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Relevance of tumor-infiltrating lymphocytes in breast cancer

  • Sathana Dushyanthen1,
  • Paul A. Beavis1,
  • Peter Savas1,
  • Zhi Ling Teo1,
  • Chenhao Zhou1,
  • Mariam Mansour1,
  • Phillip K. Darcy1, 2 and
  • Sherene Loi1, 2, 3Email author
Contributed equally
BMC Medicine201513:202

https://doi.org/10.1186/s12916-015-0431-3

Received: 11 May 2015

Accepted: 22 July 2015

Published: 24 August 2015

Abstract

While breast cancer has not been considered a cancer amenable to immunotherapeutic approaches, recent studies have demonstrated evidence of significant immune cell infiltration via tumor-infiltrating lymphocytes in a subset of patient tumors. In this review we present the current evidence highlighting the clinical relevance and utility of tumor-infiltrating lymphocytes in breast cancer. Retrospective and prospective studies have shown that the presence of tumor-infiltrating lymphocytes is a prognostic marker for higher responses to neoadjuvant chemotherapy and better survival, particularly in triple negative and HER2-positive early breast cancer. Further work is required to determine the immune subsets important in this response and to discover ways of encouraging immune infiltrate in tumor-infiltrating lymphocytes-negative patients.

Keywords

Breast cancerHER2immunityimmunotherapyNACneoadjuvant chemotherapyTILsTNBCtriple negative breast cancertumor-infiltrating lymphocytes

Introduction

In cancer, neoplastic transformation alters the structure of tissues and induces immune responses leading to the elimination of developing tumors. However, incomplete elimination of transformed cells results in escape from immune control. This process is known as cancer immunoediting and is supported by a large body of experimental data and clinical evidence showing that the intact immune system can prevent and control cancer through the generation of effective tumor-specific immune responses [1, 2]. Immunoediting describes the process of malignant progression on the basis of tumor and immune cell interactions in three phases: (1) elimination, where cancerous cells are eliminated following immunosurveillance; (2) equilibrium, where transformed cells are held in control but are not eliminated by the immune system; and (3) escape, where tumor cell modifications shape disease progression [1, 2]. In general, a patient will present once the tumor has ‘evolved’ to escape immunosurveillance and, accordingly, a subset of patients with breast cancer present clear evidence of immune suppression and aggressive disease progression, potentially driven by mechanisms of tumor tolerance [3, 4]. In the elimination phase, the innate and adaptive immune system coordinate to detect and destroy cancer cells before clinical presentation. At this stage the balance is towards antitumor immunity stimulated by natural killer (NK) cells, NK-T cells, T cells, and increased pro-immune factors in the tumor microenvironment [2]. In equilibrium, there is a balance between antitumor and tumor-promoting factors, thus maintaining the tumor in a functionally dormant state [2]. Well-documented escape mechanisms of breast cancer cells include decreased immune recognition through reduced expression of major histocompatibility complex class I (MHC I) and/or co-stimulatory molecules and increased expression of immunosuppressive factors. This results in reduced clearance (lysis) via CD8+ cytotoxic T lymphocytes (CTLs) [3, 4]. The mechanisms underlying these processes have previously been reviewed in detail in several papers [1, 2, 510].

Several studies have indicated that in addition to T cells, macrophages, NK cells, and dendritic cells (DCs) also infiltrate tumor tissue in varying capacities [1, 2, 8, 10]. It is known that CD4+ T helper 1 (Th1) cells, CD8+ cytotoxic T cells, NK cells, M1 macrophages, and DCs are protective against tumor growth [11]. Conversely, CD4+ forkhead box P3 (FOXP3+), CD4+ Th2 cells, M2 macrophages, and myeloid-derived suppressor cells (MDSCs) promote tumor growth [11]. These subsets interact in numerous ways; some of these mechanisms of interaction are shown in Fig. 1. Accordingly, tumor cells are able to suppress tumor-infiltrating lymphocytes (TILs) through multiple mechanisms either through direct suppression of antitumor immune cells or recruitment and reactivation of immunosuppressive subsets. One such mechanism is the expression of PD-L1 on tumor cells, which interacts with PD-1+ CD8+ T cells and induces subsequent anergy/apoptosis, leading to inactivation or exhaustion of TILs in the tumor microenvironment. This process leads to diminishing host antitumor immune responses [12]. Checkpoint inhibitors such as CTLA-4 and PD-1 trigger inhibitory pathways which dampen T-cell activity when bound to their ligands (CD80/CD86 and PD-L1/PD-L2) [13]. Both PD-1 and CTLA-4 blockade have proven to be very effective in preclinical animal models of melanoma and some breast cancer models [1417]. Interestingly, an increasing number of studies are revealing positive outcomes in the clinical setting to checkpoint blockade of PD-1/PD-L1 and CTLA-4 [1820]. Other targets that are of great interest in the clinical setting are the emerging T cell Ig and mucin domain (TIM) superfamily and lymphocyte activation gene 3 (LAG-3), given that they have both been associated with the inhibition of lymphocyte activity as well as induction of lymphocyte anergy [11, 12]. Additionally, several other immunosuppressive factors and inhibitory metabolites, such as adenosine [2125], FOXP3+ regulatory T cells (Tregs) [26], indoleamine 2,3-dioxygenase (IDO) [2730], arginase [3133], and MDSCs [3436], have been implicated in cancer-mediated immunosuppression, where targeting of these pathways has been shown to enhance antitumor immunity in vivo.
Fig. 1

Interactions between the immune microenvironment and tumor cells in breast cancer. The antitumor immune response is dependent upon CD4+ (Th1) IFNγ production, which in turn mediates the expansion, differentiation, and activation of tumor-specific CD8+. CD8+ cytotoxic T cells induce cell lysis via recognition of specific TAAs such as MHC, FAS, and TRAILR on the surface of cancer cells/APCs. Similarly, CD4+ T cells are able to recognize MHC II on APCs. As a result of this complex formation (TCR-MHC/Peptide), high levels of granzymes, IFNγ, and perforin are released from CTLs, resulting in granule exocytosis and tumor cell death via apoptosis. NK and NKT cells with the help of APCs (DCs/M1) and CD4+Th1 are able to recognize and eliminate tumor cells. In the pro-tumor environment, CTLA-4, TIM-3, and PD-1 deliver inhibitory signals as a result of T-cell exhaustion/anergy caused by prolonged activation. CTLA-4 negatively regulates T-cell activation during the ‘priming’ phase of T-cell response. PD-1 expressed on T cells in the effector phase of T-cell response binds to its ligand PD-L1, expressed within the tumor microenvironment. This results in inhibition of T-cell activity (apoptosis). FOXP3+ Treg cells play a critical role during the selection of high-avidity CD8+ T cells, reducing their functionality. Tregs also have inhibitory action on APCs, CD8+ T cells, NKs, and CD4+ Th1 T cells. Both Tregs and tumor cells produce adenosine, which has inhibitory effects on T cells. Tumor cells can secrete cytokines and chemokines (e.g., TGF-β, CCL2) that recruit and stimulate suppressive cells such as Tregs, MDSCs, and M2 macrophages. M2 macrophages and MDSCs inhibit T-cell responses through nutrient sequestration via arginase, ROS, and NOS generation, as well as interference with trafficking into the tumor site. The upregulation of immunosuppressive enzymes such as IDO and arginase catabolizes essential nutrients required for effector cell activation. Furthermore, tumor cells downregulate MHC molecules, lose expression of antigenic molecules, and upregulate inhibitory molecules such as PD-L1, causing immune recognition to be inhibited and thus allowing immune escape and cancer progression. This figure was made exclusively for this manuscript. A2aR A2A adenosine receptor, ADP adenosine diphosphate, AMP adenosine monophosphate, APC antigen-presenting cell, ATP adenosine triphosphate, CCl-2 chemokine ligand-2, CTL cytotoxic T lymphocyte, CTLA-4 cytotoxic t lymphocyte-associated protein, DC dendritic cell, FAS fatty-acid synthase, GAL-9 galectin-9, IDO indolamine 2,3-dioxygenase, IFNγ interferon gamma, IL interleukin, M1/M1 TAM tumor-associated macrophage, MDSC myeloid-derived suppressor cell, MHC major histocompatibility complex, NK natural killer, NKT natural killer T cell, NOS nitric oxide synthase, PD-1 programmed death, ROS reactive oxygen species, TAA tumor-associated antigen, TCR T-cell receptor, TGF-β transforming growth factor beta, TNFα tumor necrosis factor alpha, TRAIL TNF-related apoptosis-inducing ligand, Treg T regulatory cell

Preclinical evidence for the role of the immune system in cancer and in response to chemotherapy and radiotherapy

