Abstract
Decline in skeletal muscle cell size (myofiber atrophy) is a key feature of cancer-induced wasting (cachexia). In particular, atrophy of the diaphragm, the major muscle responsible for breathing, is an important determinant of cancer-associated mortality. However, therapeutic options are limited. Here, we have used Drosophila transgenic screening to identify muscle-secreted factors (myokines) that act as paracrine regulators of myofiber growth. Subsequent testing in mouse myotubes revealed that mouse Fibcd1 is an evolutionary-conserved myokine that preserves myofiber size via ERK signaling. Local administration of recombinant Fibcd1 (rFibcd1) ameliorates cachexia-induced myofiber atrophy in the diaphragm of mice bearing patient-derived melanoma xenografts and LLC carcinomas. Moreover, rFibcd1 impedes cachexia-associated transcriptional changes in the diaphragm. Fibcd1-induced signaling appears to be muscle selective because rFibcd1 increases ERK activity in myotubes but not in several cancer cell lines tested. We propose that rFibcd1 may help reinstate myofiber size in the diaphragm of patients with cancer cachexia.
Subject terms: Skeletal muscle, Cancer, Cytokines
Myofiber atrophy occurs in many diseases but the mechanisms responsible for myofiber size determination are incompletely understood. Here, the authors show that the muscle-secreted factor Fibcd1 is necessary to maintain myofiber size and mitigates myofiber atrophy induced by cancer cachexia
Introduction
Skeletal muscle wasting, defined as the loss of muscle mass and strength, is a component of cachexia, a multifactorial syndrome characterized by systemic inflammation and weight loss, and it is a severe complication of many cancers1–4. It is estimated that cancer cachexia occurs in ∼50% of tumors and that it is responsible for ∼1/3 of cancer deaths5,6. Strikingly, even a modest cancer-induced decrease (~5–10%) in skeletal muscle mass reduces the functional capacity of the organism and increases the risk of mortality from cancer, whereas muscle hypertrophy is protective7–12. Specifically, preventing muscle mass loss in tumor-bearing mice improves prognosis and prolongs their survival even if cancer growth per se is not halted8,9,13,14. The mortality due to cachexia has been primarily attributed to wasting of the heart and of the diaphragm (the major muscle responsible for breathing)9,11,15–18. Despite the importance of diaphragm atrophy in determining cancer-associated mortality, only few therapeutic approaches are currently available. In particular, inspiratory muscle training has been found effective in improving diaphragm function in a number of disease conditions19–23. However, apart from this exercise regimen, no pharmaceutical therapies are available to impede diaphragm wasting.
At the cellular level, cancer-induced muscle wasting is primarily due to a decrease in the size of myofibers, the syncytial cells that compose the muscle5,6,24. Specifically, cancer cells and associated host stromal cells secrete a number of pro-inflammatory factors that promote myofiber atrophy by inducing catabolic signaling and muscle protein degradation5,6,12,24–26. Although an increase in tumor burden can lead to an increase in cachexia, there is a broad range of variability in cachexia progression and tumor size is only one of the factors (together with cancer type and host factors) that influences cachexia progression27. Importantly, the panel of cachectic cytokines produced by cancer cells and associated host stromal cells has been found to be a key determinant of cachexia. For example, cancer cachexia is abrogated in a lymphoma model when the translation of cachectic cytokines produced by the lymphoma is reduced, and this improves survival independently from neoplastic growth28, as also found in other models8,9,13,14. Moreover, inflammatory cytokines can also be produced by immune cells, including those infiltrating the muscle, in response to tumor-derived signals29,30, thus resulting in a systemic cytokine storm that is conducive to body wasting31.
In addition to cachectic cytokines, the extent and outcome of cachexia is profoundly impacted by the responsiveness of target tissues to inflammatory/wasting signaling and/or the concurrent activation of compensatory pathways that mitigate cachexia-induced changes in target tissues27. In skeletal muscle, several signaling pathways have been found to regulate myofiber size in response to cachectic cytokines5,6,12,24–26. Interestingly, some of these pathways can also be modulated by muscle-secreted factors, i.e. myokines32, and exerkines, i.e. signaling factors secreted by myofibers, muscle-infiltrating cells, as well as by other tissues in response to exercise33. Indeed, several myokines and exerkines regulate myofiber size in an autocrine/paracrine manner34–36.
Initial evidence for the role of myokines in myofiber size regulation was found from the analysis of mice with postnatal knockout of the myokine myostatin, which resulted in myofiber hypertrophy37–39. Moreover, contraction-induced myokines (which are also referred to as exerkines33), such as irisin and decorin, were found to promote myofiber hypertrophy in response to exercise40–43. Other myokines are induced by muscle injury and promote muscle regeneration by acting on muscle satellite cells, differentiating myofibers, and/or muscle-infiltrating immune cells44–49. Importantly, a few myokines were also found to contrast disease-associated skeletal muscle wasting50–54. For example, the exerkine apelin reverses age-associated muscle wasting (sarcopenia) and also promotes regeneration, mitochondrial biogenesis, and autophagy and impedes inflammatory pathways in myofibers52. However, apart from extensive efforts in developing myostatin inhibitors55,56 and few other notable studies52,57,58, the possibility of using recombinant growth-promoting myokines to treat disease-associated myofiber atrophy has not been explored exhaustively.
Here, we have used Drosophila developmental larval muscle growth12,59,60 to screen >100 evolutionary-conserved myokines for their capacity to regulate myofiber size. Further testing of one of these myokines, secreted Fibcd1 (Fibrinogen C Domain-Containing Protein 1), determined its evolutionary-conserved role in myofiber size regulation in mice, and that recombinant Fibcd1 (rFibcd1) mitigates myofiber atrophy associated with cancer cachexia in the diaphragm muscle. Mechanistically, we find that Fibcd1 promotes MAPK/ERK signaling, which is necessary to preserve myofiber size and to respond to innervation in adult mice58,61–64. Interestingly, Fibcd1 increases ERK activity in myotubes but not in several cancer cells, although there are exceptions. This suggests that rFibcd1-based anti-wasting therapies may avoid the side effect of promoting ERK-driven cancer cell proliferation in the context of many cancers. We propose that interventions based on rFibcd1 may help reinstate myofiber size in the diaphragm of patients affected by cancer cachexia and by other disease states characterized by muscle wasting.
Results
RNAi and overexpression screening identifies evolutionary-conserved myokines that determine myofiber size in Drosophila
Several myokines have been identified by transcriptomic and mass-spectrometry studies32,36,65 but their role in muscle wasting remains largely unexplored. Signaling pathways that regulate muscle mass in mammals play similar roles also in Drosophila, as found for insulin receptor/FoxO signaling12,59. On this basis, we examined whether evolutionary-conserved myokines regulate the size of Drosophila larval body wall skeletal muscles, which each consist of a single myofiber. As previously shown12,59,60, muscle-specific interventions that change the size of the body wall musculature correspondingly change the larval body size. On this basis, the larval size was used as primary screen readout to estimate the capacity of each myokine to regulate developmental muscle growth, which was followed by quantification of myofiber size. Overall, we followed an experimental pipeline (Fig. 1a, b) similar to the one we recently employed to screen for ubiquitin ligases60 and transcription factors66. Specifically, the UAS/Gal4 system67, the skeletal muscle-specific Mef2-Gal4 driver59,68, and 508 UAS-RNAi transgenic fly stocks were used to knock down 111 evolutionary-conserved myokines that have strong muscle expression (RNA-seq FPKM values ≥4), and assess their role in myofiber growth (Fig. 1a–c). Whenever available, overexpression lines for the corresponding myokines were also tested.
In comparison to control RNAi lines for GFP and white, this muscle-specific RNAi screen and follow-up validation indicated that 31/508 (6.1%) RNAi lines induce myofiber atrophy (Fig. 1c, Supplementary Fig. 1, and Supplementary Data 1) similar to what is observed with overexpression of the transcription factor FoxO, indicating that these myokines are necessary to sustain the ~40-fold myofiber growth that occurs during larval development12,59. Conversely, similar to insulin receptor (InR) overexpression, 12/508 (2.3%) RNAi lines induced myofiber hypertrophy (Fig. 1c and Supplementary Data 1), indicating that these myokines normally limit developmental muscle growth, similar to mammalian myostatin38,69. Further testing via immunostaining confirmed that the size of representative skeletal muscles (VL3-VL4) is indeed modulated by RNAi interventions that induce atrophy and hypertrophy (Fig. 1d). Importantly, transgene expression with this Mef2-Gal4 does not affect the number of syncytial nuclei59, indicating that the changes in myofiber size here observed do not arise from altered myoblast fusion.
Among the myokines that scored, a first class of atrophic phenotypes was induced by RNAi lines for growth factors, which indicates that they are necessary for myofiber growth in an autocrine/paracrine manner. For example, 4 different RNAi lines for the myostatin-binding protein SPARC reduced myofiber size (Fig. 1d, e), suggesting that SPARC normally prevents atrophy by binding to and inhibiting TGF-β ligands such as myostatin, as found in mice70. Moreover, muscle-specific RNAi for the BMP2/4 homolog dpp also induced myofiber atrophy (Fig. 1d, e), presumably via the capacity of BMP ligands to antagonize TGF- β signaling and promote myofiber hypertrophy71.
Lastly, RNAi for the FGF homolog bnl decreased myofiber size (Fig. 1d, e), possibly by limiting the development of the muscle-associated trachea, which delivers oxygen to sustain muscle growth, similar to the mammalian vasculature72, whereas overexpression of the PDGF/VEGF homolog Pvf1 induced myofiber hypertrophy (Fig. 1f, g). Other growth factors included Wnt4 and Gpb5 (homologous to WNT9 and GPHB5, respectively), which induced hypertrophy when overexpressed. Conversely, overexpression of aos (an inhibitor of EGF receptor signaling) and myoglianin (homologous to myostatin/GDF1173) induced atrophy (Fig. 1f, g).
A second category of atrophy inducers consisted of RNAi for the extracellular matrix proteins cg25c and mfas (Fig. 1d, e), respectively homologous to collagen COL4A1 and to the collagen-binding protein TGFBI. Consistently, COL4A1 mutations cause myopathy in humans74 whereas TGFBI loss reduces developmental myofiber growth in zebrafish75. Interestingly, RNAi for lanB1, homologous to laminin LAMB2, did not significantly affect myofiber size but rather conferred an elongated shape to myofibers (Fig. 1d, e). Other inducers of myofiber atrophy included RNAi for the angiotensin-converting enzyme 1/2 ance, for the apolipoprotein rfabg, and for CG8642, a myokine homologous to mouse Fibrinogen C Domain-Containing Protein 1 (Fibcd1). Altogether, this screen has identified evolutionary-conserved myokines that regulate myofiber size.
siRNAs for mouse Fibcd1 induce atrophy in mouse C2C12 myotubes
The growth-promoting myokines identified in the Drosophila screen are evolutionary conserved. On this basis, we next selected few mouse orthologs for these Drosophila myokines to test whether they regulate the size of cultured mouse C2C12 myotubes. For these studies, we first assessed the capacity of siRNAs targeting these myokines to impact myoblast fusion, and subsequently whether siRNAs transfected post-fusion induce atrophy in myotubes. Analysis at day 4 of myogenic differentiation revealed that siRNAs for Bmp1 reduced myoblast fusion whereas siRNAs targeting Wnt9a, Tgfbi, Sparc, and Fibcd1 did not (Supplementary Fig. 2a, b).
When transfected post-fusion into C2C12 myotubes, siRNAs for Tgfbi, Sparc, and Fibcd1 induced atrophy, compared to NT control siRNAs (Supplementary Fig. 2a, c). Importantly, via a decline in Fibcd1 mRNA levels, Fibcd1 siRNAs induced the strongest atrophy and also worsened starvation-induced atrophy (Fig. 2 and Supplementary Fig. 2c, d). On this basis, we focused further studies on Fibcd1.
Secreted Fibcd1 rescues myotube atrophy induced by siRNAs for Fibcd1
In Drosophila, the Fibcd1 ortholog CG8642 encodes for a secreted protein that contains a fibrinogen-like domain. In mice, several splice variants arise from the Fibcd1 gene. Specifically, the full-length mRNA encodes for a transmembrane version of Fibcd1 (459 amino acids, FL, consisting of exons 1–7), which contains an extracellular fibrinogen domain and has been reported to work as a chitin receptor in epithelia76,77. In addition, a short Fibcd1 splice variant lacks the transmembrane region but carries the fibrinogen domain (202 amino acids, SH, consisting of exons1,5-7) and may therefore be secreted (Fig. 2a). To test this hypothesis, C-terminally flag-tagged short and long versions of mouse Fibcd1 were transfected into HEK293 cells and the amount of Fibcd1 recovered from the supernatant was probed with anti-flag antibodies. Both short (SH) and long (FL) versions of Fibcd1 were detected in similar amounts in transfected cells, compared to empty-vector (EV) controls. However, there was a ~38 kDa Fibcd1 fragment that was recovered from the culture medium of HEK293 cells transfected with full-length Fibcd1 (FL) but not from that of cells transfected with the short version of Fibcd1 (SH). These findings indicate that transmembrane Fibcd1 is cleaved C-terminally to generate a secreted Fibcd1 that includes the fibrinogen domain (Fig. 2b).
On this basis, we next tested whether secreted Fibcd1 rescues the myotube atrophy induced by Fibcd1 siRNAs. For these studies, we produced a ~38 kDa recombinant mouse Fibcd1 (rFibcd1; 282 C-terminal amino acids of FL Fibcd1) similar to the extracellular fragment released by proteolytic processing of Fibcd1. Treatment with rFibcd1 rescued the myotube atrophy induced by Fibcd1 siRNAs, indicating that the myotube atrophy induced by Fibcd1 siRNAs is indeed an RNAi on-target effect, and that rFibcd1 is sufficient to reinstate myofiber size (Fig. 2c).
rFibcd1 rescues myotube atrophy induced by cachectic cytokines
Cancer cells secrete inflammatory signaling factors that induce myofiber atrophy5,6,12,24,25. Because we have found that Fibcd1 is a myokine that preserves myofiber size, we next tested whether rFibcd1 can resolve myofiber atrophy induced by cachectic cytokines. To test this hypothesis, we treated C2C12 myotubes with IL-6 (20 ng/mL), LIF (20 ng/mL), and TNF-α (100 ng/mL), which are known to be upregulated in cancerous states and lead to muscle mass loss25. As expected based on previous reports78–80, in vitro treatment with IL-6, LIF, and TNF-α induced significant atrophy of C2C12 myotubes. However, treatment with rFibcd1 significantly reduced the atrophy induced by IL-6, LIF, and TNF-α (Fig. 2d). Altogether, these findings suggest that Fibcd1 mitigates myotube atrophy induced by cachectic cytokines.
rFibcd1 rescues myotube atrophy by promoting ERK signaling in muscle cells
To examine what signaling pathways are modulated by Fibcd1 and are responsible for its effects on myotube size determination, we examined the effect of Fibcd1 siRNAs and rFibcd1 treatments on the activity of several signaling pathways with a panel of phospho antibodies. The addition of rFibcd1 to the cell culture medium of mouse C2C12 myotubes increased P-p42 and P-p44 (ERK1/2) MAPK levels after 30 min from stimulation (Fig. 3a), whereas no substantial changes were found in the activity of other pathways including JNK and p38 MAPK (Supplementary Fig. 3a).
