Implantation of the Yoshida AH-130 ascites hepatoma to rats resulted in a decrease in muscle weight 7 days after the inoculation of the tumor. These changes were associated with increases in the mRNA content for both peroxisome proliferator-activated receptor (PPAR) γ and PPARδ in skeletal muscle. The increase in gene expression for these transcription factors was related to increases in the expression of several genes involved in fatty acid transport, activation, and oxidation. Tumor burden also resulted in increases in PPARγ coactivator-1α gene expression and pyruvate dehydrogenase kinase 4. All these changes in lipid metabolism genes suggest that a metabolic shift occurs in skeletal muscle of tumor-bearing rats toward a more oxidative phenotype. Formoterol treatment to tumor-bearing rats resulted in an amelioration of all the changes observed as a result of tumor burden. Administration of this β2-adrenergic agonist also resulted in a decrease in mRNA content of muscle PPARα, PPARδ, and PPARγ, as well as in mRNA levels of many of the genes involved in both lipid and mitochondrial metabolism. All these results suggest an involvement of the different PPARs as transcription factors related with muscle wasting and also indicate that a possible mode of action of the anticachectic compound formoterol may involve a normalization of the levels of these transcription factors. [Cancer Res 2007;67(13):6512–9]

Muscle wasting is a common feature in many pathologic states, including infection and cancer (1). Muscle wasting, the main trend of cachexia, is responsible for the death of at least 30% of cancer patients (2). Although we know the main events related with muscle wasting [activation of myofibrillar protein degradation, induction of apoptosis, and activation of uncoupling proteins (UCP); refs. 3, 4], we have contradictory evidence about the possible mediators involved. Indeed, whereas involvement of different cytokines, mainly tumor necrosis factor-α (TNFα) and interleukin-6 (IL-6), has been postulated, other studies describe a more direct role for tumor-derived factors, such as proteolysis-inducing factor (PIF) and lipid-mobilizing factor (5, 6). The intracellular signaling pathway may have a key role, from a therapeutic point of view, especially if there are different mediators involved. Taking this into consideration, a lack of knowledge about signaling pathways and transcription factors involved in muscle wasting exists. Some work has postulated a role for nuclear factor-κB (NF-κB) in muscle wasting associated with cytokines (7) and tumor-derived factors (8). Other transcription factors, such as activator protein-1 (AP-1) and CCAAT/enhancer binding protein (C/EBP), have also been involved in sepsis-induced muscle cachexia (9). Results from our laboratory indicate that the transcription factor AP-1 could also be involved during cancer cachexia (10, 11). Not much attention has been focused on the role of peroxisome proliferator-activated receptors (PPAR) in skeletal muscle. These transcription factors are associated with changes in lipid metabolism as well as UCP expression (12) and apoptosis (13).

PPARs are transcription factors belonging to the superfamily of nuclear receptors. Three isoforms (α, δ, and γ) have been described (14). They act on DNA response elements as heterodimers with the nuclear retinoic acid receptor. Their natural activating ligands are fatty acids and lipid-derived substrates. PPARα is present in liver, heart, and, to a lesser extent, skeletal muscle; when activated, it promotes fatty acid oxidation, ketone body synthesis, and glucose sparing. PPARγ is expressed in adipose tissue, lower intestine, skeletal muscle, and immune cells; activation of PPARγ induces the differentiation of preadipocytes into adipocytes and stimulates triglyceride storage. The PPARs are thus major regulators of lipid and glucose metabolism, allowing adaptation to the prevailing nutritional environment (14). PPARδ has a broad expression pattern in adult and is expressed very early during embryogenesis (15). These past few years, it has been shown that treatment with PPARδ agonists normalizes blood lipids and also reduces insulin resistance and adiposity in rodents and primates. Utilization of both cellular and animal models revealed that this nuclear receptor plays a central role in the control of fatty acid burning in adipose tissue and skeletal muscle. Furthermore, PPARδ seemed to be important for adaptive response of skeletal muscle to environmental changes, such as physical exercise (15).

β2-adrenergic agonists are potent muscle growth promoters in many animal species (16, 17), resulting in skeletal muscle hypertrophy (1820) and reducing body fat content (21, 22). Interestingly, results from our laboratory clearly indicate that formoterol is a very efficient agent preventing muscle weight loss in tumor-bearing rats (23). In vivo treatment can effectively reverse muscle wasting loss decreasing protein degradation and increasing the rate of protein synthesis in skeletal muscle, therefore favoring protein accretion (23).

Bearing this in mind, the aim of the present investigation was to ascertain if tumor burden induces any changes in PPARs gene transcription in skeletal muscle and if these changes are associated with alterations in gene transcription of different types of proteins involved in lipid metabolism. A second objective in the present investigation was to see if these changes could be reversed by administration of the β2-agonist formoterol, a molecule that shows a clear anticachectic action in skeletal muscle during cancer (23).

Animals. Male Wistar rats (Interfauna) of 5 weeks of age were used. The animals were maintained at 22 ± 2°C with a regular light-dark cycle (light on, 08:00–20:00) and had free access to food and water. The food intake was measured daily. All animal manipulations were made in accordance with the European Community guidelines for the use of laboratory animals.

Tumor inoculation and treatment. Rats were divided into two groups, namely controls and tumor hosts. The latter received an i.p. inoculum of 108 AH-130 Yoshida ascites hepatoma cells obtained from tumors growing in the exponential phase (24). Both groups were further divided into treated and untreated, the former being given daily i.p. dose of formoterol (0.3 mg/kg body weight), dissolved in physiologic solution, and the latter a corresponding volume of solvent. On day 7 after tumor transplantation, the animals were weighed and anesthetized with an i.p. injection of ketamine/xylazine mixture (3:1; Imalgene and Rompun, respectively). The tumor was harvested from the peritoneal cavity and its volume and cellularity were evaluated. Tissues were rapidly excised, weighed, and frozen in liquid nitrogen.

Biochemicals. They were all reagent grade and obtained either from Roche S.A. or from Sigma Chemical Co.

