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Special Issue: Immunity and Cancer

Immune-mediated mechanismsinfluencing the efficacy of anticancertherapiesSeth B. Coffelt and Karin E. de Visser

Division of Immunology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands

Feature Review

Conventional anticancer therapies, such as chemother-apy, radiotherapy, and targeted therapy, are designed tokill cancer cells. However, the efficacy of anticancertherapies is not only determined by their direct effectson cancer cells but also by off-target effects within thehost immune system. Cytotoxic treatment regimenselicit several changes in immune-related parametersincluding the composition, phenotype, and function ofimmune cells. Here we discuss the impact of innate andadaptive immune cells on the success of anticancertherapy. In this context we examine the opportunitiesto exploit host immune responses to boost tumor clear-ing, and highlight the challenges facing the treatment ofadvanced metastatic disease.

Then and now: the link between the immune systemand anticancer therapiesThe relationship between anticancer therapies and theimmune system is as old as the invention of anticancertherapies themselves. After the use of mustard gas in thetrenches of World War I, a seminal observation was madethat some exposed soldiers displayed severe loss of bonemarrow and lymph-node cells [1]. This observation thenspurred the idea that the antiproliferative capacity ofmustard gas may also slow the growth of cancer cells.Experiments carried out in mice transplanted with lym-phoid tumors were convincing enough to treat a lymphomapatient [2], and these events initiated the standardizedtreatment of cancer patients with chemotherapy [3,4].

Fast-forward 100 years. The influence of immune cellson tumor progression and metastasis is well established[5], and an appreciation of the impact of the immunesystem during conventional anticancer therapy treatmentis growing. Recent seminal advances indicate that immunecells can shape the outcome of various anticancer thera-pies. As such, immune cells and their molecular mediatorshave evolved into bona fide targets of therapeutic manipu-lation in cancer patients. The recent breakthrough of

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� 2015 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.it.2015.02.006

Corresponding authors: Coffelt, S.B. ([email protected]);de Visser, K.E. ([email protected]).Keywords: cancer; inflammation; adaptive immune cells; anticancer therapy; mousemodel.

198 Trends in Immunology, April 2015, Vol. 36, No. 4

immunotherapeutics that inhibit negative immune regu-latory pathways, such as anti-CTLA4 (cytotoxic T lympho-cyte-associated protein 4) and anti-PD1, has initiated anew era in the treatment of cancer [6]. In parallel, immu-nomodulatory strategies aimed at dampening protumorfunctions of immune cells are currently being tested incancer patients [7]. Immune cells also function as reliablebiomarkers because their abundance or activation statusoften predicts how well patients respond to a particulartreatment regimen. We review these novel experimentaland clinical insights, highlighting potential implicationsfor the development of synergistic therapies designed tocombat primary tumors and, more importantly, metastaticdisease.

The pros and cons of experimental mouse modelsResearch questions aimed at understanding the role ofimmune cells during anticancer therapy require modelsthat mirror the complex interactions between the immunesystem and diverse forms of human cancers. Transplant-able cancer cell line models and carcinogen-induced cancermodels are the most frequently used for these purposes.However, studies are gaining ground in genetically engi-neered mouse models (GEMMs; see Glossary) that spon-taneously develop specific cancer types as a consequence ofgermline or somatic mutations in discrete cell types. Thereare key differences between cancer cell line inoculationmodels and GEMMs of cancer (Box 1). In GEMMs, normalcells are transformed in situ resulting in the developmentof spontaneous tumors that faithfully recapitulate eachstage of cancer progression – from tumor initiation toadvanced disease, and in some models also metastasis.These spontaneous tumors develop in their natural micro-environment, and share the genetic heterogeneity andhistopathology of human tumors. In stark contrast, trans-plantable models rely on the inoculation of large numbersof selected, homogenous cancer cells grown in 2D. Thetissue of tumor origin and location of injection are oftendisparate in transplantable models, with subcutaneousinjection being the most common site of implantation.Moreover, these tumor cell line inoculation models donot mimic the multistep progression of de novo tumors,and the speed of tumor outgrowth is very fast. Uponinoculation, a large proportion of the cancer cells die,which can prime antitumor immune responses in an

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Glossary

Alkylating agents: a class of chemotherapy drugs that directly damage DNA by

substituting alkyl groups for hydrogen atoms on DNA, causing the formation of

crosslinks within DNA chains and thereby resulting in cell death. Examples of

alkylating agents are cyclophosphamide and melphalan.

Anthracyclines: a class of chemotherapy drugs that are widely used to treat

many different types of cancer. Anthracyclines prevent cell division by

disrupting the structure of the DNA via several mechanisms. Examples of

anthracyclines are doxorubicin and daunorubicin.

BrafV600E;Tyr::CreERT2 or BrafV600E;PtenF/F;Tyr::CreERT2 mouse tumor models:

a conditional GEMM of melanoma driven by an activated form of BRAF and

loss of PTEN under the control of the tyrosinase (Tyr) promoter. Tumors are

induced by topical administration of tamoxifen to the skin, and therefore the

timing of tumor development can be initiated as desired.

C3(1)-Tag mouse tumor model: a GEMM model in which SV40 large T antigen

(Tag) expression under the control of the 50 flanking region of the C3(1)

component of the rat prostate steroid-binding protein drives tumor develop-

ment. In females, mammary ductal epithelium is transformed leading to

invasive mammary tumors that resemble human ductal carcinoma in situ

(DCIS). Male mice develop phenotypic changes in the prostate that progress

into invasive carcinoma.

Genetically engineered mouse models (GEMMs) for cancer: in GEMMs for cancer,

normal cells are transformed in situ as a consequence of germline or somatic

mutations in specific cell types, resulting in the development of spontaneous

tumors that faithfully recapitulate each stage of cancer progression – from tumor

initiation to advanced disease and in some models also metastasis.

K14-HPV16 mouse tumor model: a GEMM for de novo squamous carcinogen-

esis of the skin. These mice transgenically express the early region genes of the

human papilloma-virus type 16 (HPV16) under control of the human keratin

14 promoter/enhancer. Cervical tumors can also be induced in these mice by

administration of low-dose estrogen, hence K14-HPV16/E2.

K14cre;Cdh1F/F;Trp53F/F mouse tumor model: a conditional GEMM for invasive

lobular breast cancer. These mice transgenically express Cre recombinase

under the control of the human keratin 14 promoter. In these mice, the alleles

encoding E-cadherin and p53 are homozygously floxed. As a consequence,

mammary and skin epithelial cells stochastically lose E-cadherin and p53,

which induces the formation of tumors in these tissues.

KitV558/+ mouse tumor model: these mice carry a gain-of-function point

mutation on one allele of the Kit receptor gene predisposing them to

spontaneous gastrointestinal stromal tumor (GIST) development.

Metastatic cascade: cancer dissemination is a multistep process, consisting of

the following steps: local invasion at the primary tumor site, intravasation and

survival into the circulation, extravasation and survival at distant sites,

adaptation to a foreign microenvironment, and outgrowth of a metastasis.

During every step of the metastatic cascade, cancer cells encounter normal

host cells, such as immune cells. Interactions between disseminated cancer

cells and normal host cells largely dictate the success of metastasis formation.

MMTV-Neu mouse tumor model: a GEMM for HER2+ breast cancer in which

wild type rat ERBB2 expression is driven by the mouse mammary tumor virus

(MMTV) promoter, which is only active in the mammary gland. These mice

develop multifocal tumors in all 10 mammary glands, as well as spontaneous

lung metastases in most mice. They are maintained on the FVB/n background.

MMTV-NeuT mouse tumor model: similar to MMTV-Neu mice, this GEMM

represents another model for HER2+ breast cancer. However, a mutated form

of the rat proto-oncogene, ERBB2, is expressed under control of the MMTV

promoter in this case. Multifocal tumors also arise in these mice from all five

pairs of mammary glands and they develop spontaneous lung metastases.

These mice are usually maintained on the BALB/c background.

MMTV-PyMT mouse tumor model: a GEMM for mammary tumorigenesis.

These mice transgenically express the polyomavirus middle T antigen (PyMT)

oncogene under the control of the MMTV promoter. These mice develop

multifocal tumors in all 10 mammary glands, as well as spontaneous lung

metastases.

Patient-derived xenograft (PDX) tumor models: fresh tumor tissue from

patients undergoing surgery is implanted into immunodeficient mice (usually

NOD/SCID/Il2rg, otherwise known as NSG, mice) directly or following

enzymatic digestion. Tumors can be grafted subcutaneously or orthotopically.

PDX tumors are serially passaged in additional mice.

Probasin-Cre4;PtenF/F mouse tumor model: a conditional GEMM for Pten-

deficient prostate cancer, where loss of Pten expression is driven by the

probasin promoter. These mice develop prostatic intraepithelial neoplasia

(PIN) lesions that progress to invasive adenocarcinomas.

Platinum compounds: a class of platinum-containing chemotherapy drugs that

bind to and crosslink DNA, resulting in apoptosis. Examples of platinum

compounds are cisplatin, carboplatin, and oxaliplatin.

RIP1-Tag5 mouse tumor model: a conditional GEMM of pancreatic cancer, in

which the rat insulin gene promoter drives sporadic expression of SV40 large T

antigen (Tag) in a subset of pancreatic b cells. Unlike RIP-Tag2 mice that are

systemically tolerant to SV40 large T antigen, these mice develop an

autoimmune response against the oncogene-expressing beta cells.

Taxanes: a class of chemotherapy drugs that disrupt microtubule function, and

thus inhibit mitosis. Taxanes were first derived from plants of the yew tree.

Examples of taxanes are paclitaxel and docetaxel.

Tumor microenvironment: in addition to cancer cells, many ‘normal’ cells are

recruited to and activated in tumors. The tumor microenvironment is

composed of many different types of immune cells, fibroblasts (referred to

as cancer-associated fibroblasts), endothelial cells and other cells that normally

reside in the organ afflicted by the tumor (e.g., adipocytes in breast cancer),

soluble mediators, and the extracellular matrix (ECM). Throughout cancer

progression there is extensive crosstalk between normal cells, soluble

mediators, and cancer cells. These interactions largely dictate tumor behavior

and therapy response. Each tumor type and each tumor stage is characterized

by a unique tumor microenvironment.

Feature Review Trends in Immunology April 2015, Vol. 36, No. 4

unphysiological manner. Importantly, comparative studieshave shown that immune cell behavior and tumor responseto anticancer therapies differs between transplantablecell lines derived from GEMMs and the original GEMM[8–10]. Similarly, other studies indicate that GEMMs usedin preclinical studies may be better predictors of clinicaltrials than transplantable models [11]. Xenografted humancancer cells established from cell lines or fresh patientmaterial (patient-derived xenograft, PDX) in immunocom-promised mice are other frequently used models. While itmay be argued that PDX models are the best representationof human disease from a cancer genetics or drug responsepoint-of-view, these models exclude the participation of theadaptive immune system in cancer progression and anti-cancer therapy response. Therefore, they cannot predict thefull breadth of drug response in immunocompetent humans.These issues, as well as other advantages and disadvan-tages, various strategies to refine these models, and theirsuitability for preclinical studies, have been extensivelydiscussed elsewhere [12–16].

The influence of the immune system onchemotherapeutic efficacyVarious types of chemotherapy drugs exist which killcancer cells via different mechanisms (Figure 1). Cytotoxicdrugs can eliminate cancer cells by inhibition of DNAreplication, chemical damaging of DNA, inhibition of thefunction of crucial enzymes required for DNA synthesis, orprevention of mitosis. Drug-induced cancer cell death, aswell as off-target effects of chemotherapy, elicits severalsystemic and intratumoral changes in the host immunesystem. In turn, the efficacy of chemotherapeutic drugs isinfluenced by the interplay between tumor and immunecomponents. These mechanisms are outlined below forboth innate and adaptive immune cells.

Innate immune cells

The microenvironment of solid tumors consists of multiplecell types, including many immune cell populations thatparticipate in and regulate tumorigenesis and metastasis[17,18] (Box 2). Tumor-associated macrophages (TAMs)represent one of the most extensively studied innate im-mune cell populations in chemotherapy response. Re-search spanning over the past three decades has shownthat TAMs interfere with or augment the therapeuticactivity of several types of chemotherapy, and their rolein these processes has been reviewed recently [19,20]. Oneof the first studies addressing the impact of macrophageson chemo-responsiveness showed that doxorubicin

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Box 1. Comparison of mouse models used in anticancer therapy research

In immune-related anticancer therapy research, three types of mouse

models are commonly used, including cancer cell line-based

transplantable, carcinogen-induced and genetically engineered

mouse models (GEMMs) of cancer. Several advantages and dis-

advantages are presented for each model (Table I). Transplantable

models rely on the injection of in vitro cultured cancer cells into

recipient immunocompetent or immunodeficient mice, and this is

usually done subcutaneously. In carcinogen-induced models, chemi-

cal carcinogens are injected into or topically applied to mice to induce

tumors, where the type and location of carcinogen dictates the

location of the tumors formed. For example, topical application of

DMBA/TPA results in skin carcinogenesis, and injection of methyl-

cholanthrene (MCA) intramuscularly results in fibrosarcomas. One

caveat of this model is that tumors do not always form in carcinogen-

injected mice. By their nature, carcinogen-induced tumors represent

only a small fraction of human cancers. GEMMs are driven by specific

mutations in oncogenes or tumor suppressors. The first generation

GEMMs were developed in the 1980s and depended on germline

introduction of oncogenes whose constitutive expression could be

spatially controlled by tissue-specific promoters. Many of the

experimental studies addressing the causal link between immune

system, tumorigenesis and therapy efficacy have used these so-called

‘onco-mice’. An example is the MMTV-PyMT mouse model for breast

cancer, in which the MMTV promoter drives a viral oncogene,

polyomavirus middle T antigen. MMTV-PyMT mice develop multi-

focal tumors in all five pairs of mammary glands, as well as

spontaneous lung metastases [193]. To overcome some of the

drawbacks of the first-generation GEMMs – such as embryonic

lethality or the development of tumors outside the tissue of

interest – methods have been developed to conditionally induce somatic

mutations in a tissue-specific and/or time-dependent manner. An

example of a second-generation GEMM is the K14cre;Cdh1F/F;Trp53F/F

model in which stochastic Cre recombinase-mediated loss of the floxed

genes encoding for E-cadherin and p53 results in the formation

of mammary tumors resembling human invasive lobular breast

cancer [83].

Table I. Comparison of different types of cancer mouse models.

