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At least 1,603 records · Page 89Linked to original sources
PubMed2006

Effect of an intrauterine device on the gene expression profile of the endometrium.

CONTEXT: The human endometrium acquires the ability to allow embryo attachment just for a specific period of time during each menstrual cycle. Understanding of the opposite functional status, referred to as refractoriness, can potentially be used to improve receptivity in infertile patients or as an interceptive approach to prevent gestation. OBJECTIVE: The objective of the study was to analyze the endometrial gene expression profile induced by an inert intrauterine device (IUD) at the time of implantation. DESIGN: We used a microarray containing more than 16,000 cDNAs to investigate the gene expression profile of receptive vs. refractory endometrium in the same women induced by the presence of an IUD. We compared the gene expression profile of endometrium obtained at LH+7 (window of receptivity) from the same women (n = 5) at the following time points: month 1, corresponding to the natural cycle before IUD insertion; month 3, just before IUD removal; and months 5 and 15. Data were validated by quantitative RT-PCR for IGF binding protein-3, peroxisome proliferative activated receptor-gamma, glycodelin, and leukemia inhibitory factor and immunohistochemistry for glycodelin. RESULTS: We identified 147 genes significantly dysregulated in the refractory endometrium (78 up- and 69 down-regulated). Interestingly, 52 of these genes have previously been reported to be regulated during window of implantation. Surprisingly, the majority of genes (96.6%) remained dysregulated 2 months after IUD removal, but 1 yr later most of them (80%) returned to normal. CONCLUSIONS: Our results reveal that a refractory endometrium in a fertile woman produced by an IUD is induced by preventing the normal transition to a receptive gene expression profile through effects on a specific subset or cluster of genes that impact on endometrial receptivity.

Adult↗
PubMed2006

A gene expression profile for vascular invasion can predict the recurrence after resection of hepatocellular carcinoma: a microarray approach.

BACKGROUND: Recurrence after hepatocellular carcinoma (HCC) resection is the major obstacle to improved survival. The presence of vascular invasion (VI) in pathology specimens is a well-known unfavorable prognostic factor for HCC recurrence. Though some VI-related genes have been reported, their association with recurrence-free survival is not known. We hypothesized that a gene expression profile for VI can predict the recurrence of HCC after liver resection. METHODS: Eighteen patients receiving complete HCC resection were included as a "training group". Genome-wide gene expression profile was obtained for each tumor using a microarray technique. Datasets were subjected to clustering analysis supervised by the presence or absence of VI to obtain 14 discriminative genes. We then applied those genes to execute pattern recognition using the k-Nearest Neighbor (KNN) classification method, and the best model for this VI gene signature to predict recurrence-free survival in the training group was obtained. The resulting model was then tested in an independent "test group" of 35 patients. RESULTS: A 14-gene profile was extracted which could accurately separate ten patients with VI and eight patients without VI in the "training group". In the "test group", significant difference in disease-free survival was found between patients predicted to have and not to have recurrence (P = .02823). In patients with stage_I disease, this model can also predict outcomes (P = .000205). CONCLUSIONS: Using the 14-gene expression profile extracted from microarrays based on the presence of VI can effectively predict recurrence after HCC resection. This approach might facilitate "personalized medicine" for HCC patients after surgical resection.

Aged↗
PubMed2002

Microdissection is essential for gene expression profiling of clinically resected cancer tissues.

The gene expression array method enables us to achieve expression profiling with thousands of genes. Clinically resected bulk cancer tissues, however, contain not only cancer cells but also stromal cells, which may affect gene expression profiling and hamper accurate analysis of the cancer cells per se. Therefore, a procedure for dissecting specific cells, such as laser capture microdissection, is neededfor the clinical application of a gene expression array. There has been no study actually comparing 2 gene expression profiles, one obtained using RNA extractedfrom cancer cells by laser capture microdissection and one obtained using RNA extractedfrom bulk cancer tissues. Wefirst demonstrated the difference in expression patterns between them, without any amplification procedures. In addition, differential expression analysis between tumor and nontumor tissue yielded quite different patterns between the 2 methods. We conclude that microdissection is essential for gene expression profiling of clinical specimens.

