Erin E Talbert1, Maria C Cuitiño2, Katherine J Ladner3, Priyani V Rajasekerea3, Melissa Siebert3, Reena Shakya3, Gustavo W Leone2, Michael C Ostrowski2, Brian Paleo4, Noah Weisleder4, Peter J Reiser5, Amy Webb3, Cynthia D Timmers6, Daniel S Eiferman7, David C Evans7, Mary E Dillhoff8, Carl R Schmidt8, Denis C Guttridge9. 1. Arthur G. James Comprehensive Cancer Center Cancer Cachexia Program, The Ohio State University, Columbus, OH 43210, USA; Department of Pediatrics, Medical University of South Carolina, Charleston, SC 29425, USA; Hollings Cancer Center, Medical University of South Carolina, Charleston, SC 29425, USA. 2. Arthur G. James Comprehensive Cancer Center Cancer Cachexia Program, The Ohio State University, Columbus, OH 43210, USA; Hollings Cancer Center, Medical University of South Carolina, Charleston, SC 29425, USA; Department of Biochemistry and Molecular Biology, Medical University of South Carolina, Charleston, SC 29425, USA. 3. Arthur G. James Comprehensive Cancer Center Cancer Cachexia Program, The Ohio State University, Columbus, OH 43210, USA. 4. Department of Physiology and Cell Biology, The Ohio State University, Columbus, OH 43210, USA. 5. Division of Biosciences, The Ohio State University, Columbus, OH 43210, USA. 6. Arthur G. James Comprehensive Cancer Center Cancer Cachexia Program, The Ohio State University, Columbus, OH 43210, USA; Hollings Cancer Center, Medical University of South Carolina, Charleston, SC 29425, USA; Department of Medicine, Medical University of South Carolina, Charleston, SC 29425, USA. 7. Division of Trauma, Critical Care, and Burn, The Ohio State University, Columbus, OH 43210, USA. 8. Arthur G. James Comprehensive Cancer Center Cancer Cachexia Program, The Ohio State University, Columbus, OH 43210, USA; Division of Surgical Oncology, The Ohio State University, Columbus, OH 43210, USA. 9. Arthur G. James Comprehensive Cancer Center Cancer Cachexia Program, The Ohio State University, Columbus, OH 43210, USA; Department of Pediatrics, Medical University of South Carolina, Charleston, SC 29425, USA; Hollings Cancer Center, Medical University of South Carolina, Charleston, SC 29425, USA. Electronic address: guttridg@musc.edu.
Abstract
Cachexia is a wasting syndrome characterized by pronounced skeletal muscle loss. In cancer, cachexia is associated with increased morbidity and mortality and decreased treatment tolerance. Although advances have been made in understanding the mechanisms of cachexia, translating these advances to the clinic has been challenging. One reason for this shortcoming may be the current animal models, which fail to fully recapitulate the etiology of human cancer-induced tissue wasting. Because pancreatic ductal adenocarcinoma (PDA) presents with a high incidence of cachexia, we engineered a mouse model of PDA that we named KPP. KPP mice, similar to PDA patients, progressively lose skeletal and adipose mass as a consequence of their tumors. In addition, KPP muscles exhibit a similar gene ontology as cachectic patients. We envision that the KPP model will be a useful resource for advancing our mechanistic understanding and ability to treat cancer cachexia.
Cachexia is a wasting syndrome characterized by pronounced skeletal muscle loss. In cancer, cachexia is associated with increased morbidity and mortality and decreased treatment tolerance. Although advances have been made in understanding the mechanisms of cachexia, translating these advances to the clinic has been challenging. One reason for this shortcoming may be the current animal models, which fail to fully recapitulate the etiology of humancancer-induced tissue wasting. Because pancreatic ductal adenocarcinoma (PDA) presents with a high incidence of cachexia, we engineered a mouse model of PDA that we named KPP. KPPmice, similar to PDApatients, progressively lose skeletal and adipose mass as a consequence of their tumors. In addition, KPP muscles exhibit a similar gene ontology as cachectic patients. We envision that the KPP model will be a useful resource for advancing our mechanistic understanding and ability to treat cancer cachexia.
