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. Author manuscript; available in PMC: 2014 Sep 5.
Published in final edited form as: Curr Opin Support Palliat Care. 2011 Dec;5(4):327–333. doi: 10.1097/SPC.0b013e32834c49ba

Understanding cancer-induced cachexia: imaging the flame and its fuel

Marie-France Penet a, Paul T Winnard Jr a, Michael A Jacobs a,b, Zaver M Bhujwalla a,b
PMCID: PMC4155489  NIHMSID: NIHMS619268  PMID: 21986909

Abstract

Purpose of review

One of the most under explored and yet devastating consequences of cancer is cachexia, a condition in which the body is consumed by deranged carbohydrate, lipid and protein metabolism that is induced by inflammatory cytokines. Cachexia is associated with poor treatment outcome, fatigue and poor quality of life. Because of its multifactorial characteristics, it has been difficult to understand the impact of the tumor on body organs and the sequence of events that leads to cachexia. Such insights are critically important in identifying therapeutic strategies.

Recent findings

The ability to understand the interaction between the tumor and normal tissues and to noninvasively image the development of this condition would be invaluable in identifying critical stages when cachexia becomes life-threatening. Current multimodality molecular and functional imaging capabilities provide unique opportunities to study cachexia holistically in preclinical models and clinically. In this review we have provided examples of how state-of-the-art imaging techniques in combination with molecular characterization can be used to understand cancer-induced cachexia.

Summary

Such studies will lead to clinically translatable indices for the early detection of this condition and will identify novel targets to inhibit the cachexia cascade.

Keywords: cachexia, clinical translation, metabolism, molecular and functional imaging

Introduction

The complexity of cancer dictates the necessity of studying this disease in the context of its microenvironment as well as in the context of interactions between the tumor and the body, that is the ‘macro-environment’. Indeed the past decade has witnessed a major shift in viewing cancer from the perspective of oncogenes and tumor suppressor genes, to understanding the role of the tumor stroma and microenvironment in cancer progression and treatment. Investigating interactions between the tumor and the macroenvironment is, however, largely unchartered territory.

The main causes of mortality from cancer are metastasis-related organ function failure and cachexia [1]. The term cachexia derives from the Greek words ‘kakos’ and ‘hexis’ for ‘bad condition’ [2]. It is a progressive wasting condition that is encountered not only in cancer but also in other life-threatening diseases such as AIDS, rheumatoid arthritis, chronic obstructive pulmonary diseases, and organ failure [3–6]. Several randomized clinical trials have demonstrated that the condition cannot be reversed by nutritional supplementation [7–10]. Mortality from cachexia, and not tumor burden, accounts for 20–30% of cancer deaths [1]. The significant weight loss resulting from this condition causes impairment of immune function, poor outcome of chemotherapy, fatigue, and markedly reduced quality of life [11]. Since 2011 cachexia has been defined as a multifactorial syndrome characterized by an ongoing loss of skeletal muscle mass, with or without loss of fat mass, which cannot be fully reversed by conventional nutritional support and leads to progressive functional impairment. Cachexia pathophysiology is characterized by a negative protein and energy balance driven by a variable combination of reduced food intake and abnormal metabolism [12•]. Currently there is no known cure for cachexia, as mechanisms underlying its manifestation are not defined clearly enough to identify and design effective therapeutic strategies. Several inflammatory cytokines such as tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), IL-1β and interferon-γ (IFN-γ), glucocorticoids, tumor-derived proteolysis-inducing factor (PIF) and lipid-mobilizing factor (LMF) are reportedly functional components in this condition [13]. As outlined in Table 1, significant abnormalities in carbohydrate, lipid and protein metabolism are observed with cachexia, and are a major cause for the associated profound weight loss. In addition, cancer-induced anorexia due to disruption of leptin and neuropeptide Y regulation also contributes to weight loss [13,14].

Table 1.

