Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “profiling”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 919 records · Page 51Linked to original sources
PubMed2006

NF1 mutation rather than individual genetic variability is the main determinant of the NF1-transcriptional profile of mutations affecting splicing.

A significant number of neurofibromatosis type 1 (NF1) mutations result in exon skipping. The majority of these mutations do not occur in the canonical splice sites and can produce different aberrant transcripts whose proportions have not been well studied. It has been hypothesized that differences in the mutation-determined NF1-transcriptional profile could partially explain disease variability among patients bearing the same NF1 splice defect. In order to gain insight into these aspects, we analyzed the proportion of the different transcripts generated by nine NF1-splicing mutations in 30 patients. We assessed the influence of the mutation in the NF1-related transcriptional profiles and investigated the existence of individual differences in a global manner. We analyzed potential differences in tissue-specific transcriptional profiles and evaluated the influence of sample processing and mRNA nonsense-mediated decay (NMD). Small transcriptional differences were found in neurofibromas and neurofibroma-derived Schwann cells (SC) compared to blood. We also detected a higher cell culture-dependent NMD. We observed that mutation per se explains 93.5% of the profile variability among mutations studied. However, despite the importance of mutation in determining the proportion of NF1 transcripts generated, we found certain variability among patients with the same mutation. From our results, it seems that genetic factors influencing RNA processing play a minor role in determining the NF1-transcriptional profile. Nevertheless neurofibromin studies would clarify whether these small differences translate into significant functional changes that could explain the great clinical expressivity observed in the disease or any of the disease-related traits.

Alleles↗
PubMed2002

Profiling gene expression using onto-express.

Gene expression profiles obtained through microarray or data mining analyses often exist as vast data strings. To interpret the biology of these genetic profiles, investigators must analyze this data in the context of other information such as the biological, biochemical, or molecular function of the translated proteins. This is particularly challenging for a human analyst because large quantities of less than relevant data often bury such information. To address this need we implemented an automated routine, called Onto-Express (http://vortex.cs.wayne.edu:8080), to systematically translate genetic fingerprints into functional profiles. Using strings of accession or cluster identification numbers, Onto-Express searches the public databases and returns tables that correlate expression profiles with the cytogenetic locations, biochemical and molecular functions, biological processes, cellular components, and cellular roles of the translated proteins. The profiles created by Onto-Express fundamentally increase the value of gene expression analyses by facilitating the translation of quantitative value sets to records that contain biological implications.

Gene Expression Profiling↗
PubMed2006

Expression profile analysis of microRNA (miRNA) in mouse central nervous system using a new miRNA detection system that examines hybridization signals at every step of washing.

MicroRNAs (miRNAs) are small noncoding RNAs, with a length of 19 to 23 nucleotides, which appear to be involved in the regulation of gene expression by inhibiting the translation of messenger RNA. Expression profile analysis of miRNAs is necessary to understand their complex role in the regulation of gene expression during the development and differentiation of cells and in various tissues. We describe here a detection system for miRNA expression profiles, using a new type of DNA chip and fluorescent labeled cellular RNAs, which allows real-time detection of hybridization signals at every step of washing and results in highly reproducible miRNA expression profiles. Using the system, we investigated the expression profiles of miRNA in the mouse central nervous system (CNS), namely the spinal cord, medulla oblongata, pons, cerebellum, midbrain, diencephalons, and cerebral hemispheres. The results indicated that although the CNS subregions expressed similar miRNA genes, the expression levels of the miRNAs varied among the subregions, suggesting that the CNS subregions specialized for different functions possess different expression profiles of miRNAs.

Animals↗
PubMed2006

Current challenges and developments in GC-MS based metabolite profiling technology.