RNA isolation. Total RNA from soleus and extensor digitorum longus (EDL) muscle was extracted by TriPure kit (Roche), a commercial modification of the acid guanidinium isothiocyanate/phenol/chloroform method (25).

Real-time PCR. First-strand cDNA was synthesized from total RNA with oligonucleotide dT15 primers and random primers p(dN)6 by using a cDNA synthesis kit (Transcriptor Reverse Transcriptase, Roche). Analysis of mRNA levels for PPARα, PPARδ, PPARγ, muscle carnitine palmitoyltransferase-I (MCPTI), and CPTII were done with primers designed to detect gene products as described previously (26). Oligonucleotide sequences for fatty acid translocase (FAT) were 5′-CTCTGACATTTGCAGGTC-3′ and 5′-CACAGGCTTTCCTTCTTTGC-3′ (gi: 98674378), for fatty acid transport protein (FATP) were 5′-GCATGGATGATCGGCTATTT-3′ and 5′-GATGTTCCCTGCTGAGTGGT-3′ (gi: 18811712), for PPARγ coactivator-1α (PGC1α) were 5′-AAGGTCCCCAGGCAGTAGAT-3′ and 5′-TTCAGACTCCCGCTTCTCAT-3′ (gi: 13786187), for pyruvate dehydrogenase kinase 4 (PDK4) were 5′-CCTTTGCTGGTTTTGGTTA-3′ and 5′-CACCAGTCATCAGCCTCAGA-3′ (gi: 16758425), and for acyl-CoA synthetase 4 (ACS4) were 5′-CACCATTGCCATTTTCTGTG-3′ and 5′-GCCTTCAGTTTGCTTTCCAG-3′ (gi: 16758425). Amplification conditions consisted in 5 s of denaturation at 94°C, 9 s of annealing at 60°C, and 9 s of extension at 72°C for each step for 45 cycles for FAT, PGC1α, PDK4, and ACS4 and for FATP consisted in 5 s of denaturation at 94°C, 9 s of annealing at 60°C, 9 s of extension at 72°C, and 3 s at 87°C to detect amplification product avoiding unspecific products after each cycle, for 45 cycles. Myosin heavy-chain I (MHCI) and MHCIIA primers were designed by Mortensen et al. (27). To avoid the detection of possible contamination by genomic DNA, primers were designed in different exons. The real-time PCR was done using a commercial kit (LightCycler FastStart DNA Master PLUS SYBR Green I, Roche). The relative amount of all mRNA was calculated using comparative CT method. 18S mRNA was used as the invariant control for all studies.

Protein extraction and Western blotting. For PDK4 analysis, EDL and soleus muscles were homogenized in 10 mmol/L HEPES (pH 7.5), containing 10 mmol/L MgCl2, 5 mmol/L KCl, 0.1 mmol/L EDTA, 0.1% Triton X-100, 1 mmol/L DTT, and 5 μL of a protease inhibitor cocktail (Sigma)/mL of buffer. They were then centrifuged at 7,000 rpm for 5 min at 4°C, and the supernatants were collected. For MCPTI, PGC1α, and mitochondrial complex II analysis, an enriched mitochondrial/nuclear fraction was obtained: the pellets being resuspended in 500 μL of buffer [10 mmol/L HEPES (pH 7.9) containing 0.5 mol/L NaCl, 1.5 mmol/L MgCl2, 0.2 mmol/L EDTA, 30% glycerol, 1 mmol/L DTT, 5 μL of a protease inhibitor cocktail/mL of buffer] and left for 30 min on ice. They were later centrifuged at 7,000 rpm for 5 min at 4°C, and the supernatants were collected. About FAT analysis, an enriched plasma membrane was obtained from the total protein extracts; these were obtained by ultracentrifugation at 47,000 rpm for 1 h at 4°C. Protein concentrations were determined according to the method of bicinchoninic acid (Pierce). Equal amounts of protein (50 or 100 μg) were heat denatured in sample loading buffer [50 mmol/L Tris-HCl (pH 6.8), 100 mmol/L DTT, 2% SDS, 0.1% bromphenol blue, 10% glycerol], resolved by SDS-PAGE (10% polyacrylamide, 0.1% SDS), and transferred to Immobilon membranes (Immobilon polyvinylidene difluoride, Millipore). The filters were blocked with 5% PBS-nonfat dry milk and then incubated with polyclonal antibodies: anti-PDK4, anti-PGC1α, anti-MCPTI, anti-FAT (Santa Cruz Biotechnology), and monoclonal antibody (mAb) anti-OxPhos complex II (Molecular Probes). Polyclonal antibodies anti-Na+/K+ ATPase α-subunit (Developmental Studies Hybridoma Bank), anti–glyceraldehyde-3-phosphate dehydrogenase, and mAb anti-porin (Calbiochem) were used as invariant controls for the different studies. Donkey anti-mouse peroxidase-conjugated IgG (Jackson ImmunoResearch, Laboratories, Inc.), rabbit anti-goat peroxidase-conjugated IgG (Acris Antibodies GmbH), and goat anti-rabbit horseradish peroxidase conjugate (Bio-Rad) were used as secondary antibodies. The membrane-bound immune complexes were detected by an enhanced chemiluminescence system (EZ-ECL).

Statistical analysis. Statistical analysis of the data was done by means of one-way ANOVA.