The defining symptom of cancer cachexia is unintentional weight loss because of depletion of skeletal muscle. This wasting cannot be prevented by supplemental nutrition and is often correlated with increased whole-body inflammation and anorexia (Argilés et al., 2014). Cachexia occurs in at least half of all cancerpatients and is associated with advanced disease and palliative care. However, in gastrointestinal malignancies, especially pancreatic ductal adenocarcinoma (PDA), cachexia often presents much earlier, with approximately 70% of PDApatients meeting cachexia criteria at cancer diagnosis (Fearon et al., 2011; Nemer et al., 2017).With a 9% 5-year survival rate and increasing incidence rates, PDA remains a devastating disease (American Cancer Society, 2018). Although resistance to current therapies and the difficultly of diagnosing early-stage malignancy are important contributors to the high mortality rate of PDApatients, the cachexia syndrome also contributes to poor survival in this disease by lowering patient tolerance of chemo- and radiotherapy (Andreyev et al., 1998; Bachmann et al., 2008; Kieler et al., 2017; Moningi et al., 2015; Pausch et al., 2012; von Haehling et al., 2016). Thus, as the search continues to more effectively diagnose and treat PDA, managing cachexia provides an additional strategy to decrease patient morbidity and mortality.Despite the clear need to prevent and treat cachexia, therapies are currently lacking, as evidenced by two recent phase III clinical trials that failed to achieve their primary endpoints (Le-Rademacher et al., 2017; Temel et al., 2016). Although a number of factors likely contributed to the failure of these trials, one limitation may be the animal models currently used to study cancer cachexia. Two commonly used mouse models are xenograft colon-26 (C-26) and Lewis lung carcinoma (LLC) (Acharyya et al., 2004; Bonetto et al., 2016; He et al., 2013; Judge et al., 2014; Penna et al., 2010; Talbert et al., 2017; Zhang et al., 2017). Although these models have been useful for our laboratory and others in elucidating numerous mechanisms of tissue wasting, they often come under scrutiny for their inability to fully recapitulate the phenotype of humancancers, either by not forming spontaneous tumors or because of their inability to reconstitute a tumor microenvironment. These models are used in a tumor-agnostic manner and are also quite large, typically representing more than 10% of the entire body mass (Talbert et al., 2017; Zhang et al., 2017). They are also aggressive and induce cachexia on a timescale of only a few weeks (Roberts et al., 2013a; Talbert et al., 2014, 2017).In this study, we tested for a disparity between mice and humans by comparing global gene expression changes in skeletal muscles from C-26 and LLC-bearing mice compared with biopsies obtained from PDApatients with cachexia. The results revealed little overlap in both the number and classification of genes expressed, emphasizing that, on the molecular level, these models may not be the most appropriate to study humancachexia. In addition to these xenograft models, the classic genetically engineered mouse model (GEMM) of PDA, called the Kras; p53; Cre (KPC) mouse, is gaining attraction in cachexia studies. However, as we reveal, this model also has limitations that question its usefulness to study cachexia. Such findings prompted us to design a mouse model of PDA to better reflect the features of humancancer-induced wasting.
RESULTS
The C-26 and LLC Models Do Not Resemble the Muscle Gene Expression Signature of PDA Patients
To assess the ability of the C-26 and LLC models to reflect PDA-induced cachexia, we compared differences between control and cachectic transcriptional profiles determined by RNA sequencing (RNA-seq) with differences between cachectic pancreatic cancerpatients and control patients. In the C-26 model, using a false discovery rate (FDR) of < 0.05, we identified 3,474 differentially expressed genes (DEGs) between control and cachectic muscles (Figure 1A; Table S1), which is consistent with published microarray data (Bonetto et al., 2011; Cornwell et al., 2014; Judge et al., 2014). For the LLC model, we identified 788 DEGs (Figure 1A; Table S1), again within the range of published data (Blackwell et al., 2018). Although the LLC model demonstrated fewer DEGs than C-26 mice, gene ontology analysis showed that DEGs from both models were generally associated with processes of RNA translation (Figure S1A). Interestingly, when similar gene expression profiling was performed with cachectic PDApatients, only 141 DEGs were identified compared with weight-stable patients without cancer (Figure 1B; Table S1). Although these DEGs were too few to associate with a biological process by gene ontology, all five cellular components that associated with these DEGs involved the extracellular matrix (Figure S1B).
Figure 1.
Comparing Xenograft Models with Cachectic Pancreatic Cancer Patients
(A) RNA-seq of tibialis anterior (TA) muscle from C-26 and LLC tumor-bearing mice (n = 2 males per group).
(B) RNA-seq of n = 5 male non-cancer patients and 5 male cachectic PDA patients.
(C–F) Gene expression of (C) Atrogin-1, (D) MuRF1, (E) Atg5, and (F) Bnip3 (n = 8 males for C-26; n = 6 males for LLC; n = 11 controls, 17 cachectic patients, approximately equal male and female).
Patient characteristics for RNA-seq can be found in Table S2, and patient characteristics for RT-PCR can be found in Table S3. Bars represent mean ± SEM. Closed circles represent individual data points. *p < 0.05 in a t test.
See Figure S1 for additional information.
A striking feature of these results was that more than 95% of the DEGs from human muscle were decreased in cachectic patients, which we confirmed by qRT-PCR (Figure S1C); this is consistent with previous findings in cachectic patients with upper gastrointestinal (GI) malignancies (Gallagher et al., 2012). This gene expression pattern stands in stark contrast to the overwhelming upregulation of genes seen in the C-26 model (80% upregulated) or the approximately equal proportions of up-regulated and downregulated DEGs observed in LLC tumor-bearing mice.These results suggested that the gene signatures in muscle from the standard C-26 and LLC models of cancer cachexia are distinct from that of muscle from cachectic pancreatic cancerpatients. To test for a discordance specifically in relation to muscle atrophy, we measured the expression of genes coding for components of the ubiquitin proteasome and autophagy systems, which are considered to be causative in cancer-induced muscle wasting (Tisdale, 2009). The results showed the typical large increase in expression of the E3 ubiquitin ligases MuRF1 and Atrogin-1 in C-26 and LLC models, whereas no changes in the expression of these genes were seen in muscles from cachectic PDApatients (Figures 1C and 1D). Expression of the autophagy genes Atg5 and Bnip3 was also increased in muscle from C-26 and LLC mice but remained unchanged in cachectic PDApatients (Figures 1E and 1F). A similar lack of transcriptional changes in these genes in cachectic patients has been reported by other groups (Bonetto et al., 2013; D’Orlando et al., 2014). Collectively, we conclude from these data that xenograft C-26 and LLC models are not optimal to recapitulate the muscle wasting phenotype of humancancer-induced cachexia.