Abnormalities in carbohydrate, lipid and protein metabolism in cancer cachexia

Carbohydrate metabolism Glucose intolerance PET imaging of 18F labeled deoxyglucose
Increased hepatic gluconeogenesis 13C MRSI of 13C labeled substrates
Increased Cori cycle activity 1H MRSI of lactate
Decreased skeletal muscle glucose uptake 1H MRSI of extracellular pH
Lipid metabolism Hyperlipidemia 1H MRSI of whole body lipid triglyceride and total choline phospholipid signal
Increased lipolysis
Abnormal lipoprotein metabolism
Decreased whole-body lipid stores
Protein metabolism Increased whole-body protein turnover 1H MRI of magnetization transfer to detect proteins
Increased hepatic protein synthesis, acute-phase proteins 31P MRS of energy metabolism (ATP, phosphocreatine) in muscle
Increased skeletal-muscle breakdown 1H MRSI of total creatine in muscle
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MRSI, magnetic resonance spectroscopic imaging. Adapted from [14], and the ability of imaging (column 3) to study these abnormalities.

The ability to noninvasively detect this condition early on with noninvasive imaging, preferably before weight loss occurs, can significantly contribute to the design and optimization of therapeutic strategies, and to the detection of response to such treatments. Multimodality molecular and functional imaging techniques provide a panacea of capabilities to tackle key questions in cancer cachexia (Fig. 1) [15,16]. At the bench, transgenic mice and genetically engineered cancer cells can be used to image specific molecular pathways. When combined with functional imaging significant advances can be made in understanding the interaction between the tumor and the host in the cachexia cascade. As listed in Table 1, abnormalities in carbohydrate, lipid and protein metabolism can be detected and studied with noninvasive MRI and magnetic resonance spectroscopy (MRS) as well as with nuclear imaging methods such as positron emission tomography (PET). Both magnetic resonance and PET are noninvasive and therefore discoveries made at the bench can be clinically translated with relative ease [17•].

Figure 1. Clinical manifestations of cancer cachexia.

Figure 1

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a.a., amino acid; APP, acute phase proteins; CRP, C-reactive protein; dec, decrease; inc, increase; IL-1β, interleukin 1β; IL-6, interleukin 6; LMF, lipid mobilizing factor; NPY, neuropeptide Y; PIF, proteolysis inducing factor; REE, resin energy expenditure; TNF, tumor necrosis factor α. Adapted from Couch et al. [15] and from Glunde et al. [16].

The multifaceted nature of this condition makes it imperative that a ‘holistic’ or macroenvironmental approach is used to understand the cachexic switch or cascade, and the multiple interactive networks that most likely exist between a cachexia-inducing tumor and host organs and tissue, as well as the interaction between inflammatory cytokines and metabolism. Noninvasive imaging applied to study cachexia would enable the delineation of a sequence of progressive events and identify the most lethal aspects of the cascade. Once these critical single or multiple cachexic switches or cascades are identified, molecular-targeted approaches, such as multiple small interfering RNA (siRNA) targeting or pharmaceutical interventions, can be designed and developed to down-regulate or knockout effector molecules, pathways or enzymes that control the cascade. The focus of this review is to describe how state-of-the-art molecular and functional imaging capabilities in combination with novel molecular biology techniques can be used to understand the interactions between the tumor and normal tissues in the body in inducing cachexia.

Characterization of cachexia-inducing tumors and the feasibility of imaging these characteristics

Mechanisms involved in cancer cachexia have been comprehensively reviewed by Tisdale [18]. Cachectic patients are affected by an energy imbalance due to anorexia and increased resting energy expenditure. Changes in adipose tissue in cachexia are primarily due to increased lipolysis resulting in a loss of body fat. There is impairment not only of the lipid storage function of adipocytes but also of their differentiation. The cachectic tumor can affect adipose mass through the secretion of factors such as LMF, or protein zinc α2-glycoprotein (ZAG) that induce lipolysis by a cyclic adenosine monophosphate-mediated mechanism. TNFα can also induce lipolysis in adipocytes. Inflammatory pathways are also activated in cachexia. In addition to TNFα, other cytokines known to be involved are IL-1, IL-6 and IFNγ. Cachexia results in a loss of fat tissue as well as lean muscle tissue. Muscle atrophy in the syndrome results from a decrease in protein synthesis and an increase in protein degradation. Among the several pathways implicated in muscle atrophy, the ubiquitin-proteasome pathway has been shown to have a predominant function in the degradation of myofibrillar proteins. Synthesis of proteins is also affected by changes in the phosphorylation of protein synthesis initiation factors, such as protein kinase R and eIF2α. PIF, glucocorticoids and TNFα are among the factors involved in the loss of muscle mass [18]. These mechanisms have mostly been explored in vitro and ex vivo.

