Metabolomic Methods to Predict Cancer-Associated Skeletal Muscle Wasting from Profiles of Urinary Metabolites

Abstract

It is known that cachexia is a cancer-associated muscle wasting and reduction in the function status due to treatment especially chemotherapy and in life expectancy, to assess cachexia muscle loss there are many methods as Computed Tomography (CT) scan which has many disadvantages as high cost, invasive, time consuming and cannot detect early stages of muscle wasting [1].

This novel approach uses single-time point urinary metabolite profiles for determining whether the patient is subjected to muscle wasting by analysis of 93 random urine samples from patients with cancer using 2 successive CT images by assessing of lumbar skeletal muscle area by cubic centimeter to estimate the rate of muscle change per time for every patient.

The average muscle change over time was -4.71% in 100 days in the muscle-losing group and 3.91% in 100 days in the control group. Bivariate statistics identified metabolites to muscle wasting including constituents and metabolites of muscle as creatine and creatinine, amino acids as serine, threonine, glutamic acid, isoleucine and valine.

These results suggest that urine analysis of a single random urine sample is cheap, fast, and non-invasive tool to screen muscle loss and it is useful to clarify prediction of related metabolic conditions possible with methodology presented.

The metabolomics methods used in this article are Univariate analysis T-test, correlation analysis, principal component analysis and heatmap clustering.