Characteristics Transplantable (cell line)

models

Carcinogen-induced models Genetically

engineered mouse

models (GEMMs)

Time to tumor progression 0–4 weeks 2–12 months 2–24 months

Penetrance High Variable Model-dependent

Incidence of multifocal tumors Low High High

Relevance of genetic alterations to human disease High (culturing artifacts

also present)

Usually high High

Genetic heterogeneity similar to human cancers Low Model-dependent Intermediate

Histopathologic similarity to human cancers,

including appropriate stromal microenvironment

Low Model-dependent High

Tumors formed by transformation of normal cells No Yes Yes

Controlled timing of tumor initiation High Partial Model-dependent

Tumors arise in natural, anatomically correct

microenvironment

No Yes Yes

Pre-malignant phase and progression-dependent

interplay with host immune system

No Yes Yes

Flexibility of model manipulation (either cancer or

stromal cells) in a time/cost-effective manner

High Intermediate Low

Type of inflammation Acute Carcinogen-induced Chronic

Incidence of metastasis Model-dependent Low Model-dependent

Spectrum of visceral metastasis Model-dependent Low Model-dependent

Ease of surgical resection High (depending on location) Location-dependent Typically low

Predictive value of conventional and immune-based

combinatorial therapies

Frequently low Unknown Potentially high


enhances the tumoricidal properties of TAMs in micetransplanted with leukemia or lymphomas, and thatmacrophage-inactivating agents reduce the efficacy ofdoxorubicin. Interestingly, these observations were chemo-therapy-specific because daunorubicin, another anthracy-cline, together with TAM depletion failed to exhibit anysynergism [21].

More recent literature pertaining to TAMs and solidepithelial malignancies indicates a sinister role for thesecells in limiting chemotherapy efficacy. Increased TAMabundance and low CD8+ T cell abundance in humanbreast tumors is associated with poor response to neoad-juvant chemotherapy [22]. Paclitaxel treatment of mam-mary tumor-bearing mice harboring an MMTV (mousemammary tumor virus)-PyMT (polyomavirus middle Tantigen) transgene increases TAM infiltration into tumors.These cells counteract chemotherapy efficacy via several

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mechanisms, including inhibition of antitumor CD8+ T cellresponses via interleukin 10 (IL10)-mediated suppressionof dendritic cells [22,23], as well as secretion of chemopro-tective survival signals such as cathepsins [24]. Interest-ingly, splenic macrophages have also been implicated inconferring systemic resistance to cisplatin in subcutaneouscell line models via secretion of lysophospholipids thatalter the DNA damage response [25].

In this regard, various strategies to deplete TAMs orneutralize their mediators have been used to enhancechemotherapy efficacy in preclinical tumor models. Themost common strategy used to date involves the inhibitionof colony stimulating factor 1 (CSF1)–CSF receptor(CSF1R) signaling because these molecules are requiredfor macrophage differentiation and maturation[26,27]. Paclitaxel treatment in combination with a CSF1Rinhibitor reduces tumor growth in both MMTV-PyMT and

ChemotherapyAn�metabolites • 5-Fluorouracil (5-FU) • Methotrexate • Gemcitabine

Alkyla�ng agents • Cyclophosphamide • Dacarbazine• Melphalan• Trabectedin

Anthracyclines• Doxorubicin • Daunorubicin• Mitoxantrone

Pla�num compounds • Cispla�n• Oxalipla�n

Taxanes• Paclitaxel • Docetaxel

Topoisomerase inhibitors• Irinotecan• Etoposide

Targeted therapies• AZD8055 (mTOR)• Cetuximab (EGFR)• Dabrafenib (BRAF)• Dasa�nib (BCR-ABL, cKIT, SRC)• Ima�nib (BCR-ABL, cKIT)• Lapa�nib (EGFR, ERBB2/HER2)• PLX4720 (BRAF) • Rapamycin (mTOR)• Rituximab (CD20) • Ruxoli�nib (JAK1 and 2)• Temsirolimus (mTOR)• Trastuzumab (ERBB2/HER2)• Vemurafenib (BRAF)

Radiotherapy • Single high dose • Frac�onated

Immunomodulatory agentsInnate immune cells • AMD3100 (CXCR4) • AMG820 (CSF1R) • AZD8309 (CXCR2) • BLZ945 (CSF1R) • Carlumab (CCL2)• GSK1325756 (CXCR2) • IMC-CS4 (CSF1R) • PLX3397 (cKIT, CSF1R, FLT3)• RG7155 (CSF1R) • SB-656933 (CXCR2) • SCH527123 (CXCR2) • S-265610 (CXCR2) • Trabectedin

Adap�ve immune cells • AMD3100 (CXCR4) • AZD8055 (mTOR)• Basiliximab (CD25)• Blinatumomab (CD3, CD19)• BMS-663513 (CD137) • CP-870,893 (CD40) • Dacetuzmumab (CD40)• Daclizumab (CD25)• Denileukin di�itox (CD25)• Lucatumumab (CD40)• Rapamycin (mTOR)• Rituximab (CD20) • Temsirolimus (mTOR)

Cancer cell

Stromal cell

Checkpoint inhibitors• AMP-224 (PD1) • Ipilimumab (CTLA4) • MPDL3280A (PDL1) • Nivolumab (PD1) • Pembrolizumab (PD1)

Vascular-targe�ng agents An�-angiogenic agents• Bevacizumab (VEGFA)• DC101 (mVEGFR2) • Nesvacumab (ANGPT2)• Suni�nib (VEGFRs, PDGFRs, FLT3, CSF1R)• Sorafenib (VEGFRs, RAF, PDGFRs, cKIT)• Trebananib (ANGPT1 and 2)

Vascular damaging agents • Combretasta�n A-4 phosphate

TRENDS in Immunology

Figure 1. Categories of anticancer therapies and their targets. One of the first anticancer therapies, chemotherapy, was designed to target highly proliferating cancer cells,

but over the past few decades the arsenal of anticancer weapons has increased and now also includes stromal cell targets within the tumor microenvironment. Currently,

cancer cells and stromal cells are targeted with chemotherapy, radiotherapy, targeted therapy – specific for oncogenes or hyperactive signaling pathways – vascular-

targeting agents, T cell checkpoint inhibitors, and immunomodulatory agents, among others. Examples are given of each anticancer therapy category based on their

mention in the text, and the list is not inclusive of every anticancer therapy being tested in preclinical or clinical trials. Because tumors are a collection of cancer and stromal

cells, targeted cells responding to any given anticancer therapy through secretion of molecules or death may also affect their cellular neighbors within the tumor

microenvironment indirectly.


C3(1)-Tag mice [22,23] – a conditional GEMM driven bySV40 large-T antigen in mammary epithelial cells [28]. Ofnote, this therapy combination also decreases spontaneouslung metastasis in MMTV-PyMT mice, while neither pac-litaxel nor CSF1R inhibitor alone affects metastasis for-mation [22,23]. Similarly, when paclitaxel is used with aninhibitor blocking TAM-derived cathepsins, the total lungmetastatic burden of MMTV-PyMT mice is lowered [24]. Inorthotopic pancreatic tumor transplants, blockade ofTAMs and monocytes via CSF1R or CCR2 inhibitors syner-gizes with gemcitabine and paclitaxel to slow cancergrowth and reduce peritoneal metastasis [29]. Similarlyto TAMs in MMTV-PyMT mammary tumors [22], TAMsfrom these pancreatic tumor transplants suppress CD8+ Tcell activation to foster chemoresistance [29]. Studies inxenograft tumor models using human breast cancer celllines have also shown that CSF1 neutralization togetherwith a triple chemotherapy modality (cyclophosphamide,methotrexate, and 5-FU) reverses chemoresistance[30]. Another chemotherapeutic drug, trabectedin, induces

apoptosis specifically in monocytes and macrophages, andthis forms a key component of its antitumor activity [31].

Although these studies reveal that macrophages coun-teract the efficacy of various chemotherapeutics, and sug-gest that the synergism between TAM inhibition andchemotherapy may be beneficial for several types of cancer,it will be important for future experiments to focus onresistance mechanisms within the immune system. Thestudies above combining chemotherapy with TAM block-ade show only a transient effect on tumor growth; thesetumors do not regress and they eventually grow out[22,23,29,30]. The inherent flexibility and redundancy ofthe immune system lends itself to potentially deleteriousfeedback mechanisms in which the functions of a depletedpopulation are reinstated by another population. One suchmechanism is known to occur in cervical tumors of K14-HPV/E2 mice, where genetic inhibition of matrix metallo-protease 9 (MMP9)-expressing TAMs results in a compen-satory neutrophil influx that restores MMP9 levels,angiogenesis, and tumor progression [32]. Similarly,

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Box 2. Immune complexity in tumor-bearing hosts

The immune system has long been postulated to protect against

cancer and metastatic spread; however, tumors exploit several

strategies to successfully evade destruction by the immune system.

Cancer cells hijack the immune system for their own benefit,

allowing themselves to escape from immune attack, maintain

limitless proliferation, survive under dire circumstances, and spread

to distant organs. As such, immune cells and their inflammatory

mediators can create a hospitable microenvironment that is

favorable for cancer outgrowth [194].

Immune cells and their mediators are abundantly present in the

microenvironment of (disseminated) cancer cells. The exact nature

of the tumor-induced local and systemic immune alterations is

dictated by the genetic make-up of the tumor (i.e., type of

oncogenes/loss of tumor suppressors, mutational load), tumor type

(tissue of origin and etiology), tumor stage, therapy history, and age

of the patient.

Macrophages and neutrophils make up a significant proportion of

the inflammatory infiltrate in many tumors, and their accumulation

in cancer patients has been associated with poor prognosis

[22,195,196]. Experimental studies have confirmed protumor and

prometastatic functions for these tumor-associated myeloid cells

[197]. Another type of tumor-associated immune cell that has

gained considerable recent attention is the myeloid-derived sup-

pressor cell (MDSC) [51,52]. MDSCs represent a heterogeneous

group of immature CD11b+Gr1+ cells that include precursors of

macrophages, granulocytes, and dendritic cells at different stages of

their differentiation, and they are defined by their functional ability

to suppress T cell proliferation. Tumor-derived mediators promote

aberrant differentiation of myeloid lineage cells, resulting in

accumulation of MDSCs in the circulation and lymphoid organs.

MDSCs are potent immunosuppressive and proangiogenic cells,

and their accumulation in the circulation of solid cancer patients has

been linked with disease progression and metastasis [198–200].

Alongside myeloid cells, adaptive immune cells are frequently

found in tumors. Their role in tumorigenesis is rather paradoxical

[201]. Whereas CD8+ T cells potentially recognize and kill tumor

cells, CD4+ T cells, Tregs, B cells, and gd T cells play a more sinister

role in tumor biology [49,64,65,78,202]. In tumor-bearing hosts,

crosstalk between adaptive and innate immune cells fosters

disease progression. Tumor-associated myeloid cells frequently

suppress CD8+ T cells and induce Tregs while, at the same time,

cells of the adaptive immune system, notably B lymphocytes, CD4+

T cells, and gd T cells, can actually contribute to the expansion and

protumor polarization of myeloid cells in tumor-bearing hosts

[49,64,65,78,202].

Box 3. Immune cell polarization

As normal epithelial cells make the transition to cancer cells, they

induce the aberrant expression of molecules whose concentration is

unphysiological, or molecules that may be entirely new to a

particular tumor-originating location. Immune cells respond to

these mutation-driven cues both locally and systemically, and the

resulting effect is a skewing of their phenotype and behavior. In

addition to cancer cell-derived factors, physiological aspects of the

tumor microenvironment, such as hypoxia and pH, and factors from

other cell types also educate immune cells. This alteration in

immune cell appearance and function is referred to as polarization.

For many years, researchers have used a binary nomenclature that

reflects extreme ends of immune cell polarization. As an example,

macrophages are often referred to as protumorigenic M2 TAMs or

antitumorigenic M1 TAMs. This has led to the misconception that

there are only two types of TAMs. Recent gene expression data from

several independent laboratories have discredited this oversimpli-

fied idea, showing that TAMs comprise several distinct populations

and share properties of both M1 and M2 cells [203–205]. In regards

to therapy, repolarization of immune cells from a protumorigenic to

a more antitumorigenic state is one strategy that may enhance the

efficacy of traditional anticancer therapies.


inhibition of TAMs via CSF1R in mammary tumor-transplanted mice induces a neutrophil-dependent in-crease in lung metastasis without affecting primary tumorgrowth [33]. The resistance mechanisms counteracting thesynergism between chemotherapy (or other anticancertherapies) and TAM blockade remain to be elucidated.

The CSF1 and CSF1R inhibitors utilized in the abovereports function by depleting the entire TAM population[22–24,29,30]. However, another promising strategy thatmay prevent resistance to TAM depletion is to switch thepolarization of TAMs from a protumorigenic phenotype to amore antitumorigenic phenotype (Box 3). This concept wasrecently demonstrated in a GEMM of glioblastoma [34] andan orthotopic pancreatic cancer model [35], where CSF1Rinhibitors reduce expression of immunosuppressive andproangiogenic genes and increase immunostimulatorygenes in TAMs. Overexpression of a molecule called histi-dine-rich glycoprotein (HRG) also repolarizes TAMs[36]. Resident TAMs in transplanted fibrosarcomas over-expressing HRG exhibit a more antitumorigenic, less an-giogenic phenotype than TAMs in control tumors. This

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phenotypic switching renders tumors more sensitive todoxorubicin by modulation of the tumor vasculature[36]. There is also evidence that type I interferons (IFNs)convert TAMs into tumor-antagonizing cells. TAMs engi-neered to express IFNa upregulate expression of dendriticcell markers in mammary tumors of MMTV-PyMT mice.As a consequence, these mice exhibit increased tumor-infiltrating effector CD8+ T cell frequencies, slower tumorgrowth, and reduced incidence of metastasis [37]. As such,the combination of chemotherapy together with drugs thatrepolarize TAMs may be exploited to achieve greater pa-tient responses and prevent resistance mechanisms withinthe immune system. Some chemotherapeutics skew thepolarization of macrophages directly [38], or indirectly viaregulating cancer cell secreted factors [39].

Intravital imaging of experimental tumor models hasprovided additional clues about the behavior of TAMs afterchemotherapy. In these studies, doxorubicin treatmentinduces infiltration of CCR2-expressing monocytes intonecrotic regions of MMTV-PyMT mammary tumors, wherethese cells control vascular permeability and facilitateregrowth of tumors through MMP9 expression [40]. Conse-quently, spontaneous and transplanted tumors grown inCcr2 or Mmp9 knockout mice acquire an increased sensi-tivity to doxorubicin [40]. These studies suggest that TAMscontrol drug delivery through regulating vessel function-ality and leakiness. In support of this notion, deletion ofproangiogenic molecules, such as vascular endothelialgrowth factor A (VEGFA) and placental growth factor(PlGF), in myeloid cells and bone marrow-derived cells,respectively, decreases vascular leakiness [36,41] andincreases the potency of cyclophosphamide on trans-planted tumors [41].

