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.

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Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

Summary. We propose the elastic net, a new regularization and variable selection method. Real world data and a simulation study show that the elastic net often outperforms the lasso, while enjoying a similar sparsity of representation. In addition, the elastic net encourages a grouping effect, where strongly correlated predictors tend to be in or out of the model together.The elastic net is particularly useful when the number of predictors (p) is much bigger than the number of observations (n). By contrast, the lasso is not a very satisfactory variable selection method in the

/pdf/regularization-and-variable-selection-via-the-elastic-net-4z8q6j5o0i.pdf

Regularization and variable selection via the elastic net

Human breast tumours are diverse in their natural history and in their responsiveness to treatments. Variation in transcriptional programs accounts for much of the biological diversity of human cells and tumours. In each cell, signal transduction and regulatory systems transduce information from the cell's identity to its environmental status, thereby controlling the level of expression of every gene in the genome. Here we have characterized variation in gene expression patterns in a set of 65 surgical specimens of human breast tumours from 42 different individuals, using complementary DNA microarrays representing 8,102 human genes. These patterns provided a distinctive molecular portrait of each tumour. Twenty of the tumours were sampled twice, before and after a 16-week course of doxorubicin chemotherapy, and two tumours were paired with a lymph node metastasis from the same patient. Gene expression patterns in two tumour samples from the same individual were almost always more similar to each other than either was to any other sample. Sets of co-expressed genes were identified for which variation in messenger RNA levels could be related to specific features of physiological variation. The tumours could be classified into subtypes distinguished by pervasive differences in their gene expression patterns.

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Molecular portraits of human breast tumours

Variable and feature selection have become the focus of much research in areas of application for which datasets with tens or hundreds of thousands of variables are available. These areas include text processing of internet documents, gene expression array analysis, and combinatorial chemistry. The objective of variable selection is three-fold: improving the prediction performance of the predictors, providing faster and more cost-effective predictors, and providing a better understanding of the underlying process that generated the data. The contributions of this special issue cover a wide range of aspects of such problems: providing a better definition of the objective function, feature construction, feature ranking, multivariate feature selection, efficient search methods, and feature validity assessment methods.

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An introduction to variable and feature selection

We develop fast algorithms for estimation of generalized linear models with convex penalties. The models include linear regression, two-class logistic regression, and multinomial regression problems while the penalties include l(1) (the lasso), l(2) (ridge regression) and mixtures of the two (the elastic net). The algorithms use cyclical coordinate descent, computed along a regularization path. The methods can handle large problems and can also deal efficiently with sparse features. In comparative timings we find that the new algorithms are considerably faster than competing methods.

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Regularization Paths for Generalized Linear Models via Coordinate Descent

In response to a wound, fibroblasts are activated to migrate toward the wound, to proliferate and to contribute to the wound healing process. We hypothesize that changes in pre-mRNA processing occurring as fibroblasts enter the proliferative cell cycle are also important for promoting their migration. RNA sequencing of fibroblasts induced into quiescence by contact inhibition reveals downregulation of genes involved in mRNA processing, including splicing and cleavage and polyadenylation factors. These genes also show differential exon use, especially increased intron retention in quiescent fibroblasts compared to proliferating fibroblasts. Mapping the 3′ ends of transcripts reveals that longer transcripts from distal polyadenylation sites are more prevalent in quiescent fibroblasts and are associated with increased expression and transcript stabilization based on genome-wide transcript decay analysis. Analysis of dermal excisional wounds in mice reveals that proliferating cells adjacent to wounds express higher levels of cleavage and polyadenylation factors than quiescent fibroblasts in unwounded skin. Quiescent fibroblasts contain reduced levels of the cleavage and polyadenylation factor CstF-64. CstF-64 knockdown recapitulates changes in isoform selection and gene expression associated with quiescence, and results in slower migration. Our findings support cleavage and polyadenylation factors as a link between cellular proliferation state and migration.

/pdf/alternative-polyadenylation-factors-link-cell-cycle-to-23w9wgy16e.pdf

Alternative polyadenylation factors link cell cycle to migration

We have developed a rapid method for unambiguous identification and mutant fraction determination of individual mutants in mixtures of DNA sequence variants each differing by one or a few nucleotides. This method has applications to such diverse areas as interpretation of mutational spectra, screening of populations for polymorphisms and identification of species in environmental mixtures. In our approach, a mixture of unknown sequences labeled with a fluorescent dye is combined with a set of predetermined sequences (standards) representing the variants to be assayed. Labeling the standards with another dye allows the two sets of variants to be measured independently. Using constant denaturing capillary electrophoresis, the sequence variants are separated as individual peaks on the basis of differential melting equilibria. The unknown sequence variants are initially identified based on co-migration with particular standards. This preliminary identification is verified by hybridization of the unknown variants with the comigrating standards within the capillary. We demonstrate the use of capillary electrophoresis hybridization to dissect complex mutational spectra of human cells in culture. The method described in this communication offers the capacity to identify and measure specific point mutants within a mixture of variants of the same prototype DNA sequence. Such measurements would be instrumental in several important applications. Mutational spectra, for example, are powerful tools in studying causes and mechanisms leading to mutation, cancer and aging in humans (1), and are represented by complex mixtures of somatic mutations (2). Another potential application is the analysis of spectra of polymorphisms (3). In this case, many DNA samples from a large number of individuals that represent a population of interest may be pooled together and processed as one. The distribution of polymorphisms within the population will be represented by the distribution of sequence variants in the mixture that results from such pooling and can be measured by our method. In a similar way, it may be possible to analyze the frequency distribution of

Identification of point mutations in mixtures by capillary electrophoresis hybridization

Identification of MYC target genes whose expression is either induced or repressed by c-myc induction in human fibroblasts is disclosed. Also disclosed are methods of inducing or repressing expression of MYC target genes.

Methods for defining MYC target genes and uses thereof

Development and applications of mutational spectra technology

Cell migration is a highly conserved process involving cytoskeletal reorganization and restructuring of the surrounding extracellular matrix. Although there are many studies describing mechanisms underlying cell motility, little has been reported about the contribution of alternative isoform use toward cell migration. Here, we investigated whether alternative isoform use can affect cell migration focusing on reversion-inducing-cysteine-rich protein with Kazal motifs (RECK), an established inhibitor of cell migration. We found that a shorter isoform of RECK is more highly expressed in proliferating fibroblasts, in TGF-β-treated fibroblasts, and in tumors compared with differentiated tissue. Knockdown of this short RECK isoform reduces fibroblast migration through Matrigel. Thus, this short isoform of RECK generated by a combination of alternative splicing and alternative polyadenylation plays an opposing role to the canonical RECK isoform, as knockdown of canonical RECK results in faster cell migration through Matrigel. We show that the short RECK protein competes with matrix metalloprotease 9 (MMP9) for binding to the Kazal motifs of canonical RECK, thus liberating MMP9 from an inactivating interaction with canonical RECK. Our studies provide a new paradigm and a detailed mechanism for how alternative isoform use can regulate cell migration by producing two proteins with opposing effects from the same genetic locus.

Hilary A. Coller

Papers

Alternative polyadenylation factors link cell cycle to migration

Identification of point mutations in mixtures by capillary electrophoresis hybridization

Methods for defining MYC target genes and uses thereof

Development and applications of mutational spectra technology

RECK isoforms have opposing effects on cell migration.