Journal of Cancer Therapy, 2013, 4, 1411-1425
Published Online November 2013 (http://www.scirp.org/journal/jct)
http://dx.doi.org/10.4236/jct.2013.49168
Open Access JCT
1411
Evolution of Tumor Model: From Animal Model of Tumor
to Tumor Model in Animal*
Nandini Dey1,2,#, Yuliang Sun1, Brian Leyland-Jones1,2, Pradip De1,2,#
1Edith Sanford Breast Cancer, Sanford Research, Sioux Falls, USA; 2Dept. of Internal Medicine, University of South Dakota, Ver-
million, USA.
Received October 15th, 2013; revised November 5th, 2013; accepted November 13th, 2013
Copyright © 2013 Nandini Dey et al. This is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
ABSTRACT
Patient derived xenograft (PDX) is defined as a growth of patients’ tumor in the xenograft setting. The evolution of
cancer model in animal has a century old history. The most single reason that exerted the pressure on the traditional
animal model of cancer to evolve to PDX is that the traditional models have not delivered as expected and traditional
models have not predicted clinical success. In spite of well above 50 drugs developed and approved for oncology over
the last several decades, there remains a nirking paucity of clinical success as a reminder that this war on cancer riding
on the animal model is far from won. In a backbreaking attempt to analyze the failure, the limitation of the “model”
system appeared to be the most rational cause of this shortcoming. It was more of a failure to test a drug rather than a
failure to make a drug that stunted our collective growth and success in cancer research. PDX is the product of this
age-old failure and its fitness is currently tested in virtually all organ-type solid tumors. This review will present and
appraise PDX model in the context of its evolution, its future promise, its limitations and more specifically, the current
content of PDX in different solid tumors including breast, lung, colorectal, prostrate, GBM, pancreatic, hepatocellular
carcinoma and melanoma.
Keywords: Patient Derived Xenograft Model; Solid Tumors; Breast Cancer; Lung Cancer; Colorectal Cancer; Prostrate
Cancer; GBM; Pancreatic Cancer, Melanoma; Hepatocellular Cancer
1. Introduction
After more than forty years of the National Cancer Act of
1971, the nation’s declaration of the “War on Cancer”, to-
day, two-thirds of patients survived at least five years
after being diagnosed with cancer compared with just
half of all diagnosed patients surviving five years after
diagnosis in 1975 [1]. The bill fueled major investments
in cancer research and led to significant increases in can-
cer survival. The last decade achieved significant pro-
gress in cancer understanding and therapy as the cardinal
genetic drivers of individual tumors can be identified,
and different tailor drugs have evolved to specifically in-
tercept these driver mutations/pathways [2]. The empha-
sis in cancer drug development in the course of last few
decades has shifted from cytotoxic, non-specific chemo-
therapies to molecularly targeted, rationally designed
drugs promising greater efficacy and fewer side effects
[3]. Clearly, personalized oncology, an evidence-based
and individualized medicine that delivers the right care to
the right cancer patient at the right time, is the precious
outcome of the effort of the last 50 years [4].
2. Why We Need “the Tumor Copycat” in
Mouse?
In spite of significant resource expended on cancer re-
search over the last half century, the contribution of
newly developed therapeutics to cure the disease or to
improve patient survival has been limited [3]. The major
contributors in the improvements to overall survival have
been either technological (genetic testing e.g., character-
izing BRCA1 and BRCA2 mutations; biomarker detec-
tion e.g., PSA; Tissue monitoring e.g., colonoscopy or
mammography) or medical awareness (incidence of smo-
king] which immensely improved survival/reduced deaths
through early detection of the disease, reduced preva-
lence or increased the prevention of the respective dis-
*Conflict of interest: None.
#Corresponding author.

Evolution of Tumor Model: From Animal Model of Tumor to Tumor Model in Animal 1412
eases. In contrast, only a handful of options have been
made open for the treatment in solid tumors in addition
to age-old treatment with untargeted chemotherapeutic
drugs, surgical resection and radiotherapy as primary and
often secondary courses of action in the course of last 30
years [5]. There are two major reasons for this failure.
The first one is in the built-in nature and the origin of the
disease, the tumor heterogeneity. The accumulated weal-
th of information during the last decades in the field of
molecular markers, gene expression profiling, and the
more recent implementation of next-generation DNA
sequencing technologies have helped disclose a broader
spectrum of heterogeneity among patients presenting
different tumors [6-11]. To the tumor heterogeneity add-
ed more complexity is the paradigm of the cancer stem
cell [12-14]. The second one is the limitation to have the
perfect model for the experiment. Traditional models
those evolved with the advent of genetically engineered
mice (GEM) or xenograft using athymic mice appears as
not fit for the survival as they have failed to predict
clinical success [5]. More than 68 drugs have been de-
veloped and approved for oncology over the last several
decades [15]. Based on the data from the US Food and
Drug Administration (FDA), company surveys, and pub-
licly available commercial business intelligence data-
bases on new oncology drugs approved in the United
States and on investigational oncology drugs to estimate
average development and regulatory approval times, cli-
nical approval success rates, first-in-class status, and glo-
bal market diffusion, DiMasi and Grabowski have de-
termined that the market success of oncology drugs has
induced a substantial amount of investment in oncology
drug development in the last decade [15]. The major road
block therefore in developing cancer targeted therapies is
not the lack of knowledge about specific molecular driv-
ers in these diseases, but is the inability to test the target-
based drugs in predictable preclinical models. Even a
collective effort of the scientific community failed to
mend the gap between bench and bedside due to a lack of
preclinical models capable of reliably predicting clinical
activity of novel compounds in cancer patients [16]. This
explains why only 5% of cancer therapies targeted to
specific molecular drivers tested in the clinic proved ef-
ficacious [17], indicating an unmet need for marked im-
provement in predictive preclinical research. In an old
study to assess trends in the process of global commer-
cial development of cancer treatments, Reichert JM, and
Wenger JB analyzed data for 1111 candidates that en-
tered clinical study during 1990-2006. Their results show
that although the average number of therapeutic candi-
dates entering clinical study per year more than doubled,
the US approval success rate was as low as 8% during
the period [18]. The paucity of success stories in clinics
as therapies fail far too many patients remains as a fact;
the lesson learned from the use of far-from-perfect and
proven to be a clinically irrelevant model [19].
From the failures or limitations of these xenograft or
GEM models evolved patient derived xenograft (PDX;
patient-derived xenografts; tumor graft models ), “the tu-
mor copycat” in mouse, a 21st century preclinical model
[5,19-22] with a promise to deliver clinically relevant
data. PDX models are generated using freshly resected
patient tumors immediately transplanted into immune-
compromised murine hosts without an intermediate in
vitro culture step [5]. Continuous passages of tumors
through consecutive generations of murine hosts without
in vitro cell culture permits ongoing propagation of tu-
mor lines (Figure 1). The establishment of tumorgrafts
constitutes a long-term process consisting of various
steps, with the final objective to show that the validated
model accurately reproduces human cancer, with a high
predictive value of therapeutic efficacy (regardless of the
type of treatment), and closely mimics clinical situations
frequently observed in patients with cancer, such as resis-
tance to standard treatments, metastases, and relapse after
initial therapies (involving residual tumor-initiating cells)
[23]. Currently subcutaneous (hindquarters) or in the
mammary fat pad are more common primary xenografts
sites. Transplanting under the kidney capsule or or-
thotopically is also practiced as the latter of which may
better replicate the tumor microenvironment than subcu-
taneous models [5]. Growth of PDX tumors faithfully
maintain, [1] the cellular complexity and architecture of
the original tumor in its natural state complete with in-
vading vasculature and supporting stromal cells and [2]
the chromosomal, transcriptomic, genomic and proteo-
mic architectural landscape of the original tumor [24]. In
an older study using 5 human malignant tumors, trans-
planted to athymic nude mice, effect of long-term serial
Figure 1. Schematic representation of PDX and PD ex vivo
culture; a human mouse interface at the preclinical transla-
tional level.
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Evolution of Tumor Model: From Animal Model of Tumor to Tumor Model in Animal 1413
transplantation were studied by comparing their growth
patterns and chromosomal constitutions with their early
appearance. After 27 - 56 passages over 3 1/2 to 5 1/2
years, all of the tumors (2 adenocarcinomas of the colon,
2 malignant melanomas, and 1 Burkitt’s lymphoma) were
found to retained the cytological and histological ap-
pearance. All the mitoses observed in the chromosome
studies were of human karyotype. No total chromosomal
species shift, no interspecies hybridization, and no
changes in biological properties were observed [25]. A
number of tumor-specific PDX models have been estab-
lished in melanoma, breast, pancreatic, ovarian, lung,
colorectal, and brain-derived tumors those exhibit bio-
logical stability when passaged in mice in terms of global
gene-expression patterns, molecular diversity, cellular
heterogeneity, mutational status, metastatic potential, che-
moresponsiveness to anti-neoplastic agents, histopathol-
ogy, and tumor architecture [16,26]. Mathew Ellis group
has characterized patient-derived xenografts (PDXs) for
functional studies to demonstrate that the originating tu-
mor genome provides a benchmark for assessing genetic
drift and clonal representation after transplantation. They
published whole-genome comparisons with originating
breast cancers representating major intrinsic subtypes.