Similarly to TAMs, the role of tumor-associated neutro-phils in response to chemotherapy treatment is context-and tumor type-dependent. In athymic nude mice bearingE1A/Kras/Bcl-xL-transformed murine embryonic fibro-blast (MEF) tumors, the depletion of neutrophils usingthe Gr1 antibody impairs the anticancer effect of cyclo-phosphamide [42]. The Gr1 antibody binds to the granulo-cyte-specific antigen, Ly6G, as well as to the Ly6C antigen


that is expressed by both granulocytes and monocytes. It istherefore possible that Ly6C+ inflammatory monocytesmay also contribute to tumor control in this scenario.Neutrophil depletion via the more-specific anti-Ly6G anti-body also modestly impairs the anticancer effect of doxo-rubicin on various cancer cell lines transplanted intosyngeneic, immunocompetent mice [43].

By contrast, strategies to impede neutrophil recruit-ment into tumors augment the efficacy of chemotherapy.This has mainly been accomplished by inhibiting the CXCmotif chemokine receptor 2 (CXCR2), the receptor forCXCL1, 2, and 5, that is expressed on neutrophils andother granulocytes [44]. Treatment of human breast cancerxenografts with the combination of doxorubicin, cyclophos-phamide, and a CXCR2 inhibitor significantly slows tumorgrowth and metastasis compared to chemotherapy or theCXCR2 inhibitor alone [44]. Similarly, docetaxel syner-gizes with a CXCR2 inhibitor to prevent tumor progressionin a GEMM for Pten-deficient prostate cancer [45]. In theseprostate tumors, infiltrating neutrophils secrete IL1 recep-tor antagonist (ILRA) to counteract cancer cell senescenceand activate proliferation. Clinical support for a role ofneutrophils in chemotherapy response comes from obser-vations in a variety of cancer patients, such as breast andnon-small cell lung cancer patients, where chemotherapy-induced neutropenia is associated with better patientprognosis [46,47]. We and others have established a me-tastasis-promoting role for neutrophils in breast and mel-anoma models [48–50]. Therefore, targeting neutrophils ortheir mediators may synergize with chemotherapeutics tospecifically decrease metastasis.

Myeloid-derived suppressor cells (MDSCs) are a hetero-geneous group of immature and mature myeloid cells thatare predominated by neutrophils with T cell suppressivefunctions [51,52] (Box 2). In subcutaneous and orthotopiccell line transplantation models, gemcitabine, 5-fluoroura-cil (5-FU), and doxorubicin directly induce splenicCD11b+Gr1+ MDSC apoptosis [53–56]. This chemothera-py-induced MDSC death increases the activity of cytotoxicT cells and contributes to tumor control. However, gemci-tabine and 5-FU have also been reported to induce activa-tion of the NLRP3 (NOD-like receptor family, pyrindomain containing 3) inflammasome in MDSCs, whichlimits chemotherapy efficacy [56]. Other chemotherapeu-tics, such as irinotecan, enhance immunosuppression incolorectal cancer patients and in a carcinogen-inducedcolon cancer model via MDSC expansion [57]. These dataindicate that direct killing of MDSCs by chemotherapy canbe an additional off-target benefit of anticancer therapies,but caution should be exercised because these effects arechemotherapy- and tumor type-specific.

In a variety of transplantable and chemically inducedtumors, specific types of chemotherapy, such as oxalipla-tin and anthracyclines, trigger dendritic cell activationthrough the release of high-mobility group protein B1(HMGB1) and ATP by dying cancer cells [58–60]. Thisprocess is termed immunogenic cell death and itincreases the chemotherapy response of particular tumormodels through the induction of antitumor immunity. Formany years it was thought that dendritic cells in thetumor bed are immature and lack the ability to prime

cytotoxic T cells [61]. However, this notion was recentlychallenged. MMTV-PyMT mammary tumors as well asvarious transplantable tumors contain two main popula-tions of dendritic cells: CD11b+CD11c+CD103�BATF3�

and CD11b�CD11c+CD103+BATF3+ cells. The rareCD11b� dendritic cells have a superior ability to stimu-late cytotoxic T cells [23,62], although intravital imaginghas shown that dendritic cells are outcompeted by TAMSfor T cell interaction, lessening the likelihood of a robustantitumor immune response [62,63]. Antitumor immuni-ty can be reinstated by combining paclitaxel with TAMdepletion or neutralization of their tolerizing abilities(i.e., blocking IL10) [23]. While these studies report thatthe CD11b� dendritic cell subset is important for chemo-therapy response in MMTV-PyMT mammary tumors[23,62], the CD11b+ subset plays a greater role in chemo-therapy-induced immunogenic cell death of transplant-able models [43]. These data emphasize the diverseinfluence of dendritic cell subsets in chemotherapeuticefficacy. As such, it will be interesting to learn whetherthe predominant role of one dendritic cell subset is de-pendent on specific parameters, such as the class ofchemotherapy or type of tumor.

Adaptive immune cells

Similarly to innate immune cells, the role of T cells and Bcells in chemotherapy response is paradoxical becausethese cells may promote or prevent chemotherapeuticpotency. The behavior and function of adaptive immunecells is highly dependent on the class of chemotherapy usedand tumor type and stage. Emerging evidence over the pastfew years has challenged traditionally held views about theanticancer contributions of adaptive immune cells. Takeantibody-producing B cells, for instance. B cells facilitatesquamous cell carcinoma progression in K14-HPV16 micethrough antibody-mediated activation of Fc receptors(FcRs) on TAMs and mast cells, stimulating their proan-giogenic abilities [64,65]. B cells also promote squamouscell carcinoma in a carcinogen-induced cancer model[66]. In essence, B cells are viable targets in this tumortype. Indeed, the combination of platinum-based chemo-therapy or paclitaxel together with anti-CD20 antibodiesin orthotopic squamous cell carcinomas results in stasis ofestablished tumors, whereas chemotherapy or B cell de-pletion as single agents are completely ineffective [67]. Thesynergistic effect of chemotherapy and B cell depletion isdependent upon TAMs and CD8+ T cells because depletionof either population desensitizes tumors to the absence of Bcells and chemotherapy [67]. Taken together, these studiesindicate that inhibiting B cells in combination with che-motherapy may be highly effective for some tumor types.

Studies focused on the role of CD4+ T cells provideanother example of the complexity surrounding adaptiveimmune cells in chemotherapy response. One study hasshown that CD4+ T cells limit the ability of 5-FU to delaythe growth of subcutaneous thymoma cells [56]. 5-FU-exposed MDSCs stimulate CD4+ T cells to express IL17via IL1b; however, the mechanism by which IL17-produc-ing CD4+ T cells (otherwise known as Th17 cells) counter-act the anticancer efficacy of 5-FU is unclear. By contrast,IL17 is required for therapeutic efficacy of doxorubicin in a

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subcutaneous sarcoma model, and gd T cells, not CD4+ Tcells, are the source of IL17 in this scenario [68]. In MMTV-Neu mice – a model driven by wild type rat ERBB2 [69] –inhibition of the immunosuppressive enzyme indolamine2,3-dioxygenase (IDO) cooperates with cisplatin, cyclo-phosphamide, doxorubicin, and paclitaxel to retard tumorgrowth [70]. Interestingly, the antiproliferative effects ofIDO inhibition and paclitaxel are dependent on CD4+ Tcells because their depletion reverses the phenotype.MMTV-Neu cell lines injected into nude mice and treatedwith paclitaxel/IDO inhibitor phenocopy the CD4+ T celldepletion experiments in the de novo tumor model[70]. Conversely, CD4+ T cell depletion further delaysMMTV-Neu tumor growth in mice treated with doxorubi-cin and lapatinib – a small-molecule inhibitor of epidermalgrowth factor receptor (EGFR) and ERBB2 [71]. The im-portance of CD4+ cells following paclitaxel or doxorubicin,without the addition of IDO inhibitors or lapatinib,remains to be established in mammary tumor-bearingMMTV-Neu mice because these controls were not includedin either study [70,71]. Nonetheless, manipulation of Th17cells or other CD4+ T cell subsets may be a useful strategyto combat cancer growth and metastasis when used incombination with chemotherapy.

FOXP3 (forkhead box P3)-expressing regulatory T cells(Tregs) are the most notorious subpopulation of CD4+ Tcells, known for their ability to suppress antitumor im-mune responses [72]. As early as the 1980s it was recog-nized that Tregs in tumor-bearing mice are sensitive tocyclophosphamide [73], and more recent studies confirmedthis both in non-tumor- and tumor-bearing rodent models[74,75]. Depletion of Tregs using anti-CD25 antibodiessynergizes with other types of chemotherapy, includingplatinum-containing agents and etoposide, to reduce tu-mor growth in subcutaneous, transplantable models[76,77] as well as in a GEMM of lung adenocarcinoma[78]. The mechanism of synergy is most likely dependenton reactivation or reinfiltration of CD8+ T cells in tumors[77]; however, this remains to be confirmed.

Cytotoxic lymphocytes, including CD8+ T cells and nat-ural killer (NK) cells, have been reported to contribute tothe efficacy of particular chemotherapeutics. For example,depletion of NK cells abolishes the tumor-shrinking abilityof cyclophosphamide in tumor-bearing immunodeficientmice [42] and in an experimental melanoma metastasismodel [79]. CD8+ T cells with antitumor activity areunleashed upon treatment with a non-cytotoxic dose ofpaclitaxel in a spontaneous melanoma GEMM [80]. Simi-larly, CD8+ T cells contribute to cancer cell killing byimmunogenic cell death-inducing chemotherapeutics in avariety of transplantable and carcinogen-induced tumors[59,60,81]. Chemotherapy-driven immunogenic cell deathis not dependent on NK cells [60], but IFN signaling isimportant in this process [82].

Recently, we and others have challenged the currentlyheld dogma that cytotoxic CD8+ T lymphocytes are re-quired for tumor regression following specific chemothera-peutic agents [59,60,81]. For these studies we used twodifferent GEMMs of breast cancer: K14cre;Cdh1F/F;Trp53F/F mice, a model for invasive lobular breast cancerdriven by the stochastic loss of E-cadherin and p53 [83];

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and MMTV-NeuT mice, a model driven by a mutated formof the rat proto-oncogene ERBB2 [84]. We showed that theadaptive immune system is dispensable for response tooxaliplatin, doxorubicin, and cisplatin [85]. In line withthese data, depletion of CD8+ T cells in MMTV-PyMTmammary tumor-bearing mice fails to counteract the effi-cacy of paclitaxel [22,23], indicating that CD8+ T cells arealso dispensable in this experimental setting. In addition,CD8+ T cell depletion in combination with 5-FU treatmentof subcutaneous EL4 thymomas has no impact on tumorgrowth [56]. Taken together, these observations under-score the plasticity within the adaptive immune systemin response to different chemotherapeutic regimens, andsuggest that chemotherapy on its own may not be enoughto elicit antitumor immune responses in spontaneous epi-thelial tumors. Chemotherapy together with additionalanticancer agents, such as targeted therapies and immu-nosuppression inhibitors, may be required to fully reacti-vate cytotoxic T lymphocytes.

Influence of the immune system on radiotherapyApproximately 50–60% of all cancer patients are treatedwith radiotherapy and this regimen is given alone or incombination with chemotherapy and/or surgery[86,87]. Ionizing radiation induces DNA damage in theform of single-strand and double-strand breaks. As a con-sequence, several cellular events can occur, including DNAdamage recognition, cell cycle checkpoint activation, DNArepair, and/or apoptosis pathway induction. Dying cellsthen release stress proteins and other factors that can besensed by various immune cells to clear away cellulardebris, and initiate tumor recovery processes or secondaryanticancer responses. The participation of innate andadaptive immune cells in radiotherapy efficacy is discussedhere.

Innate immune cells

Several studies have reported increased recruitment ofmonocytes and macrophages following irradiation of tu-mor-bearing mice [88–93]; however, the similarity to ra-diotherapy-treated human tumors needs furtherinvestigation. In mice, radiotherapy-induced TAM infiltra-tion is mainly attributed to radiation-induced hypoxia andthe subsequent surge in hypoxia-regulated chemokines,such as CXCL12 [90,93]. Monocytes and macrophagesexpressing TIE2 (tyrosine kinase with immunoglobulin-like and EGF-like domains 2) – the receptor for angiopoie-tins 1 and 2 – are highly receptive to increased hypoxia andCXCL12 levels [90,93,94], and TIE2-expressing mono-cytes/macrophages have a profound ability to counteracthypoxia through the induction of angiogenesis [95]. As onemay predict, neutralizing CXCL12 or blocking its receptor,CXCR4, to prevent TAM accumulation further delays tu-mor progression when combined with radiotherapy inorthotopic syngeneic and xenograft models of glioblastoma[90], as well as in subcutaneous xenografts of lung carci-noma and syngeneic mammary tumors [93].

When TAMs are depleted in various subcutaneoustransplantable and xenograft models by targeting allCD11b+ cells, the inhibitory effects of radiation on tumorgrowth and angiogenesis are augmented [88,89]. This


result may be largely explained by the contribution ofMMP9 by CD11b+ cells that drives tumor regrowththrough vasculogenesis [88,89]. Similar results are ob-served using other strategies to block TAMs, includingCSF1R inhibitors in combination with fractionated irradi-ation in subcutaneous prostate tumors [91] and carrageen-an in transplantable models [92]. In B16 melanomas,however, the anticancer effect of a single local high radio-therapy dose is not affected by the absence of TAMs[96]. Depletion of Ly6G+ neutrophils and Ly6C+ inflamma-tory monocytes using Gr1 antibodies has no synergisticeffect with radiotherapy in subcutaneous human prostatetumors [89]. Conversely, depletion of neutrophilic MDSCspotentiates the efficacy of radiotherapy on subcutaneouscolon cancer cells [97], presumably through the alleviationof T cell suppression. Dendritic cells also play a role inradiosensitivity [58,96,98], but their activation by irradia-tion varies between transplantable models. For example,HMGB1-sensing Toll-like receptor 4-positive (TLR4+) den-dritic cells are required for radiotherapy efficacy in subcu-taneous thymomas [58]. By contrast, inhibition of HMGB1or knockout of downstream TLR4 signaling componentshas no effect on subcutaneous colon cancer cells followingradiotherapy [99]. In this model, radiotherapy response isdependent on type I IFN signaling in dendritic cells andthe adaptor protein STING (stimulator of IFN genes)[98,99]. Whether the discrepancy between the roles ofmyeloid cells in these studies is caused by the differencesin tumor model, or by the differences in radiotherapy doseand schedule, remains to be investigated. What is alsoabsent from this area of anticancer therapy research is howmyeloid cells respond to irradiated metastases in mousemodels.