ERK signaling is necessary for the maintenance of skeletal muscle mass63 and its inhibition prevents IGF-I-induced myofiber hypertrophy64. Moreover, ERK has been shown to be necessary to maintain adult myofiber size and their neuromuscular junctions58,61,62. Mechanistically, ERK can preserve myofiber size via phosphorylation and inactivation of GSK3β81,82 and by promoting protein synthesis via activation of the MAPK-interacting kinase MNK1/2, which in turn phosphorylates the translation initiation factor eIF4E81,83,84.
On the basis of these studies, Fibcd1 may modulate myofiber size at least in part via ERK signaling.
To test this hypothesis, C2C12 myotubes were treated with Fibcd1 siRNAs, rFibcd1, and/or Pyrazolylpyrrole, a pharmacological inhibitor of ERK35,85,86. By using low doses of Pyrazolylpyrrole (2.5 ng/mL), we found that Pyr has no major impact on myotube size in normal conditions (Fig. 3b). However, Pyrazolylpyrrole prevents rFibcd1 from rescuing myotube atrophy induced by Fibcd1 siRNAs, indicating that rFibcd1 reinstates myotube size via its capacity to increase ERK activity (Fig. 3b).
rFibcd1 does not promote ERK signaling in a set of cancer cells
ERK is a major driver of tumorigenesis87 and therefore interventions that combat muscle wasting via ERK signaling may be hindered by the side effect of promoting cancer cell proliferation88. On this basis, we next examined whether rFibcd1 increases P-ERK levels also in cancer cells. To this purpose, we examined P-ERK levels in Lewis lung carcinoma (LLC)89, 4T1 breast cancer90,91, and Saos-2 osteosarcoma cells92. Different from C2C12 myotubes, western blot analyses indicated that rFibcd1 does not promote ERK signaling in these cancer cells, with the exception of Saos-2 cells treated with high levels of rFibcd1 (Fig. 3c). To further test whether rFibcd1 induces ERK signaling in cancer cells, we probed a panel of osteosarcoma, colorectal adenocarcinoma, melanoma, and breast cancer cell lines. In most cases, rFibcd1 induced only marginal changes in P-ERK levels. However, there were also some notable exceptions: rFibcd1 increased P-p44/42 levels in 143B-Luc osteosarcoma and 67NR breast cancer cell lines (Fig. 3d and Supplementary Fig. 3b). Altogether these findings suggest that rFibcd1 may combat myofiber atrophy by inducing ERK signaling in muscle but not in cancer cells. However, this is not universally true because Saos-2, 143B-Luc, and 67NR breast cancer cell lines responded to rFibcd1. Therefore, while rFibcd1 may provide an effective therapy for treating cachexia-induced myofiber atrophy without fueling cancer growth in the context of many cancers, this may not be generally applicable to all cancer types.
Recombinant Fibcd1 primarily consists of a structural domain related to fibrinogen, which is known to bind to and signal via specific combinations of α and β integrins93–95. On this basis, rFibcd1 may bind to integrin receptors similar to fibrinogen (Fig. 3e) and this may represent a mechanism by which Fibcd1 promotes MAPK phosphorylation, a known readout of integrin signaling95.
To examine whether α/β integrins known to bind to fibrinogen, including Itgα2b93–95, are necessary for rFibcd1-induced ERK phosphorylation, we first examined their differential expression in C2C12 muscle cells versus rFibcd1-non-responsive cancer cells. RNA-seq indicates that whereas integrin β2 and β3 expression occurs across cell lines, Itgα2b is expressed in muscle but not in cancer cells (Fig. 3f). Analysis of Itgα2b expression from larger datasets further confirmed that Itgα2b is poorly or not expressed in many pediatric and adult cancers (Supplementary Fig. 4). Subsequent qRT-PCR analysis indicates that Itgα2b is not expressed in rFibcd1-non-responsive cancer cells (4T1, E0771, Ep5). Conversely, the rFibcd1-responsive cancer cell line 67NR (Fig. 3d and Supplementary Fig. 3b) displays Itgα2b expression levels similar to those of C2C12 myotubes (Fig. 3f), suggesting that Itgα2b might be a receptor for rFibcd1.
To test whether Itgα2b is indeed required for Fibcd1-mediated P-ERK induction, C2C12 myotubes were treated with Itgα2b siRNAs (Supplementary Fig. 3c). Compared to control NT siRNAs, Itgα2b siRNAs reduced P-ERK levels both at steady state and upon rFibcd1 administration (Fig. 3g), indicating that Itgα2b expression is needed for the optimal response of muscle cells to rFibcd1.
rFibcd1 rescues LLC cancer-induced myofiber atrophy in the diaphragm muscle of mice
To test the therapeutic potential of rFibcd1 in vivo, we employed an established model of cancer cachexia based on the subcutaneous injection of Lewis Lung Carcinoma (LLC) cells60,96,97.
For these experiments, ~106 LLC cells were injected subcutaneously in each flank and allowed to grow for ~3 weeks. One week before reaching the endpoint, tumor-bearing mice were randomly allocated to receive 3 intraperitoneal injections of rFibcd1 (every other day; 1 mg/kg of rFibcd1 in PBS with 1%BSA) or mock (PBS with 1%BSA). Cohorts of isogenic C57BL/6 J control mice devoid of tumors were similarly injected with either rFibcd1 or PBS.
A key determinant of cachexia-associated mortality is wasting of the diaphragm, the muscle necessary for respiration11,98. Therefore, interventions that preserve the size of diaphragm myofibers are crucial for reducing mortality associated with cachexia and other critical illnesses99. On this basis, we have tested whether rFibcd1 rescues cancer-induced atrophy of diaphragm myofibers and found that this is the case (Fig. 4). Specifically, LLC cancer cells induce atrophy of all myofiber types (1, 2a, and 2x/2b) but this is rescued by intraperitoneal rFibcd1 injection (Fig. 4a, b), as indicated by the Feret’s minimal diameter, a geometrical parameter indicative of myofiber size100. However, rFibcd1 injection does not affect myofiber size in wild-type (non-cachectic) conditions (Fig. 4a, b), indicating that Fibcd1 maintains steady-state myofiber size but does not induce hypertrophy.
Because myofiber types have different defining sizes, the reduction in myofiber atrophy due to rFibcd1 may be explained via its capacity to promote a shift from type 1 to type 2a or 2x/2b myofibers, which are bigger101. However, immunostaining of diaphragm muscles with antibodies for distinct myosin heavy chain isoforms revealed that there are no changes in the relative abundance of different myofiber types present in the diaphragm of mice treated with rFibcd1 versus controls (Fig. 4c).
We next analyzed the distribution of myofiber sizes present in the diaphragm. For each myofiber type, LLC cancer cells induced a shift towards smaller sizes, which was rescued by rFibcd1 (Fig. 4d–g).
The capacity of rFibcd1 to limit myofiber atrophy in the diaphragm of cancer-bearing mice arises via its local action in attenuating cachectic changes in the diaphragm muscle. Systemic effects of rFibcd1 on body wasting and/or on cancer cells are unlikely given that rFibcd1 is injected locally in the peritoneal cavity. Indeed, body weight and tumor-free body mass declined in mice injected with LLC cancer cells but did not differ in response to intraperitoneal rFibcd1 injection (Fig. 4h–i), indicating that intraperitoneal rFibcd1 is active on the diaphragm, which is located in the peritoneal cavity, but not systemically. Consistently, LLC tumor mass was similar in mice treated with rFibcd1 versus controls (Fig. 4j). Altogether, these findings indicate that local injection of rFibcd1 resolves atrophy of diaphragm myofibers induced by cancer cachexia and that this is not due to an effect of rFibcd1 on tumor burden.
rFibcd1 rescues muscle transcriptional changes induced by LLC cancers
We next examined whether rFibcd1 rescues the molecular changes associated with cachexia-induced myofiber atrophy in the diaphragm. In parallel with the preservation of myofiber size (Fig. 4), RNA-sequencing revealed that LLC-induced cachexia is characterized by an increase in the expression of many genes whereas relatively few have reduced expression (Fig. 4k). However, rFibcd1 significantly mitigates LLC-induced transcriptional changes in the diaphragm muscle, compared to mock injections (Fig. 4k).
Further analysis of 247 significantly-regulated genes in LLC versus LLC + rFibcd1 (p < 0.05 and −0.5 > log2R > 0.5) revealed that several categories of genes involved in immunity and inflammation are overrepresented among LLC-upregulated genes (Fig. 4l), including the chemokine Cxcl13 (Fig. 4m) and receptors for inflammatory cachectic cytokines (Supplementary Data 2). Together, these findings indicate that cachectic factors produced by LLC cells, such as IL-6, LIF, and TNF-α96,102, induce inflammatory signaling in the diaphragm muscle and that intraperitoneal injection of rFibcd1 can impede such transcriptional changes (Fig. 4l).
Previous studies have shown that muscle proteolysis is a key mechanism responsible for myofiber atrophy induced by cancer12,24. In this respect, further analysis revealed that LLC cancer cells increase the expression of cathepsins in the diaphragm muscle, such as Ctss, Ctse, Ctsw, Ctsz, Ctsc, Ctsh, and Ctso (Fig. 4m and Supplementary Data 2). Because cathepsin are lysosomal proteolytic enzymes that have been previously implicated in myofiber atrophy103–106, they likely contribute to the proteolysis responsible for LLC cancer-induced muscle mass loss. However, rFibcd1 largely rescued the upregulation of cathepsin expression due to LLC cancers (Fig. 4m and Supplementary Data 2). Other proteolytic enzymes were also similarly regulated by LLC cancers and rFibcd1, such as Napsa, a member of the peptidase A1 family of aspartic proteases (Fig. 4m). Moreover, ubiquitin D (Ubd) expression was induced by LLC cancers but repressed by rFibcd1 (Supplementary Data 2) and may sustain proteolysis via the ubiquitin-proteasome system. Lastly, ubiquitin ligases were also regulated and are known to have important roles in muscle proteolysis during wasting24,103,107,108. Interestingly, some of them were upregulated in the diaphragm of mice with LLC cancers but this was rescued by rFibcd1 injection. These included Hgs and Syvn1 (Supplementary Data 2), which were previously shown to negatively regulate myofiber size60. However, LLC cancers did not significantly induce other ubiquitin ligases involved in myofiber atrophy24,103,107,108, such as Fbxo32/Atrogin-1 and Trim63/MuRF1 (Supplementary Data 2). Although relatively few genes were downregulated in response to LLC cancers, there were some that have been previously associated with myofiber hypertrophy, such as Pparg1a/PGC1a109, which was downregulated in LLC but not in LLC + rFibcd1 versus control (Fig. 4m and Supplementary Data 2).
Altogether, these findings indicate that rFibcd1 hinders some of the molecular changes associated with cancer cachexia in the diaphragm, including expression of genes already implicated in myofiber atrophy via their roles in inflammation, proteolysis, and other processes.
A patient-derived melanoma xenograft induces progressive atrophy of diaphragm myofibers
LLC cancer-induced cachexia is an established disease model that has led to many insights into the mechanisms of muscle wasting in cancer60,96,97. However, there is growing appreciation that patient-derived orthotopic cancer xenografts provide cachexia models that more closely mimic disease progression in humans97,110. To this purpose, we have identified a cachexia-inducing (“cachectic”) orthotopic patient-derived melanoma xenograft from the Childhood Solid Tumor Network collection established at St. Jude Children’s Research Hospital111–115. Specifically, we have established a model of cancer cachexia induced by a patient-derived melanoma xenograft (MAST360B/SJMEL030083_X2) and compared it to mice bearing a control melanoma xenograft that does not induce cachexia (MAST552A/SJMEL031086_X1; “non-cachectic”).
Compared to the commonly used LLC model of cancer-induced cachexia (Fig. 4), the melanoma model (MAST360B) used here induces severe muscle mass loss, i.e. ~25% versus ~10% loss found with LLC (Supplementary Fig. 5a). The body weight loss induced by this cachectic melanoma xenograft is characterized by a decline in the mass of the white adipose tissue, liver, pancreas, ovaries, heart, and skeletal muscles (i.e. soleus, tibialis anterior, gastrocnemius, diaphragm), (Supplementary Fig. 5b).
To better define how cachexia induced by this melanoma xenograft impacts the diaphragm, we have employed histological and transcriptional analyses to follow the progressive development of myofiber atrophy in the diaphragm muscle. There was no significant change in myofiber size at 2 weeks (Fig. 5a, d) and 4 weeks (Fig. 5e–h) post tumor implantation. However, myofiber atrophy was observed at week 6 (Fig. 5i–l) and further developed by week 8 from tumor injection (Fig. 5m–p).
Analysis of gene expression changes indicates that diaphragm atrophy associates with a set of 1033 genes (Fig. 5q) and that upregulated gene categories include secreted/immune proteins and inflammatory pathways (Fig. 5r), whereas relatively few genes were downregulated (Fig. 5s). Similar transcriptional changes were also found to occur in the tibialis anterior and soleus muscles (Supplementary Fig. 5c, d and Supplementary Data 4).
Altogether, these studies identify myofiber atrophy and transcriptional upregulation of inflammatory genes as components of diaphragm cachexia induced by pediatric melanoma xenografts.
rFibcd1 partially rescues diaphragm myofiber atrophy induced by a patient-derived melanoma xenograft
On this basis, we next tested whether rFibcd1 impedes diaphragm myofiber atrophy induced by a cachectic melanoma xenograft (MAST360B/SJMEL030083_X2), compared to a control melanoma that does not induce muscle wasting (MAST552A/SJMEL031086_X1).
For these experiments, ∼106 pediatric melanoma xenograft cells were injected subcutaneously in the flank and allowed to grow for ∼7 weeks. To test the efficacy of rFibcd1, 3 intraperitoneal injections (every other day, with 3 mg/kg of rFibcd1 in PBS with 1% BSA) were done in the last week of xenograft growth before euthanasia in half of the mice carrying xenografts whereas the other half received mock injections (PBS with 1% BSA).
