High-throughput gene expression profiling has become an important tool for investigating transcriptional activity in a variety of biological samples. To date, the vast majority of these experiments have focused on specific biological processes and perturbations. Here, we have generated and analyzed gene expression from a set of samples spanning a broad range of biological conditions. Specifically, we profiled gene expression from 91 human and mouse samples across a diverse array of tissues, organs, and cell lines. Because these samples predominantly come from the normal physiological state in the human and mouse, this dataset represents a preliminary, but substantial, description of the normal mammalian transcriptome. We have used this dataset to illustrate methods of mining these data, and to reveal insights into molecular and physiological gene function, mechanisms of transcriptional regulation, disease etiology, and comparative genomics. Finally, to allow the scientific community to use this resource, we have built a free and publicly accessible website (http:͞͞ expression.gnf.org) that integrates data visualization and curation of current gene annotations.
Oncogene overexpression activates p53 by a mechanism posited to involve uncharacterized hyperproliferative signals. We determined whether such signals produce metabolic perturbations that generate DNA damage, a known p53 inducer. Biochemical, cytological, cell cycle, and global gene expression analyses revealed that brief c-Myc activation can induce DNA damage prior to S phase in normal human fibroblasts. Damage correlated with induction of reactive oxygen species (ROS) without induction of apoptosis. Deregulated c-Myc partially disabled the p53-mediated DNA damage response, enabling cells with damaged genomes to enter the cycle, resulting in poor clonogenic survival. An antioxidant reduced ROS, decreased DNA damage and p53 activation, and improved survival. We propose that oncogene activation can induce DNA damage and override damage controls, thereby accelerating tumor progression via genetic instability.
The HE4 (WFDC2) gene encodes a WAP-type four disulphide core domain-containing protein with a presumptive role in natural immunity. Multiple studies have consistently identified upregulation of HE4 gene expression in carcinomas of the ovary; however, the expression in normal and malignant adult tissues has not been examined in detail. Here, we examined the expression of the HE4 gene and protein in a large series of normal and malignant adult tissues by oligonucleotide microarray and tissue microarray, respectively. HE4 gene expression was highest in normal human trachea and salivary gland, and to a lesser extent, lung, prostate, pituitary gland, thyroid, and kidney. In a series of 175 human adult tumors, gene expression was highest in ovarian serous carcinomas. However, adenocarcinomas of the lung, and occasional breast, transitional cell and pancreatic carcinomas had moderate or high levels of HE4 expression. Using tissue microarrays and full tissue sections of normal and 448 neoplastic tissues, HE4 immunoreactivity was found in normal glandular epithelium of the female genital tract and breast, the epididymis and vas deferens, respiratory epithelium, distal renal tubules, colonic mucosa, and salivary glands, consistent with HE4 gene expression. In addition to consistent positivity in ovarian carcinoma, some pulmonary, endometrial, and breast adenocarcinomas, mesotheliomas, and less often, gastrointestinal, renal and transitional cell carcinomas were also positive. Knowledge of the expression patterns of HE4 in our survey is useful for application in histopathologic diagnosis, and should be taken into consideration in future studies that examine the role of HE4 as a serological tumor biomarker or as a target for gene-based therapy.
Genetic alterations in tumor cells often lead to the emergence of growth-stimulatory autocrine and paracrine signals, involving overexpression of secreted peptide growth factors, cytokines, and hormones. Increased levels of these soluble proteins may be exploited for cancer diagnosis and management or as points of therapeutic intervention. Here, we combined the use of controlled vocabulary terms and sequence-based algorithms to predict genes encoding secreted proteins from among Ϸ12,500 sequences represented on oligonucleotide microarrays. Expression of these genes was queried in 150 carcinomas from 10 anatomic sites of origin and compared with 46 normal tissues derived from the corresponding sites of tumor origin and other body tissues and organs. Of 74 different genes identified as overexpressed in cancer tissues, several encode proteins with demonstrated clinical diagnostic application, such as ␣-fetoprotein in liver carcinoma, and kallikreins 6 and 10 in ovarian cancer, or therapeutic utility, such as gastrin-releasing peptide͞bombesin in lung carcinomas. We show that several of the other candidate genes encode proteins with high levels of tumor-associated expression by immunohistochemistry on tissue microarrays and further demonstrate significantly elevated levels of another novel candidate protein, macrophage inhibitory cytokine 1, a distant member of the tranforming growth factor- superfamily, in the serum of patients with metastatic prostate, breast, and colorectal carcinomas. Our results suggest that the combination of annotation͞protein sequence analysis, transcript profiling, immunohistochemistry, and immunoassay is a powerful approach for delineating candidate biomarkers with potential clinical significance and may be broadly applicable to other human diseases.gene expression ͉ microarray ͉ genome ontology ͉ sequence analysis ͉ immunohistochemistry
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