Current state-of-the-art molecular and functional imaging can be applied to noninvasively characterized tumors that induce cachexia. This would enable the development of noninvasive biomarkers to identify tumors likely to induce cachexia, and to identify changes in normal tissues that are typical of the induction of cachexia. This ability to detect the onset or presence of cachexia noninvasively could be extended to detect response to treatment and to the development of new therapies. Clinically translatable 18FDG PET imaging can be used to characterize glycolysis. Both MRI and CT can be used to image the loss of lipids and the changes in muscle mass, and MRS and magnetic resonance spectroscopic imaging (MRSI) can detect alterations in carbohydrate, protein and lipid metabolism. Optical reporters could be used to image inflammatory pathways or proteasome activity involved in the cachexia cascade.

Preclinical studies

There has been interest in identifying ‘metabolic signatures’ that might be indicative of a cachexia-inducing tumor. 1H MRS has been applied to identify cachexia biomarkers in the sera of C26 adenocarcinoma-bearing mice [19]. Increased amounts of very-low-density and low-density lipoproteins were detected along with decreased glucose levels [19]. Constantinou et al. [20••] applied 31P MRS in vivo to detect changes in the muscle energy metabolism of cachectic mice inoculated with Lewis lung carcinoma cells. 31P spectra revealed a reduction in the ATP synthesis rate in tumor-bearing mice compared with the control mice, which was attributed to mitochondrial dysfunction [20••]. The results were supported by genomic analysis that showed atypical expression levels of skeletal muscle regulatory genes such as peroxisomal proliferator activator receptor-γ-coactivator-1β (PGC-1β), which is a major regulator of mitochondrial biogenesis, and the mitochondrial uncoupling protein 3 (UCP3). These results showed that the hallmarks of skeletal muscle wasting could be detected noninvasively by in vivo using 31P MRS, which could be translated to the clinic [20••].

Progressive cancer cachexia was also associated with depletion of energy stores in the liver and skeletal muscle as detected by steady-state assessment of hepatic and skeletal muscle bioenergetic status using 31P MRS [21]. Rats were inoculated with methylcholanthrene-induced sarcoma to assess the effects of cancer on the visceral energy stores in vivo. An increased hepatic inorganic phosphate (Pi)/ATP ratio was detected by 31P MRS and occurred early in the disease process [21]. Using the same model of cachexia, Gehman et al. [22] detected, using 31P MRS, an increase in Pi generation and a more rapid removal of phosphomonoester (PME) in cachectic rat liver.

Magnetic resonance was recently applied to analyze the contribution of lipase to cancer-related cachexia [23]. Inhibition of lipolysis by targeting adipose triglyceride lipase and hormone-sensitive lipase reduced certain features of cachexia, such as myocyte apoptosis, proteasomal muscle degradation and loss of white adipose tissue. Magnetic resonance was used to assess the total body fat content demonstrating that the technique can be used to explore the effect of anticachexia treatment on lipid mass [23].

