Concordance between an FDA-approved companion diagnostic and an alternative assay kit for assessing homologous recombination deficiency in ovarian cancer

OBJECTIVE

Authors evaluated the performance of a commercially available next-generation sequencing assay kit; this was based on genomic content from Illumina's TruSight™ Oncology 500 research assay that identifies BRCA variants and proprietary algorithms licensed from Myriad and, with additional genomic content, measures the homologous recombination deficiency (HRD) genomic instability score (GIS) in tumor tissue (TSO 500 HRD assay).

METHODS

Data from the TSO 500 HRD assay were compared with data from the Myriad MyChoice®CDx PLUS assay (Myriad assay). Prevalence rates for overall HRD status and BRCA mutations (a deleterious or suspected deleterious BRCA1 or BRCA2 mutation or both) and assay agreement rates for HRD GIS and BRCA analysis were assessed in ovarian tumor samples. Pearson correlations of the continuous HRD GIS and analytic sensitivity and specificity were evaluated.

RESULTS

The prevalence of overall HRD positivity was 51.2% (TSO 500 HRD assay) versus 49.2% (Myriad assay) and the prevalence of BRCA mutations was 27.6% (TSO 500 HRD assay) versus 25.5% (Myriad assay). After post-processing optimization, concordance of the HRD GIS was 0.980 in all samples and 0.976 in the non-BRCA mutation cohort; the area under the receiver operating characteristic curve was 0.995 and 0.992, respectively.

CONCLUSIONS

Comparison between the Illumina and Myriad assays showed that overall HRD status, the individual components of BRCA analysis, and HRD GIS detection results were highly concordant (>93%), suggesting the TSO 500 HRD assay will approach the analytical accuracy of the FDA-approved Myriad assay.

Concordance between single-nucleotide polymorphism–based genomic instability assays and a next-generation sequencing–based homologous recombination deficiency test

Background:

We evaluated the performance of single-nucleotide polymorphism (SNP) genotyping arrays OncoScan (Thermo Fisher Scientific, San Diego, CA) and Infinium CytoSNP-850K (CytoSNP; Illumina, Waltham, MA) for assessing homologous recombination deficiency (HRD) genomic instability.

Methods:

DNA (pretreatment samples) across 20 tumor types was evaluated with OncoScan, CytoSNP, and the clinically validated HRD test. Copy number variation (CNV) and loss of heterozygosity (LOH) analyses were performed with ASCATv2.5.1. Aggregate HRD genomic metrics included LOH, telomeric-allelic imbalance number (TAI), and large-scale state transition (LST). Associations between BRCA mutation (BRCAm) status and the clinically validated HRD test metric (dichotomized at a clinical cut-off) were evaluated using area under the receiver operating characteristic (AUROC); Spearman ρ was calculated for continuous metrics. CNV segmentation and HRD genomic metrics were calculated (n = 120, n = 106, and n = 126 for OncoScan, CytoSNP and clinically validated HRD test, respectively).

Results:

When assessed by SNP arrays, the genomic metric demonstrated good association with BRCAm (AUROC of HRD: OncoScan, 0.87; CytoSNP, 0.75) and the clinically validated test (cut-off, 42; AUROC of HRD: OncoScan, 0.92; CytoSNP, 0.91). The genomic metrics demonstrated good correlation with the clinically validated aggregate HRD test metric (ρ: OncoScan, 0.82; CytoSNP, 0.81) and for each component (ρ: OncoScan, 0.68 [LOH], 0.76 [TAI], and 0.78 [LST]; CytoSNP, 0.59 [LOH], 0.77 [TAI], and 0.82 [LST]). HRD assessed by SNP genotyping arrays and the clinically validated test showed good correlation.

Conclusion:

OncoScan and CytoSNP may potentially identify most HRD-positive tumors with appropriate clinically relevant cut-offs.