Muscle wasting during different pathologic conditions exerts a negative effect on survival and quality of life in the patient. Therefore, understanding the molecular mechanisms and the different mediators involved provides for the design of efficient therapeutic approaches (28). From this point of view, the therapy against wasting during cachexia has concentrated on either increasing food intake or normalizing the persistent metabolic alterations that take place in the patient. It is difficult to apply a therapeutic approach based on the neutralization of the potential mediators involved in muscle wasting (i.e., TNFα, IL-6, IFN-γ, and PIF) because many of them are involved at the same time in promoting the metabolic alterations and the anorexia present in the cancer patients (29). Bearing this in mind, it is obvious that a good understanding of the molecular mechanisms involved in the signaling of these mediators may be very positive in the design of the therapeutic strategy. This is especially relevant because different mediators may be sharing the same signaling pathways (30, 31). However, very few investigations have focused on the signaling of these mediators in skeletal muscle, especially about transcription factors. Penner et al. (32) described, in a model of sepsis, the involvement of NF-κB and AP-1 in muscle wasting. Other reports, using experimental cancer models, have also suggested that NF-κB is involved in the signaling of muscle wasting (30, 31). In our own laboratory, we have shown recently that there is an increased activation of AP-1 in skeletal muscle of tumor-bearing rats, therefore suggesting that this factor is indeed involved in the muscle events that take place during cancer cachexia (10). Indeed, the i.m. administration of adenoviruses carrying TAM-67 [a negative-dominant of c-jun (AP-1)] resulted in an improvement of the muscle weight during tumor growth (11).

In spite of the involvement of PPARs in several metabolic pathways that are altered during cancer cachexia, no information is available on the mRNA levels of these transcription factors in skeletal muscle during this catabolic situation. This was the aim of the present investigation: to elucidate any changes of PPARs in skeletal muscle during tumor growth and also to relate them to the changes of mRNA content of different genes involved in lipid metabolism.

Table 1 shows the effect of tumor growth on body weight, food intake, and muscle weights in animals bearing the Yoshida AH-130 ascites hepatoma. The growth of this tumor causes in the host a rapid and progressive loss of body weight and tissue waste, particularly in skeletal muscle (33). Acceleration of tissue protein breakdown accounts for most of the waste in the AH-130 bearers (24, 34). The effects of the tumor on weight loss were very significant, with a decrease of 28% in the tumor-bearing group. This effect on body weight was accompanied by a marked anorexia: the tumor-bearing rats ate 20% less than the control ones (Table 1). It can also be seen that the implantation of the tumor resulted in a general decrease of muscle weights (30% gastrocnemius, 29% EDL, 28% tibialis, and 21% soleus) 7 days after the inoculation of the tumor. These changes were associated with increases in the mRNA content for PPARγ (48% in EDL and 208% in soleus) and PPARδ (141% in EDL and 376% in soleus) but no changes in PPARα mRNA content (Table 2A). It is interesting to note here that PPARδ is especially important for adaptable response in skeletal muscle and precisely the largest changes occur at the level of this transcription factor (15). The increase in gene expression for these two transcription factors was related with increases in the expression of genes involved in fatty acid transport activation and oxidation. Thus, FAT and FATP (both proteins associated with fatty acid cellular transport) were increased 215% and 51% in EDL and 86% and 81% in soleus, respectively (Table 2B). In addition, FAT protein content was also increased in soleus (60%) of tumor-bearing animals (Table 3). Similarly ACS4 (the protein that activates the intracellular fatty acids for their subsequent use in oxidation pathways) was increased 38% in soleus (Table 2B). Finally, MCPTI and CPTII mRNA content (both involved in the transport of fatty acid across the mitochondrial membrane) were also increased as a result of tumor burden by 153% and 116% for MCPTI in EDL and soleus, respectively, and 88% and 56% for CPTII in EDL and soleus, respectively. MCPTI protein content was also increased in EDL (156%) and in soleus (219%) muscles of tumor-bearing animals (Table 3). All these results agree with previous reports that have already suggested that lipid metabolism is increased in skeletal muscle of tumor-bearing rats (35). In addition, all these changes in lipid metabolism genes clearly suggest that a metabolic shift occurs in skeletal muscle of tumor-bearing rats toward a more oxidative phenotype. Previous studies have shown that PPARδ is involved in muscle fiber composition; an increase in this transcription factor determines a more oxidative fiber phenotype (36). Bearing this in mind, the results found in this study clearly agree with this previously reported data. In fact, as can be seen in Fig. 1A, tumor burden resulted in a clear increase (49%) in oxidative muscle fibers, as measured by the expression of the MHCI gene (27). Conversely, the presence of the tumor did not have any effects on the mRNA content of MHCIIA, a clear glycolytic marker (Fig. 1A; ref. 27). The same tendency toward a more oxidative phenotype in the muscles of tumor-bearing rats was confirmed when analyzing the mitochondrial complex II protein content as observed in Fig. 1B (37). PGC1α is a transcriptional coregulator that coordinates the formation/maintenance of slow twitch fibers in skeletal myocytes, and this seems to be directly controlled by PPARδ (37). In addition, PPARs seem to independently regulate specific PDK isoforms transcript levels, which are likely to impart important metabolic mediation of fuel utilization by the muscle. Experiments to date suggest that PDK4 is the major isoenzyme responsible for changes in pyruvate dehydrogenase complex activity in response to various different metabolic conditions (38). Tumor burden also resulted in increases in the PGC1α gene expression (83% and 102% in EDL and soleus, respectively) and PDK4 (373% and 172% in EDL and soleus, respectively; Fig. 2). In addition PDK4 and PGC1α protein content was also increased both in EDL (75% and 241%, respectively) and in soleus (70% and 96%, respectively) muscles of tumor-bearing animals (Table 3). These data agree with the work by Puigserver et al. (39) that stated that cytokine-induced activation of PGC1α in culture muscle cells or muscle in vivo causes increased respiration and expression of genes linked to mitochondrial uncoupling and energy expenditure. It is therefore possible to suggest that the cytokine changes related with cancer cachexia are altering the mRNA content of PGC1α and this may affect the transcriptional activity of both PPARγ and PPARδ. In connection with this, it is interesting to remark that the activation of UCP2 and UCP3 is also observed in tumor-bearing rats (40). This could be very well linked with PPARs activation, possibly through PGC1α coactivation.

Table 1.

