Expression microarray reproducibility is improved by optimising purification steps in RNA amplification and labelling

Genes expressed at low levels raise false discovery rates in RNA samples contaminated with genomic DNA

Background

RNA preparations contaminated with genomic DNA (gDNA) are frequently disregarded by RNA-seq studies. Such contamination may generate false results; however, their effect on the outcomes of RNA-seq analyses is unknown. To address this gap in our knowledge, here we added different concentrations of gDNA to total RNA preparations and subjected them to RNA-seq analysis.

Results

We found that the contaminating gDNA altered the quantification of transcripts at relatively high concentrations. Differentially expressed genes (DEGs) resulting from gDNA contamination may therefore contribute to higher rates of false enrichment of pathways compared with analogous samples lacking numerous DEGs. A strategy was developed to correct gene expression levels in gDNA-contaminated RNA samples, which assessed the magnitude of contamination to improve the reliability of the results.

Conclusions

Our study indicates that caution must be exercised when interpreting results associated with low-abundance transcripts. The data provided here will likely serve as a valuable resource to evaluate the influence of gDNA contamination on RNA-seq analysis, particularly related to the detection of putative novel gene elements.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08785-1.

Analysis of extracellular vesicle mRNA derived from plasma using the nCounter platform

Extracellular vesicles (EVs) are double-layered phospholipid membrane vesicles that are released by most cells and can mediate intercellular communication through their RNA cargo. In this study, we tested if the NanoString nCounter platform can be used for the analysis of EV-mRNA. We developed and optimized a methodology for EV enrichment, EV-RNA extraction and nCounter analysis. Then, we demonstrated the validity of our workflow by analyzing EV-RNA profiles from the plasma of 19 cancer patients and 10 controls and developing a gene signature to differentiate cancer versus control samples. TRI reagent outperformed automated RNA extraction and, although lower plasma input is feasible, 500 μL provided highest total counts and number of transcripts detected. A 10-cycle pre-amplification followed by DNase treatment yielded reproducible mRNA target detection. However, appropriate probe design to prevent genomic DNA binding is preferred. A gene signature, created using a bioinformatic algorithm, was able to distinguish between control and cancer EV-mRNA profiles with an area under the ROC curve of 0.99. Hence, the nCounter platform can be used to detect mRNA targets and develop gene signatures from plasma-derived EVs.

Equine early pregnancy endocrine profiles and ipsilateral endometrial immune cell, gene expression and protein localisation response

We investigated the early effects of the equine embryo on maternal serum concentrations of insulin-like growth factor 1 (IGF1), leptin and adiponectin, uterine immune cells and genes and proteins related to embryo development and the maintenance of pregnancy. Ipsilateral endometrial expression was assessed on Days 7 and 13 after ovulation for the following transcripts: oestrogen receptor ERα (ESR1), progesterone receptor (PGR), progestin and adipoQ receptor family member 5 (PAQR5), oxytocin receptor (OXTR), prostaglandin-endoperoxide synthase 2 (PTGS2), raf-1 proto-oncogene serine/threonine kinase (RAF1), p21-activated kinase 6 (PAK6), fibroblast growth factor family member 9 (FGF9), IGF1 and its receptor (IGF1R), mucin 1 (MUC1), osteopontin (OPN), leptin receptor (LEPR) and adiponectin receptors 1 and 2 (ADIPOR1 and ADIPOR2). Ipsilateral endometrial immunological cell infiltration and immunohistochemical protein localisation were evaluated on Days 7, 10 and 13 after ovulation for ERα, PGR, OXTR, PTGS2, IGF1, IGF1R, IGF2 and MUC1. Serum hormone concentrations were not affected by reproductive status. Pregnancy downregulated ESR1 and PGR mRNA levels, upregulated the expression of all other genes and affected the expression of all genes, except PGR, on Day 7 (compared with eight genes affected at Day 13). Proteins were affected by pregnancy or by its interaction with other variables (day of extraction and endometrial compartment). Pregnant mares had a higher lymphocyte count, which decreased towards Day 13. The effect of pregnancy on leucocytes and proteins was more evident in superficial endometrial compartments. The results of this study suggest that the equine embryo exerts prompt paracrine regulation of critical biological processes.