They observed that structural and copy number aberra-
tions were retained with high fidelitywhile, at the sin-
gle-nucleotide level, variable numbers of PDX-specific
somatic events were documented, although they were
only rarely functionally significant. It is reported that va-
riant allele frequencies were often preserved in the PDXs,
demonstrating that clonal representation can be trans-
plantable. Estrogen-receptor-positive PDXs were associ-
ated with ESR1 ligand-binding-domain mutations, gene
amplification, or an ESR1/YAP1 translocation. These
events produced different endocrine-therapy-response
phenotypes in human, cell line, and PDX endocrine-re-
sponse studies. Their study concluded that deeply se-
quenced PDX models are an important resource for the
search for genome-forward treatment options and capture
endocrine-drug-resistance etiologies that are not found in
standard cell lines [27]. The success of PDX model in
future will depend on its ability to reflect human disease
in the experimental settings. Outcome driven predictive
preclinical research in future expects PDX to model can-
cer as closely as possible so that the evolution of this
gene-based disease in human can be forecasted in the
laboratory. Considering the complex nature of the evolu-
tion of cancer with respect to its diverse molecular eti-
ologies, it can be argued that morepredictably we mimic
the disease in experimental settings before it happens in a
patient’s body, more chance we have to clinically en-
counter it. Today’s medicine in oncology is essentially
genomically informed science towards selection of tar-
geted therapies to treat individual patients, precision
cancer medicine [28]. The preclinical component of the
precision medicine demands right model to test targeted
drugs directed towards genomically informed pathways,
and is banking heavily on PDX.
3. Evolution to PDX
The proof of concept that it is possible to successfully
xenograft fragments of a patient’s tumor into nude mice
way back in 1969, paved the path to find to answer a
number of questions regarding the cause, prevention,
drug-screening, and targeted therapy in cancer [29]. Di-
rect transfer xenografts of tumor surgical specimens con-
serve the inter-individual diversity and the genetic het-
erogeneity typical of the tumors of origin, and yet give a
unique and flexible opportunity for drug-combination for
the preclinical analysis with a high extrapolative value in
clinics [30]. Although the challenges like limited avail-
ability of the tumor source and technical difficulties were
encountered, human tumor models established in serial
passages proved their superiority in predicting drug-re-
sponse as well as predicting drug-resistance in clinics.
Despite of technical and procedural difficulties, the use of
PDX as a tool has evolved greatly from testing a more
broader aspect of untargeted chemotherapeutic drug-
response to addressing specific and focused challenges
including a development of endocrine resistance in ER+
(estrogen receptors) subset of breast cancer (BC). As an
example, Kabosetal. in their study have recently de-
scribed patient-derived ER+ luminal breast tumor models
for the study of intra-tumor hormone and receptor action
to evoke the importance of mapping both conserved and
tumor-unique ER programs in breast cancers [31]. Their
study highlights the importance of modeling in widely
diverse patient-derived ER+ breast cancers in vivo to
advance our understanding towards improving the treat-
ment of this disease. The outcome of their study demon-
strates that patient-derived ER+ tumor xenografts display
estrogen-dependent growth and have unique ER tran-
scriptomes showing that although multiple other factors
such as genetic and epigenetic signatures, and co-regu-
lator expression patterns, collectively influence tumor
behavior, ER remains the common denominator driving
tumor growth and survival, at least initially. Since ER is
retained in most drug-resistant tumors, their study pointed
out the importance of determining the “switch” in acti-
vated/deactivated genes and signaling networks under
treatment pressure in individual tumors as the cornerstone
to overcome persistent ER+ breast disease. Patient-de-
rived xenografts thus provided a unique opportunity to
dissect the contributions of steroid hormones and their
receptors in the context of development of resistance in
this subset of breast cancer. Using patient-derived xeno-
grafts from metastatic colorectal carcinomas which relia-
bly mimicked disease response in humans, prospectively
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Evolution of Tumor Model: From Animal Model of Tumor to Tumor Model in Animal 1414
recapitulated biomarker-based case stratification, and
identified HER2 as a predictor of resistance to anti-epi-
dermal growth factor receptor antibodies Bertotti et al.,
studied the response to combination therapies against
HER2 and epidermal growth factor receptor. This proof-
of-concept, multi-arm study in HER2-amplified “xenopa-
tients” revealed that the combined inhibition of HER2 and
EGFR induced overt, long-lasting tumor regression and
suggested a promising therapeutic opportunity in cetuxi-
mab-resistant patients with metastatic colorectal cancer
[30]. Another example of a recent development in the
oncology research is the use of PDX models as a renew-
able tissue resource of phenotypically stable, biologically
and ethnically diverse breast cancers which serve as a
renewable, quality-controlled tissue resource for precli-
nical studies investigating treatment response and metas-
tasis [32]. PDX would more accurately recapitulate the
phase I/II or phase III clinical trial situation in which treat-
ment is initiated on patients with advanced, high-volume
metastatic disease [33]. Recently, Li et al. showed that
the analysis of genetic changes in patient-derived xeno-
grafts can reveal crucial details of tumor evolution, in-
cluding the emergence of functional estrogen receptor
mutations in endocrine-resistant breast cancer [34].
4. PDX as Model for Drug Discovery in
Different Organ Sites Solid Tumors
The preservation of the patient’s tumor genomic profile
and tumor microenvironment in PDX gives the opportu-
nity to use primary patient tumorgrafts as a relevant mo-
del to support the translation of new drug-based thera-
peutic strategies in oncology [35]. PDXs maintain at least
certain aspects of the human microenvironment for initial
weeks with the complete substitution with host (murine)
stroma occurring after 2 - 3 passages in mouse. Hence
this model provided more appropriate window for studies
of tumor-microenvironment interaction [36]. This is an
unique property of PDX model which provides a rare
insight to patients’ tumor-stromal interactions (at least
under controlled conditions that can be exploited for drug
discovery). In the following sections, an overview of the
state of art of the use of PDX models as main experi-
mental platforms to understand the biology of tumor cells,
their response to drugs, and their mechanism of resis-
tance to drugs will be presented in the context of differ-
ent solid tumors.
4.1. PDX in Breast Cancer
As early as 2007, study by Marangoni et al., established a
panel of human breast cancer xenografts in immune-
deficient mice suitable for pharmacologic preclinical
assays. The panel consisted of breast cancer xenografts of
15 triple-negative, one ER positive and 2 ERBB2 positive
tumors. Data showed that almost all patient tumors es-
tablished as xenografts displayed an aggressive phenotype,
i.e., high-grade, triple-negative status. The histology of
the xenografts recapitulated the features of the original
tumors. Mutation of p53 and inactivation of Rb and PTEN
proteins were found in 83%, 30%, and 42% of PDX, re-
spectively [37]. This work provided preliminary results to
demonstrate the concordance between clinical outcome
and response of xenografts supporting the use of human
tumor xenografts for the preclinical evaluation of new
compounds and predicting drug response in breast cancer.
In the subsequent years a number of studies using PDX
model opened different avenues in different subtypes of
breast cancer. Report by de Plater’s group described es-
tablishment and characterization of a breast cancer xeno-
graft obtained from a woman carrying a germline BRCA2
mutation [38]. A transplantable xenograft was obtained by
grafting the sample into nude mice and the biological and
genetic profiles of the xenograft were compared with that
of the patient's tumor in terms of histology, immunohis-
tochemistry (IHC), BRCA2 sequencing, comparative
genomic hybridisation (CGH), and qRT-PCR. Tumor
responses to standard chemotherapies including sensitiv-
ity to anthracyclin-based chemotherapy, radiotherapy and
cisplatin-based treatments as well as resistance to do-
cetaxel were also evaluated. Since PDX preserves the
genomic landscape of the tumor, the aggressive triple
negative breast tumors were more frequently modeled in
PDX compared to the other subtypes of breast cancer.
Romanelli et al., used PDX model to demonstrate that in-
hibition of aurora kinases reduces tumor growth and
suppresses tumor recurrence after chemotherapy in triple
negative breast cancer [39]. Although statistically more
PDX models were established in the triple negative sub-
sets of breast cancers, the retention of hormone receptor
heterogeneity has been reported in luminal PDX [31]. In
this study, five transplantable patient-derived ER+ breast
cancer xenografts established from tumors derived from
both primary and metastatic cases were assessed for es-
trogen dependency, steroid receptor expression, cancer
stem cell content, and endocrine therapy response. Gene
expression patterns were determined in select tumors ±
estrogen and ±endocrine therapy. Xenografts morpho-
logically resembled the patient tumors of origin, and ex-
pressed similar levels of ER (5% - 99%), and progester-
one and androgen receptors, over multiple passages.
Analysis of the ER transcriptome in select tumors re-
vealed notable differences in ER mechanism of action,
and downstream activated signaling networks, in addition
to identifying a small set of common estrogen-regulated
genes. These results evoked the importance of mapping
both conserved and tumor-unique ER programs in breast
cancers and helped to define unique estrogen-dependent
gene signatures. In another study, response to hormone
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Evolution of Tumor Model: From Animal Model of Tumor to Tumor Model in Animal 1415
therapy was evaluated in 6 luminal PDX models. The
result showed different sensitivities, thus exhibiting het-
erogeneity similar to what is encountered in the clinic.
The data demonstrated that the primary human luminal
breast cancer xenografts, recapitulates the biological and
clinical behaviors of patient tumors, and therefore can be
suitable for preclinical experiments [40]. DNA copy num-
ber analysis and gene expression analysis were carried out
by Reyal et al., using Affymetrix Microarrays comparing
PDX and patient’s original tumors for the molecular
characterization. Comparison analysis showed that 14/18
pairs of tumors shared more than 56% of copy number
alterations (CNA). Unsupervised hierarchical clustering
analysis showed that 16/18 pairs segregated together,
confirming the similarity between tumor pairs. Analysis
of recurrent CNA changes between patient tumors and
xenografts showed losses in 176 chromosomal regions
and gains in 202 chromosomal regions. Interestingly, it
was demonstrated that less than 5% of genes had recurrent
variations between patient tumors and their respective
xenografts; these genes largely corresponded to human
stromal compartment genes. Different passages of the
same tumor showed that sequential mouse-to-mouse tu-
mor grafts did not affect genomic rearrangements or gene
expression profiles, suggesting genetic stability of these
models over time [24]. Based on these studies and others
[41], patient-derived tumors were used to assess efficacy
of GDC-0941 (pan PI3K inhibitor developed by Genen-
tech Inc., CA) and docetaxel in vivo to show that GDC-
0941 augments the efficacy of docetaxel by increasing
drug-induced apoptosis in breast cancer models [42].
