A historical perspective of pancreatic cancer mouse models.

G Model

ARTICLE IN PRESS

YSCDB 1543 1–10

Seminars in Cell & Developmental Biology xxx (2014) xxx–xxx

Contents lists available at ScienceDirect

Seminars in Cell & Developmental Biology journal homepage: www.elsevier.com/locate/semcdb

1

Review

2

A historical perspective of pancreatic cancer mouse models

3 4 5 6 7

Q1

Emily K. Colvin a,∗ , Christopher J. Scarlett b a Bill Walsh Translational Cancer Research Laboratory, Kolling Institute of Medical Research, University of Sydney, Royal North Shore Hospital, St Leonards, NSW, Australia b Pancreatic Cancer Research, Nutrition, Food and Health Research Group, School of Environmental and Life Sciences, University of Newcastle, Ourimbah, NSW, Australia

8

9 19

a r t i c l e

i n f o

a b s t r a c t

10 11 12

Article history: Available online xxx

13

18

Keywords: Pancreatic cancer Mouse models Genetically engineered mouse models Patient-derived xenografts

20

Contents

14 15 16 17

21 22 23

1. 2. 3.

24 25 26 27 28 29 30 31 32 33

4. 5.

Pancreatic cancer is an inherently aggressive disease with an extremely poor prognosis and lack of effective treatments. Over the past few decades, much has been uncovered regarding the pathogenesis of pancreatic cancer and the underlying genetic alterations necessary for tumour initiation and progression. Much of what we know about pancreatic cancer has come from mouse models of this disease. This review focusses on the development of genetically engineered mouse models that phenotypically and genetically recapitulate human pancreatic cancer, as well as the increasing use of patient-derived xenografts for preclinical studies and the development of personalised medicine strategies. © 2014 Published by Elsevier Ltd.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Early attempts to model pancreatic cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Genetically engineered mouse models of pancreatic cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Mouse models of PDAC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.1. Kras models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.2. Common genetic alterations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.3. Developmental signalling pathways . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.4. Models of familial PDAC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.5. Models of random mutagenesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Mouse models of PNETs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Patient derived xenografts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

00 00 00 00 00 00 00 00 00 00 00 00 00

34

35

36 37 38 39 40 41

1. Introduction Pancreatic cancer is an aggressive malignancy and represents the 4th leading cause of cancer death, with a 5-year survival rate of approximately 5% [1]. Despite a greater understanding of the molecular characteristics of this cancer, overall patient survival has not improved for several decades. Surgical resection still remains the only potential curative treatment, however at the

∗ Corresponding author. Tel.: +61 2 9926 4846. E-mail addresses: [email protected] (E.K. Colvin), [email protected] (C.J. Scarlett).

time of diagnosis, less than 20% of patients are suitable for surgery. Treatment options are limited and largely ineffective [2,3]. Pancreatic cancer comprises several histological variants, the most common being pancreatic ductal adenocarcinoma (PDAC), which accounts for over 85% of all pancreatic malignancies. Other types of pancreatic cancers include acinar cell carcinoma, pancreatic neuroendocrine tumours and undifferentiated carcinoma. PDAC arises from well-characterised precursor lesions, the most common being pancreatic intraepithelial neoplasia (PanIN) [4,5], but also including intraductal papillary mucinous neoplasms (IPMN) [5] and mucinous cystic neoplasms (MCN) [6]. PanINs can be sub-classified into PanIN-1A, PanIN-1B, PanIN-2 and PanIN-3 based of the degree of cytological and architectural atypia and are known

http://dx.doi.org/10.1016/j.semcdb.2014.03.025 1084-9521/© 2014 Published by Elsevier Ltd.

Please cite this article in press as: Colvin EK, Scarlett CJ. A historical perspective of pancreatic cancer mouse models. Semin Cell Dev Biol (2014), http://dx.doi.org/10.1016/j.semcdb.2014.03.025

42 43 44 45 46 47 48 49 50 51 52 53 54

G Model YSCDB 1543 1–10 2 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81

82

83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117

ARTICLE IN PRESS E.K. Colvin, C.J. Scarlett / Seminars in Cell & Developmental Biology xxx (2014) xxx–xxx

to demonstrate many of the same genetic alterations seen in PDAC, with the prevalence of these alterations increasing with the degree of PanIN [5]. Activating KRAS mutations represent the most common and well-characterised genetic alteration in PDAC, occurring in >95% of cases, mainly via point mutations in codon 12 [7,8]. KRAS mutations occur in early PanIN lesions and represent a potential initiating factor for this disease. The other most common genetic events in PDAC are inactivation of the tumour suppressors CDKN2A (P16INK4A) [9,10], TP53 [11,12] and SMAD4 [13] occuring in >95%, 50–75% and 55% of patients, respectively. Recent PDAC sequencing efforts have identified many other genetic alterations that occur at much lower frequencies and highlight the genetic complexity of this malignancy [14,15]. Interestingly, despite the large number of somatic mutations identified in PDAC, these alterations can be associated with 12 core signalling pathways [15]. Many genetically engineered mouse models (GEMMs) have been developed that closely recapitulate several pancreatic cancer subtypes. These models have proven useful in identifying the molecular drivers of pancreatic tumour initiation and progression as well as providing a relevant system for developing and testing novel therapeutic strategies. Xenograft models, in particular patient-derived xenografts, are also proving to be an extremely valuable tool in evaluating novel treatment strategies in the era of personalised medicine. This review provides an overview of the major pancreatic cancer GEMMs as well as highlights the increasing use of patient-derived xenograft models of pancreatic cancer.

2. Early attempts to model pancreatic cancer Early attempts to model pancreatic cancer began in the 1980s when technologies for generating transgenic mice carrying oncogenes were developed. These early models utilised the Elastase promoter or the rat insulin promoter (RIP) to drive expression of the viral oncogene SV40 in acinar cells and ␤-cells of the mouse pancreas, respectively. RIP-Tag mice developed insulinomas (discussed below) and Elastase-SV40 mice developed acinar cell carcinomas [16–19]. Elastase-SV40 mice also developed islet cell tumours and somatostatin-cell hyperplasia, but did not develop PanINs or PDAC. Further attempts to produce transgenic mouse models also used the elastase promoter to overexpress human oncogenes in the mouse pancreas. In 1987, Quaife et al. overexpressed normal and mutant H-ras using the elastase promoter [20]. Mice expressing normal H-ras developed acinar cell hyperplasia and dysplasia, while the majority of mice expressing mutant H-ras died as newborns; those that survived were mosaic for H-ras and died of pancreatic tumours between 1.5 and 14 months. Overexpression of TGF-˛ in acinar cells did not induce pancreatic tumours, however mice did develop lesions resembling acinar-to-ductal metaplasia and pancreatic fibrosis, and was one of the first mouse models to suggest an acinar cell origin for PDAC [21,22]. In 1991, Sandgren et al. published an elastase-cmyc transgenic mouse model. These mice developed tumours with a mixed acinar/ductal histology between 2 and 7 months of age, however the ductal features were not observed until later stages of tumour development, and no PanINs were seen in this model [23]. In 2003, Grippo et al. overexpressed a common activating mutation of Kras in pancreatic acinar cells [24]. Surviving mice developed multifocal acinar cell hyperplasia and less commonly the formation of tubular complexes. In older mice, acinar to ductal metaplasia and early PanIN lesions were also observed. While no tumours developed in these mice, this model did demonstrate that activating Kras in acinar cells could result in the development of PDAC precursors and suggested additional genetic events may be required for pancreatic tumorigenesis.

3. Genetically engineered mouse models of pancreatic cancer 3.1. Mouse models of PDAC Many GEMMs of pancreatic cancer have been developed and this review focusses on models that have been developed to recapitulate the most well-known genetic aberrations found in human pancreatic cancer. These models are summarised in Table 1.

3.1.1. Kras models A breakthrough in developing GEMMs of PDAC occurred with the advent of the LSL-KrasG12D mouse [25]. This mouse harbours a knockin mutant Kras allele containing a glycine to aspartic acid transition in codon 12, upstream of which resides a conditional STOP cassette flanked by LoxP sites, preventing expression of the mutant allele. When combined with a tissue-specific Cre recombinase, the STOP cassette is excised resulting in constitutive activation of Kras at physiological levels. This mutation represents the most common activating Kras mutation seen in human PDAC. Hingorani et al. targeted this mutation to pancreatic progenitor cells by crossing LSL-KrasG12D mice with transgenic mice expressing a bacterial Cre recombinase under control of either the Pdx1 or Ptf1a (P48) promoters [26]. The resulting mice developed the full spectrum of PanIN lesions, which progressed with age. A proportion of these mice went on to develop metastatic tumours resembling human PDAC after a long latency (>12 months). Lesions in these mice expressed similar markers to human PDAC, including the Notch signalling target Hes1, COX2 and MMP7. This model demonstrated that activation of Kras is sufficient to induce precursors to PDAC and in some instances progress to invasive and metastatic PDAC and has since become the backbone for the development of many other mouse models of PDAC. One of the limitations of the LSL-KrasG12D ; Pdx1-Cre (also known as the KC) model is that Kras activation is targeted to the embryonic pancreas, with PanINs developing shortly after birth. However, PDAC occurs in older individuals through stochastic mutations in adult pancreas. Guerra et al. developed a model that allowed temporal control of Kras activation in the pancreas using a Tet-off system [27]. Similar to the KC model, when Kras was activated in the developing pancreas at E16.5, Kras+/LSL-G12VGeo; Elas-tTA/tetOCre mice developed acinar to ductal metaplasia progressing to high-grade PanINs by 12 months of age, a proportion of which went on to form PDAC after a long latency. However, activation of Kras in 10 day-old mice significantly delayed the formation of PanINs and reduced the incidence of PDAC. Importantly, activation of Kras in adult mice had no effect at all in acinar cells, indicating that mature acinar cells are resistant to transformation by oncogenic Kras. Invasive PDAC could be induced in these mice when treated with caerulein to induce chronic pancreatitis, indicating that pancreatitis increases the pool of cells susceptible to transformation by KrasG12V , potentially acinar precursors. In addition, this model supports the link between pancreatitis and an increased risk of developing PDAC, and provides a valuable model for investigating the role of pancreatitis-induced inflammation in tumorigenesis. While these models have demonstrated that targeting mutant Kras to the mouse pancreas is sufficient to induce PDAC in mice, the incomplete penetrance and long latency observed in these models suggested that additional genetic events could increase the incidence of tumours in mice and accelerate tumour progression. Since the generation of these Kras-induced PDAC models, many other models have been developed combining Kras mutations with other genes that are purported to be drivers of PDAC.