Gas chromatography-mass spectrometry (GC-MS) based metabolite profiling of biological samples is one of the key technologies for metabolite profiling and substantially contributes to our understanding of the metabolome. While the technology is in increasing use it is challenged with novel demands. Increasing the number of metabolite identifications within existing profiling platforms is prerequisite for a substantially improved scope of profiling studies. Clear, reproducible strategies for metabolite identification and exchange of identifications between laboratories will facilitate further developments, such as the extension of profiling technologies towards metabolic signals and other technically demanding trace compound analysis. Using GC-MS technology as an example the concept of mass spectral tags (MSTs) is presented. A mass spectral tag is defined by the chemometric properties, molecular mass to charge ratio, chromatographic retention index and an induced mass fragmentation pattern such as an electron impact mass spectrum (EI-MS) or secondary fragmentation (MS(2)). These properties if properly documented will allow identification of hitherto non-identified MSTs by standard addition experiments of authenticated reference substances even years after first MST description. Strategies are discussed for MST identification and enhanced MST characterization utilizing experimental schemes such as in vivo stable isotope labelling of whole organisms and open access information distribution, for example the GMG internet platform initiated in 2004 (GMD, http://www.csbdb.mpimp-golm.mpg.de/gmd.html).

Carbohydrate Metabolism↗
PubMed2004

Expression profiling of non-small cell lung carcinoma identifies metastatic genotypes based on lymph node tumor burden.

OBJECTIVE: This study hypothesized that non-small cell lung carcinoma cells from primary tumors isolated by laser capture microdissection would exhibit gene expression profiles associated with graded lymph node metastatic cell burden. METHODS: Non-small cell lung carcinoma tumors (n = 15) were classified on the basis of nodal metastatic cell burden by 2 methods, obtaining 3 groups: no metastasis, micrometastasis, and overt metastasis. We then performed microarray analysis on microdissected primary tumor cells and identified gene expression profiles associated with graded nodal tumor burden using a correlation-based selection algorithm coupled with cross-validation analysis. Hierarchical clustering showed the regrouping of tumor specimens; the classification inference was assessed with Fisher's exact test. We verified data for certain genes by using another independent assay. RESULTS: The 15 specimens clustered into 3 groups: cluster A predominated in specimens with overt nodal metastasis; cluster B had more specimens with nodal micrometastases; and cluster C included only specimens without nodal metastases. Cluster assignment was based on a validated 75-gene discriminatory subset. Notably, genes not previously associated with positive non-small cell lung carcinoma lymph node status were encountered in the profiling analysis. CONCLUSIONS: Microdissection, combined with microarray analysis, is a potentially powerful method to characterize the molecular profile of tumor cells. The 75-gene expression profiles representative of clusters A and B may define genotypes prone to metastasize. Overall, the 3 groups of tumor specimens clustered separately, suggesting that this approach may identify graded metastatic propensity. Further, genes singled out in clustering may yield insights into underlying metastatic mechanisms and may represent new therapeutic targets.

Carcinoma, Non-Small-Cell Lung↗
PubMed2006

Characterization of cell-type specific profiles in tissues and isolated cells from squamous cell carcinomas of the lung.

Lung cancer accounts for 28% of all cancer deaths, a higher percentage than any other human cancer. Squamous Cell Carcinoma (SqCC) is the most common lung neoplasm and is a tumor that is extensively associated with tobacco use. Despite the association of many genetic alterations with lung cancer, the precise molecular mechanisms of tumorigenesis, for the most part, remain ambiguous. Although many studies of lung cancer have used global transcript profiling approaches designed to uncover genes or pathways that are important in lung tumorigenesis, no strong candidates have emerged. A lack of concurrence amongst these various studies can be attributed, in a large part, to the cellular heterogeneity within lung tissue. We have attempted to reduce this complication by designing a profiling strategy that will minimize the confounding involvement of tissue heterogeneity in gene expression of lung tumors. Specifically, we have profiled transcript expression levels in both isolated cells and tissues from SqCC and normal samples. Our strategy consists of combining and subtracting the input of these various cell types which has produced a unique transcript profile of the squamous carcinoma cell. We then analyzed the data using Pathways Assist analysis software to determine which processes may be involved in SqCC tumorigenesis. The MAP/ERK pathway involved in growth and differentiation was the pathway that was most frequently identified across all comparisons. In addition, biological interaction networks of the SqCC profile identified IL-8 as playing a potentially important role SqCC development.

