Analysis of the metabolic proteome of lung adenocarcinomas by reverse-phase protein arrays (RPPA) emphasizes mitochondria as targets for therapy.

Lung cancer is the leading cause of cancer-related death worldwide despite the success of therapies targeting oncogenic drivers and immune-checkpoint inhibitors. Although metabolic enzymes offer additional targets for therapy, the precise metabolic proteome of lung adenocarcinomas is unknown, hampering its clinical translation. Herein, we used Reverse Phase Protein Arrays to quantify the changes in enzymes of glycolysis, oxidation of pyruvate, fatty acid metabolism, oxidative phosphorylation, antioxidant response and protein oxidative damage in 128 tumors and paired non-tumor adjacent tissue of lung adenocarcinomas to profile the proteome of metabolism. Steady-state levels of mitochondrial proteins of fatty acid oxidation, oxidative phosphorylation and of the antioxidant response are independent predictors of survival and/or of disease recurrence in lung adenocarcinoma patients. Next, we addressed the mechanisms by which the overexpression of ATPase Inhibitory Factor 1, the physiological inhibitor of oxidative phosphorylation, which is an independent predictor of disease recurrence, prevents metastatic disease. We highlight that IF1 overexpression promotes a more vulnerable and less invasive phenotype in lung adenocarcinoma cells. Finally, and as proof of concept, the therapeutic potential of targeting fatty acid assimilation or oxidation in combination with an inhibitor of oxidative phosphorylation was studied in mice bearing lung adenocarcinomas. The results revealed that this therapeutic approach significantly extended the lifespan and provided better welfare to mice than cisplatin treatments, supporting mitochondrial activities as targets of therapy in lung adenocarcinoma patients.

Different mitochondrial genetic defects exhibit the same protein signature of metabolism in skeletal muscle of PEO and MELAS patients: A role for oxidative stress.

A major challenge in mitochondrial diseases (MDs) is the identification of biomarkers that could inform of the mechanisms involved in the phenotypic expression of genetic defects. Herein, we have investigated the protein signature of metabolism and of the antioxidant response in muscle biopsies of clinically and genetically diagnosed patients with Progressive External Ophthalmoplegia due to single large-scale (PEO-sD) or multiple (PEO-mD) deletions of mtDNA and Mitochondrial Encephalopathy Lactic Acidosis and Stroke-like episode (MELAS) syndrome, and healthy donors. A high-throughput immunoassay technique that quantitates the expression of relevant proteins of glycolysis, glycogenolysis, pentose phosphate pathway, oxidative phosphorylation, pyruvate and fatty acid oxidation, tricarboxylic acid cycle and the antioxidant response in two large independent and retrospectively collected cohorts of PEO-sD, PEO-mD and MELAS patients revealed that despite the heterogeneity of the genetic alterations, the three MDs showed the same metabolic signatures in both cohorts of patients, which were highly divergent from those of healthy individuals. Linear Discriminant Analysis and Support Vector Machine classifier provided a minimum of four biomarkers to discriminate healthy from pathological samples. Regardless of the induction of a large number of enzymes involved in ameliorating oxidative stress, the down-regulation of mitochondrial superoxide dismutase (SOD2) and catalase expression favored the accumulation of oxidative damage in patients' proteins. Down-regulation of SOD2 and catalase expression in MD patients is not due to relevant changes in the availability of their mRNAs, suggesting that oxidative stress regulates the expression of the two enzymes post-transcriptionally. We suggest that SOD2 and catalase could provide specific targets to improve the detoxification of reactive oxygen species that affects muscle proteins in these patients.

MM-ISMSA: An Ultrafast and Accurate Scoring Function for Protein-Protein Docking.

An ultrafast and accurate scoring function for protein-protein docking is presented. It includes (1) a molecular mechanics (MM) part based on a 12-6 Lennard-Jones potential; (2) an electrostatic component based on an implicit solvent model (ISM) with individual desolvation penalties for each partner in the protein-protein complex plus a hydrogen bonding term; and (3) a surface area (SA) contribution to account for the loss of water contacts upon protein-protein complex formation. The accuracy and performance of the scoring function, termed MM-ISMSA, have been assessed by (1) comparing the total binding energies, the electrostatic term, and its components (charge-charge and individual desolvation energies), as well as the per residue contributions, to results obtained with well-established methods such as APBSA or MM-PB(GB)SA for a set of 1242 decoy protein-protein complexes and (2) testing its ability to recognize the docking solution closest to the experimental structure as that providing the most favorable total binding energy. For this purpose, a test set consisting of 15 protein-protein complexes with known 3D structure mixed with 10 decoys for each complex was used. The correlation between the values afforded by MM-ISMSA and those from the other methods is quite remarkable (r(2) ∼ 0.9), and only 0.2-5.0 s (depending on the number of residues) are spent on a single calculation including an all vs all pairwise energy decomposition. On the other hand, MM-ISMSA correctly identifies the best docking solution as that closest to the experimental structure in 80% of the cases. Finally, MM-ISMSA can process molecular dynamics trajectories and reports the results as averaged values with their standard deviations. MM-ISMSA has been implemented as a plugin to the widely used molecular graphics program PyMOL, although it can also be executed in command-line mode. MM-ISMSA is distributed free of charge to nonprofit organizations.