The PI3-Kinase p110β Isoform Controls Severity of Cocaine-Induced Sequelae and Alters the Striatal Transcriptome

Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

The Molecular Signatures Database (MSigDB) is one of the most widely used and comprehensive databases of gene sets for performing gene set enrichment analysis. Since its creation, MSigDB has grown beyond its roots in metabolic disease and cancer to include >10,000 gene sets. These better represent a wider range of biological processes and diseases, but the utility of the database is reduced by increased redundancy across, and heterogeneity within, gene sets. To address this challenge, here we use a combination of automated approaches and expert curation to develop a collection of "hallmark" gene sets as part of MSigDB. Each hallmark in this collection consists of a "refined" gene set, derived from multiple "founder" sets, that conveys a specific biological state or process and displays coherent expression. The hallmarks effectively summarize most of the relevant information of the original founder sets and, by reducing both variation and redundancy, provide more refined and concise inputs for gene set enrichment analysis.

A decade ago, we hypothesized that drug addiction can be viewed as a transition from voluntary, recreational drug use to compulsive drug-seeking habits, neurally underpinned by a transition from prefrontal cortical to striatal control over drug seeking and taking as well as a progression from the ventral to the dorsal striatum. Here, in the light of burgeoning, supportive evidence, we reconsider and elaborate this hypothesis, in particular the refinements in our understanding of ventral and dorsal striatal mechanisms underlying goal-directed and habitual drug seeking, the influence of drug-associated Pavlovian-conditioned stimuli on drug seeking and relapse, and evidence for impairments in top-down prefrontal cortical inhibitory control over this behavior. We further review animal and human studies that have begun to define etiological factors and individual differences in the propensity to become addicted to drugs, leading to the description of addiction endophenotypes, especially for cocaine addiction. We consider the prospect of novel treatments for addiction that promote abstinence from and relapse to drug use.