Chemotherapy and radiotherapy are frontline management options for breast cancer and the underlying immunogenic component of these agents make them attractive candidates for neoadjuvant therapy. Preclinical studies of chemotherapy and radiotherapy have revealed the unexpected ability of the immune system to contribute to the success of treatment. There is an abundance of experimental and, more recently, clinical evidence [3741] showing that chemotherapies are more efficient if they successfully re-activate immune surveillance through the elimination of immunosuppressive cells or through the promotion of danger signals released by the death of tumor cells, hence triggering a long-term immune response against residual tumor cells [42, 43]. Several findings have delineated a sequential series of events driving immunogenic tumor cell death that results in the activation of innate and adaptive immune responses [44]. During immunogenic cell death, dying tumor cells release danger signals such as adenosine triphosphate (ATP) and high-mobility group protein B1 (HMGB1), which act to prime an antitumor immune response [45, 46]. In landmark studies by Zitvogel and colleagues, anthracycline therapy was less effective in mice deficient in P2X7 receptors, NLRP3, and caspase-1, while oxaliplatin was dependent on HMGB1-mediated activation of toll-like receptors (TLRs). The activation of antigen-presenting cells such as DCs by ATP (P2X7) or HMGB1 (TLR4) leads to enhanced production of IL-1β, and consequently activation of both innate and adaptive immune responses [23]. Interestingly, the observation of enhanced antitumor immunity following treatment extends to various chemotherapies, including gemcitabine [4749], cyclophosphamide [50, 51], paclitaxel [52], and doxorubicin [5355]. Induction of tumor cell death by chemotherapy (e.g., gemcitabine) also enhances tumor antigen cross-presentation [56]. Furthermore, certain chemotherapies have direct effects on immune cells themselves. For example, low dose cyclophosphamide selectively reduces the number of immunosuppressive Treg cells while sparing immune effector cells [51]. These findings are summarized in Table 1. Many preclinical studies have described immune-enhancing activity in response to chemotherapies [57]. However, it is evident that not all chemotherapies induce immunogenic cell death. As such, it is apparent that combinations with specific immune-inducing or immune-targeted inhibitors are necessary to promote tumor regression and immunogenic cell death in these cases. Thus, despite initial theories suggesting that breast cancer is not an immunogenic disease, recent studies have confirmed and consolidated understanding of the underlying immunological component in breast cancer, thus revealing promising targets and novel therapies for treatment of this disease.
Table 1

Effects of chemotherapy on tumor-infiltrating lymphocytes

Drug

Target

Immunological effects and model used

Reference

Gemcitabine

Nucleoside analogue, prevents DNA replication

Reduction in the number of MDSCs

[126]

HER2/neu model; breast cancer

[127, 128]

Mesothelioma and lung cancer models

[48]

Reduction in MDSCs and Tregs when given with cyclophosphamide; CT26 colon carcinoma

[49]

Reduction of Tregs in patients with pancreatic cancer

Cyclophosphamide

DNA alkylation, cross-links DNA

Induction of immunogenic cell death, IFN-I mediated activation of dendritic cells; EG7 thymoma, B16F10 melanoma

[129]

Selective depletion of Tregs in MMTV-neu mice (breast cancer)

[88]

Selective depletion of Tregs in colon carcinoma model

[42]

Selective depletion of Tregs in melanoma model

[130]

Reduction in MDSCs and Tregs when given with gemcitabine; CT26 colon carcinoma

[48]

Paclitaxel

Inhibition of mitosis through tubulin targeting

Reduction in MDSC frequency and suppressive activity

[131]

Reduction in Treg numbers and suppressive activity

[52, 132]

Anthracyclines

Multiple mechanisms

Induction of immunogenic cell death; thymoma model, CT26 colon carcinoma

[45]

Differentiation of CD11b+ LY6C+ APCs; MCA205 fibrosarcoma

[133]

Elimination of MDSCs; 4 T1 and EMT6 breast tumor cell lines

[134]

Oxaliplatin

Cross-links DNA

Induction of immunogenic cell death resulting in the activation of myeloid cells; thymoma/colon cancer model

[45, 135]

Cisplatin

Cross-links DNA

Induce the accumulation of CD11c+ inflammatory dendritic cells; lung/colon carcinoma models

[136]

Docetaxel

Inhibition of mitosis through tubulin targeting

Reduction in MDSC frequency and suppressive activity; B16 melanoma model

[116]

5-aza-2′-deoxycytidine

DNA methyltransferase inhibition

Increased antigen presentation by tumor cells; 4 T1 breast cancer model

[137]

Reduction in MDSCs and suppressive function; lung/prostrate carcinoma

[138]

APCs antigen-presenting cell, MDSC myeloid-derived suppressor cells, Tregs regulatory T cells

Observations on the prognostic value of TILs in breast cancer

The importance of the immune system in breast cancer is increasingly being recognized, owing to the observation by several groups that the presence of TILs is a prognostic indicator for higher rates of pathological complete responses (pCRs) to neoadjuvant chemotherapy (NAC) [37, 5860]. Notably, Denkert and colleagues [41] were able to first show in a large-scale analysis of 1058 patients’ biopsies that TIL+ tumors achieved a pCR rate of 40–42 % following NAC, whereas TIL tumors achieved a pCR of only 3–7 %. This distinction was based upon comparing lymphocyte predominant breast cancer (LPBC; defined as ≥60 % TILs in either the intratumoral or stromal compartment) to the rest of the population. Interestingly, this analysis revealed that TILs within either the stromal or intratumoral compartment was of value as a prognostic indicator. Subsequently, this has also been shown in another dataset of 580 triple negative breast cancer (TNBC) and HER2-positive breast cancers (59.9 % in LPBC vs 33.8 % in non-LPBC) [41] as well as in a meta-analysis of 996 patients where an immune gene module indicative of a Th1 response was prognostic of pCR in all cancer subtypes [61]. The protective role of a Th1 response was also reported by an independent group who found that the infiltration of T-bet+ lymphocytes correlated with a favorable prognosis [62]. TILs have been reported to predict pCR in a prospective study of HER2-negative breast cancers in patients treated with NAC, confirming the prognostic value of TILs in the response to chemotherapy [63].

From a clinical perspective, the observation suggests that higher levels of TILs are associated with higher responses to chemotherapy, seemingly independent of oestrogen receptor (ER), progesterone receptor (PR), and HER2. There is in fact no biologically appropriate TILs cut-point as all studies have shown that the TIL marker is prognostic on a continuous scale: each 1 % or decile increment is associated with a further increase in the rate of pCR. The biological reasons for this observation of chemosensitivity remain poorly understood. Perhaps pre-existing immune antitumor responses are better placed to be able to clear tumor cells after chemotherapy has depleted local immunosuppression or Treg cells. An increase in TILs in the breast cancer post-NAC is also associated with improved outcomes [64]. Notably, however, although TILs correlate with pCR to NAC in all breast cancer subtypes, the correlation between TILs at diagnosis and disease-free or overall survival was only significant in TNBC and HER2-positive breast cancers, although the reasons for this are not fully understood [39, 6466]. The studies indicating a positive relationship between TILs and responses to NAC are summarized in Table 2. TILs are important in the efficacy of trastuzumab [65, 67, 68] and, moreover, trastuzumab treatment results in the activation or recruitment of multiple immune cell lineages and increases the susceptibility of tumor cells to antibody dependent cytotoxicity (ADCC) [67, 69] (reviewed by [70]). A study looking at TILs at baseline and correlation with both pCR and disease-free endpoints highlights that high levels of TILs at diagnosis bodes for an improved outcome regardless of attainment of pCR [68]. Those with low levels of TILs and residual tumor at surgery post-NAC and anti-HER2 therapy had the worst outcomes of all, suggesting that it is this group that needs more effective antitumor and immune-enhancing strategies. The fact that TILs are highly associated with responses to chemotherapy and trastuzumab suggests that the presence of TILs, both pre-NAC and post-NAC, should be taken into account for patient treatment decisions—a possible schema for this is shown in Fig. 2. The potential synergistic immune effects between chemotherapy and immunotherapies also suggest that combination approaches in the neoadjuvant setting, prior to surgery, may also be beneficial.
Table 2

A summary of the studies investigating a correlation between the extent of TIL infiltrate and responses to neoadjuvant/adjuvant chemotherapy in breast cancer

Breast cancer subtype (Number of patients)

TILs predictive of pCR?

TILs predictive of disease-free or overall survival?

Reference

Chemotherapy used

All patients (56)

Yes

ND

[60]

Anthracycline/taxane or epirubicin, cyclophosphamide, and capecitabine

All patients (73)

Yes

ND

[139]

Anthracycline/taxane based

ER+/PR+ (659)

Yes

ND

[59]

Anthracycline/cyclophosphamide/taxane

ERPR (266)

Yes

ND

All patients (1334)

 

Yes (total or distant stromal CD8+)

[75]

Cyclophosphamide/methotrexate/fluorouracil

ER+ (911)

 

No (intratumoral or adjacent stroma CD8+)

ER (485)

 

No (total CD8+)

HER2+ (169)

 

Yes (total CD8+)

HER2 (1106)

 

No (total CD8+)

Yes (total CD8+)

ER (268)

Yes

Yes

[38]

Fluorouracil/epirubicin/cyclophosphamide or docetaxel and docetaxel plus epirubicin

One cohort of 113, one of 255

All patients (3403)

 

No

[140]

Adjuvant systemic therapy

ER (927)

 

Yes

ER+ (2456)

 

No

HER2+ (216)

 

No

TNBC (535)

 

Yes

All patients (180)

Yes

ND

[37]

Anthracycline/cyclophosphamide or cyclophosphamide/epirubicin/5-fluorouracil

TNBC (82)

Yes

ND

HER2+ERPR (42)

No

ND

HER2ER+/PR+ (46)

No

ND

All patients (845)

Yes

ND

[61]

Meta-analysis: anthracycline with or without taxane-based NAC

ERHER2

Yes

ND

HER2+ (116)

Yes

ND

ER+Her2

Yes

ND

All patients (68)

Yes

ND

[141]

Anthracycline and/or taxane-based treatment

All patients (180)

Yes

ND

[71]

Paclitaxel then fluorouracil/epirubicin/cyclophosphamide

HER2 (313)

Yes

ND

[63]

Anthracycline/taxane

All patients (2009)

ND

No

[39]

Doxorubicin followed by three cycles of cyclophosphamide/methotrexate/fluorouracil

ER/HER2 (1079)

ND

No

HER2+ (297)

ND

No

TNBC (256)

ND

Yes

All patients (153)

Yes

ND

[72]

Anthracycline and/or taxane-based treatment

TNBC (38)