By examining the size of myofibers in the diaphragm muscle of these mice, we found that the cachectic melanoma induces significant atrophy, as indicated by the average Feret’s minimal diameter, compared to mice injected with a control non-cachectic melanoma. Importantly, all myofiber types (1, 2a, 2x/2b) were affected, indicating the cachectic factors released by this melanoma have the general capacity to induce wasting (Fig. 6a). However, rFibcd1 injection significantly reduced the atrophy induced by cancer cachexia in type 1 and 2a myofibers, whereas smaller effects were seen for type 2b myofibers (Fig. 6a). Similar results were found by examining the average Feret’s minimal diameter values normalized to control (Fig. 6b). These changes in myofiber size were not due to a variation in the percentage of myofiber types present in the diaphragm (Fig. 6c).
On this basis, we next examined the relative frequencies of myofibers in the diaphragm muscle. Analysis of type 1 (Fig. 6d), type 2a (Fig. 6e), and type 2x/2b (Fig. 6f) revealed that the cachectic melanoma shifts the distribution of myofiber sizes towards lower values compared to a control non-cachectic melanoma (Fig. 6g). However, rFibcd1 partially reinstated myofiber sizes, in particular for type 2a myofibers (Fig. 6a–g). Considering that type 2a myofibers are the most abundant in the diaphragm muscle (~60% of all myofibers, Fig. 6c) and are also abundant (~50%) in the diaphragm in humans116,117, these findings suggest that rFibcd1 may provide a significant means for preserving myofiber size in the diaphragm of cancer patients.
Further analyses revealed that the anti-cachectic effects of intraperitoneal injections of rFibcd1 on the diaphragm muscle were not due to a systemic decrease in cancer growth and body wasting but were rather due to local effects on the diaphragm muscle (Fig. 6h–j). Specifically, body weight significantly decreased in mice that carried the MAST360B/SJMEL030083_X2 cachectic melanoma compared to mice injected with the MAST552A/SJMEL031086_X1 non-cachectic melanoma (Fig. 6h). However, body weight equally declined in mice that carried the MAST360B/SJMEL030083_X2 cachectic melanoma and that received either rFibcd1 or mock intraperitoneal injections (Fig. 6h). The same conclusions were reached also via the analysis of the tumor-free body mass (Fig. 6i). Similarly, intraperitoneal injection of rFibcd1 does not significantly impact the weight of the tibialis anterior, a hindlimb muscle (Supplementary Fig. 6). Moreover, intraperitoneal rFibcd1 injection did not impact tumor burden (Fig. 6j). Altogether, these findings indicate that reduction in cancer-induced atrophy of diaphragm myofibers is not due to systemic effects of intraperitoneal injection of rFibcd1 on body wasting and tumor growth. Lastly, circulating inflammatory cytokines were not significantly modulated by rFibcd1 (Fig. 6k and Supplementary Fig. 7), suggesting that the capacity of rFibcd1 to decrease cancer-induced atrophy of diaphragm myofibers primarily results from its action on muscle cells.
rFibcd1 rescues muscle transcriptional changes induced by cachectic melanomas
Because rFibcd1 rescues myofiber atrophy induced by patient-derived xenografts of cachectic melanomas (Fig. 6), we next examined whether rFibcd1 rescues the muscle transcriptional changes associated with myofiber atrophy in this model. RNA-seq revealed that rFibcd1 regulates the expression of several genes, some of which are modulated also in cachectic versus non-cachectic melanomas. Altogether, as observed for transcriptional changes due to LLC cancers (Fig. 5), treatment with rFibcd1 reduces the magnitude of gene expression changes induced in the diaphragm muscle in response to cachectic versus non-cachectic melanomas (Fig. 7a).
To further examine the impact of rFibcd1 on muscle cachectic changes, we examined the GO term categories that are enriched in genes that are significantly regulated in the muscle of mice with cachectic melanomas but not in the muscle of mice with cachectic melanomas upon rFibcd1 treatment (Fig. 7b and Supplementary Data 5). Examples of genes upregulated by rFibcd1 treatment (Fig. 7c) include Capza1, a capping protein necessary for the maintenance of thin filaments in vertebrate skeletal muscle118, and troponin Tnni1, which may help preserve skeletal muscle contractile functions119. Expression of Arrdc2, a gene previously implicated in muscle atrophy120, increases in response to cachectic melanoma but this is partially prevented by rFibcd1. Likewise, rFibcd1 impedes the cachexia-mediated upregulation of: Ddit4/REDD1, a repressor of mTOR signaling and mediator of muscle wasting121–123; the secretoglobin Scgb3a1, which is induced by cachexia124; the skeletal-muscle specific kelch-like protein Klhl38, a substrate-specific adapter for cullin E3 ubiquitination implicated in muscle wasting125,126; the transcription factor Klf15, a direct target of glucocorticoid signaling that like Ddit4/REDD1 inhibits mTOR signaling and induces muscle wasting123,127,128; and the transcription factor Zbtb16, which is induced in brown adipose tissue and skeletal muscle during thermogenesis129, which is stimulated by cachexia130–132. Together, these findings indicate that intraperitoneal injection of rFibcd1 can impede some of the transcriptional changes associated with melanoma-induced cachexia (Fig. 7).
Because of its key role in respiration, diaphragm function is an important determinant of overall exercise capacity133–135. On this basis, we next used treadmill tests136,137 to determine whether i.p. injection of rFibcd1 targeting the diaphragm improves motor function in mice with cachexia. To this purpose, we compared mice with either cachectic or non-cachectic orthotopic melanoma xenografts, and which received 3 i.p. injections of either rFibcd1 or mock (BSA) a week before testing. The total running time, the maximum and average speed, and the total distance run were lower in mice implanted with cachectic versus non-cachectic melanoma xenografts (Fig. 7d). The treadmill capacity of rFibcd1-treated cachectic mice trended towards improvement compared to that of mock-treated cachectic mice but this difference did not reach statistical significance. However, cachectic mice treated with rFibcd1 have a treadmill capacity that is also not statistically different from that of non-cachectic mice (Fig. 7d), presumably because of the capacity of rFibcd1 to attenuate cancer-induced transcriptional changes and myofiber atrophy in the diaphragm (Figs. 6–7).
Discussion
Over the past decades, many studies have deciphered the signaling mechanisms responsible for skeletal muscle wasting, thereby highlighting several potential therapeutic targets12,24,138. However, despite increased understanding of the mechanisms involved and extensive industry efforts, it has proven difficult to develop interventions for muscle atrophy, for which there is an unmet medical need.
A promising avenue for translational applications in this field is provided by myokines, some of which are endogenous regulators of myofiber size36,40,51–53,57,58. In this study, we have identified evolutionary-conserved myokines that regulate myofiber size (Fig. 1). In particular, we have studied the mechanism of action and potential therapeutic use of one of them, Fibcd1. Similar to another myokine that preserves myofiber size, Irisin/FNDC540,139, secreted Fibcd1 is generated by the proteolytic cleavage of a transmembrane version (Fig. 2) and is similarly detected in the human plasma (Supplementary Fig. 8). Local injection of recombinant secreted Fibcd1 attenuates myofiber atrophy induced by cancer cachexia in the diaphragm muscle (Figs. 2–8). On this basis, recombinant Fibcd1 (rFibcd1) may be used as a therapeutic agent to impede or to improve recovery from muscle wasting. For example, intraperitoneal injection into the abdominal cavity140 may provide an effective administration route for targeting the wasting of the diaphragm, a key muscle which is necessary for respiration and that is located between the abdominal and thoracic cavities. Such intraperitoneal application of rFibcd1 to preserve the size and function of diaphragm myofibers could improve the prognosis of patients with cancer cachexia given that wasting of the diaphragm is a key determinant of mortality in these patients11,98.
We have found that rFibcd1 preserves myofiber size via ERK signaling (Fig. 2), consistent with previous studies that have demonstrated a key role for ERK in promoting protein synthesis and in maintaining skeletal muscle mass and function in mice61–64. Interestingly, another secreted factor (FGF19) has also been previously reported to preserve myofiber size via ERK signaling58. However, because ERK also promotes cell proliferation87, a possible side effect of rFibcd1 treatments may consist in the promotion of tumor growth. To test this hypothesis, we have examined the response of cancer cells to rFibcd1 and found that rFibcd1 does not induce ERK activity in many cancer cells, different from myotubes (Fig. 3). This selectivity for muscle cells depends at least in part on expression in muscle cells of Itgα2b integrin, which is needed for the optimal response to rFibcd1 (Fig. 3), whereas Itgα2b is not expressed by many cancers (Supplementary Fig. 4). However, a cancer cell line displayed high Itgα2b expression and higher P-Erk levels in response to rFibcd1 (Fig. 3), suggesting that Itgα2b and/or alternative receptors may also transduce rFibcd1 signaling in certain cancer cells. Nonetheless, intraperitoneal injections of rFibcd1 did not increase tumor growth in vivo, as estimated in experiments with melanoma and LLC cancers (Figs. 4, 6). Together, these studies suggest that certain cancers may not respond to rFibcd1, and that intraperitoneal rFibcd1 may prove to be a safe therapeutic in such contexts, given its capacity to promote ERK signaling in diaphragm myofibers but not in cancer cells. These findings appear to be of particular interest considering that the cancer cell lines and tumor types here used are highly metastatic to the lungs89–92 and that metastatic capacity is strongly associated with the induction of muscle wasting10,141. On this basis, rFibcd1-based treatments may benefit cancer patients that develop respiratory dysfunction due to lung metastases and to concurrent cancer-induced wasting of the diaphragm.
Similar to Fibcd1, our findings and previous studies indicate that ERK signaling in muscle cells is necessary to preserve myofiber size in mice. Specifically, ERK signaling is necessary for the maintenance of skeletal muscle mass63 and its inhibition prevents IGF-I-induced myofiber hypertrophy64. Moreover, ERK has been shown to be necessary to maintain adult myofiber size and their neuromuscular junctions in mice58,61,62. Consistently, our screen for myokines that regulate myofiber growth in Drosophila (Fig. 1) has found that muscle-restricted interventions that are known to promote ERK signaling induce myofiber hypertrophy (Fig. 1f, g). For example, overexpression of Pvf1 (homologous to PDGF/VEGF) induces myofiber hypertrophy, whereas overexpression of argos, an antagonist of EGF Receptor signaling, induces atrophy (Fig. 1f, g).
In addition to being necessary for the maintenance of myofiber size58,61,62, chronic activation of Erk signaling in skeletal muscle was found to induce a switch from fast-twitch to slow-twitch myofibers, which resulted in enhanced metabolic capacity and fatigue resistance of skeletal muscles and reduced the severity of muscular dystrophy in mice142. Consistent with these muscle protective functions of Erk signaling, its phosphorylation status (i.e. activity) was found to increase in myofibers upon exercise143–146. However, Erk phosphorylation was also reported to increase during cachexia in muscle147. Although the significance of this contrasting regulation is unclear, Erk activity might be induced in both conditions in response to cytokine signaling, and act as a compensatory mechanism to cope with the stress and tissue damage that occurs with both exercise148 and cachexia149. On this basis, Erk induction might contribute to an adaptive response to maintain muscle homeostasis.
This and previous studies reporting a protective role of Erk signaling in preserving myofiber size are in apparent contradiction with other studies that have found that systemic administration of MEK/ERK inhibitors in cachectic mice can cure muscle wasting150. However, such anti-wasting effect of MEK/ERK inhibitors seem to stem primarily from inhibition of ERK signaling in cancer cells rather than muscle105,106. Specifically, MEK/ERK inhibitors were found to reduce the expression of cachectic cytokines produced by cancer cells105,106, independently from reduction in cancer growth, which can also occur in response to administration of MEK/ERK inhibitors105,106. In particular, MEK/ERK inhibitors were found to reduce the circulating levels of IL-6150,151, which is a cachectic cytokine produced by cancer cells and key for the induction of muscle wasting114,115. Therefore, inhibition of ERK signaling in cancer cells likely reduces muscle wasting by reducing cancer growth and/or cachectic cytokine production114,115,152.
On the other hand, ERK signaling in skeletal muscle is known to limit myofiber atrophy via the capacity of ERK to phosphorylate and inactivate the atrophy-inducing kinase GSK3β81,82, and via ERK-mediated activation of MNK1/2-eIF4E and the consequent promotion of protein synthesis81,83,84. Moreover, in addition to general roles of ERK signaling in preserving muscle mass and function58,61–64, ERK signaling has been found to promote protein synthesis and preserve the function of the diaphragm81,153, indicating that ERK signaling is indeed protective for this key skeletal muscle. Altogether, rFibcd1-mediated promotion of ERK signaling in the diaphragm muscle without concomitant induction of ERK in cancer cells appears as an appropriate strategy to contrast myofiber atrophy.
Interestingly, rFibcd1 also activates ERK in control conditions but this does not lead to myotube hypertrophy. Possibly, there are limitations (independent from Erk signaling) that impede additional growth in normal conditions. In agreement with our findings, previous studies have shown that Erk signaling is primarily needed for the maintenance of myofiber size rather than for the induction of myofiber hypertrophy58,61–64.
In addition to modulating ERK signaling (Fig. 3), we have found that rFibcd1 reduces the expression of inflammatory genes (Fig. 4) and myofiber atrophy (Figs. 4 and 6) in the diaphragm skeletal muscle. Consistent with a role of Fibcd1 in reducing tissue inflammation, recent studies have found that gut-specific Fibcd1 overexpression reduces intestinal inflammation76,154 and impedes weight loss induced by chemotherapy in mice154. Taken together, our study and these recent publications suggest that Fibcd1 reduces tissue inflammation, which is a major driver of cancer-induced muscle wasting24. However, paradoxically, high FIBCD1 expression in cancer cells has been found to correlate with poor prognosis and survival in patients with gastric and liver cancer155,156. A possible explanation for this dichotomy is that FIBCD1 expression by cancer cells impedes local inflammatory responses and hence allows cancer immune escape, which is a key mechanism of cancer progression and metastatic dissemination157.
Although many studies have investigated the mechanisms responsible for cachexia in the context of cancer types that are prevalent in adults, relatively little is known on the mechanisms and role of cachexia in pediatric cancer patients158. In this study, we have established a model of cancer cachexia induced by a patient-derived orthotopic pediatric melanoma xenograft. We propose that this model may provide a suitable setting for testing therapeutic interventions and to extend the portfolio of tools available for basic science studies on cachexia.
In addition to cancer cachexia, muscle wasting is a common issue that occurs with aging and other common diseases such as diabetes, kidney failure, neuromuscular disorders, and infections24,159. In particular, inflammatory conditions such as chronic obstructive pulmonary disease (COPD) and lung infections induce muscle atrophy and are lethal because of the synergistic decline in the function of the lung tissue and wasting of the diaphragm160,161, which also occurs during normal aging162–164. Therefore, treatment with rFibcd1 may help preserve pulmonary function during aging and in the course of other illnesses that compromise diaphragm function165, in conjunction with inspiratory muscle training19–23 and yet-to-develop pharmaceutical treatments.
In summary, our study indicates that Fibcd1 may help reinstate myofiber size in the diaphragm muscle (Fig. 8), which is a key muscle impacted by cancer cachexia.
