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`Mouse Models of Breast Cancer: Platforms for Discovering
`Precision Imaging Diagnostics and Future Cancer Medicine
`
`H. Charles Manning1–4, Jason R. Buck1,3,4, and Rebecca S. Cook1,2
`
`1Vanderbilt University Medical Center, Nashville, Tennessee; 2Vanderbilt–Ingram Cancer Center, Nashville, Tennessee; 3Vanderbilt
`University Institute of Imaging Science, Nashville, Tennessee; and 4Vanderbilt Center for Molecular Probes, Nashville, Tennessee
`
`Representing an enormous health care and socioeconomic chal-
`lenge, breast cancer is the second most common cancer in the
`world and the second most common cause of cancer-related death.
`Although many of the challenges associated with preventing,
`treating, and ultimately curing breast cancer are addressable in the
`laboratory, successful translation of groundbreaking research to
`clinical populations remains an important barrier. Particularly when
`compared with research on other types of solid tumors, breast
`cancer research is hampered by a lack of tractable in vivo model
`systems that accurately recapitulate the relevant clinical features of
`the disease. A primary objective of this article was to provide a
`generalizable overview of the types of in vivo model systems, with
`an emphasis primarily on murine models, that are widely deployed
`in preclinical breast cancer research. Major opportunities to
`advance precision cancer medicine facilitated by molecular imaging
`of preclinical breast cancer models are discussed.
`
`Key Words: animal
`imaging; molecular imaging; breast cancer;
`coclinical trials; mouse models; precision medicine
`
`J Nucl Med 2016; 57:60S–68S
`DOI: 10.2967/jnumed.115.157917
`
`Breast cancer is the second most common cancer in the world,
`
`with an estimated 1.67 million new cases diagnosed in 2012, and
`the second most common cause of cancer-related death (1). In
`the United States alone, the American Cancer Society estimates
`diagnoses of more than 231,000 new cases of invasive breast
`cancer among women and approximately 2,350 new cases
`among men in 2015 (2). Uniquely, the term “breast cancer” does
`not reflect a single disease; rather, breast cancer should be
`thought of as a repertoire of related diseases classifiable into
`distinct subtypes, each portending distinct prognoses and poten-
`tially actionable phenotypic, molecular, or genetic characteris-
`tics. Although targeting certain molecular vulnerabilities inherent
`in specific breast cancer subtypes has improved clinical out-
`comes in a limited number of patients, a sobering reality is that
`more than 40,000 individuals in the United States will die from
`this disease in 2015 (2); this information underscores the numer-
`ous challenges that still remain in the clinical care of individuals
`with this disease.
`
`Received Aug. 6, 2015; revision accepted Sep. 23, 2015.
`For correspondence or reprints contact: H. Charles Manning, 1161 21st
`Ave. South, Medical Center North, VUIIS 3106, Nashville, TN 37232.
`E-mail: henry.c.manning@vanderbilt.edu
`COPYRIGHT © 2016 by the Society of Nuclear Medicine and Molecular
`Imaging, Inc.
`
`Although many of the challenges associated with preventing,
`treating, and ultimately curing breast cancer are addressable in the
`laboratory, successful translation of groundbreaking laboratory
`research to clinical populations remains an important barrier.
`Particularly when compared with research on other types of solid
`tumors, breast cancer research is hampered by a lack of tractable in
`vivo model systems that accurately recapitulate the relevant clinical
`features of the disease. Although certain models necessarily will be
`highlighted as a consequence of illuminating examples and oppor-
`tunities, more exhaustive catalogs of previously described models are
`reviewed in several suggested references (3–7). Here, a generalizable
`overview of the types of in vivo model systems, with an emphasis
`primarily on murine models that are widely deployed in preclinical
`breast cancer research, is provided; this overview encompasses the
`specific relationship of the models with the clinical disease and how
`imaging within the context of the models might be exploited to
`maximize translational gains to combat breast cancer.
`A distinguishing feature of this article is that the key attributes
`of various preclinical breast cancer models and their utility are
`developed from the perspective of noninvasive molecular imaging.