Yes

Non-TNBC (115)

Yes (If CD8+ component analyzed), No if CD4+ analyzed

All patients (175)

Yes

ND

[73]

Anthracycline and/or taxane-based treatment or herceptin+NAC

All patients (12439)

ND

ND

[142]

Cyclophosphamide/methotrexate/fluorouracil or epirubicin plus fluorouracil

ER (3591)

ND

Yes

ER+ (8775)

ND

No

ER+HER2+ (772)

ND

Yes

All patients (934)

ND

No

[65]

Docetaxel or vinorelbine, followed by three cycles of fluorouracil/epirubicin/cyclophosphamide

ER+HER2 (591)

ND

No

HER2+ (209)

ND

No

TNBC (134)

ND

Yes

TNBC (278)

Yes

Yes

[64]

Anthracycline-based neoadjuvant or anthracycline/taxane

TNBC (47)

Yes

ND

[143]

Panitumumab plus anthracycline/taxane-based chemotherapy

TNBC (481)

ND

Yes

[66]

Doxorubicin plus cyclophosphamide and taxol/docetaxol

All patients (580)

Yes

ND

[41]

Anthracycline/taxane with or without carboplatin

TNBC (314)

Yes

ND

HER2+ (266)

Yes

ER estrogen receptor, HER2 human epidermal growth factor receptor 2, NAC neoadjuvant chemotherapy, ND not determined, PR progesterone receptor, TNBC triple negative breast cancer

Fig. 2

Using the TIL infiltrate and response to frontline treatments to guide patient management decisions. The presence of tumor-infiltrating lymphocytes (TILs) and response to neoadjuvant chemotherapy (NAC) may be used to guide decisions on second line treatments. Patients with high TILs and exhibiting pathological complete responses to NAC (far left) have an excellent prognosis and may not require further intervention other than standard of care. Patients with high TILs at diagnosis but no pathological complete response, or patients with low TILs at diagnosis but high TILs post-NAC, may benefit from immunotherapies, such as checkpoint inhibition (PD-1 blockade), or immune agonists (e.g., 4-1BB). However, patients with little TIL infiltrate either pre-NAC or post-NAC (far right) require additional or different treatment strategies to induce an immune response, such as adoptive cellular therapy or vaccination strategies. Targeted inhibitors (e.g., MEK inhibitors) should be considered for all patient groups where appropriate, but the impact of targeted inhibitors on the immune response should be a therapeutic consideration. This figure was made exclusively for this manuscript. DC dendritic cells, FACS fluorescence-activated cell sorting, H&E hematoxylin and eosin staining

Recently, efforts have been made to sub-divide the immune infiltrate into lineage subsets to determine the prognostic value of each immune cell type. The presence of CD8+ cells in the tumor infiltrate prior to the onset of NAC predicted pCR in several studies [41, 7175]. The presence of Tregs prior to NAC has also been shown to be a prognostic indicator of pCR [7173, 76]. Although this seems somewhat counterintuitive given the suppressive role of Tregs, it is probably because FOXP3+ infiltrate is also significantly associated with CD8+ infiltrate. More informative is the observation that the presence of Tregs following NAC has a significant negative correlation with pCR and disease-free or overall survival [7779]. Indeed, the ratio of CD8 to Tregs following NAC has been shown to be a strong predictor of clinical responses [78]. The increased CD8 to Treg ratio likely facilitates the acquisition of CD8+ T-cell effector functions such as Granzyme B expression, which is elevated post-NAC [78, 80]. In this study they found that the proportion of CD8+ lymphocytes remained stable pre-NAC and post-NAC whereas Tregs were significantly reduced in the post-NAC samples. Limited work has been done on the prognostic significance of other immune cell subtypes although the presence of CD4+ [72] and CD20+ [74] lymphocytes pre-NAC is also associated with pCR. Another study found that the presence of T follicular helper (TFH) cells, which function to attract and promote the formation of memory B cells, was associated with improved responses to chemotherapy in breast cancer. These TFH cells localized to peritumoral tertiary lymphoid structures, indicating there may be localized orchestration of antitumor immune responses in certain breast cancers [81]. The link between TIL infiltrate and patient outcome has led to heightened interest in utilizing immune-modulating strategies for patients with breast cancer. Other immune subsets of interest include γδ-T cells and Th17 cells. γδ-T cells show positive correlations with CD4+ FOXP3+ T cells, and are associated with poor outcomes and advanced tumor stage, as well as low disease-free and overall survival in patients with breast cancer [82]. However, further work is needed given the apparent antitumor role of γδ-T cells in some settings [83, 84]. In a small study of 30 patients, Th17 cells negatively correlated with disease stage [85] but further work is needed to evaluate their effect on immune responses to NAC [86]. Accordingly, further work is needed to determine whether these subsets are potential targets for immunotherapy.

Combining conventional treatment with immunotherapy

The strong prognostic significance of TILs in breast cancer opens up important questions for patient management. In particular, it is likely that patients with high TILs post-NAC can benefit from strategies designed to enhance the immune response against the tumor. As discussed above, NAC has the potential to increase the CD8+ to Treg ratio, which correlates with the likelihood of pCR [87, 78]. Interestingly, certain chemotherapies, including cyclophosphamide [42, 51, 88], used to treat patients in the cohort studied by Ladoire et al., have been shown to specifically reduce the number of Tregs in preclinical models. Thus, it is worth considering the immunological consequences of any NAC regime. For example, concurrent depletion of Tregs through the use of immunotherapies such as anti-CTLA-4 mAb [89] may enhance the efficacy of NAC in inducing antitumor immune responses. There may also be clinical benefit in depleting other immunosuppressive populations such as MDSCs or tumor-associated macrophages [16]. A histopathological examination of breast cancer tissue pre-NAC and post-NAC by DeNardo et al. revealed that the presence of CD68+ macrophages inversely correlated with CD8+ TIL following NAC. Furthermore, depletion of this subset enhanced chemotherapy in preclinical models of breast cancer [90]. A recent study showed that a monocyte/DC metagene analysis held similar predictive value to NAC as the T cell/NK cell module [91]. Therefore, further work evaluating this in humans is warranted although the heterogeneity of this population makes characterization more complex than the T-cell infiltrate.

Although NAC is capable of inducing CD8+ infiltrate within the tumor microenvironment, the efficacy of the antitumor immune responses is likely limited by the presence of immunosuppressive networks. For example, a recent retrospective analysis of 94 post-NAC biopsies demonstrated that PD-L1 expression correlates with TIL infiltrate and pCR [40], which is in agreement with studies from other groups evaluating PD-L1 mRNA expression [41, 92]. This is likely because PD-L1 is expressed following IFNγ stimulation and so is a surrogate marker of an immune response. It should be noted, however, that other groups have reported that PD-1 and PD-L1 expression are correlated with poor prognosis in patients with breast cancer [9395]. Nevertheless, these studies consistently observed PD-L1 and PD-1 expression in a subset of breast tumors; because PD-L1 expression has previously been shown to be a marker for the efficacy of anti-PD-1 in other tumor types [96], it is possible that PD-L1 expression may be a predictive marker for patients likely to have good responses to a combination of NAC and anti-PD-1. It was also recently reported that expression of B7-H4, another member of the B7 family, is a marker of good prognosis in patients with breast cancer [97]. Further work is need to evaluate the potential to modulate B7-H4 because it has been reported to inhibit T-cell function [98, 99] and yet B7-H4 expression was reported to limit tumor growth in this study [97]. Immune checkpoint blockade with anti-PD-1 [100] and anti-CTLA-4 [101] has already been shown to enhance the efficacy of chemotherapy and radiotherapy [102] in preclinical models and phase I clinical trials [103], and so there is clear rationale to further evaluate these combinations in patients. Further work will investigate the potential of combining NAC with other immune modulators in breast cancer given that that these immunosuppressive pathways appear upregulated in TIL+ breast cancers [41].

The success of checkpoint inhibitors is highly dependent on the extent of a pre-existing immune response against the tumor, and the ability of immune-targeted therapies to re-stimulate/activate immune subsets. Because conventional therapies such as chemotherapy and radiotherapy result in the release of tumor-associated antigens (increased antigenicity) from the apoptotic tumor cells, the increased immunogenicity provides a promising target for immunotherapies [103]. These tumor-associated antigens, released from tumor cells after chemotherapy, are taken up by antigen-presenting cells or DCs and used to stimulate downstream effector T cells capable of recognizing and lysing tumor cells [103]. Accordingly, it is evident that subsequent immunotherapy is likely to be a beneficial endeavor, provided that the initial conventional therapy used is able to effectively “prime” tumor cells to express and present foreign tumor antigens. A study conducted by Twyman-Saint Victor et al. demonstrated that radiation is able to enhance the diversity of the T-cell receptor repertoire of intratumoral T cells. This process was found to underpin the synergy of radiotherapy and anti-PD-1/anti-CLTA-4 in patients with melanoma [103]. Notably, high-dose radiotherapy and high-dose chemotherapy can ablate immune function. Therefore, careful consideration must be given to the dosage and the timing of these therapies when combined with immunotherapy.