Breast cancer like other solid tumors possesses a rare
population of cells capable of extensive self-renewal that
contributes to metastasis and treatment resistance. PDX
model has been used to test the contribution of cancer
stem cells. Three primary human breast cancer xenografts
generated from 3 different patients. This study by Gi-
nestier et al., demonstrated that CXCR1 blockade selec-
tively targets human breast cancer stem cells in vitro and
in xenografts and suggested that combination therapy
using conventional chemotherapy and drugs against can-
cer stem cells specific targets can lead to better therapeu-
tic results, both in terms of tumor growth as well as in
terms of tumor relapse [43].
4.2. PDX in Lung Cancer
PDX models of non small cell lung cancer (NSCLC),
established following direct implants of lung cancer tissue
fragments in immune-compromised mice has been used
for targeted therapies and new drug development [36]. In
non-small cell lung cancer, the ability to form primary
tumor xenografts is itself demonstrated to have a predic-
tive value of increased risk of disease recurrence in early-
stage. Thus, there is a correlation between the ability of
the tumor to form PDXs and the risk of disease recurrence
in early stage. In this study, xenografts were established
and passaged successfully from 63 of 157 (40%) im-
planted tumor fragments from non-small cell lung cancer
patients undergoing curative surgery into NOD-SCID
(nonobese diabetic-severely combined immunodeficient)
mice [44]. Tumor factors associated with engraftment
included squamous histology, poor differentiation, and
larger tumor size. Interestingly, there was a correlation
between the success of PDX model establishment and
mutation status of the tumor. Significantly fewer EGFR
(epidermal growth factor receptor)-mutated tumors were
engrafted (P = 0.03) than KRAS-mutated tumors (P =
0.05). In an earlier study, similar results have been ob-
tained in early passages of the non-small cell lung cancer
xenografts which revealed a high degree of similarity
with the original clinical tumor sample with regard to
histology, immunohistochemistry, as well as mutation
status [45]. Even the chemotherapeutic responsiveness of
the xenografts resembled the clinical responses as the
shrinkage of tumor was obtained with paclitaxel (4 of 25),
gemcitabine (3 of 25), and carboplatin (3 of 25) with a
lower effectiveness of etoposide (1 of 25) and vinorel-
bine (0 of 11). Although, the response to the anti-EGFR
therapies did not correlate with mutations in the EGFR or
p53, but there appeared a correlation of K-Ras mutations
and erlotinib resistance. In a recent study, PDX models
were established based on first generation non-small cell
lung cancer subrenal capsule xenografts, which provided
suitable platform for quick assessment (6 - 8 weeks) of the
chemosensitivity of patients’ cancers and selection of the
most effective regimens [46]. In this study, xenografts
were established at a very high engraftment rate (90%)
with the retention of major biological characteristics of
the original cancers. PDX provided a model to test the
drug sensitiveness in human tumor-stromal settings. Thus
it provided a tool to find out the drug resistance cells
with tumor whose contribution can be extrapolated in
terms of tumor recurrence as it frequently occurs in pa-
tients after partial or even complete response. This is
important in the context of the cancer stem cell hypothe-
sis of the presence of small subpopulations of tumor ini-
tiating cells within the tumor which is proposed to ex-
plain tumor heterogeneity and the carcinogenesis process,
pre and post drug treatment. In fact, in a study by Krum-
bach et al., primary resistance to cetuximab in a panel of
patient-derived tumourxenograft models was observed
via activation of MET(receptor for hepatocyte growth
factor) as one mechanism for drug resistance indicating
that at the preclinical level, a combined treatments of a
MET inhibitor and cetuximabare additive [47]. The study
was undertaken with the background fact that despite
wide expression of EGFR, only a subgroup of cancer
patients responds to cetuximab therapy. They assessed the
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Evolution of Tumor Model: From Animal Model of Tumor to Tumor Model in Animal 1416
cetuximab response in vivo of 79 human patient-derived
xenografts originating from five tumour histotypes. A
cetuximab response score including positive and negative
factors affecting therapeutic response is proposed in the
study. In cetuximab resistant non small cell lung adeno-
carcinoma, overexpression due to gene amplification and
strong activation of MET was identified. Recently, ten
passable patient-derived non small cell lung carcinoma
xenograft models were established containing a variety of
genetic aberrations including EGFR activating mutation,
KRAS mutation, and FGFR1 and cMET amplification
[48]. Anti-tumor efficacy of gefitinib in this study dem-
onstrated that the EGFR activating mutation model had
superior sensitivity and that the KRAS mutation models
were resistant to gefitinib, which were consistent with the
results reported from clinical trials. Also, models with
FGFR1 gene amplification were found insensitive to ge-
fitinib treatment. In the case of overcoming resistance,
report by Yang et al., demonstrated a novel practical ap-
proaches to overcome the two most common resistances
to EGFR-TKIs seen in the clinic using marketed target
therapies with the help of PDX model [49]. A tailored
treatment regimen was tested using patient-derived xeno-
grafts from naïve Asian non small cell lung cancer pa-
tients including those containing “classic” EGFR activate-
ing mutations towards overcoming erlotinib resistance.
Using different combination of drugs and their response
rate in the PDX model the study was able to identify the
main drivers of resistance in patients.
4.3. PDX in Colorectal Cancer
A step forward towards personalized (evidence-based)
medicine for patients with colorectal cancer (CRC) was
achieved following the work of Bertotti et al., who re-
ported a molecularly annotated platform of PDX (“xeno-
patients”) which identified HER2 as an effective thera-
peutic target in cetuximab-resistant colorectal cancer [50].
It is known that only a fraction of patients with metastatic
colorectal cancer receive clinical benefit from therapy
with anti-epidermal growth factor receptor (EGFR) anti-
bodies, indicating the urgent need to identify novel bio-
markers for better personalized medicine. Bertotti et al.,
produced xenograft cohorts from 85 patient-derived, ge-
netically characterized metastatic colorectal cancer sam-
ples (“xenopatients”) to identify novel determinants of
therapeutic response and new oncoprotein targets. Serially
passaged tumors retained the morphologic and genomic
features of their original counterparts. Xenopatients re-
sponded to the anti-EGFR antibody cetuximab with rates
and extents analogous to those observed in the clinic
which were prospectively stratified as responders or non-
responders on the basis of several predictive biomarkers.
Genotype-response correlations indicated HER2 ampli-
fication specifically in a subset of cetuximab-resistant,
KRAS/NRAS/BRAF/PIK3CA wild-type cases. Impor-
tantly, HER2 amplification was also enriched in clinically
nonresponsive KRAS wild-type patients. Their study
indicated that PDX models could be utilized successfully
to determine the biomarkers in the drug-resistance condi-
tions with different genetic backgrounds. Julien et al.,
comprehensively characterized a large panel of patient-
derived tumor xenografts representing the clinical het-
erogeneity of human colorectal cancer [51]showing that
their collection recapitulates the clinical situation about
the histopathology and molecular diversity of CRC. It was
observed that patient tumors and corresponding models
are clustering together allowing comparison studies be-
tween clinical and preclinical data. Based on this result,
they also conducted pharmacologic mono-therapy studies
with standard of care for CRC (5-fluorouracil, oxaliplatin,
irinotecan, and cetuximab). Through an experimental
cetuximab phase II trial, we confirmed the key role of
KRAS mutation in cetuximab resistance. They reported
the loss of human stromal cells after engraftment, ob-
served a metastatic phenotype in some models, and finally
compared the molecular profile with the drug sensitivity
of each tumor model. In colorectal cancer, PDX model has
also been used to report a suppression of the growth of
tumors by an adenovector expressing small hairpin RNA
targeting Bcl-XL[52]. The result showed that Ad/Bcl-XL
shRNA with or without 5-Fu has effective anti-tumor
effects on the patient tumor-derived rectal cancer xeno-
grafts.
4.4. PDX in Prostate Cancer
Toivanen et al., reviewed the current status of xenograft-
ing human primary prostate cancer, and their potential
application to translational research [53]. Earlier, pa-
tient-derived intra-femoral xenograft model of bone me-
tastatic prostate cancer that recapitulates mixed osteolytic
and osteoblastic lesions has been reported by Raheem et
al., [54]. In their study, xenograft tumors were developed
from a femoral bone metastasis of prostate cancer (re-
moved during hemiarthroplastywhich was transplanted
into Rag2(-/-); γc(-/-) mice either intra-femorally or sub
cutaneously) were analyzed and validated for prostate
cancer biomarker expression. Similarly, Aparicio et al.,
reported derivatization of neuroendocrine prostate cancer
xenografts with large-cell and small-cell features from a
single patient’s tumor [55].In another study, an andro-
gen-dependent prostate cancer xenograft model was de-
rived from a metastatic skin lesion of a Japanese hormone-
refractory prostate cancer (HRPC) patient with poorly
differentiated prostatic adenocarcinoma. The model ex-
pressed wild-type AR and PSA and showed androgen
dependence [56]. PDX model had been proved useful for
the development of new therapies for androgen abla-
tion-resistant prostate cancers. Previously, Yosida et al.,
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Evolution of Tumor Model: From Animal Model of Tumor to Tumor Model in Animal 1417
established a serially transplantable human prostate can-
cer xenograft model from liver metastatic tissue of a pa-
tient treated with antiandrogen bicalutamide which ex-
pressed the AR with a point mutation at amino acid 741
(tryptophan to cysteine; W741C) in the ligand-binding
domain[57]. This mutation was also present in cancerous
tissue used for generation of xenograft. Data showed that
agonistic effect of bicalutamide to a xenograft with
clinically induced AR mutation. Although the growth of
KUCaP in male mice was androgen dependent, bicalu-
tamide aberrantly promoted the growth and prostate-
specific antigen production of KUCaP. Thus the bicalu-
tamide-responsive mutant AR may serve in the develop-
ment of new therapies for androgen ablation-resistant
prostate cancers. PDX model provided experimental
model to test the effect of kava root extract (Piper me-
thysticum Forst is a perennial plant indigenous to the Pa-
cific Islands) and flavokawain B on the tumor growth.