Dissection↗
PubMed2005

Oligonucleotide-directed microarray gene profiling of pancreatic adenocarcinoma.

Successful gene profiling studies involve careful experimental design, use of sensitive and accurate technologies, and statistically valid analysis of experimental results. In this chapter we describe our approach to the profiling of pancreatic adenocarcinoma to illustrate the various steps and methods involved in this type of study. Pancreatic adenocarcinoma is a particularly challenging subject for gene profiling, as these tumors have a profound desmoplastic response such that neoplastic epithelium makes up only a small proportion of the tissue mass. We have utilized statistical comparisons of gene expression between adenocarcinoma, normal pancreas, samples of chronic pancreatitis, and pancreatic cancer cell lines that provides a means to deduct the influence of the stromal elements. We utilized oligonucleotide-directed gene chips (Affymetrix), as they allow the simultaneous interrogation of thousands of genes in an efficient, reproducible, sensitive, and highly quantitative manner. The details of the approach we utilized are reported here, including information on experimental design, sample collection, expression level measurements, and data analysis for gene profiling.

Adenocarcinoma↗
PubMed2005

Gene expression profiling using RNA extracted from whole blood: technologies and clinical applications.

Gene expression profiling promises to provide an insight into normal biologic and pathologic processes with the hope of predicting disease outcome or indicating individualized courses of therapy. The entire process for gene expression profiling from clinical samples consists of sample collection, transport and storage of clinical sample, isolation of nucleic acids, enzymatic modification of nucleic acids, detection and data analysis. All steps exert an influence on the quality, accuracy and reliability of the final result. A standardization of the entire process from sample collection to nucleic acid analysis is therefore required in order to achieve reliable gene expression results. After providing a general overview of technologies for gene expression profiling and respective caveats, this review will focus on clinical applications of blood sample profiling.

Acute Disease↗
PubMed2006

Studying multiple protein profiles over time to assess biomarker validity.

Protein profile analysis is increasingly used for identification of disease biomarkers. The approaches vary from surface-enhanced laser desorption/ionization to protein arrays. Newer platforms are constantly being developed. Almost all are based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and are often coupled with sophisticated software tools. Protein profiling has been applied to a variety of samples including plasma, urine, cerebrospinal fluid, saliva and solid tissue. This article focuses on those instances where it is possible to obtain sequential samples from the same individual. In the authors use of a profile method, many protein changes with highly significant correlations to disease have been found. The main challenge lies in the validation of the marker to demonstrate its adequacy for use in the clinical setting. The latter requires a methodology that is robust and amenable to high-throughput. One problem is that interindividual variability among the healthy population can mask major changes that occur on an intraindividual basis. Often, a large change for an individual may remain within the range of healthy individuals. Thus, one strategy to optimize biomarker discovery is to examine serial samples from a given individual, where a disease biomarker is established by comparison with the individual's own baseline sample. The focus of this review is to illustrate the principle and value of serial protein profiling using a rapid protein extraction method.

Adult↗
PubMed2003

What can digital transcript profiling reveal about human cancers?

Important biological and clinical features of malignancy are reflected in its transcript pattern. Recent advances in gene expression technology and informatics have provided a powerful new means to obtain and interpret these expression patterns. A comprehensive approach to expression profiling is serial analysis of gene expression (SAGE), which provides digital information on transcript levels. SAGE works by counting transcripts and storing these digital values electronically, providing absolute gene expression levels that make historical comparisons possible. SAGE produces a comprehensive profile of gene expression and can be used to search for candidate tumor markers or antigens in a limited number of samples. The Cancer Genome Anatomy Project has created a SAGE database of human gene expression levels for many different tumors and normal reference tissues and provides online tools for viewing, comparing, and downloading expression profiles. Digital expression profiling using SAGE and informatics have been useful for identifying genes that have a role in tumor invasion and other aspects of tumor progression.

