Factor Receptor Expression in Triple Negative and Nontriple Negative Breast Carcinomas. J. Lab. Physicians 2015, 7, 79–83. [Google Scholar] [CrossRef] [PubMed]
  202. Nakai, K.; Hung, M.C.; Yamaguchi, H. A perspective on anti-EGFR therapies targeting triple-negative breast cancer. Am. J. Cancer Res. 2016, 6, 1609–1623. [Google Scholar] [PubMed]
  203. Park, H.S.; Jang, M.H.; Kim, E.J.; Kim, H.J.; Lee, H.J.; Kim, Y.J.; Kim, J.H.; Kang, E.; Kim, S.W.; Kim, I.A.; et al. High EGFR gene copy number predicts poor outcome in triple-negative breast cancer. Mod. Pathol. Off. J. U. S. Can. Acad. Pathol. Inc. 2014, 27, 1212–1222. [Google Scholar] [CrossRef] [Green Version]
  204. Gonzalez-Conchas, G.A.; Rodriguez-Romo, L.; Hernandez-Barajas, D.; Gonzalez-Guerrero, J.F.; Rodriguez-Fernandez, I.A.; Verdines-Perez, A.; Templeton, A.J.; Ocana, A.; Seruga, B.; Tannock, I.F.; et al. Epidermal growth factor receptor overexpression and outcomes in early breast cancer: A systematic review and a meta-analysis. Cancer Treat. Rev. 2018, 62, 1–8. [Google Scholar] [CrossRef]
  205. Liang, H.; Liu, X.; Wang, M. Immunotherapy combined with epidermal growth factor receptor-tyrosine kinase inhibitors in non-small-cell lung cancer treatment. OncoTargets Ther. 2018, 11, 6189–6196. [Google Scholar] [CrossRef] [Green Version]
  206. Li, C.W.; Lim, S.O.; Xia, W.; Lee, H.H.; Chan, L.C.; Kuo, C.W.; Khoo, K.H.; Chang, S.S.; Cha, J.H.; Kim, T.; et al. Glycosylation and stabilization of programmed death ligand-1 suppresses T-cell activity. Nat. Commun. 2016, 7, 12632. [Google Scholar] [CrossRef] [Green Version]
  207. Xia, L.; Zheng, Z.; Liu, J.Y.; Chen, Y.J.; Ding, J.; Hu, G.S.; Hu, Y.H.; Liu, S.; Luo, W.X.; Xia, N.S.; et al. Targeting Triple-Negative Breast Cancer with Combination Therapy of EGFR CAR T Cells and CDK7 Inhibition. Cancer Immunol. Res. 2021, 9, 707–722. [Google Scholar] [CrossRef]
  208. Liu, Y.; Zhou, Y.; Huang, K.H.; Li, Y.; Fang, X.; An, L.; Wang, F.; Chen, Q.; Zhang, Y.; Shi, A.; et al. EGFR-specific CAR-T cells trigger cell lysis in EGFR-positive TNBC. Aging 2019, 11, 11054–11072. [Google Scholar] [CrossRef]
  209. Kowanetz, M.; Ferrara, N. Vascular endothelial growth factor signaling pathways: Therapeutic perspective. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2006, 12, 5018–5022. [Google Scholar] [CrossRef] [Green Version]
  210. Voron, T.; Colussi, O.; Marcheteau, E.; Pernot, S.; Nizard, M.; Pointet, A.L.; Latreche, S.; Bergaya, S.; Benhamouda, N.; Tanchot, C.; et al. VEGF-A modulates expression of inhibitory checkpoints on CD8+ T cells in tumors. J. Exp. Med. 2015, 212, 139–148. [Google Scholar] [CrossRef]
  211. Yasuda, S.; Sho, M.; Yamato, I.; Yoshiji, H.; Wakatsuki, K.; Nishiwada, S.; Yagita, H.; Nakajima, Y. Simultaneous blockade of programmed death 1 and vascular endothelial growth factor receptor 2 (VEGFR2) induces synergistic anti-tumour effect in vivo. Clin. Exp. Immunol. 2013, 172, 500–506. [Google Scholar] [CrossRef] [PubMed]