The kava root extract and flavokawain B reduced tumor
growth, AR expression in tumor tissues and levels of
serum PSA in the patient-derived prostate cancer xeno-
graft models suggesting a potential usefulness of a safe
kava product or its active components for prevention and
treatment of advanced prostate cancer by targeting AR
[58].
4.5. PDX in GBM
Recently, high-resolution mutational profiling suggested
the genetic validity of glioblastoma patient-derived pre-
clinical models. In a comprehensive study, Yost et al.,
identified somatic coding mutations and copy number
aberrations in four glioblastoma (GBM) primary tumors
and their matched pre-clinical models: serum-free neu-
rospheres, adherent cell cultures, and mouse xenografts.
Their analysis identified known GBM mutations altering
PTEN and TP53 genes, and new actionable mutations
such as the loss of PIK3R1, and revealed clear patient-
to-patient differences. They observed approximately 96%
primary-to-model concordance in copy number calls in
the high-cellularity samples [59]. Jarzabek et al., had
shown that a xenograft model based on serial xenotrans-
plantation of human biopsy spheroids in immune-defi-
cient rodents maintains the genotype and phenotype of
the original patient tumor [60]. Based on their study they
later reported an in vivo bioluminescence imaging vali-
dation of a human biopsy-derived orthotopic mouse mo-
del of glioblastomamultiforme. PDX model has been
utilized to identify the role of Wnt/β-catenin signaling as
a key downstream effector of MET signaling and con-
tributor of GBM malignancy and the maintenance of
glioblastoma stem cells [61]. Kim et al., have identified
Wnt/β-catenin signaling pathway as one of the pathways
that is enriched in MET(high/+) cells populations com-
pared with bulk tumor cells in the established a series of
GSCs and xenograft tumors derived from freshly disso-
ciated specimens from patients with GBM.
4.6. PDX in Hepatocellular Carcinoma
Xenografts of human hepatocellular carcinoma SCID mice
have been reported by Tran’s group [62] and by other
groups [63]. These established patient-derived hepato-
cellular carcinoma xenografts were extensively used in
later years for the testing of different drugs including
AZD6244 (MEK Inhibitor), RAD001 (everolimus), Suni-
tinib (a potent inhibitor of two receptors involved in an-
giogenesis—vascular endothelial growth factor receptor
and platelet-derived growth factor receptor PDGFR), and
Brivanibalaninate (a dual inhibitor of vascular endothe-
lial growth factor receptor and fibroblast growth factor
receptor tyrosine kinases) at the preclinical setting [64-
67]. Huynh et al., treated patient-derived HCC xeno-
grafts with 1) Sorafenib (a small molecule inhibitor of
several receptor tyrosine kinases including VEGFR,
PDGFR, c-Kit and RAF-kinase), 2) AZD6244 (ARRY-
142886), and 3) Sorafenib plus AZD6244. The study
showed that the pharmacological inhibition of the MEK/
ERK pathway by AZD6244 enhanced the anti-tumor
effect of Sorafenib in both orthotopic and ectopic models
of hepatocellular carcinoma underscoring the potential of
a combined therapeutic approach with Sorafenib and
MEK inhibitors in the treatment of hepatocellular carci-
noma [64].
4.7. PDX in Melanoma
As early as 2004, Krepler et al., evaluated the in vivo
anti-tumoral effects of CpG oligonucleotides against hu-
man malignant melanomaxenografts in NOD/SCID mice
and demonstrated the antitumor activity of oligonucleo-
tides containing immune-stimulatory CpG motifs in a
xeno-transplantation model with absent B, T cells and a
lack of natural killer (NK) cell function [68]. CpG oli-
gonucleotides administered in single peri-tumoral subcu-
taneous injections three times per week resulted in ele-
vated plasma levels of interleukin-12 and significant in-
hibition of the growth of established tumor xenografts by
60% (p < 0.016) compared to the placebo control. Pa-
tient-derived tumor xenografts engrafted in immune-
compromised mice have been proposed as valuable pre-
clinical models in melanoma that can predict clinical
response to treatments[69]. Patient-derived tumor xeno-
graft model was utilized to guide the use of BRAF in-
hibitors in metastatic melanoma. Recently, Guerreschi et
al., established a PDX model of BRAF V600E mela-
noma useful for testing the efficacy of Vemurafenib
(B-RAF enzyme inhibitor developed by Plexxicon and
Genentech Inc.) [70]. They validated the stability of the
model that was similar to the original tumor with respect
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Evolution of Tumor Model: From Animal Model of Tumor to Tumor Model in Animal 1418
to histology, immunohistochemistry, mutational status,
and fluorine-18 fluorodeoxyglucose ([F]FDG)-PET/com-
puted tomography (CT). The sensitivity of the xenografts
to Vemurafenib was determined by tumor growth inhibi-
tion and decreased in standardized uptake value on [F]
FDG-PET/CT. Their result allowed successful rechal-
lenge with Vemurafenib in a patient who was adminis-
tered a lower dose of Vemurafenib because of the onset
of adverse events. Authors claimed that their study found
that PDX provides “real-time” results in an animal that
phenocopies the biology and expected Vemurafenib re-
sponses of the tumor in a patient with BRAF V600E
melanoma and this “coclinical” trial using PDX appears
to guide Vemurafenib treatment for metastatic melanoma.
PDX has been also established in uveal melanoma. The
uveal melanoma xenografts in immunodeficient mice
have been reported to accurately recapitulate the genetic
features of primary human uveal melanoma and they
exhibited genetic stability over the course of their in vivo
maintenance [71]. These models constitute valuable pre-
clinical tool for drug screening in uveal melanoma. Es-
tablishment and characterization of a panel of human
uveal melanoma xenografts derived from metastatic tu-
mors has also been reported [72]. It has been observed
that the establishment rate of human uveal melanoma in
their study was 28% (25 of 90) which was independent
of size, histologic parameters, or chromosome 3 mono-
omy but was significantly higher in metastatic tumors as
compared to the primary tumors. In vivo tumor growth
was found prognostic for a lower metastasis-free survival
in patients with primary tumors. There was a high con-
cordance between the patients’ tumors and their corre-
sponding xenografts for all parameters tested (histology,
genetic profile, and tumor antigen expression). Interest-
ingly, the four xenografts studied displayed different
response profiles to chemotherapeutic agents.
4.8. PDX in Pancreatic Cancer
Recently, PDX model has been used to isolate and cul-
ture rare cancer stem cells CSC) from pancreatic ductal
adenocarcinoma [73]. Pancreatic tumor cells from pa-
tient-derived xenografts were screened for the presence
of surface markers of pancreatic CSCs, CD24, CD44,
and CD326. Following cell isolation and culture, 35% of
sorted human xenograft cells formed tumor spheroids
retaining high expression levels of CD24, CD44, and
CD326. In another study, the efficacy of inhibition of
EGFR/HER2 receptors and the downstream KRAS ef-
fector, mitogen-activated protein kinase/extracellular-
signal regulated kinase (ERK) kinase 1 and 2 (MEK1/2),
on pancreatic cancer proliferation was tested following a
combination of MEK inhibitor trametinib and lapatinib
using pancreatic PDX model [74]. An inhibition of the
growth of patient-derived pancreatic cancer xenografts
with the MEK inhibitor trametinib is shown to be aug-
mented by combined treatment with the epidermal grow-
th factor receptor/HER2 inhibitor lapatinib. Data indi-
cated that inhibition of the EGFR family receptor signal-
ing may contribute to the effectiveness of MEK1/2 inhi-
bition of tumor growth possibly through the inhibition of
feedback activation of receptor tyrosine kinases in re-
sponse to inhibition of the RAS-RAF-MEK-ERK path-
way. In an earlier study, Rajeshkumar et al., reported a
collection of freshly generated patient-derived pancreatic
ductal adenocarcinoma xenografts were used to test the
effect of gemcitabine, the first-line chemotherapeutic
agent for pancreatic ductal adenocarcinoma, which ini-
tially proved effective in reducing tumor size. However
gemcitabine was largely ineffective in diminishing the
CSC populations, and eventually culminated in tumor
relapse. Since death receptor 5 (DR5) was found to be
enriched in pancreatic CSCs compared with the bulk of
the tumor cells, a combination of tigatuzumab, a fully hu-
manized DR5 agonist monoclonal antibody, with gem-
citabine was more efficacious by providing a double hit
to kill both CSCs and bulk tumor cells. This combination
therapy produced remarkable reduction in pancreatic
CSCs, tumor remissions, and significant improvements
in time to tumor progression in a model that is consid-
ered more difficult to treat. Thus data provided the ra-
tionale to explore the DR5-directed therapies in combi-
nation with chemotherapy as a therapeutic option to im-
prove the current standard of care for pancreatic cancer
patients [75]. A molecular profiling of direct xenograft
tumors established from human pancreatic adenocarci-
noma. Engraftment of human pancreatic tumors into im-
munodeficient mice prior to and following neoadjuvant
therapy was demonstrated by Kim et al., which provided
an in vivo platform for comparison of global gene ex-
pression patterns [76]. Recently, a prospective and ran-
domized testing was reported in a set of almost 200 sub-
cutaneous and orthotopic implanted whole-tissue primary
human tumor xenografts in pancreatic ductal adenocar-
cinoma [77]. The most pronounced therapeutic effects
were observed in gemcitabine-resistant patient-derived
tumors. Intriguingly, the proposed triple therapy ap-
proach could be further enhanced by using a PEGylated
formulation of gemcitabine, which significantly increas-
ed its bioavailability and tissue penetration, resulting in a
further improved overall outcome. The study demonstrat-
ed that a multimodal (combining chemotherapy, hedge-
hog pathway inhibition, and mTOR inhibition) treatment
can eliminate cancer stem cells and leads to long-term
survival in primary human pancreatic cancer tissue xeno-
grafts. PDXs as a tool for cancer stem cell studies have
been well developed for pancreatic cancer. A direct pan-
creatic cancer xenograft model has been used as a plat-
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Evolution of Tumor Model: From Animal Model of Tumor to Tumor Model in Animal
Open Access JCT
1419
form for cancer stem cell therapeutic development and to
bridge the enormous gap between the anti-proliferative
and in vivo antitumor efficacy of gemcitabine in cell
line-based models and its clinical efficacy [78]. Jimeno et
al. demonstrated that the chemotherapeutic treatment of
pancreatic PDXs caused an increase of cancer stem cell
markers including ALDH and CD24 in the residual tu-
mor population, proving the hypothesis of an obviously
enhanced chemo-resistance of the cancer stem cells sub-
population. Combined treatment with gemcitabine and
cyclopamine induced tumor regression and decrease in
cancer stem cell markers and hedgehog signaling. Hed-
gehog inhibitors were able to further reduce tumor grow-
th and decreased both static and dynamic markers of can-
cer stem cell. Their study proved that direct tumor xeno-
grafts are a valid platform to test multi-compartment
therapeutic approaches in pancreatic cancer. Similar ef-
fects were reported with PDXs derived from other can-
certypes, including colorectal cancer [79].
