systems biology and cancer cachexia

Accepted Manuscript Title: Omics/systems biology and cancer cachexia Author: Iain Gallagher Carsten Jacobi Nicolas Tardif Olav Rooyackers Kenneth Fearon PII: DOI: Reference:

S1084-9521(15)30036-7 http://dx.doi.org/doi:10.1016/j.semcdb.2015.12.022 YSCDB 1911

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Please cite this article as: Gallagher Iain, Jacobi Carsten, Tardif Nicolas, Rooyackers Olav, Fearon Kenneth.Omics/systems biology and cancer cachexia.Seminars in Cell and Developmental Biology http://dx.doi.org/10.1016/j.semcdb.2015.12.022 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Omics/systems biology and cancer cachexia Iain Gallagher PhDa, Carsten Jacobi PhDb, Nicolas Tardif PhDc, Olav Rooyackers PhDc and Kenneth Fearon MDd a

Health and Exercise Research Group, University of Stirling, Stirling FK9 4LA, UK.

b

Novartis Institutes for Biomedical Research, Forum 1, Novartis Campus, 4056 Basel,

Switzerland. c

Department of Anaesthesiology and Intensive Care, Karolinska Institutet Huddinge,

Stockholm, Sweden. d

Department of Clinical and Surgical Sciences (Surgery), School of Clinical Sciences,

University of Edinburgh, Royal Infirmary, 51 Little France Crescent, Edinburgh, EH16 4SA, UK.

Abstract Cancer cachexia is a complex syndrome generated by interaction between the host and tumour cells with a background of treatment effects and toxicity. The complexity of the physiological pathways likely involved in cancer cachexia necessitates a holistic view of the relevant biology. Emergent properties are characteristic of complex systems with the result that the end result is more than the sum of its parts. Recognition of the importance of emergent properties in biology led to the concept of systems biology wherein a holistic approach is taken to the biology at hand. Systems biology approaches will therefore play an important role in work to uncover key mechanisms with therapeutic potential in cancer cachexia. The 'omics' technologies provide a global view of biological systems. Genomics, transcriptomics, proteomics, lipidomics and metabolomics approaches all have application in the study of cancer cachexia to generate systems level models of the behaviour of this syndrome. The current work reviews recent applications of these technologies to muscle atrophy in general and cancer cachexia in particular with a view to progress towards integration of these approaches to better understand the pathology and potential treatment pathways in cancer cachexia.

Key words: cancer cachexia, systems biology, muscle wasting

Introduction Cancer cachexia is a complex syndrome: at its core is the interaction between the host and cancer cells. The interactive nature of cachexia is reflected in the recent expert definition of cancer cachexia as “a multifactorial syndrome defined by an ongoing loss of skeletal muscle mass (with or without loss of fat mass) that cannot be fully reversed by conventional nutritional support and leads to progressive functional impairment” [1]. The host:cancer interaction takes place against a background of treatment with attendant efficacy and/or toxicity. As a result of this interaction, a variety of cellular and soluble mediators are activated, which together with the neuro-endocrine system act on systemic metabolism and food intake with consequent changes in the mass and function of a variety of organs and tissues. In turn, these changes result in the symptoms and signs experienced by the patient that ultimately leads to reduced quality and quantity of life [2]. The complexity of cancer cachexia in humans is increased by the relatively slow pace of evolution of cancer and its complications (developing over months or years) and that implicit in this timescale is the possibility for adaptation. Such adaptation can be present in one component of a tissue, but not in another so that the cellular events of atrophy and regeneration may be present simultaneously. Equally, cancer is generally a disease of old age and patients can have multiple co-morbidities all influencing tissue metabolism, but not necessarily linked to cancer-associated tissue loss. Clearly the best way to cure cachexia is to cure the cancer, as this would resolve all domains of this multi-layered process. Unfortunately, for most advanced solid epithelial malignancies this is not a realistic goal. The next priority would be to inhibit key mediators. However, the heterogeneity of these mediators and the redundancy within activated cascades has meant that treatments that target single mediators have not proved clinically successful (e.g. anti-TNF antibody therapy:[3]). The third sphere of intervention is to target mechanisms rather than mediators. The complexity of the biological pathways possibly involved in cancer cachexia necessitates a holistic view of the relevant biology. It is the attempt to understand key mechanisms that could be turned into therapeutic targets that makes systems biology important to cancer cachexia. Given the inherent heterogeneity in patient samples, any attempt to use systems biology requires a rigorous approach to cohort design/phenotype classification [1].

Whilst it would be interesting to discuss the whole spectrum of tissues involved in the cachexia process, for the purposes of this review, the primary focus will be on skeletal muscle atrophy.

Overview of Systems Biology technologies In the last decade the traditional approach to understanding the development of disease used a focused approach: one “omics”-technology at a time. After the deciphering of the human genome, it was evident that the development and manifestation of disease cannot be explained by the nature of the genome alone. By focusing on one “omics” technology at a time, only one piece of the whole puzzle becomes visible. The basic idea of systems biology is to use a holistic approach to deciphering the complexity of biological systems. With newer technologies like RNA deep-sequencing, single nucleotide polymorphisms (SNP) analysis, metabolomics or SWATH (sequential window acquisition of all theoretical spectra) analysis, a much more detailed picture can be generated. Deeper understanding of health or disease cannot be achieved if the different technologies are used separately, but rather when approaches are combined and carefully related to the clinical phenotype. As stated above, progress towards understanding disease is difficult because human physiology is a complex system governed by genetics, interactions with the environment and stochastic behaviour. Emergent properties are characteristic of complex systems with the result that the end product is more than the sum of its parts. The recognition of the importance of emergent properties in understanding biology led to the concept of systems biology wherein a holistic approach is taken to the biology at hand [4]. This holistic approach generally combines global measurement of biological entities with a computational approach to modelling their interaction or impact on the system. Thus, systems biology combines traditional wet lab perturbation of a system or profiling cases and controls together with computational modelling of the systems behaviour. There are several platforms currently available for systems level analysis of biological samples. These are generally referred to as 'omics' technologies – genomics (gene level), epigenomics (the epigenome), transcriptomics (the transcriptome), proteomics (the proteome),

metabolomics (outcome of biological reactions) more recently lipidomics (lipid species) [5].