Combining targeted inhibitors with immunotherapy

While immunotherapy is an attractive adjuvant therapy for patients presenting with high TIL pre-NAC or post-NAC, an alternative approach is required for the treatment of patients with poorly immunogenic cancer types and low-level TILs at diagnosis. Liu et al. recently used preclinical models of melanoma to investigate the immunogenic function of the MAPK pathway inhibitors trametinib and dabrafenib in combination with immunomodulatory antibodies, including PD-L1/PD-1 and CTLA-4. They reported the potential for synergy between these therapies [104]. The combination of trametinib with anti-PD-1 increased tumor-infiltrating CD8+ T cells in CT26 mouse colon carcinoma tumors, as well as downregulating immunosuppressive factors, upregulating HLA molecules, and increasing immune responses in the tumors yes [104]. Dabrafenib had no suppressive action on the function of CD4+ and CD8+ T cells, whereas trametinib had mild partial or transient inhibitory effects on T-cell proliferation fine [104]. This phenomenon is supported by findings of Callahan et al. demonstrating that RAF inhibitors in BRAF wild-type tumors caused hyperactivation of ERK signaling, thereby enhancing T-cell activation and signaling [105]. While targeted blockade of checkpoint inhibitors has proven to be effective, recent evidence suggests that agonists may also be crucial in TIL stimulation. CD8+ T-cell responses require T-cell receptor activation in addition to co-stimulation provided through ligation of tumor necrosis factor receptor family members 4-1BB (CD137) and OX40 (CD134). Studies using the OX40 agonist in combination with either anti-4-1BB, anti-PD-L1, anti-CTLA-4, and immunization in sarcoma, melanoma, hepatoma, and breast cancer models have shown significant survival benefit by boosting the T-cell response [106109]. One hurdle to the application of immunotherapy in breast cancer is the apparent low immunogenicity of breast cancers, perhaps owing to the low mutation rate of breast cancer when compared to cancers such as melanoma, which show a high response rate to immunotherapy [110112]. One approach is to use targeted inhibitors designed to induce immunogenicity in tumors. For example, Kim et al. proposed the notion of epigenetic modulation, suggesting that MHC I-related genes are downregulated through epigenetic silencing of tumor cells [16]. They investigated this by combining anti-PD-1 and anti-CTLA-4 antibodies with 5-azacytidine (a DNA methyltransferase inhibitor) and entinostat (a class I histone deacetylase inhibitor). This study revealed complete eradication of tumors in murine 4 T1 (breast) and CT26 (colorectal) models [16]. Similarly, studies investigating DC vaccination in melanoma have shown that combination therapy with PI3K inhibitors has significant pro-inflammatory effects via TLR ligands that support antitumor immunity [113]. The results of these studies suggest that combining targeted inhibitors with immunotherapy may be a promising option for clinical treatment of breast cancer for patients with high-level TILs. However, alternative therapeutic options are still required for patients with low-level TILs. Because patients with high TILs show increased response rates to NAC, one approach is to use strategies that enhance T-cell trafficking to the tumor site. Denkert et al. reported a correlation between CXCL9/CXCL13 expression and the number of TILs in patients with breast cancer [59]. Therefore, treatments that enhance the expression of these chemokines may enhance the efficacy of NAC. Alternatively, adoptive cell therapy (ACT) utilizing TILs or chimeric antigen receptor T cells has emerged as a promising regimen for the treatment of certain cancers, including melanoma [114118], with recent reports of long-term remission in some patients [119]. In a study conducted by Koya et al., combined treatment of vemurafenib plus ACT of lymphocytes genetically modified with a T-cell receptor recognizing ovalbumin resulted in superior antitumor responses [120]. While absolute numbers of T cells infiltrating the tumor did not increase with vemurafenib treatment, they found that the combination with ACT increased the functionality of antigen-specific T lymphocytes [120]. The findings of these studies suggest that BRAF inhibitors may be effective in combination with ACT; however, evaluation of ACT in combination with other inhibitors is also necessary. The utility of this approach in breast cancer is yet to be determined. One possibility is the targeting of the HER2 antigen [121, 122]. Ishikawa et al. [123] investigated the effects of ACT in addition to anti-CTLA-4, and were able to show that the combination enhanced antitumor activity. Taken together, there is a large body of evidence demonstrating the potential utility of TIL-associated immunotherapies for breast cancer in the future.

Conclusions

There is now overwhelming data on the prognostic and predictive association of TILs. Determination of TILs is potentially universally available to all patients with breast cancer and efforts are underway to ensure that determination of TILs is standardized and reproducible [124]. If successful, the scene will be set for TILs to enter clinical practice as a biomarker that has the potential for clinical utility and prognostic implications [41].

Because TILs are associated with improved survival endpoints in a continuous fashion, they may be integrated with exiting models of risk prediction that inform decisions about adjuvant treatment, such as tumor size and nodal status, and may also serve as a stratification factor in randomized clinical trials. This may be of particular use in trial designs using NAC. pCR in the primary tumor with NAC is a very strong predictor of freedom from recurrence and long-term survival [125]. Of note, even patients without a pCR still have a relatively good outcome if they have high TILs in the primary disease [64, 124]. A composite of pCR and TILs could foreseeably be used to select patients who do not need further therapy because their risk of recurrence is negligible (pCR and high TILs) or low (pCR but low TILs), or conversely to select those at high risk of recurrence (no pCR, low TILs) who would benefit from trials of novel interventions that may include immunotherapy. Furthermore, using TILs to identify patients at very low risk of recurrence affords the opportunity for trials looking at de-escalation of therapy to avoid unnecessary long-term toxicity or focusing on novel therapeutic combinations for the poor prognostic group.

Notes

Declarations

Acknowledgments

SL is supported by Cancer Council Victoria, Australia; the National Health and Medical Research Council (NHMRC) National Breast Cancer Foundation (NBCF) of Australia, and the Breast Cancer Research Foundation (BCRF), NY. PAB was supported by a National Breast Cancer Fellowship (ID# PF-14-008). PKD was supported by an NHMRC Senior Research Fellowship (1041828).

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Division of Research and Cancer Medicine, Peter MacCallum Cancer Centre
(2)
Sir Peter MacCallum Department of Oncology, The University of Melbourne
(3)
Peter MacCallum Cancer Centre