118 119

120

121 122 123 124

125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179

G Model

ARTICLE IN PRESS

YSCDB 1543 1–10

E.K. Colvin, C.J. Scarlett / Seminars in Cell & Developmental Biology xxx (2014) xxx–xxx

3

Table 1 GEMMs of pancreatic cancer. Model Kras models LSL-KrasG12D ; Pdx1-Cre LSL-KrasG12D ; Ptf1a-Cre Kras+/LSL-G12VGeo; Elas-tTA/tetOCre

Common genetic alterations Pdx1-Cre; LSL-KrasG12D ; Ink4a/Arflox/lox Kras+/LSL-G12VGeo; Elas-tTA/tetOCre; Ink4alox/lox Pdx1-Cre; LSL-KrasG12D ; Ink4a/Arflox/lox Pdx1-Cre; LSL-KrasG12D ; Trp53lox/lox ; Ink4a/Arflox/lox LSL-KrasG12D ; Trp53R172H ; Pdx1-Cre LSL-KrasG12D ; Trp53lox/+ ; Pdx1-Cre Pdx1-Cre; LSL-KrasG12D ; Smad4lox/lox Ptf1a-Cre; LSL-KrasG12D ; Smad4lox/lox Developmental signalling pathways Pdx1-Shh Pdx1-Cre; CLEG2 Pdx1-Cre; LSL-KrasG12D ; CLEG2 Ptf1a-Cre; LSL-KrasG12D ; Trp53lox/+ ; Smolox/lox Pdx1-Cre; LSL-KrasG12D ; SmoM2 Pdx1-CreERT ; LSL-KrasG12D ; Rosa26NIC Ptf1a-Cre; LSL-KrasG12D ; Notch1lox/lox Ptf1a-Cre; LSL-KrasG12D ; Notch2lox/lox Ptf1a-Cre; ␤-cateninactive Ptf1a-Cre; LSL-KrasG12D ; ␤-cateninactive Ptf1a-Cre; LSL-KrasG12D ; Rosa26rtTA; TetO-Dkk1 Familial pancreatic cancer models Pdx1-Cre; LSL-KrasG12D ; Brca2Tr/11 Pdx1-Cre; LSL-KrasG12D ; Trp53R270H ; Brca2Tr/11 Pdx1-Cre; LSL-KrasG12D ; Brca211/11 Pdx1-Cre; Trp53lox/lox ; Brca211/11 Pdx1-Cre; Brca2lox/lox Pdx1-Cre; Lkb1lox/lox Pdx1-Cre; LSL-KrasG12D ; Lkb1lox/lox Random mutagenesis models Pdx1-Cre; LSL-KrasG12D ; T2Onc3/+; LSL-SB11/+ Pdx1-Cre; LSL-KrasG12D ; T2Onc/+; LSL-SB13/+ PNET models RIP-Tag Glucagon-SV40 Pdx1-Cre; Men1lox/lox

180 181 182 183 184 185 186

187 188 189 190 191 192 193 194 195 196 197 198

Phenotype

PanINs

Mets

References

Metastatic PDAC in a proportion of mice after a long latency Metastatic PDAC in a proportion of mice after a long latency When activated early, develop PDAC after a long latency. Chronic pancreatitic required for tumour formation when Kras activated in the adult mouse

Yes

Yes

[26]

Yes

Yes

[26]

Yes

No

[27]

Metastatic and poorly differentiated PDAC by 11 weeks Pancreatic tumours with sarcomatoid and anaplastic histology Poorly differentiated PDAC with sarcomatoid features PDAC with anaplastic histology Well-differentiated PDAC Well-differentiated PDAC IPMN resembling the gastric subtype and PDAC MCN and PDAC

Yes Yes

Yes Yes

[28] [30]

Yes Yes Yes Yes Yes Only low-grade

Yes Yes Yes No Yes Yes

[29] [29] [31] [38] [39,40] [41]

Early PanIN lesions Undifferentiated pancreatic tumours PanIN and undifferentiated pancreatic tumours No additional phenotype compared to Ptf1a-Cre; LSL-KrasG12D ; Trp53lox/+ mice No additional phenotype compared to Pdx1-Cre; LSL-KrasG12D mice Increased PanIN formation Increased PanIN formation and tumour progression Decreased PanIN formation, development of MCNs and increased survival Solid pseudopapillary tumours Addition of ␤-catenin blocks PanIN formation, tumours resemble cribriform and intraductal lobular tumours Inhibited PanIN formation and tumour progression

Only low-grade No Yes N/A

No No No N/A

[42] [43] [43] [45]

N/A

N/A

[46]

Yes Yes Yes

N/A Yes Yes

[49] [51] [52]

No No

No N/A

[57] [57]

Yes

Yes

[59]

Accelerated PDAC development Accelerated PDAC development Inhibited PanIN and PDAC development Accelerated PDAC development PDAC development after a long latency (>15 months) Serous cystadenomas Accelerated PDAC development and promoted a cystic morphology in some tumours

Yes Yes Rare Yes Yes No Yes

Yes Yes N/A N/A Yes No N/A

[62] [62] [63] [63] [64] [66] [67]

Accelerated PDAC development Accelerated PDAC development

Yes Yes

Yes Yes

[69] [70]

Insulinomas Glucagonomas Insulinomas

No No No

No N/A N/A

[71] [72–75] [89–91]

3.1.2. Common genetic alterations Inactivation of the tumour suppressor genes CDKN2A (INK4A/ARF), TP53 and SMAD4 represent the most common genetic aberrations in human PDAC behind activating KRAS mutations. However, inactivation of each these genes alone in the mouse pancreas results in no phenotype and must be combined with mutant Kras to induce PDAC, as described below. 3.1.2.1. Ink4A/Arf. Like KRAS mutations, loss of function of INK4A is an almost universal event in human PDAC and occurs in moderately advanced PanIN lesions [9,10]. Several models examining the role of loss of INK4A and the associated tumour suppressor gene ARF have been developed. When combined with Kras mutation, conditional deletion of p16Ink4a and p19Arf in the pancreas using Pdx1-Cre dramatically increases the progression of PDAC in mice, with all mice succumbing to PDAC by 11 weeks of age [28]. Another model developed by Bardeesy et al. also demonstrated that loss of p16Ink4a, with or without p19Arf loss cooperate with mutant Kras in the mouse to promote pancreatic tumorigenesis [29]. p16Ink4a/p19Arf deficiency was found to promote pancreatic

tumours with sarcomatoid morphology, whereas p53 deficiency promoted the formation of well-differentiated adenocarcinomas. Heterozygous loss of these tumour suppressor genes increased the latency to tumour formation, but also increased the incidence of metastasis. In order to investigate the effect of loss of p16/p19 in adult pancreatic acinar cells, Guerra et al. crossed their Kras+/LSLG12VGeo; Elas-tTA/tetOCre model with mice lacking p16/p19 and activated the conditional alleles in adult mice [30]. When pancreatitis was induced with caerulein, loss of p16/p19 was shown to accelerate the formation of PanINs and the development of pancreatic tumours. Loss of p16/p19 was also shown to promote the formation of tumours with sarcomatoid and anaplastic features. These mouse models all support a role for loss of INK4A in PDAC progression. 3.1.2.2. Trp53. TP53 mutations occur in 50–75% of human PDAC [11,12]. When the KC model was crossed with mice harbouring a conditional LSL-TrpR172H allele, mice displayed a marked decrease in tumour latency, with a median survival of 5 months and an increase in metastasis to the most common sites of human PDAC


199 200 201 202 203 204 205 206 207 208 209 210 211 212

213 214 215 216 217

G Model YSCDB 1543 1–10 4 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245