Genomic & Transcriptomic technologies The first 'omics' technology was DNA sequencing, independently developed by Maxam and Gilbert, and Sanger and co-workers [6,7]. Over the years this method was refined to the point where it was able to produce the first draft of the entire human genome [8]. The last decade has seen Sanger sequencing largely superseded by 'next-generation' sequencing technologies. These techniques are capable of rapidly generating large amounts of sequence information from both DNA and RNA [9,10]. The use of next generation sequencing is now routine in genomics and has reduced the cost of whole genome sequencing. These novel DNA sequencing techniques have been widely used in the examination of the contribution of gene variants to physiology and disease [11,12] including human cancer cachexia [13] and sarcopenia [14,15]. RNA also lends itself to sequencing and this has given rise to a technique known as RNA-seq. In short individual RNA molecules are amplified and the sequence of these molecules read. Gene expression is then assumed to be proportional to the number of reads mapping back to a gene scaled for gene length. Whilst RNA-seq has seen increasing use over the last 5 years the technology requires proper experimental design [16,17] and is not without bias in human disease contexts [18]. There are as yet no RNA-seq studies of human skeletal muscle in any context. Previously, many studies examining relative global levels of RNA species have used cDNA microarray technology. Microarrays are made up of predefined sequence-specific probes on a solid substrate. RNA is isolated, converted to cDNA and fragmented. The probes on the microarray capture RNA derived cDNA fragments. A fluorescent signal is then generated reflecting the amount of RNA originally present in the sample and hence gene expression. Debate continues in the literature regarding the relative merits of RNA-seq versus microarrays for transcriptomics [19–21]. Nonetheless microarray data is more accessible and cheaper to produce, and the maturity of the technology means that many of the biases and caveats are well understood while this is not necessarily true of RNA-seq [22]. RNA-seq and microarrays are

now understood to be complementary technologies [21,23].

Proteomic technologies The approach to examining protein levels in biological contexts has relied to a great extent on antibody technology and particularly western blotting. Recently awareness of the limitations of antibody technology in proteomics has increased [24,25]. In particular in western blotting titration of total protein loading is rarely carried out but failure to do so may bias results. For example, differences in the gastrocnemius MYH2 content between wild type (control) and Brucella abortis mouse model (2 weeks), in which there is an inflammation driven muscle wasting, are only seen when the total amount of protein is reduced (figure 1). Thus the snapshot gained from a single protein approach can be misleading and there is a requirement for a view of the proteome that is both global and sensitive. MacGillivray and Rickwood [26] were the first to take a more global view of the proteome. Their method, 2D-electrophoresis, combined two completely orthogonal methods: isoelectric focusing separating proteins exclusively according to the isoelectric points (pI) and SDS electrophoresis separating only according to the size of the polypeptides. Thus 2D-electrophoresis allowed visualisation of around of 200 protein spots (representing individual proteins or modifications thereof), which may change between different conditions. In a second step, the selected protein spot could be identified using traditional protein-sequencing techniques [27]. Whilst 2D electrophoresis is still in widespread use, more modern proteomics aims to profile many (possibly thousands) of proteins simultaneously. One of the main tools to study parallel changes of the proteome, the composition of protein complexes and/or post-translational modifications due to different environmental stimuli, is high mass accuracy mass spectrometry [28,29]. The most common mass spectrometry technique is termed 'shotgun' proteomics. The first step in this process is the enzymatic degradation of either whole or fractional protein lysate. The resultant peptides are then separated by for example high-pressure liquid chromatography (LC), ionised and enter a mass spectrometer. The mass spectrometer then performs a survey scan recording the mass spectrum for all the peptides present. Individual peptides are then isolated, fragmented further and then these fragments have

their masses recorded. The spectra resulting from this step can inform the amino acid sequence of the fragments and bioinformatic analysis of spectral libraries can identify parent proteins. The operation of the mass spectrometer in this way is termed data-dependent acquisition (DDA) mode [28]. Due to technical limitations low abundance peptides escape detection in DDA and the stochastic nature of peptide selection for recording leads to low reproducibility. Such low reproducibility led, in part, to the development of single reaction monitoring (SRM) techniques. These rely on a-priori definition of particular peptide fragments to monitor leading to higher reproducibility and sensitivity, but lower throughput. Recently, data independent analysis (DIA) mass spectrometry techniques have emerged with the goal of improving upon DDA [30]. DIA methods isolate all peptide ions within a relatively wide mass window and then scan non-overlapping windows within that interval to identify peptides. The SWATH-MS method uses isolation windows of 25m/z spanning 400–1200 m/z to analyse all peptide ions within this range. In essence SWATH-MS combines the advantages of shotgun techniques (high throughput) with those of SRM techniques (high reproducibility). The challenge of applying a proteomic approach to skeletal muscle is due to the fact that the muscle proteome is dominated by a number of highly abundant contractile proteins accounting for over 50% of the tissue mass reducing the number of detectable proteins [31–33]. A similar problem arises in RNA-sequencing [34]. Analysis can be carried out on samples depleted of abundant proteins but this loses potentially valuable information. One major drawback with the use of 'omics' technologies is the loss of cellular distribution or location information e.g. constitution/ fiber type distribution in skeletal muscle samples. This is an important consideration in investigations of skeletal muscle because biopsies from animals or humans will contain a range of cell types [31]. In Figure 2, tibialis muscle of young (6 month old) and old (23 month old) rats analyzed using immunohistochemistry combined with RNAscope analysis is shown. In the tibialis muscle of young rats a more or less even distribution of fibers with the same diameter was observed. In contrast, the cross sectional analysis of the tibialis of old rats showed areas of atrophic fibers and hypertrophic fibers in the same section. Loss of contextual information like this contributes to the challenges in the

interpretation of subsequent generated data-sets. Ideally a systems level approach to cancer cachexia would combine different ‘omics’-technologies, focused wet-lab techniques and immuno-histological analysis of the tissue to identify the cell type and location of molecules of interest.