5. Limitations of PDX Model
Like any other model system, PDX has limitations. The
pros and cons of the PDX model have been schematically
presented in Figure 2. First, PDX “do not” and “cannot”
represent human immune response neither from the tu-
mor side nor from the host side. The researcher and phy-
sicians scientists will have to either use a next generation
sophistication to extrapolate/simulate the immune com-
ponent or they have to rationally couple the inference
drawn from the cancer immunologists in circumventing
this built-in limitation of the model. Second, the estab-
lishment of PDX is neither cost effective nor human re-
source friendly. The burden of cost, infrastructure and
trained human resource is certainly a primary hold back
factor in the development, growth and the future evolu-
tion of PDX model. However, considering 1) the limita-
tions of different existing models (Figure 3), 2) the un-
met need to treatment different challenging aspects of
cancer including metastasis, stem cell involvement, tu-
mor dormancy and drug resistance, PDX model remains
our best hope in the preclinical translational research.
6. PDX Is Here to Stay: Future Perspectives
PDX has a promise to fulfill the primary goal of cancer
biologists to better understand tumorigenesis and cancer
progression over time which is the most formidable
challenge in cancer research [5]. PDX provides, more
realistic, gemonically stable, hispopathologically faithfull
platform of study than any other animal model of cancer
with a unique flexilibily for drug testing for various pur-
poses, 1) tumor shrinkage, 2) development of drug re-
sistance 3) metastasis and stem cell studies (Figure 4).
The preclinical setting in which PDXs can be relevant is
represented by the evaluation of the potential of new
drugs in cancer treatment as PDX faithfully represents
the heterogeneity of a cancer type as well as representing
their various subcategories on one hand and provides
consistent genomic landscape on the other hand. For the
same reason the PDX model represents an improved
model to study the evolution of a tumor and development
of drug resistance. The uniqueness of the PDX is its ca-
pability to retain the genetic stability of the tumor as well
as capability to evolve in the experimental settings as
closely as the tumor evolves and respond/resists to drugs
Figure 2. Promise of PDX model.

Evolution of Tumor Model: From Animal Model of Tumor to Tumor Model in Animal 1420
Figure 3. Pros and cons of PDX model as compared to xenograft model and GEM models of cancer.
Figure 4. Long term utility chart of PDX model.
Open Access JCT

Current Distortion Evaluation in Traction 4Q Constant Switching Frequency Converters 1421
in patients. Today’s precision medicine will have to de-
pend on the power and promise of PDX model.
7. Conclusion
Mouse models are invaluable tools for preclinical eva-
luation of new therapeutic strategies in cancer. The enor-
mous burden of cost and a high failure rate of cancer
drug development frankly highlight the need for new
preclinical strategies and resources. PDX models from
patient-derived tumor tissue at low passage have proven
to conserve original tumor characteristics such as het-
erogeneous histopathology, clinical bio-molecular signa-
ture, malignant phenotypes and genotypes, tumor archi-
tecture, gene expression profiles and tumor vasculature.
Based on this hypothesis, primary tumor xenografts have
shown to provide relevant predictive insights into clinical
outcomes when evaluating the worth of new cancer
therapies.
8. Acknowledgements
Authors acknowledge Edith Sanford Breast Cancer Re-
search, Sanford Research, Sioux Falls, SD.
9. Review Criteria
The information for this review is compiled in part by
searching the PubMed database for full length research
articles and review articles those were published before
October, 1st 2013. Electronic early-release publications
listed in these databases are also included. Only articles
published in English are considered. The search terms
used included “patient derived xenograft” and “PDX
model” in association with the following search terms:
“Breast cancer”, “Colorectal cancer”, “Lung cancer”,
“GBM”, “Tumor growth”, “Hepatocellular carcinoma”,
“Melanoma” “Pancreatic Cancer”, “Prostrate Cancer”,
“Angiogenesis”, and “Therapeutics”.
REFERENCES
[1] N. J. Vogelzang, et al., “Clinical Cancer Advances 2011:
Annual Report on Progress against Cancer from the
American Society of Clinical Oncology,” Journal of Cli-
nical Oncology: Official Journal of the American Society
of Clinical Oncology, Vol. 30, No. 1, 2012, pp. 88-109.
[2] Y. Yarden and C. Caldes, “Basic Cancer Research Is Es-
sential for the Success of Personalised Medicine,” Euro-
pean Journal of Cancer, Vol. 49, No. 12, 2013, pp. 2619-
2620. http://dx.doi.org/10.1016/j.ejca.2013.04.020
[3] J. S. de Bono and A. Ashworth, “Translating Cancer Re-
search into Targeted Therapeutics,” Nature, Vol. 467, No.
7315, 2010, pp. 543-549.
http://dx.doi.org/10.1038/nature09339
[4] M. Kalia, “Personalized Oncology: Recent Advances and
Future Challenges,” Metabolism: Clinical and Experi-
mental, Vol. 62, No. Suppl 1, 2013, pp. S11-S14.
http://dx.doi.org/10.1016/j.metabol.2012.08.016
[5] S. A. Williams, W. C. Anderson, M. T. Santaguida and S.
J. Dylla, “Patient-Derived Xenografts, the Cancer Stem
Cell Paradigm, and Cancer Pathobiology in the 21st Cen-
tury,” Laboratory Investigation; A Journal of Technical
Methods and Pathology, Vol. 93, No. 9, 2013, pp. 970-
982.
[6] E. R. Mardis, “Genome Sequencing and Cancer,” Current
Opinion in Genetics & Development, Vol. 22, No. 3,
2012, pp. 245-250.
http://dx.doi.org/10.1016/j.gde.2012.03.005
[7] J. A. Baron, “Screening for Cancer with Molecular Mark-
ers: Progress Comes with Potential Problems,” Nature
Reviews. Cancer, Vol. 12, No. 5, 2012, pp. 368-371.
http://dx.doi.org/10.1038/nrc3260
[8] A. Prat and C. M. Perou, “Deconstructing the Molecular
Portraits of Breast Cancer,” Molecular Oncology, Vol. 5,
No. 1, 2011, pp. 5-23.
http://dx.doi.org/10.1016/j.molonc.2010.11.003
[9] R. Fisher, L. Pusztai and C. Swanton, “Cancer Heteroge-
neity: Implications for Targeted Therapeutics,” British
Journal of Cancer, Vol. 108, No. 3, 2013, pp. 479-485.
http://dx.doi.org/10.1038/bjc.2012.581
[10] M. J. Ellis and C. M. Perou, “The Genomic Landscape of
Breast Cancer as a Therapeutic Roadmap,” Cancer Dis-
covery, Vol. 3, No. 1, 2013, pp. 27-34.
[11] Cancer Genome Atlas Network, “Comprehensive Mole-
cular Portraits of Human Breast Tumours,” Nature, Vol.
490, No. 7418, 2012, pp. 61-70.
http://dx.doi.org/10.1038/nature11412
[12] M. F. Clarke, et al., “Cancer Stem Cells—Perspectives on
Current Status and Future Directions: AACR Workshop
on Cancer Stem Cells,” Cancer Research, Vol. 66, No. 19,
2006, pp. 9339-9344.
http://dx.doi.org/10.1158/0008-5472.CAN-06-3126
[13] C. A. O’Brien, A. Kreso and C. H. Jamieson, “Cancer
Stem Cells and Self-Renewal,” Clinical Cancer Research:
An Official Journal of the American Association for
Cancer Research, Vol. 16, No. 12, 2010, pp. 3113-3120.
[14] P. Valent, et al., “Cancer Stem Cell Definitions and Ter-
minology: The Devil Is in the Details,” Nature Reviews.
Cancer, Vol. 12, No. 11, 2012, pp. 767-775.
http://dx.doi.org/10.1038/nrc3368
[15] J. A. DiMasi and H. G. Grabowski, “Economics of New
Oncology Drug Development,” Journal of Clinical Onco-
logy: Official Journal of the American Society of Clinical
Oncology, Vol. 25, No. 2, 2007, pp. 209-216.