KPC Mice Exhibit Variability and Tissue Mass Changes that Do Not Correlate with Pancreatic Cancer Progression
Next we tested the established KPC GEMM of PDA (Hingorani et al., 2005), which has recently been described as a model of cachexia (Parajuli et al., 2018; Petruzzelli et al., 2014; Roberts et al., 2013b). KPC mice utilize the Pdx1 promoter to drive Cre recombinase to express mutant Kras as well as either a floxed or a lox-stop-lox (LSL) mutant allele of Trp53, leading mice to a median survival of approximately 150 days (Figure S2A; Hingorani et al., 2005; Shakya et al., 2013). Consistent with previous reports, we too observed that KPC mice (Kras+/LSL-G12D, Trp53+/R270H, Pdx1) that reached endpoint criteria weighed significantly less than their littermate controls (Figures 2A and S2B). This reduction in weight correlated with reduced hindlimb muscle (tibialis anterior [TA], quadriceps [QUAD], and gastrocnemius [GAST]) mass and lower white adipose tissue mass (Figures 2B, S2C, and 2C). However, when correlating body weight and muscle wasting with pancreas pathology, we were surprised to find that KPC mice tended to be smaller than their littermate control mice regardless of the severity of their pancreatic disease (Figure 2D, 2E, and S2D). In fact, some KPC mice with non-invasive pancreatic lesions (referred to as mPanIN) were among the smallest mice compared with their littermates, whereas other mice with advanced PDA were of similar weight as their littermate controls (Figure S2E). Similarly, KPC mice tended to have smaller muscle mass regardless of pancreas pathology (Figure 2F). Consistent with the heterogeneity of the model, an RNA-seq analysis of muscle from KPC mice similar to the one performed for the C-26 and LLC models returned only a single DEG (FDR < 0.05; Table S1). These results are not in keeping with PDApatients, where lower body and peripheral tissue masses are associated with cancer.
Figure 2.
The KPC Mouse as a Model of Cancer Cachexia
(A–C) KPC mice that have reached endpoint criteria have lower body weights (A; n = 11), muscle weights (B; n = 11), and gonadal white adipose tissue masses (C; n = 5) than littermate control mice.
(D–F) However, when pancreatic histopathology is considered (D), mice with mPanIN lesions (n = 4), early PDA (n = 4), and advanced PDA (n = 3) all tend to have lower body weights (E) and muscle weights (F).
Bars represent mean ± SEM. Closed circles represent individual data points. *p < 0.05 in a paired t test on absolute weights. Scale bars, 50 μm.
See Figure S2 for additional information.
Generation of the KPP Mouse
Given the limitations we identified in both xenograft models and KPC mice, we turned our efforts to generating another model of cancer-induced wasting. When developing this model, we considered several aspects reflective of human disease. First, we sought to model PDA because this disease has among the highest incidences and severities of cancer cachexia (Baracos et al., 2018). Next, because PDA develops in adults, we wanted to induce cancer in postnatal mice. Further, we sought to achieve a direct association between the development of PDA and an ensuing cachexia condition. Specifically, because patients with PDA-induced cachexia lose existing muscle and fat, we sought to model true tissue wasting as opposed to a condition of “perceived wasting,” where tissues do not gain mass because they fail to develop. Finally, we wanted a model that developed cachexia on a slower timescale than the rapid wasting that occurs in current xenograft models.To meet these criteria, we started with the same LSL-KrasG12D mutant allele found in the KPC mouse but removed the stop cassette with a tamoxifen-inducible Cre recombinase driven by the Ptfla promoter, also known as p48, which remains active into adulthood in the pancreas (Pan et al., 2013). Our model also used two floxed alleles of the tumor suppressor Pten that were inactivated at the same time mutant Kras was induced (Stanger et al., 2005; Ying et al., 2011). Over 70% of humanpancreatic tumors demonstrate reduced Pten protein expression, making Pten deletion relevant to pancreatic cancerpatients (Jiang et al., 2014; Ying et al., 2011). Together, these mice exhibit the genotype Kras+/,Ptf1a+/, Pten (Figure 3A), which we named KPP.
Figure 3.
Generation of the KPP Mouse and Endpoint Analysis
(A) The alleles of the KPP mouse.
(B) Naive Ptfa1 mice express background fluorescence in pancreas sections, whereas pancreata of tamoxifen-treated Ptfa1 mice exhibit a high fluorescence signal.
(C) KPP mice induced with tamoxifen between 24 and 28 days of age had an average survival of 107 days of age (n = 12). Ticks on the control line indicate points when a control mouse was euthanized for comparison with a littermate KPP mouse. Control genotypes include Kras (n = 6), Kras (n = 1), Kras (n = 1), Kras (n = 1), and Kras (n = 3). Control genotypes are presented with their paired KPP mouse in Table S4.
(D) Endpoint KPP mice demonstrate moderately well-differentiated to well-differentiated PDA as evidenced by H&E, Alcian blue, CK19, Ki67, and α-smooth muscle actin (α-SMA) staining. Scale bar, 50 μm.
See Figure S3 for additional information.