Small sample sizes One of the main caveats of any global assessment of a biological system is the 'large p, small n' problem. This refers to the estimation of possibly several thousand parameters on only a small number of samples. In the case of transcriptomics, usually all the available transcripts are measured in small cohorts (<100 and often < 30 for clinical studies) and unfortunately the number of false positives increases with the number of tests carried out [35]. Several methods have been put forward to deal with this problem in both differential expression and classification contexts [36–38]. Recently, Stretch et al., used a ranking by p-value to show that larger sample sizes were important in generating reproducibility in transcriptomics [39]. However, their strategy of ranking by p-value alone does not consider the effect size i.e. fold change. Fold change and non-stringent p-value limits have been shown to be a better metric for reproducibility in microarray data [40] and in RNA-seq data [20]. Whilst debate continues over statistical methods, science moves forward by replication and even small numbers of subjects can be informative if the result can be replicated in independent cohorts [41]. Indeed this would suggest that in order to make useful conclusions about the mechanisms underlying cancer cachexia, and thus design useful treatments, a concerted effort is required to gather biological material for more analyses of modest cohorts with the aim of reproducibility rather than increasing statistical power.

Systems potentially controlling muscle wasting: data from animal models Muscle atrophy arises through an imbalance between rates of muscle protein breakdown and synthesis and is associated with a range of pathologies. Pre-clinical models have suggested a primary role for the ubiquitin proteasome pathway (UPP) in many muscle wasting contexts,

including cancer cachexia [42]. Early surveys of global gene expression in muscle wasting revealed common molecular changes across a range of atrophic conditions in rodents [43,44]. Bodine et al., surveyed gene expression using the GeneTag differential display [45] approach in response to three stimuli-denervation, immobilisation, and hindlimb suspension. The former conditions shared a number of regulated genes and demonstrated more muscle loss whilst hindlimb suspension had a more distinct profile [43]. Two UPP E3 ligases, MAFbx (Fbxo32) and Murf1 (Trim63) were consistently increased in expression in the early (3 days) stages of each treatment. Generation of separate knockout mouse lines for Fbxo32 and Trim63 demonstrated no phenotype under normal conditions, but there was sparing of muscle in response to denervation atrophy [43]. In both knockout models the rate of muscle loss after an initial 7day period slowed down [43]. This is perhaps the first 'systems' study of muscle wasting and the finding of phenotypically similar changes (gross muscle wasting), but somewhat distinct gene expression profiles underscores the approach. Gomes and co-workers used microarrays to examine skeletal muscle gene expression in starvation [44] and confirmed increased Fbxo32. These studies were expanded to examine skeletal muscle gene expression during starvation in mice, uremia, streptozotocin-induced diabetes mellitus, denervation, disuse, and cancer cachexia in rats [46,47]. The comparison of mRNA expression changes across conditions identified a common set of 120 genes regulated in these conditions including Fbxo32 and Trim63 and gave rise to the term 'atrogenes' to describe these [46]. Components of the UPP were increased in all conditions studied whilst many genes involved in energy generation were expressed at lower levels. Together these studies demonstrated the usefulness of global assessment of the transcriptome in a range of phenotypically similar muscle wasting contexts to identify a common biological signature – increased UPP gene expression and reduced energy metabolism gene expression. From a systems point of view this raises the question of what mechanism might underlie the coordinated changes in the atrogenes. Lecker et al were unable to identify any single transcription factor driving the wasting response in muscle. However, transcription factors implicated in growth were decreased in

expression whereas the signature for increased transcription factors was more mixed [46]. Of note, there was no evidence for involvement of any immune system transcription factors, but the forkhead family member, FoxO1, was increased in expression [46]. Involvement of members of the forkhead family of transcription factors in skeletal muscle atrophy was confirmed by the observation that FoxO family members increased Fbxo32 levels with accompanying myotube atrophy [48] and FoxO1 transgenic mice had lower skeletal muscle mass, decreased expression of type 1 fibre genes in skeletal muscle and enhanced expression of cathepsin L (an atrogene) in skeletal muscle [49]. The involvement of FoxO1 in cachexia was demonstrated when inhibition of FoxO1 using RNA oligonucleotides reversed loss of muscle in mice after establishment of cancer cachexia [50]. Recently a combination of microarray analysis and competitive inhibition studies has found that FoxO transcriptional activity controls the expression or repression of a number of genes involved in cancer cachexia in a murine model [51]. Specifically, dominant negative inhibition of FoxO transcriptional activity moderated C26 colon cancer induced muscle wasting in the TA, EDL, and diaphragm of mice with maintenance of force-generating capacity. These data suggest that FoxO responsive genes co-ordinate a number of systems in cancer cachexia including other transcription factors [51]. Whether these findings can be translated into the more chronic situation of human cancer cachexia remains to be seen. Despite the lack of obvious immune involvement in different atrophy contexts, the immune system has long been postulated to play a role in muscle wasting, with systemic inflammation thought to contribute specifically to amino acid mobilisation from skeletal muscle [52]. However, therapy directed against potent inflammatory mediators has had little success [3] suggesting that, whilst inflammation may contribute to cancer cachexia, the targets for therapy may be less obvious. It is therefore important to identify signalling pathways underlying inflammatory mediated muscle wasting. A screen of TNF superfamily members for activity in myotubes revealed that TWEAK (TNF-like weak inducer of apoptosis) led to a reduction in myotube size. These studies were extended in vivo with chronic treatment of soluble TWEAK or skeletal muscle specific TWEAK over-expression leading to loss of muscle mass and activation of the UPP [53]. TWEAK mediates its effects through binding to fibroblast growth factor-inducible 14 (Fn14/Tnfrsf12a) another member of the TNF superfamily. Interestingly,