The presence of an embryo affects day 14 uterine transcriptome depending on the nutritional status in sheep. b. Immune system and uterine remodeling

Transcriptomics and bioinformatics were used to investigate the potential interactions of undernutrition and the presence of the conceptus at the time of maternal recognition of pregnancy on uterine immune system and remodeling. Adult Rasa Aragonesa ewes were allocated to one of two planes of nutrition for 28 days: maintenance energy intake (control; 5 cyclic, 6 pregnant ewes) providing 7.8 MJ of metabolisable energy and 0.5 maintenance intake (undernourished; 6 cyclic, 7 pregnant ewes) providing 3.9 MJ of metabolisable energy per ewe. Uterine gene expression was measured using Agilent 15 K Sheep Microarray chip on day 14 of estrus or pregnancy. Functional bioinformatics analyses were performed using PANTHER (Protein ANalysis THrough Evolutionary Relationships) Classification System. Pregnancy affected the expression of 18 genes in both control and undernourished ewes, underscoring the relevance for embryo-maternal interactions. Immune system evidenced by classical interferon stimulated genes were activated in control and -in a lesser extent-in undernourished pregnant vs cyclic ewes. Genes involved in uterine remodeling such as protein metabolism were also upregulated with the presence of an embryo in control and undernourished ewes. However, relevant genes for the adaptation of the uterus to the embryo were differentially expressed between pregnant vs cyclic ewes both in control and undernourished groups. Undernutrition alone led to an overall weak activation of immune system pathways both in cyclic and pregnant ewes. Data revealed that cellular and immune adaptations of the uterus to pregnancy are dependent on the nutritional status.

The embryo affects day 14 uterine transcriptome depending on nutritional status in sheep. a. Metabolic adaptation to pregnancy in nourished and undernourished ewes

This study investigated the effects of undernutrition and the presence of the conceptus at the time of maternal recognition of pregnancy on the expression of uterine indicators of metabolism in ewes. Adult Rasa Aragonesa ewes were allocated to one of two planes of nutrition for 28 days: maintenance energy intake (control; 5 cyclic and 6 pregnant ewes) providing 7.8 MJ of metabolisable energy, and 0.5 maintenance intake (undernourished; 6 cyclic and 7 pregnant ewes) providing 3.9 MJ of metabolisable energy per ewe. RNA from intercaruncular uterine tissue was harvested at slaughter on Day 14 of estrous cycle or pregnancy, and hybridized to the Agilent 15K Sheep Microarray chip. Functional bioinformatics analyses were performed using PANTHER (Protein ANalysis THrough Evolutionary Relationships) Classification System. The presence of the embryo upregulated expression of genes encoding peptide and monocarboxylate transporters regardless of nutritional treatment, although the degree of gene expression was lower in undernourished ewes. Genes encoding enzymes involved in glycolysis were downregulated both in pregnant control and undernourished ewes, probably as a compensatory mechanism for the increased glucose transport to the uterus. Compared with control cyclic ewes, control pregnant ewes had greater expression of genes involved in oxidation of fatty acids, suggesting increased uterine energy demands. This was not observed in undernourished pregnant animals when compared to undernourished cyclic ewes; nevertheless, those animals had lower uterine expression of enzymes involved in fatty acid biosynthesis. The presence of the embryo upregulated genes involved in electron transport probably as a result of increased energy demands for pregnancy. Overall, the data indicate that depending on the nutritional status of ewe, pregnancy alters gene expression of metabolic pathways related to energy generation in the uterus. An impairment in nutrient transport and metabolism in the uterus of pregnant undernourished ewes may explain the greater embryo mortality associated with undernutrition.

Gene Expression Detection Assay for Cancer Clinical Use

Cancer is a genetic disease where genetic variations cause abnormally functioning genes that appear to alter expression. Proteins, the final products of gene expression, determine the phenotypes and biological processes. Therefore, detecting gene expression levels can be used for cancer diagnosis, prognosis, and treatment prediction in a clinical setting. In this review, we investigated six gene expression assay systems (qRT-PCR, DNA microarray, nCounter, RNA-Seq, FISH, and tissue microarray) that are currently being used in clinical cancer studies. Some of these methods are also commonly used in a modified way; for example, detection of DNA content or protein expression. Herein, we discuss their principles, sample preparation, design, quantification and sensitivity, data analysis, time for sample preparation and processing, and cost. We also compared these methods according to their sample selection, particularly for the feasibility of using formalin-fixed paraffin-embedded (FFPE) samples, which are routinely archived for clinical cancer studies. We intend to provide a guideline for choosing an assay method with respect to its oncological applications in a clinical setting.