T cell-inflamed gene expression profile and PD-L1 expression and pembrolizumab efficacy in advanced esophageal cancer

Aim: Investigate the relationship between response to pembrolizumab and expression of the 18-gene T cell-inflamed gene expression profile (TcellinfGEP) or PD-L1 combined positive score (CPS) in esophageal cancer. Materials & methods: This analysis included heavily pretreated patients with advanced/metastatic esophageal/gastroesophageal junction adenocarcinoma or squamous cell carcinoma who received pembrolizumab in the single-arm, phase II study KEYNOTE-180. PD-L1 CPS was evaluated with PD-L1 IHC 22C3 pharmDx. Results: In patients with squamous cell carcinoma, trends toward enrichment for responders were observed for patients with PD-L1 CPS ≥10 tumors. In patients with adenocarcinoma, a trend was observed for TcellinfGEP but not for PD-L1. Conclusion: TcellinfGEP and PD-L1 CPS may enrich for responders to pembrolizumab in patients with esophageal cancer. Clinical trial registration: NCT02559687 (ClinicalTrials.gov).

OUP accepted manuscript

Background

Homologous recombination deficiency (HRD) is a phenotype that is characterized by the inability of a cell to effectively repair DNA double-strand breaks using the homologous recombination repair (HRR) pathway. Loss-of-function genes involved in this pathway can sensitize tumors to poly(adenosine diphosphate [ADP]-ribose) polymerase (PARP) inhibitors and platinum-based chemotherapy, which target the destruction of cancer cells by working in concert with HRD through synthetic lethality. However, to identify patients with these tumors, it is vital to understand how to best measure homologous repair (HR) status and to characterize the level of alignment in these measurements across different diagnostic platforms. A key current challenge is that there is no standardized method to define, measure, and report HR status using diagnostics in the clinical setting.

Methods

Friends of Cancer Research convened a consortium of project partners from key healthcare sectors to address concerns about the lack of consistency in the way HRD is defined and methods for measuring HR status.

Results

This publication provides findings from the group’s discussions that identified opportunities to align the definition of HRD and the parameters that contribute to the determination of HR status. The consortium proposed recommendations and best practices to benefit the broader cancer community.

Conclusion

Overall, this publication provides additional perspectives for scientist, physician, laboratory, and patient communities to contextualize the definition of HRD and various platforms that are used to measure HRD in tumors.

Prognostic significance of T-cell-inflamed gene expression profile and PD-L1 expression in patients with esophageal cancer

Purpose

The ability of the T‐cell–inflamed gene expression profile (GEP) to predict clinical outcome in esophageal cancer (EC) is unknown. This retrospective observational study assessed the prognostic value of GEP and programmed death ligand 1 (PD‐L1) expression in patients with EC treated in routine clinical practice.

Methods

Tumor samples of 294 patients from three centers in Denmark, South Korea, and the United States, collected between 2005 and 2017, were included. T‐cell–inflamed GEP score was defined as non‐low or low using a cutoff of −1.54. A combined positive score (CPS) ≥10 was defined as PD‐L1 expression positivity. Associations between overall survival (OS) and GEP status and PD‐L1 expression were explored by Cox proportional hazards models adjusting for age, sex, histology, stage, and performance status.

Results

Median age was 65 years; 63% of patients had adenocarcinoma (AC) and 37% had squamous cell carcinoma (SCC). Thirty‐six percent of tumors were GEP non‐low, with higher prevalence in AC (46%) than SCC (18%). Twenty‐one percent were PD‐L1–positive: 32% in South Korean samples versus 16% in non‐Asian samples and 26% in SCC versus 18% in AC. GEP scores and PD‐L1 CPS were weakly correlated (Spearman’s R = 0.363). OS was not significantly associated with GEP status (non‐low vs low; adjusted hazard ratio, 0.91 [95% CI, 0.69–1.19]) or PD‐L1 expression status.

Conclusion

Neither GEP nor PD‐L1 expression was a prognostic marker in Asian and non‐Asian patients with EC.