References

  1. Schreiber RD, Old LJ, Smyth MJ. Cancer immunoediting: integrating immunity’s roles in cancer suppression and promotion. Science. 2011;331:1565–70.PubMedGoogle Scholar
  2. Mittal D, Gubin MM, Schreiber RD, Smyth MJ. New insights into cancer immunoediting and its three component phases--elimination, equilibrium and escape. Curr Opin Immunol. 2014;27:16–25.PubMedPubMed CentralGoogle Scholar
  3. Andre F, Dieci MV, Dubsky P, Sotiriou C, Curigliano G, Denkert C, et al. Molecular pathways: involvement of immune pathways in the therapeutic response and outcome in breast cancer. Clin Cancer Res. 2013;19:28–33.PubMedGoogle Scholar
  4. Caras I, Grigorescu A, Stavaru C, Radu DL, Mogos I, Szegli G, et al. Evidence for immune defects in breast and lung cancer patients. Cancer Immunol Immunother. 2004;53:1146–52.PubMedGoogle Scholar
  5. Monjazeb AM, Zamora AE, Grossenbacher SK, Mirsoian A, Sckisel GD, Murphy WJ. Immunoediting and antigen loss: overcoming the Achilles heel of immunotherapy with antigen non-specific therapies. Front Oncol. 2013;3:197.PubMedPubMed CentralGoogle Scholar
  6. Enderling H, Hlatky L, Hahnfeldt P. Immunoediting: evidence of the multifaceted role of the immune system in self-metastatic tumor growth. Theor Biol Med Model. 2012;9:31.PubMedPubMed CentralGoogle Scholar
  7. Vesely MD, Schreiber RD. Cancer immunoediting: antigens, mechanisms, and implications to cancer immunotherapy. Ann N Y Acad Sci. 2013;1284:1–5.PubMedPubMed CentralGoogle Scholar
  8. Quezada SA, Peggs KS, Simpson TR, Allison JP. Shifting the equilibrium in cancer immunoediting: from tumor tolerance to eradication. Immunol Rev. 2011;241:104–18.PubMedPubMed CentralGoogle Scholar
  9. Dunn GP, Bruce AT, Ikeda H, Old LJ, Schreiber RD. Cancer immunoediting: from immunosurveillance to tumor escape. Nat Immunol. 2002;3:991–8.PubMedGoogle Scholar
  10. O’Sullivan T, Saddawi-Konefka R, Vermi W, Koebel CM, Arthur C, White JM, et al. Cancer immunoediting by the innate immune system in the absence of adaptive immunity. J Exp Med. 2012;209:1869–82.PubMedPubMed CentralGoogle Scholar
  11. Emens LA. Breast cancer immunobiology driving immunotherapy: vaccines and immune checkpoint blockade. Expert Rev Anticancer Ther. 2012;12:1597–611.PubMedPubMed CentralGoogle Scholar
  12. Pardoll DM. The blockade of immune checkpoints in cancer immunotherapy. Nat Rev Cancer. 2012;12:252–64.PubMedPubMed CentralGoogle Scholar
  13. Wolchok JD, Chan TA. Cancer: antitumour immunity gets a boost. Nature. 2014;515:496–8.PubMedGoogle Scholar
  14. van Elsas A, Hurwitz AA, Allison JP. Combination immunotherapy of B16 melanoma using anti-cytotoxic T lymphocyte-associated antigen 4 (CTLA-4) and granulocyte/macrophage colony-stimulating factor (GM-CSF)-producing vaccines induces rejection of subcutaneous and metastatic tumors accompanied by autoimmune depigmentation. J Exp Med. 1999;190:355–66.PubMedPubMed CentralGoogle Scholar
  15. Fan X, Quezada SA, Sepulveda MA, Sharma P, Allison JP. Engagement of the ICOS pathway markedly enhances efficacy of CTLA-4 blockade in cancer immunotherapy. J Exp Med. 2014;211:715–25.PubMedPubMed CentralGoogle Scholar
  16. Kim K, Skora AD, Li Z, Liu Q, Tam AJ, Blosser RL, et al. Eradication of metastatic mouse cancers resistant to immune checkpoint blockade by suppression of myeloid-derived cells. Proc Natl Acad Sci U S A. 2014;111:11774–9.PubMedPubMed CentralGoogle Scholar
  17. Pentcheva-Hoang T, Simpson TR, Montalvo-Ortiz W, Allison JP. Cytotoxic T lymphocyte antigen-4 blockade enhances antitumor immunity by stimulating melanoma-specific T-cell motility. Cancer Immunol Res. 2014;2:970–80.PubMedGoogle Scholar
  18. Brahmer JR, Drake CG, Wollner I, Powderly JD, Picus J, Sharfman WH, et al. Phase I study of single-agent anti-programmed death-1 (MDX-1106) in refractory solid tumors: safety, clinical activity, pharmacodynamics, and immunologic correlates. J Clin Oncol. 2010;28:3167–75.PubMedPubMed CentralGoogle Scholar
  19. Wolchok JD, Neyns B, Linette G, Negrier S, Lutzky J, Thomas L, et al. Ipilimumab monotherapy in patients with pretreated advanced melanoma: a randomised, double-blind, multicentre, phase 2, dose-ranging study. Lancet Oncol. 2010;11:155–64.PubMedGoogle Scholar
  20. Postow MA, Callahan MK, Wolchok JD. Immune checkpoint blockade in cancer therapy. J Clin Oncol. 2015;33:1974–198.PubMedPubMed CentralGoogle Scholar
  21. Beavis PA, Divisekera U, Paget C, Chow MT, John LB, Devaud C, et al. Blockade of A2A receptors potently suppresses the metastasis of CD73+ tumors. Proc Natl Acad Sci U S A. 2013;110:14711–6.PubMedPubMed CentralGoogle Scholar
  22. Beavis PA, Milenkovski N, Henderson MA, John LB, Allard B, Loi S, et al. Adenosine receptor 2A blockade increases the efficacy of anti-PD-1 through enhanced antitumor t-cell responses. Cancer Immunol Res. 2015;3:506–17.PubMedGoogle Scholar
  23. Beavis PA, Stagg J, Darcy PK, Smyth MJ. CD73: a potent suppressor of antitumor immune responses. Trends Immunol. 2012;33:231–7.PubMedGoogle Scholar
  24. Waickman AT, Alme A, Senaldi L, Zarek PE, Horton M, Powell JD. Enhancement of tumor immunotherapy by deletion of the A2A adenosine receptor. Cancer Immunol Immunother. 2012;61:917–26.PubMedGoogle Scholar
  25. Ohta A, Gorelik E, Prasad SJ, Ronchese F, Lukashev D, Wong MK, et al. A2A adenosine receptor protects tumors from antitumor T cells. Proc Natl Acad Sci U S A. 2006;103:13132–7.PubMedPubMed CentralGoogle Scholar
  26. Nishikawa H, Sakaguchi S. Regulatory T cells in cancer immunotherapy. Curr Opin Immunol. 2014;27:1–7.PubMedGoogle Scholar
  27. Zheng X, Koropatnick J, Chen D, Velenosi T, Ling H, Zhang X, et al. Silencing IDO in dendritic cells: a novel approach to enhance cancer immunotherapy in a murine breast cancer model. Int J Cancer. 2013;132:967–77.PubMedGoogle Scholar
  28. Holmgaard RB, Zamarin D, Munn DH, Wolchok JD, Allison JP. Indoleamine 2,3-dioxygenase is a critical resistance mechanism in antitumor T cell immunotherapy targeting CTLA-4. J Exp Med. 2013;210:1389–402.PubMedPubMed CentralGoogle Scholar
  29. Holtzhausen A, Zhao F, Evans KS, Hanks BA. Early carcinogenesis involves the establishment of immune privilege via intrinsic and extrinsic regulation of indoleamine 2,3-dioxygenase-1: translational implications in cancer immunotherapy. Front Immunol. 2014;5:438.PubMedPubMed CentralGoogle Scholar
  30. Platten M, von Knebel DN, Oezen I, Wick W, Ochs K. Cancer immunotherapy by targeting IDO1/TDO and their downstream effectors. Front Immunol. 2014;5:673.PubMedGoogle Scholar
  31. Wang Z, Shi X, Li Y, Fan J, Zeng X, Xian Z, et al. Blocking autophagy enhanced cytotoxicity induced by recombinant human arginase in triple-negative breast cancer cells. Cell Death Dis. 2014;5:e1563.PubMedPubMed CentralGoogle Scholar
  32. Bedoya AM, Tate DJ, Baena A, Cordoba CM, Borrero M, Pareja R, et al. Immunosuppression in cervical cancer with special reference to arginase activity. Gynecol Oncol. 2014;135:74–80.PubMedGoogle Scholar
  33. Vasquez-Dunddel D, Pan F, Zeng Q, Gorbounov M, Albesiano E, Fu J, et al. STAT3 regulates arginase-I in myeloid-derived suppressor cells from cancer patients. J Clin Invest. 2013;123:1580–9.PubMedPubMed CentralGoogle Scholar
  34. Ghansah T. A novel strategy for modulation of MDSC to enhance cancer immunotherapy. Oncoimmunology. 2012;1:984–5.PubMedPubMed CentralGoogle Scholar
  35. Forghani P, Khorramizadeh MR, Waller EK. Silibinin inhibits accumulation of myeloid-derived suppressor cells and tumor growth of murine breast cancer. Cancer Med. 2014;3:215–24.PubMedPubMed CentralGoogle Scholar
  36. Markowitz J, Wesolowski R, Papenfuss T, Brooks TR, Carson 3rd WE. Myeloid-derived suppressor cells in breast cancer. Breast Cancer Res Treat. 2013;140:13–21.PubMedPubMed CentralGoogle Scholar
  37. Ono M, Tsuda H, Shimizu C, Yamamoto S, Shibata T, Yamamoto H, et al. Tumor-infiltrating lymphocytes are correlated with response to neoadjuvant chemotherapy in triple-negative breast cancer. Breast Cancer Res Treat. 2012;132:793–805.PubMedGoogle Scholar
  38. West NR, Milne K, Truong PT, Macpherson N, Nelson BH, Watson PH. Tumor-infiltrating lymphocytes predict response to anthracycline-based chemotherapy in estrogen receptor-negative breast cancer. Breast Cancer Res. 2011;13:R126.PubMedPubMed CentralGoogle Scholar
  39. Loi S, Sirtaine N, Piette F, Salgado R, Viale G, Van Eenoo F, 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. 2013;31:860–7.PubMedGoogle Scholar
  40. Wimberly H, Brown JR, Schalper KA, Haack H, Silver MR, Nixon C, et al. PD-L1 expression correlates with tumor-infiltrating lymphocytes and response to neoadjuvant chemotherapy in breast cancer. Cancer Immunol Res. 2014;3:326–32.PubMedPubMed CentralGoogle Scholar