We first confirmed that the Ptf1a promoter is active only in the presence of tamoxifen by breeding Ptf1a+/mice to Rosa26-tdTomato reporter mice (Madisen et al., 2010). Mice treated with five consecutive injections of tamoxifen expressed Tomato in acinar cells throughout the pancreas, whereas Tomato expression was not present in Ptf1a+/ mice not treated with tamoxifen (Figure 3B). To initiate tumorigenesis, KPPmice were injected with tamoxifen between 24 and 28 days of age. At this age, there was no difference in body mass between control and KPPmice (Figure S3A). With 100% penetrance, KPPmice reached endpoint criteria (ascites, weight loss, and lethargy) at a median age of 107 days (Figure 3C). In comparison, all control mice showed no obvious phenotype at this age (genotypes for each control mouse can be found in Table S4). At the endpoint, the weights of KPP pancreata were significantly increased compared with littermate controls, consistent with tumor burden (Figure S3B). Histological analysis demonstrated well-differentiated to moderately well-differentiated ductal adenocarcinomas composed of anastomosing and branching glands lined by mucinous epithelium accompanied by abundant fibrous stromata. The pancreatic parenchyma was extensively replaced by the neoplasms (Figure 3D; Figure S3C). Cystic glands with intraluminal papillary projections were often noted. Expression of cytokeratin 19 (CK19) demonstrated the ductal phenotype of the glandular epithelium, and Alcian blue staining confirmed the presence of mucin. Additional staining for Ki-67 and α-smooth muscle actin revealed epithelial and stromal proliferative activity and the presence of large numbers of stromal myofibroblasts, respectively (Figure 3D; Figure S3C; Aichler et al., 2012).
KPP Mice Exhibit a Cachectic Phenotype
We next sought to evaluate whether KPPmice suffered from cachexia. KPPmice at their endpoint exhibited decreased body weight compared with their littermate controls (Figure 4A; Figure S4A) but, importantly, had similar tibia lengths (Figure 4B), suggesting that the lower body weights of KPPmice were not due to a failure to grow. KPPmice also exhibited decreased TA, QUAD, and GAST muscle masses (Figure 4C). In the GAST, this decrease in muscle weight was primarily due to decreased cross-sectional area (CSA) of type IIB or IIX muscle fibers (Figure 4D). KPP muscle also showed a trend toward reduced type IIA fiber size (p = 0.06), whereas type I fibers were spared, which is consistent with other mouse models of cancer cachexia (Acharyya et al., 2004; Roberts et al., 2013a). Functionally, muscles from KPPmice exhibited a decrease in total muscle force production at higher stimulation frequencies, but specific force was not altered (Figure 4E), suggesting that the sarcomere structure was intact. Consistent with this phenotype, the content of sarcomeric proteins actin and myosin per mass of muscle was unchanged in KPPmice (Figure S4B), which is unlike what we and others have reported in xenograft cachexia models (Acharyya et al., 2004; Bonetto et al., 2011) but in line with reports suggesting that sarcomeric protein content and specific force are maintained in muscles from cachectic cancerpatients (Toth et al., 2013; Weber et al., 2009). Further, night cage activity was decreased, indicating that KPPmice exhibit reduced whole-body function (Figure 4F).
Figure 4.
The KPP Mouse Develops Cachexia
(A and B) KPP mice are smaller than their littermate controls when reaching endpoint criteria (A) but have similar tibia lengths (B).
(C) KPP mice exhibit reduced TA, quadriceps (QUAD), and gastrocnemius (GAST) muscle masses.
(D) Muscle wasting in KPP GAST is associated with lower type IIB or IIX fiber cross-sectional area, whereas type IIA fibers tended to be smaller (p = 0.06).
(E) Absolute ex vivo extensor digitorum longus (EDL) muscle force was significantly reduced at higher stimulation frequencies, but specific force was not altered.
(F) Endpoint KPP mice demonstrate decreased night (awake) activity counts, indicative of depressed whole-body function.
(G and H) KPP mice demonstrate decreased heart weight (G) and decreased masses of gonadal white and subscapular brown adipose (H).
(I) Consistent with decreased adipose tissue stores, KPP mice exhibit an increased daytime respiratory exchange ratio (RER).
(J) KPP mice exhibited decreased night oxygen consumption (VO2).
Bars represent mean ± SEM. Closed circles represent individual data points. *p < 0.05 in a paired t test. n = 12 per group; for cross-sectional area and metabolic data, n = 5 per group, and for muscle function data, n = 3 per group. Even when expressed as percent controls, statistical tests were conducted on absolute weights.
See Figure S4 for additional information.
In addition to reduced muscle mass and function, endpoint KPPmice had enlarged spleens (Figure S4C), which is a feature of both PDA and cachexia (Bonetto et al., 2016; Michaelis et al., 2017; Talbert et al., 2014). Furthermore, KPPmice had significantly lower heart masses (Figure 4G), which is also associated with many models of cancer cachexia (Bonetto et al., 2016; Michaelis et al., 2017; Talbert et al., 2014). KPPmice also had pronouncedly lower white and brown adipose tissue masses (Figure 4H). Consistent with depleted adipose tissue stores, KPPmice displayed an increased resting respiratory exchange ratio (RER), indicative of greater utilization of carbohydrate fuel stores (Figure 4I). Finally, KPPmice consumed less oxygen during dark hours (Figure 4J), which may suggest that carbohydrate utilization is increased or may simply reflect differences in activity (Figure 4F).To ensure that these cachectic phenotypes were not limited to young mice, where tumor induction was initiated between 3 and 4 weeks of age, we attempted to mimic humanPDA in older adults by injecting tamoxifen in 1-year-old KPPmice. Importantly, uninjected KPPmice showed no apparent pancreas pathology, confirming tight regulation of the Ptf1a allele (Figure S4D). In contrast, 1-year-old KPPmice developed PDA with a median post-tumor initiation survival of 158 days (Figures S4D–S4F) and exhibited weight loss with associated lower masses of skeletal, cardiac, and adipose tissues (Figures S4G–S4J). Thus, induced cachexia occurs in adult KPPmice.