246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267

268 269 270 271 272

273 274 275 276 277 278 279 280


metastasis: the liver, lung and peritoneum [31]. Mice developed the full spectrum of PanIN lesions and tumours resembled desmoplastic well-differentiated human PDAC. One of the advantages of this model as a model for human PDAC, is that tumours displayed marked molecular heterogeneity and genomic instability, specifically chromosomal instability, both features of human PDAC that are absent from most other mouse models. Due to the many similarities to human PDAC, LSL-KrasG12D ; LSL-Trp53R172H ; Pdx1-Cre mice, (now commonly known as KPC mice) represent the most commonly used mouse model of PDAC and have subsequently been used in many studies. Unlike xenografts and allografts derived from cell lines, KPC mice are resistant to gemcitabine and represent an excellent model for preclinical testing of novel drugs [32–34]. Also, because tumours are autochthonous and occur in an immunocompetent animal, KPC mice are also proving useful for chemoprevention and immunotherapy studies [35–37]. The importance of mutant Trp53 in this model has been investigated further by Morton et al. when they compared the effects of mutant Trp53 versus p53 deficiency [38]. Firstly, they demonstrated that in the KC model, many KrasG12D -expressing cells are lost in the pancreas, with those that survive contributing to the formation of premalignant lesions. Both mutant Trp53 or p53 deficiency promote Kras-induced tumorigenesis by allowing retention of KrasG12D -positive cells. While there was no significant difference in tumour latency between mutant Trp53 mice versus p53-null mice, only mice expressing mutant Trp53 demonstrated metastasis, indicating the importance of the gain-of-function properties of mutant Trp53 in PDAC. 3.1.2.3. SMAD4. The tumour supressor gene SMAD4 is a central effector of the TGF-␤ signalling pathway and is inactivated in approximately 55% of human PDAC [13]. When crossed with KC mice, loss of Smad4 resulted in decreased survival, promoted the formation of PanINs and the development of tumours resembling the gastric subtype of IPMN [39]. Given that the majority of human PDAC displays inactivation of INK4A, the authors also examined the effect of loss of Smad4 in mice harbouring Kras mutations and loss of p16Ink4a/p19Arf and found that loss of Smad4 accelerated tumour formation and promoted a well-differentiated histology, indicating that active TGF-ˇ/SMAD4 signalling could contribute to a loss of epithelial differentiation in PDAC. Another group also demonstrated that mutant Kras combined with loss of Smad4 leads to the development of PanIN and IPMN in mice, as well as chronic pancreatitis [40]. These mice also developed gastric tumours, consistent with the foregut expression of Pdx1. In order to circumvent this, a third group used the Ptf1a-cre promoter to drive mutant Kras and inactivate Smad4 in the developing pancreas. In this model, loss of Smad4 was shown to promote the formation of mucinous cystic lesions resembling human MCN, including the characteristic “ovarian” type stroma [41]. 3.1.3. Developmental signalling pathways Signalling pathways essential for embryonic pancreas development (Hedgehog, Notch and Wnt) have also been heavily implicated in the development of PDAC. Their role in human PDAC has been supported using several mouse models. 3.1.3.1. Hedgehog. Aberrant overexpression of the sonic hedgehog (SHH) ligand is present in 70% of human PDAC [42] and several mouse models investigating the role of hedgehog signalling in pancreatic carcinogenesis have been developed. Initial evidence for a causal role of activated hedgehog signalling in PDAC development came by transgenic overexpression of Shh using the Pdx-1 promoter [42]. Pdx1-Shh mice develop early PanIN lesions, however due to disrupted epithelial-mesenchymal signalling normal

pancreatic development in these mice is severely affected, leading to a decreased life-span. Conditional activation of CLEG2, a dominant active form of the GLI2 transcription factor and a downstream mediator of hedgehog signalling, leads to activation of hedgehog signalling in the pancreatic epithelium and normal pancreatic organogenesis [43]. 30% of Pdx1-cre;CLEG2 mice develop pancreatic tumours, however they were undifferentiated and do not form PanINs. When crossed with mutant Kras, PanINs did develop and there was a decrease in tumour latency, however tumours remained undifferentiated. Using pancreatic cancer cell line xenograft models, Yauch et al. has demonstrated a paracrine requirement for Hedgehog signalling in pancreatic cancer [44]. This was further supported in GEMMs that used conditional deletion of the Smoothened receptor in the pancreatic epithelium to demonstrate that this had no effect at any stage of tumour progression in Ptf1a-Cre; LSL-KrasG12D ; Trp53F/+ mice [45]. Similarly, constitutive activation of Smoothened in Pdx1-cre; LSL-KrasG12D ; SmoM2 mice had no effect of pancreatic development or neoplasia [46], further supporting that the pancreatic epithelium is unresponsive to activated hedgehog signals. The authors of this study confirmed this by crossing two pancreatic cancer mouse models, KC and Pdx1cre; LSL-KrasG12D ; Ink4a/Arffl/fl models, with Ptc-lacZ reporter mice and demonstrated activation of hedgehog signalling was absent in tumour epithelium but present in the surrounding stromal cells. Treatment of KPC mice with the smoothened inhibitor IPI-926 was shown to target the tumour stroma, rather than the tumour cells, and most importantly, was able to enhance intra-tumoural delivery of gemcitabine and other chemotherapies by decreasing the fibroblastic component of tumours and transiently increasing the density of the tumour vasculature allowing and increased concentration of gemcitabine to tumour cells [34]. These mouse models have proven instrumental in demonstrating the importance of hedgehog signalling in the PDAC tumour microenvironment and shed light on potential approaches to successfully target this pathway in PDAC patients. 3.1.3.2. Notch. Like hedgehog, Notch signalling is essential for embryonic pancreatic development and is aberrantly reactivated in PDAC [47,48]. Several mouse models have been developed to elucidate the function of activated Notch signalling in PDAC. In order to investigate the role of Notch in tumorigenesis, De La O et al. crossed a Cre-dependent Notch1 gain-of-function transgene mouse (Rosa26NIC ) with LSL-KrasG12D mice [49]. To prevent the lethality observed in Pdx1-Cre;Rosa26NIC mice due to the absence of islet differentiation [50], the authors used a Pdx1-CreERT inducible transgene to generate mosaic pancreata. LSL-KrasG12D ; Rosa26NIC ; Pdx1-CreERT mice demonstrated a marked increase in PanIN formation compared to LSL-KrasG12D ; Pdx1-CreERT mice. They also used an Ela-CreERT inducible transgene to examine the effect of activated Notch signalling in adult acinar cells with similar results. In contrast, another study conditionally knocked out Notch1 in the KC model to find that loss of Notch1 combined with activated Kras leads to an increase in PanIN formation and tumour progression, implying that Notch1 can act as a tumour suppressor gene [51]. There are several possible reasons for the observed differences between these studies including a difference in the target cells and the timing of recombination, as well as the limited physiological relevance of using constitutively active transgenes. However, it is becoming increasingly recognised that Notch signalling can have both oncogenic and tumour suppressive functions in many cancer types. A third study examined the function of Notch1 and Notch2 in the KC model and found that deletion of Notch1 decreased survival, although not significantly, however loss of Notch2 led to a decrease in PanIN progression, the development of MCN-like lesions and a prolonged survival [52], supporting dual roles for Notch signalling in PDAC.


281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315

316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344

G Model YSCDB 1543 1–10


345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390

391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409

3.1.3.3. Wnt. Canonical Wnt signalling is also implicated in PDAC with nuclear accumulation of ␤-catenin occurring in a subset of human PanIN lesions and PDAC [53–55]. Pancreas specific inactivation of Apc, an inhibitor of ˇ-catenin, results in pancreatomegaly from 3 weeks of age due to acinar cell hyperplasia, but mice do not form tumours [56]. Conditional activation of ˇ-catenin in the pancreas led to the development of solid pseudopapillary tumours (SPTs) and expressed similar markers to human SPTs [57]. Stabilisation of ˇ-catenin is also a common feature of human SPTs. Interestingly, when combined with mutant Kras, activated ˇ-catenin was able to completely block PanIN formation [57]. In addition, Ptf1a-Cre; ␤-catactive ; LSL-KrasG12D displayed an increase in desmoplasia and the formation of tumours resembling rare human intraductal lobular tumours. The ability of activated ˇ-catenin to block Kras-induced PanIN and PDAC development was confirmed in another study by Morris et al. This study used caerulein-induced pancreatitis to demonstrate that active ˇ-catenin signalling is required for efficient acinar regeneration, whereas Kras blocks acinar regeneration and promotes acinar to ductal metaplasia and PanIN formation [58]. When combined with mutant Kras, ˇ-catenin inhibited the development of PanINs. The results of these studies suggest that ˇ-catenin mutations may be absent in the majority of PDAC due to the antagonism with the role of Kras in PDAC initiation. However, a recent study has demonstrated that Wnt signalling may indeed play a role in PDAC initiation. Rather than conditionally overexpressing ˇcatenin above physiological levels, the authors inactivated it in the Ptf1a-Cre; LSL-KrasG12D model. Ptf1a-Cre; LSL-KrasG12D ; ␤cateninfl/fl mice, which lack a functional ␤-catenin protein, are mosaic for ␤-catenin-expressing cells [59]. It was found that acinar to ductal metaplasia and PanINs only consisted of ␤-catenin positive cells. They also created another model allowing conditional inducible expression of the Wnt inhibitor Dkk1 using a Tet-on system. Ptf1a-Cre; LSL-KrasG12D ; Rosa26rtTA; TetO-Dkk1 mice were treated with doxycycline to induce Dkk1 expression in the pancreas from 1 month of age, when PanINs are rare and the pancreas is largely normal. This resulted in mice displaying fewer PanINs, slower disease progression and longer survival, suggesting a requirement for Wnt signalling in pancreatic carcinogenesis. Activation of Dkk1 expression at a later time point when PanINs are more frequent demonstrated inactivation of Wnt signalling prevents proliferation of PanINs and interestingly may also play a role in maintaining desmoplasia during tumour progression. The results of these studies highlight the potential limitations when interpreting models using aberrant overexpression of genes as well as the importance of the timing of gene activation/inactivation. 3.1.4. Models of familial PDAC Approximately 10% of PDAC patients have a family history of the malignancy [60]. Several germline mutations that increase the risk of developing PDAC have been characterised including BRCA2, CDKN2A/P16INK4A, STK11/LKB1, PRSS1 and PALB2 [60]. In addition, there still remains other, as yet, unidentified causes for hereditary PDAC. Several mouse models have been developed investigating the role these germline mutations play in the development of PDAC. Familial atypical mole and multiple melanoma (FAMMM) syndrome patients display an increased risk of developing malignant melanoma and are characterised by germline mutations in CDKN2A/P16INK4A. These patients are also known to harbour an increased risk of developing PDAC. Several mouse models investigating loss of P16INK4A have been developed and are discussed above (section 3.1.2.1). BRCA2 is a well-known tumour suppressor gene with an essential role in maintaining chromosomal stability [61]. Patients with germline mutations in BRCA2 have been identified to carry an increased risk of developing several cancer types, including PDAC.