Adenocarcinoma↗
PubMed2005

Comparison of supervised clustering methods to discriminate genotoxic from non-genotoxic carcinogens by gene expression profiling.

Prediction of the toxic properties of chemicals based on modulation of gene expression profiles in exposed cells or animals is one of the major applications of toxicogenomics. Previously, we demonstrated that by Pearson correlation analysis of gene expression profiles from treated HepG2 cells it is possible to correctly discriminate and predict genotoxic from non-genotoxic carcinogens. Since to date many different supervised clustering methods for discrimination and prediction tests are available, we investigated whether application of the methods provided by the Whitehead Institute and Stanford University improved our initial prediction. Four different supervised clustering methods were applied for this comparison, namely Pearson correlation analysis (Pearson), nearest shrunken centroids analysis (NSC), K-nearest neighbour analysis (KNN) and Weighted voting (WV). For each supervised clustering method, three different approaches were followed: (1) using all the data points for all treatments, (2) exclusion of the samples with marginally affected gene expression profiles and (3) filtering out the gene expression signals that were hardly altered. On the complete data set, NSC, KNN and WV outperformed the Pearson test, but on the reduced data sets no clear difference was observed. Exclusion of samples with marginally affected profiles improved the prediction by all methods. For the various prediction models, gene sets of different compositions were selected; in these 27 genes appeared three times or more. These 27 genes are involved in many different biological processes and molecular functions, such as apoptosis, cell cycle control, regulation of transcription, and transporter activity, many of them related to the carcinogenic process. One gene, BAX, was selected in all 10 models, while ZFP36 was selected in 9, and AHR, MT1E and TTR in 8. Summarising, this study demonstrates that several supervised clustering methods can be used to discriminate certain genotoxic from non-genotoxic carcinogens by gene expression profiling in vitro in HepG2 cells. None of the methods clearly outperforms the others.

Carcinogens↗
PubMed2004

Gene expression profiling of mesoblastic nephroma and Wilms tumors--comparison and clinical implications.

OBJECTIVES: To better understand the molecular mechanisms in the tumorigenesis and progression of mesoblastic nephroma (MN), we studied its gene expression profiles. MN is the most common tumor of the neonatal kidney. It occurs in a younger age group than the Wilms tumor (WT). To date, very little is known about the etiology and pathogenesis of MN. METHODS: Using microarrays containing 22,943 cDNA, we analyzed the expression profiles of MN and compared its expression profiles with those of several other types of kidney tumors, including WT. RESULTS: MN has a distinct molecular signature that clusters close to the WT, suggesting that both types of tumor share some similarity in gene expression and biology. When comparing the two profiles closely, we identified a number of genes that are commonly upregulated in both tumors, including insulin-like growth factor 2, thrombospondin 4, and mesenchyme homeo box 1. We also identified a set of genes that distinguish MN from WT, some of which may underlie the difference in their behaviors and can be used as diagnostic markers. Among this group of genes, topoisomerase II-alpha, highly expressed in WTs, is not overexpressed in MN. Immunohistochemical staining of topoisomerase II-alpha in additional cases of WTs and MNs confirmed this distinction further. CONCLUSIONS: The results of our study demonstrated that MN has a distinct gene expression profile and that some of the newly identified genes can be potentially used as novel diagnostic markers.

Antigens, Neoplasm↗
PubMed2003

Liver gene expression profiles of rats treated with clofibric acid: comparison of whole liver and laser capture microdissected liver.

Clofibric acid (CLO) is a peroxisome proliferator (PP) that acts through the peroxisome proliferator activated receptor alpha, leading to hepatocarcinogenesis in rodents. CLO-induced hepatocarcinogenesis is a multi-step process, first transforming normal liver cells into foci. The combination of laser capture microdissection (LCM) and genomics has the potential to provide expression profiles from such small cell clusters, giving an opportunity to understand the process of cancer development in response to PPs. To our knowledge, this is the first evaluation of the impact of the successive steps of LCM procedure on gene expression profiling by comparing profiles from LCM samples to those obtained with non-microdissected liver samples collected after a 1 month CLO treatment in the rat. We showed that hematoxylin and eosin (H&E) staining and laser microdissection itself do not impact on RNA quality. However, the overall process of the LCM procedure affects the RNA quality, resulting in a bias in the gene profiles. Nonetheless, this bias did not prevent accurate determination of a CLO-specific molecular signature. Thus, gene-profiling analysis of microdissected foci, identified by H&E staining may provide insight into the mechanisms underlying non-genotoxic hepatocarcinogenesis in the rat by allowing identification of specific genes that are regulated by CLO in early pre-neoplastic foci.