Association of programmed death ligand 1 expression with prognosis among patients with ten uncommon advanced cancers

AIM

PD-L1 expression and high levels of microsatellite instability (MSI-H) may predict response to checkpoint inhibitors, but their prevalence and prognostic value are unknown in many cancers.

METHODS

We retrospectively evaluated PD-L1 combined positive score (CPS) and MSI-H and their association with clinical outcomes among patients with ten advanced uncommon cancers.

RESULTS

398 of 426 patients (93%) had a valid PD-L1 result; most (242; 61%) had CPS ≥1. Prevalence of MSI-H tumors was 8/360. Median overall survival was shorter among patients with PD-L1 CPS ≥1 tumors after first-line treatment (23.0 vs 39.7 months, p = 0.014).

CONCLUSION

PD-L1 was commonly expressed in solid tumors, and CPS ≥1 was associated with shorter overall survival. Prevalence of MSI-H was low.

Pre-Analytical Considerations for Successful Next-Generation Sequencing (NGS): Challenges and Opportunities for Formalin-Fixed and Paraffin-Embedded Tumor Tissue (FFPE) Samples

In cancer drug discovery, it is important to investigate the genetic determinants of response or resistance to cancer therapy as well as factors that contribute to adverse events in the course of clinical trials. Despite the emergence of new technologies and the ability to measure more diverse analytes (e.g., circulating tumor cell (CTC), circulating tumor DNA (ctDNA), etc.), tumor tissue is still the most common and reliable source for biomarker investigation. Because of its worldwide use and ability to preserve samples for many decades at ambient temperature, formalin-fixed, paraffin-embedded tumor tissue (FFPE) is likely to be the preferred choice for tissue preservation in clinical practice for the foreseeable future. Multiple analyses are routinely performed on the same FFPE samples (such as Immunohistochemistry (IHC), in situ hybridization, RNAseq, DNAseq, TILseq, Methyl-Seq, etc.). Thus, specimen prioritization and optimization of the isolation of analytes is critical to ensure successful completion of each assay. FFPE is notorious for producing suboptimal DNA quality and low DNA yield. However, commercial vendors tend to request higher DNA sample mass than what is actually required for downstream assays, which restricts the breadth of biomarker work that can be performed. We evaluated multiple genomics service laboratories to assess the current state of NGS pre-analytical processing of FFPE. Significant differences in pre-analytical capabilities were observed. Key aspects are highlighted and recommendations are made to improve the current practice in translational research.

Analytical Validation of AmpliChip p53 Research Test for Archival Human Ovarian FFPE Sections

The p53 tumor suppressor gene (TP53) is reported to be mutated in nearly half of all tumors and plays a central role in genome integrity. Detection of mutations in p53 can be accomplished by many assays, including the AmpliChip p53 Research Test. The AmpliChip p53 Research Test has been successfully used to determine p53 status in hematologic malignancies and fresh frozen solid tissues but there are few reports of using the assay with formalin fixed, paraffin-embedded (FFPE) tissue. The objective of this study was to describe analytical performance characterization of the AmpliChip p53 Research Test to detect p53 mutations in genomic DNA isolated from archival FFPE human ovarian tumor tissues. Method correlation with sequencing showed 96% mutation-wise agreement and 99% chip-wise agreement. We furthermore observed 100% agreement (113/113) of the most prevalent TP53 mutations. Workflow reproducibility was 96.8% across 8 samples, with 2 operators, 2 reagent lots and 2 instruments. Section-to-section reproducibility was 100% for each sample across a 60 μm region of the FFPE block from ovarian tumors. These data indicate that the AmpliChip p53 Research Test is an accurate and reproducible method for detecting mutations in TP53 from archival FFPE human ovarian specimens.