Clinical studies

Few imaging studies have been performed on patients who suffer from cachexia. Most of these have explored muscle mass. In the clinic, the order of preference for muscle mass assessment was listed as cross-sectional imaging [computed tomography (CT) or MRI], dual energy X-ray imaging (DEXA), anthropometry (mid-arm muscle area), and bioimpedance analysis [12•]. CT imaging provides an accurate assessment of muscle mass and body composition in patients with cancer [24–26]. CT scans acquired on pancreatic cancer patients with and without cachexia revealed that in the lower part of the abdomen, there was no significant difference between these groups in any of the examined muscle tissue thicknesses (Fig. 2) [27]. However, fat tissue thickness was significantly reduced in cachectic patients (Fig. 2). Although no significant difference between the two groups was observed in muscle thicknesses, lung function in cachectic patients was significantly decreased, demonstrating that in the early stages of the cachectic syndrome the muscle is preserved but its function is impaired. CT scans revealed a significant influence of cachexia on fat metabolism, underlining the systemic effects of cachexia in patients with pancreatic cancer [27]. These studies demonstrated the advantages of using CT imaging in the assessment of the effect of cachexia on muscle and fat tissues. CT measurement of body composition was also shown to have potential in predicting prognosis and possibly chemotherapy toxicity [24,25]. CT imaging can also be used in clinical intervention trials to assess treatment efficacy on fat-free mass and specific muscles [28•].

Figure 2. Computed tomography scans of pancreatic cancer patients with and without cachexia.

Figure 2

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(a) Computed tomography (CT) slide of the renal pelvis demonstrating measurements of muscles. (1) Peri-renal fat: orthograft to renal capsule and to line 2. (2) Musculus erector spinae: thickness of the muscle in a parallel line to the dorsal process. (b) CT slide of iliac crest. (3a) Thickness of the musculus psoas in a parallel line to the dorsal process. (3b) Area of the psoas muscle. (4) Subcutaneous fat medial: parallel to the dorsal process. (5) Subcutaneous fat lateral: parallel to the dorsal process starting at the iliac spine posterior superior area of the psoas muscle. Adapted from [27].

Other imaging techniques have been applied to explore the effect of cachexia on normal tissues in cancer patients. To assess the impact of cachexia on skeletal muscle morphology, metabolism, and microcirculation, Weber et al. [29] acquired MRI, MRS and contrast-enhanced ultrasonography (CEUS) in cachectic patients and compared the results with measurements acquired in matched healthy volunteers (Fig. 3). As shown in Fig. 3, it is possible to quantify the muscle cross-sectional area, in this instance of the right quadriceps femoris, in magnetic resonance images. The cross-sectional area in a cachectic patient and a volunteer were 51.3 and 85.9 cm2, respectively. Skeletal muscle microcirculation was quantified by CEUS, a technique that analyzes the replenishment kinetics after destruction of intravenously injected microbubbles by ultrasonographic pulses [29]. This study showed that morphologic parameters, body mass index, cross-sectional area and total fiber size were lower in cachectic patients than in volunteers. Capillary density, determined on histology sections, as well as microcirculation, measured in vivo by CEUS, and concentrations of muscular energy metabolites, pH, and trimethyl-ammonium-containing compounds, analyzed in vivo with MRS were comparable in both groups [29]. In this study, cancer cachexia was associated with a loss of muscle volume but not of muscular functionality.

Figure 3. Comparison of MRI, magnetic resonance spectroscopy and contrast-enhanced ultrasonography of cachectic patients and healthy individuals.

Figure 3

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Magnetic resonance T1-weighted imaging of the right thigh in a 54-year-old man with cachexia due to pancreatic cancer (a) and the corresponding right thigh at the same level of a matched healthy volunteer (b). The corresponding 1H magnetic resonance spectrum (c) from the right vastus lateralis muscle and the 31P magnetic resonance spectrum of the same region (d) of the patient with cachexia illustrate the metabolites that were quantified. Peak assignments in (c): Cr, (phospho-)creatine; TMA peak, trimethyl-ammonium-containing compounds including choline; IMCL, intramyocellular lipids; EMCL, extramyocellular lipids. Peak assignments in D): phosphocreatine (PCr), inorganic phosphate (Pi), phosphodiester (PDE), and the three resonances (α, β, γ) of adenosine 5′-triphosphate (ATP). Only the signals printed in bold in (c) and (d) were quantified. The corresponding transverse power Doppler images after bolus injection of 10 ml Levovist at a depth of 1.5 cm (focus area) show the initial increase (e) and maximum plateau (f) of microbubbles replenishment within the right vastus lateralis muscle of the patient with cachexia. Microcirculation and concentration of lipid and energy metabolites in vivo were comparable in muscles of volunteers and cachectic patients at rest. Adapted from [29].