Antigens, Neoplasm↗
PubMedDate not supplied

Stability and heterogeneity of expression profiles in lung cancer specimens harvested following surgical resection.

One of the major concerns in microarray profiling studies of clinical samples is the effect of tissue sampling and RNA extraction on data. We analyzed gene expression in lung cancer specimens that were serially harvested from tumor mass and snap-frozen at several intervals up to 120 minutes after surgical resection. Global gene expression was profiled on cDNA microarrays, and selected stress and hypoxia-activated genes were evaluated using real-time reverse transcription polymerase chain reaction (RT-PCR). Remarkably, similar gene expression profiles were obtained for the majority of samples regardless of the time that had elapsed between resection and freezing. Real-time RT-PCR studies showed significant heterogeneity in the expression levels of stress and hypoxia-activated genes in samples obtained from different areas of a tumor specimen at one time point after resection. The variations between multiple samplings were significantly greater than those of elapsed time between sampling/freezing. Overall samples snap-frozen within 30 to 60 minutes of surgical resection are acceptable for gene expression studies, thus making sampling and snap-freezing of tumor samples in a routine surgical pathology laboratory setting feasible. However, sampling and pooling from multiple sites of each tumor may be necessary for expression profiling studies to overcome the molecular heterogeneity present in tumor specimens.

Carcinoma, Non-Small-Cell Lung↗
PubMed2005

Gene-expression profiling and the future of adjuvant therapy.

Gene-expression profiling can help distinguish between patients at high risk and those at low risk for developing distant metastases, and so identify patients for adjuvant therapy. For several years, the Netherlands Cancer Institute has been working on gene-expression profiling of breast cancer using a microarray platform containing 25,000 genes. Using supervised classification, a prognostic classifier consisting of 70 genes could be identified. In addition to providing prognostic information, gene profiling should also enable us to detect patients who are likely to respond to particular adjuvant interventions. Well-known predictors for response to systemic therapy include estrogen receptor status HER-2 status, c-kit mutation, and epidermal growth factor receptor mutation. Because of the long periods required for predicting responsiveness in the adjuvant setting, neoadjuvant trials promise far quicker results. Several neoadjuvant studies are under way or planned to investigate gene-expression profiling as a means of predicting the therapeutic response to docetaxel (Taxotere; Aventis Pharmaceuticals Inc., Bridgewater, NJ, http://www.aventispharma-us.com), paclitaxel (Taxol; Bristol-Myers Squibb, Princeton, NJ, http://www.bms.com), cyclophosphamide, and doxorubicin (Adriamycin; Bedford Laboratories, Bedford, OH, http://www.bedfordlabs.com) in breast cancer patients. It is expected that in the coming years an increasing number of novel prognostic and predictive tests will help in guiding the adjuvant systemic treatment of breast cancer and other malignancies.

Chemotherapy, Adjuvant↗
PubMed2002

Expression profile of active genes in the human pituitary gland.

To characterize transcripts abundantly expressed in the human pituitary gland in general as well as to isolate novel transcripts expressed specifically in this gland, we generated an expression profile of the active genes transcribed in it. A total of 1015 randomly collected 3prime prime or minute expressed sequence tags (ESTs) (gene signatures, GSs) were grouped into 527GS species. The results showed the relative expression levels of genes in the pituitary gland. The genes comprising more than 1% of total mRNA were prolactin, growth hormone and chromogranin B genes. When known genes were categorized, the genes for pituitary hormones were the most actively transcribed, followed by the genes for ribosomal proteins, nuclear proteins and secretory granule proteins. Through comparison of this gene expression profile with the BodyMap database containing profiles generated from 63 other human tissues, we obtained 11 genes which appeared to be specifically expressed in the pituitary gland. In addition to the eight known genes, we identified three novel pituitary-specific transcripts which encode putative proteins: pituitary gland specific factor 1a (PGSF1a), PGSF1b and PGSF2. This expression profile method is a novel approach to the isolation of pituitary-specific genes that may have important functions.

