Matthew J. Marton

Gene expression profiling predicts clinical outcome of breast cancer.

Breast cancer patients with the same stage of disease can have markedly different treatment responses and overall outcome. The strongest predictors for metastases (for example, lymph node status and histological grade) fail to classify accurately breast tumours according to their clinical behaviour. Chemotherapy or hormonal therapy reduces the risk of distant metastases by approximately one-third; however, 70–80% of patients receiving this treatment would have survived without it. None of the signatures of breast cancer gene expression reported to date allow for patient-tailored therapy strategies. Here we used DNA microarray analysis on primary breast tumours of 117 young patients, and applied supervised classification to identify a gene expression signature strongly predictive of a short interval to distant metastases (‘poor prognosis’ signature) in patients without tumour cells in local lymph nodes at diagnosis (lymph node negative). In addition, we established a signature that identifies tumours of BRCA1 carriers. The poor prognosis signature consists of genes regulating cell cycle, invasion, metastasis and angiogenesis. This gene expression profile will outperform all currently used clinical parameters in predicting disease outcome. Our findings provide a strategy to select patients who would benefit from adjuvant therapy.

Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer

We describe a flexible system for gene expression profiling using arrays of tens of thousands of oligonucleotides synthesized in situ by an ink-jet printing method employing standard phosphoramidite chemistry. We have characterized the dependence of hybridization specificity and sensitivity on parameters including oligonucleotide length, hybridization stringency, sequence identity, sample abundance, and sample preparation method. We find that 60-mer oligonucleotides reliably detect transcript ratios at one copy per cell in complex biological samples, and that ink-jet arrays are compatible with several different sample amplification and labeling techniques. Furthermore, results using only a single carefully selected oligonucleotide per gene correlate closely with those obtained using complementary DNA (cDNA) arrays. Most of the genes for which measurements differ are members of gene families that can only be distinguished by oligonucleotides. Because different oligonucleotide sequences can be specified for each array, we anticipate that ink-jet oligonucleotide array technology will be useful in a wide variety of DNA microarray applications.

Transcriptional Profiling Shows that Gcn4p Is a Master Regulator of Gene Expression during Amino Acid Starvation in Yeast

ABSTRACT Starvation for amino acids induces Gcn4p, a transcriptional activator of amino acid biosynthetic genes in Saccharomyces cerevisiae. In an effort to identify all genes regulated by Gcn4p during amino acid starvation, we performed cDNA microarray analysis. Data from 21 pairs of hybridization experiments using two different strains derived from S288c revealed that more than 1,000 genes were induced, and a similar number were repressed, by a factor of 2 or more in response to histidine starvation imposed by 3-aminotriazole (3AT). Profiling of a gcn4Δ strain and a constitutively induced mutant showed that Gcn4p is required for the full induction by 3AT of at least 539 genes, termed Gcn4p targets. Genes in every amino acid biosynthetic pathway except cysteine and genes encoding amino acid precursors, vitamin biosynthetic enzymes, peroxisomal components, mitochondrial carrier proteins, and autophagy proteins were all identified as Gcn4p targets. Unexpectedly, genes involved in amino acid biosynthesis represent only a quarter of the Gcn4p target genes. Gcn4p also activates genes involved in glycogen homeostasis, and mutant analysis showed that Gcn4p suppresses glycogen levels in amino acid-starved cells. Numerous genes encoding protein kinases and transcription factors were identified as targets, suggesting that Gcn4p is a master regulator of gene expression. Interestingly, expression profiles for 3AT and the alkylating agent methyl methanesulfonate (MMS) overlapped extensively, and MMS inducedGCN4 translation. Thus, the broad transcriptional response evoked by Gcn4p is produced by diverse stress conditions. Finally, profiling of a gcn4Δ mutant uncovered an alternative induction pathway operating at many Gcn4p target genes in histidine-starved cells.

Experimental annotation of the human genome using microarray technology.