MRI can be used to not only measure muscle cross-sectional area and volume, but also to distinguish between different tissue types, such as muscle and subcutaneous fat, as shown in Fig. 4. Fatty infiltration within the quadriceps muscle can be observed in these magnetic resonance images. Gray et al. [30•] have developed a noninvasive optimization technique to separately quantify the contractile and the noncontractile compartments within the muscle on magnetic resonance images. The k-means technique allows a noninvasive estimation of the proportion of fatty infiltration in the muscle. Women with upper gastrointestinal cancer who have a predilection for cachexia presented with 48% less muscle with significantly higher fatty infiltration than healthy young women, indicating that the muscles of patients are not only smaller but also less homogeneous [30•].

Figure 4. Magnetic resonance images showing fatty infiltration within the quadriceps muscle group.

Figure 4

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Magnetic resonance cross-sectional images at the mid-thigh level in healthy women aged 23 years (a) and 80 years (b) and a woman with upper gastrointestinal cancer who was 75 years old (c). Adapted from [30•].

Conclusion

Cancer-induced cachexia is an under explored problem that has devastating consequences. There are no known cures for this condition, and its multifaceted nature makes it difficult to investigate. Current state-of-the-art multimodality molecular and functional imaging approaches are ideally suited to identifying and characterizing this problem but to date they have not been extensively pursued. Studying and solving this problem would have a significant impact on improving the quality of life for patients, treatment outcome, and increasing the life expectancy of cancer patients.

Molecular and functional imaging of preclinical models of cachexia can be used to answer critical questions such as the sequence of changes in metabolism and whether these occur simultaneously or subsequent to inflammation. The sequence of changes in carbohydrate, protein and lipid metabolism in organs during the onset of cachexia can also be identified, together with the earliest and most life-threatening processes associated with cachexia. The tumor microenvironment is characterized by inflammation-inducing environments such as hypoxia and an acidic extracellular pH. One critical question that can be identified with molecular and functional imaging is whether these abnormal and inflammation-inducing physiological environments make a significant contribution to the cachexic response. Using preclinical tumor models and noninvasive imaging of hypoxia [31] and extracellular pH [32] we can study the interaction between cachexia-inducing and noncachexia-inducing tumors and the role of the tumor micro-environment in inducing cachexia. A significant alteration in choline metabolism, detected by MRS, and by molecular characterization of enzymes in the choline pathway are hallmarks of highly aggressive tumors, and this is currently being exploited for potential new therapies [33]. Increased total choline is also found to occur with inflammation [34]. The relationship between NF-κB activity, choline metabolism and cachexia is entirely unexplored and should be a key focus of future investigations in order to identify early markers of cancer cachexia and to uncover new targets for its treatment. Once key organs or cancer-specific metabolic pathways and enzymes involved in the cascade are revealed, image-guided delivery of siRNA to target-specific enzymes using liposomes decorated with imaging reporters can be used as target-specific therapeutics against essential enzymes to reverse the condition.

Key points.

  • The ability to noninvasively detect cachexia early on with noninvasive imaging could significantly improve the design of therapeutic strategies and treatment efficacy.

  • The sequence of changes in carbohydrate, protein and lipid metabolism in organs during the onset of cachexia can be identified.

  • Biomarkers of cachexia determined in preclinical studies noninvasively with imaging techniques can be translated to the clinic.

  • Imaging studies of cachectic muscle have been performed in the clinic; however, studies have not as yet been performed on primary tumors inducing cachexia.

Acknowledgments

Support from P50 CA103175, P30 CA006973, R01 CA73850, R01 CA82337, R01 CA136576, R01 CA138515, R01 CA138264, U01CA140204 and R21 CA133600 is gratefully acknowledged.

References and recommended reading

Papers of particular interest, published within the annual period of review, have been highlighted as:

• of special interest

•• of outstanding interest Additional references related to this topic can also be found in the Current World Literature section in this issue (p. 366).

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