HCV genotyping from NGS short reads and its application in genotype detection from HCV mixed infected plasma

Genotyping of hepatitis C virus (HCV) plays an important role in the treatment of HCV. As new genotype-specific treatment options become available, it has become increasingly important to have accurate HCV genotype and subtype information to ensure that the most appropriate treatment regimen is selected. Most current genotyping methods are unable to detect mixed genotypes from two or more HCV infections. Next generation sequencing (NGS) allows for rapid and low cost mass sequencing of viral genomes and provides an opportunity to probe the viral population from a single host. In this paper, the possibility of using short NGS reads for direct HCV genotyping without genome assembly was evaluated. We surveyed the publicly-available genetic content of three HCV drug target regions (NS3, NS5A, NS5B) in terms of whether these genes contained genotype-specific regions that could predict genotype. Six genotypes and 38 subtypes were included in this study. An automated phylogenetic analysis based HCV genotyping method was implemented and used to assess different HCV target gene regions. Candidate regions of 250-bp each were found for all three genes that have enough genetic information to predict HCV genotypes/subtypes. Validation using public datasets shows 100% genotyping accuracy. To test whether these 250-bp regions were sufficient to identify mixed genotypes, we developed a random primer-based method to sequence HCV plasma samples containing mixtures of two HCV genotypes in different ratios. We were able to determine the genotypes without ambiguity and to quantify the ratio of the abundances of the mixed genotypes in the samples. These data provide a proof-of-concept that this random primed, NGS-based short-read genotyping approach does not need prior information about the viral population and is capable of detecting mixed viral infection.

Past, current and future approaches to querying MAPK pathway activation: status and clinical implications

MAPK pathway activation related to cancer development has drawn a great deal of attention in the field of personalized medicine in recent years. Many different approaches and assays have been developed to query the activation of this pathway and to develop life-saving treatments. The goal of this review article is threefold. First, to provide a brief overview of the many mutation assays that have been used to detect MAPK pathway activation, and to compare pros and cons of these assay platforms. Second, to focus on one custom-designed multiplexing mutation assay that is currently used to support an ongoing clinical trial and to show the novel features of this assay and its relevance in addressing unmet clinical needs. Third, to provide future perspectives of these MAPK pathway gene mutation detection efforts and to suggest how what we have learned from past and current approaches should guide future developments.

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.

Development and validation of a clinical trial patient stratification assay that interrogates 27 mutation sites in MAPK pathway genes

Somatic mutations identified on genes related to the cancer-developing signaling pathways have drawn attention in the field of personalized medicine in recent years. Treatments developed to target a specific signaling pathway may not be effective when tumor activating mutations occur downstream of the target and bypass the targeted mechanism. For instance, mutations detected in KRAS/BRAF/NRAS genes can lead to EGFR-independent intracellular signaling pathway activation. Most patients with these mutations do not respond well to anti-EGFR treatment. In an effort to detect various mutations in FFPE tissue samples among multiple solid tumor types for patient stratification many mutation assays were evaluated. Since there were more than 30 specific mutations among three targeted RAS/RAF oncogenes that could activate MAPK pathway genes, a custom designed Single Nucleotide Primer Extension (SNPE) multiplexing mutation assay was developed and analytically validated as a clinical trial assay. Throughout the process of developing and validating the assay we overcame many technical challenges which include: the designing of PCR primers for FFPE tumor tissue samples versus normal blood samples, designing of probes for detecting consecutive nucleotide double mutations, the kinetics and thermodynamics aspects of probes competition among themselves and against target PCR templates, as well as validating an assay when positive control tumor tissue or cell lines with specific mutations are not available. We used Next Generation sequencing to resolve discordant calls between the SNPE mutation assay and Sanger sequencing. We also applied a triplicate rule to reduce potential false positives and false negatives, and proposed special considerations including pre-define a cut-off percentage for detecting very low mutant copies in the wild-type DNA background.

High-throughput simultaneous analysis of RNA, protein, and lipid biomarkers in heterogeneous tissue samples

BACKGROUND

With expanding biomarker discovery efforts and increasing costs of drug development, it is critical to maximize the value of mass-limited clinical samples. The main limitation of available methods is the inability to isolate and analyze, from a single sample, molecules requiring incompatible extraction methods. Thus, we developed a novel semiautomated method for tissue processing and tissue milling and division (TMAD).