Amino Acid Sequence↗
PubMed2003

A transgene and its expression profile are stably transmitted to offspring in transgenic medaka generated by the particle gun method.

A particle gun is used in a potential method for introducing foreign genes into fish. In this paper, we report on the stable transmission of a transgene and its expression profile of the F4 generation in the transgenic medaka (Oryzias latipes). We established four transgenic strains, which contained a green fluorescent protein (GFP) gene controlled by a medaka beta-actin promoter, using a particle gun. One more transgenic strain was also generated by microinjection for comparison. In all five strains, the founder was discovered to be mosaic for the transgene. However, from the F1 to F4 generations, transgenes and their expression profiles were stably inherited in the Mendelian manner. The expression profile was common among the five strains regardless of the method for gene transfer: GFP fluorescence became detectable at an early neurula stage. In this stage, the fluorescence was observed ubiquitously in most tissues. As somite developed, GFP fluorescence became intense only in the skeletal muscle and lens but it decreased in other tissues. In adult fish, an intense fluorescence was restricted in the skeletal muscle and lens, while a considerably weak fluorescence was observed in the brain, gill, heart, kidney, spleen, and ovary. From these results, it was concluded that the transgene and its expression profile were stably transmitted to offspring, and thus the particle gun is an effective method for transgenesis in spite of its easiness.

Actins↗
PubMed2003

Epigenomic profiling using microarrays.

Genes occupy only a minor fraction of genomes such as ours; however, histone and nonhistone chromosomal proteins and methylated DNA bases are distributed over both genic and nongenic regions. These widespread "epigenomic" features can be mapped and characterized by alternative applications of the same microarray technologies that have been used for conventional transcriptional profiling. Here we describe diverse microarray-based strategies for profiling patterns of DNA methylation, DNA replication, DNA binding, and chromatin-associated proteins and histone modifications. The rapid progress that is being made in developing and applying epigenomic profiling methods and the increasing availability of microarrays mean that epigenomic profiling is likely to become a standard research tool for understanding chromatin structure and gene expression during development.

Animals↗
PubMed2004

Monitoring therapy with gene expression profiling reveals physiological differences in drug action.

Gene expression profiling has become a versatile tool for biomedical research, which allows the assessment of a wide variety of basic questions in cellular regulation, in particular when a large number of molecular parameters have changed. There are various applications in drug research for which gene expression profiling is a very suitable approach. This includes: target identification, target validation, validation of drug specificity and monitoring of drug action during therapy. The focus of this article is the therapy monitoring and the interpretation of the gene expression profiles in respect to physiological differences of drug action. As an example, we will discuss changes in gene expression in blood samples from CML patients treated with the tyrosine kinase inhibitor (imatinib mesylate) and compare the observed effects on gene expression with the effects of IFNalpha treatment. In comparison with other examples of therapy monitoring the potential of this application of gene expression profiling for optimizing individual therapy will be discussed.

Animals↗
PubMed2026

Epigenetic Profiling for Early Detection and Treatment Response Monitoring in Non-Small Cell Lung Cancer: Protocol for a Prospective Translational Biomarker Study.