Johnston and colleagues recently suggested that Fn14 in muscle does not cause cancer cachexia and increased skeletal muscle expression of Fn14 is a bystander effect. They demonstrated, in mice, that Fn14 positive tumours drive cachexia and that this can be moderated with anti-Fn14 antibodies. Notably whilst antibody treated mice lived longer and experienced little weight loss there was no effect on tumour size [54]. However, whether the TWEAK-Fn14 interaction can be successfully translated to human cancer cachexia to improve treatment outcomes requires further work. Whilst the work detailed above examined systems thought to activate catabolism the question arises as to whether there might also be inhibition of muscle growth pathways in cachexia. Myostatin, a member of the TGF-β family, is a potent inhibitor of muscle growth [55]. The finding that myostatin can bind the activin receptor type IIB (ActRIIB) [56] led to an examination of whether this interaction was important in cancer cachexia [57]. In several rodent tumour models a soluble Act RIIB decoy receptor not only protected against cachexia, but was able to reverse established cachexia with attendant increases in survival. Whilst this is an encouraging result there was continued loss of fat mass, no shrinkage of the tumour and no change in the pro-inflammatory state brought about by the tumour [57]. These results were replicated simultaneously by a second group using an antibody directed against ActRIIB [58]. Circulating activin A has been correlated to cachexia in human cancer patients [59] suggesting that inhibition of ActRIIB may be a useful therapeutic strategy. However, a recent clinical trial (NCT01099761) to examine the use of an ActRIIB decoy antibody in Duchenne muscular dystrophy was stopped early due to safety concerns, although several other trials are ongoing. In summary, the study of animal models has produced valuable data on the biology of muscle wasting in various contexts. Activation of proteolytic pathways is a feature common to many model systems of muscle wasting including cancer cachexia. Members of the FoxO transcription family play a role in muscle wasting and seem to coordinate both increases in catabolic and decreases in anabolic systems. TWEAK may be an important link between muscle atrophy and the immune system with signals generated through the Fn14 receptor. Whether this plays a role locally or is a tumour effect is an open question in cancer cachexia. The recent work

on ActRIIB has illustrated the potential value in investigating growth pathways. Whether there is potential to translate these findings to treatments for humans also remains an open question. However, there is ample opportunity for an integrated systems biology approach to investigate this potential.

What has been learned from the transcriptome about control of human muscle physiology in general and muscle wasting in particular (exercise, diabetes, sarcopenia, COPD)? Much work has been done in both acute and chronic human models and human disease to unravel the mechanisms underlying skeletal muscle atrophy in general. Cachexia, defined as disease-related wasting, would be expected to manifest differently according to the underlying pathology (e.g. sepsis, lung disease, cardiac disease, or cancer). Thus the molecular alterations may be different at early and late phases of the wasting process [60].

Acute contexts Data from acute studies of muscle wasting suggest that many of the candidate genes identified in animal studies are also altered early in human muscle wasting, but not later. One potent physiological stimulus for acute skeletal muscle atrophy is immobilisation. Adabi et al., used microarray technology to profile the skeletal muscle of young males and females (n=12 of each) in response to two weeks of limb immobilisation. They examined global mRNA expression 5 days before immobilisation, 48 hours into immobilisation, and after two weeks of immobilisation [61]. Altogether, some 73% of the genes identified as regulated at the early time-point (48 hours) were still differentially expressed after 14 days indicating a degree of stability in the mRNA expression changes. Notably FBXO32 and TRIM63 were amongst those regulated at the early time-point only. Thus, these may not be useful markers for pre-existing skeletal muscle atrophy in humans. There was also evidence for increased ubiquitination of skeletal muscle protein only at the 48 hour time-point indicating that UPP activation may be an early process that is moderated rapidly. Abadi et al., also examined the potential role for

anabolic pathways by measuring the p-mTOR:mTOR ratio and found that although this was decreased at 48 hours, suggesting decreased mTOR activity, there was no difference at 14 days. The reduced energy requirement of immobilisation was reflected in a profound reduction in expression of mitochondrial genes. Similar reductions in gene expression involved in energy generation pathways and little evidence of increased gene expression patterns related to proteasome activity were found by Chen et al., who compared the global transcriptional signature in patients after immobilisation for fracture treatment with that of healthy controls (62) . Further supporting these results, in both young and elderly there was an initial increase in mRNA for FBXO32 and TRIM63 for up to four days after immobilisation with marked downregulation of both genes at 14 days [63]. These changes were more marked in elderly skeletal muscle than in young muscle. These results suggest that in immobilisation there may be an early imbalance between protein synthesis and degradation, but later muscle loss is a product of reduced turnover rather than runaway catabolism. Reduced turnover is accompanied by homeostatic adjustment in the transcriptome to the reduced energy requirements of the immobilised limb. However, different clinical contexts may lead to a different patterns of pathway activation in human muscle wasting. The data from immobilisation studies (see above) would support an early activation, but subsequent down-regulation of the UPP accompanied by down-regulation of energy generating pathways. In the skeletal muscle of septic intensive care patients [64] a complex picture of lower mitochondrial density with normal per organelle activity and no change in mitochondrial protein synthesis emerged. Interestingly, microarray analysis suggested that most of the detected mitochondrial genes were modestly increased in expression in septic patients in contrast to the findings described above in immobilisation. Indeed, comparison with models of disuse atrophy alone suggested that the disuse signature was less pronounced in human muscle subjected to sepsis-induced wasting than in animal model muscle wasting contexts. This would suggest that immobilisation per se does not contribute much to muscle wasting in sepsis and that increased energy generation is required even in 'immobile' muscle in some contexts. Also at odds with the immobilisation data was that the expression of genes involved in protein catabolism (including FOXO3), suppression of growth/differentiation and

extracellular matrix proteins was in the same direction as in the animal models [64] perhaps reflecting the rapid nature and profound physiological dysregulation of sepsis-induced wasting.