`Despite major successes and lessons learned from the genomic
`landscape of cancer, it is now widely recognized that individual
`cancer genomes, like individual patients, are exquisitely hetero-
`geneous; each contains a unique spectrum of drivers accompanied
`by passengers of less obvious significance. Tools that illuminate
`the cellular and molecular underpinnings of tumors on a patient-
`by-patient basis, such as noninvasive molecular imaging, will be
`essential to bringing precision cancer therapy to fruition. As such,
`preclinical imaging techniques relevant to mouse models of breast
`cancer, with an emphasis on molecular imaging, are also discussed
`in some detail.
`
`MICE AS MODELS OF HUMAN CANCER
`
`Although it might seem obvious, it is worth noting at the outset
`that all “models” of human disease are imperfect. Regardless of
`the degree of sophistication, model systems are, by definition, not
`humans. Rationales for late-phase clinical failures of new drugs
`are frequently based on a (healthy) skepticism of the translational
`value of certain preclinical models; much has been written about
`this issue already, and the value of model systems as a transla-
`tional bridge to clinical applications is not debated in this article.
`However, in vivo modeling provides gains to the breast cancer
`field that complement what can be discovered at the laboratory
`bench. Indeed, the strongest experimental approaches will test
`hypotheses in multiple model systems. Therefore, it is critical to
`understand both the strengths and the limitations of in vivo
`models of breast cancer to maximize what can be learned with
`this approach.
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`The laboratory mouse (Mus musculus) represents a truly ideal
`model system for simulating the entire spectrum of events that lead
`to advanced breast cancer in humans. Mouse model systems enable
`elucidation of distinct facets of cancer biology that may not be frankly
`addressable in patients. Some of the advantages of the mouse as a
`model system are as follows: it is a mammal of small size, facilitating
`inexpensive housing and convenient handling; rapid breeding can
`facilitate colony expansion on convenient time scales; it has a rela-
`tively long life-span (;3 y); the complete sequence and characteriza-
`tion of the mouse genome are available; and manipulation of the
`mouse genome can be accomplished with relative ease. Additionally,
`mice and other rodents share many physiologic similarities with hu-
`mans (8) and therefore are commonly used in drug metabolism and
`pharmacokinetic and toxicity studies. Ironically, for imaging studies,
`the small size of the mouse can be a limitation, particularly when
`studies aim to image tumors whose diameters approximate or are
`smaller than the effective resolution of the imaging modality
`of choice. Some notable differences between humans and mice include
`a higher metabolic rate in mice, an altered telomere length in inbred
`mouse strains, and an altered time frame for cancer onset (9).
`
`HUMAN BREAST CANCER SUBTYPES: WHAT MODELS AIM
`TO RECAPITULATE
`
`Several clinical and pathologic features of human breast cancer
`that allow stratification of patients on the basis of risk, prognosis,
`and likelihood of a response to certain types of therapy have been
`identified (10); in this light, for clinical breast cancer there are
`several impressive precision medicine–related success stories (11)
`and opportunities for future drug development (Table 1). Distinct
`molecular subtypes can be initially stratified on the basis of hor-
`mone receptor status; luminal breast cancers are typically hormone
`receptor–positive, whereas human epidermal growth factor receptor
`2 (HER2) and basallike breast cancers (BLBCs) are hormone receptor–
`negative. Other potential molecular subtypes, including luminal C and
`normallike tumors, have been reported; at present, however, little is
`known about these subtypes (10).
`
`Luminal A and Luminal B Subtypes
`Luminal breast cancers are characterized by the expression of
`the estrogen receptor (ER) and the progesterone receptor (PR),
`which are nuclear hormone receptors, and other associated genes
`(12). Taken together, luminal A and luminal B subtypes account
`for approximately 65% of all breast cancers, although there are
`some differences between these subtypes. Luminal A breast
`cancers tend to express greater quantities of hormone receptors,
`particularly the PR, than luminal B breast cancers. In contrast,
`luminal B tumors tend to exhibit characteristics associated with
`higher-grade disease, are frequently more proliferative, are clini-
`cally more aggressive, and have a poorer prognosis than luminal A
`tumors. Because of their hormone receptor expression and activity,
`luminal A and luminal B breast cancers are routinely treated with
`endocrine therapies that block ER activity, including selective ER
`modulators (such as tamoxifen), selective ER downregulators
`(such as fulvestrant), and aromatase inhibitors (such as letrozole)
`that block the systemic production of the native ligand (b-estradiol).