Animals↗
PubMed2003

Integrated analysis of transcript profiling and protein sequence data.

Transcript profiling can be used to elucidate the molecular and cellular mechanisms involved in ageing and cancer. A recent study of human gastrointestinal stromal tumours (GISTs) with mutations in the KIT gene, Cancer Res. 61 (2001) 8624 exemplifies a common type of investigation. cDNA microarrays were used to generate measurements for 1987 clones in two types of tissues: 13 KIT mutation-positive GISTs and 6 spindle cell tumours from locations outside the gastrointestinal tract. Statistical problems associated with such two-class, high-dimensional profiling data include simultaneous classification and relevant feature identification, probabilistic clustering and protein sequence family modelling. Here, the GIST data were reexamined using specific solutions to these problems, namely sparse hyperplanes, nai;ve Bayes models and profile hidden Markov models respectively. The integrated analysis of molecular profiling and sequence data highlighted 6 clones that may be of clinical and experimental interest. The protein encoded by one of these putative biomarkers defined a novel protein family present in diverse eucarya. The family may be involved in chromosome segregation and/or stability. One family member is a potential biomarker identified recently from a retrospective analysis of transcript profiles for sporadic breast cancer samples from patients with poor and good prognosis, Signal Process. (in press).

Amino Acid Sequence↗
PubMed2003

Exploitation of molecular profiling techniques for GM food safety assessment.

Several strategies have been developed to identify unintended alterations in the composition of genetically modified (GM) food crops that may occur as a result of the genetic modification process. These include comparative chemical analysis of single compounds in GM food crops and their conventional non-GM counterparts, and profiling methods such as DNA/RNA microarray technologies, proteomics and metabolite profiling. The potential of profiling methods is obvious, but further exploration of specificity, sensitivity and validation is needed. Moreover, the successful application of profiling techniques to the safety evaluation of GM foods will require linked databases to be built that contain information on variations in profiles associated with differences in developmental stages and environmental conditions.

Consumer Product Safety↗
PubMed2002

Genome-wide transcript profiles in aging and calorically restricted Drosophila melanogaster.

BACKGROUND: We characterized RNA transcript levels for the whole Drosophila genome during normal aging. We compared age-dependent profiles from animals aged under full-nutrient conditions with profiles obtained from animals maintained on a low-calorie medium to determine if caloric restriction slows the aging process. Specific biological functions impacted by caloric restriction were identified using the Gene Ontology annotation. We used the global patterns of expression profiles to test if particular genomic regions contribute differentially to changes in transcript profiles with age and if global disregulation of gene expression occurs during aging. RESULTS: Whole-genome transcript profiles contained a statistically powerful genetic signature of normal aging. Nearly 23% of the genome changed in transcript representation with age. Caloric restriction was accompanied by a slowing of the progression of normal, age-related changes in transcript levels. Many genes, including those associated with stress response and oogenesis, showed age-dependent transcript representation. Caloric restriction resulted in the downregulation of genes primarily involved in cell growth, metabolism, and reproduction. We found no evidence that age-dependent changes in transcription level were confined to genes localized to specific regions of the genome and found no support for widespread disregulation of gene expression with age. CONCLUSIONS: Aging is characterized by highly dynamic changes in the expression of many genes, which provides a powerful molecular description of the normal aging process. Caloric restriction extends life span by slowing down the rate of normal aging. Transcription levels of genes from a wide variety of biological functions and processes are impacted by age and dietary conditions.

Aging↗
PubMed2002

Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling.