Chronic contexts The gene expression changes underpinning chronic or sustained muscle loss would be expected to be different from those seen in acute studies and indeed the literature reviewed above would suggest this to be the case. In keeping with the observation that activation of atrogenes may be an early hallmark of muscle wasting there was an increase in atrogene gene expression in early [65] but not late spinal injury [66]. Indeed, in chronic spinal cord injury atrogene proteins, myostatin and the nuclear presence of FoxO transcription factors are all reduced [66] indicating a moderation of atrophy pathways and potentiation of growth pathways to conserve muscle mass. Sarcopenia, the age-related loss of muscle mass has been the subject of several studies [67–70], but on the whole these have failed to confirm a reproducible molecular signature. A recent analysis using a correlative approach rather than differential expression between young and old suggested that ageing skeletal muscle shared an inhibition of MYC signalling with exercise training and that the molecular signature of elderly muscle does not simply reflect lower physical activity level [71]. The same study also demonstrated that gains in muscle mass in response to resistance training (RT) were greatest in those who moderated the activity of the mTOR pathway. Follow-up work has since identified a transcriptomic signature in healthy ageing that is reproducible across different tissues [41]. Since RT is suggested as a treatment for muscle wasting generally [72,73], this raises the question of how best to alter pharmacologically this pathway for treatment of wasting. Whilst skeletal muscle wasting in ageing generally takes place over years, and in spinal cord injury takes weeks, there are several disease states where, like cancer cachexia, the time course of tissue loss is less certain and may precede diagnosis of the underlying disease by some time. Chronic obstructive airways disease (COPD) is one example. An early microarray survey revealed increased expression of FoxO transcription factors, but not atrogenes or inflammatory cytokines in the locomotor skeletal muscle of COPD patients [74]. A survey of atrophy

mediators at the protein level in COPD confirmed increased FoxO1 nuclear content (as well as increased FOXO1 mRNA) and increased FBXO32 and TRIM63 mRNA. FBXO32 protein tended towards increase, but did not reach statistical significance. Interestingly, the same study found no difference in atrogene related mRNA expression between weight-stable and weightlosing COPD patients, but there was a signature for anabolic pathways in weight losing patients suggesting either an attempt at compensation for muscle loss or deranged muscle turnover [75]. Others have identified increased autophagy as a mechanism in COPD-driven muscle wasting (in the absence of FBXO32 and TRIM63 mRNA changes) and this was also accompanied by increased phosphorylation of FoxO1 but not FoxO3a in patients compared with controls. Notably, the ratio of the phosphorylated to non-phosphorylated FoxO protein was not statistically different between patients and controls indicating that only a small change may be required in this ratio to activate muscle wasting [76]. Loss of skeletal muscle mass is an important prognostic predictor in heart failure [77]. No global survey of skeletal muscle changes in cardiac cachexia have been carried out in humans. This is rather surprising and even more so when one considers that the 'muscle hypothesis' postulates that skeletal muscle changes re-set the perception of exercise intensity leading to dyspnoea and fatigue at low exercise loads [78]. This hypothesis has had support from studies examining the role of the ergoreceptor reflex in heart failure [79,80]. Whilst not yet investigated in other chronic wasting contexts, this may be a mechanism for skeletal muscle wasting unique to heart failure and thus the global response of skeletal muscle in the transition to exercise intolerance merits further investigation. One study has found increased activity of the proteasome in the quadriceps of heart failure patients [81]. Increased proteasomal activity in this condition may be driven by NF-κB but work in animal models has also suggested a role of angiotensin II [82,83]. A role for increased apoptosis in heart failure has been suggested by the finding that in some heart failure patients apoptosis is increased in skeletal muscle and the amount of apoptosis correlates with exercise intolerance [84,85], but these findings have been criticised on the grounds of flawed methodology [86]. Inhibition of adequate skeletal muscle growth responses in heart failure is suggested by findings that myostatin is secreted from the failing myocardium and may dysregulate skeletal muscle growth [87,88], but others have found

no relationship between myostatin and severity of heart failure although skeletal muscle mass was not assessed [89]. The mixed results might be explained by changes in regulators of myostatin in some individuals as has been seen in rodent models [90]. Acute studies of immobilisation-driven human muscle wasting suggest a transient increase in the UPP. The transcriptome adapts to the reduced energy requirements of immobilisation. However, in acute systemic illness, a different picture is seen with less overlap with the signature derived from pre-clinical disuse models. In chronic contexts increased autophagy has been implicated in COPD with potentially increased Foxo transcription factor activity. In general there is little evidence from limited COPD or cardiac cachexia data to suggest the UPP is responsible for the failure to maintain muscle mass. An integrated approach with well phenotyped clinical cohorts would be a very powerful approach to open new avenues for maintaining muscle mass in these diseases.

Human cancer cachexia data We have used microarrays to examine global mRNA expression in cancer cachexia. Using a correlative approach we were able to demonstrate that mRNA expression in the rectus abdominis of upper gastrointestinal (UGI) cancer patients was able to cluster individuals across a clinically meaningful weight loss of 5% or more [91]. This gene signature was not related to inflammation as assessed by C-reactive protein measurement. Increased expression of both mRNA and protein for CAM-kinase II indicated that calcium handling was altered in skeletal muscle of UGI cancer patients. We did not identify any of the pre-clinical candidate atrogenes as altered in either the microarray data or by RT-qPCR [91]. We followed this analysis up with an examination of the effect of surgical removal of the tumour on mRNA levels in the quadriceps [92]. We found that the vast majority of regulated genes were suppressed in cancer cachexia and that removal of the tumour normalised gene expression such that mRNA levels were indistinguishable from healthy control muscle. We were unable to identify any underlying definitive transcription factor signature in the regulated mRNAs, but network analysis suggested that NF-κB and caspases were network hubs. The regulated mRNA were enriched for both