Food intake, body weight, and muscle weight in tumor-bearing rats

Experimental groups
C, n (mean ± SE)C + F, n (mean ± SE)TB, n (mean ± SE)TB + F, n (mean ± SE)P, ANOVA
IBW-FBW 5 (49 ± 3a5 (50 ± 2a6 (11 ± 5b7 (17 ± 5b<0.001 
Food intake 5 (133 ± 1a5 (131 ± 2a6 (106 ± 1b7 (108 ± 1b<0.001 
Muscle weights      
    GSN 5 (718 ± 10.5a4 (774 ± 8b5 (505 ± 17c7 (611 ± 18d<0.001 
    Soleus 5 (52 ± 2.2a4 (52 ± 1.6a5 (41 ± 2.7b6 (44 ± 1.4b0.001 
    EDL 5 (59 ± 2a5 (60 ± 1.6a5 (42 ± 1.8b6 (51 ± 2c<0.001 
    Tibialis 5 (236 ± 2.5a5 (266 ± 4.5b5 (171 ± 4.8c7 (200 ± 9d<0.001 
Experimental groups
C, n (mean ± SE)C + F, n (mean ± SE)TB, n (mean ± SE)TB + F, n (mean ± SE)P, ANOVA
IBW-FBW 5 (49 ± 3a5 (50 ± 2a6 (11 ± 5b7 (17 ± 5b<0.001 
Food intake 5 (133 ± 1a5 (131 ± 2a6 (106 ± 1b7 (108 ± 1b<0.001 
Muscle weights      
    GSN 5 (718 ± 10.5a4 (774 ± 8b5 (505 ± 17c7 (611 ± 18d<0.001 
    Soleus 5 (52 ± 2.2a4 (52 ± 1.6a5 (41 ± 2.7b6 (44 ± 1.4b0.001 
    EDL 5 (59 ± 2a5 (60 ± 1.6a5 (42 ± 1.8b6 (51 ± 2c<0.001 
    Tibialis 5 (236 ± 2.5a5 (266 ± 4.5b5 (171 ± 4.8c7 (200 ± 9d<0.001 

NOTE: For further details, see Materials and Materials. n is the number of animals. Food intake (grams) refers to the ingestion for each rat during the period of the experiment before sacrifice (7 d). Initial body weight-final body weight without tumor is expressed as grams. Tissue weights are expressed as mg/100 g of initial body weight. Formoterol was given for 7 d s.c. (0.3 mg/kg body weight). Statistical significance of the results by one-way ANOVA and statistically significant difference by post-hoc Duncan test. Different superscripts indicate differences between groups.

Abbreviations: IBW, initial body weight; FBW, final body weight without tumor; GSN, gastrocnemius; C, control; F, formoterol-treated animals; TB, tumor-bearing animals.

Table 2.

Gene expression of different proteins related to lipid metabolism

Experimental groups
C, n (mean ± SE)C + F, n (mean ± SE)TB, n (mean ± SE)TB + F, n (mean ± SE)P, ANOVA
(A) Skeletal muscle mRNA content of the different PPARs      
PPARα      
    EDL 4 (100 ± 13a5 (49 ± 10b5 (102 ± 26a5 (23 ± 18b<0.05 
    Soleus 4 (100 ± 24ab4 (111 ± 12ab5 (137 ± 12a4 (76 ± 22b0.1 
PPARγ      
    EDL 4 (100 ± 8ab5 (45 ± 5ac4 (148 ± 31b5 (30 ± 12c<0.05 
    Soleus 5 (100 ± 28a6 (119 ± 6a6 (308 ± 31b6 (77 ± 19a<0.05 
PPARδ      
    EDL 5 (100 ± 12a5 (93 ± 9a4 (241 ± 20b5 (85 ± 22a<0.001 
    Soleus 4 (100 ± 13a5 (109 ± 12a5 (476 ± 46b6 (140 ± 29ab0.09 
(B) Skeletal muscle mRNA content of the different genes related to lipid metabolism      
Fatty acid transport and activation      
    FAT      
        EDL 4 (100 ± 18a4 (22 ± 11a5 (315 ± 34b5 (26 ± 10a<0.05 
        Soleus 4 (100 ± 6ab5 (57 ± 28a4 (186 ± 12c4 (135 ± 5b<0.001 
    FATP      
        EDL 4 (100 ± 9a4 (51 ± 10b4 (151 ± 17c4 (31 ± 14b<0.001 
        Soleus 4 (100 ± 22a5 (68 ± 15a5 (181 ± 14b4 (105 ± 11a<0.05 
    ACS4      
        EDL 5 (100 ± 18a5 (68 ± 6ab4 (100 ± 14a 5 (58 ± 9b<0.05 
        Soleus 4 (100 ± 5a5 (160 ± 9b4 (138 ± 7bc5 (123 ± 9ac<0.05 
Oxidation      
    MCPTI      
        EDL 4 (100 ± 11a4 (38 ± 5b3 (253 ± 38c5 (35 ± 5b<0.001 
        Soleus 5 (100 ± 7a6 (110 ± 5a4 (216 ± 17b4 (145 ± 10a<0.001 
    CPTII      
        EDL 3 (100 ± 16a4 (40 ± 9b3 (188 ± 19c5 (20 ± 16b<0.001 
        Soleus 4 (100 ± 12a6 (91 ± 6a4 (156 ± 11b4 (112 ± 20a<0.05 
Experimental groups
C, n (mean ± SE)C + F, n (mean ± SE)TB, n (mean ± SE)TB + F, n (mean ± SE)P, ANOVA
(A) Skeletal muscle mRNA content of the different PPARs      
PPARα      
    EDL 4 (100 ± 13a5 (49 ± 10b5 (102 ± 26a5 (23 ± 18b<0.05 
    Soleus 4 (100 ± 24ab4 (111 ± 12ab5 (137 ± 12a4 (76 ± 22b0.1 
PPARγ      
    EDL 4 (100 ± 8ab5 (45 ± 5ac4 (148 ± 31b5 (30 ± 12c<0.05 
    Soleus 5 (100 ± 28a6 (119 ± 6a6 (308 ± 31b6 (77 ± 19a<0.05 
PPARδ      
    EDL 5 (100 ± 12a5 (93 ± 9a4 (241 ± 20b5 (85 ± 22a<0.001 
    Soleus 4 (100 ± 13a5 (109 ± 12a5 (476 ± 46b6 (140 ± 29ab0.09 
(B) Skeletal muscle mRNA content of the different genes related to lipid metabolism      
Fatty acid transport and activation      
    FAT      
        EDL 4 (100 ± 18a4 (22 ± 11a5 (315 ± 34b5 (26 ± 10a<0.05 
        Soleus 4 (100 ± 6ab5 (57 ± 28a4 (186 ± 12c4 (135 ± 5b<0.001 
    FATP      
        EDL 4 (100 ± 9a4 (51 ± 10b4 (151 ± 17c4 (31 ± 14b<0.001 
        Soleus 4 (100 ± 22a5 (68 ± 15a5 (181 ± 14b4 (105 ± 11a<0.05 
    ACS4      
        EDL 5 (100 ± 18a5 (68 ± 6ab4 (100 ± 14a 5 (58 ± 9b<0.05 
        Soleus 4 (100 ± 5a5 (160 ± 9b4 (138 ± 7bc5 (123 ± 9ac<0.05 
Oxidation      
    MCPTI      
        EDL 4 (100 ± 11a4 (38 ± 5b3 (253 ± 38c5 (35 ± 5b<0.001 
        Soleus 5 (100 ± 7a6 (110 ± 5a4 (216 ± 17b4 (145 ± 10a<0.001 
    CPTII      
        EDL 3 (100 ± 16a4 (40 ± 9b3 (188 ± 19c5 (20 ± 16b<0.001 
        Soleus 4 (100 ± 12a6 (91 ± 6a4 (156 ± 11b4 (112 ± 20a<0.05 