`Luminal A and luminal B tumors exhibit disparate responses
`to chemotherapy, with higher-grade luminal B tumors frequently
`responding more favorably to chemotherapy (10). Given the hor-
`mone receptor expression and activity of luminal A and luminal B
`breast cancers, PET imaging with an 18F-labeled form of estradiol
`(16a-18F-fluoro-17b-estradiol [18F-FES]) is often useful and may
`
`represent a suitable companion diagnostic approach for predicting
`a response to anti-ER therapy in selected patients (13,14).
`
`HER2-Enriched Subtype
`The HER2 gene is amplified in approximately 15% of invasive
`breast cancers. Some breast cancers of this subtype have been
`shown to express ER, but most HER2-enriched tumors lack ER
`or PR expression. HER2-enriched tumors are frequently higher-
`grade tumors, with positive lymph node involvement. Precision
`medicine approaches to this cancer include the use of trastuzumab
`(Tz) (Herceptin; Genentech), a monoclonal antibody that selec-
`tively targets the HER2 gene product, a receptor tyrosine kinase,
`as well as small-molecule kinase inhibitors (lapatinib and ever-
`olimus) (15,16). HER2-enriched breast cancers with metastatic
`disease are additionally treated with anthracyclines (doxorubicin)
`and often display an initial response to treatment, although recur-
`rence is seen in nearly all cases. Other strategies targeting the
`HER2 receptor and its pathway include novel small-molecule in-
`hibitors and HER2 antibodies, heat shock protein 90 inhibitors,
`agents targeting downstream components of the HER2 signaling
`pathway, and antibody–drug conjugates. Certain molecular imag-
`ing strategies targeting HER2-enriched tumors have leveraged the
`selectivity of Tz labeled with a positron-emitting isotope (64Cu or
`89Zr). Promising clinical results in patients with metastatic breast
`cancer have been shown for these strategies (17,18).
`
`BLBCs
`BLBCs abundantly express epithelial genes, such as those for
`cytokeratins 5 and 17, but the expression of ER, PR, and HER2 is
`notoriously absent. On the basis of their lack of ER, PR, and
`HER2 expression, many BLBCs are deemed “triple-negative
`breast cancer” (TNBC). BLBCs are especially common in African
`American women (10) and are generally associated with a poor
`prognosis. Given the typical lack of ER, PR, and HER2 expression
`in BLBCs, molecularly targeted agents used to treat other breast
`cancer subtypes are often highly ineffective for BLBCs; therefore,
`chemotherapy is a mainstay for treating BLBCs (19). However,
`recent efforts to develop increasingly effective therapies against
`TNBC have led to the identification of several novel TNBC sub-
`types distinguishable by gene expression profiles and with poten-
`tial vulnerabilities (20). Provocatively, noninvasive imaging of the
`androgen receptor by PET with 16b-18F-fluoro-5a-dihydrotestos-
`terone (18F-FDHT), a structural analog of 5a-dihydrotestosterone,
`may represent a companion diagnostic approach for this challeng-
`ing subtype. At present, a study is exploring the feasibility of
`using 18F-FDHT PET to assess androgen receptor expression in
`metastatic breast cancer (ClinicalTrials.gov NCT01988324); this
`study is examining whether the effects of antiandrogens on tumor
`18F-FDHT uptake could aid in identifying optimum dosing for
`blocking the androgen receptor in metastatic breast cancer.