Treatment of pediatric acute lymphoblastic leukemia (ALL) is based on the concept of tailoring the intensity of therapy to a patient's risk of relapse. To determine whether gene expression profiling could enhance risk assignment, we used oligonucleotide microarrays to analyze the pattern of genes expressed in leukemic blasts from 360 pediatric ALL patients. Distinct expression profiles identified each of the prognostically important leukemia subtypes, including T-ALL, E2A-PBX1, BCR-ABL, TEL-AML1, MLL rearrangement, and hyperdiploid >50 chromosomes. In addition, another ALL subgroup was identified based on its unique expression profile. Examination of the genes comprising the expression signatures provided important insights into the biology of these leukemia subgroups. Further, within some genetic subgroups, expression profiles identified those patients that would eventually fail therapy. Thus, the single platform of expression profiling should enhance the accurate risk stratification of pediatric ALL patients.

Algorithms↗
PubMed2026

Long-term outcomes of top-down therapy versus a conventional step-up strategy in adults newly diagnosed with Crohn's disease: 5-year follow-up of the PROFILE trial.

BACKGROUND: The PROFILE trial previously reported better 48-week outcomes for patients with Crohn's disease who received top-down anti-TNF treatment from diagnosis, compared with a conventional step-up strategy. Through subsequent follow-up of PROFILE participants, we aimed to assess whether the benefit of top-down treatment from diagnosis results in modification of the long-term disease course. METHODS: PROFILE was a multicentre, open-label, randomised controlled trial completed in 40 hospitals in the UK, which included patients aged 16-80 years with newly diagnosed Crohn's disease. Eligible patients were randomly assigned via a secure online platform to a top-down (infliximab plus immunomodulator) or a step-up protocolised treatment strategy for 48 weeks, after which participants reverted to local standards of care. Objective outcome data were extracted for up to 5 years after the week 48 visit, including need for Crohn's-related abdominal surgery as the primary outcome. Data were analysed based on the original PROFILE randomisation and intention-to-treat population. Participants without long-term follow-up data were censored at the week 48 visit. Time-to-event analyses were performed using the Kaplan-Meier method and Cox proportional hazards model. The trial was registered with the ISRCTN registry, number 11808228 and is complete. FINDINGS: Between Dec 29, 2017, and Jan 5, 2022, 483 patients were assessed for inclusion. 389 patients were enrolled and randomly assigned (three patients were excluded due to ineligibility), 193 to top-down treatment and 193 to step-up treatment. Of the 386 participants in the PROFILE primary trial, 358 (93%) had post-week 48 records available for review (182 [51%] top-down and 176 [49%] step-up). Median follow-up was approximately 5 years from randomisation (1809 days [IQR 1300-2101]), by which point 172 (89%) of 193 patients in the step-up group and 191 (99%) of 193 patients in the top-down group had received biological or immunomodulator therapy. Relating to the primary outcome, during follow-up there were 28 Crohn's disease-related abdominal surgeries in 26 patients treated with a step-up approach versus six surgeries in six patients treated with a top-down approach. Time to surgery was shorter in the step-up group than the top-down group (adjusted hazard ratio [aHR] 5·23 [95% CI 1·99-13·76]; p=0·0008). For the secondary outcomes, incidence of Crohn's disease-related hospital admissions was higher in patients originally managed with step-up treatment versus top-down treatment (41 [21%] of 193 patients vs 22 [11%] of 193 patients); and time to first hospital admission was shorter with step-up treatment than with top-down treatment (aHR 2·01 [95% CI 1·18-3·41], p=0·017). Progression to B2 or B3 complications was also more frequent in those originally managed with step-up treatment compared with top-down treatment (32 [17%] of 192 patients vs 13 [7%] of 193 patients); with time to disease progression being shorter in the step-up group than in the top-down group (aHR 2·46 [95% CI 1·25-4·86]; p=0·010). There was no difference in safety outcomes between groups for either serious infections (12 [6%] of 193 step-up patients and 14 [7%] of 193 top-down patients) or malignancies (five patients [3%] and three patients [2%] respectively). INTERPRETATION: Early top-down anti-TNF treatment from diagnosis was associated with improved long-term outcomes at 5 years compared with step-up treatment and is suggestive of a disease-modifying effect in Crohn's disease. FUNDING: Wellcome and Celltrion.