METHODS

We used a SilverHawk atherectomy catheter to collect atherosclerotic plaques from patients requiring peripheral atherectomy. Tissue preservation by flash freezing was compared with immersion in RNAlater®, and tissue grinding by traditional mortar and pestle was compared with TMAD. Comparators were protein, RNA, and lipid yield and quality. Reproducibility of analyte yield from aliquots of the same tissue sample processed by TMAD was also measured.

RESULTS

The quantity and quality of biomarkers extracted from tissue prepared by TMAD was at least as good as that extracted from tissue stored and prepared by traditional means. TMAD enabled parallel analysis of gene expression (quantitative reverse-transcription PCR, microarray), protein composition (ELISA), and lipid content (biochemical assay) from as little as 20 mg of tissue. The mean correlation was r = 0.97 in molecular composition (RNA, protein, or lipid) between aliquots of individual samples generated by TMAD. We also demonstrated that it is feasible to use TMAD in a large-scale clinical study setting.

CONCLUSIONS

The TMAD methodology described here enables semiautomated, high-throughput sampling of small amounts of heterogeneous tissue specimens by multiple analytical techniques with generally improved quality of recovered biomolecules.

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.

Effects of atmospheric ozone on microarray data quality

A data anomaly was observed that affected the uniformity and reproducibility of fluorescent signal across DNA microarrays. Results from experimental sets designed to identify potential causes (from microarray production to array scanning) indicated that the anomaly was linked to a batch process; further work allowed us to localize the effect to the posthybridization array stringency washes. Ozone levels were monitored and highly correlated with the batch effect. Controlled exposures of microarrays to ozone confirmed this factor as the root cause, and we present data that show susceptibility of a class of cyanine dyes (e.g., Cy5, Alexa 647) to ozone levels as low as 5-10 ppb for periods as short as 10-30 s. Other cyanine dyes (e.g., Cy3, Alexa 555) were not significantly affected until higher ozone levels (> 100 ppb). To address this environmental effect, laboratory ozone levels should be kept below 2 ppb (e.g., with filters in HVAC) to achieve high quality microarray data.

Functional interactions between yeast translation eukaryotic elongation factor (eEF) 1A and eEF3

The translation elongation machinery in fungi differs from other eukaryotes in its dependence upon eukaryotic elongation factor 3 (eEF3). eEF3 is essential in vivo and required for each cycle of the translation elongation process in vitro. Models predict eEF3 affects the delivery of cognate aminoacyl-tRNA, a function performed by eEF1A, by removing deacylated tRNA from the ribosomal Exit site. To dissect eEF3 function and its link to the A-site activities of eEF1A, we have identified a temperature-sensitive allele of the YEF3 gene. The F650S substitution, located between the two ATP binding cassettes, reduces both ribosome-dependent and intrinsic ATPase activities. In vivo this mutation increases sensitivity to aminoglycosidic drugs, causes a 50% reduction of total protein synthesis at permissive temperatures, slows run-off of polyribosomes, and reduces binding to eEF1A. Reciprocally, excess eEF3 confers synthetic slow growth, increased drug sensitivity, and reduced translation in an allele specific fashion with an E122K mutation in the GTP binding domain of eEF1A. In addition, this mutant form of eEF1A shows reduced binding of eEF3. Thus, optimal in vivo interactions between eEF3 and eEF1A are critical for protein synthesis.

A gene-expression signature as a predictor of survival in breast cancer

BACKGROUND

A more accurate means of prognostication in breast cancer will improve the selection of patients for adjuvant systemic therapy.

METHODS

Using microarray analysis to evaluate our previously established 70-gene prognosis profile, we classified a series of 295 consecutive patients with primary breast carcinomas as having a gene-expression signature associated with either a poor prognosis or a good prognosis. All patients had stage I or II breast cancer and were younger than 53 years old; 151 had lymph-node-negative disease, and 144 had lymph-node-positive disease. We evaluated the predictive power of the prognosis profile using univariable and multivariable statistical analyses.