Various independent research groups have reported thatradiosensitivity requires CD8+ T cells for tumor controlin transplantable models [58,96,99–101]. By contrast,CD4+ T cells may not be so important for this process[96]. Similar experiments in GEMMs are unavailable,and the importance of CD8+ T cells in radiotherapyresponse therefore remains unanswered in these models.Interestingly, one study showed that paclitaxel togetherwith irradiation actually increases mammary tumorgrowth and pulmonary metastases when compared toirradiation alone [100]. The same study switched to adifferent model system to explain this phenomenon.Experiments using dacarbazine and radiotherapy inB16 melanomas showed that the radiation-inducedpriming and activation of CD8+ T cells is blunted bychemotherapy [100]. Whether the combination of chemo-therapy and radiotherapy is detrimental to T cell prim-ing in cancer patients is unclear at present. Based onthese data, enhancement of CD8+ T cell activity incombination with radiotherapy may provide additionalbenefit to cancer patients. Indeed, mice bearing trans-plantable MMTV-PyMT mammary tumors depleted ofTregs and treated with irradiation survive longer thaneither animals treated with radiotherapy or Treg deple-tion alone [102]. Various immunotherapeutic strategiesto achieve these effects will be discussed below.

Contribution of immune cells to targeted therapyOver the past decade, targeted therapies have emergedfrom the identification of tumor type-specific driver muta-tions and hyperactive signaling pathways. Some examplesinclude BRAF (B-Raf proto-oncogene, serine/threonine ki-nase) inhibitors (vemurafenib) for melanomas, ERRB2inhibitors (trastuzumab) for HER2+ (ERBB2+) breast can-cer, and PARP (poly ADP-ribose polymerase) inhibitors(olaparib) for BRCA (breast cancer, early-onset)-deficientbreast and ovarian tumors (Figure 1). Many of these areperforming exceptionally well in the clinic. Nevertheless,the lack of durable responses is posing a major problem,highlighting the need to find synergistic therapies. Theimportance of stromal cells in mediating resistance totargeted therapies has recently been shown in vitro usingan extensive co-culture system. In this study, fibroblastswere reported to secrete hepatocyte growth factor (HGF)that activates the MET receptor (MET proto-oncogene,receptor tyrosine kinase) in melanoma cells and down-stream mitogen activated protein kinase (MAPK) andAKT (protein kinase B) signaling pathways to bypassthe dependency on BRAF [103]. We highlight the studiespertaining to immune cells and mouse models. A moreextensive discussion has been provided elsewhere [104].

When assessing the influence of innate and adaptiveimmune cells on the efficacy of targeted therapies, it isimportant to take into account the distinctive properties ofthe two types of targeted drugs: monoclonal antibodies andsmall-molecule inhibitors. Unlike small-molecule inhibi-tors, therapeutic antibodies can activate immune cells,such as macrophages, neutrophils, and natural killer cells,via binding to their FcRs, resulting in complement-depen-dent cytotoxicity (CDC) or antibody-dependent cellularcytotoxicity (ADCC) [105]. Thus, the actual working mech-anism of the targeted antibody drugs is in part dependenton their ability to trigger immune cell activation, whereasthis is not the case for small-molecule inhibitors.

Innate immune cells

In mice bearing melanoma cell lines derived from Braf-V600E;Tyr::CreERT2 tumors, the release of tumor necrosisfactor (TNF) by TAMs protects tumors from MEK (mito-gen-activated protein kinase kinase 1; also known asMAP2K1) inhibitor-induced cell death [106]. This resis-tance mechanism can be overcome by combining MEKinhibitors with an inhibitor of nuclear factor kB (NF-kB)signaling to prevent TAM accumulation and TNF secretionin tumors. Interestingly, TNF expression is independent ofthe state of TAM polarization in this model because allcultured macrophages expressed TNF regardless of thestimuli used in vitro to skew their polarization [106]. Bycontrast, TAM polarization may be important for the re-sponse to targeted therapies in other cancer types and caneven result in adverse effects. Imatinib treatment of tu-mor-bearing KitV558/+ mice – which carry a gain-of-functionpoint mutation on one allele of the Kit receptor genepredisposing them to spontaneous gastrointestinal stro-mal tumor (GIST) development [107] – has been shown torepolarize TAMs from their normal antitumorigenic, T cellstimulating phenotype to a more protumorigenic pheno-type [108]. However, the consequence of TAM skewing by

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imatinib, whether this is beneficial or detrimental fortumor progression, remains untested.

Numerous studies have shown that FcR expression onTAMs and neutrophils is required for the response toantibody-based targeted therapies through ADCC. Usingvarious transplantable models in knockout mice that lackone or more FcRs, tumor regression mediated by rituxi-mab, anti-CTLA4, trastuzumab, and other anti-ERBB2antibodies is reversed [109–115]. A lymphoma patientstudy showing that high TAM infiltration correlates withimproved prognosis after a rituximab-containing regimen,but worsened prognosis without rituximab, supports theseobservations [116]. These data suggest that whereas highnumbers of TAMs serve as an indicator of poor diseaseoutcome in untreated, chemo- or radiotherapy-treatedpatients, they may predict good disease outcome inpatients treated with targeted antibody drugs. Of note,however, FcR activation on TAMs and mast cells by en-dogenous antibodies promotes squamous cell carcinomaprogression and protumorigenic myeloid cell polarizationin the K14-HPV16 model [65]. Similarly, the therapeuticantibody targeting EGFR, cetuximab, induces an immu-nosuppressive phenotype in human monocytes culturedwith colon cancer cell lines in vitro [117]. These datasuggest that the importance of FcR expression on myeloidcells in regulating therapeutic antibody response may becontext-, drug-, and model-dependent.

It has been reported that the efficacy of anti-ERBB2antibodies is also dependent on HMGB1 and TLR signaling[110], suggesting that the mechanism of targeted therapy-induced tumor regression may be similar to immunogeniccell death processes. However, the addition of doxorubicin,an immunogenic cell death-inducing chemotherapy, toanti-ERBB2 treatment counteracts the effects of singleagent anti-ERBB2 and fails to augment the rejection ofestablished mammary tumors. Why the combination of twoimmunogenic cell death inducers fails to synergize remainsa mystery. Paclitaxel, by contrast, boosts the effects of anti-ERBB2 treatment and this combination results in tumorrejection in 100% of mice [110]. These data underscore theimportance of optimally matching targeted therapy withchemotherapeutic agents.

There is evidence from preclinical models that targetingthe JAK/STAT pathway counteracts immunosuppressionand controls cancer progression. For example, Pten-defi-cient prostate tumors from Probasin-Cre4;PtenF/F miceexhibit activation of the JAK2 (janus kinase 2)/STAT3(signal transducer and activator of transcription 3) path-way that mediates a MDSC-driven immunosuppressiveenvironment. Genetic deletion of Stat3 in prostate epithe-lial cells or treatment of prostate tumors with a JAK2inhibitor in combination with docetaxel prevents MDSCrecruitment to tumors and slows tumor growth [118]. Inaddition, JAK2/STAT3 inhibition in mice bearing subcuta-neous sarcomas that lack STAT3 activation modulatesMDSC and dendritic cell proportions as well as theiractivity to reinstate antitumor immunity [119]. BecauseJAK/STAT inhibition directly affects immune cell abun-dance and phenotype in some models, it is tempting tospeculate about the implications beyond this study.Targeted therapies that take out two birds with one

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stone – cancer cells and immunosuppressive myeloidcells – could result in more positive outcomes than whentwo distinct anticancer therapies are used simultaneously.


Elegant proof-of-principle experiments performed in trans-genic mouse models, where targeted therapy is emulatedby switching off an oncogene-driving mutation (i.e., MYC)during tumor development, have shown that T cells medi-ate tumor clearance through the killing of both cancer cellsand endothelial cells [120,121]. These studies establishedthe importance of T cells in mouse models that mimictargeted therapies, and there are other reports demon-strating the importance of adaptive immune cells usingspecific targeted therapies. Treatment of melanomapatients with BRAF inhibitors increases infiltration ofCD4+ and CD8+ T cells into tumors, and this correlateswith reduced tumor size [122]. In experimental melanomametastasis models, NK cells mediate the antitumor effectsof a BRAF inhibitor, while CD4+ and CD8+ T cells aredispensable [123]. By contrast, CD8+ T cells are requiredfor the response of BRAF inhibitors in transplantablemelanoma models [124,125]. CD4+ T cells, but not CD8+

T cells, mediate tumor clearance following BRAF inhibitortreatment of spontaneous melanomas in a GEMM [126](BrafV600E;PtenF/F;Tyr::CreERT2 mice [127]). Interesting-ly, each of these examples using melanoma models appliedthe same BRAF inhibitor, PLX4720, which is a researchanalog of vemurafenib. Why does each study show a de-pendency on a different immune cell population? Oneexplanation may be the location of the tumor in the modelsused, including subcutaneous, skin and lungs, as well asthe timing of targeted therapy in relation to immune celldepletion. Similarly, imatinib efficacy is dependent on NKcells in melanoma metastasis models [128], whereas CD8+

T cells contribute to tumor regression following imatinibtreatment of GIST-bearing mice or dasatinib treatment ofsubcutaneous mastocytoma-bearing mice [129,130].

In terms of immune regulation, mTOR (mammaliantarget of rapamycin) inhibitors are very interesting tar-geted drugs. mTOR is a crucial regulator of immune func-tion because it promotes the differentiation, activation,and function of T cells, B cells, and antigen-presentingcells [131]. It also controls the balance between effector Tcells and Tregs [132]. Based on its strong immunomodula-tory effects, mTOR inhibition has been successfully uti-lized to prevent transplant rejection over the past decades.In the cancer setting, the immunosuppressive effects ofmTOR inhibitors are very complex and mTOR inhibitor-dependent. For example, the mTOR inhibitor AZD8055, incontrast to rapamycin, enhances the anticancer efficacy ofan CD40 agonist by activating TAMs and DCs, and inducesa strong Th1 response in an experimental liver metastasismodel [133]. Similarly, temsirolimus synergizes with de-pletion of CD4+ T cells or Tregs to reactivate CD8+ T cellsand reduce the growth of subcutaneous renal cell carcino-mas [134].

Further investigations should work out whether depen-dency of targeted therapies on adaptive immune cells istumor type- and/or location-specific. If indeed the impor-tance of adaptive immune cells in regulating the response


to targeted therapy is governed by the location of thetumor, these data would suggest that the roles of immunecells are also likely to be different between primary tumorsand metastasis in distant organs.

Immune cell function following vascular-targetingagentsAngoigenesis inhibitors – the most famous being the anti-VEGF antibody, bevacizumab – and vascular damagingagents target blood vessels, and thus limit re-oxygenationand delivery of nutrients (Figure 1). The link betweenangiogenesis and the immune system is well established[135], and perhaps therefore it is not surprising thatimmune cells regulate the response to antiangiogenictherapies.

The proangiogenic functions of TAMs have been knownfor about a decade [95,136,137]. More recent studies haveshown that TAMs are recruited to experimental tumorsfollowing different forms of antiangiogenic therapies [138–140], often because of the hypoxia-induced increase inchemotactic factors [94,138]. Various studies havereported that TAMs counteract the efficacy of antiangio-genic agents. For example, TAM depletion with clodronateliposomes synergizes with sorafinib in human hepatocel-lular carcinoma xenograft models [141] and with the anti-VEGFR2 antibody, DC101, in subcutaneous colon tumors[142] to reduce tumor growth. Synergy also occurs whencombining a CSF1R inhibitor with DC101 in anothertransplantable model [143].

Blockade of the angiopoietin–TIE2 signaling axis isanother potent strategy to prevent tumor angiogenesisand slow tumor growth. In MMTV-PyMT mice, an anti-angiopoietin 2 (ANGPT2) antibody not only decreasesblood vessel density and retards tumor progression, butit also prohibits TIE2-expressing macrophages from asso-ciating with endothelial cells. The TAM–endothelial cellinteraction is required for angiogenesis, because condi-tional deletion of Tie2 in TAMs decreases blood vesseldensity and mirrors anti-ANGPT2 treatment [140]. Inaddition, ANGPT2 inhibitors reduce lung metastasisin spontaneous breast cancer metastasis models[140,144]. The effect of ANGPT2 inhibitors on metastasismost likely occurs during the late stages of the metastaticcascade when monocyte-derived macrophages facilitateangiogenesis [145], because neutralization of ANGPT2decreases CCL2-dependent monocyte recruitment tolungs and ICAM-mediated monocyte adhesion to endothe-lial cells [144]. Furthermore, inhibition of recruitment ofTIE2-expressing macrophages to transplanted tumors viaCXCR4 blockade amplifies the tumor inhibitory effect ofthe vascular-damaging agent, combretastatin, indicatingthat this subset of TAMs counteracts the efficacy of com-bretastatin [138]. Thus, combining inhibitors of bothTAMs and the angiopoietin–TIE2 axis may yield promis-ing tumor-reductive results.

Studies from a few years ago showed that tumor-induced CD11b+Gr1+ cells (Box 2) also mediate intrinsicresistance to anti-VEGF therapies [146]. More recently, asuppressive functionality was demonstrated for thesecells [147], indicating that CD11b+Gr1+ cells in this sub-cutaneous lymphoma model can be categorized as

MDSCs. These CD11b+Gr1+ cells express proangiogenicmolecules, such as PROK2 (prokineticin 2, also known asBV8), that circumvent the dependency of transplantabletumors on VEGF. Targeting MDSCs or PROK2 syner-gizes with anti-VEGF treatment to reduce tumor growth[146,148,149]. Tumor-derived G-CSF is responsible forinitiating this cascade by mobilizing MDSCs and upre-gulating their expression of PROK2. As one may predict,neutralization of G-CSF also synergizes with anti-VEGFtherapy [149]. The cytokine, IL17, is also involved in thiscascade. Similarly to inhibition of MDSCs, PROK2 or G-CSF blockade, or genetic knockout of IL17, sensitizeresistant, transplanted tumors to anti-VEGF therapy[147]. Interestingly, CD4+ T cells appear to be the sourceof IL17 in these tumor models, and IL17 regulates G-CSFexpression in tumor-associated fibroblasts. We have re-cently shown that IL17-producing gd T cells induce sys-temic expression of G-CSF to expand immunosuppressiveneutrophils and facilitate breast cancer metastasis[49]. In this regard, targeting the IL17-producing Tcell�G-CSF�neutrophil axis in combination with anti-angiogenic therapies may benefit patients with metastat-ic disease.

Much less is known about the role of Tregs and T cellsduring antiangiogenic therapy. In renal cell and colorectalcarcinoma patients, sunitinib reduces the number of Tregsand MDSCs [150–152], and bevacizumab does the same incolorectal carcinoma patients [151]. A few experimentalstudies have shown that endogenous T cell infiltration isincreased following antiangiogenic agents [153–155], andone study has shown that the efficacy of DC101 treatmentis dependent on both CD4+ and CD8+ T cells in a trans-plantable mammary tumor model [153]. As such, the needfor more investigations into the role of immunosuppressiveand adaptive immune cells is warranted to help guide thefuture clinical possibility of combining vascular-targetingagents with immunotherapy.

