Comparative plasma proteomics in muscle atrophy during cancer‐cachexia and disuse: The search for atrokines

Lim, Seongkyun; Dunlap, Kirsten R.; Rosa‐Caldwell, Megan E.; Haynie, Wesley S.; Jansen, Lisa T.; Washington, Tyrone A.

doi:10.14814/phy2.14608

Cited by 20 publications

(18 citation statements)

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“…FoxOcontrolled atrophy-related genes were discovered as commonly regulated in conditions as diverse as cachexia, starvation, diabetes and kidney disease. 13 Aiming at downstream common changes, in line with previous studies, 17 we thus explored by proteomics two conditions causing skeletal muscle atrophy. We highlight a group of potential biomarkers that can be explored for their correlation to muscle atrophy in different pathological states.…”

Section: Introductionmentioning

confidence: 85%

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Plasma proteome profiling of healthy subjects undergoing bed rest reveals unloading‐dependent changes linked to muscle atrophy

Murgia

Brocca

Monti

et al. 2022

J cachexia sarcopenia muscle

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Background Inactivity and unloading induce skeletal muscle atrophy, loss of strength and detrimental metabolic effects. Bed rest is a model to study the impact of inactivity on the musculoskeletal system. It not only provides information for bed‐ridden patients care, but it is also a ground‐based spaceflight analogue used to mimic the challenges of long space missions for the human body. In both cases, it would be desirable to develop a panel of biomarkers to monitor muscle atrophy in a minimally invasive way at point of care to limit the onset of muscle loss in a personalized fashion. Methods We applied mass spectrometry‐based proteomics to measure plasma protein abundance changes in response to 10 days of bed rest in 10 young males. To validate the correlation between muscle atrophy and the significant hits emerging from our study, we analysed in parallel, with the same pipeline, a cohort of cancer patients with or without cachexia and age‐matched controls. Our analysis resulted in the quantification of over 500 proteins. Results Unloading affected plasma concentration of proteins of the complement cascade, lipid carriers and proteins derived from tissue leakage. Among the latter, teneurin‐4 increased 1.6‐fold in plasma at bed rest day 10 (BR10) compared with BR0 (6.E9 vs. 4.3E9, P = 0.02) and decreased to 0.6‐fold the initial abundance after 2 days of recovery at normal daily activity (R + 2, 2.7E9, P = 3.3E‐4); the extracellular matrix protein lumican was decreased to 0.7‐fold (1.2E9 vs. 8.5E8, P = 1.5E‐4) at BR10 and remained as low at R + 2. We identified six proteins distinguishing subjects developing unloading‐mediated muscle atrophy (decrease of >4% of quadriceps cross‐sectional area) from those largely maintaining their initial muscle mass. Among them, transthyretin, a thyroid hormone‐binding protein, was significantly less abundant at BR10 in the plasma of subjects with muscle atrophy compared with those with no atrophy (1.6E10 vs. 2.6E10, P = 0.001). Haptoglobin‐related protein was also significantly reduced in the serum of cancer patients with cachexia compared with that of controls. Conclusions Our findings highlight a combination or proteomic changes that can be explored as potential biomarkers of muscle atrophy occurring under different conditions. The panel of significant proteomic differences distinguishing atrophy‐prone and atrophy‐resistant subjects after 10 days of bed rest need to be tested in a larger cohort to validate their potential to predict inactivity‐triggered muscle loss in humans.