  41. Denkert C, von Minckwitz G, Brase JC, Sinn BV, Gade S, Kronenwett R, et al. Tumor-infiltrating lymphocytes and response to neoadjuvant chemotherapy with or without carboplatin in human epidermal growth factor receptor 2-positive and triple-negative primary breast cancers. J Clin Oncol. 2015;33:983–91.PubMedGoogle Scholar
  42. Ghiringhelli F, Larmonier N, Schmitt E, Parcellier A, Cathelin D, Garrido C, et al. CD4+CD25+ regulatory T cells suppress tumor immunity but are sensitive to cyclophosphamide which allows immunotherapy of established tumors to be curative. Eur J Immunol. 2004;34:336–44.PubMedGoogle Scholar
  43. Zitvogel L, Apetoh L, Ghiringhelli F, Kroemer G. Immunological aspects of cancer chemotherapy. Nat Rev Immunol. 2008;8:59–73.PubMedGoogle Scholar
  44. Ghiringhelli F, Apetoh L. The interplay between the immune system and chemotherapy: emerging methods for optimizing therapy. Expert Rev Clin Immunol. 2014;10:19–30.PubMedGoogle Scholar
  45. Ghiringhelli F, Apetoh L, Tesniere A, Aymeric L, Ma Y, Ortiz C, et al. Activation of the NLRP3 inflammasome in dendritic cells induces IL-1beta-dependent adaptive immunity against tumors. Nat Med. 2009;15:1170–8.PubMedGoogle Scholar
  46. Apetoh L, Ghiringhelli F, Tesniere A, Obeid M, Ortiz C, Criollo A, et al. Toll-like receptor 4-dependent contribution of the immune system to anticancer chemotherapy and radiotherapy. Nat Med. 2007;13:1050–9.PubMedGoogle Scholar
  47. Nowak AK, Robinson BW, Lake RA. Gemcitabine exerts a selective effect on the humoral immune response: implications for combination chemo-immunotherapy. Cancer Res. 2002;62:2353–8.PubMedGoogle Scholar
  48. Tongu M, Harashima N, Monma H, Inao T, Yamada T, Kawauchi H, et al. Metronomic chemotherapy with low-dose cyclophosphamide plus gemcitabine can induce anti-tumor T cell immunity in vivo. Cancer Immunol Immunother. 2013;62:383–91.PubMedGoogle Scholar
  49. Homma Y, Taniguchi K, Nakazawa M, Matsuyama R, Mori R, Takeda K, et al. Changes in the immune cell population and cell proliferation in peripheral blood after gemcitabine-based chemotherapy for pancreatic cancer. Clin Transl Oncol. 2014;16:330–5.PubMedGoogle Scholar
  50. Mozaffari F, Lindemalm C, Choudhury A, Granstam-Bjorneklett H, Lekander M, Nilsson B, et al. Systemic immune effects of adjuvant chemotherapy with 5-fluorouracil, epirubicin and cyclophosphamide and/or radiotherapy in breast cancer: a longitudinal study. Cancer Immunol Immunother. 2009;58:111–20.PubMedGoogle Scholar
  51. Lutsiak ME, Semnani RT, De Pascalis R, Kashmiri SV, Schlom J, Sabzevari H. Inhibition of CD4(+)25+ T regulatory cell function implicated in enhanced immune response by low-dose cyclophosphamide. Blood. 2005;105:2862–8.PubMedGoogle Scholar
  52. Zhu Y, Liu N, Xiong SD, Zheng YJ, Chu YW. CD4+Foxp3+ regulatory T-cell impairment by paclitaxel is independent of toll-like receptor 4. Scand J Immunol. 2011;73:301–8.PubMedGoogle Scholar
  53. Machiels JP, Reilly RT, Emens LA, Ercolini AM, Lei RY, Weintraub D, et al. Cyclophosphamide, doxorubicin, and paclitaxel enhance the antitumor immune response of granulocyte/macrophage-colony stimulating factor-secreting whole-cell vaccines in HER-2/neu tolerized mice. Cancer Res. 2001;61:3689–97.PubMedGoogle Scholar
  54. Park JY, Jang MJ, Chung YH, Kim KY, Kim SS, Lee WB, et al. Doxorubicin enhances CD4(+) T-cell immune responses by inducing expression of CD40 ligand and 4-1BB. Int Immunopharmacol. 2009;9:1530–9.PubMedGoogle Scholar
  55. Hannesdottir L, Tymoszuk P, Parajuli N, Wasmer MH, Philipp S, Daschil N, et al. Lapatinib and doxorubicin enhance the Stat1-dependent antitumor immune response. Eur J Immunol. 2013;43:2718–29.PubMedGoogle Scholar
  56. Nowak AK, Lake RA, Marzo AL, Scott B, Heath WR, Collins EJ, et al. Induction of tumor cell apoptosis in vivo increases tumor antigen cross-presentation, cross-priming rather than cross-tolerizing host tumor-specific CD8 T cells. J Immunol. 2003;170:4905–13.PubMedGoogle Scholar
  57. Kroemer G, Galluzzi L, Kepp O, Zitvogel L. Immunogenic cell death in cancer therapy. Annu Rev Immunol. 2013;31:51–72.PubMedGoogle Scholar
  58. Menard S, Tomasic G, Casalini P, Balsari A, Pilotti S, Cascinelli N, et al. Lymphoid infiltration as a prognostic variable for early-onset breast carcinomas. Clin Cancer Res. 1997;3:817–9.PubMedGoogle Scholar
  59. Denkert C, Loibl S, Noske A, Roller M, Muller BM, Komor M, et al. Tumor-associated lymphocytes as an independent predictor of response to neoadjuvant chemotherapy in breast cancer. J Clin Oncol. 2010;28:105–13.PubMedGoogle Scholar
  60. Ladoire S, Arnould L, Apetoh L, Coudert B, Martin F, Chauffert B, et al. Pathologic complete response to neoadjuvant chemotherapy of breast carcinoma is associated with the disappearance of tumor-infiltrating foxp3+ regulatory T cells. Clin Cancer Res. 2008;14:2413–20.PubMedGoogle Scholar
  61. Ignatiadis M, Singhal SK, Desmedt C, Haibe-Kains B, Criscitiello C, Andre F, et al. Gene modules and response to neoadjuvant chemotherapy in breast cancer subtypes: a pooled analysis. J Clin Oncol. 2012;30:1996–2004.PubMedGoogle Scholar
  62. Yu H, Yang J, Jiao S, Li Y, Zhang W, Wang J. T-box transcription factor 21 expression in breast cancer and its relationship with prognosis. Int J Clin Exp Pathol. 2014;7:6906–13.PubMedPubMed CentralGoogle Scholar
  63. Issa-Nummer Y, Darb-Esfahani S, Loibl S, Kunz G, Nekljudova V, Schrader I, et al. Prospective validation of immunological infiltrate for prediction of response to neoadjuvant chemotherapy in HER2-negative breast cancer--a substudy of the neoadjuvant GeparQuinto trial. PLoS One. 2013;8:e79775.PubMedPubMed CentralGoogle Scholar
  64. Dieci MV, Criscitiello C, Goubar A, Viale G, Conte P, Guarneri V, et al. Prognostic value of tumor-infiltrating lymphocytes on residual disease after primary chemotherapy for triple-negative breast cancer: a retrospective multicenter study. Ann Oncol. 2014;25:611–8.PubMedPubMed CentralGoogle Scholar
  65. Loi S, Michiels S, Salgado R, Sirtaine N, Jose V, Fumagalli D, et al. Tumor infiltrating lymphocytes are prognostic in triple negative breast cancer and predictive for trastuzumab benefit in early breast cancer: results from the FinHER trial. Ann Oncol. 2014;25:1544–50.PubMedGoogle Scholar
  66. Adams S, Gray RJ, Demaria S, Goldstein L, Perez EA, Shulman LN, et al. Prognostic value of tumor-infiltrating lymphocytes in triple-negative breast cancers from two phase III randomized adjuvant breast cancer trials: ECOG 2197 and ECOG 1199. J Clin Oncol. 2014;32:2959–66.PubMedPubMed CentralGoogle Scholar
  67. Gennari R, Menard S, Fagnoni F, Ponchio L, Scelsi M, Tagliabue E, et al. Pilot study of the mechanism of action of preoperative trastuzumab in patients with primary operable breast tumors overexpressing HER2. Clin Cancer Res. 2004;10:5650–5.PubMedGoogle Scholar
  68. Salgado R, Denkert C, Campbell C, Savas P, Nucifero P, Aura C, et al. Tumor-infiltrating lymphocytes and associations with pathological complete response and event-free survival in HER2-positive early stage breast cancer treated with lapatinib and trastuzumab. JAMA Oncol. 2015;1:448–54.PubMedGoogle Scholar
  69. Arnould L, Gelly M, Penault-Llorca F, Benoit L, Bonnetain F, Migeon C, et al. Trastuzumab-based treatment of HER2-positive breast cancer: an antibody-dependent cellular cytotoxicity mechanism? Br J Cancer. 2006;94:259–67.PubMedPubMed CentralGoogle Scholar
  70. Bianchini G, Gianni L. The immune system and response to HER2-targeted treatment in breast cancer. Lancet Oncol. 2014;15:e58–68.PubMedGoogle Scholar
  71. Oda N, Shimazu K, Naoi Y, Morimoto K, Shimomura A, Shimoda M, et al. Intratumoral regulatory T cells as an independent predictive factor for pathological complete response to neoadjuvant paclitaxel followed by 5-FU/epirubicin/cyclophosphamide in breast cancer patients. Breast Cancer Res Treat. 2012;136:107–16.PubMedGoogle Scholar
  72. Seo AN, Lee HJ, Kim EJ, Kim HJ, Jang MH, Lee HE, et al. Tumour-infiltrating CD8+ lymphocytes as an independent predictive factor for pathological complete response to primary systemic therapy in breast cancer. Br J Cancer. 2013;109:2705–13.PubMedPubMed CentralGoogle Scholar
  73. Lee HJ, Seo JY, Ahn JH, Ahn SH, Gong G. Tumor-associated lymphocytes predict response to neoadjuvant chemotherapy in breast cancer patients. J Breast Cancer. 2013;16:32–9.PubMedPubMed CentralGoogle Scholar
  74. Brown JR, Wimberly H, Lannin DR, Nixon C, Rimm DL, Bossuyt V. Multiplexed quantitative analysis of CD3, CD8, and CD20 predicts response to neoadjuvant chemotherapy in breast cancer. Clin Cancer Res. 2014;20:5995–6005.PubMedPubMed CentralGoogle Scholar
