Multiplatform plasma fingerprinting in cancer cachexia: a pilot observational and translational study

BACKGROUND: Cachexia is a metabolic syndrome that affects up to 50–80% of cancer patients. The pathophysiology is characterized by a variable combination of reduced food intake and abnormal metabolism, including systemic inflammation and negative protein and energy balance. Despite its high clinical significance, defined diagnostic criteria and established therapeutic strategies are lacking. The ‘omics’ technologies provide a global view of biological systems. We hypothesize that blood‐based metabolomics might identify findings in cachectic patients that could provide clues to gain knowledge on its pathophysiology, and eventually postulate new therapeutic strategies. METHODS: This is a cross‐sectional observational study in two cohorts of cancer patients, with and without cachexia. Patients were consecutively recruited from routine clinical practice of a General Oncology Department at ‘12 de Octubre’ University Hospital. Selected clinical and biochemical features were collected. Blood metabolite fingerprinting was performed using three analytical platforms, gas chromatography coupled to mass spectrometry (GC–MS), capillary electrophoresis coupled to mass spectrometry (CE–MS), and liquid chromatography coupled to mass spectrometry (LC–MS). Besides, we performed pathway‐based metabolite analyses to obtain more information on biological functions. RESULTS: A total of 15 subjects were included in this study, 8 cachectic and 7 non‐cachectic patients. Metabolomic analyses were able to correctly classify their samples in 80% (GC–MS), 97% (CE–MS), 96% [LC–MS (positive mode)], and 89% [LC–MS (negative mode)] of the cases. The most prominent metabolic alteration in plasma of cachectic patients was the decrease of amino acids and derivatives [especially arginine, tryptophan, indolelactic acid, and threonine, with 0.4‐fold change (FC) compared with non‐cachectic patients], along with the reduction of glycerophospholipids [mainly lysophosphatidylcholines(O‐16:0) and lysophosphatidylcholines(20:3) sn‐1, FC = 0.1] and sphingolipids [SM(d30:0), FC = 0.5]. The metabolite with the highest increase was cortisol (FC = 1.6). Such alterations suggest a role of the following metabolic pathways in the pathophysiology of cancer cachexia: arginine and proline metabolism; alanine, aspartate, and glutamate metabolism; phenylalanine metabolism; lysine degradation; aminoacyl‐tRNA biosynthesis; fatty acid elongation in mitochondria; tricarboxylic acids cycle; among others. CONCLUSIONS: These findings suggest that plasma amino acids and lipids profiling has great potential to find the mechanisms involved in the pathogenesis of cachexia. Metabolic profiling of plasma from cancer patients show differences between cachexia and non‐cachexia in amino acids and lipids that might be related to mechanisms involved in its pathophysiology. A better understanding of these mechanisms might identify novel therapeutic approaches to palliate this unmet medical condition.