RESULTS

Among the 295 patients, 180 had a poor-prognosis signature and 115 had a good-prognosis signature, and the mean (+/-SE) overall 10-year survival rates were 54.6+/-4.4 percent and 94.5+/-2.6 percent, respectively. At 10 years, the probability of remaining free of distant metastases was 50.6+/-4.5 percent in the group with a poor-prognosis signature and 85.2+/-4.3 percent in the group with a good-prognosis signature. The estimated hazard ratio for distant metastases in the group with a poor-prognosis signature, as compared with the group with the good-prognosis signature, was 5.1 (95 percent confidence interval, 2.9 to 9.0; P<0.001). This ratio remained significant when the groups were analyzed according to lymph-node status. Multivariable Cox regression analysis showed that the prognosis profile was a strong independent factor in predicting disease outcome.

CONCLUSIONS

The gene-expression profile we studied is a more powerful predictor of the outcome of disease in young patients with breast cancer than standard systems based on clinical and histologic criteria.

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.

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.

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.

Transcriptional profiling shows that Gcn4p is a master regulator of gene expression during amino acid starvation in yeast

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 gcn4Delta 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 induced GCN4 translation. Thus, the broad transcriptional response evoked by Gcn4p is produced by diverse stress conditions. Finally, profiling of a gcn4Delta mutant uncovered an alternative induction pathway operating at many Gcn4p target genes in histidine-starved cells.

Transcriptional profiling shows that Gcn4p is a master regulator of gene expression during amino acid starvation in yeast

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 gcn4Delta 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 induced GCN4 translation. Thus, the broad transcriptional response evoked by Gcn4p is produced by diverse stress conditions. Finally, profiling of a gcn4Delta mutant uncovered an alternative induction pathway operating at many Gcn4p target genes in histidine-starved cells.

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.

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.

Functional discovery via a compendium of expression profiles

Ascertaining the impact of uncharacterized perturbations on the cell is a fundamental problem in biology. Here, we describe how a single assay can be used to monitor hundreds of different cellular functions simultaneously. We constructed a reference database or "compendium" of expression profiles corresponding to 300 diverse mutations and chemical treatments in S. cerevisiae, and we show that the cellular pathways affected can be determined by pattern matching, even among very subtle profiles. The utility of this approach is validated by examining profiles caused by deletions of uncharacterized genes: we identify and experimentally confirm that eight uncharacterized open reading frames encode proteins required for sterol metabolism, cell wall function, mitochondrial respiration, or protein synthesis. We also show that the compendium can be used to characterize pharmacological perturbations by identifying a novel target of the commonly used drug dyclonine.

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.

Signaling and circuitry of multiple MAPK pathways revealed by a matrix of global gene expression profiles

Genome-wide transcript profiling was used to monitor signal transduction during yeast pheromone response. Genetic manipulations allowed analysis of changes in gene expression underlying pheromone signaling, cell cycle control, and polarized morphogenesis. A two-dimensional hierarchical clustered matrix, covering 383 of the most highly regulated genes, was constructed from 46 diverse experimental conditions. Diagnostic subsets of coexpressed genes reflected signaling activity, cross talk, and overlap of multiple mitogen-activated protein kinase (MAPK) pathways. Analysis of the profiles specified by two different MAPKs-Fus3p and Kss1p-revealed functional overlap of the filamentous growth and mating responses. Global transcript analysis reflects biological responses associated with the activation and perturbation of signal transduction pathways.

Drug target validation and identification of secondary drug target effects using DNA microarrays

We describe here a method for drug target validation and identification of secondary drug target effects based on genome-wide gene expression patterns. The method is demonstrated by several experiments, including treatment of yeast mutant strains defective in calcineurin, immunophilins or other genes with the immunosuppressants cyclosporin A or FK506. Presence or absence of the characteristic drug 'signature' pattern of altered gene expression in drug-treated cells with a mutation in the gene encoding a putative target established whether that target was required to generate the drug signature. Drug dependent effects were seen in 'targetless' cells, showing that FK506 affects additional pathways independent of calcineurin and the immunophilins. The described method permits the direct confirmation of drug targets and recognition of drug-dependent changes in gene expression that are modulated through pathways distinct from the drug's intended target. Such a method may prove useful in improving the efficiency of drug development programs.