`
`ATTRIBUTES OF PRECLINICAL MOUSE MODELS OF CANCER
`
`Rapidly increasing knowledge about breast cancer molecular
`subtypes may affect the genesis of, progression of, and therapeutic
`strategy for any given breast cancer and underscores the impor-
`tance of mouse model selection in designing preclinical studies
`and coclinical trials. Astounding growth in the reported number as
`well as the biologic elegance of mouse models for cancer research
`has been witnessed in the last decade. An extensive repertoire
`of mouse models with which to study breast cancer progression
`and treatment is now available. In genetically engineered mouse
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`TABLE 1
`Major Subtypes of Human Breast Cancer
`
`Molecular
`subtype
`
`Luminal
`
`Gene expression features
`
`Clinical features
`
`Treatment and prognosis
`
`Elevated expression of hormone
`receptors and associated
`genes (luminal A . luminal B)
`
`∼65% of invasive breast cancers
`are ER- or PR-positive
`
`Respond to endocrine therapy
`(responses to tamoxifen and
`aromatase inhibitors may differ in
`luminal A and B cancers)
`
`HER2
`
`Elevated expression of HER2 and
`other genes in amplicon
`
`Luminal B cancers tend to be of
`higher histologic grade than
`luminal A cancers
`
`Variable response to chemotherapy
`(greater in luminal B cancers than in
`luminal A cancers)
`
`Some overexpress HER2
`(luminal B)
`∼15% of invasive breast cancers
`are ER- or PR-negative
`
`Prognosis is better for luminal A cancers
`than for luminal B cancers
`
`Respond to trastuzumab (Herceptin)
`
`Basallike
`
`Low expression of ER, PR, and
`associated genes
`
`Elevated expression of basal
`epithelial genes and basal
`cytokeratins
`
`High probability of being high-
`grade and node-positive
`∼15% of invasive breast cancers
`
`Low expression of ER, PR, and
`associated genes
`
`Most are ER-, PR-, and HER2-
`negative (TNBC)
`
`Respond to anthracycline-based
`chemotherapy
`
`Prognosis is typically poor
`
`No response to endocrine therapy or
`trastuzumab (Herceptin)
`
`Appear to be sensitive to platinum-
`based chemotherapy and
`polyadenosine ribose polymerase
`inhibitors
`
`Low expression of HER2
`
`BRCA1 dysfunction (germ line,
`sporadic)
`
`Prognosis is typically poor (but not
`uniformly poor)
`
`Particularly common in African
`American women
`
`Adapted with permission of (10).
`
`models (GEMMs), the tumor develops through all stages of
`epithelial transformation with the native stroma, immune system,
`and microenvironment (21). This trend has been propelled in part
`by the sheer volume of laboratories developing and deploying
`innovative mouse models to advance basic cancer research as
`well as by the adoption of contemporary and comparatively in-
`expensive genome editing technologies, such as the clustered
`regularly interspersed short palindromic repeats (CRISPR)/CRISPR-
`associated protein 9 (Cas9) system (22) and RNA interference ap-
`proaches (23). Another important contribution to the volume of
`mouse models recently described has come from the assembly of
`patient-derived xenograft (PDX) banks and, particularly for some
`cancer types, standardization of the infrastructure and protocols
`required to support these systems (24). Here we describe 4 types
`of mouse model systems that can be used for breast cancer re-
`search, identifying both the strengths and the limitations of each
`(Table 2).
`
`Cell Line Xenograft Models
`Mouse models of breast cancer derived by transplanting
`immortalized human cancer cell lines into an immunocompro-
`mised murine host are among the simplest and most frequently
`deployed model systems in cancer research. Most preclinical drug
`
`treatment studies performed in vivo have involved the use of
`immortalized human breast cancer cell lines growing within the
`subcutaneous dorsal flank of immunocompromised mice. Given
`the vast research history accumulated for many immortalized
`breast cancer cell lines and the numerous, diverse cell lines that
`represent all breast cancer molecular subtypes, xenografting breast
`cancer cell lines has become a staple in preclinical breast cancer
`research.
`Although these models are technically simple to establish and are
`inexpensive to maintain over the short term, they have critical
`weaknesses that should be considered before larger programmatic
`efforts are based solely on them. In particular, shortcomings
`inherent in cell line xenograft models are commonly cited as the
`Achilles’ heel of drug discovery efforts, especially when preclinical
`and clinical results are incongruent (25). An insightful commentary
`suggested that cell line xenografts are useful as a bridge between in
`vitro and in vivo studies (3). Objectively, cell line xenograft models
`have clear strengths, especially for rapid hypothesis testing, includ-