anabolic and catabolic processes indicating altered muscle turnover rather than runaway catabolism. These results are similar to those of D'Orlando et al., who found no difference in atrogenes, myostatin, follistatin (a negative regulator of myostatin), activinA or inhibin-α in the skeletal muscle of gastric cancer patients with 4% weight loss [93]. Similarly, there was no evidence of increased atrogene expression in lung cancer patients or oesphageal cancer patients whilst activation of autophagy was seen in both studies [94,95]. However, others have found increased UPP gene expression and activity in weight-losing cancer patients [96–100]. Increased apoptosis could also account for reduction in muscle mass in cancer cachexia and increased DNA laddering has been found in the skeletal muscle of cachectic cancer patients [101]. Muscle protein breakdown and synthesis are very sensitive to both physical activity and the feed/fast cycle [102,103]. Acute disease often results in both immobilisation and some degree of anorexia or fasting whereas in chronic disease physical activity may be maintained [92] and anorexia or fasting less pronounced. Measures of gene expression and muscle protein synthesis/breakdown are often made whilst the patient is fasted and/or immobilised and this may affect the physiological readouts. Optimally, assessment of skeletal muscle should be made in a state that reflects the lifestyle or circumstance of the individual. We have recently developed a method for examining myofibrillar protein synthesis using a single bolus dose of singly (2H) labelled water [104] that allows such measures to be made over the course of days. This technique avoids the requirement for fasting and acute immobilisation used in many intravenous tracer studies. Using the former method we have concluded that a small increase in muscle protein breakdown may be responsible for the loss of muscle mass seen in cachexia related to upper gastrointesinal malignancy [105]. Thus, even in cancer cachexia, the underlying mechanisms of muscle wasting are not clear. Whilst reduced turnover and autophagy activation would be broadly in agreement with COPD data, there is some evidence that the UPP also plays a role. These discrepancies highlight that the majority of the human studies have been made on unselected patients with variations in weight loss and aetiology (i.e. primary tumour). Thus, any systems approach requires well

phenotyped cases and controls. This is especially true with regard to cachexia status i.e. noncachectic, pre-cachectic, cachectic and refractory cachectic patients.

A role for microRNA? MicroRNA (miRNA) are short (~23nt) RNA species that moderate gene expression predominantly via translational inhibition of mRNA [106]. The effects of miRNA expression are thought to be most important during development and stress responses in cells. Several miRNA have been described as tissue specific and a group of miRNA including miRNA-1-1/12, miRNA-133a/b, miRNA-206, miRNA-208a/b are termed the myomirs because of their role in cardiac and skeletal muscle. Several of these miRNA are duplicate genes or highly similar and are predicted to target the same genes in skeletal and/or cardiac muscle development (107, 108).Whilst single knockouts in mice often display no phenotypic effects, double knockouts are usually embryonic or neonatal lethal demonstrating the redundancy and the importance of miRNA in developmental contexts [109]. Many studies have examined myomir function in the context of cardiomyopathy, but less work has been done in skeletal muscle. Soares et al., used in-house microarrays to survey skeletal muscle global miRNA and mRNA expression in denervation, starvation, streptozotocin-induced diabetes and C26-induced cancer cachexia [110]. Each treatment led to muscle loss with a distinct miRNA signature. Indeed, denervation was examined at three time-points and each time-point had a particular miRNA signature. Notably miRNA-21 and miRNA-206 were increased from 7 days after denervation. MiRNA-21 has recently been implicated in cancer cachexia as a paracrine factor [111]. In denervation, miRNA-206 elevation accompanies atrophy and promotes rapid reinnervation in a mechanism that relies on repression of HDAC4 [112,113]. In terms of cancer cachexia, two weeks after C26 tumour implant in BALB/c mice, gastrocnemius mass was reduced by 25% and the majority of differentially expressed miRNA were down-regulated. These included miRNA-23a and miRNA-1 whilst the bicistronic partner of miRNA-1, miRNA133a was up-regulated. In contrast, microarray revealed elevation of miRNA-1-1 in dexamethasone-induced skeletal muscle atrophy [114] via a mechanism thought to involve

myostatin [115]. The increase in miRNA-23a found in cancer cachexia may reflect the importance of the UPP and particularly Fbxo32 and in the murine system. Wada et al., identified miRNA-23a as a potential regulator of Fbxo32 and Trim63 and forced expression of miRNA-23a led to resistance to dexamethasone induced skeletal muscle atrophy [116]. Similar results in terms of specific signatures were seen in a study of miRNA expression in 10 different human primary muscle wasting disorders [117]. These workers identified 55 miRNA that were regulated in at least 5 primary muscle disorders compared with normal skeletal muscle. Most were increased in expression indicating repression of target gene product expression. Again none of the myomirs were included in this list although miRNA-21 was elevated across 8 of the diseases [117]. In a microarray study examining potential miRNA contributions to sarcopenia Drummond et al., examined miRNA expression between young and old human skeletal muscle [118]. They determined that 18 miRNA were regulated, although a number of these could not be validated by qPCR and the fold changes were often very small (FC=0.1-0.2). Of the classic myomirs, only miRNA 133a and b were altered. Both weredown-regulated in the elderly, butonly by a small amount (FC=0.1). There was little overlap with the miRNA seen altered in the multiple comparison study by Soares et al., - although species, platform and temporal confounders could account for this observation. We have previously shown that bioinformatic interrogation of a cohort of regulated miRNA can provide information relevant to disease in skeletal muscle [119]. Using a similar approach in myotonic dystrophy type 2, Greco et al., revealed that miRNA may regulate pathways relevant to muscle wasting such as skeletal and muscular disorders, TGF-β signaling, and PI3K/AKT signaling [120]. There are various control mechanisms involved in miRNA expression. In a study examining the potential circuitry involved in muscle wasting in chronic kidney disease, Wang et al., identified a role for miRNA-29 [121]. A microarray survey of miRNA expression in a murine model of chronic kidney disease revealed 12 differentially regulated miRNA including reduced miRNA-29a/b. The primary and precursor transcripts for these miRNA were reduced, suggesting transcriptional control. The YY1 consensus motif was detected upstream of the miRNA primary transcripts and YY1 was expressed at a higher level in the muscle of CKD mice. Transfection of a miRNA-29 expression vector into C2C12 cells led