KPP Mice Undergo Progressive Wasting
Although patients can exhibit cachexia throughout the course of their disease, the incidence of cachexia tends to increase as the disease progresses (Dewys et al., 1980). To determine whether KPPmice exhibited progressive wasting, we induced tumorigenesis at 24-28 days of age and then euthanized cohorts of mice at 60, 75, and 90 days of age during disease progression, as evidenced by tumor burden (Figure S5A). The extent to which the pancreatic parenchyma of KPPmice was replaced by proliferating ductal profiles and accompanying stromal fibrosis increased remarkably with age (Figure 5A). Acinar-to-ductal metaplasia, pancreatic intraepithelial neoplasia (mPanIN), and cystic papillary neoplasms, all of which constitute non-invasive lesions, and occasional focally invasive (early carcinoma) lesions were predominant at 60 and 75 days. Notably, large areas of the exocrine and endocrine pancreas remained unaffected. In contrast, significantly larger portions of the pancreatic parenchyma were replaced by both non-invasive and invasive (advanced carcinoma) lesions at later time points, with severe parenchymal atrophy at 90 days and virtually no remaining histologically normal pancreas by the endpoint.
Figure 5.
KPP Mice Exhibit Progressive Cachexia Associated with Advancing Pancreas Pathology
(A) Pancreatic disease in KPP mice progresses across their lifespan.
(B–E) Additionally, compared with their littermate controls, KPP mice progressively lose bodyweight (B) , skeletal muscle (C), heart mass (D), and white and brown adipose tissue (E).
Bars represent mean ± SEM. Closed circles represent individual data points. “Endpoint” KPP mice have reached Institutional Animal Care and Use Committee (IACUC) euthanasia criteria and are the same mice as shown in Figures 3 and 4 (n = 12). n = 5–6 mice per group for the 60-, 75-, and 90-day time points. Genotypes for each control mouse can be found in Table S6. *p < 0.05 in a paired t test on absolute weights. Scale bar, 50 μm.
See Figure S5 for additional information.
Although tibia length was not different between control and KPPmice across all time points (Figure S5B), KPPmice exhibited a progressive decline in body weight compared with their littermate controls (Figure 5B). Significantly, this decrease in weight matched a progressive decline in skeletal muscle (TA, QUAD, and GAST; Figure 5C), heart (Figure 5D), and adipose mass relative to controls (Figure 5E). In both male and female KPPmice, the decline in both absolute skeletal muscle began between days 75 and 90 (Figure S5C), showing that KPPmice exhibit progressive PDA-induced tissue loss, reflective of the human disease. Although KPPmice clearly lose existing adipose tissue, 60-day KPPmice tend to have less adipose tissue than their controls, suggesting that KPPmice may not put on adipose tissue as effectively as control mice during development (Figure S5D).
Cachectic Muscle from KPP Mice and PDA Patients Exhibits a Similar Gene Ontology
Finally, we compared transcriptional profiles between KPPmice and PDApatients with cachexia (Figures 6A and 6B). In sharp contrast to our findings with the C-26 and LLC xenograft models, only 172 DEGs were identified in KPPmice using an FDR of < 0.05. However, the five most significant biological process categories identified by gene ontology were related to the extracellular matrix, reminiscent of the cellular component gene ontology of cachectic PDApatients (Figure S6A). Furthermore, KPPmice exhibited smaller increases in the expression of E3 ubiquitin ligase and autophagy genes compared with the common xenograft models (Figures 6C–6F), and these modest increases only occurred during end-stage cachexia (Figure S6B). Together, these results imply that the cachexia phenotype of KPPmice may more closely resemble that of PDApatients.
Figure 6.
The Gene Ontology of KPP Mice Resembles that of Cachectic PDA Patients
(A) RNA-seq of TA muscle from KPP mice (n = 2 males per group).
(B) RNA-seq of n = 5 male non-cancer patients and 5 male cachectic PDA patients.
(C–F) Gene expression of (C) Atrogin-1, (D) MuRF1, (E) Atg5, and (F) Bnip3 (n = 8 males for C-26; n = 6 males for LLC, n = 3 males and 3 females for KPP; n = 11 controls, 17 cachectic patients, approximately equal male and female).
Patient characteristics for RNA-seq can be found in Table S2, and patient characteristics for RT-PCR can be found in Table S3. Bars represent mean ± SEM. Closed circles represent individual data points. *p < 0.05 in a t test.
See Figure S6 for additional information.