  75. Mahmoud S, Paish E, Powe D, Macmillan R, Grainge M, Lee A, et al. Tumor-infiltrating CD8+ lymphocytes predict clinical outcome in breast cancer. J Clin Oncol. 2011;29:1949–55.PubMedGoogle Scholar
  76. West NR, Kost SE, Martin SD, Milne K, Deleeuw RJ, Nelson BH, et al. Tumour-infiltrating FOXP3(+) lymphocytes are associated with cytotoxic immune responses and good clinical outcome in oestrogen receptor-negative breast cancer. Br J Cancer. 2013;108:155–62.PubMedGoogle Scholar
  77. Aruga T, Suzuki E, Saji S, Horiguchi S, Horiguchi K, Sekine S, et al. A low number of tumor-infiltrating FOXP3-positive cells during primary systemic chemotherapy correlates with favorable anti-tumor response in patients with breast cancer. Oncol Rep. 2009;22:273–8.PubMedGoogle Scholar
  78. Ladoire S, Mignot G, Dabakuyo S, Arnould L, Apetoh L, Rebe C, et al. In situ immune response after neoadjuvant chemotherapy for breast cancer predicts survival. J Pathol. 2011;224:389–400.PubMedGoogle Scholar
  79. Liu F, Li Y, Ren M, Zhang X, Guo X, Lang R, et al. Peritumoral FOXP3(+) regulatory T cell is sensitive to chemotherapy while intratumoral FOXP3(+) regulatory T cell is prognostic predictor of breast cancer patients. Breast Cancer Res Treat. 2012;135:459–67.PubMedGoogle Scholar
  80. Ruffell B, Au A, Rugo HS, Esserman LJ, Hwang ES, Coussens LM. Leukocyte composition of human breast cancer. Proc Natl Acad Sci U S A. 2012;109:2796–801.PubMedGoogle Scholar
  81. Gu-Trantien C, Loi S, Garaud S, Equeter C, Libin M, de Wind A, et al. CD4(+) follicular helper T cell infiltration predicts breast cancer survival. J Clin Invest. 2013;123:2873–92.PubMedPubMed CentralGoogle Scholar
  82. Ma C, Zhang Q, Ye J, Wang F, Zhang Y, Wevers E, et al. Tumor-infiltrating gammadelta T lymphocytes predict clinical outcome in human breast cancer. J Immunol. 2012;189:5029–36.PubMedPubMed CentralGoogle Scholar
  83. Mattarollo SR, Kenna T, Nieda M, Nicol AJ. Chemotherapy and zoledronate sensitize solid tumour cells to Vgamma9Vdelta2 T cell cytotoxicity. Cancer Immunol Immunother. 2007;56:1285–97.PubMedGoogle Scholar
  84. Kobayashi H, Tanaka Y, Yagi J, Osaka Y, Nakazawa H, Uchiyama T, et al. Safety profile and anti-tumor effects of adoptive immunotherapy using gamma-delta T cells against advanced renal cell carcinoma: a pilot study. Cancer Immunol Immunother. 2007;56:469–76.PubMedGoogle Scholar
  85. Yang L, Qi Y, Hu J, Tang L, Zhao S, Shan B. Expression of Th17 cells in breast cancer tissue and its association with clinical parameters. Cell Biochem Biophys. 2012;62:153–9.PubMedGoogle Scholar
  86. Verma C, Eremin JM, Robins A, Bennett AJ, Cowley GP, El-Sheemy MA, et al. Abnormal T regulatory cells (Tregs: FOXP3+, CTLA-4+), myeloid-derived suppressor cells (MDSCs: monocytic, granulocytic) and polarised T helper cell profiles (Th1, Th2, Th17) in women with large and locally advanced breast cancers undergoing neoadjuvant chemotherapy (NAC) and surgery: failure of abolition of abnormal treg profile with treatment and correlation of treg levels with pathological response to NAC. J Transl Med. 2013;11:16.PubMedPubMed CentralGoogle Scholar
  87. Demaria S, Volm MD, Shapiro RL, Yee HT, Oratz R, Formenti SC, et al. Development of tumor-infiltrating lymphocytes in breast cancer after neoadjuvant paclitaxel chemotherapy. Clin Cancer Res. 2001;7:3025–30.PubMedGoogle Scholar
  88. Ercolini AM, Ladle BH, Manning EA, Pfannenstiel LW, Armstrong TD, Machiels JP, et al. Recruitment of latent pools of high-avidity CD8(+) T cells to the antitumor immune response. J Exp Med. 2005;201:1591–602.PubMedPubMed CentralGoogle Scholar
  89. Simpson TR, Li F, Montalvo-Ortiz W, Sepulveda MA, Bergerhoff K, Arce F, et al. Fc-dependent depletion of tumor-infiltrating regulatory T cells co-defines the efficacy of anti-CTLA-4 therapy against melanoma. J Exp Med. 2013;210:1695–710.PubMedPubMed CentralGoogle Scholar
  90. DeNardo DG, Brennan DJ, Rexhepaj E, Ruffell B, Shiao SL, Madden SF, et al. Leukocyte complexity predicts breast cancer survival and functionally regulates response to chemotherapy. Cancer Discov. 2011;1:54–67.PubMedPubMed CentralGoogle Scholar
  91. Alistar A, Chou J, Nagalla S, Black M, DAgostino R, Miller L. Dual roles for immune metagenes in breast cancer prognosis and therapy prediction. Genome Med. 2014;6:80.PubMedPubMed CentralGoogle Scholar
  92. Schalper KA, Velcheti V, Carvajal D, Wimberly H, Brown J, Pusztai L, et al. In situ tumor PD-L1 mRNA expression is associated with increased TILs and better outcome in breast carcinomas. Clin Cancer Res. 2014;20:2773–82.PubMedGoogle Scholar
  93. Muenst S, Schaerli AR, Gao F, Daster S, Trella E, Droeser RA, et al. Expression of programmed death ligand 1 (PD-L1) is associated with poor prognosis in human breast cancer. Breast Cancer Res Treat. 2014;146:15–24.PubMedPubMed CentralGoogle Scholar
  94. Muenst S, Soysal SD, Gao F, Obermann EC, Oertli D, Gillanders WE. The presence of programmed death 1 (PD-1)-positive tumor-infiltrating lymphocytes is associated with poor prognosis in human breast cancer. Breast Cancer Res Treat. 2013;139:667–76.PubMedGoogle Scholar
  95. Sun S, Fei X, Mao Y, Wang X, Garfield DH, Huang O, et al. PD-1(+) immune cell infiltration inversely correlates with survival of operable breast cancer patients. Cancer Immunol Immunother. 2014;63:395–406.PubMedGoogle Scholar
  96. Taube JM, Klein AP, Brahmer JR, Xu H, Pan X, Kim JH, et al. Association of PD-1, PD-1 ligands, and other features of the tumor immune microenvironment with response to anti-PD-1 therapy. Clin Cancer Res. 2014;20:5064.PubMedPubMed CentralGoogle Scholar
  97. Rahbar R, Lin A, Ghazarian M, Yau HL, Paramathas S, Lang PA, et al. B7-h4 expression by nonhematopoietic cells in the tumor microenvironment promotes antitumor immunity. Cancer Immunol Res. 2015;3:184–95.PubMedGoogle Scholar
  98. Sica GL, Choi IH, Zhu G, Tamada K, Wang SD, Tamura H, et al. B7-H4, a molecule of the B7 family, negatively regulates T cell immunity. Immunity. 2003;18:849–61.PubMedGoogle Scholar
  99. Zang X, Loke P, Kim J, Murphy K, Waitz R, Allison JP. B7x: a widely expressed B7 family member that inhibits T cell activation. Proc Natl Acad Sci U S A. 2003;100:10388–92.PubMedPubMed CentralGoogle Scholar
  100. Lu L, Xu X, Zhang B, Zhang R, Ji H, Wang X. Combined PD-1 blockade and GITR triggering induce a potent antitumor immunity in murine cancer models and synergizes with chemotherapeutic drugs. J Transl Med. 2014;12:36.PubMedPubMed CentralGoogle Scholar
  101. Lesterhuis WJ, Salmons J, Nowak AK, Rozali EN, Khong A, Dick IM, et al. Synergistic effect of CTLA-4 blockade and cancer chemotherapy in the induction of anti-tumor immunity. PLoS One. 2013;8:e61895.PubMedPubMed CentralGoogle Scholar
  102. Verbrugge I, Hagekyriakou J, Sharp LL, Galli M, West A, McLaughlin NM, et al. Radiotherapy increases the permissiveness of established mammary tumors to rejection by immunomodulatory antibodies. Cancer Res. 2012;72:3163–74.PubMedGoogle Scholar
  103. Twyman-Saint Victor C, Rech AJ, Maity A, Rengan R, Pauken KE, Stelekati E, et al. Radiation and dual checkpoint blockade activate non-redundant immune mechanisms in cancer. Nature. 2015;520:373–7.PubMedGoogle Scholar
  104. Liu L, Mayes PA, Eastman S, Shi H, Yadavilli S, Zhang T, et al. The BRAF and MEK inhibitors dabrafenib and trametinib: effects on immune function and in combination with immunomodulatory antibodies targeting PD-1, PD-L1, and CTLA-4. Clin Cancer Res. 2015;21:1639.PubMedGoogle Scholar
  105. Callahan MK, Masters G, Pratilas CA, Ariyan C, Katz J, Kitano S, et al. Paradoxical activation of T cells via augmented ERK signaling mediated by a RAF inhibitor. Cancer Immunol Res. 2014;2:70–9.PubMedGoogle Scholar
  106. Lee SJ, Myers L, Muralimohan G, Dai J, Qiao Y, Li Z, et al. 4-1BB and OX40 dual costimulation synergistically stimulate primary specific CD8 T cells for robust effector function. J Immunol. 2004;173:3002–12.PubMedGoogle Scholar
  107. Gray JC, French RR, James S, Al-Shamkhani A, Johnson PW, Glennie MJ. Optimising anti-tumour CD8 T-cell responses using combinations of immunomodulatory antibodies. Eur J Immunol. 2008;38:2499–511.PubMedGoogle Scholar
  108. Morales-Kastresana A, Sanmamed MF, Rodriguez I, Palazon A, Martinez-Forero I, Labiano S, et al. Combined immunostimulatory monoclonal antibodies extend survival in an aggressive transgenic hepatocellular carcinoma mouse model. Clin Cancer Res. 2013;19:6151–62.PubMedGoogle Scholar