The most important product of the sequencing of a genome is a complete, accurate catalogue of genes and their products, primarily messenger RNA transcripts and their cognate proteins. Such a catalogue cannot be constructed by computational annotation alone; it requires experimental validation on a genome scale. Using ‘exon’ and ‘tiling’ arrays fabricated by ink-jet oligonucleotide synthesis, we devised an experimental approach to validate and refine computational gene predictions and define full-length transcripts on the basis of co-regulated expression of their exons. These methods can provide more accurate gene numbers and allow the detection of mRNA splice variants and identification of the tissue- and disease-specific conditions under which genes are expressed. We apply our technique to chromosome 22q under 69 experimental condition pairs, and to the entire human genome under two experimental conditions. We discuss implications for more comprehensive, consistent and reliable genome annotation, more efficient, full-length complementary DNA cloning strategies and application to complex diseases.

Widespread aneuploidy revealed by DNA microarray expression profiling

Expression profiling using DNA microarrays holds great promise for a variety of research applications, including the systematic characterization of genes discovered by sequencing projects. To demonstrate the general usefulness of this approach, we recently obtained expression profiles for nearly 300 Saccharomyces cerevisiae deletion mutants. Approximately 8% of the mutants profiled exhibited chromosome-wide expression biases, leading to spurious correlations among profiles. Competitive hybridization of genomic DNA from the mutant strains and their isogenic parental wild-type strains showed they were aneuploid for whole chromosomes or chromosomal segments. Expression profile data published by several other laboratories also suggest the use of aneuploid strains. In five separate cases, the extra chromosome harboured a close homologue of the deleted gene; in two cases, a clear growth advantage for cells acquiring the extra chromosome was demonstrated. Our results have implications for interpreting whole-genome expression data, particularly from cells known to suffer genomic instability, such as malignant or immortalized cells.

Role of scaffolds in MAP kinase pathway specificity revealed by custom design of pathway-dedicated signaling proteins

BACKGROUND Signal transduction pathways with shared components must be insulated from each other to avoid the inappropriate activation of multiple pathways by a single stimulus. Scaffold proteins are thought to contribute to this specificity by binding select substrates. RESULTS We have studied the ability of scaffold proteins to influence signaling by the yeast kinase Ste11, a MAPKKK molecule that participates in three distinct MAP kinase pathways: mating, filamentation, and HOG. We used protein fusions to force Ste11 to associate preferentially with a subset of its possible binding partners in vivo, including Ste5, Ste7, and Pbs2. Signaling became confined to a particular pathway when Ste11 was covalently attached to these scaffolds or substrates. This pathway bias was conferred upon both stimulus-activated and constitutively active forms of Ste11. We also used membrane-targeted derivatives of the mating pathway scaffold, Ste5, to show that stimulus-independent signaling initiated by this scaffold remained pathway specific. Finally, we demonstrate that loss of pathway insulation has a negative physiological consequence, as nonspecific activation of both the HOG and mating pathways interfered with proper execution of the mating pathway. CONCLUSIONS The signaling properties of these kinase fusions support a model in which scaffold proteins dictate substrate choice and promote pathway specificity by presenting preferred substrates in high local concentration. Furthermore, insulation is inherent to scaffold-mediated signaling and does not require that signaling be initiated by pathway-specific stimuli or activator proteins. Our results give insight into the mechanisms and physiological importance of pathway insulation and provide a foundation for the design of customized signaling proteins.

Identification of genes over-expressed in small cell lung carcinoma using suppression subtractive hybridization and cDNA microarray expression analysis

To identify genes that are differentially over-expressed in Small Cell Lung Carcinoma (SCLC) we have used a combination of suppression subtractive hybridization and cDNA microarray to analyse the expression profiles of 2400 cDNAs clones. Genes that are over-expressed in SCLC were identified using 32 pairs of fluorescence-labeled cDNA samples representing various lung tumors and normal tissues. This comprehensive approach has resulted in the identification of 209 genes that are differentially over-expressed in SCLC. Quantitative real-time PCR was used to further validate the expression of 43 genes in SCLC tumors and various normal tissues. Discussed in this report are nine genes, which showed the most promising SCLC tumor to normal tissue differential expression profiles, including seven known and two novel genes. The large number of differentially expressed genes identified from this analysis and the characterization of these genes will provide valuable information in better understanding the biology of SCLC and help us in developing these gene products as potential targets for diagnostic as well as therapeutic usage.