DISCUSSION
Because mechanistic studies of cancer cachexia are difficult to complete in humanpatients, our current knowledge of mechanisms of cancer-induced wasting derives mainly from animal models of the disease. However, our work presented here suggests that, in many ways, two of the most commonly used xenograft mouse models of cachexia do not reflect gene expression changes seen in muscle of cachectic PDApatients. This is perhaps not surprising because both the C-26 and LLC models result in aggressive tumors and induce rapid wasting over an approximately 1- to 2-week period (Acharyya et al., 2004, 2005; He et al., 2013; Talbert et al., 2014, 2017; Zhang et al., 2017). In addition, the loss of skeletal muscle and adipose mass in these models is generally dependent on inflammatory factors whose concentration in the circulation far exceeds levels recorded in cachectic patients (Lerner et al., 2015, 2016a, 2016b; Llovera et al., 1998b; Strassmann et al., 1992; Talbert et al., 2018).In an effort to better model the cachexia experienced by patients, a number of laboratories have recently published new mouse models of cancer cachexia, often utilizing more relevant cachexia-inducing cancers, with PDA being the most common. The three main approaches of these models have been (1) intraperitoneal injections of PDA cells, which localize to the pancreas; (2) orthotopic models of PDA in which cancer cells are injected directly into the pancreas; and (3) patient-derived xenograft (PDX) models in which a portion of a resected humanpancreatic tumor is surgically attached to a mouse pancreas (Delitto et al., 2017; Go et al., 2017; Greco et al., 2015; Michaelis et al., 2017). Although these models have the advantage of establishing tumors within the pancreas, some are limited by their narrow window of wasting, similar to the C-26 and LLC models (Greco et al., 2015; Michaelis et al., 2017; Yang et al., 2019). Additionally, it is possible that the post-surgical inflammatory environment created by orthotopic injections and surgical tumor implantation contributes to the appearance of wasting rather than deriving from bona fide, tumor-induced tissue loss. Finally, use of humantumors or tumor cells necessitates the use of immunocompromised mice, which themselves may fall short in reconstituting the immune profile of cachexia. Thus, although these models may be an improvement over the C-26 or LLC models, they still face challenges in replicating humancancer cachexia.Although a growing number of reports describe KPC mice as a model of cancer cachexia, in our view, this model also has significant limitations. Although humanPDA is estimated to develop over the course of at least a decade (Yachida et al., 2010), no evidence suggests that mutant Kras is active prior to birth, as in the KPC mouse (Guz et al., 1995). Because neonatal skeletal muscle quadruples in size during the first 3 weeks of life (White et al., 2010), this raises the suspicion that prenatal activation of an oncogene might affect the development of skeletal muscle. This notion is supported by our findings that KPC mice tend to be smaller than their littermate controls regardless of pancreas pathology. An additional consideration with the use of KPC mice as a cachexia model is the propensity of these mice to develop other tumors outside of the pancreas (Gades et al., 2008; Lampson et al., 2012), which might influence how cachexia is interpreted. Admittedly, it may be possible to reduce the incidence of non-pancreas tumors by backcrossing mice into a pure strain, but this remains to be tested. Finally, we speculate that performing pre-clinical cachexia studies would be challenging in the KPC model because the slope of the survival curve of these mice is gradual (Hingorani et al., 2005; Shakya et al., 2013), meaning large cohorts would likely be required to achieve sufficient power to assess the effectiveness of an anti-cachexia compound.For our purposes, we sought to use a GEMM of PDA that could overcome some of the shortcomings of the current models. Our findings show that the KPPmouse is suitable as a model of cancer cachexia for several reasons. The inducible nature of the Cre re-combinase utilized in the KPPmouse allows PDA and its associated cachexia to be induced after the rapid neonatal growth of mice has concluded. This allowed us to better model the actual loss of muscle and adipose tissue in patients with PDA, as opposed to potentially slowing development and giving the appearance of cachexia. We also showed that the inducible Cre is amenable to inducing tumor developments older mice, which allows manipulation of experimental conditions associated with PDA in older adults. Moreover, the slope of the survival curve of KPPmice is steeper than that of KPC mice (Figure S6C; Hingorani et al., 2005; Shakya et al., 2013), improving the feasibility of testing potential anti-cachexia compounds.Although tumor-induced muscle wasting in KPPmice appears to more closely model the cachexia seen in PDApatients, this model is not without limitations. Because KPPmice lose normal pancreatic parenchyma, we cannot exclude the possibility, as reported recently (Danai et al., 2018), that pancreatic exocrine insufficiency contributes to tumor-induced wasting in this model. Further, it is possible that features of KPPmice are selective to PDA and, thus, less useful to study other tumor types that also promote cachexia. Despite these limitations, we view the KPPmouse as an improvement over existing animal models of cachexia and anticipate that KPPmice will prove to be a useful tool in improving our understanding of the mechanisms driving tissue wasting and in translating that understanding into new anti-cachexia therapies.
STAR★METHODS
LEAD CONTACT AND MATERIALS AVAILABILITY
Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Denis Guttridge (guttridg@musc.edu).
EXPERIMENTAL MODEL AND SUBJECT DETAILS
Animals
All animal experiments were approved by the Ohio State University Institutional Animal Care and Use Committee under protocol 2010A00000177 or the Medical University of South Carolina Institutional Animal Care and Use Committee under protocol 2018-00328. All animals were housed with littermates and given ad libitum access to standard chow and water. C-26 and LLC mice were allocated to tumor-bearing and control groups randomly, genetic models were allocated by genotype.
C-26 Mice
Experiments using the colon-26 (C-26) model were conducted as previously described (He et al., 2013; Talbert et al., 2014; Tanaka et al., 1990). Male CD2F1 mice from Charles River Laboratories were injected subcutaneously in the right flank with 1×106 C-26 cells under anesthesia. Control mice received an injection the same volume of phosphate buffered saline. Mice were euthanized by CO2 asphyxiation 21 days after injection, at which time tumor-bearing mice had reached IACUC euthanasia criteria of tumor volume or greater than 20% body weight loss.