to lower YY1, suggesting negative feedback and increased differentiation. Conversely, transfection of a YY1 expression vector led to the opposite outcome [121]. Notably NF-κB was found to up-regulate YY1, and thus reduce miRNA-29 expression, adding evidence for a role of NF-κB in muscle wasting [122]. These findings suggest miRNA control of processes active in cachexia, or the mechanisms controlling miRNA expression may be therapeutic targets in cancer cachexia. We have carried out a preliminary microarray of miRNA expression in the skeletal muscle of cachectic cancer patients using the Affymetrix Gene miRNA platform (ver 2.0). We detected 30 miRNA as regulated between cachectic cancer patients and control surgical patients (n=6 in each group); all miRNA were increased in expression (Figure 3). There was no evidence for involvement of the myomirs or the myomir network. Analysis of the biological pathways likely targeted by these elevated miRNA [119] revealed control of the Wnt, Adherens junction, Focal adhesion, mTOR signalling and UPP pathways (Table 1). These pathways all have potential relevance in cachectic muscle and may have therapeutic potential. In general, however, the apparent individuality of miRNA regulation in different muscle wasting contexts would suggest that potential therapies may have to be targeted to individual diseases rather than targeting one over-arching pathway that may control muscle wasting. Again, this underscores the requirement for an effort to collect and biobank material from diverse populations and disease states associated with muscle wasting, if there is to be progress towards understanding the mechanisms involved.

Proteomic approaches As in surveys of mRNA changes, several studies have used proteomic approaches to examine muscle atrophy in conditions other than cachexia. Ibebunjo et al., used a combination of transcriptional and proteomic analysis to examine aging skeletal muscle in rats [123]. Using k-means clustering, mRNAs with a profile matching that of muscle loss were found to be enriched for energy metabolism and myofibrillar content. Genes thatwere expressed inversely to muscle loss with age were enriched for translation and immune function. Cluster analysis of

proteins identified using LC-MS/MS essentially confirmed the patterns seen in the transcriptome [123]. Due to the heterogenous nature of skeletal muscle and the technical issues in whole proteome identification in this tissue (see Proteomic technologies section), mass spectrometry techniques might be best applied to specific questions. Ryder et al., used LCMS/MS to examine the proteomic response to immobilization in rat skeletal muscle concentrating on differential lysine acetylation (which promotes) and ubiquitination. Lysine acetylation on proteins has been shown to inhibit UPP driven protein degradation. Assessment of mRNA expression of Fbxo32 and Trim63 demonstrated an initial increase over the first four days of the study and falling expression at day 6. After 6 days of immobilization, up to 50 proteins were differentially acetylated at lysine residues with the majority of these residues showing de-acetylation. De-acetylated proteins were enriched for contractile and energy generating processes [124]. Up to 220 proteins were differentially ubiquitinated under immobilisation at 2, 4 and 6 days, with an over-riding signature for contractile proteins [124]. Interestingly, more differentially ubiquitinated proteins showed a decrease in ubiquitin than an increase at each time-point, although overall, contractile proteins had increased ubiquitination. Given the changes in ubiquitination, it is unfortunate that the techniques used could not differentiate between monoubiquitination (regulatory) versus polyubiquitination (proteasomal activity). Gelfi et al., used 2D gel electrophoresis and ESI-MS/MS to profile aged (70-76, n=3) and young (20-25, n=6) skeletal muscle. Proteins involved in aerobic metabolism were increased in young muscle whilst elderly muscle demonstrated increased expression of proteins involved in aerobic metabolism [125]. Whilst these findings are somewhat contradictory to those described above in rodents, the elderly subjects used in this study were healthy and physically active. and unfortunately the degree of sarcopenia was not quantified. It was also unclear whether the biopsies were taken in the fasted or fed state. Proteomic studies of human cancer cachexia are few and far between. Most studies aimed at examining proteomic profiles in cachexia have used a focused approach correlating clinical parameters with subsequent analysis of proteolytic, autophagic and/or protein synthesis pathways using biochemical methods like western blot. Tardif et al., examined the role of the UPP, calpains and autophagy in patients (n=14) with upper-gastrointestinal cancer versus non-

cancer controls (n=8). They found no difference in the expression of protein products of the atrogenes (Fbxo32, Trim63) or activity of the UPP and no difference in calpain activity [95]. There was, however, evidence of increased autophagosome numbers and increased activity of both cathepsin B and cathepsin L activity in both the diaphragm and the vastus lateralis of the cancer patients compared with controls [95]. These findings suggest a role for autophagy in cancer cachexia. Williams et al., studied the effect of tumor burden and subsequent surgical resection on anabolic responses in skeletal muscle comparing inpatients with colorectal cancer (n=13) and matched healthy controls (n=8) [126]. Surgical resection led to re-instatement of the anabolic response to feeding in cancer patients (increased fractional synthetic rate) although there were no post-operative changes in selected anabolic phospho-protein signatures as assessed by western blot [126]. One important area where proteomic techniques could be valuable is the identification of biomarkers in serum and urine. Skipworth et al., used MALDI-MS to profile the urine of weight-stable or frankly cachectic cancer patients with the aim of identifying biomarkers for ongoing muscle wasting. Peptides belonging to myosin species and spectrin and several other proteins were variably evident in the urine of all the cachectic patients. Weight-stable cancer patients had neither of these in the urine and one healthy control had myosin18b [127]. In a follow-up study using SELDI-TOF MS and examining cancer patients and controls, there was no identification of myosin peptides in the urine of upper gastro-intestinal cancer patients, but several urinary markers associated with cancer or other diseases were identified [128]. The drawback of these studies is that they are stand-alone and additional information allowing a better interpretation of the data like genetic information or muscle function and quality is not available. Thus poor phenotyping may contribute to the low reproducibility of identified biomarker candidates [129,130].