Methods
Drosophila larval screening and body wall skeletal muscle analysis
Flies were maintained at 25 °C with 60% humidity in tubes containing cornmeal/soy flour/yeast fly food. Fly stocks were obtained from either the Bloomington Drosophila Stock Center (BDSC), The National Institute of Genetics Fly Stocks (NIG-Fly), or the Vienna Drosophila Resource Center (VDRC) and are listed in Supplementary Data 1 alongside the full results of larval screening for regulators of myofiber size.
To define the list of Drosophila stocks for transgenic RNAi and overexpression of evolutionary conserved myokines, the following procedures were used: first, a list of 788 predicted secreted factors (based on the GLAD, Gene List Annotation for Drosophila166) was filtered to retain only 274 Drosophila secreted factors with sufficient homology to humans, i.e. with a score ≥2 as defined by DIOPT167; second, the list was further filtered to retain only 111 Drosophila secreted factors with sufficient skeletal muscle expression, as defined by RNA-seq FPKM ≥ 4; lastly, the function of these evolutionary-conserved muscle-secreted factors was screened with 508 stocks for RNAi and overexpression.
For the screen, we used similar procedures as we recently used60,66. Specifically, virgin Mef2-Gal4 females (10 flies for each cross) were mated with males (5 flies for each cross) of each RNAi or overexpression stock and transferred to new food tubes every 3 days to avoid overcrowding. Breeders were maintained at 25 °C. The sizes of 3rd instar larvae were assessed qualitatively as either bigger or smaller than control larvae. As secondary validation, skeletal muscles from selected candidates were analyzed by dissecting larvae into filets and by exposing the ventral lateral muscles VL3 and VL4 (each consisting of a single myofiber) from abdominal segments 2-4, which were then fixed for 30 min with 4% EM-grade PFA in PBS without Ca2+ and Mg2+ 59. Following washes, larval body wall muscles (typically from 10 larvae) were stained with DAPI (1:1000) and imaged to detect the endogenous fluorescence of a Mhc-GFP fusion protein. Subsequently, the total area, width, and length of VL3 + VL4 myofibers was quantified with the Zeiss Zen software. All schemes were drawn with Biorender.
Production of recombinant mouse Fibcd1
The ~38-kDa C-terminal part of mouse Fibcd1 (consisting of 282 amino acids, approximately corresponding to the secreted Fibcd1 fragment retrieved from the cell culture medium, as shown in Fig. 2) was cloned into the pAcGP67-B vector with BamHI and BglII. Expression of the C-terminal part of mouse Fibcd1 was achieved with the Bac-to-Bac Baculovirus Expression System (Invitrogen) and the recombinant protein (rFibcd1) retrieved in PBS (GIBCO, #10010023) with 1% BSA. The identity of purified rFibcd1 was confirmed by mass-spectrometry.
C2C12 culture, myotube siRNA transfection, and rFibcd1 treatment
C2C12 mouse muscle cells (ATCC, #CRL-1772) were cultured at 37 °C with 5% CO2 in DMEM (high glucose DMEM, with Glutamax, GIBCO, #10566016) containing 10% fetal bovine serum (GIBCO, #10437-028), and 1% penicillin/streptomycin (10,000 U/mL, GIBCO, #15140122). C2C12 cells were maintained as myoblasts with media containing 10% fetal bovine serum and switched to 2% horse serum-containing media (GIBCO, #26050070) to induce differentiation into myotubes when near confluence. 4 days after differentiation, myotube-enriched cultures were generated by adding media containing 4 mg/mL of Cytosine b-D-arabinofuranoside (Ara-C, Sigma, #C1768) for a further 2 days at which point the remaining myotubes were transfected with siRNAs. To this purpose, myotubes were transfected with 50 mM siRNAs targeting the specified gene or with control non-targeting (NT) siRNAs, by using a ratio of 2 mL Lipofectamine 2000 (Invitrogen, #11668027) to 50 pmol of siRNA in OptiMEM (GIBCO, #31985062), as previously done60. Myotube size was assayed 2 days after transfection. The following ON-TARGET plus siRNA reagents (Dharmacon) were used: mouse Fibcd1 (#L-0581480-01), non-targeting (NT) control (#D-001810-10), Itga2b (#L-046584-01), Wnt9a (#L-0581480-01), Tgfbi (#L-040939-03), Bmp1(#L-057019-01), and Sparc (#L-043364-00).
For concurrent treatment with rFibcd1, myotubes were then treated for 24 h with either serum-free media containing 100 ng/mL rFibcd1 or control serum-free media (containing the same amount of BSA as the medium with rFibcd1). Myotubes were then fixed and stained for myosin heavy chain (MF20 clone, eBioscience, #14-6503-82; used at 1:150) and myotube diameters analyzed by ImageJ, as explained in detail below. For the analysis of myoblast fusion shown in Supplementary Fig. 2, siRNAs were transfected into myoblasts following the procedures explained above.
Nutrient-starvation experiments
For nutrient starvation experiments, C2C12 myotubes were transfected as indicated above with Fibcd1 or NT siRNAs. After 48 h, the normal cell culture medium (10% FBS in DMEM-high glucose) was replaced with culture medium diluted 1:10 in Dulbecco’s PBS for 8 h and 24h168.
Pharmacological inhibition of ERK
C2C12 myotubes were transfected individually with Fibcd1 siRNA or NT siRNA for 48 h, as explained in detail above. The cells were incubated in serum-free media overnight and they were then treated at the same time with either control serum-free media or serum-free media containing rFibcd1 at 100 ng/mL, and/or Pyrazolylpyrrole (pharmacological inhibitor of ERK; Santa Cruz, CAS#933786-58-4)35,85,86 at 2.5 ng/mL, for further 24 h. Cells were then fixed and stained with anti-Myosin Heavy Chain antibodies (MF20 clone, eBioscience, #14-6503-82; used at 1:150) and myotube size determined with ImageJ.
C2C12 myotube size analysis
To determine the myotube size, cultures of differentiated C2C12 myotubes were fixed by adding an equal volume of 4% PFA (paraformaldehyde, Electron Microscopy Sciences, #15710) to the medium for 10 min. Cells were then washed with PBS and blocked for 1 h in blocking buffer containing PBS with 0.1% Triton X-100 and 2% BSA, and then incubated with anti-myosin heavy chain antibodies (MF20 clone, eBioscience, #14-6503-82; used at 1:150) overnight at 4 °C. The cells were then stained with a fluorophore-conjugated anti-mouse secondary antibody to detect myosin heavy chain and with DAPI (Roche, #10236276001; 1:1000) to visualize the myotube area and the nuclei respectively. The size of myotubes was measured by taking the average width value across a myotube at three separate points along it. Typically, ~100 myotubes were measured for each group, as previously done60.
Induction of myotube atrophy via cachectic cytokines
For the induction of myotube atrophy via cachectic cytokines, C2C12 myotubes were incubated in serum-free media for 6 h and then cachectic cytokines and rFibcd1 were added at the same time for a further 2 days. The cytokines used were IL-6 (recombinant mouse IL-6, R&D Systems, #406-ML-025) at 20 ng/mL80, TNFα (recombinant mouse TNFα, R&D Systems, #410-ML-025) at 100 ng/mL79, and LIF (recombinant mouse LIF, R&D Systems, #8878-lf-025) at 20 ng/mL78. Recombinant Fibcd1 (rFibcd1) was added to serum-free media at 10 ng/mL and 100 ng/mL, as indicated.
Culture of cancer cells
Cancer cells tested in Fig. 3 and Supplementary Fig. 3b are the following: the mouse B16F0 and B16F10 melanoma cells169 (ATCC #CRL-6322 and #CRL-6475); the human MDA-MB-231 breast cancer cells170 (ATCC #CRM-HTB-26); the mouse Ep5171, Ep5ExTu171 (Labelle lab collection), E0771172 (CH3 BioSystems #94A001), 67NR173 (F. Miller lab collection, Karmanos Cancer Institute), and 4T164,65 (ATCC #CRL-2539) breast cancer cells; the human LS180 colorectal adenocarcinoma cells174 (ATCC #CL-187); the mouse MC38 colorectal adenocarcinoma cells175 (D. Vignali lab collection, University of Pittsburgh); the human U-2OS-Luc/YFP176, 143B-Luc/YFP177, and Saos-292,178 osteosarcoma cells (ATCC #HTB-96, #CRL-8303, and #HTB-85); and the mouse Lewis lung carcinoma cells (LLC)89 (ATCC, #CRL-1642).
The following culture media were used: RPMI-1640 (ATCC, #30-2001) for B16F0, B16F10, 67NR, and E0771; DMEM (ATCC, #30-2002) for MDA-MB-231, Ep5, Ep5ExTu, LS180, MC38, and LLC; EMEM (ATCC, #30-2003) for 143B-Luc/YFP; and McCoy’s 5 A (ATCC, #30-2007) for U-2OS-Luc/YFP, 143B-Luc/YFP, and Saos-2. All culture media included 10% FCS (ATCC, #30-2020) with 1% penicillin/streptomycin (GIBCO, #15140122) apart for Saos-2 cells, which were cultured in 15% FCS, and for E0771 cells, which were cultured with 10% iron-supplemented FCS (GE Healthcare, HyClone, #SH30072.04HI). All cells were cultured at 37 °C with 5% CO2.
All cell lines were screened regularly to ensure the absence of mycoplasma (universal mycoplasma detection kit, ATCC #30-1012 K) and authenticated based on their morphology and behavior. Human cell lines were also authenticated via STR (short tandem repeat) profiling.
Treatment of cancer cells with rFibcd1
Cancer cells were incubated in serum-free media overnight and they were then treated with rFibcd1 at 10 ng/mL and 100 ng/mL for 30 and 120 min when they were ~50% confluent. The cell lysate was then collected with NP40 buffer and used for western blotting.
HEK293 cell culture and transfection
Human embryonic kidney cells (HEK293T cells; ATCC, #CRL-3216) were cultured at 37 °C with 5% CO2 in DMEM (high glucose DMEM, with Glutamax, GIBCO, #10566016) containing 10% fetal bovine serum (GIBCO, #10437-028), and penicillin/streptomycin (10,000 U/mL, GIBCO, #15140122). HEK293 cells were transfected with either empty vector (EV) or vector containing C-terminal FLAG tagged full length (FL) or short (SH) Fibcd1. 2 days after transfection, growth media was replaced with serum-free media for an additional 24 h. The media was then collected alongside the cell lysate using NP40 buffer and the samples run on SDS-PAGE and analyzed by western blot with anti-FLAG antibodies (Sigma clone M2, #A2220).
Western blotting
For cell culture experiments, the cells were homogenized in 100 μL of NP40 cell lysis buffer (Invitrogen, #FNN0021). Subsequently, the cell samples were sonicated for 10 sec at 30% of frequency, and the protein extracts were quantified by using Bradford assay (Bio-Rad Protein assay dye reagent concentrate, #5000006). Protein samples were prepared by addition of SDS-Blue loading buffer (Cell Signaling, #7722) and DTT (dithiothreitol; to a final concentration of 0.1 M, Cell Signaling, CST#1425 S) and heating at 95 °C for 5 min. Samples were then run on 4-20% gradient SDS-PAGE gels (Mini-PROTEAN TGX Pre-cast gels, Bio-Rad, 4561096) alongside a molecular weight ladder (Precision Plus protein standard, Bio-Rad, #1610374) and transferred to PVDF membranes (Immobilon-P PVDF membrane, Millipore, #IPVH00010), which were blocked with either 5% milk powder or 5% BSA (according to manufacturer’s instructions) for 1 h.
Subsequently, the membranes were incubated overnight at 4 °C with the following primary antibodies (all used at 1:1000): mouse anti-phospho-p44/42 MAPK (Erk1/2; Thr202/Tyr204) (Cell Signaling, #9106), rabbit anti-phospho-p38 MAPK (Thr180/Tyr182) (Cell Signaling, #4511), rabbit anti-phospho-Smad2 (Ser465/467) (Cell Signaling, #8828), rabbit anti-phospho-Akt (Ser473; D9E) (Cell Signaling, #4060 S), rabbit anti-phospho-SAPK/JNK (Thr183/Tyr185; 81E11) (Cell Signaling, #4668 S), rabbit anti-α-Tubulin (11H10) (Cell Signaling, #2125), rabbit anti-SQSTM1/p62 (Cell Signaling, #5114), and mouse anti-Flag (M2) (Sigma, #F3165). After washing, the appropriate HRP-conjugated secondary antibodies (Cell Signaling #7074, #7076; used at 1:2000) were incubated at 4 °C for 2 h, washed again, and then probed with ECL reagents (Amersham ECL Western Blotting Detection Reagents, #RPN2209) to detect the protein of interest. Ponceau S (Sigma, #P7170) staining was also used to confirm even loading of protein samples. The Source Data file reports the full scan of all blots.
qRT-PCR
qRT-PCR was performed as previously described35. Total RNA from C2C12 myotubes was extracted by using Trizol (Ambion, #15596018). 500 ng of RNA was used for reverse transcription with the iScript cDNA synthesis kit (Bio-Rad, #1708840). qRT-PCR was done by using the IQ Sybr Green supermix (Bio-Rad, #170-8885) and the oligonucleotides reported in Supplementary Data 3. Ppia was used for normalization.
Mouse husbandry
All mice were housed in the Animal Resource Center at St. Jude Children’s Research Hospital and handled in accordance with a protocol (#563) approved by the St. Jude Children’s Research Hospital Institutional Animal Care and Use Committee (IACUC). Additional accreditation of the Animal Resource Center at St. Jude Children’s Research Hospital was provided by the Association for Assessment and Accreditation of Laboratory Animal Care (AAALAC). Mice were housed in a ventilated rodent-housing system with a controlled temperature (22-23 °C), 40% humidity, 12-hour light/dark cycle, and given free access to food and water. Humane endpoints were not exceeded in any experiment.
Mice that carry LLC (Lewis Lung Cancer) tumors
Male C57BL/6 J (The Jackson Laboratory, JAX#000664) mice were utilized at 4 months of age. 1×106 LLC cells were each injected into the right and left flank60,96,97 and tumors were allowed to grow up to ~3 weeks. Treatment with rFibcd1 began at day 16 after LLC tumor cell implantation. Specifically, mice were treated with three injections of recombinant Fibcd1 (rFibcd1) administrated intraperitoneally at 1 mg/kg of body weight or with 1%BSA in PBS on every other day for a week, at which time tumor-bearing mice were euthanized. Supplementary Fig. 9 reports a flow chart of the experimental design.