LLC Mice
Experiments using the Lewis Lung Carcinoma (LLC) model were conducted as previously described (He et al., 2013; Llovera et al., 1998a; Talbert et al., 2017). Male C57BL/6J mice from Jackson Laboratories were injected intramuscularly in the right gluteus muscle with 5×105 LLC cells under anesthesia. Control mice received an injection the same volume of phosphate buffered saline. Mice were euthanized by CO2 asphyxiation 21 days after injection, at which time tumor-bearing mice had reached IACUC euthanasia criteria of tumor volume or > 20% weight loss.
KPC Mice
KPC mice (Kras+/, Trp53+/, Pdx1+/) were provided by the Target Validation Shared Resource of The Ohio State Comprehensive Cancer Center. Mice were maintained on a mixed background (Shakya et al., 2013). Mice were euthanized by CO2 asphyxiation upon reaching IACUC-approved endpoint criteria, which included ascites, weight loss, lethargy, and severe skin papillomas. Both male and female KPC mice were utilized, with same-sex littermates were used as controls.
KPP Mice
Alleles used to generate KPPmice were obtained from Jackson Laboratory on a C57BL/6J background. The initial cohort of KPPmice was generated by breeding Kras, Pten+/ mice to Ptf1a, Pten+/ mice. Subsequent mice, including all mice euthanized prior to reaching endpoint criteria, were generated by breeding Kras, Ptenmice to Ptf1a, Ptenmice. Both male and female KPPmice were utilized, with same-sex littermates were used as controls. Genotypes of control mice appear in Tables S4, S5, and S6.KPPmice and littermate controls were treated with tamoxifen by five consecutive daily intraperitoneal injections. Mice treated between 24-28 days of age received 1 mg tamoxifen/10 g of body weight, while year-old mice received 2 mg tamoxifen/dose.Endpoint KPPmice euthanized upon reaching IACUC endpoint criteria, which included ascites, weight loss, lethargy, and a body condition score less than 1.5 (Ullman-Culleré and Foltz, 1999). Mice were euthanized at a surgical plane of isoflurane by cardiac puncture followed by cervical dislocation. Final body weights were collected after the draining of ascites fluid. Absence of pancreas pathology was confirmed in all mice utilized as controls by a veterinary pathologist.
Human Subjects
Patients undergoing attempted pancreatic resections at The Ohio State University Wexner Medical Center were asked to participate in a tissue banking protocol under which rectus abdominus muscle biopsies taken during surgery were deposited into a tissue bank run by The Ohio State University Comprehensive Cancer Center Pancreatic Cancer Program. Control muscle tissue was obtained from consenting volunteers without malignancy who were undergoing laparotomy for elective indications (e.g., hernia repair, ostomy reversal). All experiments were approved by The Ohio State University Cancer Institutional Review Board and all patients provided informed consent.Patients with greater than 5% loss of their pre-illness weight were classified as cachectic (Fearon et al., 2011). When possible, self-reported weight loss was supported by a patient’s existing medical record. All tissue samples used in this analysis were from patients who had not received chemotherapy or radiation prior to surgery for this incidence of cancer. A previous history of a cancer was not an exclusionary criterion. Clinical characteristics of the patients from which muscle was used for RNA-Seq are included in Table S2, with characteristics of patients used for RT-PCR in Table S3. RNA-Seq was conducted on muscle from male subjects, while RT-PCR was performed on a roughly even mix of male and female subjects.
METHOD DETAILS
RNA-Seq and Gene Ontology
RNA was isolated from snap-frozen tibialis anterior (mouse) or rectus abdominus (human) muscle using Trizol reagent (Life Technologies, Carlsbad, CA) according to the manufacturer’s instructions. RNA quality was assessed using an Agilent Bioanalyzer RNA 6000 Nano chip and RIN numbers for all samples were greater than 7. rRNA was removed from purified total RNA using Ribo-Zero Gold rRNA Removal kit (Illumina; MRZG12324). 200 ng of rRNA-depleted RNA was used for the construction of the library using the SureSelect Strand Specific RNA library prep kit (Agilent; G9691A) according to the manufacturer’s instruction, except for omitting the purification step before fragmentation. Barcoded libraries were pooled and sequenced using an Illumina HiSeq4000.For muscle samples from mice, raw reads were aligned to Mus musculus GRCm38 from ensembl with tophat2v2.1.0 (Kim et al., 2013) which ran with gene model annotations provided by GRCm38 v83. Sequence for samples from multiple lanes were combined. Alignment QC was generated with RSeQCv2.6.4 (Wang et al., 2012) and picardv2.4.1 (http://broadinstitute.github.io/picard). Fragment counts were generated with featureCounts v1.4.5 (Liao et al., 2014) from the subread package for genes described by ensembl GRCm38 v83. For reads with multiple alignments, the primary alignment was counted by featureCounts. Strand-specific read counting was performed based on sequence that is reversely stranded. Differential expression was performed with limma (Ritchie et al., 2015) for genes with CPM > 2 in 4 or more samples.For muscle samples from patients, raw reads for human samples were aligned to Homo sapiens GRCh38 with HISAT2 v2.0.5 (Kim et al., 2015). Alignment QC was generated with RSeQCv2.6.4 (Wang et al., 2012) and picardv2.4.1 (http://broadinstitute.github.io/ picard). Fragment counts were generated with featureCounts v1.4.5 (Liao et al., 2014) from the subread package for genes described by ensembl GRCh38 v86. For reads with multiple alignments, the primary alignment was counted by featureCounts. Strand-specific read counting was performed based on sequence that is reversely stranded. Differential expression was performed with limma (Ritchie et al., 2015) for genes with CPM > 2 in more than half the samples. For human samples, gene downregulation confirmed by real-time RT-PCR for 9 samples with RNA available. For both human and mouse samples, gene ontology was performed using the ToppFun application of the ToppGene Suite (Chen et al., 2009). Heatmaps were produced with Morpheus from the Broad Institute (https://software.broadinstitute.org/morpheus).