`ing the following: the development and extensive characterization
`of a panoply of human breast cancer cell lines from all molecular
`subtypes; the development of tumor stromal characteristics that can
`mimic the characteristics of human tumors (albeit incompletely);
`easily interrogated tumors; and quick tumor manifestation, which
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`
`TABLE 2
`Preclinical Murine Models of Human Cancer
`
`Model
`
`Main components
`
`Advantages
`
`Limitations
`
`Time and Cost*
`
`Xenograft
`(cell line)
`
`Immortalized human tumor
`cell lines transplanted into
`immunodeficient host
`(mouse)
`
`Numerous established and
`well-annotated cell lines
`
`Immunodeficient host
`
`2–4 wk, $
`
`Xenograft
`(patient-derived)
`
`Human tumor explant
`propagated in
`immunodeficient host
`(mouse)
`
`Representation from various
`human tumor types
`
`Features of tumor
`microenvironment,
`including stromal and
`vascular cells,
`incorporated within tumor
`
`Subcutaneous location may not allow
`cultivation of key tissue-specific
`stromal infiltrate
`
`Cross-species divide; stromal
`components are mouse, whereas
`tumor cells are human
`
`Tumors are easily and
`precisely measured
`
`Limited or no genetic heterogeneity
`present within tumor
`
`Heterogeneity and genetic
`diversity within tumors
`
`Immunodeficient host
`
`8–24 wk†, $$$
`
`Representation from various
`human tumor types
`
`Features of tumor
`microenvironment,
`including stromal and
`vascular cells,
`incorporated within tumor
`
`Tumors are easily and
`precisely measured
`
`Subcutaneous location may not allow
`cultivation of key tissue-specific
`stromal infiltrate
`
`Surgical implantation required
`
`Cross-species divide; stromal
`components are mouse, whereas
`tumor cells are human
`
`Genetic and phenotypic drift with
`passage
`
`Syngeneic
`
`Immortalized mouse tumor
`cell line allografted into
`immunocompetent host
`(mouse)
`
`Presence of intact immune
`system
`
`Limited number of established cell
`lines, which are poorly annotated
`
`2–4 wk, $
`
`GEMMs
`
`Genetic modification that
`permits induced or
`spontaneous tumor
`development
`
`Features of tumor
`microenvironment,
`including stromal and
`vascular cells,
`incorporated within tumor
`
`Strong immunogenicity of some lines
`promotes spontaneous regression
`
`All cell types within tumor
`are of mouse origin
`
`Rapid growth rate of many lines limits
`use in longer-term studies
`
`Tumors are easily and
`precisely measured
`
`Tumors develop in tissue of
`origin
`
`Limited genetic mosaicism and
`heterogeneity of tumors
`
`12–24 wk†, $$
`
`Presence of intact immune
`system
`
`Technical hurdles for monitoring tumor
`response in internal organs
`
`Low throughput and high investment
`
`All cell types within tumor
`are of mouse origin
`
`Features of tumor
`microenvironment,
`including stromal and
`vascular cells, and
`immune system
`components
`
`*$5low cost; $$5intermediate cost; $$$5high cost.
`†Up to 1 y to observe metastases.
`Adapted with permission of (21).
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`reduces attendant housing costs and speeds discovery. These
`strengths are balanced by the following limitations of cell line
`xenografts: the immunodeficiency of the host in which tumors arise,
`resulting in major contributions from the immune system to cancer
`development, cancer progression, and a therapeutic response being
`ignored; subcutaneous tumor propagation, which fails to simulate
`organotypic tumor microenvironments; a species disconnect be-
`tween the tumor cells (human) and the stroma (mouse); and extreme
`homogeneity within the tumor, which poorly reflects the intratu-
`moral heterogeneity seen in clinical breast tumors.
`
`PDX Models
`An often overlooked shortcoming of the cell line xenograft model
`is the fact that immortalized cell lines are developed through clonal
`attrition, resulting in cell populations that are propagated through
`multiple passages on a (typically) plastic surface. Selective pressures
`and genetic drift give rise to genotypic and phenotypic changes that
`may irreversibly distinguish daughter clones from paternal tumors
`(26); this scenario may poorly recapitulate the original underlying
`cancer biology of the patient. Models developed from patient-derived
`tumors, otherwise known as PDX models—in which patient tumors
`are surgically implanted into recipient murine hosts without being
`cultured—overcome this limitation. PDX models of various human
`tumors have been developed with great success, although breast
`cancer PDX models have historically been especially challenging
`(27). DeRose et al. reported exemplary success when multiple
`PDX tumor models derived from patient specimens recapitulated
`ER- or PR-positive, ER- or PR-negative, and HER2-positive tumors
`and TNBC (28).