  212. Lin, Y.; Zhang, H.; Liang, J.; Li, K.; Zhu, W.; Fu, L.; Wang, F.; Zheng, X.; Shi, H.; Wu, S.; et al. Identification and characterization of alphavirus M1 as a selective oncolytic virus targeting ZAP-defective human cancers. Proc. Natl. Acad. Sci. USA 2014, 111, E4504–E4512. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  213. Bourgeois-Daigneault, M.C.; Roy, D.G.; Aitken, A.S.; El Sayes, N.; Martin, N.T.; Varette, O.; Falls, T.; St-Germain, L.E.; Pelin, A.; Lichty, B.D.; et al. Neoadjuvant oncolytic virotherapy before surgery sensitizes triple-negative breast cancer to immune checkpoint therapy. Sci. Transl. Med. 2018, 10, eaao1641. [Google Scholar] [CrossRef] [Green Version]
  214. Martin, N.T.; Roy, D.G.; Workenhe, S.T.; van den Wollenberg, D.J.M.; Hoeben, R.C.; Mossman, K.L.; Bell, J.C.; Bourgeois-Daigneault, M.C. Pre-surgical neoadjuvant oncolytic virotherapy confers protection against rechallenge in a murine model of breast cancer. Sci. Rep. 2019, 9, 1865. [Google Scholar] [CrossRef] [Green Version]
  215. Xie, N.; Shen, G.; Gao, W.; Huang, Z.; Huang, C.; Fu, L. Neoantigens: Promising targets for cancer therapy. Signal Transduct Target Ther. 2022, 20, 62. [Google Scholar] [CrossRef]
  216. Al-Awadhi, A.; Lee Murray, J.; Ibrahim, N.K. Developing anti-HER2 vaccines: Breast cancer experience. Int. J. Cancer 2018, 143, 2126–2132. [Google Scholar] [CrossRef] [Green Version]
  217. Martinez-Cannon, B.A.; Castro-Sanchez, A.; Barragan-Carrillo, R.; de la Rosa Pacheco, S.; Platas, A.; Fonseca, A.; Vega, Y.; Bojorquez-Velazquez, K.; Bargallo-Rocha, J.E.; Mohar, A.; et al. Adherence to Adjuvant Tamoxifen in Mexican Young Women with Breast Cancer. Patient Prefer. Adherence 2021, 15, 1039–1049. [Google Scholar] [CrossRef]
  218. Barve, M.; Aaron, P.; Manning, L.; Bognar, E.; Wallraven, G.; Horvath, S.; Stanbery, L.; Nemunaitis, J. Pilot Study of Combination Gemogenovatucel-T (Vigil) and Durvalumab in Women With Relapsed BRCA-wt Triple-Negative Breast or Ovarian Cancer. Clin. Med. Insights Oncol. 2022, 16, 11795549221110501. [Google Scholar] [CrossRef]
  219. Labrijn, A.F.; Janmaat, M.L.; Reichert, J.M.; Parren, P. Bispecific antibodies: A mechanistic review of the pipeline. Nat. Rev. Drug Discov. 2019, 18, 585–608. [Google Scholar] [CrossRef]
  220. Tian, H.; Zhang, T.; Qin, S.; Huang, Z.; Zhou, L.; Shi, J.; Nice, E.C.; Xie, N.; Huang, C.; Shen, Z. Enhancing the therapeutic efficacy of nanoparticles for cancer treatment using versatile targeted strategies. J. Hematol. Oncol. 2022, 15, 132. [Google Scholar] [CrossRef]
  221. LaMotte-Mohs, R.; Shah, K.; Smith, D.; Gorlatov, S.; Ciccarone, V.; Tamura, J.; Li, H.; Rillema, J.; Licea, M.; He, L.; et al. Abstract 3217: MGD013, a bispecific PD-1 x LAG-3 Dual-Affinity Re-Targeting (DART®) protein with T-cell immunomodulatory activity for cancer treatment. Cancer Res. 2016, 76, 3217. [Google Scholar] [CrossRef] [Green Version]