5

Conditional knockout of Brca2 in the mouse pancreas has led to differences between studies. Skoulidis et al. combined two variations of mutant Brca2 mice, a germline truncating allele (Brca2Tr ), and a conditional Brca2 deletion in exon 11 (Brca211 ), in order to model loss of heterozygosity seen in humans [62]. No phenotype was observed in these mice until they were crossed with KC or KPC mice. Both homozygous or heterozygous Brca2 inactivation led to the acceleration of PDAC in the mice regardless of Trp53 status. However, Rowley et al. developed a similar model using the same conditional Brca2 deletion (Brca211 ) and found that, when combined with mutant Kras, inactivation of Brca2 inhibited the formation of PanIN and PDAC, but accelerated PDAC formation when combined with loss of Trp53 [63]. Finally, a third model demonstrated that conditional inactivation of Brca2 alone was sufficient to induce PanIN and PDAC in a small number of mice with a long latency of >15 months [64]. Addition of mutant Trp53 was able to reduce the latency for tumour development. The reasons for these discrepancies are not completely clear and need to be further clarified, and a recent review discusses the findings from these three models in depth [65]. Peutz-Jeghers Syndrome is caused by germline LKB1 lossof-function mutations and patients have a predisposition for developing gastrointestinal neoplasms and a high risk of developing pancreatic cancer, including PDAC, IPMN and serous cystadenoma. Conditional Lkb1 deletion in the pancreas results in mice displaying impaired acinar cell polarity, postnatal acinar cell degeneration and the development of serous cystadenomas [66]. Heterozygous loss of Lkb1 also accelerates PDAC development in the KC model and promoted a cystic morphology in some tumours. Homozygous deletion of Lkb1 alone was sufficient to induce pancreatic tumours resembling human benign mucinous cystadenomas [67]. 3.1.5. Models of random mutagenesis A more recent step in the development of mouse models for pancreatic cancer has been to use novel mutagenesis strategies to uncover possible driver mutations in pancreatic cancer. Next generation sequencing studies have been able to confirm many of the genetic mutations already known to occur with high frequency in PDAC, but are also beginning to uncover many other somatic mutations that occur at much lower frequencies in patients. Jones et al. sequenced 24 tumours and was able to detect an average of 63 mutations per tumour, that could be grouped into 12 core signalling pathways [15]. With next generation sequencing technologies becoming increasingly affordable, larger scale sequencing projects have been established and will likely identify even more mutations as larger cohorts are sequenced [14]. Determining which of these mutations are likely to play a role in driving tumorigenesis is more difficult. Using mouse models of random mutagenesis is a potential way that novel driver mutations of cancer can be discovered. The Sleeping Beauty model is a mouse model of insertional mutagenesis that consists of one transgene that contains a concatomer of transposons and another transgene that expresses a Sleeping Beauty transposase enzyme [68]. When expression of these transgenes occurs in the same cell, the transposase enzyme mobilises the transposons where they are free to insert randomly into the genome. These insertion events may occur to activate oncogenes or inactivate tumour suppressor genes, thereby initiating tumorigenesis. To date, two separate Sleeping Beauty models of pancreatic cancer have been published, each using different variations of the Sleeping Beauty transposon and conditional transposase [69,70]. Both models combined Sleeping Beauty with the KC model. In each of these studies, Sleeping Beauty was found to cooperate with Kras and accelerate tumorigenesis in mice. Analysis of transposon insertion sites identified many candidate cancer


410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441

442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474



6

494

genes and an enrichment in signalling pathways such as TGF␤ and chromatin modification [69]. Similarly, Perez-Mancera et al. identified many genes that were mutated in mouse tumours, including mutations in TGF␤ pathway members, which occurred in approximately a third of tumours [70]. Their study identified the X-linked deubiquitinase Usp9x as the most frequently mutated gene. Interestingly, this gene was also the second most commonly mutated gene in Mann et al. USP9X has not previously been associated with human PDAC, however the authors went on to demonstrate that low expression of USP9X was an independent poor prognostic factor following pancreatectomy. They also developed a mouse model and found that LSL-KrasG12D ; Pdx1-Cre; Usp9xfl mice rapidly develop PanIN and microinvasive neoplasms by 3 months of age, however the majority of mice needed to be culled due to the development of aggressive oral papillomas. The validity of using such models as Sleeping Beauty to investigate human PDAC is highlighted in a recent paper that used data from both of the studies mentioned to provide supportive evidence for novel genes identified by exome sequencing of human PDAC patients [14].

495

3.2. Mouse models of PNETs

475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493

496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537

Pancreatic neuroendocrine tumours (PNETs) account for only approximately 1% of pancreatic cancers however, like PDAC, surgery is the most effective treatment and for the majority of patients who are diagnosed with metastatic disease, treatment options are limited and largely ineffective. The first mouse models of PNETs were developed several decades ago and utilised the viral oncogene, SV40. Expression of SV40 has been targeted to pancreatic islets using the Rat Insulin Promoter (RIP-Tag) [71] and the Glucagon promoter (Glucagon-SV40) [72–75] with mice developing insulinomas and glucagonomas, respectively. The use of these mice of preclinical models of human PNETs has been criticised in the past, as SV40 is not implicated in the aetiology of this malignancy, nor the SV40 targets p53 and Rb [76–79]. However, MDM2, MDM4 and WIP1, which are negative regulators of p53 activity, are aberrantly activated in approximately 70% of PNETs [80] and overexpression of the Rb pathway components Cdk4 and Cyclin D1 occuring in the majority of human PNETs [81]. Recently, mutations of both TP53 and RB1 have been associated with poorly differentiated neuroendocrine carcinomas of the pancreas [82]. In-depth characterisation of RIP-Tag mice demonstrated that in addition to insulinomas, 70% of mice develop at least one poorly differentiated carcinoma [83]. Importantly, the RIP-Tag model has proven utility in predicting the efficacy of several therapeutics in treating human pancreatic neuroendocrine tumours [84–87]. Other models of PNETs have since been developed, the majority involving ablation of Men1 expression. This is based on the fact that germline mutations in MEN1 result in multiple endocrine neoplasia type 1 (MEN1) syndrome, of which PNETs are a feature. In addition to germline mutations, sporadic mutations in MEN1 are present in up to 44% of pancreatic neuroendocrine tumours. Mice heterozygous for Men1 display several features of the MEN1 syndrome including the development of insulinomas and parathyroid adenomas [88]. Pancreas-specific deletion of Men1, also resulted in the formation of insulinomas [89–91]. Men1 models of insulinoma undergo a similar progression to the RIP-Tag model including ␤-cell hyperplasia, induction of angiogenesis and a downregulation in Ecadherin, however they do so with a much longer latency, taking at least 6 months to form tumours. Models based on loss of MEN1 are clinically relevant for patients harbouring mutations in this gene; models based on other genes recently identified as being mutated in a significant number of pancreatic neuroendocrine tumours, for example DAXX/ATRX and mTOR pathway genes [78], have yet to be developed.

4. Patient derived xenografts Xenografts derived from human pancreatic cancer cell lines have been extensively used for the investigation and characterisation of numerous anti-cancer therapeutic agents, as well as the study of tumour biology, tumour–host interactions, the tumour microenvironment, preclinical efficacy and chemoresistance. While cell line xenograft models possess many advantages warranting its use as a quick “first pass” assessment of drug efficacy, there are many disadvantages that limits its use as a valid pre-clinical model of pancreatic cancer. These include the use of immunodeficient mice, thereby removing any possible investigations into the contribution of the immune system to tumorigenesis; immortalised cell lines are homogeneous thereby not recapitulating the heterogeneity evident amongst pancreatic cancer patients [15,14,92]; the tumour microenvironment does not reflect the clinical situation due to the absence of human stroma; the tumours do not reflect the histopathology of the primary tumour; the tumour growth occurs away from the tissue origin of the tumour; observed drug regimens that are curative in these models often do not reflect the clinical response in the human disease [34]; and the tumours rarely metastasise [93,94]. The patient derived xenograft (PDX) uses tumour fragments directly from the primary tumour and maintains the whole structure of the human parental tumour during the initial passages, and as such is an excellent model for assessing personalised chemotherapeutic drug regimens in a pre-clinical setting. Comparisons between cell line-derived and patient-derived xenografts are summarised in Table 2. Recent sequencing approaches (whole exome and whole genome sequencing) have identified the substantial genomic heterogeneity that characterises pancreatic cancer [15,14,92]. With cell line based xenograft models, this heterogeneity is not taken into account and thus these models substantially overestimate the anti-tumour effects of a given therapeutic strategy. The inability of these conventional xenograft models to reliably predict clinical efficacy is one of the most frequently cited reasons for the high failure rate of novel anti-cancer therapies in clinical trials [95–98]. An important issue surrounding the PDX model concerns the retention of tumour characteristics (genotype; phenotype; stroma) during passaging, and that these xenografts faithfully represent the original patient tumour they were derived from. This has been recently addressed by a number of studies [96,99–101], who collectively demonstrated the genomic stability of key pancreatic cancer related genes through to at least the third generation of expansion (3 passages). Of note, some studies have also reported that the response rates of PDX to several anti-cancer drugs in clinical use are similar to the overall response rate recorded for monotherapy clinical trials with these agents [101–105]. With this evidence strongly confirming the genomic and architectural stability of tumours, the PDX model has recently returned to favour to drive discoveries into biomarkers that predict therapeutic responsiveness to novel and established therapies, enable studies into the molecular mechanisms of chemoresistance, and also facilitate the testing of personalised medicine strategies by administering target treatments based on the genomic/molecular signature of each individual tumour/patient [92,101,106,107]. The PDX model involves the direct implantation of small tumour fragments, either heterotopic subcutaneous or sub-renal capsular, from individual patients into immunodeficient mice. While this type of PDX model was reported over 40 years ago, the advantages of these models and their use in therapeutic testing has only recently been recognised and implemented, particularly for the heterogeneous disease that is pancreatic cancer [101,108–112]. The generation of PDX models from tumours that have been extensively characterised via large-scale sequencing efforts allows