Real-Time RT-PCR
Messenger RNA was isolated from snap-frozen quadriceps (mouse) or rectus abdominus (human) muscle using Trizol reagent (Life Technologies, Carlsbad, CA) according to the manufacturer’s instructions. M-MLV Reverse Transcriptase (Life Technologies) was used to reverse-transcribe total RNA to cDNA according to the manufacturer’s instructions. Real-time PCR was performed on an Applied Biosystems StepOnePlus instrument using SYBR Green mix (Bio-Rad, Hercules, CA). GAPDH was used as the housekeeping gene. Primer sequences appear in Table S7.
Pancreas Histopathology
Formalin-fixed, paraffin-embedded, hematoxylin-and-eosin-stained pancreata of KPC and KPPmice were assessed by a veterinary pathologist employing recommended nomenclature for pancreatic exocrine neoplasia (Hruban et al., 2006). To better characterize the lesions, pancreas sections from endpoint KPPmice were stained for Alcian blue to detect mucin and glycoproteins, Ki67 (1:200), α-smooth muscle actin (α-SMA, 1:5000), and cytokeratin 19 (CK19, 1:500). The sections were imaged using a Vectra Multispectral Imaging System (Perkin-Elmer).
CLAMS
Endpoint KPPmice (n = 5) were single-housed in a Comprehensive Lab Animal Monitoring System (CLAMS) unit (Columbus Instruments, Columbus, OH) for 24 hours prior to euthanasia. Environmental temperature was held constant at 25 °C. Mice were placed in the unit at 10 AM, and daytime data were collected from 12 PM until five minutes prior to lights out. Night data were collected from one hour after lights out until 5 minutes prior to lights on.
Muscle Fiber Size Measurements
Muscle fiber cross-sectional area (CSA) of individual fiber types was determined from 10 μM sections of gastrocnemius stained for laminin, myosin heavy chain Type IIA, and myosin heavy chain Type I by a modification of Minnaard (Minnaard et al., 2005). Muscle fiber CSA was determined using a semi-automated ImageJ plug-in designed in the Guttridge lab which outlines the internal laminin border of individual muscle fibers and then assigns fiber types based upon color of the fiber.
Muscle Function Measurements
Extensor digitorum longus (EDL) force production was measured across a force-frequency curve. Force was normalized to CSA as previously described (Segal et al., 1986).
Sarcomeric Protein Analysis
Muscle sarcomere components were analyzed as previously described (Blough et al., 1996).
QUANTIFICATION AND STATISTICAL ANALYSIS
Statistical analysis was conducted with GraphPad Prism 7, and the details of these analyses appear in the figure legends with samples per group (n). Unless otherwise noted, data are presented as mean ± the standard error of the mean (SEM). For KPC and KPPmice, comparisons between groups were made by two-tailed paired t tests. For C-26 and LLC mice and comparisons between human subjects, unpaired two-tailed tests were used. Statistical analysis of tissue masses was conducted on absolute values, regardless of the presentation of the data. Statistical significance was defined a priori as p < 0.05.
DATA AND CODE AVAILABILITY
Raw RNA-Seq data files are available in the NCBI’s GEO: GSE133523 and GSE133524.
KEY RESOURCES TABLE
REAGENT or RESOURCE
SOURCE
IDENTIFIER
Antibodies
Ki67
Abcam
ab16667; RRID: AB_302459
α-smooth muscle actin (α-SMA)
Abcam
ab5694; RRID: AB_2223021
cytokeratin 19 (CK19)
Iowa Development Studies Hybridoma Bank
TROMA-III; RRID: AB_2133570
laminin
ThermoScientific
MA1-06100; RRID: AB_559896
myosin heavy chain Type I
Iowa Development Studies Hybridoma Bank
A4.840; RRID: AB_528384
myosin heavy chain Type IIA
Iowa Development Studies Hybridoma Bank
sc-71; RRID: AB_2147165
Biological Samples
rectus abdominus muscle biopsies
Pancreatic cancer patients and control patients undergoing abdominal surgery
Authors: Sarah M Judge; Michael R Deyhle; Daria Neyroud; Rachel L Nosacka; Andrew C D'Lugos; Miles E Cameron; Ravneet S Vohra; Ashley J Smuder; Brandon M Roberts; Chandler S Callaway; Patrick W Underwood; Stephen M Chrzanowski; Abhinandan Batra; Meghan E Murphy; Jonathan D Heaven; Glenn A Walter; Jose G Trevino; Andrew R Judge Journal: Cancer Res Date: 2020-03-04 Impact factor: 12.701
Authors: Calvin L Cole; John F Bachman; Jian Ye; Joseph Murphy; Scott A Gerber; Christopher A Beck; Brendan F Boyce; Gowrishankar Muthukrishnan; Joe V Chakkalakal; Edward M Schwarz; David Linehan Journal: J Cachexia Sarcopenia Muscle Date: 2021-05-07 Impact factor: 12.910