[16] J. J. Tentler, et al., “Patient-Derived Tumour Xenografts
as Models for Oncology Drug Development,” Nature Re-
views. Clinical Oncology, Vol. 9, No. 6, 2012, pp. 338-
350.
[17] T. Van Dyke, “Finding the Tumor Copycat: Approximat-
ing a Human Cancer,” Nature Medicine, Vol. 16, No. 9,
2010, pp. 976-977. http://dx.doi.org/10.1038/nm0910-976
[18] J. M. Reichert and J. B. Wenger “Development Trends
Open Access JCT

Evolution of Tumor Model: From Animal Model of Tumor to Tumor Model in Animal 1422
for New Cancer Therapeutics and Vaccines,” Drug Dis-
covery Today, Vol. 13, No. 1-2, 2008, pp. 30-37.
http://dx.doi.org/10.1016/j.drudis.2007.09.003
[19] L. M. Ellis and I. J. Fidler “Finding the Tumor Copycat.
Therapy Fails, Patients Don’t,” Nature Medicine, Vol. 16,
No. 9, 2010, pp. 974-975.
http://dx.doi.org/10.1038/nm0910-974
[20] D. Siolas and G. J. Hannon “Patient-Derived Tumor Xeno-
grafts: Transforming Clinical Samples into Mouse Mod-
els,” Cancer Research, Vol. 73, No. 17, 2013, pp. 5315-
5319. http://dx.doi.org/10.1158/0008-5472.CAN-13-1069
[21] K. Jin, et al., “Patient-Derived Human Tumour Tissue
Xenografts in Immunodeficient Mice: A Systematic Re-
view,” Clinical & Translational Oncology: Official Pub-
lication of the Federation of Spanish Oncology Societies
and of the National Cancer Institute of Mexico, Vol. 12,
No. 7, 2010, pp. 473-480.
[22] C. L. Morton and P. J. Houghton, “Establishment of Hu-
man Tumor Xenografts in Immunodeficient Mice,” Na-
ture Protocols, Vol. 2, No. 2, 2007, pp. 247-250.
http://dx.doi.org/10.1038/nprot.2007.25
[23] D. Decaudin, “Primary Human Tumor Xenografted Mod-
els (Tumorgrafts) for Good Management of Patients with
Cancer,” Anticancer Drugs, Vol. 22, No. 9, 2011, pp.
827-841.
http://dx.doi.org/10.1097/CAD.0b013e3283475f70
[24] F. Reyal, et al., “Molecular Profiling of Patient-Derived
Breast Cancer Xenografts,” Breast Cancer Research:
BCR, Vol. 14, No. 1, 2012, p. R11.
http://dx.doi.org/10.1186/bcr3095
[25] C. O. Povlsen, J. Visfeldt, J. Rygaard and G. Jensen,
“Growth Patterns and Chromosome Constitutions of Hu-
man Malignant Tumours after Long-Term Serial Trans-
plantation in Nude Mice,” Acta Pathologica et Microbi-
ologica Scandinavica. Section A, Pathology, Vol. 83, No.
6, 1975, pp. 709-716.
[26] S. Kopetz, R. Lemos and G. Powis, “The Promise of Pa-
tient-Derived Xenografts: The Best Laid Plans of Mice
and Men,” Clinical Cancer Research: An Official Journal
of the American Association for Cancer Research, Vol.
18, No. 19, 2012, pp. 5160-5162.
[27] S. Li, et al., “Endocrine-Therapy-Resistant ESR1 Vari-
ants Revealed by Genomic Characterization of Breast-
Cancer-Derived Xenografts,” Cell Reports, Vol. 4, No. 6,
2013, pp. 1116-1130.
[28] J. Mendelsohn, “Personalizing Oncology: Perspectives
and Prospects,” Journal of Clinical Oncology: Official
Journal of the American Society of Clinical Oncology,
Vol. 31, No. 15, 2013, pp. 1904-1911.
[29] Fiebig H-H & Burger AM (Human Tumor Xenografts
and Explants, Springer, 2002.
[30] A. Bertotti, et al., “A Molecularly Annotated Platform of
Patient-Derived Xenografts (Xenopatients) Identifies
HER2 as an Effective Therapeutic Target in Cetuximab-
Resistant Colorectal Cancer,” Cancer Discovery, Vol. 1,
No. 6, 2011, pp. 508-523.
[31] P. Kabos, et al., “Patient-Derived Luminal Breast Cancer
Xenografts Retain Hormone Receptor Heterogeneity and
Help Define Unique Estrogen-Dependent Gene Signa-
tures,” Breast Cancer Research and Treatment, Vol. 135,
No. 2, 2012, pp. 415-432.
http://dx.doi.org/10.1007/s10549-012-2164-8
[32] X. Zhang, et al., “A Renewable Tissue Resource of Phe-
notypically Stable, Biologically and Ethnically Diverse,
Patient-Derived Human Breast Cancer Xenograft Mod-
els,” Cancer Research, Vol. 73, No. 15, 2013, pp. 4885-
4897. http://dx.doi.org/10.1158/0008-5472.CAN-12-4081
[33] R. S. Kerbel, “Human Tumor Xenografts as Predictive
Preclinical Models for Anticancer Drug Activity in Hu-
mans: Better than Commonly Perceived, But They Can
Be Improved,” Cancer Biology & Therapy, Vol. 2, No. 4,
2003, pp. S134-S139.
[34] S. Oesterreich, A. M. Brufsky and N. E. Davidson, “Us-
ing Mice to Treat (Wo)men: Mining Genetic Changes in
Patient Xenografts to Attack Breast Cancer,” Cell Reports,
Vol. 4, No. 6, 2013, pp. 1061-1062.
[35] D. J. Monsma, et al., “Genomic Characterization of Ex-
plant Tumorgraft Models Derived from Fresh Patient Tu-
mor Tissue,” Journal of Translational Medicine, Vol. 10,
No. 1, 2012, p. 125.
http://dx.doi.org/10.1186/1479-5876-10-125
[36] M. Moro, G. Bertolini, M. Tortoreto, U. Pastorino, G.
Sozzi and L. Roz, “Patient-Derived Xenografts of Non
Small Cell Lung Cancer: Resurgence of an Old Model for
Investigation of Modern Concepts of Tailored Therapy
and Cancer Stem Cells,” Journal of Biomedicine & Bio-
Technology, Vol. 2012, No. 2012, 2012, Article ID:
568567. http://dx.doi.org/10.1155/2012/568567
[37] E. Marangoni, A. Vincent-Salomon, N. Auger, A. De-
georges, F. Assayag, P. de Cremoux, L. de Plater, C.
Guyader, G. De Pinieux, J. G. Judde, M. Rebucci, C.
Tran-Perennou, X. Sastre-Garau, B. Sigal-Zafrani, O.
Delattre, V. Diéras and M. F. Poupon, “A New Model of
Patient Tumor-Derived Breast Cancer Xenografts for Pre-
clinical Assays,” Clinical Cancer Research: An Official
Journal of the American Association for Cancer Research,
Vol. 13, No. 13, 2007, pp. 3989-3998.
[38] L. de Plater, A. Laugé, C. Guyader, M.-F. Poupon, F. As-
sayag, P. de Cremoux, A. Vincent-Salomon, D. Stoppa-Ly-
onnet, B. Sigal-Zafrani, J.-J. Fontaine, R. Brough, C. J. Lord,
A. Ashworth, P. Cottu, D. Decaudin and E. Marangoni,
“Establishment and Characterisation of a New Breast Can-
cer Xenograft Obtained from a Woman Carrying a Germ-
line BRCA2 Mutation,” British Journal of Cancer, Vol.
103, No. 8, 2010, pp. 1192-1200.
http://dx.doi.org/10.1038/sj.bjc.6605900
[39] A. Romanelli, A. Clark, F. Assayag, S. Chateau-Joubert,
M.-F. Poupon, J.-L. Servely, J.-J. Fontaine, X. H. Liu, E.
Spooner, S. Goodstal, P. de Cremoux, I. Bièche, D. De-
caudin and E. Marangon, “Inhibiting Aurora Kinases Re-
duces Tumor Growth and Suppresses Tumor Recurrence
after Chemotherapy in Patient-Derived Triple-Negative
Breast Cancer Xenografts,” Molecular Cancer Therapeu-
tics, Vol. 11, No. 12, 2012, pp. 2693-2703.
http://dx.doi.org/10.1158/1535-7163.MCT-12-0441-T
[40] P. Cottu, E. Marangoni, F. Assayag, P. de Cremoux, A. Vin-
cent-Salomon, Ch. Guyader, L. de Plater, C. Elbaz, N. Kar-
boul, J. J. Fontaine, S. Chateau-Joubert, P. Boudou-Rou-
Open Access JCT

Evolution of Tumor Model: From Animal Model of Tumor to Tumor Model in Animal 1423
quette, S. Alran, V. Dangles-Marie, D. Gentien, M.-F. Pou-
pon and D. Decaudin, “Modeling of Response to Endo-
crine Therapy in a Panel of Human Luminal Breast Can-
cer Xenografts,” Breast Cancer Research and Treatment,
Vol. 133, No. 2, 2012, pp. 595-606.
http://dx.doi.org/10.1007/s10549-011-1815-5
[41] Y. S. DeRose, K. M. Gligorich, G. Wang, A. Georgelas, P.
Bowman, S. J. Courdy, A. L. Welm, B. E. Welm, “Pa-
tient-Derived Models of Human Breast Cancer: Protocols
for in Vitro and in Vivo Applications in Tumor Biology
and Translational Medicine,” Current Protocols in Phar-
macology, 2013, Chapter 14: Unit 14 23.
[42] J. J. Wallin, J. Guan, W. W. Prior, L. B. Lee, L. Berry, L.