Journal Article↗
PubMed2005

MicroRNA expression profiles classify human cancers.

Recent work has revealed the existence of a class of small non-coding RNA species, known as microRNAs (miRNAs), which have critical functions across various biological processes. Here we use a new, bead-based flow cytometric miRNA expression profiling method to present a systematic expression analysis of 217 mammalian miRNAs from 334 samples, including multiple human cancers. The miRNA profiles are surprisingly informative, reflecting the developmental lineage and differentiation state of the tumours. We observe a general downregulation of miRNAs in tumours compared with normal tissues. Furthermore, we were able to successfully classify poorly differentiated tumours using miRNA expression profiles, whereas messenger RNA profiles were highly inaccurate when applied to the same samples. These findings highlight the potential of miRNA profiling in cancer diagnosis.

Animals↗
PubMed2005

Combined static and dynamic analysis for determining the quality of time-series expression profiles.

Expression profiling of time-series experiments is widely used to study biological systems. However, determining the quality of the resulting profiles remains a fundamental problem. Because of inadequate sampling rates, the effect of arrest-and-release methods and loss of synchronization, the measurements obtained from a series of time points may not accurately represent the underlying expression profiles. To solve this, we propose an approach that combines time-series and static (average) expression data analysis--for each gene, we determine whether its temporal expression profile can be reconciled with its static expression levels. We show that by combining synchronized and unsynchronized human cell cycle data, we can identify many cycling genes that are missed when using only time-series data. The algorithm also correctly distinguishes cycling genes from genes that specifically react to an environmental stimulus even if they share similar temporal expression profiles. Experimental validation of these results shows the utility of this analytical approach for determining the accuracy of gene expression patterns.

Algorithms↗
PubMed2003

Genomic scale profiling of nutrient and trace elements in Arabidopsis thaliana.

Understanding the functional connections between genes, proteins, metabolites and mineral ions is one of biology's greatest challenges in the postgenomic era. We describe here the use of mineral nutrient and trace element profiling as a tool to determine the biological significance of connections between a plant's genome and its elemental profile. Using inductively coupled plasma spectroscopy, we quantified 18 elements, including essential macro- and micronutrients and various nonessential elements, in shoots of 6,000 mutagenized M2 Arabidopsis thaliana plants. We isolated 51 mutants with altered elemental profiles. One mutant contains a deletion in FRD3, a gene known to control iron-deficiency responses in A. thaliana. Based on the frequency of elemental profile mutations, we estimate 2-4% of the A. thaliana genome is involved in regulating the plant's nutrient and trace element content. These results demonstrate the utility of elemental profiling as a useful functional genomics tool.

Algorithms↗
PubMed2006

A distinct inflammatory gene expression profile in patients with psoriatic arthritis.

Psoriatic arthritis (PsA) is a systemic inflammatory condition featuring polyarthritis associated with psoriasis. Apart from clinical indicators, few biomarkers exist to aid in the diagnosis and management of PsA. We hypothesized that whole blood gene expression profiling would provide new diagnostic markers and/or insights into pathogenesis of the disease. We compared whole blood gene expression profiles in PsA patients and in age-matched controls. We identified 310 differentially expressed genes, the majority of which are upregulated in PsA patients. The PsA expression profile does not significantly overlap with profiles derived from patients with rheumatoid arthritis or systemic lupus erythematosus. Logistic regression identified two lymphocyte-specific genes (zinc-finger protein 395 and phosphoinositide-3-kinase 2B) that discriminate PsA patients from normal controls. In addition, a highly coregulated cluster of overexpressed genes implicated in protein kinase A regulation strongly correlates with erythrocyte sedimentation rate. Other clusters of coregulated, yet suppressed genes in PsA patient blood include molecules involved in T-cell signaling. Finally, differentially expressed genes in PsA fall into diverse functional categories, but many downregulated genes belong to a CD40 signaling pathway. Together, the data suggest that gene expression profiles of PsA patient blood contain candidate novel disease markers and clues to pathogenesis.

Adolescent↗