Immunotherapeutic strategies to enhance the responseto anticancer therapiesThe studies highlighted above have established that bothinnate and adaptive immune cells are viable targets fortherapeutic manipulation. Three main immunomodulato-ry approaches are under intense preclinical and clinicalinvestigation: (i) immunotherapy aimed at boosting thepatients’ own immune system to fight cancer, for examplevia T cell checkpoint inhibitors targeting CTLA4 and thePD1–PDL1 axis (Figure 1), or via cancer vaccines; (ii)immunotherapy through adoptive transfer of (geneticallyengineered) autologous T cells; and (iii) therapies aimed atsuppressing protumor inflammatory processes (Figure 1),such as anti-CSF1R [7] and anti-CCL2 [156,157].

The clinical success of immunotherapeutics that blocknegative immune regulatory pathways, including anti-CTLA4 (ipilimumab) and anti-PD1 (pembrolizumab andnivolumab) [158–160], has reinvigorated cancer researchand oncology. The potential of these drugs shows no signsof stopping because the list of tumor types that respond tocheckpoint inhibitors is expanding rapidly [161,162]. How-ever, checkpoint inhibitors do not benefit every patient[158,163,164]. To increase the number of cancer patients

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Table 1. Beneficial and antagonistic roles of immune cells in anticancer therapy response of various cancer mouse modelsa

Immune cell Anticancer therapy Beneficial

role

Antagonistic

role

Cancer mouse model Tumor location Refs

TAMs Doxorubicin U SL2 lymphoma, L1210 Ha leukemia cell lines Subcutaneous [21]

Paclitaxel U MMTV-PyMT mammary tumor Autochthonous,

orthotopic, lung

metastasis

[22–24]

Paclitaxel U C3(1)-Tag mammary tumor Autochthonous [23]

Doxorubicin U MMTV-PyMT mammary tumor Autochthonous [40]

Gemcitabine U PAN02 and Kras-INK pancreatic cell lines Orthotopic,

liver metastasis

[29]

Paclitaxel U Kras-INK pancreatic cell line Orthotopic [29]

Doxorubicin U HRG-overexpressing T241 fibrosarcomas Subcutaneous [36]

Cyclophosphamide U Lewis lung carcinoma (LLC) cells in

LysM-Cre;VegfaF/F mice

Subcutaneous [41]

Cyclophosphamide +

methotrexate + 5-FU

U MCF-7 human breast cancer cells Subcutaneous [30]

Irradiation U MT1A2 mammary cancer cell line Intradermal [88]

Irradiation U FaDu human prostate cancer cell line Intradermal [89]

Irradiation U U251 and U87MG human glioblastoma cell

lines

Orthotopic [90]

Irradiation U 54A human lung and MCa8 mammary

tumors

Subcutaneous [93]

Irradiation U RM-1 prostate tumor cells Subcutaneous [91]

Irradiation U 4T1 mammary cancer cell line Subcutaneous [92]

Irradiation S S B16F10 melanoma cell line Subcutaneous [96]

MEKi U BrafV600E;Tyr::CreERT2 melanoma cell line Subcutaneous [106]

AZD8055 + anti-CD40 U Renca renal carcinoma cell line Liver metastasis [133]

Sorafinib U SMMC7721 and LM3-R human

hepatocellular carcinoma cell lines

Orthotopic [141]

DC101 U CT26 and LLC cell lines Subcutaneous [142,143]

Anti-ANGPT2 U MMTV-PyMT mammary tumor Autochthonous,

lung metastasis

[140]

Combretastatin U MMTV-PyMT mammary tumor Autochthonous [138]

Combretastatin U N202 mammary tumor cell line Subcutaneous [138]

Neutrophils Cyclophosphamide U Transformed murine embryonic fibroblasts Subcutaneous [42]

Doxorubicin U MCA205, AT3, H2N100 cell lines Subcutaneous [43]

Doxorubicin +

cyclophosphamide

U MDA-231-LM2 and CN34-LM1 human

breast cancer cells

Orthotopic [44]

Docetaxel U Probasin-Cre4;PtenF/F prostate tumor Autochthonous [45]

Irradiation S S FaDu human prostate cancer cell line Intradermal [89]

Trastuzumab U BT474 human breast cancer cell line Subcutaneous [114]

MDSCs gemcitabine U TC1, LLC, AE17, AB12, L1C2 cell lines Subcutaneous [53]

Doxorubicin U 4T1 mammary cancer cell line Orthotopic [55]

5-FU U EL4, LLC, B16F10 and 4T1 cell lines Subcutaneous [54,56]

Docetaxel + JAK2i U Probasin-Cre4;PtenF/F prostate tumor Autochthonous [118]

Irradiation U MC38 colon cancer cell line Subcutaneous [97]

Anti-VEGF U EL4 and LLC cell lines Subcutaneous [146–149]

Dendritic cells Irradiation, oxaliplatin,

doxorubicin,

mitoxantrone

U B16F10, CT26, EG7, EL4, F244, MCA205, TS/

A cell lines

Subcutaneous [43,58–60,

96,98,99]

Paclitaxel U MMTV-PyMT mammary tumor Autochthonous,

orthotopic,

lung metastasis

[23]

CD4+ T cells 5-FU, gemcitabine U EL4 lymphoma cell line Subcutaneous [56]

Paclitaxel + IDO inhibitor U MMTV-Neu mammary tumor Autochthonous [70]

Doxorubicin + lapatinib U MMTV-Neu mammary tumor Autochthonous [71]

Irradiation S S B16F10 melanoma cell line Subcutaneous [96]

PLX4720 S S LWT1 melanoma experimental metastasis Lung metastasis [123]

PLX4720 S S SM1WT1 melanoma cell line Subcutaneous [124]

PLX4720 U BrafV600E;PtenF/F;Tyr::CreERT2

melanomas

Autochthonous [126]

Dasatinib U P815 mastocytoma cell line Subcutaneous [129]

Imatinib S S KitV558/+ gastrointestinal stromal tumor Autochthonous [130]

Temsirolimus U Renca renal carcinoma cell line Subcutaneous [134]

DC101 U NT2.5 mammary tumor cell line Orthotopic [153]


208

Table 1 (Continued )

Immune cell Anticancer therapy Beneficial

role

Antagonistic

role

Cancer mouse model Tumor location Refs

Tregs Cisplatin,

cyclophosphamide,

etoposide

U AC29, B16F10, Meth A, PROb, REBb cell

lines

Subcutaneous [73,74,76,77]

Carboplatin U CC10-Tag non-small cell lung cancer Autochthonous [78]

Irradiation U MMTV-PyMT mammary cell line Orthotopic [102]


CD8+ T cells 5-FU S S EL4 cell line Subcutaneous [56]

Oxaliplatin, doxorubicin,

irradiation

U AT3, B16F10, CT26, EG7, EL4, EO771,

H2N100, MC38, MCA2, MCA205 cell lines

Subcutaneous [58–60,81,

96,99,100]

Doxorubicin + lapatinib U MMTV-Neu mammary tumor Autochthonous [71]

Paclitaxel U Metallothionein I-Ret melanoma tumor Autochthonous [80]

Oxaliplatin S S K14cre;Cdh1F/F;Trp53F/F mammary tumor Autochthonous [85]

Paclitaxel S S MMTV-PyMT mammary tumor Autochthonous [22,23]

Irradiation U B16, EG7, LLC cell lines Intradermal [101]

Anti-ERBB2/Neu U TUBO mammary tumor cell line Subcutaneous [110]

PLX4720 S S LWT1 melanoma experimental metastasis Lung metastasis [123]

PLX4720 U SM1WT1 and BrafV600E;PtenF/

F;Tyr::CreERT2 melanoma cell lines

Subcutaneous [124,125]

PLX4720 S S BrafV600E;PtenF/F;Tyr::CreERT2 melanomas Autochthonous [126]

Dasatinib U P815 mastocytoma cell line Subcutaneous [129]

Imatinib U KitV558/+ gastrointestinal stromal tumor Autochthonous [130]



DC101 U NT2.5 mammary tumor cell line Orthotopic [153]

NK cells Cyclophosphamide U Transformed murine embryonic fibroblasts Subcutaneous [42]

Cyclophosphamide U B16F10 melanoma experimental metastasis Lung metastasis [79]

Doxorubicin S S CT26 cell line Subcutaneous [60]

PLX4720 U LWT1 melanoma experimental metastasis Lung metastasis [123]

PLX4720 S S SM1WT1 melanoma cell line Subcutaneous [124]

Imatinib U B16F10 melanoma experimental metastasis Lung metastasis [128]

Imatinib S S KitV558/+ gastrointestinal stromal tumor Autochthonous [130]


gd T cells Doxorubicin, irradiation U CT26, EG7, MCA2, MCA205, TS/A cell lines Subcutaneous [68]

B cells Cisplatin, carboplatin,

paclitaxel

U K14-HPV16 squamous skin carcinoma Autochthonous,

orthotopic

[67]

aA checkmark indicates a confirmed role for an immune cell, whereas a dash represents a tested but unimportant role.


that benefit from immunotherapy, it will be crucial to fill inseveral gaps. First, biomarkers that preselect thosepatients most likely to respond to immunotherapy needto be uncovered and implemented into clinical practice.Recent reports suggest that both mutational load as well asthe nature of neo-antigens might dictate whether a tumorwill respond to immune checkpoint inhibitors [165]. Inaddition, high intratumoral CD8+ T cells, PD1+, andPDL1+ cells are associated with increased responsivenessto therapies targeting PD1–PDL1 signaling [160–162,166]. Because many human cancers are characterizedby the influx of T cell suppressive immune cells, such asTregs, TAMs, MDSCs, and neutrophils, it is likely that thequantity and/or phenotype of these cells also contain pre-dictive value. Second, the most efficacious combinations ofconventional anticancer therapies and immunotherapyneed to be established. Given the predictive power ofCD8+ T cell infiltration in tumors, anticancer therapiesthat augment CD8+ T cell infiltration and inhibit immu-nosuppressive cells into tumors are obvious candidates totest with immune checkpoint inhibitors. In support of thisnotion, gemcitabine – a chemotherapeutic that targetsTregs and MDSCs [53,167,168] – and melphalan synergize

with anti-CTLA4 in transplantable tumor models[169,170]. Experimental and clinical studies have alsorevealed synergy between cyclophosphamide – knownfor its Treg-reducing effects [73–75] – and various immu-notherapeutic approaches [171,172]. By contrast, the syn-ergy between cisplatin, a chemotherapeutic that does notaffect immunosuppressive cells, and anti-CTLA4 is contro-versial [170,173]. Radiotherapy also synergizes withCTLA4, PDL1, and combined CD40/CD137 targeting tocontrol the growth of various transplantable models andlung metastases [97,174,175] – a process that is dependenton CD4+ T cells, CD8+ T cells, NK cells, or all of the above[97,174]. These data suggest that intervention strategiesthat induce a favorable T cell influx and/or reduced FOXP3/CD8 ratio in tumors are efficacious partners for checkpointinhibitors.

Chemo-, radio-, targeted, and antiangiogenic therapieshave all been shown to increase recruitment of adoptivelytransferred T cells to transplanted tumors and enhanceantitumor responses [96,176–183], but the mechanism bywhich this occurs has not been fully elucidated. One recentreport showed that irradiation of spontaneous pancreatictumors in RIP1–Tag5 mice increases recruitment of

209


adoptively transferred CD8+ T cells and T cell-mediatedtumor rejection, which depends on repolarization of TAMstowards an antitumorigenic phenotype [184]. Thus, strat-egies that condition the microenvironment to become morereceptive to T cells with antitumor activity may enhancetumor eradication. Intriguingly, the tumor microenviron-ment not only regulates the initial therapeutic effect ofadoptively transferred T cells, by influencing their intra-tumoral recruitment, but can also induce resistance oftumors to adoptively transferred T cells. In a GEMM ofmelanoma, cancer cells acquire resistance to T cell adop-tive transfer through inflammation-induced tumor celldedifferentiation, which is characterized by reversible lossof tumor antigen expression [185].

As discussed above, many tumors are characterized byinflux of myeloid cells with immunosuppressive activity,such as macrophages, MDSCs, and neutrophils, which mayimpede successful T cell mediated eradication of cancercells. Relieving the immunosuppressive networks in tu-mor-bearing patients might be an alternative strategy tomaximize success of immunotherapy, and there is experi-mental evidence to support this idea. For instance, block-ade of CXCR2-mediated MDSC trafficking into

Chemotherap• 5-FU • Cyclophosp• Gemcitabin• Irinotecan• Oxalipla�n

anthracycl• Paclitaxel • Trabectedi

Radiotherapy

Pro-tumorigenicTAM

MDSC

Indirect effects

DC CD8+ T cell

Targeted ther• Ima�nib• JAK/STAT • mTOR inhiTumoricidal

TAM

Vascular-targeagents• An�-ANGP• An�-VEGFR• Combretas

phosphate

TAM

TAM

Monocytes

CD8+ T cell

Figure 2. The effects of anticancer therapies on immune cells. Anticancer therapies, suc

have been shown to modulate various immune cell populations in different ways. Thes

importance of immunogenic cell death processes and CD8+ T cell function in response

[59,60,81], whereas response to oxaliplatin and anthracyclines in some genetically en

processes or CD8+ T cell function [85].

210

transplanted rhabdomyosarcomas increases the efficacyof anti-PD1 therapy [186]. In an orthotopic pancreatictumor model, the triple combination of gemcitabine,TAM blockade via CSF1R inhibition, and anti-CTLA4 –or the quadruple combination with anti-PD1 – are veryeffective at inducing tumor regression [35]. Blockade ofCCL2, a monocyte chemoattractant, has been reported toincrease the anticancer efficacy of various cancer vaccineson subcutaneous tumors [187]. A growing number of next-generation immunomodulatory drugs aimed at targetingtumor-associated myeloid cells are being developed andtested in clinical trials [7]. Combining these immunomod-ulatory drugs with the emerging immunotherapeuticapproaches will likely increase the number of cancerpatients that benefit from immunotherapy.

Concluding remarksWhat is clear from the aforementioned experimental andclinical studies is that the immune system is a majorregulator of anticancer therapy response and resistance.At the same time, it is difficult to deduce one over-archingconclusion from these studies because of the overwhelmingcomplexity and the diversity of immune cell responses to

y

hamide e

andines*

n

TAM

TregMDSC

Direct effects

apies

bitors

MDSC

�ng

T2 2 ta�n A-4

TAM

Endothelial cells

Treg

CD8+ T cell

CD4+ T cell


h as chemotherapy, radiotherapy, targeted therapy, and vascular-targeting agents,

e include both indirect and direct effects and a few examples are illustrated. *The

to oxaliplatin and anthracyclines is largely based on transplantable tumor models

gineered mouse models (GEMMs) is not dependent on immunogenic cell death

Box 4. Outstanding questions

� What are the determinants in each tissue/tumor type that dictate

the involvement of immune cells to therapy response?

� What is the role of other, more rare populations of immune cells –

such as mast cells, eosinophils, and innate lymphoid cells – in

anticancer therapy response and resistance?

� Which tumor types will be most responsive to immunotherapy

and/or immunomodulatory agents, and what are the underlying

mechanisms?