Melanoma xenograft-bearing mice
Female 2-month-old NCI Ath/nude mice were purchased from Charles River Laboratory. MAST360B/SJMEL030083_X2 and MAST552A/SJMEL031086_X1 cells were patient-derived melanoma cancer xenografts from the Childhood Solid Tumor Network collection at St. Jude Children’s Research Hospital111–115. 1.5×106 cells of each tumor stock were inoculated into the flank of nude mice. Treatment with rFibcd1 began at day 39 after implantation of MAST360B/SJMEL030083_X2 (“cachectic”, i.e. cachexia-inducing melanoma) and MAST552A/ SJMEL031086_X1 (“non-cachectic”, i.e. cachexia-non-inducing melanoma). Mice were treated with three injections of recombinant Fibcd1 (rFibcd1) or with 1%BSA in PBS administrated intraperitoneally at 3 mg/kg of body weight on every other day for a week, after which tumor-bearing mice were euthanized. Supplementary Fig. 10 reports a flow chart of the experimental design.
Tissue collection
For tissue collection, mice were euthanized and the diaphragm muscle was dissected and isolated from tendons. Only the skeletal muscle portion of the dissected tissue was used for further analyses. Half of diaphragm muscle was frozen in liquid nitrogen-cooled isopentane (Sigma-Aldrich, #277258) and mounted for cryosectioning at a thickness of 10 µm whereas the other half was snap-frozen and stored at -80 °C until RNA extraction. The tumors were removed and weighed alongside.
Analysis of myofiber type, size, and number
Myofiber type analysis was done as previously described179,180. Unfixed slides holding the sections were incubated with blocking buffer (PBS with 2% BSA and 0.1% Triton-X100) for 1 h before incubation with primary antibodies (used at 1:150) overnight at 4 °C. The primary antibodies used were mouse IgG2b anti-myosin heavy chain type I (DSHB, #BA-F8), mouse IgG1 anti-myosin heavy chain type IIA (DSHB, #SC-71), and rat anti-laminin α2 (4H8-2; Santa Cruz, #sc-59854). The sections were then washed and incubated with secondary antibodies (1:200) which were anti-mouse IgM Alexa 555 (Life Technologies, A21426), anti-mouse IgG1 Alexa488 (Life Technologies, #A21121), and anti-rat IgG Alexa647 (Life Technologies, #A21247). Diaphragm sections were imaged on a Nikon C2 confocal microscope with a 10x objective and the myofiber types and sizes were analyzed in an automated manner with the Nikon Elements software by using the inverse threshold of laminin α2 immunostaining to determine myofiber boundaries. The myosin heavy chain staining was used to classify type I (red), type IIA (green), and presumed type IIX/IIB myofibers (black, i.e. that were not stained for MHC I or IIA). After myofibers were classified by type, myofiber size was estimated in an automated manner by the Nikon Elements software via the Feret’s minimal diameter, a geometrical parameter for the analysis of unevenly shaped or cut objects179. For the quantification of the number of myofibers, all fibers in the diaphragm cross-sections were counted based on the myofiber borders identified by laminin α2 immunostaining.
Analysis of motor function with the treadmill
Mice were introduced onto the treadmill belt for acclimatization before the actual test (motor speed set to zero, for 5 min). Subsequently, the motor speed was set to 9 m/min in a flat position, and the speed was increased by 1 m/min every 2 min until the tested mouse was exhausted. Exhaustion was defined as the inability of the animal to run on the treadmill for 10 s. Instead of a shock stimulus, mice were prompted to run by using a tongue depressor, as previously done136,137,181. Running time and maximum speed were measured, whereas total running distance and average speed were calculated. Throughout this protocol, mice were assessed by an investigator blinded to the experimental conditions of the mice examined. No mice were excluded from the analysis.
RNA-seq
Diaphragm muscles were homogenized in Trizol and RNA extracted by isopropanol precipitation from the aqueous phase. RNA sequencing libraries for each sample were prepared with 1 μg total RNA by using the Illumina TruSeq RNA Sample Prep v2 Kit per the manufacturer’s instructions, and sequencing was completed on the Illumina NovaSeq 6000. The 100-bp paired-end reads were trimmed, filtered against quality (Phred-like Q20 or greater) and length (50-bp or longer), and aligned to a mouse reference sequence GRCm38 (UCSC mm10) by using CLC Genomics Workbench v12.0.1 (Qiagen). For gene expression comparisons, we obtained the TPM (transcript per million) counts from the RNA-Seq Analysis tool. The differential gene expression analysis was performed by using the non-parametric ANOVA using the Kruskal-Wallis and Dunn’s tests on log-transformed TPM values between biological replicates of experimental groups, implemented in Partek Genomics Suite v7.0 software (Partek Inc.).
The average TPM counts from each experimental group for significant genes (defined as indicated in the corresponding figure legends) were further clustered in a heatmap using z-score normalization and similarity measure by correlation. Specifically, for the heatmap in Fig. 4, the cutoff for significance is p < 0.05 and log2R > 0.585 (50% change) between these sets, and genes with significant call for at least one of the comparisons were included in the heatmap. The heatmaps in Fig. 5 includes all genes with significance in at least one of eight comparisons, with cutoffs of significance at p < 0.01 and log2R > 1. The heatmap in Supplementary Fig. 5 was generated following the same criteria as for Fig. 5. For the heatmap in Fig. 7, the cutoff of significance was set at p < 0.05 with log2R > 1 (one-fold change) for the comparison of CAC versus NCAC, and p < 0.05 with log2R > 0.585 (50% change) for the comparison of rFibcd1 versus mock treatment.
The RNA-seq data discussed in this publication has been deposited in the NCBI’s Gene Expression Omnibus and is accessible through GEO Series accession numbers GSE156815, GSE158581, and GSE183833.
Measurement of cytokine levels in the plasma of experimental mice
The plasma cytokine levels were measured by using the Milliplex Map mouse cytokine assay kit (Millipore, #MCYTOMAG-70K) as previously done182,183. In total 600 μL of blood was collected from the abdominal aorta of mice that carry melanoma xenografts by using 100 μL of 50 mM EDTA as an anti-coagulant and centrifuged for 20 min at 1,000 g. All reagents were brought to room temperature before use. Wash buffer, assay buffer, serum matrix, standard 6, quality controls 1 and 2, premixed beads, detection antibodies, and streptavidin-PE were prepared as recommended by the manufacturer. Plasma samples were diluted 1:4 by using the assay buffer. To create a homogeneous mixture, the premixed beads bottle was sonicated in water bath for 30 s and then vortexed for 1 min before use. For pre-wetting, 200 μL assay buffer was pipetted into each well, the plate was covered with sealer and then shaken at 70 g for 10 min. The fluid was removed by tapping the plate on a paper towel and by centrifuging it briefly at 1,200 g lying top down on a paper sheet in the centrifuge. A total of 25 μL of standards 1–6 and quality controls 1 and 2 were pipetted in duplicate into the appropriate wells and 25 μL of serum matrix was added. Next, 25 μL of diluted plasma samples and 25 μL of assay buffer was pipetted into the appropriate wells. Finally, the magnetic premixed beads were vortexed for 1 min and 25 μL was pipetted into each well. The plate was sealed, covered with aluminum foil and then shaken at 70 g for 16 h at 4 °C. After overnight incubation, the magnetic bead plates were washed 2 times by using assay buffer, as recommended by the manufacturer. Then, 25 μL of detection antibodies were added into each well, the plate was sealed and covered with aluminum foil and shaken at 70 g for 1 h. After that, 25 μL of streptavidin-phycoerythrin was added to each well containing the 25 μL of detection antibodies. The plate was again sealed, covered with foil and incubated with agitation for 30 min at room temperature. Subsequently, the plate was washed 2 times again. In 150 μL of assay buffer were added to all wells and shaken for 5 min to resuspend the beads. Lastly, the plate was read on a Luminex® 200TM apparatus. The analysis was done by the Luminex software by using the spline curve-fitting method for calculating cytokine/chemokines concentrations in samples.
Reporting summary
Further information on research design is available in the Nature Research Reporting Summary linked to this article.
Supplementary information
Acknowledgements
Fly stocks were provided by the VDRC, NIG-Fly, and Bloomington stock centers whereas the DSHB provided MHC antibodies. We thank Dr. Richard Heath and the Protein Production core, the Light Microscopy facility, and the Hartwell Center for Bioinformatics and Biotechnology at St. Jude Children’s Research Hospital. We further thank Åsa Karlström and the CIVIT at St. Jude Children’s Research Hospital for assistance with xenograft experiments. This work was supported primarily by a research grant to F.D. from The Hartwell Foundation (Individual Biomedical Research award). F.D. is supported also by the National Cancer Institute (P30CA021765-developmental funds) and the National Institute on Aging (R01AG055532 and R56AG63806). B.X. and Y.F. are supported by P30CA021765. M.L. is supported by the National Cancer Institute (R01CA245301). L.C.H. was supported by a Glenn/AFAR Postdoctoral Fellowship. Research at St. Jude Children’s Research Hospital is supported by the ALSAC. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Source data
Author contributions
F.A.G. did most of the cell culture and mouse experiments, with help from L.C.H. and A.S.; M.R. did the Drosophila RNAi screen; F.A.G., M.R., and L.C.H, analyzed data; Y.-D. W. analyzed RNA-seq data; B.X. and Y.F. provided support for other computational analyses; F.A.G. and G.Q. measured circulating cytokines; B.G. established and provided cancer xenografts; M.L. and R.W. provided expertise and tools for experiments with cancer cell lines; F.A.G. is the first author; M.R. and L.C.H. equally contributed as second authors; F.D. supervised the project and wrote the manuscript.
Peer review
Peer review information
Nature Communications thanks Ruben Artero, Alejandro Lucia and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.
Data availability
The RNA-seq data discussed in this publication have been deposited in the NCBI’s Gene Expression Omnibus and are publicly accessible through GEO Series accession numbers GSE156815, GSE158581, and GSE183833.
Additional primary data are available in Supplementary Data 1–5 and in the Source Data File.
Publicly-available datasets that have been interrogated in this study are the following and were used to retrieve RNA-seq data from pediatric cancers (ProteinPaint; https://proteinpaint.stjude.org/) and adult cancers (FireBrowse; http://firebrowse.org/viewGene.html?gene=ITGA2B), and for assessing circulating levels of Fibcd1 (Aging Plasma Proteome dataset; https://twc-stanford.shinyapps.io/aging_plasma_proteome/).
Statistics and Reproducibility. Data organization, scientific graphing and statistical analyses were performed with Microsoft Excel (version 14.7.3) and GraphPad Prism (version 6). The unpaired two-tailed Student’s t-test was used to compare the means of two independent groups to each other. One-way and two-way ANOVA with post hoc testing were used for multiple comparisons of more than two groups of normally distributed data. The “n” for each experiment can be found in the figure legends and represents independently generated samples for all experiments, including myotubes and cell culture samples for in vitro assays, and individual animals or tissues sourced from independent animals for in vivo experiments. Bar graphs present the mean ± SD. Throughout the figures, asterisks and ampersand symbols indicate the significance of P values: *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. A significant result was defined as P < 0.05. Representative micrographs are derived from the analysis of multiple muscles (>5) and cell culture results typically obtained from 2-3 experiments.
Competing interests
F.A.G., M.R., L.C.H., and F.D. are named co-inventors of a pending U.S. provisional patent application based in part on the research reported in this paper. The remaining authors declare no competing interests.
Footnotes
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
These authors contributed equally: Mamta Rai, Liam C. Hunt.
Supplementary information
The online version contains supplementary material available at 10.1038/s41467-022-30120-1.