Interaction between the retinoid X receptor and transcription factor IIB is ligand-dependent in vivo

The retinoid X receptor (RXR) influences gene activation through heterodimeric and homodimeric association with DNA and associates with TATA binding protein, TAF110, and cAMP response element-binding protein-binding protein; yet the molecular mechanisms responsible for gene activation by RXRs remain incompletely defined. Since the general transcription factor IIB (TFIIB) is a common target of sequence-specific transcriptional activators, we suspected that RXR might regulate target genes via an interaction with TFIIB. Coimmunoprecipitation, far Western analysis, and glutathione S-transferase binding studies indicated that murine RXR beta (mRXR beta) was capable of binding to human TFIIB in vitro. Functional analysis with a dual-hybrid yeast system and cotransfection assays revealed the interaction of mRXR beta with TFIIB to be ligand-dependent in vivo. Truncation experiments mapped the essential binding regions to the carboxyl region of mRXR beta (amino acids (aa) 254-389) and two regions in the carboxyl region of TFIIB (aa 178-201 and aa 238-271). Furthermore, the delta 390-410 mRXR beta mutant bound to TFIIB in vitro but was not active in the dual-hybrid yeast system, suggesting that the extreme carboxyl region of RXR was required for in vivo interaction with TFIIB. These data indicate that interaction of mRXR beta with TFIIB is specific, direct, and ligand-dependent in vivo and suggest that gene activation by RXR involves TFIIB.

Evidence that GCN1 and GCN20, translational regulators of GCN4, function on elongating ribosomes in activation of eIF2alpha kinase GCN2

In the yeast Saccharomyces cerevisiae, phosphorylation of translation initiation factor eIF2 by protein kinase GCN2 leads to increased translation of the transcriptional activator GCN4 in amino acid-starved cells. The GCN1 and GCN20 proteins are components of a protein complex required for the stimulation of GCN2 kinase activity under starvation conditions. GCN20 is a member of the ATP-binding cassette (ABC) family, most of the members of which function as membrane-bound transporters, raising the possibility that the GCN1/GCN20 complex regulates GCN2 indirectly as an amino acid transporter. At odds with this idea, indirect immunofluorescence revealed cytoplasmic localization of GCN1 and no obvious association with plasma or vacuolar membranes. In addition, a fraction of GCN1 and GCN20 cosedimented with polysomes and 80S ribosomes, and the ribosome association of GCN20 was largely dependent on GCN1. The C-terminal 84% of GCN20 containing the ABCs was found to be dispensable for complex formation with GCN1 and for the stimulation of GCN2 kinase function. Because ABCs provide the energy-coupling mechanism for ABC transporters, these results also contradict the idea that GCN20 regulates GCN2 as an amino acid transporter. The N-terminal 15 to 25% of GCN20, which is critically required for its regulatory function, was found to interact with an internal segment of GCN1 similar in sequence to translation elongation factor 3 (EF3). Based on these findings, we propose that GCN1 performs an EF3-related function in facilitating the activation of GCN2 by uncharged tRNA on translating ribosomes. The physical interaction between GCN20 and the EF3-like domain in GCN1 could allow for modulation of GCN1 activity, and the ABC domains in GCN20 may be involved in this regulatory function. A human homolog of GCN1 has been identified, and the portion of this protein most highly conserved with yeast GCN1 has sequence similarity to EF3. Thus, similar mechanisms for the detection of uncharged tRNA on translating ribosomes may operate in yeast and human cells.