  222. Catenacci, D.V.; Rosales, M.; Chung, H.C.; Yoon, H.H.; Shen, L.; Moehler, M.; Kang, Y.K. MAHOGANY: Margetuximab combination in HER2+ unresectable/metastatic gastric/gastroesophageal junction adenocarcinoma. Future Oncol. 2021, 17, 1155–1164. [Google Scholar] [CrossRef] [PubMed]
Figure 1. PD-1/PD-L1-mediated inhibition of T cell activation. The binding of PD-1 to PD-L1 recruits SHP-2, thereby weakening the TCR signaling pathway mediated by LCK and inhibiting the RAS-MEK-ERK and PI3K-Akt-mTOR pathways. In addition, PD-1 activation induces the expression of BTAF, which inhibits the expression of effectors for T cell activation. Collectively, the activation of T cells can be inhibited by PD-1/PD-L1-mediated inhibiting of these signaling pathways. Abbreviations: PD-1, programmed cell death protein 1; PD-L1, programmed cell death 1 ligand 1; TCR, T cell receptor; MHC, major histocompatibility complex; APC, antigen-presenting cell; ITIM, immunoreceptor tyrosine inhibitory motif; ITSM, immunoreceptor tyrosine-based switch motif; P, phosphorylation; LCK, lymphocyte-specific protein-tyrosine kinase; ZAP70, zeta chain of T cell receptor associated protein kinase 70; SHP-2, src homology-2 domain-containing protein tyrosine phosphatase; BATF, basic leucine zipper transcriptional factor ATF-like; RAS, rat sarcoma; MEK, mitogen-activated extracellular signal-regulated kinase; ERK, extracellular regulated protein kinase; NFAT, nuclear factor of activated T cell; CK2, casein kinase II; PTEN, phosphatase and tensin homolog; PI3K, phosphoinositide 3-kinase; AKT, protein kinase B; mTOR, mammalian target of rapamycin; NF-κB, nuclear factor kappa-B.
Figure 1. PD-1/PD-L1-mediated inhibition of T cell activation. The binding of PD-1 to PD-L1 recruits SHP-2, thereby weakening the TCR signaling pathway mediated by LCK and inhibiting the RAS-MEK-ERK and PI3K-Akt-mTOR pathways. In addition, PD-1 activation induces the expression of BTAF, which inhibits the expression of effectors for T cell activation. Collectively, the activation of T cells can be inhibited by PD-1/PD-L1-mediated inhibiting of these signaling pathways. Abbreviations: PD-1, programmed cell death protein 1; PD-L1, programmed cell death 1 ligand 1; TCR, T cell receptor; MHC, major histocompatibility complex; APC, antigen-presenting cell; ITIM, immunoreceptor tyrosine inhibitory motif; ITSM, immunoreceptor tyrosine-based switch motif; P, phosphorylation; LCK, lymphocyte-specific protein-tyrosine kinase; ZAP70, zeta chain of T cell receptor associated protein kinase 70; SHP-2, src homology-2 domain-containing protein tyrosine phosphatase; BATF, basic leucine zipper transcriptional factor ATF-like; RAS, rat sarcoma; MEK, mitogen-activated extracellular signal-regulated kinase; ERK, extracellular regulated protein kinase; NFAT, nuclear factor of activated T cell; CK2, casein kinase II; PTEN, phosphatase and tensin homolog; PI3K, phosphoinositide 3-kinase; AKT, protein kinase B; mTOR, mammalian target of rapamycin; NF-κB, nuclear factor kappa-B.