References
- 1.Fearon K, et al. Definition and classification of cancer cachexia: an international consensus. Lancet Oncol. 2011;12:489–495. doi: 10.1016/S1470-2045(10)70218-7. [DOI] [PubMed] [Google Scholar]
- 2.Lu F, et al. Comparison of cachectic and non-cachectic sarcoma patients reveals an important role of Notch signaling in metastasis and myogenesis. Am. J. Cancer Res. 2019;9:1746–1756. [PMC free article] [PubMed] [Google Scholar]
- 3.Schmidt SF, Rohm M, Herzig S, Berriel Diaz M. Cancer cachexia: more than skeletal muscle wasting. Trends Cancer. 2018;4:849–860. doi: 10.1016/j.trecan.2018.10.001. [DOI] [PubMed] [Google Scholar]
- 4.Argiles JM, Busquets S, Stemmler B, Lopez-Soriano FJ. Cancer cachexia: understanding the molecular basis. Nat. Rev. Cancer. 2014;14:754–762. doi: 10.1038/nrc3829. [DOI] [PubMed] [Google Scholar]
- 5.Baracos VE, Martin L, Korc M, Guttridge DC, Fearon KCH. Cancer-associated cachexia. Nat. Rev. Dis. Prim. 2018;4:17105. doi: 10.1038/nrdp.2017.105. [DOI] [PubMed] [Google Scholar]
- 6.Fearon KC, Glass DJ, Guttridge DC. Cancer cachexia: mediators, signaling, and metabolic pathways. Cell Metab. 2012;16:153–166. doi: 10.1016/j.cmet.2012.06.011. [DOI] [PubMed] [Google Scholar]
- 7.Winbanks CE, et al. Smad7 gene delivery prevents muscle wasting associated with cancer cachexia in mice. Sci. Transl. Med. 2016;8:348ra398. doi: 10.1126/scitranslmed.aac4976. [DOI] [PubMed] [Google Scholar]
- 8.Johnston AJ, et al. Targeting of Fn14 prevents cancer-induced cachexia and prolongs survival. Cell. 2015;162:1365–1378. doi: 10.1016/j.cell.2015.08.031. [DOI] [PubMed] [Google Scholar]
- 9.Zhou X, et al. Reversal of cancer cachexia and muscle wasting by ActRIIB antagonism leads to prolonged survival. Cell. 2010;142:531–543. doi: 10.1016/j.cell.2010.07.011. [DOI] [PubMed] [Google Scholar]
- 10.Wang G, et al. Metastatic cancers promote cachexia through ZIP14 upregulation in skeletal muscle. Nat. Med. 2018;24:770–781. doi: 10.1038/s41591-018-0054-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Roberts BM, et al. Diaphragm and ventilatory dysfunction during cancer cachexia. FASEB J. 2013;27:2600–2610. doi: 10.1096/fj.12-222844. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Piccirillo R, Demontis F, Perrimon N, Goldberg AL. Mechanisms of muscle growth and atrophy in mammals and Drosophila. Dev. Dyn. 2014;243:201–215. doi: 10.1002/dvdy.24036. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Tisdale MJ. Reversing cachexia. Cell. 2010;142:511–512. doi: 10.1016/j.cell.2010.08.004. [DOI] [PubMed] [Google Scholar]
- 14.Kurk S, et al. Skeletal muscle mass loss and dose-limiting toxicities in metastatic colorectal cancer patients. J. Cachexia Sarcopenia Muscle. 2019;10:803–813. doi: 10.1002/jcsm.12436. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Florea VG, et al. The cardiac component of cardiac cachexia. Am. Heart J. 2002;144:45–50. doi: 10.1067/mhj.2002.123314. [DOI] [PubMed] [Google Scholar]
- 16.Florea VG, et al. Wasting of the left ventricle in patients with cardiac cachexia: a cardiovascular magnetic resonance study. Int J. Cardiol. 2004;97:15–20. doi: 10.1016/j.ijcard.2003.05.050. [DOI] [PubMed] [Google Scholar]
- 17.Greising SM, Ottenheijm CAC, O’Halloran KD, Barreiro E. Diaphragm plasticity in aging and disease: therapies for muscle weakness go from strength to strength. J. Appl Physiol. (1985) 2018;125:243–253. doi: 10.1152/japplphysiol.01059.2017. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Salazar-Degracia A, et al. Phenotypic and metabolic features of mouse diaphragm and gastrocnemius muscles in chronic lung carcinogenesis: influence of underlying emphysema. J. Transl. Med. 2016;14:244. doi: 10.1186/s12967-016-1003-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Beaumont M, Forget P, Couturaud F, Reychler G. Effects of inspiratory muscle training in COPD patients: a systematic review and meta-analysis. Clin. Respir. J. 2018;12:2178–2188. doi: 10.1111/crj.12905. [DOI] [PubMed] [Google Scholar]
- 20.Dres M, Goligher EC, Heunks LMA, Brochard LJ. Critical illness-associated diaphragm weakness. Intensive Care Med. 2017;43:1441–1452. doi: 10.1007/s00134-017-4928-4. [DOI] [PubMed] [Google Scholar]
- 21.Eidenberger M, Nowotny S. Inspiratory muscle training in patients with amyotrophic lateral sclerosis: a systematic review. NeuroRehabilitation. 2014;35:349–361. doi: 10.3233/NRE-141148. [DOI] [PubMed] [Google Scholar]
- 22.Palermo AE, Cahalin LP, Nash MS. A case for inspiratory muscle training in SCI: potential role as a preventative tool in infectious respiratory diseases like COVID-19. Spinal Cord. Ser. Cases. 2020;6:87. doi: 10.1038/s41394-020-00337-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Wang LY, et al. Inspiratory muscle training attenuates irradiation-induced diaphragm dysfunction. Am. J. Transl. Res. 2019;11:5599–5610. [PMC free article] [PubMed] [Google Scholar]
- 24.Bonaldo P, Sandri M. Cellular and molecular mechanisms of muscle atrophy. Dis. Models Mechanisms. 2013;6:25–39. doi: 10.1242/dmm.010389. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Tsoli M, Robertson G. Cancer cachexia: malignant inflammation, tumorkines, and metabolic mayhem. Trends Endocrinol. Metab.: TEM. 2013;24:174–183. doi: 10.1016/j.tem.2012.10.006. [DOI] [PubMed] [Google Scholar]
- 26.Argiles JM, Stemmler B, Lopez-Soriano FJ, Busquets S. Inter-tissue communication in cancer cachexia. Nat. Rev. Endocrinol. 2018;15:9–20. doi: 10.1038/s41574-018-0123-0. [DOI] [PubMed] [Google Scholar]
- 27.De Lerma Barbaro A. The complex liaison between cachexia and tumor burden (Review) Oncol. Rep. 2015;34:1635–1649. doi: 10.3892/or.2015.4164. [DOI] [PubMed] [Google Scholar]
- 28.Robert F, et al. Targeting protein synthesis in a Myc/mTOR-driven model of anorexia-cachexia syndrome delays its onset and prolongs survival. Cancer Res. 2012;72:747–756. doi: 10.1158/0008-5472.CAN-11-2739. [DOI] [PubMed] [Google Scholar]
- 29.Pillon NJ, Bilan PJ, Fink LN, Klip A. Cross-talk between skeletal muscle and immune cells: muscle-derived mediators and metabolic implications. Am. J. Physiol. Endocrinol. Metab. 2013;304:E453–E465. doi: 10.1152/ajpendo.00553.2012. [DOI] [PubMed] [Google Scholar]
- 30.VanderVeen BN, Murphy EA, Carson JA. The impact of immune cells on the skeletal muscle microenvironment during cancer cachexia. Front Physiol. 2020;11:1037. doi: 10.3389/fphys.2020.01037. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Douglas E, McMillan DC. Towards a simple objective framework for the investigation and treatment of cancer cachexia: the Glasgow Prognostic Score. Cancer Treat. Rev. 2014;40:685–691. doi: 10.1016/j.ctrv.2013.11.007. [DOI] [PubMed] [Google Scholar]
- 32.Deshmukh AS, Cox J, Jensen LJ, Meissner F, Mann M. Secretome analysis of lipid-induced insulin resistance in skeletal muscle cells by a combined experimental and bioinformatics workflow. J. Proteome Res. 2015;14:4885–4895. doi: 10.1021/acs.jproteome.5b00720. [DOI] [PubMed] [Google Scholar]
- 33.Safdar A., Tarnopolsky M. A. Exosomes as mediators of the systemic adaptations to endurance exercise. Cold Spring Harb Perspect Med8, (2018). [DOI] [PMC free article] [PubMed]
- 34.Pedersen BK, Febbraio MA. Muscles, exercise and obesity: skeletal muscle as a secretory organ. Nat. Rev. Endocrinol. 2012;8:457–465. doi: 10.1038/nrendo.2012.49. [DOI] [PubMed] [Google Scholar]
- 35.Hunt LC, et al. The glucose-sensing transcription factor MLX promotes myogenesis via myokine signaling. Genes Dev. 2015;29:2475–2489. doi: 10.1101/gad.267419.115. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Rai M, Demontis F. Systemic nutrient and stress signaling via myokines and myometabolites. Annu Rev. Physiol. 2016;78:85–107. doi: 10.1146/annurev-physiol-021115-105305. [DOI] [PubMed] [Google Scholar]
- 37.Argiles JM, Orpi M, Busquets S, Lopez-Soriano FJ. Myostatin: more than just a regulator of muscle mass. Drug Disco. Today. 2012;17:702–709. doi: 10.1016/j.drudis.2012.02.001. [DOI] [PubMed] [Google Scholar]
- 38.Lee SJ. Regulation of muscle mass by myostatin. Annu Rev. Cell Dev. Biol. 2004;20:61–86. doi: 10.1146/annurev.cellbio.20.012103.135836. [DOI] [PubMed] [Google Scholar]
- 39.Whittemore LA, et al. Inhibition of myostatin in adult mice increases skeletal muscle mass and strength. Biochem Biophys. Res Commun. 2003;300:965–971. doi: 10.1016/S0006-291X(02)02953-4. [DOI] [PubMed] [Google Scholar]
- 40.Reza MM, et al. Irisin is a pro-myogenic factor that induces skeletal muscle hypertrophy and rescues denervation-induced atrophy. Nat. Commun. 2017;8:1104. doi: 10.1038/s41467-017-01131-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Kanzleiter T, et al. The myokine decorin is regulated by contraction and involved in muscle hypertrophy. Biochem. Biophys. Res. Commun. 2014;450:1089–1094. doi: 10.1016/j.bbrc.2014.06.123. [DOI] [PubMed] [Google Scholar]
- 42.Broholm C, et al. LIF is a contraction-induced myokine stimulating human myocyte proliferation. J. Appl. Physiol. 2011;111:251–259. doi: 10.1152/japplphysiol.01399.2010. [DOI] [PubMed] [Google Scholar]
- 43.Gonzalez-Franquesa A., et al. Discovery of thymosin beta-4 as a human exerkine and growth factor. Am. J. Physiol. Cell Physiol., (2021). [DOI] [PubMed]
- 44.Guerci A, et al. Srf-dependent paracrine signals produced by myofibers control satellite cell-mediated skeletal muscle hypertrophy. Cell Metab. 2012;15:25–37. doi: 10.1016/j.cmet.2011.12.001. [DOI] [PubMed] [Google Scholar]
- 45.Horsley V, Pavlath GK. Prostaglandin F2(alpha) stimulates growth of skeletal muscle cells via an NFATC2-dependent pathway. J. cell Biol. 2003;161:111–118. doi: 10.1083/jcb.200208085. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Mu X, Urso ML, Murray K, Fu F, Li Y. Relaxin regulates MMP expression and promotes satellite cell mobilization during muscle healing in both young and aged mice. Am. J. Pathol. 2010;177:2399–2410. doi: 10.2353/ajpath.2010.091121. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Serrano AL, Baeza-Raja B, Perdiguero E, Jardi M, Munoz-Canoves P. Interleukin-6 is an essential regulator of satellite cell-mediated skeletal muscle hypertrophy. Cell Metab. 2008;7:33–44. doi: 10.1016/j.cmet.2007.11.011. [DOI] [PubMed] [Google Scholar]
- 48.Umemoto T, Furutani Y, Murakami M, Matsui T, Funaba M. Endogenous Bmp4 in myoblasts is required for myotube formation in C2C12 cells. Biochimica et. biophysica acta. 2011;1810:1127–1135. doi: 10.1016/j.bbagen.2011.09.008. [DOI] [PubMed] [Google Scholar]
- 49.Zeng L, et al. Insulin-like 6 is induced by muscle injury and functions as a regenerative factor. J. Biol. Chem. 2010;285:36060–36069. doi: 10.1074/jbc.M110.160879. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Piccirillo R. Exercise-Induced Myokines With Therapeutic Potential for Muscle Wasting. Front Physiol. 2019;10:287. doi: 10.3389/fphys.2019.00287. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Re Cecconi A. D., et al. Musclin, A Myokine induced by aerobic exercise, retards muscle atrophy during cancer cachexia in mice. Cancers (Basel)11, (2019). [DOI] [PMC free article] [PubMed]
- 52.Vinel C, et al. The exerkine apelin reverses age-associated sarcopenia. Nat. Med. 2018;24:1360–1371. doi: 10.1038/s41591-018-0131-6. [DOI] [PubMed] [Google Scholar]
- 53.Lee JH, Jun HS. Role of myokines in regulating skeletal muscle mass and function. Front Physiol. 2019;10:42. doi: 10.3389/fphys.2019.00042. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Manole E, Ceafalan LC, Popescu BO, Dumitru C, Bastian AE. Myokines as Possible Therapeutic Targets in Cancer Cachexia. J. Immunol. Res. 2018;2018:8260742. doi: 10.1155/2018/8260742. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Murphy KT, et al. Antibody-directed myostatin inhibition enhances muscle mass and function in tumor-bearing mice. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2010;301:R716–R726. doi: 10.1152/ajpregu.00121.2011. [DOI] [PubMed] [Google Scholar]
- 56.Smith RC, Lin BK. Myostatin inhibitors as therapies for muscle wasting associated with cancer and other disorders. Curr. Opin. supportive Palliat. care. 2013;7:352–360. doi: 10.1097/SPC.0000000000000013. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57.Suriben R, et al. Antibody-mediated inhibition of GDF15-GFRAL activity reverses cancer cachexia in mice. Nat. Med. 2020;26:1264–1270. doi: 10.1038/s41591-020-0945-x. [DOI] [PubMed] [Google Scholar]
- 58.Benoit B, et al. Fibroblast growth factor 19 regulates skeletal muscle mass and ameliorates muscle wasting in mice. Nat. Med. 2017;23:990–996. doi: 10.1038/nm.4363. [DOI] [PubMed] [Google Scholar]
- 59.Demontis F, Perrimon N. Integration of Insulin receptor/Foxo signaling and dMyc activity during muscle growth regulates body size in Drosophila. Development. 2009;136:983–993. doi: 10.1242/dev.027466. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60.Hunt LC, et al. A Key Role for the Ubiquitin Ligase UBR4 in Myofiber Hypertrophy in Drosophila and Mice. Cell Rep. 2019;28:1268–1281 e1266. doi: 10.1016/j.celrep.2019.06.094. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 61.Seaberg B, et al. Muscle-derived extracellular signal-regulated kinases 1 and 2 are required for the maintenance of adult myofibers and their neuromuscular junctions. Mol. Cell Biol. 2015;35:1238–1253. doi: 10.1128/MCB.01071-14. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Murgia M, et al. Ras is involved in nerve-activity-dependent regulation of muscle genes. Nat. Cell Biol. 2000;2:142–147. doi: 10.1038/35004013. [DOI] [PubMed] [Google Scholar]
- 63.Shi H, et al. Mitogen-activated protein kinase signaling is necessary for the maintenance of skeletal muscle mass. Am. J. Physiol. Cell Physiol. 2009;296:C1040–C1048. doi: 10.1152/ajpcell.00475.2008. [DOI] [PubMed] [Google Scholar]
- 64.Haddad F, Adams GR. Inhibition of MAP/ERK kinase prevents IGF-I-induced hypertrophy in rat muscles. J. Appl Physiol. (1985) 2004;96:203–210. doi: 10.1152/japplphysiol.00856.2003. [DOI] [PubMed] [Google Scholar]
- 65.Norheim F, et al. Proteomic identification of secreted proteins from human skeletal muscle cells and expression in response to strength training. Am. J. Physiol. Endocrinol. Metab. 2011;301:E1013–E1021. doi: 10.1152/ajpendo.00326.2011. [DOI] [PubMed] [Google Scholar]
