03645nas a2200565 4500008004100000022001400041245014000055210006900195260001300264300001200277490000700289520189600296653004202192653003102234653001502265653001902280653002002299653002402319653001902343653003002362653003202392653001502424653001902439653002802458653001002486653001102496653001602507653004402523653001402567653003602581653002702617100002102644700003102665700001502696700001402711700001502725700002202740700001602762700001202778700002302790700001402813700001302827700001902840700002402859700001502883700001402898700001902912700001502931856013302946 2020 eng d a1469-069100aAssociation of a single nucleotide polymorphism in the ubxn6 gene with long-term non-progression phenotype in HIV-positive individuals.0 aAssociation of a single nucleotide polymorphism in the ubxn6 gen c2020 Jan a107-1140 v263 a
OBJECTIVES: The long-term non-progressors (LTNPs) are a heterogeneous group of HIV-positive individuals characterized by their ability to maintain high CD4 T-cell counts and partially control viral replication for years in the absence of antiretroviral therapy. The present study aims to identify host single nucleotide polymorphisms (SNPs) associated with non-progression in a cohort of 352 individuals.
METHODS: DNA microarrays and exome sequencing were used for genotyping about 240 000 functional polymorphisms throughout more than 20 000 human genes. The allele frequencies of 85 LTNPs were compared with a control population. SNPs associated with LTNPs were confirmed in a population of typical progressors. Functional analyses in the affected gene were carried out through knockdown experiments in HeLa-P4, macrophages and dendritic cells.
RESULTS: Several SNPs located within the major histocompatibility complex region previously related to LTNPs were confirmed in this new cohort. The SNP rs1127888 (UBXN6) surpassed the statistical significance of these markers after Bonferroni correction (q = 2.11 × 10). An uncommon allelic frequency of rs1127888 among LTNPs was confirmed by comparison with typical progressors and other publicly available populations. UBXN6 knockdown experiments caused an increase in CAV1 expression and its accumulation in the plasma membrane. In vitro infection of different cell types with HIV-1 replication-competent recombinant viruses caused a reduction of the viral replication capacity compared with their corresponding wild-type cells expressing UBXN6.
CONCLUSIONS: A higher prevalence of Ala31Thr in UBXN6 was found among LTNPs within its N-terminal region, which is crucial for UBXN6/VCP protein complex formation. UBXN6 knockdown affected CAV1 turnover and HIV-1 replication capacity.
10aAdaptor Proteins, Vesicular Transport10aAutophagy-Related Proteins10aCaveolin 110aCohort Studies10aDendritic Cells10aDisease Progression10aGene Frequency10aGene Knockdown Techniques10aGenetic Association Studies10aHeLa Cells10aHIV Infections10aHIV Long-Term Survivors10aHIV-110aHumans10aMacrophages10aOligonucleotide Array Sequence Analysis10aPhenotype10aPolymorphism, Single Nucleotide10awhole exome sequencing1 aDíez-Fuertes, F1 aDe La Torre-Tarazona, H, E1 aCalonge, E1 aPernas, M1 aBermejo, M1 aGarcía-Pérez, J1 aÁlvarez, A1 aCapa, L1 aGarcía-García, F1 aSaumoy, M1 aRiera, M1 aBoland-Auge, A1 aLópez-Galíndez, C1 aLathrop, M1 aDopazo, J1 aSakuntabhai, A1 aAlcamí, J uhttps://www.clinbioinfosspa.es/content/association-single-nucleotide-polymorphism-ubxn6-gene-long-term-non-progression-phenotype02950nas a2200445 4500008004100000022001400041245009500055210006900150260001500219300001400234490000700248520156700255653002101822653002101843653002401864653003001888653004301918653002901961653001101990653002602001653001502027653001302042653001402055653001402069653001402083653001402097653002702111653002702138653001802165653002202183100001802205700002202223700001902245700002202264700002102286700002002307700003102327700002002358856012602378 2018 eng d a1538-744500aGene Expression Integration into Pathway Modules Reveals a Pan-Cancer Metabolic Landscape.0 aGene Expression Integration into Pathway Modules Reveals a PanCa c2018 11 01 a6059-60720 v783 aMetabolic reprogramming plays an important role in cancer development and progression and is a well-established hallmark of cancer. Despite its inherent complexity, cellular metabolism can be decomposed into functional modules that represent fundamental metabolic processes. Here, we performed a pan-cancer study involving 9,428 samples from 25 cancer types to reveal metabolic modules whose individual or coordinated activity predict cancer type and outcome, in turn highlighting novel therapeutic opportunities. Integration of gene expression levels into metabolic modules suggests that the activity of specific modules differs between cancers and the corresponding tissues of origin. Some modules may cooperate, as indicated by the positive correlation of their activity across a range of tumors. The activity of many metabolic modules was significantly associated with prognosis at a stronger magnitude than any of their constituent genes. Thus, modules may be classified as tumor suppressors and oncomodules according to their potential impact on cancer progression. Using this modeling framework, we also propose novel potential therapeutic targets that constitute alternative ways of treating cancer by inhibiting their reprogrammed metabolism. Collectively, this study provides an extensive resource of predicted cancer metabolic profiles and dependencies. Combining gene expression with metabolic modules identifies molecular mechanisms of cancer undetected on an individual gene level and allows discovery of new potential therapeutic targets. .
