Background Loss of muscle mass worsens many diseases such as cancer and renal failure, contributes to the frailty syndrome , and is associated with an increased risk of death. Studies conducted on animal models have revealed the preponderant role of muscle proteolysis and in particular the activation of the ubiquitin proteasome system (UPS). Studies conducted in humans remain scarce, especially within renal deficiency. Whether a shared atrophying programme exists independently of the nature of the disease remains to be established. The aim of this work was to identify common modifications at the transcriptomic level or the proteomic level in atrophying skeletal muscles from cancer and renal failure patients. Methods Muscle biopsies were performed during scheduled interventions in early-stage (no treatment and no detectable muscle loss) lung cancer (LC), chronic haemodialysis (HD), or healthy (CT) patients (n = 7 per group; 86% male; 69.6 ± 11.4, 67.9 ± 8.6, and 70.2 ± 7.9 years P > 0.9 for the CT, LC, and HD groups, respectively). Gene expression of members of the UPS, autophagy, and apoptotic systems was measured by quantitative real-time PCR. A global analysis of the soluble muscle proteome was conducted by shotgun proteomics for investigating the processes altered. Results We found an increased expression of several UPS and autophagy-related enzymes in both LC and HD patients. The E3 ligases MuRF1 (+56 to 78%, P < 0.01), MAFbx (+68 to 84%, P = 0.02), Hdm2 (+37 to 59%, P = 0.02), and MUSA1/Fbxo30 (+47 to 106%, P = 0.01) and the autophagy-related genes CTPL (+33 to 47%, P = 0.03) and SQSTM1 (+47 to 137%, P < 0.01) were overexpressed. Mass spectrometry identified >1700 proteins, and principal component analysis revealed three differential proteomes that matched to the three groups of patients. Orthogonal partial least square discriminant analysis created a model, which distinguished the muscles of diseased patients (LC or HD) from those of CT subjects. Proteins that most contributed to the model were selected. Functional analysis revealed up to 238 proteins belonging to nine metabolic processes (inflammatory response, proteolysis, cytoskeleton organization, glucose metabolism, muscle contraction, oxidant detoxifica-tion, energy metabolism, fatty acid metabolism, and extracellular matrix) involved in and/or altered by the atrophying programme in both LC and HD patients. This was confirmed by a co-expression network analysis. Conclusions We were able to identify highly similar modifications of several metabolic pathways in patients exhibiting diseases with different aetiologies (early-stage LC vs. long-term renal failure). This strongly suggests that a common atrophying programme exists independently of the disease in human.