NOTE: For further details, see Materials and Methods. n is the number of animals. The results are expressed as a percentage of controls. Statistical significance of the results by one-way ANOVA and statistically significant difference by post-hoc Duncan test. Different superscripts indicate differences between groups.

Abbreviations: C, control; F, formoterol-treated animals; TB, tumor-bearing animals; FAT, fatty acid translocase; PPAR, peroxisome proliferator-activated receptor; FATP, fatty acid transport protein; ACS4, acyl-CoA synthetase 4; MCPTI, muscle carnitine palmitoyltransferase I; CPTII, carnitine palmitoyltransferase II.

Table 3.

Skeletal muscle protein content of different proteins related to lipid metabolism

Experimental groups
C, n (mean ± SE)C + F, n (mean ± SE)TB, n (mean ± SE)TB + F, n (mean ± SE)P, ANOVA
FAT      
    EDL 4 (100 ± 14ab6 (99 ± 17ab3 (198 ± 97a3 (66 ± 12bns 
    Soleus 5 (100 ± 5a7 (108 ± 17ab5 (160 ± 25b3 (99 ± 18a0.09 
MCPTI      
    EDL 5 (100 ± 7ab6 (38 ± 14a5 (256 ± 93b3 (97 ± 12ab<0.05 
    Soleus 4 (100 ± 16a7 (94 ± 22a5 (319 ± 50b4 (185 ± 35a<0.001 
PDK4      
    EDL 4 (100 ± 16a4 (77 ± 6a3 (175 ± 21b4 (99 ± 29a<0.001 
    Soleus 5 (100 ± 20) 6 (109 ± 13) 3 (170 ± 31) 4 (135 ± 55) ns 
PGC1α      
    EDL 5 (100 ± 11a6 (92 ± 13a4 (341 ± 83b4 (131 ± 20a<0.05 
    Soleus 4 (100 ± 9a7 (64 ± 9a4 (196 ± 26b3 (95 ± 21a<0.001 
Experimental groups
C, n (mean ± SE)C + F, n (mean ± SE)TB, n (mean ± SE)TB + F, n (mean ± SE)P, ANOVA
FAT      
    EDL 4 (100 ± 14ab6 (99 ± 17ab3 (198 ± 97a3 (66 ± 12bns 
    Soleus 5 (100 ± 5a7 (108 ± 17ab5 (160 ± 25b3 (99 ± 18a0.09 
MCPTI      
    EDL 5 (100 ± 7ab6 (38 ± 14a5 (256 ± 93b3 (97 ± 12ab<0.05 
    Soleus 4 (100 ± 16a7 (94 ± 22a5 (319 ± 50b4 (185 ± 35a<0.001 
PDK4      
    EDL 4 (100 ± 16a4 (77 ± 6a3 (175 ± 21b4 (99 ± 29a<0.001 
    Soleus 5 (100 ± 20) 6 (109 ± 13) 3 (170 ± 31) 4 (135 ± 55) ns 
PGC1α      
    EDL 5 (100 ± 11a6 (92 ± 13a4 (341 ± 83b4 (131 ± 20a<0.05 
    Soleus 4 (100 ± 9a7 (64 ± 9a4 (196 ± 26b3 (95 ± 21a<0.001 

NOTE: For further details, see Materials and Methods. n is the number of animals. The results are expressed as a percentage of controls. Statistical significance of the results by one-way ANOVA and statistically significant difference by post-hoc Duncan test. Different superscripts indicate differences between groups.

Abbreviations: C, control; F, formoterol-treated animals; TB, tumor-bearing animals; FAT, fatty acid translocase; MCPTI, muscle carnitine palmitoyltransferase I; PDK4, pyruvate dehydrogenase kinase-4; PGC1α, PPAR coactivator-1α; ns, nonsignificant differences.

Figure 1.

A, skeletal muscle protein content of mitochondrial complex II. Porin was used as invariant control. B, soleus mRNA content of the different MHCs. 18S was used as invariant control. For further details, see Materials and Methods. Columns, mean of four animals in each group; bars, SE. The results are expressed as a percentage of controls. C, control; F, formoterol-treated animals; TB, tumor-bearing animals. Statistical significance of the results by one-way ANOVA and statistically significant difference by post-hoc Duncan test. a, b, and c, differences between groups.

Figure 1.

A, skeletal muscle protein content of mitochondrial complex II. Porin was used as invariant control. B, soleus mRNA content of the different MHCs. 18S was used as invariant control. For further details, see Materials and Methods. Columns, mean of four animals in each group; bars, SE. The results are expressed as a percentage of controls. C, control; F, formoterol-treated animals; TB, tumor-bearing animals. Statistical significance of the results by one-way ANOVA and statistically significant difference by post-hoc Duncan test. a, b, and c, differences between groups.

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Figure 2.

A, mRNA content of PDK4 and PGC1α in EDL muscle of tumor-bearing animals. 18S was used as invariant control. B, mRNA content of PDK4 and PGC1α in soleus muscle of tumor-bearing animals. 18S was used as invariant control. For further details, see Materials and Methods. Columns, mean values of four animals in each group; bars, SE. The results are expressed as a percentage of controls. Statistical significance of the results by one-way ANOVA and statistically significant difference by post-hoc Duncan test. a and b, differences between groups.

Figure 2.

A, mRNA content of PDK4 and PGC1α in EDL muscle of tumor-bearing animals. 18S was used as invariant control. B, mRNA content of PDK4 and PGC1α in soleus muscle of tumor-bearing animals. 18S was used as invariant control. For further details, see Materials and Methods. Columns, mean values of four animals in each group; bars, SE. The results are expressed as a percentage of controls. Statistical significance of the results by one-way ANOVA and statistically significant difference by post-hoc Duncan test. a and b, differences between groups.

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Formoterol, a β2-adrenergic agonist, is a very efficient agent preventing muscle weight loss in tumor-bearing rats (23). Bearing this in mind, we decided to see if the effects of formoterol on muscle wasting during experimental tumor growth were connected with changes in PPARs and the genes involved in lipid metabolism studied above. The results obtained seem to indicate that formoterol treatment can normalize the changes induced by the tumor (Fig. 2; Tables 13). Several studies have shown that β2-adrenergic agonists act on skeletal muscle by changing the fiber composition toward a more glycolytic pattern (41). Taking this into account, the different effects of formoterol on different types of muscles were studied; therefore, these studies were done in a predominantly oxidative muscle (soleus) and in a predominantly glycolytic muscle (EDL). The results found here are in line with previously described observations (41). As seen in Fig. 1A, formoterol treatment resulted in a significant increase in MHCIIA (a glycolytic marker) in mRNA soleus content, in both control and tumor-bearing animals. In addition, formoterol also significantly decreased mitochondrial complex II content in tumor-bearing rats (Fig. 1B), this observation supporting further the change in fiber composition.

It is interesting to note that formoterol also had an effect on nontumor-bearing animals (Table 3A and B), therefore suggesting that the action [possibly linked with variations of the intracellular concentration of cyclic AMP (cAMP) in cells] may be linked with changes in PPARs (42, 43). In fact, a previous report using the β2-agonist phenylephrine already suggests this possibility (44). On the other hand, it is well known that β2-agonists also affect lipid metabolism on adipose tissue, decreasing lipid synthesis and favoring lipid oxidation (45), but this is the first report that clearly shows a possible action of β2-agonists on skeletal muscle lipid metabolism. The effects of the β2-agonists via β2-adrenergic receptors increase cAMP and interfere with PPARs gene expression (Fig. 3). However, another possibility is that formoterol actually interferes with the signaling of TNFα on skeletal muscle cells. Indeed, a report already suggests that the β2-agonist clenbuterol decreases the circulating levels and activity of TNFα (46). This makes particular sense for the tumor model involved in this study because the Yoshida AH-130 ascites hepatoma seems to be highly dependent on the increase of TNFα circulating levels (47). In addition, in this study, formoterol treatment also reduced the TNFα mRNA content in gastrocnemius muscle [tumor, 185 ± 15a arbitrary units (4); tumor treated with formoterol, 115 ± 9b arbitrary units (3); P < 0.05]. (Statistical significance of the results by one-way ANOVA and statistically significant difference by post-hoc Duncan test; different superscripts indicate differences between groups).

Figure 3.

Hypothetical involvement of the different transcription factors during muscle wasting in cancer cachexia. ARβ2, β2-adrenoceptor; IL-6R, IL-6 receptor; PIFR, PIF receptor; TNFR1, TNF receptor 1; TNFR2, TNF receptor 2.

Figure 3.

Hypothetical involvement of the different transcription factors during muscle wasting in cancer cachexia. ARβ2, β2-adrenoceptor; IL-6R, IL-6 receptor; PIFR, PIF receptor; TNFR1, TNF receptor 1; TNFR2, TNF receptor 2.

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The data presented here, in a way, complicate the understanding of the different transcription factors in muscle wasting because some reports have suggested that activation of different PPARs may be useful in preventing metabolic alterations linked with inflammation by cytokines (48). However, other reports suggest the opposite, emphasizing that PPARs may have a role in mediating cytokine action in skeletal muscle (39). In addition, several studies (49) indicate that PPARs can partially interfere in NF-κB signaling in skeletal muscle, therefore controlling to some extent the action exerted by cytokines through these transcription factors (Fig. 3). Bearing all this in mind, one has to look at the plethora of transcription factors involved in muscle wasting during cancer cachexia because possibly some of them play a more important role in some cases, depending on the species, the tumor model, and the tumor stage. It is perfectly conceivable to understand that by agonizing PPARγ and PPARδ, one can produce a reduction in muscle weight partly through the interference in the NF-κB signaling system. It can also be suggested that the elevation of the different PPARs during muscle wasting in cancer may be a counter metabolism triggered by the host to control an excessive degradation of muscle protein and favoring lipid utilization for muscle.

In conclusion, the results presented here contribute to a better understanding of the role of transcription factors in the muscle tissue during cancer cachexia. It becomes clear that future research into this field is necessary and may provide important tools to design effective drugs for the treatment of wasting in skeletal muscle during pathologic conditions.