Extraction of bacterial RNA from soil: challenges and solutions

Detection of bacterial gene expression in soil emerged in the early 1990s and provided information on bacterial responses in their original soil environments. As a key procedure in the detection, extraction of bacterial RNA from soil has attracted much interest, and many methods of soil RNA extraction have been reported in the past 20 years. In addition to various RT-PCR-based technologies, new technologies for gene expression analysis, such as microarrays and high-throughput sequencing technologies, have recently been applied to examine bacterial gene expression in soil. These technologies are driving improvements in RNA extraction protocols. In this mini-review, progress in the extraction of bacterial RNA from soil is summarized with emphasis on the major difficulties in the development of methodologies and corresponding strategies to overcome them.

Microgenomics of ameloblastoma

Gene expression profiles of human ameloblastoma microdissected cells were characterized with the purpose of identifying genes and their protein products that could be targeted as diagnostic and prognostic markers as well as for potential therapeutic interventions. Five formalin-fixed, decalcified, paraffin-embedded samples of ameloblastoma were subjected to laser capture microdissection, linear mRNA amplification, and hybridization to oligonucleotide human 41,000 RNA arrays and compared with universal human reference RNA, to determine the gene expression signature. Assessment of the data by Significance Analysis of Microarrays (SAM) and cluster analysis showed that 38 genes were highly expressed (two-fold increase) in all samples, while 41 genes were underexpressed (two-fold reduction). Elements of the sonic hedgehog pathway and Wingless type MMTV integration site family were validated by immunohistochemistry. We have identified the expression of multiple genes and protein products that could serve as potential diagnostic, prognostic, and therapeutic targets.

Comparison of gene expression patterns between avian and human ovarian cancers

OBJECTIVES

A putative model of spontaneous cancer has been described in the laying hen that bears significant similarities to human ovarian cancer. Our objective was to characterize and compare the patterns of gene expression in chicken and human forms of this disease.

METHODS

RNA from 20 localized and metastatic ovarian and oviductal chicken tumor samples was isolated, amplified using in vitro transcription, and hybridized against normal ovarian epithelium to a customized cDNA microarray constructed for these studies. Differentially expressed genes were identified for localized ovarian, metastatic ovarian, and oviductal (or tubal) cancer by class comparison using BRB-ArrayTools. Results were validated with semi-quantitative PCR. A gene list (prediction model) constructed with the class prediction tool was used in a human ovarian cancer microarray obtained from the GEO datasets (GSE6008) in order to compare these results across species.

RESULTS

Class comparison analysis between localized ovarian, metastatic ovarian and oviductal cancer yielded 41 different informative probes that coded for 27 unique genes. Localized ovarian samples clustered between metastatic ovarian and oviductal cancer samples. Using our chicken data as a training set and leaving oviductal samples out of the analysis, we created a prediction model that classified early stage and advanced stage human ovarian cancer gene expression arrays with 78% overall accuracy.

CONCLUSIONS

Gene expression of spontaneous ovarian cancer in the chicken is comparable to gene expression patterns of human ovarian cancer.

Tissue banking of diagnostic lung cancer biopsies for extraction of high quality RNA

INTRODUCTION

There is a clear need to develop a practical approach to obtain high quality RNA for gene expression analysis from lung cancer patients. Current approaches are restricted to using material from surgical resection specimens. We systematically investigated whether high quality RNA could be obtained from routine lung cancer diagnostic biopsies to determine the optimum method.

METHODS

Extra biopsies were taken at diagnosis from patients later confirmed to have lung cancer. Comparisons were made between RNA extracted from samples snap frozen in liquid nitrogen and those treated with an RNA preservative before freezing. Further comparisons were made between biopsies taken by different methods.