- 66.Graca FA, et al. A large-scale transgenic RNAi screen identifies transcription factors that modulate myofiber size in Drosophila. PLoS Genet. 2021;17:e1009926. doi: 10.1371/journal.pgen.1009926. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 67.Brand AH, Perrimon N. Targeted gene expression as a means of altering cell fates and generating dominant phenotypes. Development. 1993;118:401–415. doi: 10.1242/dev.118.2.401. [DOI] [PubMed] [Google Scholar]
- 68.Ranganayakulu G, et al. A series of mutations in the D-MEF2 transcription factor reveal multiple functions in larval and adult myogenesis in Drosophila. Developmental Biol. 1995;171:169–181. doi: 10.1006/dbio.1995.1269. [DOI] [PubMed] [Google Scholar]
- 69.McPherron AC, Lawler AM, Lee SJ. Regulation of skeletal muscle mass in mice by a new TGF-beta superfamily member. Nature. 1997;387:83–90. doi: 10.1038/387083a0. [DOI] [PubMed] [Google Scholar]
- 70.Nakamura K, Nakano S, Miyoshi T, Yamanouchi K, Nishihara M. Loss of SPARC in mouse skeletal muscle causes myofiber atrophy. Muscle Nerve. 2013;48:791–799. doi: 10.1002/mus.23822. [DOI] [PubMed] [Google Scholar]
- 71.Sartori R, et al. BMP signaling controls muscle mass. Nat. Genet. 2013;45:1309–1318. doi: 10.1038/ng.2772. [DOI] [PubMed] [Google Scholar]
- 72.Hayashi S, Kondo T. Development and function of the Drosophila tracheal system. Genetics. 2018;209:367–380. doi: 10.1534/genetics.117.300167. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 73.Demontis F, Patel VK, Swindell WR, Perrimon N. Intertissue control of the nucleolus via a myokine-dependent longevity pathway. Cell Rep. 2014;7:1481–1494. doi: 10.1016/j.celrep.2014.05.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 74.Labelle-Dumais C, et al. COL4A1 Mutations Cause Neuromuscular Disease with Tissue-Specific Mechanistic Heterogeneity. Am. J. Hum. Genet. 2019;104:847–860. doi: 10.1016/j.ajhg.2019.03.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 75.Kim HR, Ingham PW. The extracellular matrix protein TGFBI promotes myofibril bundling and muscle fibre growth in the zebrafish embryo. Developmental Dyn.: Off. Publ. Am. Assoc. Anatomists. 2009;238:56–65. doi: 10.1002/dvdy.21812. [DOI] [PubMed] [Google Scholar]
- 76.Moeller JB, et al. Modulation of the fungal mycobiome is regulated by the chitin-binding receptor FIBCD1. J. Exp. Med. 2019;216:2689–2700. doi: 10.1084/jem.20182244. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 77.Schlosser A, et al. Characterization of FIBCD1 as an acetyl group-binding receptor that binds chitin. J. Immunol. 2009;183:3800–3809. doi: 10.4049/jimmunol.0901526. [DOI] [PubMed] [Google Scholar]
- 78.Kandarian SC, et al. Tumour-derived leukaemia inhibitory factor is a major driver of cancer cachexia and morbidity in C26 tumour-bearing mice. J. Cachexia Sarcopenia Muscle. 2018;9:1109–1120. doi: 10.1002/jcsm.12346. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 79.Wang DT, et al. Resveratrol prevents TNF-alpha-induced muscle atrophy via regulation of Akt/mTOR/FoxO1 signaling in C2C12 myotubes. Int Immunopharmacol. 2014;19:206–213. doi: 10.1016/j.intimp.2014.02.002. [DOI] [PubMed] [Google Scholar]
- 80.Yamaki T, et al. Rel A/p65 is required for cytokine-induced myotube atrophy. Am. J. Physiol. Cell Physiol. 2012;303:C135–C142. doi: 10.1152/ajpcell.00111.2012. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 81.Argadine HM, Mantilla CB, Zhan WZ, Sieck GC. Intracellular signaling pathways regulating net protein balance following diaphragm muscle denervation. Am. J. Physiol. Cell Physiol. 2011;300:C318–C327. doi: 10.1152/ajpcell.00172.2010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 82.Saito Y, Vandenheede JR, Cohen P. The mechanism by which epidermal growth factor inhibits glycogen synthase kinase 3 in A431 cells. Biochem J. 1994;303:27–31. doi: 10.1042/bj3030027. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 83.Waskiewicz AJ, Flynn A, Proud CG, Cooper JA. Mitogen-activated protein kinases activate the serine/threonine kinases Mnk1 and Mnk2. EMBO J. 1997;16:1909–1920. doi: 10.1093/emboj/16.8.1909. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 84.Waskiewicz AJ, et al. Phosphorylation of the cap-binding protein eukaryotic translation initiation factor 4E by protein kinase Mnk1 in vivo. Mol. Cell Biol. 1999;19:1871–1880. doi: 10.1128/MCB.19.3.1871. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 85.Aronov AM, et al. Flipped out: structure-guided design of selective pyrazolylpyrrole ERK inhibitors. J. Med Chem. 2007;50:1280–1287. doi: 10.1021/jm061381f. [DOI] [PubMed] [Google Scholar]
- 86.Junttila MR, Li SP, Westermarck J. Phosphatase-mediated crosstalk between MAPK signaling pathways in the regulation of cell survival. FASEB J. 2008;22:954–965. doi: 10.1096/fj.06-7859rev. [DOI] [PubMed] [Google Scholar]
- 87.Dhillon AS, Hagan S, Rath O, Kolch W. MAP kinase signalling pathways in cancer. Oncogene. 2007;26:3279–3290. doi: 10.1038/sj.onc.1210421. [DOI] [PubMed] [Google Scholar]
- 88.Musaro A, et al. Localized Igf-1 transgene expression sustains hypertrophy and regeneration in senescent skeletal muscle. Nat. Genet. 2001;27:195–200. doi: 10.1038/84839. [DOI] [PubMed] [Google Scholar]
- 89.Kaplan RN, et al. VEGFR1-positive haematopoietic bone marrow progenitors initiate the pre-metastatic niche. Nature. 2005;438:820–827. doi: 10.1038/nature04186. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 90.Jia H, et al. The tumor cell-secreted matricellular protein WISP1 drives pro-metastatic collagen linearization. EMBO J. 2019;38:e101302. doi: 10.15252/embj.2018101302. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 91.Labelle M, Begum S, Hynes RO. Platelets guide the formation of early metastatic niches. Proc. Natl Acad. Sci. USA. 2014;111:E3053–E3061. doi: 10.1073/pnas.1411082111. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 92.Yu S, et al. Lung cells support osteosarcoma cell migration and survival. BMC Cancer. 2017;17:78. doi: 10.1186/s12885-017-3047-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 93.Hantgan RR, Stahle MC, Lord ST. Dynamic regulation of fibrinogen: integrin alphaIIbbeta3 binding. Biochemistry. 2010;49:9217–9225. doi: 10.1021/bi1009858. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 94.Suehiro K, Gailit J, Plow EF. Fibrinogen is a ligand for integrin alpha5beta1 on endothelial cells. J. Biol. Chem. 1997;272:5360–5366. doi: 10.1074/jbc.272.8.5360. [DOI] [PubMed] [Google Scholar]
- 95.Hynes RO. Integrins: bidirectional, allosteric signaling machines. Cell. 2002;110:673–687. doi: 10.1016/S0092-8674(02)00971-6. [DOI] [PubMed] [Google Scholar]
- 96.Puppa MJ, Gao S, Narsale AA, Carson JA. Skeletal muscle glycoprotein 130’s role in Lewis lung carcinoma-induced cachexia. FASEB J.: Off. Publ. Federation Am. Societies Exp. Biol. 2014;28:998–1009. doi: 10.1096/fj.13-240580. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 97.Talbert EE, et al. Modeling Human Cancer-induced Cachexia. Cell Rep. 2019;28:1612–1622 e1614. doi: 10.1016/j.celrep.2019.07.016. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 98.Smith IJ, et al. Janus kinase inhibition prevents cancer- and myocardial infarction-mediated diaphragm muscle weakness in mice. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2016;310:R707–R710. doi: 10.1152/ajpregu.00550.2015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 99.Berger D, et al. Dysfunction of respiratory muscles in critically ill patients on the intensive care unit. J. Cachexia Sarcopenia Muscle. 2016;7:403–412. doi: 10.1002/jcsm.12108. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 100.Briguet A, Courdier-Fruh I, Foster M, Meier T, Magyar JP. Histological parameters for the quantitative assessment of muscular dystrophy in the mdx-mouse. Neuromuscul. Disord.: NMD. 2004;14:675–682. doi: 10.1016/j.nmd.2004.06.008. [DOI] [PubMed] [Google Scholar]
- 101.Schiaffino S, Reggiani C. Fiber types in mammalian skeletal muscles. Physiol. Rev. 2011;91:1447–1531. doi: 10.1152/physrev.00031.2010. [DOI] [PubMed] [Google Scholar]
- 102.Zhang G, et al. Toll-like receptor 4 mediates Lewis lung carcinoma-induced muscle wasting via coordinate activation of protein degradation pathways. Sci. Rep. 2017;7:2273. doi: 10.1038/s41598-017-02347-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 103.Lecker SH, et al. Multiple types of skeletal muscle atrophy involve a common program of changes in gene expression. FASEB J.: Off. Publ. Federation Am. Societies Exp. Biol. 2004;18:39–51. doi: 10.1096/fj.03-0610com. [DOI] [PubMed] [Google Scholar]
- 104.Ruff RL, Secrist D. Inhibitors of prostaglandin synthesis or cathepsin B prevent muscle wasting due to sepsis in the rat. J. Clin. Invest. 1984;73:1483–1486. doi: 10.1172/JCI111352. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 105.Tjondrokoesoemo A, et al. Cathepsin S Contributes to the Pathogenesis of Muscular Dystrophy in Mice. J. Biol. Chem. 2016;291:9920–9928. doi: 10.1074/jbc.M116.719054. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 106.Zhao J, et al. FoxO3 coordinately activates protein degradation by the autophagic/lysosomal and proteasomal pathways in atrophying muscle cells. Cell Metab. 2007;6:472–483. doi: 10.1016/j.cmet.2007.11.004. [DOI] [PubMed] [Google Scholar]
- 107.Gomes MD, Lecker SH, Jagoe RT, Navon A, Goldberg AL. Atrogin-1, a muscle-specific F-box protein highly expressed during muscle atrophy. Proc. Natl Acad. Sci. USA. 2001;98:14440–14445. doi: 10.1073/pnas.251541198. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 108.Bodine SC, Baehr LM. Skeletal muscle atrophy and the E3 ubiquitin ligases MuRF1 and MAFbx/atrogin-1. Am. J. Physiol. Endocrinol. Metab. 2014;307:E469–E484. doi: 10.1152/ajpendo.00204.2014. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 109.Ruas JL, et al. A PGC-1alpha isoform induced by resistance training regulates skeletal muscle hypertrophy. Cell. 2012;151:1319–1331. doi: 10.1016/j.cell.2012.10.050. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 110.Delitto D, et al. Human pancreatic cancer xenografts recapitulate key aspects of cancer cachexia. Oncotarget. 2017;8:1177–1189. doi: 10.18632/oncotarget.13593. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 111.Stewart E, et al. The Childhood Solid Tumor Network: A new resource for the developmental biology and oncology research communities. Dev. Biol. 2016;411:287–293. doi: 10.1016/j.ydbio.2015.03.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 112.Stewart E, et al. Orthotopic patient-derived xenografts of paediatric solid tumours. Nature. 2017;549:96–100. doi: 10.1038/nature23647. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 113.Bahrami A., Barnhill R. L. Pathology and genomics of pediatric melanoma: A critical reexamination and new insights. Pediatr Blood Cancer65, (2018). [DOI] [PMC free article] [PubMed]
- 114.Newman S, et al. Clinical genome sequencing uncovers potentially targetable truncations and fusions of MAP3K8 in spitzoid and other melanomas. Nat. Med. 2019;25:597–602. doi: 10.1038/s41591-019-0373-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 115.Newman S, et al. Pathologic Characteristics of Spitz Melanoma With MAP3K8 Fusion or Truncation in a Pediatric Cohort. Am. J. Surg. Pathol. 2019;43:1631–1637. doi: 10.1097/PAS.0000000000001362. [DOI] [PubMed] [Google Scholar]
- 116.Lieberman DA, Faulkner JA, Craig AB, Jr, Maxwell LC. Performance and histochemical composition of guinea pig and human diaphragm. J. Appl Physiol. 1973;34:233–237. doi: 10.1152/jappl.1973.34.2.233. [DOI] [PubMed] [Google Scholar]
- 117.Polla B, D’Antona G, Bottinelli R, Reggiani C. Respiratory muscle fibres: specialisation and plasticity. Thorax. 2004;59:808–817. doi: 10.1136/thx.2003.009894. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 118.Pappas CT, Bhattacharya N, Cooper JA, Gregorio CC. Nebulin interacts with CapZ and regulates thin filament architecture within the Z-disc. Mol. Biol. Cell. 2008;19:1837–1847. doi: 10.1091/mbc.e07-07-0690. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 119.Liu W, et al. Regular aerobic exercise-ameliorated troponin I carbonylation to mitigate aged rat soleus muscle functional recession. Exp. Physiol. 2019;104:715–728. doi: 10.1113/EP087564. [DOI] [PubMed] [Google Scholar]
- 120.Gordon BS, Rossetti ML, Eroshkin AM. Arrdc2 and Arrdc3 elicit divergent changes in gene expression in skeletal muscle following anabolic and catabolic stimuli. Physiol. Genomics. 2019;51:208–217. doi: 10.1152/physiolgenomics.00007.2019. [DOI] [PubMed] [Google Scholar]
- 121.Britto FA, et al. REDD1 deletion prevents dexamethasone-induced skeletal muscle atrophy. Am. J. Physiol. Endocrinol. Metab. 2014;307:E983–E993. doi: 10.1152/ajpendo.00234.2014. [DOI] [PubMed] [Google Scholar]
- 122.Niu M, et al. An integrative transcriptome study reveals Ddit4/Redd1 as a key regulator of cancer cachexia in rodent models. Cell Death Dis. 2021;12:652. doi: 10.1038/s41419-021-03932-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 123.Shimizu N, et al. Crosstalk between glucocorticoid receptor and nutritional sensor mTOR in skeletal muscle. Cell Metab. 2011;13:170–182. doi: 10.1016/j.cmet.2011.01.001. [DOI] [PubMed] [Google Scholar]
- 124.Bonetto A, et al. STAT3 activation in skeletal muscle links muscle wasting and the acute phase response in cancer cachexia. PloS one. 2011;6:e22538. doi: 10.1371/journal.pone.0022538. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 125.de OCP, et al. Identification of potential target genes associated with the reversion of androgen-dependent skeletal muscle atrophy. Arch. Biochem Biophys. 2019;663:173–182. doi: 10.1016/j.abb.2019.01.009. [DOI] [PubMed] [Google Scholar]
- 126.Ehrlich K. C., Baribault C., Ehrlich M. Epigenetics of Muscle- and Brain-Specific Expression of KLHL Family Genes. Int J Mol Sci21, (2020). [DOI] [PMC free article] [PubMed]
- 127.Hirata Y., et al. Hyperglycemia induces skeletal muscle atrophy via a WWP1/KLF15 axis. JCI Insight4, (2019). [DOI] [PMC free article] [PubMed]