538

539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602

G Model

ARTICLE IN PRESS

YSCDB 1543 1–10


7

Table 2 Advantages and disadvantages of xenograft models for pancreatic cancer pre-clinical research. Cell line xenograft Heterotopic Advantages Low cost Low time consumption

Patient derived heterotopic xenograft Orthotopic

Tumour

Cell line

Sub-renal capsule

Tumour grows in correct anatomical site More closely recapitulates human pancreatic cancer

Heterogeneity of tumours



Tumour microenvironment resembles parent tumour (includes stroma) Phenotypically resembles primary tumour Can be characterised (e.g. genome sequencing)

Tumour microenvironment resembles parent tumour (includes stroma) Phenotypically resembles primary tumour Useful for rapid pre-clinical drug- and personalised medicine drug-trials Easy to monitor/measure (if heterotopic)

Tumour microenvironment (includes stroma)

Frequently used

Resectable

Easy propagation

Metastatic

Genetic manipulation

Tumour microenvironment (some)

Ease of monitoring/measuring tumour growth Virtually unlimited source of material (immortal cell line) Disadvantages Use of immunodeficient Use of immunodeficient mice mice Immune system Immune system interactions cannot be interactions cannot be investigated investigated Divergent from primary Tumour homogeneity/lacks the tumour histopathology of pancreatic cancer Moderate time Divergent from primary tumour consumption Technically complicated – Poor tumour microenvironment (no Potential for tumour cell spillage during human stroma) implantation Away from tissue of Monitoring requires low origin throughput imaging Rarely metastasises

603 604 605 606 607 608 609 610

Easy to monitor/measure (if heterotopic) Rapid expansion of primary tumour

Phenotypically resembles primary tumour Useful for rapid pre-clinical drug- and personalised medicine drug-trials Rapid expansion of primary tumour High organ perfusion/rapid development of graft microvasculature

Use of immunodeficient mice Immune system interactions cannot be investigated Away from tissue of origin



Some selection in mice



Limited source material

Monitoring requires low throughput imaging

Source material must be processed rapidly

Technically complicated

for the expansion of the individual’s tumour specimen to provide a resource for ongoing experimentation into efficacy of novel therapeutic agents, personalised medicine strategies, discovery of biomarkers of therapeutic response as well as molecular mechanism of chemoresistance [106]. As the tumour is renewable in a PDX model, multiple treatments can be assessed thereby providing the opportunity to test personalised medicine strategies that are currently intractable in a clinical trial setting (Fig. 1) [106]. Due

to the heterogeneity of pancreatic cancer, the molecular signature of an individual’s tumour is very complex and may involve aberrations in numerous signalling pathways. As such, the use of multiple therapeutic agents targeting these mechanisms can be administered and assessed in parallel with each other and compared to the standard of care, gemcitabine. Further, the PDX model will assist in the discovery of biomarkers of therapeutic responsiveness, facilitate investigations into the mechanisms of therapeutic resistance,

Fig. 1. Personalised medicine strategy using the PDX preclinical model. Modified from [106].


611 612 613 614 615 616 617 618



8 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662

663

664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681

ARTICLE IN PRESS

which remains an insurmountable challenge in the field pancreatic cancer research [106]. PDX models are typically engrafted subcutaneously, however another heterotopic xenograft model used for the implantation of tissue fragments derived directly from the primary tumour is the sub-renal capsule (SRC) model. The SRC site offers the particular advantage of very high organ perfusion and potentially rapid development of graft microvasculature [113,114], while engraftment rates of SRC xenografts are high with >95% reported in studies of cancers of the ovary, lung, kidney and prostate [114–117]. Additionally, the SRC xenograft model allows for retainment of the heterogeneity of the parent tumour, importantly including abundant human tumour-associated stroma, which is essential for the cross-talk and tumour–host interactions driving tumorigenesis [118]. As for the subcutaneous patient derived xenografts derived above, the SRC model allows for the rapid expansion of tumour tissue that phenotypically and genotypically resembles the primary tumour; an important feature for the pre-clinical assessment of novel therapies. SRC xenografts are also a very useful model for screening the in vivo efficacy of selected therapeutic agents in a pre-clinical setting [119]. For example, Carter and colleagues [120] used the SRC model to implant fresh tissue from HER2 positive breast tumours [121], to assess the efficacy of a panel of anti-HER2 antibodies to decide which murine antibody should be humanised for future clinical development, in particular trastuzumab [120]. In the context of pancreatic cancer, Xue and colleagues [122] established SRC xenografts with successful engraftment of >90%, with the post-graft tissues demonstrating >90% concordance histopathologically to the original tumour. Also, of the pancreatic cancer patients who donated tissue to the study, whose tumours responded to gemcitabine in the SRC xenografts, had not developed recurrence during the study period, while those that developed early metastatic disease did not respond to gemcitabine in the SRC model [122]. While still in its relative infancy in pancreatic cancer pre-clinical studies, the patient derived subrenal capsule xenograft represents an excellent alternate model for the study of personalised medicine approaches. As with the subcutaneous PDX model, the SRC xenograft has the disadvantage of the need for immunodeficient mice for tumour growth and expansion, as well as the tumour growing away from the tissue of origin. The SRC xenograft is also more technically challenging and invasive than the PDX model and monitoring of the tumour kinetics requires the use of costly low throughput imaging modalities (Table 2).

5. Conclusion Both GEMMs and PDX models provide valuable resources to study pancreatic cancer. GEMMs have the advantage of allowing study of the earliest stages of tumorigenesis, tumour development occurs within the pancreas and in some models is accompanied by metastasis. Importantly, tumour–host interactions can be examined at all stages of disease progression in an immunocompetent animal. In addition, GEMMs, particularly the KPC model, are proving useful in investigating the efficacy of novel therapeutics and can be used to assess chemoprevention strategies. Novel GEMMs of random mutagenesis using Sleeping Beauty have identified novel driver mutations of pancreatic carcinogenesis and provide a complementary resource for the growing number of next generation sequencing studies. However, the major disadvantages of GEMMs include the time and cost associated with generating them, with some models requiring crossing of three or more lines of mice, and inherent physiological differences between mice and humans. Also, many of the pancreatic cancer GEMMs target the activation or inactivation of genes to the embryonic pancreas

to initiate tumorigenesis, which is very different to pancreatic tumour development in humans. PDXs are emerging as an important tool in the development of personalised treatments for pancreatic cancer patients. They are relatively cheap to produce compared to GEMMs, and have been shown to retain the genetic characteristics and response to therapy as the original tumour. However, given the increasingly recognised role of the tumour microenvironment in tumour progression and its potential as a therapeutic target, the need to use immunodeficient mice is a major drawback of PDXs. Advances in immunodeficient mouse models have increased the potential to create “humanised” immunodeficient mice via engraftment of human immune cells, and this approach may increase the physiological relevance of PDX studies. Over the past few decades, many models of pancreatic cancer have been developed that have greatly increased our understanding of this malignancy. Each model has its advantages and disadvantages, however they all contribute to provide an extremely useful resource that can be used to provide new insights into pancreatic cancer and most importantly help to identify and test new, and more effective therapies.

References [1] Siegel R, Naishadham D, Jemal A. Cancer statistics, 2013. CA Cancer J Clin 2013;63:11–30. [2] Hidalgo M. Pancreatic cancer. N Engl J Med 2010;362:1605–17. [3] Vincent A, Herman J, Schulick R, Hruban RH, Goggins M. Pancreatic cancer. Lancet 2011;378:607–20. [4] Hruban RH, Adsay NV, Albores-Saavedra J, Compton C, Garrett ES, Goodman SN, et al. Pancreatic intraepithelial neoplasia: a new nomenclature and classification system for pancreatic duct lesions. Am J Surg Pathol 2001;25: 579–86. [5] Hruban RH, Takaori K, Klimstra DS, Adsay NV, Albores-Saavedra J, Biankin AV, et al. An illustrated consensus on the classification of pancreatic intraepithelial neoplasia and intraductal papillary mucinous neoplasms. Am J Surg Pathol 2004;28:977–87. [6] Wilentz RE, Albores-Saavedra J, Hruban RH. Mucinous cystic neoplasms of the pancreas. Semin Diagn Pathol 2000;17:31–42. [7] Almoguera C, Shibata D, Forrester K, Martin J, Arnheim N, Perucho M. Most human carcinomas of the exocrine pancreas contain mutant c-K-ras genes. Cell 1988;53:549–54. [8] Hruban RH, van Mansfeld AD, Offerhaus GJ, van Weering DH, Allison DC, Goodman SN, et al. K-ras oncogene activation in adenocarcinoma of the human pancreas. A study of 82 carcinomas using a combination of mutant-enriched polymerase chain reaction analysis and allele-specific oligonucleotide hybridization. Am J Pathol 1993;143:545–54. [9] Caldas C, Hahn SA, da Costa LT, Redston MS, Schutte M, Seymour AB, et al. Frequent somatic mutations and homozygous deletions of the p16 (MTS1) gene in pancreatic adenocarcinoma. Nat Genet 1994;8:27–32. [10] Schutte M, Hruban RH, Geradts J, Maynard R, Hilgers W, Rabindran SK, et al. Abrogation of the Rb/p16 tumor-suppressive pathway in virtually all pancreatic carcinomas. Cancer Res 1997;57:3126–30. [11] Redston MS, Caldas C, Seymour AB, Hruban RH, da Costa L, Yeo CJ, et al. p53 mutations in pancreatic carcinoma and evidence of common involvement of homocopolymer tracts in DNA microdeletions. Cancer Res 1994;54:3025–33. [12] Rozenblum E, Schutte M, Goggins M, Hahn SA, Panzer S, Zahurak M, et al. Tumor-suppressive pathways in pancreatic carcinoma. Cancer Res 1997;57:1731–4. [13] Hahn SA, Schutte M, Hoque AT, Moskaluk CA, da Costa LT, Rozenblum E, et al. DPC4, a candidate tumor suppressor gene at human chromosome 18q21.1. Science 1996;271:350–3. [14] Biankin AV, Waddell N, Kassahn KS, Gingras MC, Muthuswamy LB, Johns AL, et al. Pancreatic cancer genomes reveal aberrations in axon guidance pathway genes. Nature 2012;491:399–405. [15] Jones S, Zhang X, Parsons DW, Lin JC, Leary RJ, Angenendt P, et al. Core signaling pathways in human pancreatic cancers revealed by global genomic analyses. Science 2008;321:1801–6. [16] Ornitz DM, Hammer RE, Messing A, Palmiter RD, Brinster RL. Pancreatic neoplasia induced by SV40 T-antigen expression in acinar cells of transgenic mice. Science 1987;238:188–93. [17] Ornitz DM, Palmiter RD, Messing A, Hammer RE, Pinkert CA, Brinster RL. Elastase I promoter directs expression of human growth hormone and SV40T antigen genes to pancreatic acinar cells in transgenic mice. Cold Spring Harb Symp Quant Biol 1985;50:399–409. [18] Bell Jr RH, Memoli VA, Longnecker DS. Hyperplasia and tumors of the islets of Langerhans in mice bearing an elastase I-SV40 T-antigen fusion gene. Carcinogenesis 1990;11:1393–8.