`The major strengths of the PDX approach include genetic diversity
`and heterogeneity that more accurately reflect human breast cancer;
`the ability to model various cancer subtypes; the incorporation of
`contextually correct human stroma within the tumor, including
`vascularity and inflammation; the documented ability to model
`metastasis; and easy interrogation of tumors, such as breast cancers,
`for correlative studies. This approach maintains the genetic and
`phenotypic integrity of the tumor cells, without the clonal selection
`or inadvertent genetic drift seen in immortalized breast cancer cell
`lines. PDX models are increasingly being used on the basis of the
`observation that the histologic and molecular (gene expression and
`copy number variations) characteristics of the PDX can be maintained
`through several mouse “passages.” Importantly, PDX models retain
`clinical responses to many drug treatments, making them ideal for
`coclinical trials.
`Nevertheless, there are several potential drawbacks of PDX models,
`including the requirement to use a severely immunodeficient murine
`host; the fact that the surgical procedure for implanting tumors into
`mice is invasive and requires skill (29); a species disconnect between
`the implanted tumor cells and stroma (human) and subsequently
`infiltrating stroma (mouse); and the time required to generate the
`models, which can require several months simply for the estab-
`lishment of engraftment (30). Technical issues aside, the fact that
`establishing and maintaining PDX model systems require major
`capital investments in supporting infrastructure and personnel
`must not be overlooked.
`
`Syngeneic Models
`The requirement for the use of immunocompromised mice in
`xenograft models fails to incorporate the impact of the immune
`system on the tumor response. This area of cancer research is in its
`early stages, with rapid progress and vast promise that underscores
`the need for immunocompetent models of breast cancer for more
`
`rigorous analyses. Adequately modeling cancer immunology re-
`quires a propagating tumor within an immunocompetent host. One
`approach is to use mouse mammary tumors or mouse mammary
`tumor cell lines implanted into syngeneic immunocompetent murine
`hosts. Devoid of the species constraints inherent in xenografts and
`xenotransplants, allografted mouse tumors are not typically rejected
`by the murine host, given the similar genetic backgrounds. Synge-
`neic model systems offer the distinct advantage of studying cancer
`biology within the context of an intact immune system and species-
`specific tumor microenvironment. However, mouse tumor cell lines
`are limited and annotated to various degrees, and although small-
`molecule therapies may be adequately evaluated within these
`models, the species specificity of antibody imaging agents and
`therapies generally precludes their evaluation in syngeneic model
`systems.
`
`GEMMs
`GEMMs are the most sophisticated in vivo platforms used to
`simulate human cancer. These models are capable of not only
`accurately mimicking many relevant pathophysiologic features of
`human cancer but also recapitulating the sequence of molecular
`events that give rise to cancer. The transgenic expression of an
`oncogene specifically within the mouse mammary epithelium
`under the control of a strong mammary epithelial promoter is
`frequently used to induce mammary tumor formation. This is a
`clinically relevant model of tumor initiation and progression,
`enforcing the stepwise procession of cells from hyperplasia to ductal
`carcinoma in situ and then to invasive ductal carcinoma. Importantly,
`this process occurs within the context of the native stromal matrix
`(requiring stromal remodeling and angiogenesis) and the native
`immune system (requiring immune system evasion). The genetic
`manipulations can drive oncogene expression in a reversible or
`irreversible manner, in a tissue-specific manner (3) or, more broadly,
`throughout an entire organism. Frequently, GEMMs that harbor on-
`cogenic driver genes (e.g., HER2) or lack tumor suppressor genes (e.g.,
`p53), thus genetically mimicking human cancers, are developed.
`The diverse array of oncogenes used to generate transgenic models
`of breast cancer has resulted in a multitude of models that mimic
`many of the specific molecular subtypes seen in clinical breast
`cancers, as confirmed by comparative expression analyses of mouse
`and human breast tumor samples (31). The advantages of GEMMs
`include tumor formation in the contextually appropriate tissue and
`potentially cell of origin through the use of tissue-specific or cell-
`specific promoters; an intact immune system; and a native tumor
`microenvironment that more accurately reflects human disease, in-
`cluding stromal components, vascularity, and inflammation. However,
`GEMMs are limited by the time, expense, and resources required to
`derive, establish, and maintain them; these demands can be overly
`burdensome given the potentially low experimental throughput of
`GEMMs. Few GEMMs of breast cancer truly harbor ER expression,
`despite commonalities in expression profiles between mouse and hu-
`man luminal breast cancers. Although metastases in mouse breast
`cancer models are hematogenous and almost exclusively pulmonary,
`human breast cancer metastases occur though lymphatic spread that
`often precedes hematogenous metastasis to the lungs, liver, bone,
`brain, and elsewhere.