BACKGROUND: Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related mortality worldwide and continues to have poor survival outcomes, with most patients diagnosed at advanced stages of disease. In New Zealand, NSCLC contributes substantially to cancer inequities, with Māori communities experiencing disproportionately high incidence and mortality rates. Although low-dose computed tomography screening can improve early detection, major limitations remain, including false-positive findings, overdiagnosis, high infrastructure costs, and limited accessibility for rural and underserved populations. Liquid biopsy approaches using circulating tumor DNA (ctDNA), particularly DNA methylation profiling, have emerged as promising, minimally invasive strategies for improving cancer detection, treatment monitoring, and precision oncology. OBJECTIVE: This study aims to establish integrated genomic and epigenomic predictive and prognostic biomarkers using ctDNA, tumor tissue, and transcriptomic profiling to improve early detection, risk stratification, treatment selection and response prediction, and longitudinal monitoring, with particular emphasis on identifying molecular mechanisms associated with treatment resistance and disease progression. METHODS: This prospective observational translational biomarker study is being conducted through the University of Otago and associated respiratory and oncology services in New Zealand. The study will recruit participants with NSCLC (including squamous and nonsquamous subtypes), individuals referred to fast-track lung nodule assessment clinics, and nonmalignant respiratory controls. Serial peripheral blood sampling will be performed in selected participants at predefined clinical follow-up time points to evaluate treatment response and disease progression. The availability of formalin-fixed paraffin-embedded archival tissues will be recorded, but will not be mandatory for enrollment. Genome-scale DNA methylation profiling will be performed using cell-free reduced representation bisulfite sequencing (cfRRBS), while targeted genomic profiling and transcriptomic analyses will be conducted using targeted sequencing panels and RNA sequencing. Integrative bioinformatic analyses will be used to identify molecular biomarkers associated with early-stage disease, advanced disease, treatment response, and therapeutic resistance. RESULTS: Ethics approval for the study has been obtained from the New Zealand Health and Disability Ethics Committee (2022 EXP 12566). This study commenced in 2022, and recruitment and biospecimen collection are ongoing. The study aims to recruit approximately 450 participants, including patients with NSCLC, individuals referred through respiratory diagnostic pathways, and nonmalignant controls. As of July 31, 2026, 205 participants have been recruited, with recruitment continuing until the target sample size is reached. Molecular and data analyses are ongoing, with additional publications expected as the cohort matures. CONCLUSIONS: This study will generate one of the first integrated genomic, epigenomic, and transcriptomic liquid biopsy datasets for NSCLC in New Zealand. The findings are expected to support the development of sensitive, accessible, and equitable blood-based biomarkers for NSCLC detection and treatment monitoring while also contributing to improved precision oncology approaches and reducing NSCLC inequities among Māori populations.

Humans↗
PubMed2006

Gene expression profiling to monitor therapeutic and adverse effects of antisense therapies for Duchenne muscular dystrophy.

OBJECTIVES: The objective of this study was to assess the utility of the gene expression profiling technique for the preclinical evaluation of drug efficacy and safety, taking a new therapeutic approach for Duchenne muscular dystrophy (DMD) as an example. METHODS: Muscles from dystrophin-deficient (mdx) mice, a well-characterized animal model for DMD, were injected with antisense constructs that restore the open reading frame in the Dmd gene. Synthetic antisense oligonucleotides (AONs) complexed with different carriers to enhance cellular uptake and recombinant adeno-associated virus (rAAV)-expressed antisense sequences were evaluated. Muscular gene expression profiles were analyzed on oligonucleotide microarrays. RESULTS: Polyethylenimine (PEI)-complexed AONs restored the reading frame slightly more effectively than uncomplexed, F127- or Optison-complexed AONs. However, PEI induced the expression of many immune genes, reflecting an aggravation of the inflammation present in untreated mdx mice. Expression profiles in Optison and F127-injected muscles were similar to those of saline treated muscles, implying that these carriers did not evoke adverse responses. Due to moderate levels of exon skipping, a significant shift toward wild-type expression levels was not detected. Injection with rAAV vectors resulted in much higher production of dystrophin and greatly improved the histological appearance of the muscle. Depending on the efficacy of the treatment, the expression of genes previously shown to be elevated in muscular dystrophies, partly or completely returned to wild-type expression levels. Reductions in inflammation and fibrosis were among the most prominent changes observed. CONCLUSION: Expression profiling is a powerful tool for the evaluation of both desired and adverse effects of new pharmacological therapies. It is sensitive and detects changes that are not histologically visible. In addition, its ability to simultaneously monitor a large number of different biological processes not only reduces the number of different assays required in preclinical research and clinical trials, but may also assist in the early detection of potential side effects.

Animals↗
PubMed2006

Metabolic profiling technologies for biomarker discovery in biomedicine and drug development.

The state-of-the-art of nuclear magnetic resonance spectroscopy, mass spectrometry and statistical tools for the acquisition and evaluation of complex multidimensional spectroscopic data in metabolic profiling is reviewed in this article. The continuous evolution of the sensitivity, precision and throughput has made these technologies powerful and extremely robust tools for application in systems biology, pharmaceutical and diagnostics research. Particular emphasis is also given to the collection and storage of biological samples that are subjected to metabolite profiling. Selected examples from preclinical and clinical applications are paradigmatically shown. These illustrate the power of the profiling technologies for characterizing the metabolic phenotype of healthy, diseased and treated subjects. The complexity of disease and drug treatment is asking for an adequate response by integrated and comprehensive metabolite profiling approaches that allow the discovery of new combinations of metabolic biomarkers.

Animals↗
PubMed2006

Prognostic testing in uveal melanoma by transcriptomic profiling of fine needle biopsy specimens.

Many uveal melanoma patients die of metastasis despite ocular treatment. Transcriptomic profiling of enucleated tumors can identify patients at high metastatic risk. Because most uveal melanomas do not require enucleation, a biopsy would be required for this analysis. Here, we establish the feasibility of transcriptomic analysis of uveal melanomas from fine needle aspirates. Transcriptomic profiles were analyzed from postenucleation "mock" needle biopsies and matching tumors from eight enucleated eyes and from fine needle aspirates in 17 uveal melanomas before radiotherapy. Predictive accuracy was assessed using a weighted voting classifier optimized for probe set selection using a minimal redundancy/maximum relevance algorithm. Transcriptomic profiles from mock biopsies were highly similar to those from their matching tumor samples (P < 0.0001). Transcriptomic profiles from fine needle aspirates clustered into two classes with discriminating probe sets that overlapped significantly with those for our published classification (P < 0.00001). No loss of predictive accuracy was identified among eight needle aspirates obtained from a distant location. Thus, it is feasible to obtain RNA of adequate quality and quantity to perform transcriptomic analysis on uveal melanoma samples obtained by fine needle biopsy. This method can be applied to specimens obtained from distant geographic locations and can stratify uveal melanoma patients based on metastatic risk.

Adult↗
PubMed2003

Gene expression profiles at different stages of human esophageal squamous cell carcinoma.

AIM: To characterize the gene expression profiles in different stages of carcinogenesis of esophageal epithelium. METHODS: A microarray containing 588 cancer related genes was employed to study the gene expression profile at different stages of esophageal squamous cell carcinoma including basal cell hyperplasia, high-grade dysplasia, carcinoma in situ, early and late cancer. Principle component analysis was performed to search the genes which were important in carcinogenesis. RESULTS: More than 100 genes were up or down regulated in esophageal epithelial cells during the stages of basal cell hyperplasia, high-grade dysplasia, carcinoma in situ, early and late cancer. Principle component analysis identified a set of genes which may play important roles in the tumor development. Comparison of expression profiles between these stages showed that some genes, such as P160ROCK, JNK2, were activated and may play an important role in early stages of carcinogenesis. CONCLUSION: These findings provided an esophageal cancer-specific and stage-specific expression profiles, showing that complex alterations of gene expression underlie the development of malignant phenotype of esophageal cancer cells.

Carcinoma, Squamous Cell↗