682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702

Q2

703

704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757



758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843

[19] Glasner S, Memoli V, Longnecker DS. Characterization of the ELSV transgenic mouse model of pancreatic carcinoma. Histologic type of large and small tumors. Am J Pathol 1992;140:1237–45. [20] Quaife CJ, Pinkert CA, Ornitz DM, Palmiter RD, Brinster RL. Pancreatic neoplasia induced by ras expression in acinar cells of transgenic mice. Cell 1987;48:1023–34. [21] Sandgren EP, Luetteke NC, Palmiter RD, Brinster RL, Lee DC. Overexpression of TGF alpha in transgenic mice: induction of epithelial hyperplasia, pancreatic metaplasia, and carcinoma of the breast. Cell 1990;61:1121–35. [22] Wagner M, Luhrs H, Kloppel G, Adler G, Schmid RM. Malignant transformation of duct-like cells originating from acini in transforming growth factor transgenic mice. Gastroenterology 1998;115:1254–62. [23] Sandgren EP, Quaife CJ, Paulovich AG, Palmiter RD, Brinster RL. Pancreatic tumor pathogenesis reflects the causative genetic lesion. Proc Natl Acad Sci U S A 1991;88:93–7. [24] Grippo PJ, Nowlin PS, Demeure MJ, Longnecker DS, Sandgren EP. Preinvasive pancreatic neoplasia of ductal phenotype induced by acinar cell targeting of mutant Kras in transgenic mice. Cancer Res 2003;63:2016–9. [25] Jackson EL, Willis N, Mercer K, Bronson RT, Crowley D, Montoya R, et al. Analysis of lung tumor initiation and progression using conditional expression of oncogenic K-ras. Genes Dev 2001;15:3243–8. [26] Hingorani SR, Petricoin EF, Maitra A, Rajapakse V, King C, Jacobetz MA, et al. Preinvasive and invasive ductal pancreatic cancer and its early detection in the mouse. Cancer Cell 2003;4:437–50. [27] Guerra C, Schuhmacher AJ, Canamero M, Grippo PJ, Verdaguer L, PerezGallego L, et al. Chronic pancreatitis is essential for induction of pancreatic ductal adenocarcinoma by K-Ras oncogenes in adult mice. Cancer Cell 2007;11:291–302. [28] Aguirre AJ, Bardeesy N, Sinha M, Lopez L, Tuveson DA, Horner J, et al. Activated Kras and Ink4a/Arf deficiency cooperate to produce metastatic pancreatic ductal adenocarcinoma. Genes Dev 2003;17:3112–26. [29] Bardeesy N, Aguirre AJ, Chu GC, Cheng KH, Lopez LV, Hezel AF, et al. Both p16(Ink4a) and the p19(Arf)-p53 pathway constrain progression of pancreatic adenocarcinoma in the mouse. Proc Natl Acad Sci U S A 2006;103:5947–52. [30] Guerra C, Collado M, Navas C, Schuhmacher AJ, Hernandez-Porras I, Canamero M, et al. Pancreatitis-induced inflammation contributes to pancreatic cancer by inhibiting oncogene-induced senescence. Cancer Cell 2011;19:728–39. [31] Hingorani SR, Wang L, Multani AS, Combs C, Deramaudt TB, Hruban RH, et al. Trp53R172H and KrasG12D cooperate to promote chromosomal instability and widely metastatic pancreatic ductal adenocarcinoma in mice. Cancer Cell 2005;7:469–83. [32] Jacobetz MA, Chan DS, Neesse A, Bapiro TE, Cook N, Frese KK, et al. Hyaluronan impairs vascular function and drug delivery in a mouse model of pancreatic cancer. Gut 2013;62:112–20. [33] Frese KK, Neesse A, Cook N, Bapiro TE, Lolkema MP, Jodrell DI, et al. nabPaclitaxel potentiates gemcitabine activity by reducing cytidine deaminase levels in a mouse model of pancreatic cancer. Cancer Discov 2012;2:260–9. [34] Olive KP, Jacobetz MA, Davidson CJ, Gopinathan A, McIntyre D, Honess D, et al. Inhibition of Hedgehog signaling enhances delivery of chemotherapy in a mouse model of pancreatic cancer. Science 2009;324:1457–61. [35] Plentz R, Park JS, Rhim AD, Abravanel D, Hezel AF, Sharma SV, et al. Inhibition of gamma-secretase activity inhibits tumor progression in a mouse model of pancreatic ductal adenocarcinoma. Gastroenterology 2009;136:1741–9, e6. [36] Beatty GL, Chiorean EG, Fishman MP, Saboury B, Teitelbaum UR, Sun W, et al. CD40 agonists alter tumor stroma and show efficacy against pancreatic carcinoma in mice and humans. Science 2011;331:1612–6. [37] Funahashi H, Satake M, Dawson D, Huynh NA, Reber HA, Hines OJ, et al. Delayed progression of pancreatic intraepithelial neoplasia in a conditional Kras(G12D) mouse model by a selective cyclooxygenase-2 inhibitor. Cancer Res 2007;67:7068–71. [38] Morton JP, Timpson P, Karim SA, Ridgway RA, Athineos D, Doyle B, et al. Mutant p53 drives metastasis and overcomes growth arrest/senescence in pancreatic cancer. Proc Natl Acad Sci U S A 2010;107:246–51. [39] Bardeesy N, Cheng KH, Berger JH, Chu GC, Pahler J, Olson P, et al. Smad4 is dispensable for normal pancreas development yet critical in progression and tumor biology of pancreas cancer. Genes Dev 2006;20:3130–46. [40] Kojima K, Vickers SM, Adsay NV, Jhala NC, Kim HG, Schoeb TR, et al. Inactivation of Smad4 accelerates Kras(G12D)-mediated pancreatic neoplasia. Cancer Res 2007;67:8121–30. [41] Izeradjene K, Combs C, Best M, Gopinathan A, Wagner A, Grady WM, et al. Kras(G12D) and Smad4/Dpc4 haploinsufficiency cooperate to induce mucinous cystic neoplasms and invasive adenocarcinoma of the pancreas. Cancer Cell 2007;11:229–43. [42] Thayer SP, di Magliano MP, Heiser PW, Nielsen CM, Roberts DJ, Lauwers GY, et al. Hedgehog is an early and late mediator of pancreatic cancer tumorigenesis. Nature 2003;425:851–6. [43] Pasca di Magliano M, Sekine S, Ermilov A, Ferris J, Dlugosz AA, Hebrok M. Hedgehog/Ras interactions regulate early stages of pancreatic cancer. Genes Dev 2006;20:3161–73. [44] Yauch RL, Gould SE, Scales SJ, Tang T, Tian H, Ahn CP, et al. A paracrine requirement for hedgehog signalling in cancer. Nature 2008;455:406–10. [45] Nolan-Stevaux O, Lau J, Truitt ML, Chu GC, Hebrok M, Fernandez-Zapico ME, et al. GLI1 is regulated through Smoothened-independent mechanisms in neoplastic pancreatic ducts and mediates PDAC cell survival and transformation. Genes Dev 2009;23:24–36.