`
`Molecular Imaging Applications: Biomarkers, Drug
`Discovery, and Coclinical Trials
`Molecular imaging is an indispensable tool uniquely poised to
`address major challenges obstructing the delivery of personalized
`cancer therapy. Capable of noninvasively quantifying the cellular
`
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`and molecular underpinnings of tumors on a patient-by-patient
`basis, molecular imaging enables the detection of tumors at early,
`potentially curable stages and provides a means to accurately
`predict the response of a tumor to therapy well before conven-
`tional means of assessment.
`Numerous excellent review articles that thoroughly discuss the
`attributes of various molecular imaging modalities in both patients
`and preclinical animal models have been disseminated. Rather than
`recapitulate a description of specific imaging systems and methods,
`we simply suggest that interested readers consult specific articles that
`already relate directly to this topic (32–34). However, as an introduc-
`tion to preclinical molecular imaging in breast cancer models, it is
`worth noting that a range of imaging modalities can be entirely
`suitable for this purpose; such modalities include optical techniques
`(bioluminescence and fluorescence), ultrasound, MRI, MR spectros-
`copy, and nuclear imaging techniques that use ionizing radiation,
`namely, PET and SPECT (Table 3).
`The modalities can be generally parsed into 2 major categories:
`anatomic, which centers on morphology (gross and fine), and
`molecular, which centers on underlying biologic function (metab-
`olism, biochemistry, gene expression, and systems). The choice
`of imaging modality for addressing in vivo hypotheses depends
`largely on the biologic question of interest and is often guided by the
`strengths and limitations inherent in the modality. As highlighted in
`Table 3, certain modalities are better suited for molecular imaging
`(PET, SPECT, MR spectroscopy, and optical techniques), whereas
`others may serve in both capacities under some scenarios (ultrasound
`and MRI). Although all have been used in preclinical studies, only a
`select few are considered eminently translational.
`
`Once the modality and the model have been selected, numerous
`clinically unmet needs can potentially be addressed in the
`laboratory through the marriage of noninvasive molecular imaging
`and preclinical mouse models of breast cancer. For example, the
`development of inhibitors targeting various portions of the ErbB
`signaling axis is an active and clinically important area of breast
`cancer research. Tz is a Food and Drug Administration–approved,
`recombinant, humanized monoclonal antibody that selectively binds
`to the extracellular domain of HER2, yet objective means to assess
`the treatment response to Tz therapy remain undeveloped. To this
`end, Whisenant et al. recently reported the use of 39-deoxy-39-18F-
`fluorothymidine (18F-FLT) PET as an early marker of the response
`to Tz in HER2-overexpressing xenografts (35). The researchers
`showed that 18F-FLT PET was sensitive to early molecular changes
`in Tz-sensitive, HER2-overexpressing breast cancer xenografts and
`that it could differentiate mouse models of HER2-overexpressing
`breast cancer with various Tz sensitivities.
`The development of noninvasive imaging methods that could
`identify nonresponders earlier during therapeutic intervention is of
`great clinical interest because of the desire to spare patients any
`delay in the initiation of effective combination therapies. For
`example, Kramer-Marek et al. reported the feasibility of Affibody
`(Affibody AB)–based (18F-FBEM-HER2:342) PET for quantifying
`changes in ErbB2 (HER2/neu) expression and predicting the re-
`sponse to Tz in mouse (BT474) breast cancer xenografts (36). In
`addition to immunohistochemical correlation of the overall de-
`crease in 18F-FBEM-HER2:342 Affibody uptake with a tumor re-
`sponse and downregulation of ErbB2 expression, their work also
`reaffirmed that the number of vessels in a tumor could act as a
`
`TABLE 3
`Imaging Modalities
`
`Modality
`
`Signal/contrast
`
`Translational Preclinical Sensitivity* Resolution
`
`Depth
`
`Quantitative
`
`Target
`
`Acquisition
`time (s) Cost†
`
`PET
`
`SPECT
`
`MRI
`
`11C, 13N, 15O, 18F,
`64Cu, 68Ga, 89Zr,
`124I
`
`99mTc, 123/125I, 201Tl,
`111In, 177Lu,
`67Ga, 133Xe
`
`Hydrogen,
`gadolinium,
`magnetic or
`paramagnetic
`particles
`
`MR spectroscopy Hyperpolariza