Cancers 15 00104 g001
Figure 2. Immunosuppressive tumor microenvironment in anti-PD-1/PD-L1 therapy. TNBC cells can directly inhibit the activity of effector T cells by upregulating PD-L1 and releasing TGF-β2 and IL-10. Additionally, immunosuppressive cells, including TAM, Tregs and MDSCs, are recruited to the tumor microenvironment, where they can inhibit the anti-tumor of T cells. TAM can also promote tumor cell proliferation by secreting EGF and PDGF, facilitates tumor invasion and metastasis by releasing pro-tumor cell metastasis factors such as MMPs, triggers immune escape of tumor cells by producing IL-10, PGE2, TGF-β and CSF-1, as well as contributes to tumor microvascular growth by expressing VEGF. Abbreviations: PD-1, Programmed cell death-1; PD-L1, Programmed cell death-ligand-1; CSF1, colony stimulating factor 1; CCL2, C-C motif ligand 2; CCL22, C-C motif ligand 22; TGF-β, transforming growth factor-β; IL-6, interleukin-6; IL-10, interleukin-10; IL-35, interleukin-35; NOS, nitric oxide synthase; EGF, endothelial growth factor; VEGF, vascular endothelial growth factor; PDGF, platelet derived growth factor; MMPs, matrix metallopeptidase; PGE2, Prostaglandin E2; MDSC, myeloid-derived suppressor cell; TAM, tumor-associated macrophage.
Figure 2. Immunosuppressive tumor microenvironment in anti-PD-1/PD-L1 therapy. TNBC cells can directly inhibit the activity of effector T cells by upregulating PD-L1 and releasing TGF-β2 and IL-10. Additionally, immunosuppressive cells, including TAM, Tregs and MDSCs, are recruited to the tumor microenvironment, where they can inhibit the anti-tumor of T cells. TAM can also promote tumor cell proliferation by secreting EGF and PDGF, facilitates tumor invasion and metastasis by releasing pro-tumor cell metastasis factors such as MMPs, triggers immune escape of tumor cells by producing IL-10, PGE2, TGF-β and CSF-1, as well as contributes to tumor microvascular growth by expressing VEGF. Abbreviations: PD-1, Programmed cell death-1; PD-L1, Programmed cell death-ligand-1; CSF1, colony stimulating factor 1; CCL2, C-C motif ligand 2; CCL22, C-C motif ligand 22; TGF-β, transforming growth factor-β; IL-6, interleukin-6; IL-10, interleukin-10; IL-35, interleukin-35; NOS, nitric oxide synthase; EGF, endothelial growth factor; VEGF, vascular endothelial growth factor; PDGF, platelet derived growth factor; MMPs, matrix metallopeptidase; PGE2, Prostaglandin E2; MDSC, myeloid-derived suppressor cell; TAM, tumor-associated macrophage.
Cancers 15 00104 g002
Figure 3. Disturbed IFN-γ signaling pathway results in resistance to anti-PD-1/PD-L1 therapy. IFN-γ secreted by T cells binds to IFNγR1/2 on the surface of TNBC cells, activating the JAK1/1-STAT1/2 pathway. The phosphorylated STAT1/2 translocates to the nucleus where it binds to GAS and ISRE, promoting the expression of MHC-II, PD-L1 and CXCL9/10. After receiving immunotherapy, tumor cells may downregulate or alter the IFN-γ signaling pathway, such as by reducing JAK1/2 activity to escape the anti-tumor effects of T cell-derived IFN-γ. Abbreviations: PD-L1, programmed cell death 1 ligand 1; TCR, T cell receptor; MHC-Ⅰ, major histocompatibility complex class Ⅰ; IFN-γ, interferon-γ; IFNγR 1/2, interferon-γ receptor 1/2; JAK 1/2, Janus kinase 1/2; STAT 1/2, signal transducer and activator of transcription 1/2; GAS, growth arrest-specific protein; ISRE, interferon-sensitive response element; CXCL9/10, C-X-C motif chemokine 9/10; TNBC, triple negative breast cancer.
Figure 3. Disturbed IFN-γ signaling pathway results in resistance to anti-PD-1/PD-L1 therapy. IFN-γ secreted by T cells binds to IFNγR1/2 on the surface of TNBC cells, activating the JAK1/1-STAT1/2 pathway. The phosphorylated STAT1/2 translocates to the nucleus where it binds to GAS and ISRE, promoting the expression of MHC-II, PD-L1 and CXCL9/10. After receiving immunotherapy, tumor cells may downregulate or alter the IFN-γ signaling pathway, such as by reducing JAK1/2 activity to escape the anti-tumor effects of T cell-derived IFN-γ. Abbreviations: PD-L1, programmed cell death 1 ligand 1; TCR, T cell receptor; MHC-Ⅰ, major histocompatibility complex class Ⅰ; IFN-γ, interferon-γ; IFNγR 1/2, interferon-γ receptor 1/2; JAK 1/2, Janus kinase 1/2; STAT 1/2, signal transducer and activator of transcription 1/2; GAS, growth arrest-specific protein; ISRE, interferon-sensitive response element; CXCL9/10, C-X-C motif chemokine 9/10; TNBC, triple negative breast cancer.