10aCell Line, Tumor10aCluster Analysis10aDisease Progression10aGene Expression Profiling10aGene Expression Regulation, Neoplastic10aGene Regulatory Networks10aHumans10aKaplan-Meier Estimate10aMetabolome10amutation10aNeoplasms10aOncogenes10aPhenotype10aPrognosis10aRNA, Small Interfering10aSequence Analysis, RNA10aTranscriptome10aTreatment Outcome1 aCubuk, Cankut1 aHidalgo, Marta, R1 aAmadoz, Alicia1 aPujana, Miguel, A1 aMateo, Francesca1 aHerranz, Carmen1 aCarbonell-Caballero, José1 aDopazo, Joaquin uhttps://www.clinbioinfosspa.es/content/gene-expression-integration-pathway-modules-reveals-pan-cancer-metabolic-landscape02610nas a2200397 4500008004100000022001400041245017300055210006900228260001600297300001300313490000600326520129300332653001001625653000901635653002201644653003501666653002401701653001101725653001101736653001901747653000901766653001701775653001601792653004301808100003001851700002801881700002501909700002901934700001501963700002101978700001601999700002002015700001802035700002702053856013202080 2016 eng d a1949-255300aSerum metabolomic profiling facilitates the non-invasive identification of metabolic biomarkers associated with the onset and progression of non-small cell lung cancer.0 aSerum metabolomic profiling facilitates the noninvasive identifi c2016 Mar 15 a12904-160 v73 aLung 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.
10aAdult10aAged10aBiomarkers, Tumor10aCarcinoma, Non-Small-Cell Lung10aDisease Progression10aFemale10aHumans10aLung Neoplasms10aMale10ametabolomics10aMiddle Aged10aProton Magnetic Resonance Spectroscopy1 aPuchades-Carrasco, Leonor1 aJantus-Lewintre, Eloisa1 aPérez-Rambla, Clara1 aGarcia-Garcia, Francisco1 aLucas, Rut1 aCalabuig, Silvia1 aBlasco, Ana1 aDopazo, Joaquin1 aCamps, Carlos1 aPineda-Lucena, Antonio uhttps://www.clinbioinfosspa.es/content/serum-metabolomic-profiling-facilitates-non-invasive-identification-metabolic-biomarkers03760nas a2200625 4500008004100000022001400041245009800055210006900153260001600222300001100238490000600249520178700255653001002042653004902052653001102101653002102112653004902133653002502182653002902207653002402236653002802260653001102288653001902299653003802318653003402356653001302390653002302403653001102426653001502437653001102452653003602463653003702499653002902536653003802565653002002603653002002623653002002643653001702663100002102680700002002701700002402721700002702745700002102772700002202793700002202815700002502837700001702862700002002879700002102899700001902920700001902939700002102958700002602979856012903005 2010 eng d a1932-620300aExploring the link between germline and somatic genetic alterations in breast carcinogenesis.0 aExploring the link between germline and somatic genetic alterati c2010 Nov 22 ae140780 v53 aRecent genome-wide association studies (GWASs) have identified candidate genes contributing to cancer risk through low-penetrance mutations. Many of these genes were unexpected and, intriguingly, included well-known players in carcinogenesis at the somatic level. To assess the hypothesis of a germline-somatic link in carcinogenesis, we evaluated the distribution of somatic gene labels within the ordered results of a breast cancer risk GWAS. This analysis suggested frequent influence on risk of genetic variation in loci encoding for "driver kinases" (i.e., kinases encoded by genes that showed higher somatic mutation rates than expected by chance and, therefore, whose deregulation may contribute to cancer development and/or progression). Assessment of these predictions using a population-based case-control study in Poland replicated the association for rs3732568 in EPHB1 (odds ratio (OR) = 0.79; 95% confidence interval (CI): 0.63-0.98; P(trend) = 0.031). Analyses by early age at diagnosis and by estrogen receptor α (ERα) tumor status indicated potential associations for rs6852678 in CDKL2 (OR = 0.32, 95% CI: 0.10-1.00; P(recessive) = 0.044) and rs10878640 in DYRK2 (OR = 2.39, 95% CI: 1.32-4.30; P(dominant) = 0.003), and for rs12765929, rs9836340, rs4707795 in BMPR1A, EPHA3 and EPHA7, respectively (ERα tumor status P(interaction)<0.05). The identification of three novel candidates as EPH receptor genes might indicate a link between perturbed compartmentalization of early neoplastic lesions and breast cancer risk and progression. Together, these data may lay the foundations for replication in additional populations and could potentially increase our knowledge of the underlying molecular mechanisms of breast carcinogenesis.
10aAdult10aBone Morphogenetic Protein Receptors, Type I10aBreast10aBreast Neoplasms10aCalcium-Calmodulin-Dependent Protein Kinases10aCase-Control Studies10aCyclin-Dependent Kinases10aDisease Progression10aEstrogen Receptor alpha10aFemale10aGene Frequency10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aGenotype10aGerm-Line Mutation10aHumans10aOdds Ratio10aPoland10aPolymorphism, Single Nucleotide10aProtein Serine-Threonine Kinases10aProtein-Tyrosine Kinases10aReceptor Protein-Tyrosine Kinases10aReceptor, EphA310aReceptor, EphA710aReceptor, EphB110aRisk Factors1 aBonifaci, Núria1 aGórski, Bohdan1 aMasojć, Bartlomiej1 aWokołorczyk, Dominika1 aJakubowska, Anna1 aDębniak, Tadeusz1 aBerenguer, Antoni1 aMusach, Jordi, Serra1 aBrunet, Joan1 aDopazo, Joaquin1 aNarod, Steven, A1 aLubiński, Jan1 aLázaro, Conxi1 aCybulski, Cezary1 aPujana, Miguel, Angel uhttps://www.clinbioinfosspa.es/content/exploring-link-between-germline-and-somatic-genetic-alterations-breast-carcinogenesis