D. Belmont, H. Koeppen, M. Belvin, L. S. Friedman, D.
Sampath, “GDC-0941, a Novel Class I Selective PI3K
Inhibitor, Enhances the Efficacy of Docetaxel in Human
Breast Cancer Models by Increasing Cell Death in Vitro
and in Vivo,” Clinical Cancer Research: An Official Jour-
nal of the American Association for Cancer Research,
Vol. 18, No. 14, 2012, pp. 3901-3911.
[43] C. Ginestier, S. L. Liu, M. E. Diebel, H. Korkaya, M. Luo,
M. Brown, J. Wicinski, O. Cabaud, E. Charafe-Jauffret, D.
Birnbaum, J.-L. Guan, G. Dontu and M. S. Wicha, “CXCR1
Blockade Selectively Targets Human Breast Cancer Stem
Cells in Vitro and in Xenografts,” The Journal of Clinical
Investigation, Vol. 120, No. 2, 2010, pp. 485-497.
http://dx.doi.org/10.1172/JCI39397
[44] T. John, D. Kohler, M. Pintilie, N. Yanagawa, N. A.
Pham, M. Li, D. Panchal, F. Hui, F. Meng, F. A. Shep-
herd and M. S. Tsao, “The Ability to Form Primary Tu-
mor Xenografts Is Predictive of Increased Risk of Disease
Recurrence in Early-Stage Non-Small Cell Lung Cancer,”
Clinical Cancer Research: An Official Journal of the Ameri-
can Association for Cancer Research, Vol. 17, No. 1, 2011,
pp. 134-141.
[45] Fichtner I, J. Rolff, R. Soong, J. Hoffmann, S. Hammer,
A. Sommer, M. Becker and J. Merk, “Establishment of
Patient-Derived Non-Small Cell Lung Cancer Xenografts
as Models for the Identification of Predictive Biomark-
ers,” Clinical Cancer Research: An Official Journal of the
American Association for Cancer Research, Vol. 14, No.
20, 2008, pp. 6456-6468.
[46] X. Dong, J. Guan, J. C. English, J. Flint, J. Yee, K. Evans,
N. Murray, C. Macaulay, R. T. Ng, P. W. Gout, W. L. Lam,
J. Laskin, V. Ling, S. Lam and Y. Wang, “Patient-Derived
First Generation Xenografts of Non-Small Cell Lung
Cancers: Promising Tools for Predicting Drug Responses
for Personalized Chemotherapy,” Clinical Cancer Research:
An Official Journal of the American Association for Cancer
Research, Vol. 16, No. 5 , 2010, pp. 1442-1451.
[47] R. Krumbach, J. Schüler, M. Hofmann, T. Giesemann,
H.-H. Fiebig and T. Beckers, “Primary Resistance to Cetu-
ximab in a Panel of Patient-Derived Tumour Xenograft
Models: Activation of MET as One Mechanism for Drug
Resistance,” European Journal of Cancer, Vol. 47, No. 8,
2011, pp. 1231-1243.
http://dx.doi.org/10.1016/j.ejca.2010.12.019
[48] X. C. Zhang, J. C. Zhang, M. Li, X.-S. Huang, X.-N. Yang,
W.-Z. Zhong, L. Xie, L. Zhang, M. H. Zhou, P. Gavine, X.
Y. Su, L. Zheng, G. S. Zhu, P. Zhan, Q. S. Ji and Y.-L. Wu,
“Establishment of Patient-Derived Non-Small Cell Lung
Cancer Xenograft Models with Genetic Aberrations within
EGFR, KRAS and FGFR1: Useful Tools for Preclinical
Studies of Targeted Therapies,” Journal of Translational
Medicine, Vol. 11, 2013, p. 168.
http://dx.doi.org/10.1186/1479-5876-11-168
[49] M. Yang, B. Shan, Q. Li, X. Song, J. Cai, J. Deng, L.
Zhang, Z. Du, J. Lu, T. Chen, J. P. Wery, Y. Chen and Q.
Li, “Overcoming Erlotinib Resistance with Tailored Treat-
ment Regimen in Patient-Derived Xenografts from Naive
Asian NSCLC Patients,” International Journal of Cancer,
Vol. 132, No. 2, 2013, pp. E74-E84.
[50] A. Bertotti, et al., “A Molecularly Annotated Platform of
Pa- tient-Derived Xenografts (‘Xenopatients’) Identifies
HER2 as an Effective Therapeutic Target in Cetuxi-
mab-Resistant Colorectal Cancer,” Cancer Discovery, Vol.
1, 2011, pp. 508-523.
http://dx.doi.org/10.1158/2159-8290.CD-11-0109
[51] S. Julien, et al., “Characterization of a Large Panel of Pa-
tient-Derived Tumor Xenografts Representing the Clini-
cal Heterogeneity of Human Colorectal Cancer,” Clinical
Cancer Research: An Official Journal of the American
Association for Cancer Research, Vol. 18, No. 19, 2012,
pp. 5314-5328.
[52] H. B. Zhu, W. Zhou, J. Z. Hu, Z. T. Huang, W. F. Lao, X.
F. Huang and C. He, “Suppressing the Growth of Rectal
Cancer Xenografts Derived from Patient Tumors by an
Adenovector Expressing Small Hairpin RNA Targeting
Bcl-XL,” The Journal of Gene Medicine, Vol. 14, No. 12,
2012. pp. 761-768. http://dx.doi.org/10.1002/jgm.2681
[53] R. Toivanen, R. A. Taylor, D. W. Pook, S. J. Ellem and G.
P. Risbridger, “Breaking through a Roadblock in Prostate
Cancer Research: An Update on Human Model Systems,”
The Journal of Steroid Biochemistry and Molecular Bi-
ology, Vol. 131, No. 3-5, 2012, pp. 122-131.
http://dx.doi.org/10.1016/j.jsbmb.2012.01.005
[54] O. Raheem, A. A. Kulidjian, C. Wu, Y. B. Jeong, T. Ya-
maguchi, K. M. Smith, D. Goff, H. Leu, S. R. Morris, N. A
Cacalano, K. Masuda, C. H. M. Jamieson, C. J. Kane and C.
A. M. Jamieson, “A Novel Patient-Derived Intra-Femoral
Xenograft Model of Bone Metastatic Prostate Cancer that
Recapitulates Mixed Osteolytic and Osteoblastic Lesions,”
Journal of Translational Medicine, Vol. 9, 2011, p. 185.
http://dx.doi.org/10.1186/1479-5876-9-185
[55] A. Aparicio, V. Tzelepi, J. C. Araujo, C. C. Guo, S. D.
Liang, P. Troncoso, C. J. Logothetis, N. M. Navone and S.
N. Maity, “Neuroendocrine Prostate Cancer Xenografts with
Large-Cell and Small-Cell Features Derived from a Single
Patient’s Tumor: Morphological, Immunohistochemical, and
Gene Expression Profiles,” The Prostate, Vol. 71, No. 8,
2011, pp. 846-856.
http://dx.doi.org/10.1002/pros.21301
[56] T. Kimura, H. Kiyota1, D. Nakata, T. Masaki, Masami
Kusaka and S. Egawa, “A Novel Androgen-Dependent
Prostate Cancer Xenograft Model Derived from Skin
Metastasis of a Japanese Patient,” The Prostate, Vol. 69,
No. 15, 2009, pp. 1660-1667.
http://dx.doi.org/10.1002/pros.21016
[57] T. Yoshida, H. Kinoshita, T. Segawa, E. Nakamura, T.
Inoue, Y. Shimizu, T. Kamoto and O. Ogawa, “Antian-
Open Access JCT

Evolution of Tumor Model: From Animal Model of Tumor to Tumor Model in Animal 1424
drogen Bicalutamide Promotes Tumor Growth in a Novel
Androgen-Dependent Prostate Cancer Xenograft Model
Derived from a Bicalutamide-Treated Patient,” Cancer
Research, Vol. 65, No. 21, 2005, pp. 9611-9616.
http://dx.doi.org/10.1158/0008-5472.CAN-05-0817
[58] X. S. Li, Z. B. Liu, X. Xu, C. A. Blair, Z. Sun, J. Xie, M.
B. lilly and X. L. Zi, “Kava Components Down-Regulate
Expression of AR and AR Splice Variants and Reduce
Growth in Patient-Derived Prostate Cancer Xenografts in
Mice,” PLoS ONE, Vol. 7, No. 2, 2012, Article ID: e31213.
http://dx.doi.org/10.1371/journal.pone.0031213
[59] S. E. Yost, S. Pastorino, S. Rozenzhak, E. N. Smith, Y. S.
Chao, P. F. Jiang, S. Kesari, K. A. Frazer and O. Haris-
mendy, “High-Resolution Mutational Profiling Suggests
the Genetic Validity of Glioblastoma Patient-Derived
Pre-Clinical Models,” PLoS ONE, Vol. 8, No. 2, 2013,
Article ID: e56185.
http://dx.doi.org/10.1371/journal.pone.0056185
[60] M. A. Jarzabek, P. C. Huszthy, K. O. Skaftnesmo, E.
McCormack, P. Dicker, J. H.M. Prehn, R. Bjerkvig and A.
T. Byrne, “In Vivo Bioluminescence Imaging Validation
of a Human Biopsy-Derived Orthotopic Mouse Model of
Glioblastoma Multiforme,” Molecular Imaging, Vol. 12,
No. 3, 2013, pp. 161-172.
[61] K. H. Kim, H. J. Seol, E. H. Kim, J. Rheey, H. J. Jin, Y.
Lee, K. M. Joo, J. Lee and D.-H. Nam, “Wnt/Beta-Catenin
Signaling Is a Key Downstream Mediator of MET Sig-
naling in Glioblastoma Stem Cells,” Neuro-Oncology, Vol.