Cancers 15 00104 g003
Figure 4. T cell exhaustion contributes to therapeutic resistance of TNBC to PD-1/PD-L1 inhibitors. Continuous exposure of T cells to tumor antigens and suppressive cytokines (IL-10, TGF-β) leads to T cell exhaustion, which results in a poor response to immunotherapy and therapeutic resistance. The accumulated ROS, increased HIF-α and activated calcium-calcineurin-NFAT signaling pathway play a key role in T cell exhaustion, which contributes to therapeutic resistance. Abbreviations: PD-1, programmed cell death protein 1; PD-L1, programmed cell death 1 ligand 1; TCR, T cell receptor; MHC, major histocompatibility complex; APC, antigen-presenting cell; TNBC, triple negative breast cancer; TIM-3, T cell immunoglobulin domain and mucin domain-3; TGF-β, transforming growth factor-beta; IL-10, interleukin-10; IL-1, interleukin-1; IFN-γ, interferon-γ; TNF-α, tumor necrosis factor-α; ROS, reactive oxygen species; NFAT, nuclear factor of activated T cells; HIF-1α, hypoxia inducible factor-1α; TOX, thymocyte selection associated high mobility group box; BATF, basic leucine zipper transcriptional factor ATF-like; IFR-4, interferon regulatory factor 4.
Figure 4. T cell exhaustion contributes to therapeutic resistance of TNBC to PD-1/PD-L1 inhibitors. Continuous exposure of T cells to tumor antigens and suppressive cytokines (IL-10, TGF-β) leads to T cell exhaustion, which results in a poor response to immunotherapy and therapeutic resistance. The accumulated ROS, increased HIF-α and activated calcium-calcineurin-NFAT signaling pathway play a key role in T cell exhaustion, which contributes to therapeutic resistance. Abbreviations: PD-1, programmed cell death protein 1; PD-L1, programmed cell death 1 ligand 1; TCR, T cell receptor; MHC, major histocompatibility complex; APC, antigen-presenting cell; TNBC, triple negative breast cancer; TIM-3, T cell immunoglobulin domain and mucin domain-3; TGF-β, transforming growth factor-beta; IL-10, interleukin-10; IL-1, interleukin-1; IFN-γ, interferon-γ; TNF-α, tumor necrosis factor-α; ROS, reactive oxygen species; NFAT, nuclear factor of activated T cells; HIF-1α, hypoxia inducible factor-1α; TOX, thymocyte selection associated high mobility group box; BATF, basic leucine zipper transcriptional factor ATF-like; IFR-4, interferon regulatory factor 4.
Cancers 15 00104 g004
Figure 5. Inhibitory immune checkpoints for TNBC. TNBC cells express immune checkpoint ligands, which mediate resistance to PD-1/PD-L1 inhibitors by inhibiting T cell function. After the PD-1/PD-L1 signaling pathway is blocked by inhibitors, other immune checkpoints, such as CTLA-4, TIGIT, TIM-3 and LAG-3, are compensated upregulated. Abbreviations: PD-1, programmed cell death protein 1; PD-L1, programmed cell death 1 ligand 1; CTLA-4, cytotoxic T-lymphocyte-associated protein 4; TIGIT, T cell immunoglobulin and ITIM domain; TIM-3, T cell immunoglobulin domain and mucin domain-3; LAG-3, lymphocyte activation gene-3; TCR, T cell receptor; MHC-II, major histocompatibility complex class II; TNBC, triple negative breast cancer.