GCN20, a novel ATP binding cassette protein, and GCN1 reside in a complex that mediates activation of the eIF-2 alpha kinase GCN2 in amino acid-starved cells

GCN2 is a protein kinase that phosphorylates the alpha-subunit of translation initiation factor 2 (eIF-2) and thereby stimulates translation of GCN4 mRNA in amino acid-starved cells. We isolated a null mutation in a previously unidentified gene, GCN20, that suppresses the growth-inhibitory effect of eIF-2 alpha hyperphosphorylation catalyzed by mutationally activated forms of GCN2. The deletion of GCN20 in otherwise wild-type strains impairs derepression of GCN4 translation and reduces the level of eIF-2 alpha phosphorylation in vivo, showing that GCN20 is a positive effector of GCN2 kinase function. In accordance with this conclusion, GCN20 was co-immunoprecipitated from cell extracts with GCN1, another factor required to activate GCN2, and the two proteins interacted in the yeast two-hybrid system. We conclude that GCN1 and GCN20 are components of a protein complex that couples the kinase activity of GCN2 to the availability of amino acids. GCN20 is a member of the ATP binding cassette (ABC) family of proteins and is closely related to ABC proteins identified in Caenorhabditis elegans, rice and humans, suggesting that the function of GCN20 may be conserved among diverse eukaryotic organisms.

GCN1, a translational activator of GCN4 in Saccharomyces cerevisiae, is required for phosphorylation of eukaryotic translation initiation factor 2 by protein kinase GCN2

Phosphorylation of the alpha subunit of eukaryotic translation initiation factor 2 (eIF-2 alpha) by the protein kinase GCN2 mediates increased translation of the transcriptional activator GCN4 in amino acid-starved yeast cells. We show that this key phosphorylation event and the attendant translational induction of GCN4 are dependent on the product of a previously uncharacterized gene, GCN1. Inactivation of GCN1 did not affect the level of eIF-2 alpha phosphorylation when mammalian eIF-2 alpha kinases were expressed in yeast cells in place of GCN2, arguing against an involvement of GCN1 in dephosphorylation of eIF-2 alpha. In addition, while GCN1 is required in vivo for phosphorylation of eIF-2 alpha by GCN2, cell extracts from gcn1 delta strains contained wild-type levels of GCN2 eIF-2 alpha-kinase activity. On the basis of these results, we propose that GCN1 is not needed for GCN2 kinase activity per se but is required for in vivo activation of GCN2 in response to the starvation signal, uncharged tRNA. GCN1 encodes a protein of 297 kDa with an 88-kDa region that is highly similar in sequence to translation elongation factor 3 identified in several fungal species. This sequence similarity raises the possibility that GCN1 interacts with ribosomes or tRNA molecules and functions in conjunction with GCN2 in monitoring uncharged tRNA levels during the process of translation elongation.

The adenovirus E4 17-kilodalton protein complexes with the cellular transcription factor E2F, altering its DNA-binding properties and stimulating E1A-independent accumulation of E2 mRNA

E2F is a cellular DNA-binding factor. Its binding activity is changed within adenovirus-infected cells so that it binds cooperatively to pairs of properly spaced and oriented E2F recognition sites. In the work described in this report, the conversion to cooperative binding was shown to require the adenovirus E4 17-kilodalton (kDa) polypeptide. Mutant viruses carrying alterations within the E4 17-kDa coding region failed to generate the infection-specific, cooperatively binding form of E2F. It was possible to alter E2F from uninfected cells so that it bound cooperatively by incubation with a partially purified fraction obtained from infected cells. The E4 17-kDa protein copurified with this activity and was also found to be present in a complex containing E2F. Consistent with its ability to alter the binding of E2F to its recognition sites within the E2 promoter, the E4 17-kDa polypeptide contributed to maximal expression of E2 mRNAs in some cell types. Its ability to enhance E2 transcription did not require expression of the E1A transactivator protein. These results are consistent with a model which proposes that the E4 17-kDa polypeptide binds to the cellular E2F factor, altering its binding behavior and thereby enhancing its ability to stimulate transcription.