9

[46] Tian H, Callahan CA, DuPree KJ, Darbonne WC, Ahn CP, Scales SJ, et al. Hedgehog signaling is restricted to the stromal compartment during pancreatic carcinogenesis. Proc Natl Acad Sci U S A 2009;106:4254–9. [47] Radtke F, Raj K. The role of Notch in tumorigenesis: oncogene or tumour suppressor. Nat Rev Cancer 2003;3:756–67. [48] Miyamoto Y, Maitra A, Ghosh B, Zechner U, Argani P, Iacobuzio-Donahue CA, et al. Notch mediates TGF alpha-induced changes in epithelial differentiation during pancreatic tumorigenesis. Cancer Cell 2003;3:565–76. [49] De La OJ, Emerson LL, Goodman JL, Froebe SC, Illum BE, Curtis AB, et al. Notch and Kras reprogram pancreatic acinar cells to ductal intraepithelial neoplasia. Proc Natl Acad Sci U S A 2008;105:18907–12. [50] Murtaugh LC, Stanger BZ, Kwan KM, Melton DA. Notch signaling controls multiple steps of pancreatic differentiation. Proc Natl Acad Sci U S A 2003;100:14920–5. [51] Hanlon L, Avila JL, Demarest RM, Troutman S, Allen M, Ratti F, et al. Notch1 functions as a tumor suppressor in a model of K-ras-induced pancreatic ductal adenocarcinoma. Cancer Res 2010;70:4280–6. [52] Mazur PK, Einwachter H, Lee M, Sipos B, Nakhai H, Rad R, et al. Notch2 is required for progression of pancreatic intraepithelial neoplasia and development of pancreatic ductal adenocarcinoma. Proc Natl Acad Sci U S A 2010;107:13438–43. [53] Al-Aynati MM, Radulovich N, Riddell RH, Tsao MS. Epithelial-cadherin and beta-catenin expression changes in pancreatic intraepithelial neoplasia. Clin Cancer Res: Off J Am Assoc Cancer Res 2004;10:1235–40. [54] Zeng G, Germinaro M, Micsenyi A, Monga NK, Bell A, Sood A, et al. Aberrant Wnt/beta-catenin signaling in pancreatic adenocarcinoma. Neoplasia 2006;8:279–89. [55] Pasca di Magliano M, Biankin AV, Heiser PW, Cano DA, Gutierrez PJ, Deramaudt T, et al. Common activation of canonical Wnt signaling in pancreatic adenocarcinoma. PLoS ONE 2007;2:e1155. [56] Strom A, Bonal C, Ashery-Padan R, Hashimoto N, Campos ML, Trumpp A, et al. Unique mechanisms of growth regulation and tumor suppression upon Apc inactivation in the pancreas. Development 2007;134:2719–25. [57] Heiser PW, Cano DA, Landsman L, Kim GE, Kench JG, Klimstra DS, et al. Stabilization of beta-catenin induces pancreas tumor formation. Gastroenterology 2008;135:1288–300. [58] Morris JPt, Cano DA, Sekine S, Wang SC, Hebrok M. Beta-catenin blocks Krasdependent reprogramming of acini into pancreatic cancer precursor lesions in mice. J Clin Invest 2010;120:508–20. [59] Zhang Y, Morris JPt, Yan W, Schofield HK, Gurney A, Simeone DM, et al. Canonical wnt signaling is required for pancreatic carcinogenesis. Cancer Res 2013;73:4909–22. [60] Hruban RH, Canto MI, Goggins M, Schulick R, Klein AP. Update on familial pancreatic cancer. Adv Surg 2010;44:293–311. [61] Venkitaraman AR. Linking the cellular functions of BRCA genes to cancer pathogenesis and treatment. Annu Rev Pathol 2009;4:461–87. [62] Skoulidis F, Cassidy LD, Pisupati V, Jonasson JG, Bjarnason H, Eyfjord JE, et al. Germline Brca2 heterozygosity promotes Kras(G12D)-driven carcinogenesis in a murine model of familial pancreatic cancer. Cancer Cell 2010;18: 499–509. [63] Rowley M, Ohashi A, Mondal G, Mills L, Yang L, Zhang L, et al. Inactivation of Brca2 promotes Trp53-associated but inhibits KrasG12D-dependent pancreatic cancer development in mice. Gastroenterology 2011;140:1303–13, e1–3. [64] Feldmann G, Karikari C, dal Molin M, Duringer S, Volkmann P, Bartsch DK, et al. Inactivation of Brca2 cooperates with Trp53(R172H) to induce invasive pancreatic ductal adenocarcinomas in mice: a mouse model of familial pancreatic cancer. Cancer Biol Ther 2011;11:959–68. [65] Cassidy LD, Liau SS, Venkitaraman AR. Chromosome instability and carcinogenesis: insights from murine models of human pancreatic cancer associated with BRCA2 inactivation. Mol Oncol 2014;8:161–8. [66] Hezel AF, Gurumurthy S, Granot Z, Swisa A, Chu GC, Bailey G, et al. Pancreatic LKB1 deletion leads to acinar polarity defects and cystic neoplasms. Mol Cell Biol 2008;28:2414–25. [67] Morton JP, Jamieson NB, Karim SA, Athineos D, Ridgway RA, Nixon C, et al. LKB1 haploinsufficiency cooperates with Kras to promote pancreatic cancer through suppression of p21-dependent growth arrest. Gastroenterology 2010;139:586–97, e1–6. [68] Howell VM. Sleeping Beauty—a mouse model for all cancers. Cancer Lett 2012;317:1–8. [69] Mann KM, Ward JM, Yew CC, Kovochich A, Dawson DW, Black MA, et al. Sleeping Beauty mutagenesis reveals cooperating mutations and pathways in pancreatic adenocarcinoma. Proc Natl Acad Sci U S A 2012;109: 5934–41. [70] Perez-Mancera PA, Rust AG, van der Weyden L, Kristiansen G, Li A, Sarver AL, et al. The deubiquitinase USP9X suppresses pancreatic ductal adenocarcinoma. Nature 2012;486:266–70. [71] Hanahan D. Heritable formation of pancreatic beta-cell tumours in transgenic mice expressing recombinant insulin/simian virus 40 oncogenes. Nature 1985;315:115–22. [72] Asa SL, Lee YC, Drucker DJ. Development of colonic and pancreatic endocrine tumours in mice expressing a glucagon-SV40 T antigen transgene. Virchows Arch: Int J Pathol 1996;427:595–606. [73] Efrat S, Teitelman G, Anwar M, Ruggiero D, Hanahan D. Glucagon gene regulatory region directs oncoprotein expression to neurons and pancreatic alpha cells. Neuron 1988;1:605–13.


844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929

G Model YSCDB 1543 1–10 10 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007


[74] Lee YC, Asa SL, Drucker DJ. Glucagon gene 5 -flanking sequences direct expression of simian virus 40 large T antigen to the intestine, producing carcinoma of the large bowel in transgenic mice. J Biol Chem 1992;267:10705–8. [75] Rindi G, Efrat S, Ghatei MA, Bloom SR, Solcia E, Polak JM. Glucagonomas of transgenic mice express a wide range of general neuroendocrine markers and bioactive peptides. Virchows Arch A Pathol Anat Histopathol 1991;419:115–29. [76] Wang DG, Johnston CF, Anderson N, Sloan JM, Buchanan KD. Overexpression of the tumour suppressor gene p53 is not implicated in neuroendocrine tumour carcinogenesis. J Pathol 1995;175:397–401. [77] Bartz C, Ziske C, Wiedenmann B, Moelling K. p53 tumour suppressor gene expression in pancreatic neuroendocrine tumour cells. Gut 1996;38:403–9. [78] Jiao Y, Shi C, Edil BH, de Wilde RF, Klimstra DS, Maitra A, et al. DAXX/ATRX, MEN1, and mTOR pathway genes are frequently altered in pancreatic neuroendocrine tumors. Science 2011;331:1199–203. [79] Chung DC, Smith AP, Louis DN, Graeme-Cook F, Warshaw AL, Arnold A. Analysis of the retinoblastoma tumour suppressor gene in pancreatic endocrine tumours. Clin Endocrinol (Oxf) 1997;47:523–8. [80] Hu W, Feng Z, Modica I, Klimstra DS, Song L, Allen PJ, et al. Gene amplifications in well-differentiated pancreatic neuroendocrine tumors inactivate the p53 pathway. Genes Cancer 2010;1:360–8. [81] Tang LH, Contractor T, Clausen R, Klimstra DS, Du YC, Allen PJ, et al. Attenuation of the retinoblastoma pathway in pancreatic neuroendocrine tumors due to increased cdk4/cdk6. Clin Cancer Res: Off J Am Assoc Cancer Res 2012;18:4612–20. [82] Yachida S, Vakiani E, White CM, Zhong Y, Saunders T, Morgan R, et al. Small cell and large cell neuroendocrine carcinomas of the pancreas are genetically similar and distinct from well-differentiated pancreatic neuroendocrine tumors. Am J Surg Pathol 2012;36:173–84. [83] Hunter KE, Quick ML, Sadanandam A, Hanahan D, Joyce JA. Identification and characterization of poorly differentiated invasive carcinomas in a mouse model of pancreatic neuroendocrine tumorigenesis. PLoS ONE 2013;8:e64472. [84] Chiu CW, Nozawa H, Hanahan D. Survival benefit with proapoptotic molecular and pathologic responses from dual targeting of mammalian target of rapamycin and epidermal growth factor receptor in a preclinical model of pancreatic neuroendocrine carcinogenesis. J Clin Oncol 2010;28:4425–33. [85] Paez-Ribes M, Allen E, Hudock J, Takeda T, Okuyama H, Vinals F, et al. Antiangiogenic therapy elicits malignant progression of tumors to increased local invasion and distant metastasis. Cancer Cell 2009;15:220–31. [86] Raymond E, Dahan L, Raoul JL, Bang YJ, Borbath I, Lombard-Bohas C, et al. Sunitinib malate for the treatment of pancreatic neuroendocrine tumors. N Engl J Med 2011;364:501–13. [87] Yao JC, Shah MH, Ito T, Bohas CL, Wolin EM, Van Cutsem E, et al. Everolimus for advanced pancreatic neuroendocrine tumors. N Engl J Med 2011;364:514–23. [88] Crabtree JS, Scacheri PC, Ward JM, Garrett-Beal L, Emmert-Buck MR, Edgemon KA, et al. A mouse model of multiple endocrine neoplasia, type 1, develops multiple endocrine tumors. Proc Natl Acad Sci U S A 2001;98:1118–23. [89] Crabtree JS, Scacheri PC, Ward JM, McNally SR, Swain GP, Montagna C, et al. Of mice and MEN1: insulinomas in a conditional mouse knockout. Mol Cell Biol 2003;23:6075–85. [90] Bertolino P, Tong WM, Herrera PL, Casse H, Zhang CX, Wang ZQ. Pancreatic beta-cell-specific ablation of the multiple endocrine neoplasia type 1 (MEN1) gene causes full penetrance of insulinoma development in mice. Cancer Res 2003;63:4836–41. [91] Shen HC, He M, Powell A, Adem A, Lorang D, Heller C, et al. Recapitulation of pancreatic neuroendocrine tumors in human multiple endocrine neoplasia type I syndrome via Pdx1-directed inactivation of Men1. Cancer Res 2009;69:1858–66. [92] Cowley MJ, Chang DK, Pajic M, Johns AL, Waddell N, Grimmond SM, et al. Understanding pancreatic cancer genomes. J Hepato-Biliary-Pancreatic Sci 2013. [93] Hoffman RM. Orthotopic is orthodox: why are orthotopic-transplant metastatic models different from all other models. J Cell Biochem 1994;56:1–3. [94] Fidler IJ. Critical factors in the biology of human cancer metastasis: twentyeighth G.H.A. Clowes memorial award lecture. Cancer Res 1990;50:6130–8. [95] Ellis LM, Fidler IJ. Finding the tumor copycat. Therapy fails, patients don’t. Nat Med 2010;16:974–5. [96] Mattie M, Christensen A, Chang MS, Yeh W, Said S, Shostak Y, et al. Molecular characterization of patient-derived human pancreatic tumor xenograft models for preclinical and translational development of cancer therapeutics. Neoplasia 2013;15:1138–50. [97] Tentler JJ, Tan AC, Weekes CD, Jimeno A, Leong S, Pitts TM, et al. Patientderived tumour xenografts as models for oncology drug development. Nat Rev Clin Oncol 2012;9:338–50. [98] Voskoglou-Nomikos T, Pater JL, Seymour L. Clinical predictive value of the in vitro cell line, human xenograft, and mouse allograft preclinical cancer models. Clin Cancer Res: Off J Am Assoc Cancer Res 2003;9:4227–39.