Figure 5. Inhibitory immune checkpoints for TNBC. TNBC cells express immune checkpoint ligands, which mediate resistance to PD-1/PD-L1 inhibitors by inhibiting T cell function. After the PD-1/PD-L1 signaling pathway is blocked by inhibitors, other immune checkpoints, such as CTLA-4, TIGIT, TIM-3 and LAG-3, are compensated upregulated. Abbreviations: PD-1, programmed cell death protein 1; PD-L1, programmed cell death 1 ligand 1; CTLA-4, cytotoxic T-lymphocyte-associated protein 4; TIGIT, T cell immunoglobulin and ITIM domain; TIM-3, T cell immunoglobulin domain and mucin domain-3; LAG-3, lymphocyte activation gene-3; TCR, T cell receptor; MHC-II, major histocompatibility complex class II; TNBC, triple negative breast cancer.
Cancers 15 00104 g005
Figure 6. Combination therapies with anti-PD-1/PD-L1 antibodies. Combination therapies: including PD-1/PD-L1 antibodies along with radiotherapy, chemotherapy, other immune checkpoint antibodies, targeted therapy, oncolytic viruses and neoantigen-based immunotherapy are being developed to treat cancer patients effectively. Abbreviations: PD-1, Programmed cell death-1; PD-L1, Programmed cell death-ligand-1; CTLA-4, Cytotoxic T Lymphocyte-Associated Antigen-4; TIGIT, T cell immunoglobulin and ITIM domains; ITIM, immunoreceptor tyrosine-based inhibitory motif; TIM-3, T cell immunoglobulin domain and mucin domain-3; IDO, indoleamine 2, 3 dioxygenase; Siglec-15, Sialic Acid Binding Ig Like Lectin-15; PPAP inhibitors, Poly ADP-ribosepolymerase inhibitor; EGFR-TKI, epidermal growth factor receptor-tyrosine kinase inhibitors; VEGF antibody, vascular endothelial growth factor antibody; CKD4/6 inhibitors, cyclin dependent kinase4/6 inhibitors.
Figure 6. Combination therapies with anti-PD-1/PD-L1 antibodies. Combination therapies: including PD-1/PD-L1 antibodies along with radiotherapy, chemotherapy, other immune checkpoint antibodies, targeted therapy, oncolytic viruses and neoantigen-based immunotherapy are being developed to treat cancer patients effectively. Abbreviations: PD-1, Programmed cell death-1; PD-L1, Programmed cell death-ligand-1; CTLA-4, Cytotoxic T Lymphocyte-Associated Antigen-4; TIGIT, T cell immunoglobulin and ITIM domains; ITIM, immunoreceptor tyrosine-based inhibitory motif; TIM-3, T cell immunoglobulin domain and mucin domain-3; IDO, indoleamine 2, 3 dioxygenase; Siglec-15, Sialic Acid Binding Ig Like Lectin-15; PPAP inhibitors, Poly ADP-ribosepolymerase inhibitor; EGFR-TKI, epidermal growth factor receptor-tyrosine kinase inhibitors; VEGF antibody, vascular endothelial growth factor antibody; CKD4/6 inhibitors, cyclin dependent kinase4/6 inhibitors.
Cancers 15 00104 g006
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Chen, X.; Feng, L.; Huang, Y.; Wu, Y.; Xie, N. Mechanisms and Strategies to Overcome PD-1/PD-L1 Blockade Resistance in Triple-Negative Breast Cancer. Cancers 2023, 15, 104. https://doi.org/10.3390/cancers15010104

AMA Style

Chen X, Feng L, Huang Y, Wu Y, Xie N. Mechanisms and Strategies to Overcome PD-1/PD-L1 Blockade Resistance in Triple-Negative Breast Cancer. Cancers. 2023; 15(1):104. https://doi.org/10.3390/cancers15010104

Chicago/Turabian Style

Chen, Xingyu, Lixiang Feng, Yujing Huang, Yi Wu, and Na Xie. 2023. "Mechanisms and Strategies to Overcome PD-1/PD-L1 Blockade Resistance in Triple-Negative Breast Cancer" Cancers 15, no. 1: 104. https://doi.org/10.3390/cancers15010104

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop