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PubMed2006

Gene expression profiling reveals unique pathways associated with differential severity of lyme arthritis.

The murine model of Lyme disease provides a unique opportunity to study the localized host response to similar stimulus, Borrelia burgdorferi, in the joints of mice destined to develop severe arthritis (C3H) or mild disease (C57BL/6). Pathways associated with the response to infection and the development of Lyme arthritis were identified by global gene expression patterns using oligonucleotide microarrays. A robust induction of IFN-responsive genes was observed in severely arthritic C3H mice at 1 wk of infection, which was absent from mildly arthritic C57BL/6 mice. In contrast, infected C57BL/6 mice displayed a novel expression profile characterized by genes involved in epidermal differentiation and wound repair, which were decreased in the joints of C3H mice. These expression patterns were associated with disease state rather than inherent differences between C3H and C57BL/6 mice, because C57BL/6-IL-10(-/-) mice infected with B. burgdorferi develop more severe arthritis than C57BL/6 mice and displayed an early gene expression profile similar to C3H mice. Gene expression profiles at 2 and 4 wk postinfection revealed a common response of all strains that was likely to be important for the host defense to B. burgdorferi and mediated by NF-kappaB-dependent signaling. The gene expression profiles identified in this study add to the current understanding of the host response to B. burgdorferi and identify two novel pathways that may be involved in regulating the severity of Lyme arthritis.

Animals↗

PubMed2005

Whole-genome expression profiling of the melanoma progression pathway reveals marked molecular differences between nevi/melanoma in situ and advanced-stage melanomas.

Over the past two decades, several known genes have been shown to govern important functions in the development of primary and metastatic melanomas. However, from this limited number of genes, it is not possible to establish detailed molecular profiles for the early and advanced stages of melanoma development. To gain insights into the genetic profile of every stage of the melanoma progression pathway, and to determine to what extent these profiles are similar or distinct, we performed whole-genome expression profiling of tissue specimens representing normal skin, benign and atypical nevi, and early and advanced-stage melanomas. The results of this study provide first-time evidence that significant molecular changes occur distinctly at the border of/transition from melanoma in situ to primary melanoma, and that genes involved in mitotic cell cycle regulation and cell proliferation constitute the two leading categories of genes associated with these changes.

Carcinoma in Situ↗

PubMed2006

Gene expression profiling data in lymphoma and leukemia: review of the literature and extrapolation of pertinent clinical applications.

CONTEXT: Gene expression (GE) analyses using microarrays have become an important part of biomedical and clinical research in hematolymphoid malignancies. However, the methods are time-consuming and costly for routine clinical practice. OBJECTIVES: To review the literature regarding GE data that may provide important information regarding pathogenesis and that may be extrapolated for use in diagnosing and prognosticating lymphomas and leukemias; to present GE findings in Hodgkin and non-Hodgkin lymphomas, acute leukemias, and chronic myeloid leukemia in detail; and to summarize the practical clinical applications in tables that are referenced throughout the text. DATA SOURCE: PubMed was searched for pertinent literature from 1993 to 2005. CONCLUSIONS: Gene expression profiling of lymphomas and leukemias aids in the diagnosis and prognostication of these diseases. The extrapolation of these findings to more timely, efficient, and cost-effective methods, such as flow cytometry and immunohistochemistry, results in better diagnostic tools to manage the diseases. Flow cytometric and immunohistochemical applications of the information gained from GE profiling assist in the management of chronic lymphocytic leukemia, other low-grade B-cell non-Hodgkin lymphomas and leukemias, diffuse large B-cell lymphoma, nodular lymphocyte-predominant Hodgkin lymphoma, and classic Hodgkin lymphoma. For practical clinical use, GE profiling of precursor B acute lymphoblastic leukemia, precursor T acute lymphoblastic leukemia, and acute myeloid leukemia has supported most of the information that has been obtained by cytogenetic and molecular studies (except for the identification of FLT3 mutations for molecular analysis), but extrapolation of the analyses leaves much to be gained based on the GE profiling data.

DNA, Neoplasm↗

PubMed2006

The Trauma Symptom Inventory: factors associated with invalid profiles in a sample of combat veterans with post-traumatic stress disorder.

The assessment of combat-related post-traumatic stress disorder (PTSD) relies upon self-reported symptoms and the need for indicators of valid reporting is critical. The Trauma Symptom Inventory (TSI) is a testing instrument specific to PTSD which includes validity scales. In a pilot study examining the use of the TSI with combat veterans, 50 male veterans diagnosed with PTSD were administered the TSI. Nineteen percent of the profiles were invalid, all but one based on the Atypical Response Scale. Differences between veterans with valid and invalid TSI profiles are examined in terms of demographic and historical factors, TSI profiles, and individual scale items. The model best able to predict invalid profiles included high scores on subscales measuring dissociative experiences and tension reduction behaviors. Implications for the interpretation of TSI validity scales in assessing combat-related PTSD are discussed.

Adult↗

PubMed2000

Changes in tumorigenesis- and angiogenesis-related gene transcript abundance profiles in ovarian cancer detected by tailored high density cDNA arrays.

BACKGROUND: Complementary DNA array analysis of gene expression has a potential application for clinical diagnosis of disease processes. However, accessibility, affordability, reproducibility of results, and management of the data generated remain issues of concern. Use of cDNA arrays tailored for studies of specific pathways, tissues, or disease states may render a cost- and time-effective method to define potential hallmark genotype alterations. MATERIALS AND METHODS: We produced a 332-membered human cDNA array on nylon membranes tailored for studies of angiogenesis and tumorigenesis in reproductive disease. We tested the system for reproducibility using a novel statistical approach for analysis of array data and employed the arrays to investigate gene expression alterations in ovarian cancer. RESULTS: Intra-assay analysis and removal of agreement outliers was shown to be a critical step prior to interpretation of cDNA array data. The system revealed highly reproducible results, with intermembrane coefficient of reproducibility of +/- 0.98. Comparison of placental and ovarian sample data confirmed expected differences in angiogenic profiles and tissue-specific markers, such as human placental lactogen (hPL). Analysis of expression profiles of five normal ovary and four poorly differentiated serous papillary ovarian adenocarcinoma samples revealed an overall increase in angiogenesis-related markers, including vascular endothelial growth factor (VEGF) and angiopoietin-1 in the diseased tissue. These were accompanied by increases in immune response mediators (e.g. HLA-DR, Ron), apoptotic and neoplastic markers (e.g. BAD protein, b-myb), and novel potential markers of ovarian cancer, such as cofilin, moesin, and neuron-restrictive silencer factor (REST) protein. CONCLUSIONS: In-house production of tailored cDNA arrays, coupled to comprehensive analysis of resulting hybridization profiles, provides an accessible, reliable, and highly effective method of applying array technology to study disease processes. In the ovary, abundance of specific tumor markers, increased macrophage recruitment mediators, a late-stage angiogenesis profile, and the presence of chemoresistance-related markers distinguished normal and advanced ovarian cancer tissue samples. Detection of such parallel changes in pathway- and tissue-specific markers may prove a hallmark ready for application in reproductive disease diagnostic and therapeutic developments.

Biomarkers, Tumor↗

PubMed2002

Microarray-based copy number and expression profiling in dedifferentiated and pleomorphic liposarcoma.

Sixteen dedifferentiated and pleomorphic liposarcomas were analyzed by comparative genomic hybridization (CGH) to genomic microarrays (matrix-CGH), cDNA-derived microarrays for expression profiling, and by quantitative PCR. Matrix-CGH revealed copy number gains of numerous oncogenes, i.e., CCND1, MDM2, GLI, CDK4, MYB, ESR1, and AIB1, several of which correlate with a high level of transcripts from the respective gene. In addition, a number of genes were found differentially expressed in dedifferentiated and pleomorphic liposarcomas. Application of dedicated clustering algorithms revealed that both tumor subtypes are clearly separated by the genomic profiles but only with a lesser power by the expression profiles. Using a support vector machine, a subset of five clones was identified as "class discriminators." Thus, for the distinction of these types of liposarcomas, genomic profiling appears to be more advantageous than RNA expression analysis.

Algorithms↗

PubMed2002

Identification of differentially expressed genes in normal and malignant prostate by electronic profiling of expressed sequence tags.

Differentially expressed genes between corresponding normal and cancertissue can advance our understanding of the molecular basis of malignancy and potentially serve as biomarkers or prognostic markers of malignancy. To identify differentially expressed genes in prostate cancer, we used a procedure combining electronic expression profiling of the prostate expressed sequence tag (EST) database and molecular biology techniques. A novel electronic expression-profiling algorithm was developed to search publicly available EST sequences for genes that show significant differential expression in prostate cancer compared with normal prostate tissue. Approximately 600 genes expressed in prostate were identified through adequate EST counts of ESTs for electronic profiling. Of these 600 genes, 9 showed statistically significant differences in their EST counts between cancer and normal prostate and were further analyzed. The predictions associated with electronic profiling were experimentally verified for two genes, cysteine-rich secretory protein 3 (CRISP-3) and deadenylating nuclease (DAN), using real-time reverse transcription-PCR with total RNA extracted from cells isolated by laser capture microdissection. In five of five Gleason score 6 cancer cases, CRISP-3 expression was increased >50 fold, whereas the expression of DAN was reduced by >80%.

Algorithms↗

PubMed2002

Etiology-specific gene expression profiles in rat mammary carcinomas.

Identification of etiology of human cancers is important for effective cancer prevention, and attempts to estimate the roles of a variety of environmental carcinogens in human cancers are being made. Here, we applied cDNA microarray technology to estimate whether gene expression profiles of cancers would reflect their etiology. Using rat mammary carcinoma models, expression profiles were analyzed in two groups of carcinomas induced by distinct carcinogens but with the same histological classification. Four carcinomas induced by 7,12-dimethylbenz[a]anthracene (DMBA) and three carcinomas induced by 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) and a high-fat diet were analyzed by a GeneChip oligonucleotide microarray that contained approximately 8000 rat genes. By hierarchical clustering analysis, the seven carcinomas were classified into two groups that exactly coincided with the DMBA-induced and the PhIP-induced groups. The correlation coefficient between the two groups was 0.63, and those between any carcinomas within each group ranged from 0.78 to 0.95. In addition, characteristic clusters of genes were also identified that highlighted distinct and common characteristics of both groups. Seventeen genes were down-regulated in the DMBA and up-regulated in the PhIP-induced groups. Thirty-three genes were regulated in the opposite manner. Our results indicated that gene expression profiles in cancers reflect their etiology and suggested a possibility that etiology of cancers could be retrospectively estimated from their expression profiles.

9,10-Dimethyl-1,2-benzanthracene↗

PubMed2002

Expression profiles of craniosynostosis-derived fibroblasts.

BACKGROUND: Craniosynostosis syndromes, a group of connective disorders characterized by abnormalities in vault osteogenesis and premature fusion of bone sutures, are associated with point mutations in FGF receptor family members. The cellular phenotype is characterized by abnormal extracellular matrix turnover. MATERIAL AND METHODS: We used primary cultures of periosteal fibroblasts derived from two different craniosynostosis syndromes, the Apert and Crouzon syndromes. The FGFR2 third immunoglobulin-like domain and its flanking linker regions were analyzed for mutation. DNA microarrays containing 19,200 cDNAs were used to study the gene expression profiles of Apert and Crouzon fibroblasts. The pathologic cells were compared to wild-type human periosteal fibroblasts. RESULTS: The P253R missense mutation and the G338R mutation were observed in Apert and Crouzon fibroblasts, respectively. The genetic profiles, as evaluated by DNA microarrays, yielded different clusters of expressed sequence tag (ESTs) expression within the experiment. Expression profiles from craniosynostosis-derived fibroblasts differ from those of wild-type fibroblasts (288 human ESTs, p< 0.01, pFDR = 0.12). Furthermore, two ESTs clusters discriminate the Crouzon from Apert fibroblasts. The differentially expressed genes cover a broad range of functional activities, including (1) bone differentiation, (2) cell-cycle regulation, (3) apoptotic stimulation, and (4) signaling transduction, cytoskeleton, and vesicular transport. CONCLUSIONS: The transcriptional program of craniosynostosis fibroblasts differs from that of wild-type fibroblasts. Expression profiles of Crouzon and Apert fibroblasts can also be distinguished by two EST expression clusters, thus hinting at a different genetic background.

Acrocephalosyndactylia↗

PubMed2002

[Preliminary analysis on the gene expression profiles of different types of gliomas with cDNA array].

BACKGROUND & OBJECTIVE: There is great signification to classify the molecular pathogenesis of gliomas. Gene chip is able to profile the gene expression of tumors, which may become a new method for studying molecular pathology of tumors. The cDNA was used in order to detect the differences in gene expression profiles of different types of gliomas. METHODS: cDNA probes tagged with 32P were converted from total RNA extracted from 4 samples of 3 different pathological types, including oligodendrogliomas, anaplastic astrocytomas and ependymomas, and one sample of normal human brain tissue as well, which were then hybridized to the Atlas array. After autoradiography, the gene expression profiles were analyzed with the special software and by the cluster analysis. RESULTS: As compared to the normal brain tissue, the number of differential expressed genes in these tumor samples ranging from 11 to 118 was found. These 4 samples could be divided into 3 kinds of types when 107 differential expressed genes were selected to be as the cluster analysis index. This result was in accordance with the neuropathological diagnosis. CONCLUSION: cDNA array is able to profile gene expression in different types of gliomas. Combined with the bioinformational method, we may further obtain useful information about molecular pathology of gliomas.

Gene Expression Profiling↗

PubMed2003

Kernel Cox regression models for linking gene expression profiles to censored survival data.

In functional genomics, one important problem is to relate the microarray gene expression profiles to various clinical phenotypes from patients. The success has been demonstrated in molecular classification of cancer in which gene expression data serve as predictors and different types of cancer are the binary or multi-categorical outcome variable. However, there has been less research in linking gene expression profiles to other types of phenotypes, in particular, the censored survival data such as patients' overall survival or cancer relapse times. In the paper, we develop a kernel Cox regression model for relating gene expression profiles to censored phenotypes in the framework the penalization method in terms of function estimation in reproducing kernel Hilbert spaces. To circumvent the problem of censoring, we use the negative partial likelihood as a loss function in the estimation procedure. The functional combinations of the original gene expression data identified by the method are highly correlated with the patients' survival times and at the same time account for the variability in the gene expression levels. We apply our method to data sets from diffuse large B-cell lymphoma, lung adenocarcinoma and breast carcinoma studies to verify its effectiveness. The results from these analyses indicate that the proposed method works very well in identifying subgroups of patients with different risks of death or relapse and in predicting the risk of relapse or death based on the gene expression profiles measured from the tumor samples taken from the patients.

Artificial Intelligence↗

PubMed2003

Handling of clinical tissue specimens for molecular profiling studies.

The relationship between gene expression profiles and cellular phenotypes is an important aspect of functional genomics. Clinical tissue specimens will play a vital role in this effort. The usefulness of tissue for molecular profiling is significantly influenced by the manner of specimen handling. Crucial components of this process include the optimization of the methods of tissue fixation and embedding, not only to obtain excellent histological detail, but also to promote the elucidation of the gene and protein expression profiles. In this article, we describe handling of clinical specimens using whole-mount prostate as an example, the use of new high-throughput techniques that allow molecular profiling analysis and the use of a web-based 3-dimensional model to combine these data to make it available to clinicians and the research community. Complete protocols and additional discussion are available on the website, http://cgap-mf.nih.gov.

Cryopreservation↗

PubMed2003

Successful prediction of prostate cancer recurrence by gene profiling in combination with clinical data: a 5-year follow-up study.

We show here that gene expression profiling, performed with conventional techniques and focused on a selected group of genes, when used in combination with standard clinical information, provides reliable prognostic prediction of prostate cancer (CaP). We showed previously that changes in the expression of metabolically related genes are involved in CaP progression. We then proceeded to search further for correlations between patients' gene profiling and recurrence with a 5-year follow-up study conducted on the same cohort of patients in which the molecular data were obtained. CaP prognosis was first assessed on the basis of gene expression profiling alone; then the result was compared with the prediction obtained using clinical and pathological information (Gleason score, Tumor-Node-Metastasis staging, prostate volume, or prostate-specific antigen levels at the time of diagnosis). The best result was obtained with a selected combination of gene profiling and clinical/pathological parameters, which resulted in prediction of recurrence in 95.7% of patients.

Aged↗

PubMed2003

[Infection of Coxsackievirus group B type 3 regulates the expression profile of chemokines in myocardial tissue/cells].