Grant support: Ministerio de Educación y Ciencia Dirección General de Investigación Científica y Técnica BFI2002-02186 (G. Fuster); Ministerio de Sanidad y Consumo Instituto de Salud Carlos III grant 03/0100 (E. Ametller); La Marató TV3 grant 04/1010 (M. Olivan); Programme Alβan, the European Union Programme of High Level Scholarships for Latin America, scholarship E05D059293BR (C.C. Fontes de Oliveira); Fondo de Investigaciones Sanitarias de la Seguridad Social of the Ministerio de Sanidad y Consumo grant 06/0907; and Ministerio de Ciencia y Tecnología grant SAF 4744-2005.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

We thank Industriale Chimica s.r.l. for providing micronized formoterol fumarate; Dr. Carles Barceló-Vidal for his statistical support.

1
Argilés JM, Alvarez B, López-Soriano FJ. The metabolic basis of cancer cachexia.
Med Res Rev
1997
;
17
:
477
–98.
2
Warren S. The immediate causes of death in cancer.
Am J Med Sci
1932
;
184
:
610
–5.
3
Argilés JM, Moore-Carrasco R, Fuster G, Busquets S, López-Soriano FJ. Cancer cachexia: the molecular mechanisms.
Int J Biochem Cell Biol
2003
;
35
:
405
–9.
4
Argilés JM, Busquets S, López-Soriano FJ. The role of uncoupling proteins in pathophysiological states.
Biochem Biophys Res Commun
2002
;
293
:
1145
–52.
5
Lorite MJ, Smith HJ, Arnold JA, Morris A, Thompson MG, Tisdale MJ. Activation of ATP-ubiquitin-dependent proteolysis in skeletal muscle in vivo and murine myoblasts in vitro by a proteolysis-inducing factor (PIF).
Br J Cancer
2001
;
85
:
297
–302.
6
Todorov PT, McDevitt TM, Meyer DJ, Ueyama H, Ohkubo I, Tisdale MJ. Purification and characterization of a tumor lipid-mobilizing factor.
Cancer Res
1998
;
58
:
2353
–8.
7
Guttridge DC, Mayo MW, Madrid LV, Wang CY, Baldwin AS, Jr. NF-κB-induced loss of MyoD messenger RNA: possible role in muscle decay and cachexia.
Science
2000
;
289
:
2363
–6.
8
Wyke SM, Russell ST, Tisdale MJ. Induction of proteasome expression in skeletal muscle is attenuated by inhibitors of NF-κB activation.
Br J Cancer
2004
;
91
:
1742
–50.
9
Penner G, Gang G, Sun X, Wray C, Hasselgren PO. C/EBP DNA-binding activity is upregulated by a glucocorticoid-dependent mechanism in septic muscle.
Am J Physiol Regul Integr Comp Physiol
2002
;
282
:
R439
–44.
10
Costelli P, Muscaritoli M, Bossola M, et al. Skeletal muscle wasting in tumor-bearing rats is associated with MyoD down-regulation.
Int J Oncol
2005
;
26
:
1663
–8.
11
Moore-Carrasco R, García-Martínez C, Busquets S, et al. The AP-1/cjun signaling cascade is involved in muscle differentiation: implications in muscle wasting during cancer cachexia.
FEBS Lett
2006
;
580
:
691
–6.
12
Dressel U, Allen TL, Pippal JB, Rohde PR, Lau P, Muscat GE. The peroxisome proliferator-activated receptor β/δ agonist, GW501516, regulates the expression of genes involved in lipid catabolism and energy uncoupling in skeletal muscle cells.
Mol Endocrinol
2003
;
17
:
2477
–93.
13
Chinetti G, Griglio S, Antonucci M, et al. Activation of proliferator-activated receptors α and γ induces apoptosis of human monocyte-derived macrophages.
J Biol Chem
1998
;
273
:
25573
–80.
14
Ferre P. The biology of peroxisome proliferator-activated receptors: relationship with lipid metabolism and insulin sensitivity.
Diabetes
2004
;
53
:
S43
–50.
15
Grimaldi PA. Regulatory role of peroxisome proliferator-activated receptor δ (PPARδ) in muscle metabolism. A new target for metabolic syndrome treatment?
Biochimie
2005
;
87
:
5
–8.
16
Stock MJ, Rothwell NJ. Effects of β-adrenergic agonists on metabolism and body composition. In: Buttery PJ, Hayes NB, Lindsay DB, editors. Control and manipulation of animal growth. London: Butterworths; 1985. p. 249–57.
17
Kim YS, Sainz RD. β-Adrenergic agonists and hypertrophy of skeletal muscles.
Life Sci
1992
;
50
:
397
–407.
18
Agbenyega ET, Wareham AC. Effect of clenbuterol on skeletal muscle atrophy in mice induced by the glucocorticoid dexamethasone.
Comp Biochem Physiol Comp Physiol
1992
;
102
:
141
–5.
19
Hinkle RT, Hodge KM, Cody DB, Sheldon RJ, Kobilka BK, Isfort RJ. Skeletal muscle hypertrophy and anti-atrophy effects of clenbuterol are mediated by the β2-adrenergic receptor.
Muscle Nerve
2002
;
25
:
729
–34.
20
Wineski LE, von Deutsch DA, Abukhalaf IK, Pitts SA, Potter DE, Paulsen DF. Muscle-specific effects of hindlimb suspension and clenbuterol in mature male rats.
Cells Tissues Organs
2002
;
171
:
188
–98.
21
Yang YT, McElligot MA. Multiple actions of β-adrenergic agonists on skeletal muscle and adipose tissue.
Biochem J
1989
;
261
:
1
–10.
22
Mersmann HJ. Overview of the effects of β-adrenergic receptor agonists on animal growth including mechanisms of action.
J Anim Sci
1998
;
76
:
160
–72.
23
Busquets S, Figueras MT, Fuster G, et al. Anticachectic effects of formoterol: a drug for potential treatment of muscle wasting.
Cancer Res
2004
;
64
:
6725
–31.
24
Tessitore L, Costelli P, Bonetti G, Baccino FM. Cancer cachexia, malnutrition, and tissue protein turnover in experimental animals.
