Cancer patients display systemic inflammation, which leads to an increase in protein catabolism, thus promoting the release of free amino acids to further support metabolism and remodelling of muscle proteins. Inflammation associated with tumor growth leads to malnutrition, a factor that increases the risk of developing cachexia. With cancer-induced cachexia, nutritional interventions have gained traction as a preventative method to manage this condition. Currently, cancer consensus recommendations suggest a protein intake above 1.0 g/kg.day-1 up to 2.0 g/k.day-1 for cancer patients, although an ideal amount for some amino acids in isolation has yet to be determined. Due to controversy in the literature regarding the benefits of the biochemical mechanisms of various muscle mass supplements, such as L-leucine (including whey protein and BCAA), β-hydroxy-beta-methyl butyrate (HMβ), arginine, glutamine and creatine, several studies have carefully examined their effects. L-leucine and its derivatives appear to regulate protein synthesis by direct or indirect activation of the mTORC1 pool of kinases, further promoting muscle protein balance. Arginine and glutamine may act by reducing inflammation and infection progression, thus promoting improvements in food intake. Creatine exerts anabolic activity, acting as an immediate energy substrate to support muscle contraction further increasing lean mass, mainly due to greater water uptake by the muscle. In this narrative review, we highlighted the main findings regarding protein consumption and amino acids to mitigate cancer-induced skeletal muscle depletion.

Bioelectrical impedance analysis (BIA) and anthropometry are considered alternatives to well-established reference techniques for assessing body composition. In team sports, the percentage of fat mass (FM%) is one of the most informative parameters, and a wide range of predictive equations allow for its estimation through both BIA and anthropometry. Although it is not clear which of these two techniques is more accurate for estimating FM%, the choice of the predictive equation could be a determining factor. The present study aimed to examine the validity of BIA and anthropometry in estimating FM% with different predictive equations, using dual X-ray absorptiometry (DXA) as a reference, in a group of futsal players. A total of 67 high-level male futsal players (age 23.7 ± 5.4 years) underwent BIA, anthropometric measurements, and DXA scanning. Four generalized, four athletic, and two sport-specific predictive equations were used for estimating FM% from raw bioelectric and anthropometric parameters. DXA-derived FM% was used as a reference. BIA-based generalized equations overestimated FM% (ranging from 1.13 to 2.69%, p < 0.05), whereas anthropometry-based generalized equations underestimated FM% in the futsal players (ranging from −1.72 to −2.04%, p < 0.05). Compared to DXA, no mean bias (p > 0.05) was observed using the athletic and sport-specific equations. Sport-specific equations allowed for more accurate and precise FM% estimations than did athletic predictive equations, with no trend (ranging from r = −0.217 to 0.235, p > 0.05). Regardless of the instrument, the choice of the equation determines the validity in FM% prediction. In conclusion, BIA and anthropometry can be used interchangeably, allowing for valid FM% estimations, provided that athletic and sport-specific equations are applied.