Navigating the rapids: the development of regulated next-generation sequencing-based clinical trial assays and companion diagnostics

Over the past decade, next-generation sequencing (NGS) technology has experienced meteoric growth in the aspects of platform, technology, and supporting bioinformatics development allowing its widespread and rapid uptake in research settings. More recently, NGS-based genomic data have been exploited to better understand disease development and patient characteristics that influence response to a given therapeutic intervention. Cancer, as a disease characterized by and driven by the tumor genetic landscape, is particularly amenable to NGS-based diagnostic (Dx) approaches. NGS-based technologies are particularly well suited to studying cancer disease development, progression and emergence of resistance, all key factors in the development of next-generation cancer Dxs. Yet, to achieve the promise of NGS-based patient treatment, drug developers will need to overcome a number of operational, technical, regulatory, and strategic challenges. Here, we provide a succinct overview of the state of the clinical NGS field in terms of the available clinically targeted platforms and sequencing technologies. We discuss the various operational and practical aspects of clinical NGS testing that will facilitate or limit the uptake of such assays in routine clinical care. We examine the current strategies for analytical validation and Food and Drug Administration (FDA)-approval of NGS-based assays and ongoing efforts to standardize clinical NGS and build quality control standards for the same. The rapidly evolving companion diagnostic (CDx) landscape for NGS-based assays will be reviewed, highlighting the key areas of concern and suggesting strategies to mitigate risk. The review will conclude with a series of strategic questions that face drug developers and a discussion of the likely future course of NGS-based CDx development efforts.

Refined anatomical isolation of functional sleep circuits exhibits distinctive regional and circadian gene transcriptional profiles

Powerful new approaches to study molecular variation in distinct neuronal populations have recently been developed enabling a more precise investigation of the control of neural circuits involved in complex behaviors such as wake and sleep. We applied laser capture microdissection (LCM) to isolate precise brain nuclei from rat CNS at opposing circadian time points associated with wake and sleep. Discrete anatomical and temporal analysis was performed to examine the extent of variation in the transcriptional control associated with both identifiable anatomical nuclei and with light/dark cycle. Precise isolation of specific brain nuclei regulating sleep and arousal, including the LC, SCN, TMN, VTA, and VLPO, demonstrated robust changes in gene expression. Many of these differences were not observed in previous studies where whole brain lysates or gross dissections were used to probe for changes in gene expression. The robust and differential profiles of genomic data obtained from the approaches used herein underscore the requirement for careful anatomical refinement in CNS gene expression studies designed to understand genomic control within behaviorally-linked, but functionally isolated brain nuclei.

Practical Guidance for Implementing Predictive Biomarkers into Early Phase Clinical Studies

The recent U.S. Food and Drug Administration (FDA) coapprovals of several therapeutic compounds and their companion diagnostic devices (FDA News Release, 2011, 2013) to identify patients who would benefit from treatment have led to considerable interest in incorporating predictive biomarkers in clinical studies. Yet, the translation of predictive biomarkers poses unique technical, logistic, and regulatory challenges that need to be addressed by a multidisciplinary team including discovery scientists, clinicians, biomarker experts, regulatory personnel, and assay developers. These issues can be placed into four broad categories: sample collection, assay validation, sample analysis, and regulatory requirements. In this paper, we provide a primer for drug development teams who are eager to implement a predictive patient segmentation marker into an early clinical trial in a way that facilitates subsequent development of a companion diagnostic. Using examples of nucleic acid-based assays, we briefly review common issues encountered when translating a biomarker to the clinic but focus primarily on key practical issues that should be considered by clinical teams when planning to use a biomarker to balance arms of a study or to determine eligibility for a clinical study.