  109. Cuadros C, Dominguez AL, Lollini PL, Croft M, Mittler RS, Borgstrom P, et al. Vaccination with dendritic cells pulsed with apoptotic tumors in combination with anti-OX40 and anti-4-1BB monoclonal antibodies induces T cell-mediated protective immunity in Her-2/neu transgenic mice. Int J Cancer. 2005;116:934–43.PubMedGoogle Scholar
  110. Greenman C, Stephens P, Smith R, Dalgliesh GL, Hunter C, Bignell G, et al. Patterns of somatic mutation in human cancer genomes. Nature. 2007;446:153–8.PubMedPubMed CentralGoogle Scholar
  111. Krauthammer M, Kong Y, Ha BH, Evans P, Bacchiocchi A, McCusker JP, et al. Exome sequencing identifies recurrent somatic RAC1 mutations in melanoma. Nat Genet. 2012;44:1006–14.PubMedPubMed CentralGoogle Scholar
  112. Wood LD, Parsons DW, Jones S, Lin J, Sjoblom T, Leary RJ, et al. The genomic landscapes of human breast and colorectal cancers. Science. 2007;318:1108–13.PubMedGoogle Scholar
  113. Marshall NA, Galvin KC, Corcoran AM, Boon L, Higgs R, Mills KH. Immunotherapy with PI3K inhibitor and Toll-like receptor agonist induces IFN-gamma+IL-17+ polyfunctional T cells that mediate rejection of murine tumors. Cancer Res. 2012;72:581–91.PubMedGoogle Scholar
  114. Dudley ME, Gross CA, Somerville RP, Hong Y, Schaub NP, Rosati SF, et al. Randomized selection design trial evaluating CD8+−enriched versus unselected tumor-infiltrating lymphocytes for adoptive cell therapy for patients with melanoma. J Clin Oncol. 2013;31:2152–9.PubMedPubMed CentralGoogle Scholar
  115. Chacon JA, Wu RC, Sukhumalchandra P, Molldrem JJ, Sarnaik A, Pilon-Thomas S, et al. Co-stimulation through 4-1BB/CD137 improves the expansion and function of CD8(+) melanoma tumor-infiltrating lymphocytes for adoptive T-cell therapy. PLoS One. 2013;8:e60031.PubMedPubMed CentralGoogle Scholar
  116. Kodumudi KN, Weber A, Sarnaik AA, Pilon-Thomas S. Blockade of myeloid-derived suppressor cells after induction of lymphopenia improves adoptive T cell therapy in a murine model of melanoma. J Immunol. 2012;189:5147–54.PubMedPubMed CentralGoogle Scholar
  117. Radvanyi LG, Bernatchez C, Zhang M, Fox PS, Miller P, Chacon J, et al. Specific lymphocyte subsets predict response to adoptive cell therapy using expanded autologous tumor-infiltrating lymphocytes in metastatic melanoma patients. Clin Cancer Res. 2012;18:6758–70.PubMedPubMed CentralGoogle Scholar
  118. Kershaw MH, Westwood JA, Darcy PK. Gene-engineered T cells for cancer therapy. Nat Rev Cancer. 2013;13:525–41.PubMedGoogle Scholar
  119. Maude SL, Frey N, Shaw PA, Aplenc R, Barrett DM, Bunin NJ, et al. Chimeric antigen receptor T cells for sustained remissions in leukemia. N Engl J Med. 2014;371:1507–17.PubMedPubMed CentralGoogle Scholar
  120. Koya RC, Mok S, Otte N, Blacketor KJ, Comin-Anduix B, Tumeh PC, et al. BRAF inhibitor vemurafenib improves the antitumor activity of adoptive cell immunotherapy. Cancer Res. 2012;72:3928–37.PubMedPubMed CentralGoogle Scholar
  121. John LB, Devaud C, Duong CP, Yong CS, Beavis PA, Haynes NM, et al. Anti-PD-1 antibody therapy potently enhances the eradication of established tumors by gene-modified T cells. Clin Cancer Res. 2013;19:5636–46.PubMedGoogle Scholar
  122. Ahmed N, Brawley VS, Hegde M, Robertson C, Ghazi A, Gerken C, et al. Human epidermal growth factor receptor 2 (HER2)-specific chimeric antigen receptor-modified T cells for the immunotherapy of HER2-positive sarcoma. J Clin Oncol. 2015;33:1688.PubMedPubMed CentralGoogle Scholar
  123. Ishikawa T, Adachi S, Okayama T, Kokura S, Mizushima K, Doi T, et al. Cytotoxic T lymphocyte-associated antigen 4 inhibition increases the antitumor activity of adoptive T-cell therapy when carried out with naive rather than differentiated T cells. Oncol Rep. 2015;33:2545.PubMedGoogle Scholar
  124. Salgado R, Denkert C, Demaria S, Sirtaine N, Klauschen F, Pruneri G, et al. The evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer: recommendations by an International TILs Working Group 2014. Ann Oncol. 2015;26:259–71.PubMedGoogle Scholar
  125. Cortazar P, Zhang L, Untch M, Mehta K, Costantino JP, Wolmark N, et al. Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis. Lancet. 2014;384:164–72.PubMedGoogle Scholar
  126. Ko HJ, Kim YJ, Kim YS, Chang WS, Ko SY, Chang SY, et al. A combination of chemoimmunotherapies can efficiently break self-tolerance and induce antitumor immunity in a tolerogenic murine tumor model. Cancer Res. 2007;67:7477–86.PubMedGoogle Scholar
  127. Fridlender ZG, Sun J, Singhal S, Kapoor V, Cheng G, Suzuki E, et al. Chemotherapy delivered after viral immunogene therapy augments antitumor efficacy via multiple immune-mediated mechanisms. Mol Ther. 2010;18:1947–59.PubMedPubMed CentralGoogle Scholar
  128. Suzuki E, Kapoor V, Jassar AS, Kaiser LR, Albelda SM. Gemcitabine selectively eliminates splenic Gr-1+/CD11b+ myeloid suppressor cells in tumor-bearing animals and enhances antitumor immune activity. Clin Cancer Res. 2005;11:6713–21.PubMedGoogle Scholar
  129. Schiavoni G, Sistigu A, Valentini M, Mattei F, Sestili P, Spadaro F, et al. Cyclophosphamide synergizes with type I interferons through systemic dendritic cell reactivation and induction of immunogenic tumor apoptosis. Cancer Res. 2011;71:768–78.PubMedGoogle Scholar
  130. Xu W, Cai J, Li S, Zhang H, Han J, Wen M, et al. Improving the in vivo persistence, distribution and function of cytotoxic T lymphocytes by inhibiting the tumor immunosuppressive microenvironment. Scand J Immunol. 2013;78:50–60.PubMedGoogle Scholar
  131. Umansky V, Sevko A. Overcoming immunosuppression in the melanoma microenvironment induced by chronic inflammation. Cancer Immunol Immunother. 2012;61:275–82.PubMedGoogle Scholar
  132. Zhang L, Dermawan K, Jin M, Liu R, Zheng H, Xu L, et al. Differential impairment of regulatory T cells rather than effector T cells by paclitaxel-based chemotherapy. Clin Immunol. 2008;129:219–29.PubMedGoogle Scholar
  133. Ma Y, Adjemian S, Mattarollo SR, Yamazaki T, Aymeric L, Yang H, et al. Anticancer chemotherapy-induced intratumoral recruitment and differentiation of antigen-presenting cells. Immunity. 2013;38:729–41.PubMedGoogle Scholar
  134. Alizadeh D, Trad M, Hanke NT, Larmonier CB, Janikashvili N, Bonnotte B, et al. Doxorubicin eliminates myeloid-derived suppressor cells and enhances the efficacy of adoptive T-cell transfer in breast cancer. Cancer Res. 2014;74:104–18.PubMedGoogle Scholar
  135. Tesniere A, Schlemmer F, Boige V, Kepp O, Martins I, Ghiringhelli F, et al. Immunogenic death of colon cancer cells treated with oxaliplatin. Oncogene. 2010;29:482–91.PubMedGoogle Scholar
  136. Kang TH, Mao CP, Lee SY, Chen A, Lee JH, Kim TW, et al. Chemotherapy acts as an adjuvant to convert the tumor microenvironment into a highly permissive state for vaccination-induced antitumor immunity. Cancer Res. 2013;73:2493–504.PubMedPubMed CentralGoogle Scholar
  137. Guo ZS, Hong JA, Irvine KR, Chen GA, Spiess PJ, Liu Y, et al. De novo induction of a cancer/testis antigen by 5-aza-2′-deoxycytidine augments adoptive immunotherapy in a murine tumor model. Cancer Res. 2006;66:1105–13.PubMedPubMed CentralGoogle Scholar
  138. Mikyskova R, Indrova M, Vlkova V, Bieblova J, Simova J, Parackova Z, et al. DNA demethylating agent 5-azacytidine inhibits myeloid-derived suppressor cells induced by tumor growth and cyclophosphamide treatment. J Leukoc Biol. 2014; in press.Google Scholar
  139. Hornychova H, Melichar B, Tomsova M, Mergancova J, Urminska H, Ryska A. Tumor-infiltrating lymphocytes predict response to neoadjuvant chemotherapy in patients with breast carcinoma. Cancer Invest. 2008;26:1024–31.PubMedGoogle Scholar
  140. Liu S, Lachapelle J, Leung S, Gao D, Foulkes WD, Nielsen TO. CD8+ lymphocyte infiltration is an independent favorable prognostic indicator in basal-like breast cancer. Breast Cancer Res. 2012;14:R48.PubMedPubMed CentralGoogle Scholar
  141. Yamaguchi R, Tanaka M, Yano A, Tse GM, Yamaguchi M, Koura K, et al. Tumor-infiltrating lymphocytes are important pathologic predictors for neoadjuvant chemotherapy in patients with breast cancer. Hum Pathol. 2012;43:1688–94.PubMedGoogle Scholar
  142. Ali HR, Provenzano E, Dawson SJ, Blows FM, Liu B, Shah M, et al. Association between CD8+ T-cell infiltration and breast cancer survival in 12,439 patients. Ann Oncol. 2014;25:1536–43.PubMedGoogle Scholar
  143. Nabholtz JM, Abrial C, Mouret-Reynier MA, Dauplat MM, Weber B, Gligorov J, et al. Multicentric neoadjuvant phase II study of panitumumab combined with an anthracycline/taxane-based chemotherapy in operable triple-negative breast cancer: identification of biologically defined signatures predicting treatment impact. Ann Oncol. 2014;25:1570–7.PubMedGoogle Scholar

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