- 128.Walter LM, et al. Interventions Targeting Glucocorticoid-Kruppel-like Factor 15-Branched-Chain Amino Acid Signaling Improve Disease Phenotypes in Spinal Muscular Atrophy Mice. EBioMedicine. 2018;31:226–242. doi: 10.1016/j.ebiom.2018.04.024. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 129.Plaisier CL, et al. Zbtb16 has a role in brown adipocyte bioenergetics. Nutr. Diabetes. 2012;2:e46. doi: 10.1038/nutd.2012.21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 130.Kir S, et al. PTH/PTHrP Receptor Mediates Cachexia in Models of Kidney Failure and Cancer. Cell Metab. 2016;23:315–323. doi: 10.1016/j.cmet.2015.11.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 131.Kir S, et al. Tumour-derived PTH-related protein triggers adipose tissue browning and cancer cachexia. Nature. 2014;513:100–104. doi: 10.1038/nature13528. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 132.Petruzzelli M, et al. A switch from white to brown fat increases energy expenditure in cancer-associated cachexia. Cell Metab. 2014;20:433–447. doi: 10.1016/j.cmet.2014.06.011. [DOI] [PubMed] [Google Scholar]
- 133.Hart N, et al. Effect of severe isolated unilateral and bilateral diaphragm weakness on exercise performance. Am. J. Respir. Crit. Care Med. 2002;165:1265–1270. doi: 10.1164/rccm.2110016. [DOI] [PubMed] [Google Scholar]
- 134.Kress JP, Pohlman AS, Alverdy J, Hall JB. The impact of morbid obesity on oxygen cost of breathing (VO(2RESP)) at rest. Am. J. Respir. Crit. Care Med. 1999;160:883–886. doi: 10.1164/ajrccm.160.3.9902058. [DOI] [PubMed] [Google Scholar]
- 135.Laroche CM, Carroll N, Moxham J, Green M. Clinical significance of severe isolated diaphragm weakness. Am. Rev. Respir. Dis. 1988;138:862–866. doi: 10.1164/ajrccm/138.4.862. [DOI] [PubMed] [Google Scholar]
- 136.Castro B., Kuang S. Evaluation of Muscle Performance in Mice by Treadmill Exhaustion Test and Whole-limb Grip Strength Assay. Bio Protoc7, (2017). [DOI] [PMC free article] [PubMed]
- 137.Costamagna D, et al. Interleukin-4 administration improves muscle function, adult myogenesis, and lifespan of colon carcinoma-bearing mice. J. Cachexia Sarcopenia Muscle. 2020;11:783–801. doi: 10.1002/jcsm.12539. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 138.Glass DJ. Signaling pathways perturbing muscle mass. Curr. Opin. Clin. Nutr. Metab. Care. 2010;13:225–229. doi: 10.1097/MCO.0b013e32833862df. [DOI] [PubMed] [Google Scholar]
- 139.Bostrom P, et al. A PGC1-alpha-dependent myokine that drives brown-fat-like development of white fat and thermogenesis. Nature. 2012;481:463–468. doi: 10.1038/nature10777. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 140.Dinarvand P, Hassanian SM, Weiler H, Rezaie AR. Intraperitoneal administration of activated protein C prevents postsurgical adhesion band formation. Blood. 2015;125:1339–1348. doi: 10.1182/blood-2014-10-609339. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 141.Biswas AK, Acharyya S. Understanding cachexia in the context of metastatic progression. Nat. Rev. Cancer. 2020;20:274–284. doi: 10.1038/s41568-020-0251-4. [DOI] [PubMed] [Google Scholar]
- 142.Boyer J. G., et al. ERK1/2 signaling induces skeletal muscle slow fiber-type switching and reduces muscular dystrophy disease severity. JCI Insight5, (2019). [DOI] [PMC free article] [PubMed]
- 143.Widegren U, Ryder JW, Zierath JR. Mitogen-activated protein kinase signal transduction in skeletal muscle: effects of exercise and muscle contraction. Acta Physiol. Scand. 2001;172:227–238. doi: 10.1046/j.1365-201x.2001.00855.x. [DOI] [PubMed] [Google Scholar]
- 144.Widegren U, Wretman C, Lionikas A, Hedin G, Henriksson J. Influence of exercise intensity on ERK/MAP kinase signalling in human skeletal muscle. Pflug. Arch. 2000;441:317–322. doi: 10.1007/s004240000417. [DOI] [PubMed] [Google Scholar]
- 145.Yu M, Blomstrand E, Chibalin AV, Krook A, Zierath JR. Marathon running increases ERK1/2 and p38 MAP kinase signalling to downstream targets in human skeletal muscle. J. Physiol. 2001;536:273–282. doi: 10.1111/j.1469-7793.2001.00273.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 146.Ryder JW, et al. Effect of contraction on mitogen-activated protein kinase signal transduction in skeletal muscle. Involvement Of the mitogen- and stress-activated protein kinase 1. J. Biol. Chem. 2000;275:1457–1462. doi: 10.1074/jbc.275.2.1457. [DOI] [PubMed] [Google Scholar]
- 147.Brown JL, et al. Protein imbalance in the development of skeletal muscle wasting in tumour-bearing mice. J. Cachexia Sarcopenia Muscle. 2018;9:987–1002. doi: 10.1002/jcsm.12354. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 148.Peake JM, Neubauer O, Della Gatta PA, Nosaka K. Muscle damage and inflammation during recovery from exercise. J. Appl Physiol. (1985) 2017;122:559–570. doi: 10.1152/japplphysiol.00971.2016. [DOI] [PubMed] [Google Scholar]
- 149.Iwata Y, et al. Cancer cachexia causes skeletal muscle damage via transient receptor potential vanilloid 2-independent mechanisms, unlike muscular dystrophy. J. Cachexia Sarcopenia Muscle. 2016;7:366–376. doi: 10.1002/jcsm.12067. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 150.Talbert EE, et al. Dual Inhibition of MEK and PI3K/Akt Rescues Cancer Cachexia through both Tumor-Extrinsic and -Intrinsic Activities. Mol. Cancer Ther. 2017;16:344–356. doi: 10.1158/1535-7163.MCT-16-0337. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 151.Au ED, Desai AP, Koniaris LG, Zimmers TA. The MEK-Inhibitor Selumetinib Attenuates Tumor Growth and Reduces IL-6 Expression but Does Not Protect against Muscle Wasting in Lewis Lung Cancer Cachexia. Front Physiol. 2016;7:682. doi: 10.3389/fphys.2016.00682. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 152.Song W, et al. Tumor-Derived Ligands Trigger Tumor Growth and Host Wasting via Differential MEK Activation. Dev. Cell. 2019;48:277–286 e276. doi: 10.1016/j.devcel.2018.12.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 153.Zuo L, Pannell BK, Re AT, Best TM, Wagner PD. Po2 cycling protects diaphragm function during reoxygenation via ROS, Akt, ERK, and mitochondrial channels. Am. J. Physiol. Cell Physiol. 2015;309:C759–C766. doi: 10.1152/ajpcell.00174.2015. [DOI] [PubMed] [Google Scholar]
- 154.Andersen MCE, et al. FIBCD1 ameliorates weight loss in chemotherapy-induced murine mucositis. Support Care Cancer. 2021;29:2415–2421. doi: 10.1007/s00520-020-05762-w. [DOI] [PubMed] [Google Scholar]
- 155.Jiang C, et al. Overexpression of FIBCD1 is predictive of poor prognosis in gastric cancer. Am. J. Clin. Pathol. 2018;149:474–483. doi: 10.1093/ajcp/aqy013. [DOI] [PubMed] [Google Scholar]
- 156.Wang Y, et al. FIBCD1 overexpression predicts poor prognosis in patients with hepatocellular carcinoma. Oncol. Lett. 2020;19:795–804. doi: 10.3892/ol.2019.11183. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 157.Beatty GL, Gladney WL. Immune escape mechanisms as a guide for cancer immunotherapy. Clin. Cancer Res. 2015;21:687–692. doi: 10.1158/1078-0432.CCR-14-1860. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 158.Lai JS, Cella D, Peterman A, Barocas J, Goldman S. Anorexia/cachexia-related quality of life for children with cancer. Cancer. 2005;104:1531–1539. doi: 10.1002/cncr.21315. [DOI] [PubMed] [Google Scholar]
- 159.Piccirillo R., Demontis F., Perrimon N., Goldberg A. L. Mechanisms of muscle growth and atrophy in mammals and Drosophila. Dev. Dyn. 201–215 (2014). [DOI] [PMC free article] [PubMed]
- 160.Ottenheijm CA, Heunks LM, Dekhuijzen PN. Diaphragm muscle fiber dysfunction in chronic obstructive pulmonary disease: toward a pathophysiological concept. Am. J. Respir. Crit. Care Med. 2007;175:1233–1240. doi: 10.1164/rccm.200701-020PP. [DOI] [PubMed] [Google Scholar]
- 161.Ottenheijm CA, et al. Activation of the ubiquitin-proteasome pathway in the diaphragm in chronic obstructive pulmonary disease. Am. J. Respir. Crit. Care Med. 2006;174:997–1002. doi: 10.1164/rccm.200605-721OC. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 162.Elliott JE, Greising SM, Mantilla CB, Sieck GC. Functional impact of sarcopenia in respiratory muscles. Respir. Physiol. Neurobiol. 2016;226:137–146. doi: 10.1016/j.resp.2015.10.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 163.Greising SM, Mantilla CB, Gorman BA, Ermilov LG, Sieck GC. Diaphragm muscle sarcopenia in aging mice. Exp. Gerontol. 2013;48:881–887. doi: 10.1016/j.exger.2013.06.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 164.Vang P, et al. Diaphragm muscle sarcopenia into very old age in mice. Physiol. Rep. 2020;8:e14305. doi: 10.14814/phy2.14305. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 165.Hooijman PE, et al. Diaphragm muscle fiber weakness and ubiquitin-proteasome activation in critically ill patients. Am. J. Respir. Crit. Care Med. 2015;191:1126–1138. doi: 10.1164/rccm.201412-2214OC. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 166.Hu Y, Comjean A, Perkins LA, Perrimon N, Mohr SE. GLAD: an online database of gene list annotation for Drosophila. J. Genomics. 2015;3:75–81. doi: 10.7150/jgen.12863. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 167.Hu Y, et al. An integrative approach to ortholog prediction for disease-focused and other functional studies. BMC Bioinforma. 2011;12:357. doi: 10.1186/1471-2105-12-357. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 168.Stevenson EJ, Koncarevic A, Giresi PG, Jackman RW, Kandarian SC. Transcriptional profile of a myotube starvation model of atrophy. J. Appl. Physiol. 2005;98:1396–1406. doi: 10.1152/japplphysiol.01055.2004. [DOI] [PubMed] [Google Scholar]
- 169.Fidler IJ. Biological behavior of malignant melanoma cells correlated to their survival in vivo. Cancer Res. 1975;35:218–224. [PubMed] [Google Scholar]
- 170.Cailleau R, Young R, Olive M, Reeves WJ., Jr Breast tumor cell lines from pleural effusions. J. Natl Cancer Inst. 1974;53:661–674. doi: 10.1093/jnci/53.3.661. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 171.Oft M, et al. TGF-beta1 and Ha-Ras collaborate in modulating the phenotypic plasticity and invasiveness of epithelial tumor cells. Genes Dev. 1996;10:2462–2477. doi: 10.1101/gad.10.19.2462. [DOI] [PubMed] [Google Scholar]
- 172.Ewens A, Mihich E, Ehrke MJ. Distant metastasis from subcutaneously grown E0771 medullary breast adenocarcinoma. Anticancer Res. 2005;25:3905–3915. [PubMed] [Google Scholar]
- 173.Aslakson CJ, Miller FR. Selective events in the metastatic process defined by analysis of the sequential dissemination of subpopulations of a mouse mammary tumor. Cancer Res. 1992;52:1399–1405. [PubMed] [Google Scholar]
- 174.Tom BH, et al. Human colonic adenocarcinoma cells. I. Establishment and description of a new line. Vitro. 1976;12:180–191. doi: 10.1007/BF02796440. [DOI] [PubMed] [Google Scholar]
- 175.Corbett TH, Griswold DP, Jr, Roberts BJ, Peckham JC, Schabel FM., Jr Tumor induction relationships in development of transplantable cancers of the colon in mice for chemotherapy assays, with a note on carcinogen structure. Cancer Res. 1975;35:2434–2439. [PubMed] [Google Scholar]
- 176.Ponten J, Saksela E. Two established in vitro cell lines from human mesenchymal tumours. Int J. Cancer. 1967;2:434–447. doi: 10.1002/ijc.2910020505. [DOI] [PubMed] [Google Scholar]
- 177.Diller L, et al. p53 functions as a cell cycle control protein in osteosarcomas. Mol. Cell Biol. 1990;10:5772–5781. doi: 10.1128/mcb.10.11.5772. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 178.Fogh J, Fogh JM, Orfeo T. One hundred and twenty-seven cultured human tumor cell lines producing tumors in nude mice. J. Natl Cancer Inst. 1977;59:221–226. doi: 10.1093/jnci/59.1.221. [DOI] [PubMed] [Google Scholar]
- 179.Bloemberg D, Quadrilatero J. Rapid determination of myosin heavy chain expression in rat, mouse, and human skeletal muscle using multicolor immunofluorescence analysis. PLoS ONE. 2012;7:e35273. doi: 10.1371/journal.pone.0035273. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 180.Hunt LC, et al. Antagonistic control of myofiber size and muscle protein quality control by the ubiquitin ligase UBR4 during aging. Nat. Commun. 2021;12:1418. doi: 10.1038/s41467-021-21738-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 181.Yue F, et al. Conditional loss of Pten in myogenic progenitors leads to postnatal skeletal muscle hypertrophy but age-dependent exhaustion of satellite cells. Cell Rep. 2016;17:2340–2353. doi: 10.1016/j.celrep.2016.11.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 182.Zhou X, et al. Reversal of cancer cachexia and muscle wasting by ActRIIB antagonism leads to prolonged survival. Cell. 2011;142:531–543. doi: 10.1016/j.cell.2010.07.011. [DOI] [PubMed] [Google Scholar]
- 183.Hermann N, Dressen K, Schildberg FA, Jakobs C, Holdenrieder S. Methodical and pre-analytical characteristics of a multiplex cancer biomarker immunoassay. World J. Methodol. 2014;4:219–231. doi: 10.5662/wjm.v4.i4.219. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The RNA-seq data discussed in this publication have been deposited in the NCBI’s Gene Expression Omnibus and are publicly accessible through GEO Series accession numbers GSE156815, GSE158581, and GSE183833.
Additional primary data are available in Supplementary Data 1–5 and in the Source Data File.
Publicly-available datasets that have been interrogated in this study are the following and were used to retrieve RNA-seq data from pediatric cancers (ProteinPaint; https://proteinpaint.stjude.org/) and adult cancers (FireBrowse; http://firebrowse.org/viewGene.html?gene=ITGA2B), and for assessing circulating levels of Fibcd1 (Aging Plasma Proteome dataset; https://twc-stanford.shinyapps.io/aging_plasma_proteome/).
Statistics and Reproducibility. Data organization, scientific graphing and statistical analyses were performed with Microsoft Excel (version 14.7.3) and GraphPad Prism (version 6). The unpaired two-tailed Student’s t-test was used to compare the means of two independent groups to each other. One-way and two-way ANOVA with post hoc testing were used for multiple comparisons of more than two groups of normally distributed data. The “n” for each experiment can be found in the figure legends and represents independently generated samples for all experiments, including myotubes and cell culture samples for in vitro assays, and individual animals or tissues sourced from independent animals for in vivo experiments. Bar graphs present the mean ± SD. Throughout the figures, asterisks and ampersand symbols indicate the significance of P values: *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. A significant result was defined as P < 0.05. Representative micrographs are derived from the analysis of multiple muscles (>5) and cell culture results typically obtained from 2-3 experiments.