Arch Biochem Biophys
1993
;
306
:
52
–8.
25
Chomczynski P, Sacchi N. Single-step method of RNA isolation by acid guanidinium thiocyanate phenol chloroform extraction.
Anal Biochem
1987
;
162
:
156
–9.
26
Almendro V, Busquets S, Ametller E, et al. Effects of interleukin-15 on lipid oxidation. Disposal of an oral [14C]-triolein load.
Biochim Biophys Acta
2006
;
1761
:
37
–42.
27
Mortensen OH, Frandsen L, Schjerling P, Nishimura E, Grunnet N. PGC-1α and PGC-1β have both similar and distinct effects on myofiber switching toward an oxidative phenotype.
Am J Physiol Endocrinol Metab
2006
;
291
:
E807
–16.
28
Argilés JM, Almendro V, Busquets S, López-Soriano FJ. The pharmacological treatment of cachexia.
Curr Drug Targets
2004
;
5
:
265
–77.
29
Argilés JM, Busquets S, García-Martínez C, López-Soriano FJ. Mediators involved in the cancer anorexia-cachexia syndrome: past, present, and future.
Nutrition
2005
;
21
:
977
–85.
30
Whitehouse AS, Tisdale MJ. Increased expression of the ubiquitin-proteasome pathway in murine myotubes by proteolysis-inducing factor (PIF) is associated with activation of the transcription factor NF-κB.
Br J Cancer
2003
;
89
:
1116
–22.
31
Wyke SM, Tisdale MJ. NF-κB mediates proteolysis-inducing factor induced protein degradation and expression of the ubiquitin-proteasome system in skeletal muscle.
Br J Cancer
2005
;
92
:
711
–21.
32
Penner CG, Gang G, Wray C, Fischer JE, Hasselgren PO. The transcription factors NF-κb and AP-1 are differentially regulated in skeletal muscle during sepsis.
Biochem Biophys Res Commun
2001
;
281
:
1331
–6.
33
Llovera M, García-Martínez C, Agell N, López-Soriano FJ, Argilés JM. Muscle wasting associated with cancer cachexia is linked to an important activation of the ATP-dependent ubiquitin-mediated proteolysis.
Int J Cancer
1995
;
61
:
138
–41.
34
Tessitore L, Bonelli G, Baccino FM. Early development of protein metabolic perturbations in the liver and skeletal muscle of tumour-bearing rats.
Biochem J
1987
;
241
:
153
–9.
35
Seelaender MC, Nascimento CM, Curi R, Williams JF. Studies on the lipid metabolism of Walker 256 tumour-bearing rats during the development of cancer cachexia.
Biochem Mol Biol Int
1996
;
39
:
1037
–47.
36
Luquet S, Lopez-Soriano J, Holst D, et al. Roles of peroxisome proliferator-activated receptor δ (PPARδ) in the control of fatty acid catabolism. A new target for the treatment of metabolic syndrome.
Biochimie
2004
;
86
:
833
–7.
37
Schuler M, Ali F, Chambon C, et al. PGC1α expression is controlled in skeletal muscles by PPARβ, whose ablation results in fiber-type switching, obesity, and type 2 diabetes.
Cell Metab
2006
;
4
:
407
–14.
38
Abbot EL, McCormack JG, Reynet C, Hassall DG, Buchan KW, Yeaman SJ. Diverging regulation of pyruvate dehydrogenase kinase isoform gene expression in cultured human muscle cells.
FEBS J
2005
;
272
:
3004
–14.
39
Puigserver P, Rhee J, Lin J, et al. Cytokine stimulation of energy expenditure through p38 MAP kinase activation of PPARγ coactivator-1.
Mol Cell
2001
;
8
:
971
–82.
40
Sanchís D, Busquets S, Alvarez B, Ricquier D, López-Soriano FJ, Argilés JM. Skeletal muscle UCP2 and UCP3 gene expression in a rat cancer cachexia model.
FEBS Lett
1998
;
436
:
415
–8.
41
Stevens L, Firinga C, Gohlsch B, Bastide B, Mounier Y, Pette D. Effects of unweighting and clenbuterol on myosin light and heavy chains in fast and slow muscles of rat.
Am J Physiol Cell Physiol
2000
;
279
:
C1558
–63.
42
Herzig S, Hedrick S, Morantte I, Koo SH, Galimi F, Montminy M. CREB controls hepatic lipid metabolism through nuclear hormone receptor PPAR-γ.
Nature
2003
;
426
:
190
–3.
43
Farmer SR. Regulation of PPARγ activity during adipogenesis.
Int J Obes
2005
;
1
:
S13
–6.
44
Planavila A, Rodríguez-Calvo R, Jové M, et al. Peroxisome proliferator-activated receptor β/δ activation inhibits hypertrophy in neonatal rat cardiomyocytes.
Cardiovasc Res
2005
;
65
:
832
–41.
45
Orcutt AL, Cline TR, Mills SE. Influence of the β2-adrenergic agonist clenbuterol on insulin-stimulated lipogenesis in mouse adipocytes.
Domest Anim Endocrinol
1989
;
6
:
59
–69.
46
Izeboud CA, Monshouwer M, van Miert AS, Witkamp RF. The β-adrenoceptor agonist clenbuterol is a potent inhibitor of the LPS-induced production of TNF-α and IL-6 in vitro and in vivo.
Inflamm Res
1999
;
48
:
497
–502.
47
Costelli P, Carbó N, Tessitore L, et al. Tumor necrosis factor-α mediates changes in tissue protein turnover in a rat cancer cachexia model.
J Clin Invest
1993
;
92
:
2783
–9.
48
Moller DE, Berger JP. Role of PPARs in the regulation of obesity-related insulin sensitivity and inflammation.
Int J Obes Relat Metab Disord
2003
;
3
:
S17
–21.
49
Jove M, Laguna JC, Vazquez-Carrera M. Agonist-induced activation releases peroxisome proliferator-activated receptor β/δ from its inhibition by palmitate-induced nuclear factor-κB in skeletal muscle cells.
Biochim Biophys Acta
2005
;
1734
:
52
–61.