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.

To study the role of c-Src in breast cancer tumorigenesis, we generated a cell line derived from MCF7 carrying an inducible dominant negative c-Src (c-SrcDN: K295M/Y527F) under tetracycline control (Tet-On system). c-SrcDN expression caused phenotypic changes, relocation of c-Src, Fak, and paxillin, and loss of correct actin fiber assembly. These alterations were coupled to increased Fak-Tyr³⁹⁷ autophosphorylation and to inhibition of Fak-Tyr⁹²⁵, p130^CAS, and paxillin phosphorylation. An increased association of total Src with Fak and a decreased interaction of p130^CAS and p85-PI3K with Fak were also observed. SrcDN inhibited cell attachment, spreading, and migration. Serum and EGF-induced stimulation of cell proliferation and Akt phosphorylation were also significantly reduced by SrcDN, whereas p27^Kip1 expression was increased. Consistently, silencing c-Src expression by siRNA in MCF7 cells significantly reduced cell migration, attachment, spreading and proliferation. Inoculation of MCF7 cells carrying inducible SrcDN to nude mice generated tumors. However, doxycycline administration to mice significantly reduced tumorigenesis, and when doxycycline treatment was installed after tumor development, a significant tumor regression was observed. In both situations, inhibition of tumorigenesis was associated with decreased Ki67 staining and increased apoptosis in tumors. These data undoubtedly demonstrate the relevance of the Src/Fak complex in breast cancer tumorigenesis.

With the completion of the human genome sequence, biomedical sciences have entered in the “omics” era, mainly due to high-throughput genomics techniques and the recent application of mass spectrometry to proteomics analyses. However, there is still a time lag between these technological advances and their application in the clinical setting. Our work is designed to build bridges between high-performance proteomics and clinical routine. Protein extracts were obtained from fresh frozen normal lung and non-small cell lung cancer samples. We applied a phosphopeptide enrichment followed by LC-MS/MS. Subsequent label-free quantification and bioinformatics analyses were performed. We assessed protein patterns on these samples, showing dozens of differential markers between normal and tumor tissue. Gene ontology and interactome analyses identified signaling pathways altered on tumor tissue. We have identified two proteins, PTRF/cavin-1 and MIF, which are differentially expressed between normal lung and non-small cell lung cancer. These potential biomarkers were validated using western blot and immunohistochemistry. The application of discovery-based proteomics analyses in clinical samples allowed us to identify new potential biomarkers and therapeutic targets in non-small cell lung cancer.

Squamous cell lung cancer (SCC) and adenocarcinoma are the most common histological subtypes of non-small cell lung cancer (NSCLC), and have been traditionally managed in the clinic as a single entity. Increasing evidence, however, illustrates the biological diversity of these two histological subgroups of lung cancer, and supports the need to improve our understanding of the molecular basis beyond the different phenotypes if we aim to develop more specific and individualized targeted therapy. The purpose of this study was to identify microRNA (miRNA)-dependent transcriptional regulation differences between SCC and adenocarcinoma histological lung cancer subtypes. In this work, paired miRNA (667 miRNAs by TaqMan Low Density Arrays (TLDA)) and mRNA profiling (Whole Genome 44 K array G112A, Agilent) was performed in tumor samples of 44 NSCLC patients. Nine miRNAs and 56 mRNAs were found to be differentially expressed in SCC versus adenocarcinoma samples. Eleven of these 56 mRNA were predicted as targets of the miRNAs identified to be differently expressed in these two histological conditions. Of them, 6 miRNAs (miR-149, miR-205, miR-375, miR-378, miR-422a and miR-708) and 9 target genes (CEACAM6, CGN, CLDN3, ABCC3, MLPH, ACSL5, TMEM45B, MUC1) were validated by quantitative PCR in an independent cohort of 41 lung cancer patients. Furthermore, the inverse correlation between mRNAs and microRNAs expression was also validated. These results suggest miRNA-dependent transcriptional regulation differences play an important role in determining key hallmarks of NSCLC, and may provide new biomarkers for personalized treatment strategies.