� How can the optimal therapy combinations be determined for

individual patients?

� What are the mechanisms underlying resistance towards immu-

notherapy and immunomodulatory agents, and how can resis-

tance be anticipated and prevented?

� Should immune-based treatment strategies for metastatic pa-

tients be the same as for non-metastatic patients?

� How can GEMMs be further sophisticated to better model

anticancer therapy response in humans?


specific anticancer therapies. What we can say for sure isthat the involvement of immune cells is largely dictated bytumor type, mutational signature, tumor model, and tumorlocation (e.g., orthotopic vs subcutaneous) (Table 1), andgeneralizing immune cell response to a particular antican-cer therapy across multiple tumor types or locations shouldbe avoided. Proof of this principle was recently provided bydirectly comparing the efficacy of immunotherapy on threeorthotopic tumors versus their subcutaneous counterparts.This study showed that, in addition to microenvironmentaldifferences in immune cell profile and vascularity, ortho-topic tumors are more immunosuppressive in nature andless sensitive to immunotherapy than subcutaneoustumors [188]. We have also learned that conventionalanticancer therapies have both direct and indirect effectson the immune system (Figure 2). Relatively little is knownabout the role of immune cells during other anticancer

CD4+ T cell

CD8+ T cell

CD8+ T cell

CD8+ T cell

TAM

NK cell

Cancercells

IL4 EGF

CSF1

Paclitaxel +an�-CSF1R

IL1β

IL17/G-CSF

γδ T cell Neutrophils

TAM

Gemcitabine +an�-CSF1R

iNOS

Breasttumor

Cancer cells

Pancrea�ctumor

Lung

Liver

An�-ANGPT2

PLX4720 orima�nib

TNF

Melanoma

Radiotherapy +an�-CTLA4

DC IL10

IL12

Neutrophil

Cancer cells Monocyte

TAM

CCL2


Figure 3. Immune cell participation in metastasis at the primary tumor site and distant organs: potential therapeutic targets. Metastasis occurs through a cascade of events

in which cancer cells escape from the primary tumor site, travel through the blood or lymph system, seed in distant organs or lymph nodes and grow out. Based on this

cascade, experimental and clinical investigations are attempting to counteract metastasis by two major strategies that include preventing metastasis from occurring or

combating established metastatic lesions. Preclinical evidence indicates that immune cells are important mediators of the metastatic cascade [17,197], providing additional

opportunities to incorporate immunotherapy and/or immunomodulatory agents into conventional treatment regimens. This figure highlights the studies we reference in

the text regarding the role of immune cells in metastasis formation and the specific anticancer therapies used to block or reduce metastasis in mouse models. These studies

show that immune cells promote or prevent metastasis at the primary tumor site or in distant organs. In genetically engineered mouse models (GEMMs) and transplantable

models of breast cancer, paclitaxel in combination with the TAM (tumor-associated macrophage) targeted antibody, anti-CSF1R, as well as radiotherapy and anti-CTLA4,

inhibits the formation of spontaneous metastasis [22,23,175,202]. Neutralization of angiopoietin 2 (ANGPT2) also reduces metastasis in breast cancer models by preventing

TAM association with endothelial cells and angiogenesis [140] as well as CCL2-dependent recruitment of monocytes to metastatic lesions in lung [144,145]. TAMs resident

in pancreatic tumors suppress CD8+ T cell functions, and targeting TAMs via anti-CSF1R together with gemcitabine decreases liver metastasis through reactivation of CD8+

T cells [29]. Experiments carried out in melanoma metastasis models have shown that the BRAF inhibitor, PLX4720, and the cKIT inhibitor, imatinib, are effective against

lung metastases via an NK cell-dependent mechanism [123,128]. In addition, other mechanistic studies have identified several putative targets that may be effective at

combating metastasis, including IL17-producing gd T cells [49] and prometastatic neutrophils [48,49].

211


therapies not mentioned here, such as hormonal therapy.Future experiments and clinical trials will undoubtedlybroaden our knowledge in this arena.

Right now, the excitement and success of immune check-point inhibitors in advanced cancer patients has set thestage for new therapeutic approaches in the treatment ofcancer with a focus on combined targeting of cancer cell-intrinsic and -extrinsic processes. For optimal clinical im-plementation, however, several key questions and issuesneed to be addressed (Box 4). First, conventional therapiesneed to be optimally matched to specific immunotherapyand/or immunomodulatory drugs to achieve maximal bene-fit. The timing of treatments will be crucial in this process.These combinations will require some aspects of personali-zation, taking into account tumor type, mutation status, andintratumoral immune profiles before treatment. Second,researchers should be on the lookout for immune-basedresistance mechanisms limiting the efficacy of traditionalanticancer therapies and immunotherapies. Because im-mune cells are highly versatile and plastic cells that aredesigned to adapt quickly to a variety of unanticipatedsituations, resistance to immunotherapy and immunomod-ulatory agents is inevitable and may be dictated by rewiringof immune processes. Finally, more effort should be focusedon metastasis. Metastatic disease, not primary tumors, isresponsible for the majority of cancer-related mortality, andcontrolling metastatic disease is the most urgent need in theclinic. The discrepancy between the effects of anticancertherapies on experimental tumor growth and the responseto these drugs in metastatic patients enrolled in earlyclinical trials may explain why about 85% of new drugs fail[189]. Mouse models have revealed meaningful disparitiesbetween the response of primary tumors and their visceralmetastases to anticancer therapies [190,191]. In this regard,choosing preclinical models that accurately represent eachstage of the metastatic cascade is also crucial for under-standing the basic biological mechanisms of metastasisformation as it occurs in patients [192] and to specificallytarget metastatic disease (Figure 3). Furthermore, target-ing both cancer cells and immune cells may be the key toprevent metastasis from occurring and to combat estab-lished metastasis.

AcknowledgmentsWe thank members of the laboratory of K.E.dV. for helpful discussions.S.B.C is supported by a Marie Curie Intra-European Fellowship(BMDCMET 275610) and K.E.dV is funded by a European ResearchCouncil Consolidator award (INFLAMET 615300), the Dutch CancerSociety (2011-5004), Worldwide Cancer Research (AICR 11-0677), theNetherlands Organization for Scientific Research NWO VIDI(917.96.307), and the European Union (FP7 MCA-ITN 317445 TIMCC).

References1 Krumbhaar, E.B. and Krumbhaar, H.D. (1919) The blood and bone

marrow in yellow cross gas (mustard gas) poisoning: changesproduced in the bone marrow of fatal cases. J. Med. Res. 40, 497–508

2 Goodman, L.S. et al. (1946) Nitrogen mustard therapy; use of methyl-bis (beta-chloroethyl) amine hydrochloride and tris (beta-chloroethyl)amine hydrochloride for Hodgkin’s disease, lymphosarcoma, leukemiaand certain allied and miscellaneous disorders. J. Am. Med. Assoc.132, 126–132

3 Chabner, B.A. and Roberts, T.G., Jr (2005) Timeline: chemotherapyand the war on cancer. Nat. Rev. Cancer 5, 65–72

212

4 DeVita, V.T., Jr and Chu, E. (2008) A history of cancer chemotherapy.Cancer Res. 68, 8643–8653

5 Hanahan, D. and Weinberg, R.A. (2011) Hallmarks of cancer: the nextgeneration. Cell 144, 646–674

6 Pardoll, D.M. (2012) The blockade of immune checkpoints in cancerimmunotherapy. Nat. Rev. Cancer 12, 252–264

7 Ries, C.H. et al. (2014) Targeting tumor-associated macrophages withanti-CSF-1R antibody reveals a strategy for cancer therapy. CancerCell 25, 846–859

8 Olive, K.P. et al. (2009) Inhibition of Hedgehog signaling enhancesdelivery of chemotherapy in a mouse model of pancreatic cancer.Science 324, 1457–1461

9 DuPage, M. et al. (2011) Endogenous T cell responses to antigensexpressed in lung adenocarcinomas delay malignant tumorprogression. Cancer Cell 19, 72–85

10 Garbe, A.I. et al. (2006) Genetically induced pancreaticadenocarcinoma is highly immunogenic and causes spontaneoustumor-specific immune responses. Cancer Res. 66, 508–516

11 Singh, M. et al. (2010) Assessing therapeutic responses in Krasmutant cancers using genetically engineered mouse models. Nat.Biotechnol. 28, 585–593

12 DuPage, M. and Jacks, T. (2013) Genetically engineered mousemodels of cancer reveal new insights about the antitumor immuneresponse. Curr. Opin. Immunol. 25, 192–199

13 Dranoff, G. (2012) Intensifying tumour immunity throughcombination therapy. Lancet Oncol. 13, 440–442

14 Singh, M. et al. (2012) Genetically engineered mouse models: closingthe gap between preclinical data and trial outcomes. Cancer Res. 72,2695–2700

15 De Palma, M. and Hanahan, D. (2012) The biology of personalizedcancer medicine: facing individual complexities underlying hallmarkcapabilities. Mol. Oncol. 6, 111–127

16 Singh, M. and Ferrara, N. (2012) Modeling and predicting clinicalefficacy for drugs targeting the tumor milieu. Nat. Biotechnol. 30,648–657

17 Quail, D.F. and Joyce, J.A. (2013) Microenvironmental regulation oftumor progression and metastasis. Nat. Med. 19, 1423–1437

18 Hanahan, D. and Coussens, L.M. (2012) Accessories to the crime:functions of cells recruited to the tumor microenvironment. CancerCell 21, 309–322

19 De Palma, M. and Lewis, C.E. (2013) Macrophage regulation of tumorresponses to anticancer therapies. Cancer Cell 23, 277–286

20 Noy, R. and Pollard, J.W. (2014) Tumor-associated macrophages: frommechanisms to therapy. Immunity 41, 49–61

21 Mantovani, A. et al. (1979) Role of host defense merchanisms in theantitumor activity of adriamycin and daunomycin in mice. J. Natl.Cancer Inst. 63, 61–66

22 DeNardo, D.G. et al. (2011) Leukocyte complexity predicts breastcancer survival and functionally regulates response tochemotherapy. Cancer Discov. 1, 54–67

23 Ruffell, B. et al. (2014) Macrophage IL-10 blocks CD8+ T cell-dependent responses to chemotherapy by suppressing IL-12expression in intratumoral dendritic cells. Cancer Cell 26, 623–637

24 Shree, T. et al. (2011) Macrophages and cathepsin proteases bluntchemotherapeutic response in breast cancer. Genes Dev. 25, 2465–2479

25 Houthuijzen, J.M. et al. (2014) Lysophospholipids secreted by splenicmacrophages induce chemotherapy resistance via interference withthe DNA damage response. Nat. Commun. 5, 5275

26 Lin, E.Y. et al. (2001) Colony-stimulating factor 1 promotesprogression of mammary tumors to malignancy. J. Exp. Med. 193,727–740

27 Stanley, E.R. et al. (1983) CSF-1 – a mononuclear phagocyte lineage-specific hemopoietic growth factor. J. Cell Biochem. 21, 151–159

28 Maroulakou, I.G. et al. (1994) Prostate and mammaryadenocarcinoma in transgenic mice carrying a rat C3(1) simianvirus 40 large tumor antigen fusion gene. Proc. Natl. Acad. Sci.U.S.A. 91, 11236–11240

29 Mitchem, J.B. et al. (2013) Targeting tumor-infiltrating macrophagesdecreases tumor-initiating cells, relieves immunosuppression, andimproves chemotherapeutic responses. Cancer Res. 73, 1128–1141

30 Paulus, P. et al. (2006) Colony-stimulating factor-1 antibody reverseschemoresistance in human MCF-7 breast cancer xenografts. CancerRes. 66, 4349–4356

http://refhub.elsevier.com/S1471-4906(15)00037-X/sbref1000





















































































31 Germano, G. et al. (2013) Role of macrophage targeting in theantitumor activity of trabectedin. Cancer Cell 23, 249–262

32 Pahler, J.C. et al. (2008) Plasticity in tumor-promoting inflammation:impairment of macrophage recruitment evokes a compensatoryneutrophil response. Neoplasia 10, 329–340

33 Swierczak, A. et al. (2014) The promotion of breast cancer metastasiscaused by inhibition of CSF-1R/CSF-1 signaling is blocked bytargeting the G-CSF receptor. Cancer Immunol. Res. 2, 765–776

34 Pyonteck, S.M. et al. (2013) CSF-1R inhibition alters macrophagepolarization and blocks glioma progression. Nat. Med. 19, 1264–1272

35 Zhu, Y. et al. (2014) CSF1/CSF1R blockade reprograms tumor-infiltrating macrophages and improves response to T-cellcheckpoint immunotherapy in pancreatic cancer models. CancerRes. 74, 5057–5069

36 Rolny, C. et al. (2011) HRG inhibits tumor growth and metastasis byinducing macrophage polarization and vessel normalization throughdownregulation of PlGF. Cancer Cell 19, 31–44

37 De Palma, M. et al. (2008) Tumor-targeted interferon-alpha deliveryby Tie2-expressing monocytes inhibits tumor growth and metastasis.Cancer Cell 14, 299–311

38 Kodumudi, K.N. et al. (2010) A novel chemoimmunomodulatingproperty of docetaxel: suppression of myeloid-derived suppressorcells in tumor bearers. Clin. Cancer Res. 16, 4583–4594

39 Dijkgraaf, E.M. et al. (2013) Chemotherapy alters monocytedifferentiation to favor generation of cancer-supporting M2macrophages in the tumor microenvironment. Cancer Res. 73,2480–2492

40 Nakasone, E.S. et al. (2012) Imaging tumor-stroma interactions duringchemotherapy reveals contributions of the microenvironment toresistance. Cancer Cell 21, 488–503

41 Stockmann, C. et al. (2008) Deletion of vascular endothelial growthfactor in myeloid cells accelerates tumorigenesis. Nature 456,814–818

42 Guerriero, J.L. et al. (2011) DNA alkylating therapy induces tumorregression through an HMGB1-mediated activation of innateimmunity. J. Immunol. 186, 3517–3526

43 Ma, Y. et al. (2013) Anticancer chemotherapy-induced intratumoralrecruitment and differentiation of antigen-presenting cells. Immunity38, 729–741

44 Acharyya, S. et al. (2012) A CXCL1 paracrine network links cancerchemoresistance and metastasis. Cell 150, 165–178

45 Di Mitri, D. et al. (2014) Tumour-infiltrating Gr-1+ myeloid cellsantagonize senescence in cancer. Nature 515, 134–137

46 Han, Y. et al. (2012) Prognostic value of chemotherapy-inducedneutropenia in early-stage breast cancer. Breast Cancer Res. Treat.131, 483–490

47 Di Maio, M. et al. (2005) Chemotherapy-induced neutropenia andtreatment efficacy in advanced non-small-cell lung cancer: a pooledanalysis of three randomised trials. Lancet Oncol. 6, 669–677