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Section: Introductionmentioning

confidence: 85%

“…Aiming at downstream common changes, in line with previous studies, 17 we thus explored by proteomics two conditions causing skeletal muscle atrophy. We highlight a group of potential biomarkers that can be explored for their correlation to muscle atrophy in different pathological states.…”

Section: Introductionmentioning

confidence: 91%

Plasma proteome profiling of healthy subjects undergoing bed rest reveals unloading‐dependent changes linked to muscle atrophy

Murgia

Brocca

Monti

et al. 2022

J cachexia sarcopenia muscle

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“…84–86 Table 2 summarizes the mechanism of cachexia. 13,14,34,87–124 The broad picture of CC is summarized in Figure 1.…”

Section: Imbalance Of Anabolism and Catabolism: Insight Into The Mole...mentioning

confidence: 99%

Tumor cell anabolism and host tissue catabolism-energetic inefficiency during cancer cachexia

Hegde

Daimary

Girisa

et al. 2022

Exp Biol Med (Maywood)

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Cancer-associated cachexia (CC) is a pathological condition characterized by sarcopenia, adipose tissue depletion, and progressive weight loss. CC is driven by multiple factors such as anorexia, excessive catabolism, elevated energy expenditure by growing tumor mass, and inflammatory mediators released by cancer cells and surrounding tissues. In addition, endocrine system, systemic metabolism, and central nervous system (CNS) perturbations in combination with cachexia mediators elicit exponential elevation in catabolism and reduced anabolism in skeletal muscle, adipose tissue, and cardiac muscle. At the molecular level, mechanisms of CC include inflammation, reduced protein synthesis, and lipogenesis, elevated proteolysis and lipolysis along with aggravated toxicity and complications of chemotherapy. Furthermore, CC is remarkably associated with intolerance to anti-neoplastic therapy, poor prognosis, and increased mortality with no established standard therapy. In this context, we discuss the spatio-temporal changes occurring in the various stages of CC and highlight the imbalance of host metabolism. We provide how multiple factors such as proteasomal pathways, inflammatory mediators, lipid and protein catabolism, glucocorticoids, and in-depth mechanisms of interplay between inflammatory molecules and CNS can trigger and amplify the cachectic processes. Finally, we highlight current diagnostic approaches and promising therapeutic interventions for CC.

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“… 44 Furthermore, our recent data show plasma-derived proteins such as Serum Amyloid A1 (SAA1) content was exclusively higher in mice with LLC-induced cachexia even when compared to models of disuse-induced muscle atrophy. 45 However, it should be noted that biomarkers may differ depending on the type of cancer. 46 More recently, clinical trials have been conducted to identify novel biomarkers for CC in humans.…”

Section: Cancer Cachexia Patient Demographics and Clinical Progressionmentioning

confidence: 99%

Development and progression of cancer cachexia: Perspectives from bench to bedside

Lim

Brown

Washington

et al. 2020

Sports Medicine and Health Science

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Cancer cachexia (CC) is a devastating syndrome characterized by weight loss, reduced fat mass and muscle mass that affects approximately 80% of cancer patients and is responsible for 22%–30% of cancer-associated deaths. Understanding underlying mechanisms for the development of CC are crucial to advance therapies to treat CC and improve cancer outcomes. CC is a multi-organ syndrome that results in extensive skeletal muscle and adipose tissue wasting; however, CC can impair other organs such as the liver, heart, brain, and bone as well. A considerable amount of CC research focuses on changes that occur within the muscle, but cancer-related impairments in other organ systems are understudied. Furthermore, metabolic changes in organ systems other than muscle may contribute to CC. Therefore, the purpose of this review is to address degenerative mechanisms which occur during CC from a whole-body perspective. Outlining the information known about metabolic changes that occur in response to cancer is necessary to develop and enhance therapies to treat CC. As much of the current evidences in CC are from pre-clinical models we should note the majority of the data reviewed here are from preclinical models.

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Comparative plasma proteomics in muscle atrophy during cancer‐cachexia and disuse: The search for atrokines

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 20 publications

References 50 publications

Plasma proteome profiling of healthy subjects undergoing bed rest reveals unloading‐dependent changes linked to muscle atrophy

Plasma proteome profiling of healthy subjects undergoing bed rest reveals unloading‐dependent changes linked to muscle atrophy

Tumor cell anabolism and host tissue catabolism-energetic inefficiency during cancer cachexia

Development and progression of cancer cachexia: Perspectives from bench to bedside

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