Genome: the genetic basis for variation in the prevalence of cachexia? For any given type of tumour it is evident that some patients lose weight early, some at a later

phase of their illness and some seem relatively resistant to weight loss. Such a pattern suggests that there may be at least a component of the cachexia syndrome that is determined by host factors rather than by the tumour alone. One hypothesis to account for such inter-individual variation is that the susceptibility to cachexia is due, in part, to inherited genetic variations (host), the remaining phenotypic variance being ascribed to the contribution of the tumour or other comorbidity. The primary approach to investigating this issue has been to compare individual or a panel of candidate single nucleotide polymorphisms (SNPs) and their association with the cachexia phenotype. A key issue has been accurate definition of the cachexia phenotype [1] in a large enough cohort of patients. Equally, for a candidate gene approach, there is the issue of choosing relevant SNPs in genes that may be involved in aspects of the syndrome. Cachexia is a complex syndrome with mechanisms of weight loss including both reduced food intake and abnormal metabolism. Moreover, although there is general consensus that systemic inflammation in combination with neuro-endocrine activation are key mediators, the precise individual components of the mediator network involved in any one group of patients has not been resolved [131]. As might have been expected, initial single SNPs with potential functional associations in the elaboration of various pro-inflammatory cytokines were associated with cancer cachexia. In one of the few studies with a more adequate sample size, but small validation cohort, a variant, rs-6136 from the SELP gene (that encodes for the cell adhesion molecule P-selectin) was identified and investigated in depth for functional significance in animal models [13]. The association with SELP and cancer cachexia has since been replicated in pancreatic cancer patients, however in the latter study the C allele, thought to increase risk of weight loss was found to be protective for the development of cachexia [132]. This may illustrate a diverse biological affect in different cancers but also the requirement for large, well phenotyped informative cohorts. Many new target genes that might potentially influence the development of cancer cachexia have been reported including AKT1 [132], and have been incorporated into a recently published review of candidate genes and polymorphisms to aid association studies for the identification and characterisation of genetic determinants of the different phenotypic domains described in cachexia [133]. Candidate genes and their polymorphisms include pro/anti-inflammatory pathways, neuronal melanocortin signalling

pathways, energy regulation, appetite regulation, muscle, and adipose tissue catabolic pathways. However, such analyses are not of a genome-wide nature and therefore genetic variants with much greater functional significance may have not have been examined. Equally, the true functional significance of any individual SNP for cancer patients is mostly unknown. It may, therefore, be better to consider the genetic associations identified as genetic signatures or biomarkers associated with the cachexia syndrome. Many of the SNPs reported as showing significant associations with the cachexia phenotypes are in intronic, 3’, or 5’ UTRs. The correlation pattern (albeit, low to modest) observed is still encouraging since the trends reported for such SNP loci are (by definition) within the scope of the known cachexia literature. Further replication of current findings and fine mapping of the loci may offer insights. Without doubt, however, the next step is to assemble a large enough (3-5,000) cohort of well characterised patients to allow genome-wide studies.

Conclusion The enormous progress in our understanding of muscle physiology (partly stimulated by the developments around sports medicine) is now being applied to the numerous clinical situations where muscle wasting contributes to the illness experienced by the patient and the outcome of treatment. In terms of cancer cachexia, the transcriptome has suggested that although the ubiquitin proteasome pathway may be activated early, there is little evidence for chronic highlevel activity to account for progressive muscle wasting and failure to maintain muscle mass – thus other pathways including autophagy or altered regeneration may be important. The integrated approach of systems biology would help to decipher which pathways are activated/inhibited in early and late phases of cachexia. This information will probably lead to the use of different strategies to treat cancer cachexia depending on the stage the patient is at. Proteomic studies of muscle from cachectic cancer patients are very scarce and more data from carefully characterised groups of patients are awaited. Candidate gene studies would suggest that there may be a genetic component to the development of cachexia. Components of innate immunity are leading contenders to account for such phenotypic variation. However, it will require a major effort in biobanking to allow sufficient sample size for genome-wide techniques

to be applied. The approach to systems biology using “omics” technologies is evolving with novel techniques and better bio-informatics. However, most studies still use single “omics” platforms and focus too much on single pathways. Research in human cancer cachexia will benefit from better integration of the different platforms and better use of integrated pathway analyses. In addition, such science is only as good as the clinical classification of the patients being studied and the reproducibility of the findings. Evaluation of longitudinal as well as cross-sectional cohorts with clinically well-defined and described patients is required. All this will lead to the best usage of system biology and the discovery of new pathways/systems important in the cachexia of that individual patient or well-defined groups of patients.

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Figure Legends Figure 1. Western blotting for myosin heavy chain 2 (MYH2) in wild type (WT) and Brucella abortis mouse model (2 weeks). Visualisation of differences in MYH2 protein content less discernable when 3ug of total protein are loaded onto the gel (top panel) than after loading 1ug of total protein (bottom panel). Figure 2. Immunohistochemistry for laminin (green) with visualisation of CDKN2 mRNA via RNAScope (yellow) in young (6mo) and old (23mo) rat tibialis muscle. Information about fibre shape and continuity is retained. Figure 3. Heatmap representation of expression of differentially regulated miRNA assayed using Affymetrix miRNA ver 2.0 microarrays in the skeletal muscle of surgical control and cancer patients.

Table 1. Pathways targeted by the cohort of miRNA demonstrating increased expression in the skeletal muscle of cachectic cancer patients compared with control patients. Analysis was carried out as in [119]. KEGG ID 4310 4520 4510 4150 4120

Pathway Name Wnt signaling pathway Adherens junction Focal adhesion mTOR signaling pathway Ubiquitin mediated proteolysis

p-value <0.01 <0.01 <0.05 <0.05 <0.1

OR 4.2 3.5 2.2 2.9 1.7