Dataset Information

Integrated genomic and proteomic analyses identify stimulus-dependent distinct molecular changes associated with skeletal muscle wasting

ABSTRACT: Skeletal muscle wasting is a debilitating condition that occurs with aging and with many diseases, but the underlying mechanisms are incompletely understood. Previous work determined that common transcriptional changes occur in skeletal muscle during atrophy induced by different stimuli. However, whether this holds true at the proteome level remains largely unexplored. Here, we find that, contrary to this earlier model, distinct atrophic stimuli (corticosteroids, cancer, and aging) induce largely different mRNA and protein changes during muscle wasting in mice. Moreover, there is widespread transcriptome-proteome disconnect. Consequently, atrophy markers (atrogenes) identified in earlier microarray-based studies do not emerge from these proteomic surveys as the most relevantly associated with atrophy. Based on these analyses, we identify atrophy-regulated proteins (here defined as “atroproteins”) such as the myokine CCN1/Cyr61, which we find regulates myofiber type switching during sarcopenia. Altogether, these integrated analyses indicate that different catabolic stimuli induce muscle wasting via largely distinct mechanisms.

ORGANISM(S): Mus musculus

PROVIDER: GSE159952 | GEO | 2021/10/22

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Background Loss of skeletal muscle mass in advanced cancer is recognized as an independent predictor of mortality. Mechanisms involved in this wasting process and parameters for early diagnosis are still lacking. As skeletal muscle is considered as a secretory organ, the aim of this present experimental work was to characterize the changes in muscle proteome and secretome associated with cancer-induced cachexia to better understand cellular mechanisms involved in this wasting process and to identify secreted proteins which might reflect the ongoing muscle atrophy process. Methods We investigated first the changes in the muscle proteome associated with cancer-induced cachexia by using differential label-free proteomic analysis on muscle of the C26 mouse model. The differentially abundant proteins were submitted to sequential bioinformatic secretomic analysis in order to identify potentially secreted proteins. Selected reaction monitoring and Western blotting were used to verify the presence of candidate proteins at the circulating level. Their muscle source was demonstrated by assessing their gene expression in skeletal muscle and in cultured myotubes. Finally, we also investigated their regulation in muscle cells. Alterations in several molecular pathways potentially involved in muscle atrophy were highlighted using Gene ontology enrichment analyses. Results Our results revealed a dramatic increased production (2-to 25-fold) by the muscle of several acute phase reactants (APR: Haptoglobin, Serpina3n, Complement C3, Serum amyloid A1) which are also released in the circulation during C26 cancer cachexia. Their production was confirmed in other preclinical models of cancer cachexia as well as in cancer patients. The muscular origin of these APR was demonstrated by their increased expression in skeletal muscle and myotubes. Glucocorticoids and pro-inflammatory cytokines contribute directly to their increased expression in muscle cells in vitro, while the role of IL-6 in the muscular induction of these APR was demonstrated in vivo. Conclusions Cancer is associated with marked changes in muscle secretome during muscle wasting. Our study demonstrates a marked increased production of APR by skeletal muscle in pre-clinical models of cancer cachexia and in cancer patients. Further studies are required to unravel the potential role of these proteins in muscle atrophy and their interest as biomarkers of cancer cachexia.

Dataset Information

Integrated genomic and proteomic analyses identify stimulus-dependent distinct molecular changes associated with skeletal muscle wasting

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets