@article {446,
	title = {Integrating transcriptomic and metabolomic analysis to understand natural leaf senescence in sunflower.},
	journal = {Plant Biotechnol J},
	volume = {14},
	year = {2016},
	month = {2016 Feb},
	pages = {719-34},
	abstract = {<p>Leaf senescence is a complex process, which has dramatic consequences on crop yield. In sunflower, gap between potential and actual yields reveals the economic impact of senescence. Indeed, sunflower plants are incapable of maintaining their green leaf area over sustained periods. This study characterizes the leaf senescence process in sunflower through a systems biology approach integrating transcriptomic and metabolomic analyses: plants being grown under both glasshouse and field conditions. Our results revealed a correspondence between profile changes detected at the molecular, biochemical and physiological level throughout the progression of leaf senescence measured at different plant developmental stages. Early metabolic changes were detected prior to anthesis and before the onset of the first senescence symptoms, with more pronounced changes observed when physiological and molecular variables were assessed under field conditions. During leaf development, photosynthetic activity and cell growth processes decreased, whereas sucrose, fatty acid, nucleotide and amino acid metabolisms increased. Pathways related to nutrient recycling processes were also up-regulated. Members of the NAC, AP2-EREBP, HB, bZIP and MYB transcription factor families showed high expression levels, and their expression level was highly correlated, suggesting their involvement in sunflower senescence. The results of this study thus contribute to the elucidation of the molecular mechanisms involved in the onset and progression of leaf senescence in sunflower leaves as well as to the identification of candidate genes involved in this process. </p>},
	keywords = {Gas Chromatography-Mass Spectrometry, Gene Expression Profiling, Gene Expression Regulation, Plant, Gene ontology, Genes, Plant, Helianthus, Ions, metabolomics, Oligonucleotide Array Sequence Analysis, Plant Leaves, Principal Component Analysis, RNA, Messenger, Transcription Factors},
	issn = {1467-7652},
	doi = {10.1111/pbi.12422},
	author = {Moschen, Sebasti{\'a}n and Bengoa Luoni, Sof{\'\i}a and Di Rienzo, Julio A and Caro, Mar{\'\i}a Del Pilar and Tohge, Takayuki and Watanabe, Mutsumi and Hollmann, Julien and Gonzalez, Sergio and Rivarola, M{\'a}ximo and Garcia-Garcia, Francisco and Dopazo, Joaquin and Hopp, Horacio Esteban and Hoefgen, Rainer and Fernie, Alisdair R and Paniego, Norma and Fernandez, Paula and Heinz, Ruth A}
}
@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}
}