48 Bald, T. et al. (2014) Ultraviolet-radiation-induced inflammationpromotes angiotropism and metastasis in melanoma. Nature 507,109–113

49 Coffelt, S.B. et al. (2015) IL17-producing gd T cells and neutrophilsconspire to promote breast cancer metastasis. Nature (in press)

50 Kowanetz, M. et al. (2010) Granulocyte-colony stimulating factorpromotes lung metastasis through mobilization of Ly6G+Ly6C+

granulocytes. Proc. Natl. Acad. Sci. U.S.A. 107, 21248–2125551 Youn, J.I. et al. (2008) Subsets of myeloid-derived suppressor cells in

tumor-bearing mice. J. Immunol. 181, 5791–580252 Talmadge, J.E. and Gabrilovich, D.I. (2013) History of myeloid-

derived suppressor cells. Nat. Rev. Cancer 13, 739–75253 Suzuki, E. et al. (2005) Gemcitabine selectively eliminates splenic Gr-

1+/CD11b+ myeloid suppressor cells in tumor-bearing animals andenhances antitumor immune activity. Clin. Cancer Res. 11, 6713–6721

54 Vincent, J. et al. (2010) 5-Fluorouracil selectively kills tumor-associated myeloid-derived suppressor cells resulting in enhancedT cell-dependent antitumor immunity. Cancer Res. 70, 3052–3061

55 Alizadeh, D. et al. (2014) Doxorubicin eliminates myeloid-derivedsuppressor cells and enhances the efficacy of adoptive T-celltransfer in breast cancer. Cancer Res. 74, 104–118

56 Bruchard, M. et al. (2013) Chemotherapy-triggered cathepsin Brelease in myeloid-derived suppressor cells activates the Nlrp3inflammasome and promotes tumor growth. Nat. Med. 19, 57–64

57 Kanterman, J. et al. (2014) Adverse immunoregulatory effects of 5FUand CPT11 chemotherapy on myeloid-derived suppressor cells andcolorectal cancer outcomes. Cancer Res. 74, 6022–6035

58 Apetoh, L. et al. (2007) Toll-like receptor 4-dependent contribution ofthe immune system to anticancer chemotherapy and radiotherapy.Nat. Med. 13, 1050–1059

59 Ghiringhelli, F. et al. (2009) Activation of the NLRP3 inflammasomein dendritic cells induces IL-1beta-dependent adaptive immunityagainst tumors. Nat. Med. 15, 1170–1178

60 Casares, N. et al. (2005) Caspase-dependent immunogenicityof doxorubicin-induced tumor cell death. J. Exp. Med. 202,1691–1701

61 Gabrilovich, D.I. et al. (2012) Coordinated regulation of myeloid cellsby tumours. Nat. Rev. Immunol. 12, 253–268

62 Broz, M.L. et al. (2014) Dissecting the tumor myeloid compartmentreveals rare activating antigen-presenting cells critical for T cellimmunity. Cancer Cell 26, 638–652

63 Engelhardt, J.J. et al. (2012) Marginating dendritic cells of the tumormicroenvironment cross-present tumor antigens and stably engagetumor-specific T cells. Cancer Cell 21, 402–417

64 de Visser, K.E. et al. (2005) De novo carcinogenesis promoted by chronicinflammation is B lymphocyte dependent. Cancer Cell 7, 411–423

65 Andreu, P. et al. (2010) FcRgamma activation regulates inflammation-associated squamous carcinogenesis. Cancer Cell 17, 121–134

66 Schioppa, T. et al. (2011) B regulatory cells and the tumor-promotingactions of TNF-alpha during squamous carcinogenesis. Proc. Natl.Acad. Sci. U.S.A. 108, 10662–10667

67 Affara, N.I. et al. (2014) B cells regulate macrophage phenotype andresponse to chemotherapy in squamous carcinomas. Cancer Cell 25,809–821

68 Ma, Y. et al. (2011) Contribution of IL-17-producing gamma delta Tcells to the efficacy of anticancer chemotherapy. J. Exp. Med. 208,491–503

69 Guy, C.T. et al. (1992) Expression of the neu protooncogene in themammary epithelium of transgenic mice induces metastatic disease.Proc. Natl. Acad. Sci. U.S.A. 89, 10578–10582

70 Muller, A.J. et al. (2005) Inhibition of indoleamine 2,3-dioxygenase, animmunoregulatory target of the cancer suppression gene Bin1,potentiates cancer chemotherapy. Nat. Med. 11, 312–319

71 Hannesdottir, L. et al. (2013) Lapatinib and doxorubicin enhance theStat1-dependent antitumor immune response. Eur. J. Immunol. 43,2718–2729

72 Savage, P.A. et al. (2013) Basic principles of tumor-associatedregulatory T cell biology. Trends Immunol. 34, 33–40

73 North, R.J. (1982) Cyclophosphamide-facilitated adoptiveimmunotherapy of an established tumor depends on elimination oftumor-induced suppressor T cells. J. Exp. Med. 155, 1063–1074

74 Ghiringhelli, F. et al. (2004) CD4+CD25+ regulatory T cells suppresstumor immunity but are sensitive to cyclophosphamide which allowsimmunotherapy of established tumors to be curative. Eur. J.Immunol. 34, 336–344

75 Lutsiak, M.E. et al. (2005) Inhibition of CD4+25+ T regulatory cellfunction implicated in enhanced immune response by low-dosecyclophosphamide. Blood 105, 2862–2868

76 Wu, L. et al. (2011) Tumor cell repopulation between cycles ofchemotherapy is inhibited by regulatory T-cell depletion in amurine mesothelioma model. J. Thorac. Oncol. 6, 1578–1586

77 Sahu, R.P. et al. (2014) Chemotherapeutic agents subvert tumorimmunity by generating agonists of platelet-activating factor.Cancer Res. 74, 7069–7078

78 Ganesan, A.P. et al. (2013) Tumor-infiltrating regulatory T cellsinhibit endogenous cytotoxic T cell responses to lungadenocarcinoma. J. Immunol. 191, 2009–2017

79 Hanna, N. and Burton, R.C. (1981) Definitive evidence that naturalkiller (NK) cells inhibit experimental tumor metastases in vivo. J.Immunol. 127, 1754–1758

80 Sevko, A. et al. (2013) Antitumor effect of paclitaxel is mediated byinhibition of myeloid-derived suppressor cells and chronicinflammation in the spontaneous melanoma model. J. Immunol.190, 2464–2471

81 Mattarollo, S.R. et al. (2011) Pivotal role of innate and adaptiveimmunity in anthracycline chemotherapy of established tumors.Cancer Res. 71, 4809–4820

213




























































































































































82 Sistigu, A. et al. (2014) Cancer cell-autonomous contribution of type Iinterferon signaling to the efficacy of chemotherapy. Nat. Med. 20,1301–1309

83 Derksen, P.W. et al. (2006) Somatic inactivation of E-cadherin and p53in mice leads to metastatic lobular mammary carcinoma throughinduction of anoikis resistance and angiogenesis. Cancer Cell 10,437–449

84 Muller, W.J. et al. (1988) Single-step induction of mammaryadenocarcinoma in transgenic mice bearing the activated c-neuoncogene. Cell 54, 105–115

85 Ciampricotti, M. et al. (2012) Chemotherapy response of spontaneousmammary tumors is independent of the adaptive immune system.Nat. Med. 18, 344–346

86 Begg, A.C. et al. (2011) Strategies to improve radiotherapy withtargeted drugs. Nat. Rev. Cancer 11, 239–253

87 Liauw, S.L. et al. (2013) New paradigms and future challenges inradiation oncology: an update of biological targets and technology. Sci.Transl. Med. 5, 173sr2

88 Ahn, G.O. and Brown, J.M. (2008) Matrix metalloproteinase-9 isrequired for tumor vasculogenesis but not for angiogenesis: role ofbone marrow-derived myelomonocytic cells. Cancer Cell 13, 193–205

89 Ahn, G.O. et al. (2010) Inhibition of Mac-1 (CD11b/CD18) enhancestumor response to radiation by reducing myeloid cell recruitment.Proc. Natl. Acad. Sci. U.S.A. 107, 8363–8368

90 Kioi, M. et al. (2010) Inhibition of vasculogenesis, but notangiogenesis, prevents the recurrence of glioblastoma afterirradiation in mice. J. Clin. Invest. 120, 694–705

91 Xu, J. et al. (2013) CSF1R signaling blockade stanches tumor-infiltrating myeloid cells and improves the efficacy of radiotherapyin prostate cancer. Cancer Res. 73, 2782–2794

92 Li, F. et al. (2007) Regulation of HIF-1alpha stability through S-nitrosylation. Mol. Cell 26, 63–74

93 Kozin, S.V. et al. (2010) Recruitment of myeloid but not endothelialprecursor cells facilitates tumor regrowth after local irradiation.Cancer Res. 70, 5679–5685

94 Du, R. et al. (2008) HIF1alpha induces the recruitment of bonemarrow-derived vascular modulatory cells to regulate tumorangiogenesis and invasion. Cancer Cell 13, 206–220

95 De Palma, M. et al. (2005) Tie2 identifies a hematopoietic lineage ofproangiogenic monocytes required for tumor vessel formation and amesenchymal population of pericyte progenitors. Cancer Cell 8,211–226

96 Gupta, A. et al. (2012) Radiotherapy promotes tumor-specific effectorCD8+ T cells via dendritic cell activation. J. Immunol. 189, 558–566

97 Deng, L. et al. (2014) Irradiation and anti-PD-L1 treatmentsynergistically promote antitumor immunity in mice. J. Clin.Invest. 124, 687–695

98 Burnette, B.C. et al. (2011) The efficacy of radiotherapy relies uponinduction of type i interferon-dependent innate and adaptiveimmunity. Cancer Res. 71, 2488–2496

99 Deng, L. et al. (2014) STING-dependent cytosolic DNA sensingpromotes radiation-induced type i interferon-dependent antitumorimmunity in immunogenic tumors. Immunity 41, 843–852

100 Lee, Y. et al. (2009) Therapeutic effects of ablative radiation on localtumor require CD8+ T cells: changing strategies for cancer treatment.Blood 114, 589–595

101 Takeshima, T. et al. (2010) Local radiation therapy inhibits tumorgrowth through the generation of tumor-specific CTL: its potentiationby combination with Th1 cell therapy. Cancer Res. 70, 2697–2706

102 Bos, P.D. et al. (2013) Transient regulatory T cell ablation detersoncogene-driven breast cancer and enhances radiotherapy. J. Exp.Med. 210, 2435–2466

103 Straussman, R. et al. (2012) Tumour micro-environment elicits innateresistance to RAF inhibitors through HGF secretion. Nature 487,500–504

104 Vanneman, M. and Dranoff, G. (2012) Combining immunotherapyand targeted therapies in cancer treatment. Nat. Rev. Cancer 12,237–251

105 Imai, K. and Takaoka, A. (2006) Comparing antibody and small-molecule therapies for cancer. Nat. Rev. Cancer 6, 714–727

106 Smith, M.P. et al. (2014) The immune microenvironment confersresistance to MAPK pathway inhibitors through macrophage-derived TNFalpha. Cancer Discov. 4, 1214–1229

214

107 Sommer, G. et al. (2003) Gastrointestinal stromal tumors in a mousemodel by targeted mutation of the Kit receptor tyrosine kinase. Proc.Natl. Acad. Sci. U.S.A. 100, 6706–6711

108 Cavnar, M.J. et al. (2013) KIT oncogene inhibition drivesintratumoral macrophage M2 polarization. J. Exp. Med. 210,2873–2886

109 Clynes, R.A. et al. (2000) Inhibitory Fc receptors modulate in vivocytotoxicity against tumor targets. Nat. Med. 6, 443–446

110 Park, S. et al. (2010) The therapeutic effect of anti-HER2/neu antibodydepends on both innate and adaptive immunity. Cancer Cell 18,160–170

111 Grugan, K.D. et al. (2012) Tumor-associated macrophages promoteinvasion while retaining Fc-dependent anti-tumor function. J.Immunol. 189, 5457–5466

112 Chao, M.P. et al. (2010) Anti-CD47 antibody synergizes withrituximab to promote phagocytosis and eradicate non-Hodgkinlymphoma. Cell 142, 699–713

113 Minard-Colin, V. et al. (2008) Lymphoma depletion during CD20immunotherapy in mice is mediated by macrophage FcgammaRI,FcgammaRIII, and FcgammaRIV. Blood 112, 1205–1213

114 Albanesi, M. et al. (2013) Neutrophils mediate antibody-inducedantitumor effects in mice. Blood 122, 3160–3164

115 Simpson, T.R. et al. (2013) Fc-dependent depletion of tumor-infiltrating regulatory T cells co-defines the efficacy of anti-CTLA-4therapy against melanoma. J. Exp. Med. 210, 1695–1710

116 Taskinen, M. et al. (2007) A high tumor-associated macrophagecontent predicts favorable outcome in follicular lymphoma patientstreated with rituximab and cyclophosphamide-doxorubicin-vincristine-prednisone. Clin. Cancer Res. 13, 5784–5789

117 Pander, J. et al. (2011) Activation of tumor-promoting type2 macrophages by EGFR-targeting antibody cetuximab. Clin.Cancer Res. 17, 5668–5673

118 Toso, A. et al. (2014) Enhancing chemotherapy efficacy in Pten-deficient prostate tumors by activating the senescence-associatedantitumor immunity. Cell Rep. 9, 75–89

119 Nefedova, Y. et al. (2005) Regulation of dendritic cell differentiationand antitumor immune response in cancer by pharmacologic-selectiveinhibition of the janus-activated kinase 2/signal transducers andactivators of transcription 3 pathway. Cancer Res. 65, 9525–9535

120 Anders, K. et al. (2011) Oncogene-targeting T cells reject large tumorswhile oncogene inactivation selects escape variants in mouse modelsof cancer. Cancer Cell 20, 755–767

121 Rakhra, K. et al. (2010) CD4+ T cells contribute to the remodeling ofthe microenvironment required for sustained tumor regression upononcogene inactivation. Cancer Cell 18, 485–498

122 Wilmott, J.S. et al. (2012) Selective BRAF inhibitors induce marked T-cell infiltration into human metastatic melanoma. Clin Cancer Res.18, 1386–1394

123 Ferrari de Andrade, L. et al. (2014) Natural killer cells are essentialfor the ability of BRAF inhibitors to control BRAFV600E-mutantmetastatic melanoma. Cancer Res. 74, 7298–7308

124 Knight, D.A. et al. (2013) Host immunity contributes to the anti-melanoma activity of BRAF inhibitors. J. Clin. Invest. 123,1371–1381

125 Cooper, Z.A. et al. (2014) Response to BRAF inhibition in melanoma isenhanced when combined with immune checkpoint blockade. CancerImmunol. Res. 2, 643–654

126 Ho, P.C. et al. (2014) Immune-based antitumor effects of BRAFinhibitors rely on signaling by CD40L and IFNgamma. Cancer Res.74, 3205–3217