OBJECTIVE: To investigate the role of Coxsackievirus group B type 3 (CVB3) infection on the expression profile of chemokines (ChKs) in myocardial tissue/cells. METHODS: CVB3 was inoculated into male BALB/c intraperitoneally and primary neonatal myocardial cells of BALB/c to establish CVB3 infection models in vivo and in vitro, where the expression profile of ChKs was detected at different time points post-infection as well as under different loading of CVB3 qualitatively and quantitatively by RT-PCR. RESULTS: The expression of MIP-2 and IP-10 was induced post-infection, while SDF-1, MCP-1, MCP-2, MCP-3, MCP-5, MDC, FKN and Ltn were constitutively expressed in myocardial tissue. The expression of MCP-1, MCP-2, MCP-3, MCP-5, MDC and Ltn increased 1.8, 1.9, 3.7, 1.7, 1.3 and 1.2 folds post-infection higher than that of uninfected control (P < 0.01). There was not significant difference in the expression of SDF-1 and FKN between infected myocardial tissue and uninfected myocardial tissue (P > 0.05). The expression of Eot was not detected in infected and uninfected myocardial tissue. Every chemokine had different expression at different infection time points. For example, the expression of MIP-2 at the 4th day was 1.1 and 1.5 times than that of the 7th and 14th day (P < 0.01). IP-10 showed similar expression between the 4th and 7th days (P > 0.05), which is 2.47 and 2.54 times compared to that of the 9th day (P < 0.01). And the expression of MCP-1 at the 14th day post-infection was 1.3, 1.2 and 1.0 times comparing to that of the 4th, 7th, 9th day post-infection, which showed statistical meaning. The expression of MCP-2 at the 4th was 1.4, 1.5 and 2.2 times comparing to that of the 7th, 9th, 14th day, and moreover, the expression was lower than that of the basal expression. The expression of MCP-1 and MCP-3 was up-regulated significantly, which occurred at different time points post-infection in vitro. While the expression of MIP-2 and MCP-5 was down-regulated in vitro. The expression patterns of MCP-2, MCP-3, MCP-5 and MDC were consistent with CVB3 loading. But that of the others (FKN, SDF-1, et al) were inconsistent with CVB3 loading. There was a correlation between change patterns of MCP-3 and CVB3 loading post-infection (r = 0.881, P < 0.05) within 14 days after infection. The varied expression trend of MCP-1 and MCP-3 was similar to the titer of anti-CVB3 antibody (r = 0.913, P = 0.031), while the expression of MCP-2, MCP-5 and MDC shows contrary change. There was not a significant correlation between change patterns of other ChKs (IP-10, SDF-1, et al) and the titer of anti-CVB3 antibody. A positive correlation between anti-CVB3 antibody and MCP-1 (r = 0.976, P < 0.05) was showed. CONCLUSION: The expression level and kind of ChKs in vivo and in vitro was varied significantly in clusters after CVB3 infection. The ChKs changed in clusters consisted of the expression profiles of ChKs. There were complexity and unbalance in the change of the expression of ChKs in every expression profile. It suggested that CVB3 infection could regulate the expression of ChKs in myocardial tissue/cells likely in different ways.

Animals↗

PubMed2003

Breast cancer gene expression analysis--the case for dynamic profiling.

Cancer is a complicated disease with each individual tumor exhibiting to a variable degree a set of overlapping phenotypes that include abnormal proliferation and cell survival, genetic instability, tissue invasion, metastasis and angiogenesis. Each of these pathophysiological functions requires abnormal signaling that fails to respect the normal restraints imposed on healthy cells through homeostatic regulation. Understanding of deregulated gene expression is therefore an essential goal for cancer research because unraveling this problem will provide insights into the fundamental nature of cancer as well as provide opportunities for therapeutic intervention. Gene expression profiling is a remarkable technique that addresses this complexity by documenting the expression of thousands of genes at the level of mRNA abundance. From the standpoint of clinical investigation, the initial focus of gene profiling experiments has been on screening primary tumors for markers of poor prognosis. However this is only a first step in demonstrating the utility of this technique. Future advances will focus on understanding the evolution of an organ confined primary cancer to a treatment resistant lethal systemic disease through repeated tumor sampling and analysis, an approach termed in this paper "dynamic profiling". Using breast cancer endocrine therapy as an example our initial approaches to dynamic profiling will be described.

Aromatase Inhibitors↗

PubMed2003

[Non small cell lung cancer gene expression profiles by cDNA microarrays].

OBJECTIVE: To study lung squamamouscarcinoma and lung adenocarcinoma gene expression profiles by cDNA microarrays, compare them with those of pulmonary inflammatory pseudoneoplasma, and screen the differential expression gene and the common expression gene in these types of lung cancer in order to further study early diagnosis and treatment of lung cancer. METHODS: cDNA microarray chips containing 4096 human target genes were used to identify gene expression profiles in lung squamous cell carcinoma, adenocarcinoma, and pulmonary inflammatory pseudoneoplasma. RESULTS: Among the target genes, 591 differentially expressed genes were identified in lung squamous cell carcinoma; among them, there were 476 genes unexpressed in pulmonary inflammatory pseudoneoplasma; 293 of 476 differentially expressed genes were up-regulated and the other 183 were down-regulated. There were 524 differentially expressed genes in adenocarcinoma; among them, 460 genes were not expressed in pulmonary inflammatory pseudoneoplasma; 214 of the 460 differentially expressed genes were up-regulated and 246 were down-regulated. However, there were a total of 113 genes differentially expressed the both lung squamous cell carcinoma and adenocarcinoma. CONCLUSION: There were distinct gene expression profiles among lung squamous cell carcinoma and adenocarcinoma. All those gene expression profiles and genes screened out provide important clues for further investigation of carcinogenesis, invasion and metastasis of non small cell lung cancer and its molecular characteristics.

Adenocarcinoma↗

PubMed2003

Quick gene expression profiling of promyelocytic cell line HL-60.

OBJECTIVE: A number of techniques have been developed to perform gene expression profiling. We report preliminary results from our exploratory study, using sequential analysis of gene expression (SAGE) technique, to profile the undifferentiated and differentiated HL-60 cells in line with our interest to characterize the cancer phenotype. The aim of the study is to evaluate the technique and to understand the molecular bases of these 2 states of cells. METHODS: HL-60 cells were differentiated after treatment with dimethyl sulfoxide. Tag libraries were prepared from the messenger RNAs of the undifferentiated and differentiated cells according to the SAGE protocol. The search for genes corresponding to the tags was carried out using SAGE software. The tags and the genes from the 2 libraries were compared for their levels of expression. The study was carried out at the King Faisal Specialist Hospital and Research Centre, Riyadh, Kingdom of Saudi Arabia during the year 2001. RESULTS: A comparison of tags from the 2 libraries revealed that 151 tags corresponding to 57 genes expressed differentially: 60 tags were elevated and 59 were repressed in the undifferentiated cells. Thirty-two tags were equally expressed in both types of cells. Of the corresponding genes, 25 were expressed at higher, 17 at lower, while 15 were expressed at comparable levels in both cell types. In the profile of undifferentiated cells, the genes involved in mitochondrial function and protein synthesis were prominent, while in the differentiated cells, the genes coding for proteins associated with cell membranes, signal transduction and for cell specific functions were prominent. The genes, expressed equally in both the cell types, were concerned with the maintenance of the living state. CONCLUSION: Sequential analysis of gene expression is a useful technique for gene expression profiling. As previously indicated by others, a dedicated team can generate useful data within reasonable time limits.

Cell Differentiation↗

PubMed2004

Insights from the gene expression profiling of multiple myeloma.

Recent gene expression profiling using high throughput sequencing and microarray analysis of multiple myeloma has shed new light on this morphologically homogeneous yet clinically heterogeneous disease. The biology of the disease has been interrogated in studies, which reveal that patients have unique gene expression clusters that correlate with disease severity. These studies have also revealed that some myeloma cells have gene expression characteristics that resemble the molecular profile of late-stage B cells. Expression profiling can identify hallmark immunoglobulin translocations and other common structural genetic changes that impart prognostic significance. Molecular profiling has been demonstrated to be of value in pharmacogenomic studies predicting response to therapy and revealing novel therapeutic targets. These studies are providing insight into many previously unexplained features of this difficult disease.

Bone Marrow↗