Regulation of gene expression

About: Regulation of gene expression is a research topic. Over the lifetime, 85456 publications have been published within this topic receiving 5832845 citations. The topic is also known as: GO:0010468 & gene expression regulation.

Multiple types of skeletal muscle atrophy involve a common program of changes in gene expression

Abstract: Skeletal muscle atrophy is a debilitating response to starvation and many systemic diseases including diabetes, cancer, and renal failure. We had proposed that a common set of transcriptional adaptations underlie the loss of muscle mass in these different states. To test this hypothesis, we used cDNA microarrays to compare the changes in content of specific mRNAs in muscles atrophying from different causes. We compared muscles from fasted mice, from rats with cancer cachexia, streptozotocin-induced diabetes mellitus, uremia induced by subtotal nephrectomy, and from pair-fed control rats. Although the content of >90% of mRNAs did not change, including those for the myofibrillar apparatus, we found a common set of genes (termed atrogins) that were induced or suppressed in muscles in these four catabolic states. Among the strongly induced genes were many involved in protein degradation, including polyubiquitins, Ub fusion proteins, the Ub ligases atrogin-1/MAFbx and MuRF-1, multiple but not all subunits of the 20S proteasome and its 19S regulator, and cathepsin L. Many genes required for ATP production and late steps in glycolysis were down-regulated, as were many transcripts for extracellular matrix proteins. Some genes not previously implicated in muscle atrophy were dramatically up-regulated (lipin, metallothionein, AMP deaminase, RNA helicase-related protein, TG interacting factor) and several growth-related mRNAs were down-regulated (P311, JUN, IGF-1-BP5). Thus, different types of muscle atrophy share a common transcriptional program that is activated in many systemic diseases.

A gene expression database for the molecular pharmacology of cancer

Abstract: We used cDNA microarrays to assess gene expression profiles in 60 human cancer cell lines used in a drug discovery screen by the National Cancer Institute. Using these data, we linked bioinformatics and chemoinformatics by correlating gene expression and drug activity patterns in the NCI60 lines. Clustering the cell lines on the basis of gene expression yielded relationships very different from those obtained by clustering the cell lines on the basis of their response to drugs. Gene-drug relationships for the clinical agents 5-fluorouracil and L-asparaginase exemplify how variations in the transcript levels of particular genes relate to mechanisms of drug sensitivity and resistance. This is the first study to integrate large databases on gene expression and molecular pharmacology.