127 Dankort, D. et al. (2009) Braf(V600E) cooperates with Pten loss toinduce metastatic melanoma. Nat. Genet. 41, 544–552

128 Borg, C. et al. (2004) Novel mode of action of c-kit tyrosine kinaseinhibitors leading to NK cell-dependent antitumor effects. J. Clin.Invest. 114, 379–388

129 Yang, Y. et al. (2012) Antitumor T-cell responses contribute to theeffects of dasatinib on c-KIT mutant murine mastocytoma and arepotentiated by anti-OX40. Blood 120, 4533–4543

130 Balachandran, V.P. et al. (2011) Imatinib potentiates antitumor T cellresponses in gastrointestinal stromal tumor through the inhibition ofIdo. Nat. Med. 17, 1094–1100

131 Powell, J.D. et al. (2012) Regulation of immune responses by mTOR.Annu. Rev. Immunol. 30, 39–68























































































































































132 Pollizzi, K.N. and Powell, J.D. (2015) Regulation of T cells by mTOR:the known knowns and the known unknowns. Trends Immunol. 36,13–20

133 Jiang, Q. et al. (2011) mTOR kinase inhibitor AZD8055 enhances theimmunotherapeutic activity of an agonist CD40 antibody in cancertreatment. Cancer Res. 71, 4074–4084

134 Wang, Y. et al. (2014) Foxp3+ T cells inhibit antitumor immunememory modulated by mTOR inhibition. Cancer Res. 74, 2217–2228

135 Murdoch, C. et al. (2008) The role of myeloid cells in the promotion oftumour angiogenesis. Nat. Rev. Cancer 8, 618–631

136 Lin, E.Y. et al. (2006) Macrophages regulate the angiogenic switch in amouse model of breast cancer. Cancer Res. 66, 11238–11246

137 De Palma, M. et al. (2003) Targeting exogenous genes to tumorangiogenesis by transplantation of genetically modifiedhematopoietic stem cells. Nat. Med. 9, 789–795

138 Welford, A.F. et al. (2011) TIE2-expressing macrophages limit thetherapeutic efficacy of the vascular-disrupting agent combretastatinA4 phosphate in mice. J. Clin. Invest. 121, 1969–1973

139 Gabrusiewicz, K. et al. (2014) Anti-vascular endothelial growth factortherapy-induced glioma invasion is associated with accumulation ofTie2-expressing monocytes. Oncotarget 5, 2208–2220

140 Mazzieri, R. et al. (2011) Targeting the ANG2/TIE2 axis inhibitstumor growth and metastasis by impairing angiogenesis anddisabling rebounds of proangiogenic myeloid cells. Cancer Cell 19,512–526

141 Zhang, W. et al. (2010) Depletion of tumor-associated macrophagesenhances the effect of sorafenib in metastatic liver cancer models byantimetastatic and antiangiogenic effects. Clin. Cancer Res. 16,3420–3430

142 Fischer, C. et al. (2007) Anti-PlGF inhibits growth of VEGF(R)-inhibitor-resistant tumors without affecting healthy vessels. Cell131, 463–4675

143 Priceman, S.J. et al. (2010) Targeting distinct tumor-infiltratingmyeloid cells by inhibiting CSF-1 receptor: combating tumorevasion of antiangiogenic therapy. Blood 115, 1461–1471

144 Srivastava, K. et al. (2014) Postsurgical adjuvant tumor therapy bycombining anti-angiopoietin-2 and metronomic chemotherapy limitsmetastatic growth. Cancer Cell 26, 880–895

145 Qian, B.Z. et al. (2011) CCL2 recruits inflammatory monocytes tofacilitate breast-tumour metastasis. Nature 475, 222–225

146 Shojaei, F. et al. (2007) Tumor refractoriness to anti-VEGF treatmentis mediated by CD11b+Gr1+ myeloid cells. Nat. Biotechnol. 25,911–920

147 Chung, A.S. et al. (2013) An interleukin-17-mediated paracrinenetwork promotes tumor resistance to anti-angiogenic therapy.Nat. Med. 19, 1114–1123

148 Shojaei, F. et al. (2007) Bv8 regulates myeloid-cell-dependent tumourangiogenesis. Nature 450, 825–8231

149 Shojaei, F. et al. (2009) G-CSF-initiated myeloid cell mobilization andangiogenesis mediate tumor refractoriness to anti-VEGF therapy inmouse models. Proc. Natl. Acad. Sci. U.S.A. 106, 6742–6747

150 Finke, J.H. et al. (2008) Sunitinib reverses type-1 immunesuppression and decreases T-regulatory cells in renal cellcarcinoma patients. Clin. Cancer Res. 14, 6674–6682

151 Terme, M. et al. (2013) VEGFA-VEGFR pathway blockade inhibitstumor-induced regulatory T-cell proliferation in colorectal cancer.Cancer Res. 73, 539–549

152 Ko, J.S. et al. (2009) Sunitinib mediates reversal of myeloid-derivedsuppressor cell accumulation in renal cell carcinoma patients. Clin.Cancer Res. 15, 2148–2157

153 Manning, E.A. et al. (2007) A vascular endothelial growth factorreceptor-2 inhibitor enhances antitumor immunity through animmune-based mechanism. Clin. Cancer Res. 13, 3951–3959

154 Dirkx, A.E. et al. (2006) Anti-angiogenesis therapy can overcomeendothelial cell anergy and promote leukocyte-endotheliuminteractions and infiltration in tumors. FASEB J. 20, 621–630

155 Huang, Y. et al. (2012) Vascular normalizing doses of antiangiogenictreatment reprogram the immunosuppressive tumor microenvironmentand enhance immunotherapy. Proc. Natl. Acad. Sci. U.S.A. 109,17561–17566

156 Sandhu, S.K. et al. (2013) A first-in-human, first-in-class, phase Istudy of carlumab (CNTO 888), a human monoclonal antibody against

CC-chemokine ligand 2 in patients with solid tumors. CancerChemother. Pharmacol. 71, 1041–1050

157 Pienta, K.J. et al. (2013) Phase 2 study of carlumab (CNTO 888), ahuman monoclonal antibody against CC-chemokine ligand 2 (CCL2),in metastatic castration-resistant prostate cancer. Invest. New Drugs31, 760–768

158 Hodi, F.S. et al. (2010) Improved survival with ipilimumab in patientswith metastatic melanoma. N. Engl. J. Med. 363, 711–723

159 Hamid, O. et al. (2013) Safety and tumor responses withlambrolizumab (anti-PD-1) in melanoma. N. Engl. J. Med. 369,134–144

160 Robert, C. et al. (2015) Nivolumab in previously untreated melanomawithout BRAF mutation. N. Engl. J. Med. 372, 320–330

161 Powles, T. et al. (2014) MPDL3280A (anti-PD-L1) treatment leads toclinical activity in metastatic bladder cancer. Nature 515, 558–562

162 Herbst, R.S. et al. (2014) Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients. Nature 515, 563–567

163 Robert, C. et al. (2011) Ipilimumab plus dacarbazine for previouslyuntreated metastatic melanoma. N. Engl. J. Med. 364, 2517–2526

164 Robert, C. et al. (2015) Nivolumab in previously untreated melanomawithout BRAF mutation. N. Engl. J. Med. 372, 320–330

165 Snyder, A. et al. (2014) Genetic basis for clinical response to CTLA-4blockade in melanoma. N. Engl. J. Med. 371, 2189–2199

166 Tumeh, P.C. et al. (2014) PD-1 blockade induces responses byinhibiting adaptive immune resistance. Nature 515, 568–571

167 Suzuki, E. et al. (2007) Gemcitabine has significant immunomodulatoryactivity in murine tumor models independent of its cytotoxic effects.Cancer Biol. Ther. 6, 880–885

168 Shevchenko, I. et al. (2013) Low-dose gemcitabine depletes regulatoryT cells and improves survival in the orthotopic Panc02 model ofpancreatic cancer. Int. J. Cancer 133, 98–107

169 Mokyr, M.B. et al. (1998) Realization of the therapeutic potential ofCTLA-4 blockade in low-dose chemotherapy-treated tumor-bearingmice. Cancer Res. 58, 5301–5304

170 Lesterhuis, W.J. et al. (2013) Synergistic effect of CTLA-4 blockadeand cancer chemotherapy in the induction of anti-tumor immunity.PLoS ONE 8, e61895

171 Walter, S. et al. (2012) Multipeptide immune response to cancervaccine IMA901 after single-dose cyclophosphamide associates withlonger patient survival. Nat. Med. 18, 1254–1261

172 Le, D.T. and Jaffee, E.M. (2012) Regulatory T-cell modulation usingcyclophosphamide in vaccine approaches: a current perspective.Cancer Res. 72, 3439–3444

173 Wu, L. et al. (2012) CTLA-4 blockade expands infiltrating T cells andinhibits cancer cell repopulation during the intervals of chemotherapyin murine mesothelioma. Mol. Cancer Ther. 11, 1809–1819

174 Verbrugge, I. et al. (2012) Radiotherapy increases the permissivenessof established mammary tumors to rejection by immunomodulatoryantibodies. Cancer Res. 72, 3163–3174

175 Demaria, S. et al. (2005) Immune-mediated inhibition of metastasesafter treatment with local radiation and CTLA-4 blockade in a mousemodel of breast cancer. Clin. Cancer Res. 11, 728–734

176 Reits, E.A. et al. (2006) Radiation modulates the peptide repertoire,enhances MHC class I expression, and induces successful antitumorimmunotherapy. J. Exp. Med. 203, 1259–1271

177 Matsumura, S. et al. (2008) Radiation-induced CXCL16 releaseby breast cancer cells attracts effector T cells. J. Immunol. 181,3099–3107

178 Ramakrishnan, R. et al. (2010) Chemotherapy enhances tumor cellsusceptibility to CTL-mediated killing during cancer immunotherapyin mice. J. Clin. Invest. 120, 1111–1124

179 Zhang, B. et al. (2007) Induced sensitization of tumor stroma leads toeradication of established cancer by T cells. J. Exp. Med. 204, 49–55

180 Liu, C. et al. (2013) BRAF inhibition increases tumor infiltration by Tcells and enhances the antitumor activity of adoptive immunotherapyin mice. Clin. Cancer Res. 19, 393–403

181 Koya, R.C. et al. (2012) BRAF inhibitor vemurafenib improves theantitumor activity of adoptive cell immunotherapy. Cancer Res. 72,3928–3937

182 Shrimali, R.K. et al. (2010) Antiangiogenic agents can increaselymphocyte infiltration into tumor and enhance the effectiveness ofadoptive immunotherapy of cancer. Cancer Res. 70, 6171–6180

215





















































































































































183 Ugel, S. et al. (2012) Immune tolerance to tumor antigens occurs in aspecialized environment of the spleen. Cell Rep. 2, 628–639

184 Klug, F. et al. (2013) Low-dose irradiation programs macrophagedifferentiation to an iNOS+/M1 phenotype that orchestrateseffective T cell immunotherapy. Cancer Cell 24, 589–602

185 Landsberg, J. et al. (2012) Melanomas resist T-cell therapy throughinflammation-induced reversible dedifferentiation. Nature 490,412–416

186 Highfill, S.L. et al. (2014) Disruption of CXCR2-mediated MDSCtumor trafficking enhances anti-PD1 efficacy. Sci. Transl. Med. 6,237ra67

187 Fridlender, Z.G. et al. (2010) CCL2 blockade augments cancerimmunotherapy. Cancer Res. 70, 109–118

188 Devaud, C. et al. (2014) Tissues in different anatomical sites cansculpt and vary the tumor microenvironment to affect responses totherapy. Mol. Ther. 22, 18–27

189 Ledford, H. (2011) Translational research: 4 ways to fix the clinicaltrial. Nature 477, 526–528

190 Guerin, E. et al. (2013) A model of postsurgical advanced metastaticbreast cancer more accurately replicates the clinical efficacy ofantiangiogenic drugs. Cancer Res. 73, 2743–2748

191 Munoz, R. et al. (2006) Highly efficacious nontoxic preclinical treatmentfor advanced metastatic breast cancer using combination oral UFT-cyclophosphamide metronomic chemotherapy. Cancer Res. 66,3386–3391

192 Francia, G. et al. (2011) Mouse models of advanced spontaneousmetastasis for experimental therapeutics. Nat. Rev. Cancer 11,135–141

193 Guy, C.T. et al. (1992) Induction of mammary tumors by expression ofpolyomavirus middle T oncogene: a transgenic mouse model formetastatic disease. Mol. Cell Biol. 12, 954–961

194 Hagerling, C. et al. (2014) Balancing the innate immune system intumor development. Trends Cell Biol. Published online November 28,2014, http://dx.doi.org/10.1016/j.tcb.2014.11.001

216

195 Azab, B. et al. (2012) Usefulness of the neutrophil-to-lymphocyte ratioin predicting short- and long-term mortality in breast cancer patients.Ann. Surg. Oncol. 19, 217–224

196 Noh, H. et al. (2013) Usefulness of pretreatment neutrophil tolymphocyte ratio in predicting disease-specific survival in breastcancer patients. J. Breast Cancer 16, 55–59

197 Kitamura, T. et al. (2015) Immune cell promotion of metastasis. Nat.Rev. Immunol. 15, 73–86

198 Diaz-Montero, C.M. et al. (2009) Increased circulating myeloid-derived suppressor cells correlate with clinical cancer stage,metastatic tumor burden, and doxorubicin-cyclophosphamidechemotherapy. Cancer Immunol. Immunother. 58, 49–59

199 Porembka, M.R. et al. (2012) Pancreatic adenocarcinoma induces bonemarrow mobilization of myeloid-derived suppressor cells whichpromote primary tumor growth. Cancer Immunol. Immunother. 61,1373–1385

200 Wang, L. et al. (2013) Increased myeloid-derived suppressor cells ingastric cancer correlate with cancer stage and plasma S100A8/A9proinflammatory proteins. J. Immunol. 190, 794–804

201 de Visser, K.E. et al. (2006) Paradoxical roles of the immune systemduring cancer development. Nat. Rev. Cancer 6, 24–37

202 DeNardo, D.G. et al. (2009) CD4+ T cells regulate pulmonarymetastasis of mammary carcinomas by enhancing protumorproperties of macrophages. Cancer Cell 16, 91–102

203 Ojalvo, L.S. et al. (2009) High-density gene expression analysis oftumor-associated macrophages from mouse mammary tumors. Am. J.Pathol. 174, 1048–1064

204 Pucci, F. et al. (2009) A distinguishing gene signature shared bytumor-infiltrating Tie2-expressing monocytes, blood ‘resident’monocytes, and embryonic macrophages suggests commonfunctions and developmental relationships. Blood 114, 901–914

205 Xue, J. et al. (2014) Transcriptome-based network analysis reveals aspectrum model of human macrophage activation. Immunity 40,274–288







































































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