15, No. 2, 2013, pp. 161-171.
http://dx.doi.org/10.1093/neuonc/nos299
[62] H. Huynh, K. C. Soo, P. K. Chow, L. Panasci and E. Tran,
“Xenografts of Human Hepatocellular Carcinoma: A Use-
ful Model for Testing Drugs,” Clinical Cancer Research,
Vol. 12, 2006, pp. 4306-4314.
http://dx.doi.org/10.1158/1078-0432.CCR-05-2568
[63] M. Yan, H. Li, F. Y. Zhao, L. X. Zhang, C. Ge, M. Yao,
and J. J. Li, “Establishment of NOD/SCID Mouse Models
of Human Hepatocellular Carcinoma via Subcutaneous
Transplantation of Histologically Intact Tumor Tissue,”
Chinese Journal of Cancer Research, Vol. 25, No. 3,
2013, pp. 289-298.
[64] H. Huynh, V. C. Ngo, H. N. Koong, D. Poon, S. P. Choo,
H. C. Toh, C. H. Thng, P. Chow, H. S. Ong, A. Chung, B.
C. Goh, P. D. Smith and K. C. Soo, “AZD6244 Enhances
the Anti-Tumor Activity of Sorafenib in Ectopic and Or-
thotopic Models of Human Hepatocellular Carcinoma
(HCC),” Journal of Hepatology, Vol. 52, No. 1, 2010, pp.
79-87. http://dx.doi.org/10.1016/j.jhep.2009.10.008
[65] H. Huynh, V. C. Ngo, J. Fargnoli, M. Ayers, K. C. Soo, H.
N. Koong, C. H. Thng, H. S. Ong, A. Chung, P. Chow, P.
Pollock, S. Byron and E. Tran, “Brivanib Alaninate, a
Dual Inhibitor of Vascular Endothelial Growth Factor
Receptor and Fibroblast Growth Factor Receptor Tyro-
sine Kinases, Induces Growth Inhibition in Mouse Mod-
els of Human Hepatocellular Carcinoma,” Clinical Can-
cer Research, Vol. 14, 2008, pp. 6146-6153.
http://dx.doi.org/10.1158/1078-0432.CCR-08-0509
[66] H. Huynh, V. C. Ngo, S. P. Choo, D. Poon, H. N. Koong,
C. H. Thng, H. C. Toh, L. Zheng, L. C. Ong, Y. Jin, I. C.
Song, A. P.C. Chang, H. S. Ong, A. Y.F. Chung, P. K.H.
Chow and K. C. Soo, “Sunitinib (SUTENT, SU11248)
Suppresses Tumor Growth and Induces Apoptosis in
Xenograft Models of Human Hepatocellular Carcinoma,”
Current Cancer Drug Targets, Vol. 9, No. 6, 2009, pp.
738-747. http://dx.doi.org/10.2174/156800909789271530
[67] H. Huynh, K. H. P. Chow, K. C. Soo, H. C. Toh, S. P.
Choo, K. F. Foo, D. Poon, V, C. Ngo and E. Tran,
“RAD001 (Everolimus) Inhibits Tumour Growth in Xeno-
graft Models of Human Hepatocellular Carcinoma,” Journal
of Cellular and Molecular Medicine, Vol. 13, No. 7, 2009,
pp. 1371-1380.
http://dx.doi.org/10.1111/j.1582-4934.2008.00364.x
[68] C. Krepler, V. Wacheck, S. Strommer, G. Hartmann, P.
Polterauer, K. Wolff, H. Pehamberger and B. Jansen,
“CpG Oligonucleotides Elicit Antitumor Responses in a
Human Melanoma NOD/SCID Xenotransplantation Mo-
del,” The Journal of Investigative Dermatology, Vol. 122,
No. 2, 2004, pp. 387-391.
http://dx.doi.org/10.1046/j.0022-202X.2004.22202.x
[69] J. M. Pimiento, E. M. Larkin, K. S. M. Smalley, G. L.
Wiersma, N. R. Monks, I. V. Fedorenko, C. A. Peterson
and B. J. Nickoloff, “Melanoma Genotypes and Pheno-
types Get Personal,” Laboratory Investigation, Vol. 93,
No. 8, 2013, pp. 858-867.
[70] P. Guerreschi, C. Scalbert, A. Qassemyar, J. Kluza, L.
Ravasi, D. Huglo, V. Martinot-Duquennoy, P. Formstecher,
P. Marchetti and L. Mortier, “Patient-Derived Tumor Xe-
nograft Model to Guide the Use of BRAF Inhibitors in
Metastatic Melanoma,” Melanoma Research, Vol. 23, No.
5, 2013, pp. 373-380.
http://dx.doi.org/10.1097/CMR.0b013e328363ed92
[71] C. Laurent, D. Gentien, S. Piperno-Neumann, F. Némati, A.
Nicolas, B. Tesson, L. Desjardins, P. Mariani, A. Rapinat,
X. Sastre-Garau, J. Couturier, P. Hupé, L. de Koning, T.
Dubois, S. Roman-Roman, M. H. Stern, E. Barillot, J. W.
Harbour, S. Saule and D. Decaudin, “Patient-Derived Xeno-
grafts Recapitulate Molecular Features of Human Uveal
Melanomas,” Molecular Oncology, Vol. 7, No. 3, 2013,
pp. 625-636.
http://dx.doi.org/10.1016/j.molonc.2013.02.004
[72] F. Nemati, X. Sastre-Garau, C. Laurent, J. Couturier, P.
Mariani, L. Desjardins, S. Piperno-Neumann, O. Lantz, B.
Asselain, C. Plancher, D. Robert, I. Péguillet, M. H. Don-
nadieu, A. Dahmani, M. A. Bessard, D. Gentien, C.
Reyes, S. Saule, E. Barillot, S. Roman-Roman and D.
Decaudin, “Establishment and Characterization of a Panel
of Human Uveal Melanoma Xenografts Derived from
Primary and/or Metastatic Tumors,” Clinical Cancer Re-
search: An Official Journal of the American Association
for Cancer Research, Vol. 16, No. 8, 2010, pp. 2352-
2362.
[73] P. C. Gach, P. J. Attayek, G. Herrera, J. J. Yeh and N. L.
Allbritton, “Isolation and in Vitro Culture of Rare Cancer
Stem Cells from Patient-Derived Xenografts of Pancreatic
Ductal Adenocarcinoma,” Analytical Chemistry, Vol. 85,
No. 15, 2013, pp. 7271-7278.
http://dx.doi.org/10.1021/ac401165s
[74] D. M. Walters, J. M. Lindberg, S. J. Adair, T. E. New-
hook, C. R. Cowan, J. B. Stokes, C. A. Borgman, E. B.
Stelow, B. T. Lowrey, M. E. Chopivsky, T. M. Gilmer, J.
Open Access JCT

Evolution of Tumor Model: From Animal Model of Tumor to Tumor Model in Animal
Open Access JCT
1425
T. Parsons and T. W. Bauer, “Inhibition of the Growth of
Patient-Derived Pancreatic Cancer Xenografts with the
MEK Inhibitor Trametinib Is Augmented by Combined
Treatment with the Epidermal Growth Factor Receptor/
HER2 Inhibitor Lapatinib,” Neoplasia, Vol. 15, No. 2,
2013, pp. 143-155.
[75] N. V. Rajeshkumar, Z. A. Rasheed, E. García-García, F.
López-Ríos, K. Fujiwara, W. H. Matsui1 and M. Hidalgo,
“A Combination of DR5 Agonistic Monoclonal Antibody
with Gemcitabine Targets Pancreatic Cancer Stem Cells
and Results in Long-Term Disease Control in Human
Pancreatic Cancer Model,” Molecular Cancer Therapeu-
tics, Vol. 9, No. 9, 2010, pp. 2582-2592.
http://dx.doi.org/10.1158/1535-7163.MCT-10-0370
[76] M. P. Kim, M. J. Truty, W. Choi, Y. Kang, X. Chopin-
Lally, G. E. Gallick, H. Wang, D. J. McConkey, R.
Hwang, C. Logsdon, J. Abbruzzesse and J. B. Fleming,
“Molecular Profiling of Direct Xenograft Tumors Estab-
lished from Human Pancreatic Adenocarcinoma after
Neoadjuvant Therapy,” Annals of Surgical Oncology, Vol.
19, No. Suppl. 3, 2012, pp. 395-403.
http://dx.doi.org/10.1245/s10434-011-1839-4
[77] P. C. Hermann, et al., “Multimodal Treatment Eliminates
Cancer Stem Cells and Leads to Long-Term Survival in
Primary Human Pancreatic Cancer Tissue Xenografts,”
PLoS ONE, Vol. 8, No. 6, 2013, Article ID: e66371.
http://dx.doi.org/10.1371/journal.pone.0066371
[78] A. Jimeno, G. Feldmann, A Suárez-Gauthier, Z. Rasheed,
A. Solomon1, G.-M. Zou, B. Rubio-Viqueira, E. García-
García, F. López-Ríos, W. Matsui, A. Maitra1 and M.
Hidalgo, “A Direct Pancreatic Cancer Xenograft Model
as a Platform for Cancer Stem Cell Therapeutic Devel-
opment,” Molecular Cancer Therapeutics, Vol. 8, No. 2,
2009, pp. 310-314.
http://dx.doi.org/10.1158/1535-7163.MCT-08-0924
[79] T. Hoey, W.-C. Yen, F. Axelrod, J. Basi, L. Donigian, S.
Dylla, M. Fitch-Bruhns, S. Lazetic, I.-K. Park, A. Sato, S.
Satyal, X. H. Wang, M. F. Clarke, J. Lewicki and A.
Gurney, “DLL4 Blockade Inhibits Tumor Growth and
Reduces Tumor-Initiating Cell Frequency,” Cell Stem
Cell, Vol. 5, No. 2, 2009, pp. 168-177.
http://dx.doi.org/10.1016/j.stem.2009.05.019