@article {445,
	title = {Serum metabolomic profiling facilitates the non-invasive identification of metabolic biomarkers associated with the onset and progression of non-small cell lung cancer.},
	journal = {Oncotarget},
	volume = {7},
	year = {2016},
	month = {2016 Mar 15},
	pages = {12904-16},
	abstract = {<p>Lung cancer (LC) is responsible for most cancer deaths. One of the main factors contributing to the lethality of this disease is the fact that a large proportion of patients are diagnosed at advanced stages when a clinical intervention is unlikely to succeed. In this study, we evaluated the potential of metabolomics by 1H-NMR to facilitate the identification of accurate and reliable biomarkers to support the early diagnosis and prognosis of non-small cell lung cancer (NSCLC).We found that the metabolic profile of NSCLC patients, compared with healthy individuals, is characterized by statistically significant changes in the concentration of 18 metabolites representing different amino acids, organic acids and alcohols, as well as different lipids and molecules involved in lipid metabolism. Furthermore, the analysis of the differences between the metabolic profiles of NSCLC patients at different stages of the disease revealed the existence of 17 metabolites involved in metabolic changes associated with disease progression.Our results underscore the potential of metabolomics profiling to uncover pathophysiological mechanisms that could be useful to objectively discriminate NSCLC patients from healthy individuals, as well as between different stages of the disease. </p>},
	keywords = {Adult, Aged, Biomarkers, Tumor, Carcinoma, Non-Small-Cell Lung, Disease Progression, Female, Humans, Lung Neoplasms, Male, metabolomics, Middle Aged, Proton Magnetic Resonance Spectroscopy},
	issn = {1949-2553},
	doi = {10.18632/oncotarget.7354},
	author = {Puchades-Carrasco, Leonor and Jantus-Lewintre, Eloisa and P{\'e}rez-Rambla, Clara and Garcia-Garcia, Francisco and Lucas, Rut and Calabuig, Silvia and Blasco, Ana and Dopazo, Joaquin and Camps, Carlos and Pineda-Lucena, Antonio}
}
@article {460,
	title = {A Pan-Cancer Catalogue of Cancer Driver Protein Interaction Interfaces.},
	journal = {PLoS Comput Biol},
	volume = {11},
	year = {2015},
	month = {2015 Oct},
	pages = {e1004518},
	abstract = {<p>Despite their importance in maintaining the integrity of all cellular pathways, the role of mutations on protein-protein interaction (PPI) interfaces as cancer drivers has not been systematically studied. Here we analyzed the mutation patterns of the PPI interfaces from 10,028 proteins in a pan-cancer cohort of 5,989 tumors from 23 projects of The Cancer Genome Atlas (TCGA) to find interfaces enriched in somatic missense mutations. To that end we use e-Driver, an algorithm to analyze the mutation distribution of specific protein functional regions. We identified 103 PPI interfaces enriched in somatic cancer mutations. 32 of these interfaces are found in proteins coded by known cancer driver genes. The remaining 71 interfaces are found in proteins that have not been previously identified as cancer drivers even that, in most cases, there is an extensive literature suggesting they play an important role in cancer. Finally, we integrate these findings with clinical information to show how tumors apparently driven by the same gene have different behaviors, including patient outcomes, depending on which specific interfaces are mutated. </p>},
	keywords = {Animals, Base Sequence, Biomarkers, Tumor, Catalogs as Topic, Chromosome Mapping, Computer Simulation, DNA Mutational Analysis, Genetic Predisposition to Disease, Humans, Models, Genetic, Molecular Sequence Data, mutation, Neoplasm Proteins, Neoplasms, Polymorphism, Single Nucleotide, Protein Interaction Mapping, Signal Transduction},
	issn = {1553-7358},
	doi = {10.1371/journal.pcbi.1004518},
	author = {Porta-Pardo, Eduard and Garc{\'\i}a-Alonso, Luz and Hrabe, Thomas and Dopazo, Joaquin and Godzik, Adam}
}