[99] Garcia PL, Council LN, Christein JD, Arnoletti JP, Heslin MJ, Gamblin TL, et al. Development and histopathological characterization of tumorgraft models of pancreatic ductal adenocarcinoma. PLoS ONE 2013;8:e78183. [100] Walters DM, Stokes JB, Adair SJ, Stelow EB, Borgman CA, Lowrey BT, et al. Clinical, molecular and genetic validation of a murine orthotopic xenograft model of pancreatic adenocarcinoma using fresh human specimens. PLoS ONE 2013;8:e77065. [101] Rubio-Viqueira B, Jimeno A, Cusatis G, Zhang X, Iacobuzio-Donahue C, Karikari C, et al. An in vivo platform for translational drug development in pancreatic cancer. Clin Cancer Res: Off J Am Assoc Cancer Res 2006;12:4652–61. [102] Perez-Soler R, Kemp B, Wu QP, Mao L, Gomez J, Zeleniuch-Jacquotte A, et al. Response and determinants of sensitivity to paclitaxel in human non-small cell lung cancer tumors heterotransplanted in nude mice. Clin Cancer Res: Off J Am Assoc Cancer Res 2000;6:4932–8. [103] Rubio-Viqueira B, Hidalgo M. Direct in vivo xenograft tumor model for predicting chemotherapeutic drug response in cancer patients. Clin Pharmacol Ther 2009;85:217–21. [104] Fichtner I, Slisow W, Gill J, Becker M, Elbe B, Hillebrand T, et al. Anticancer drug response and expression of molecular markers in early-passage xenotransplanted colon carcinomas. Eur J Cancer 2004;40:298–307. [105] Fiebig HH, Maier A, Burger AM. Clonogenic assay with established human tumour xenografts: correlation of in vitro to in vivo activity as a basis for anticancer drug discovery. Eur J Cancer 2004;40:802–20. [106] Pajic M, Scarlett CJ, Chang DK, Sutherland RL, Biankin AV. Preclinical strategies to define predictive biomarkers for therapeutically relevant cancer subtypes. Hum Genet 2011;130:93–101. [107] Jin K, Teng L, Shen Y, He K, Xu Z, Li G. Patient-derived human tumour tissue xenografts in immunodeficient mice: a systematic review. Clin Transl Oncol Off Publ Fed Spanish Oncol Soc Natl Cancer Inst Mexico 2010;12:473–80. [108] Giovanella BC, Yim SO, Morgan AC, Stehlin JS, Williams Jr LJ. Brief communication: metastases of human melanomas transplanted in nude mice. J Natl Cancer Inst 1973;50:1051–3. [109] Rygaard J, Povlsen CO. Heterotransplantation of a human malignant tumour to Nude mice. Acta Pathol Microbiol Scand 1969;77:758–60. [110] Jimeno A, Feldmann G, Suarez-Gauthier A, Rasheed Z, Solomon A, Zou GM, et al. A direct pancreatic cancer xenograft model as a platform for cancer stem cell therapeutic development. Mol Cancer Therap 2009;8:310–4. [111] Avan A, Caretti V, Funel N, Galvani E, Maftouh M, Honeywell RJ, et al. Crizotinib inhibits metabolic inactivation of gemcitabine in c-met-driven pancreatic carcinoma. Cancer Res 2013;73:6745–56. [112] Hermann PC, Trabulo SM, Sainz Jr B, Balic A, Garcia E, Hahn SA, et al. Multimodal treatment eliminates cancer stem cells and leads to long-term survival in primary human pancreatic cancer tissue xenografts. PLoS ONE 2013;8:e66371. [113] Bogden AE, Haskell PM, LePage DJ, Kelton DE, Cobb WR, Esber HJ. Growth of human tumor xenografts implanted under the renal capsule of normal immunocompetent mice. Exp Cell Biol 1979;47:281–93. [114] Cutz JC, Guan J, Bayani J, Yoshimoto M, Xue H, Sutcliffe M, et al. Establishment in severe combined immunodeficiency mice of subrenal capsule xenografts and transplantable tumor lines from a variety of primary human lung cancers: potential models for studying tumor progression-related changes. Clin Cancer Res: Off J Am Assoc Cancer Res 2006;12:4043–54. [115] Chang YS, Adnane J, Trail PA, Levy J, Henderson A, Xue D, et al. Sorafenib (BAY 43-9006) inhibits tumor growth and vascularization and induces tumor apoptosis and hypoxia in RCC xenograft models. Cancer Chemother Pharmacol 2007;59:561–74. [116] Lee CH, Xue H, Sutcliffe M, Gout PW, Huntsman DG, Miller DM, et al. Establishment of subrenal capsule xenografts of primary human ovarian tumors in SCID mice: potential models. Gynecol Oncol 2005;96:48–55. [117] Wang Y, Xue H, Cutz JC, Bayani J, Mawji NR, Chen WG, et al. An orthotopic metastatic prostate cancer model in SCID mice via grafting of a transplantable human prostate tumor line. Lab Invest J Tech Methods Pathol 2005;85:1392–404. [118] Vonlaufen A, Phillips PA, Xu Z, Goldstein D, Pirola RC, Wilson JS, et al. Pancreatic stellate cells and pancreatic cancer cells: an unholy alliance. Cancer Res 2008;68:7707–10. [119] Pegram M, Ngo D. Application and potential limitations of animal models utilized in the development of trastuzumab (Herceptin): a case study. Adv Drug Deliv Rev 2006;58:723–34. [120] Carter P, Presta L, Gorman CM, Ridgway JB, Henner D, Wong WL, et al. Humanization of an anti-p185HER2 antibody for human cancer therapy. Proc Natl Acad Sci U S A 1992;89:4285–9. [121] Giovanella BC, Stehlin JS, Coil D. Human tumors heterotransplanted in nude mice and rats. A comparative study. Exp Cell Biol 1984;52:76–9. [122] Xue A, Julovi SH, Samra JS, Hugh TJ, Gill A, Wong M, et al. Establishment of patient-derived subrenal capsule xenograft of pancreatic cancers in NOD/SCID mice: potential models for drug responses of personalized chemotherapy. In: Proceedings of the Australian Health and Medical Research Congress (AHMRC). 2012.


1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086

Cancer Immunotherapy: Historical Perspective of a Clinical Revolution and Emerging Preclinical Animal Models.

Historical perspective.

Checkerspot butterflies: a historical perspective.

Testosterone deficiency: a historical perspective.

Porcine circovirus: a historical perspective.

BCG-associated heterologous immunity, a historical perspective: intervention studies in animal models of infectious diseases.

BCG-associated heterologous immunity, a historical perspective: intervention studies in animal models of infectious diseases.

Contrasting illness and behavioral models for the treatment of autistic children: a historical perspective.

Metformin suppresses cancer initiation and progression in genetic mouse models of pancreatic cancer.

Neurophysiology of conversion disorders: a historical perspective.

Exercise Metabolism: Historical Perspective.

Psychotherapy in historical perspective.

Imidazoline receptors: historical perspective.

Madness in historical perspective.

An historical perspective.

Bovine tuberculosis: historical perspective.

Mouse models of human disease: An evolutionary perspective.

Historical perspective of Indian neurology.

Of time and historical perspective.

President's Address: The Climatological: A Historical Perspective.

Mouse models of human cancer.

Mouse models of gastric cancer.

Prognostic Disclosures to Children: A Historical Perspective.

The bradykinin-forming cascade: a historical perspective.