RESULTS

Acceptable RNA for gene expression analysis was extracted from 72% of lung cancer biopsies. Use of an RNA preservative for storage allowed the extraction of higher quality, more intact RNA from biopsies gathered by both endobronchial forceps and transbronchial needle aspiration. High quality RNA could also be extracted from computed tomography-guided needle core biopsies.

CONCLUSION

Banking lung cancer biopsy specimens by storage in an RNA preservative solution will allow use of a broader spectrum of lung cancers for gene expression analysis. We describe a model that makes personalized medicine for lung cancer patients a more practical proposition.

Early pregnancy alters the metabolic responses to restricted nutrition in sheep

This study investigated whether a 27-day period of nutrition at half-maintenance during early pregnancy (up to Day 14) could alter maternal endocrine responses. Forty-six ewes were fed all or half of their maintenance requirements and slaughtered on Day 14 of the oestrous cycle or pregnancy. We used real time RT-PCR to study gene expression of growth hormone receptor (GHR) and leptin in adipose tissue and GHR, GHR1A and of the insulin-like growth factor I (IGF-I) in the liver. Blood profiles of metabolites and metabolic hormones were also determined. Throughout the experiment, underfed animals presented lower body weight and body condition, greater plasma concentrations of non-esterified fatty acids (NEFA), and lower plasma concentrations of leptin, compared to adequately fed animals. Undernutrition affected the patterns of gene expression in adipose and hepatic tissues, and the responses differed between pregnant and non-pregnant ewes. In adequately fed ewes, pregnancy up-regulated leptin mRNA expression in adipose tissue, a response that was impaired in underfed ewes. The hepatic expression of IGF-I mRNA was increased by pregnancy in underfed animals while no effect was observed in adequately fed ewes. It remains to be determined whether the changes in the endocrine milieu are paralleled by modifications in uterine gene expression that could alter the environment of the embryo during early pregnancy.

Effect of undernutrition on the uterine environment during maternal recognition of pregnancy in sheep

The effects of pregnancy and undernutrition on endometrial gene expression were investigated in ewes fed all or half their maintenance requirements and killed on Day 14 of pregnancy or of the oestrous cycle. The endometrial expression of progesterone, oestrogen, oxytocin and interferon receptors (PR, ERα, OXTR and IFNAR, respectively), cyclo-oxygenase (COX)-2, proliferating cell nuclear antigen (PCNA), insulin-like growth factors (IGF)-I and -II, and IGF-1 receptor (IGF-1R) was studied by immunohistochemistry or real-time reverse transcription–polymerase chain reaction. The luminal epithelium of cyclic control ewes was devoid of PR staining and had relatively high levels of ERα, OXTR, COX-2 and IFNAR2. The presence of a conceptus decreased the in vitro uterine secretion of prostaglandin (PG) F2α and the expression of IFNAR2 in most cell types, and increased the gene expression of IGF-I and IGF-II. Undernutrition tended to increase ERα protein and gene, but decreased in vitro uterine secretion of PGE2 and the gene expression of IFNAR2 in cyclic ewes. There was no effect of undernutrition on pregnancy rates or the number of conceptuses recovered. Consistent with this, undernutrition of pregnant ewes did not have any effect on uterine gene expression. Moreover, in cases where changes were observed in cyclic ewes, these changes were negated when a conceptus was present.

In vitro differentiation of human calvarial suture derived cells with and without dexamethasone does not induce in vivo-like expression

Osteogenic supplements are a requirement for osteoblastic cell differentiation during in vitro culture of human calvarial suture-derived cell populations. We investigated the ability of ascorbic acid and beta-glycerophosphate with and without the addition of dexamethasone to stimulate in vivo-like osteoblastic differentiation. Cells were isolated from unfused and prematurely fused suture tissue from patients with syndromic and non-syndromic craniosynostosis and cultured in each osteogenic medium for varying lengths of time. The effect of media supplementation was investigated with respect to the ability of cells to form mineralised bone nodules and the expression of five osteodifferentiation marker genes (COL1A1, ALP, BSP, OC and RUNX2), and five genes that are differentially expressed during human premature suture fusion (GPC3, RBP4, C1QTNF3, WIF1 and FGF2). Cells from unfused sutures responded more slowly to osteogenic media but formed comparable bone nodules to fused suture-derived cells after 16 days of culture in either osteogenic media. However, gene expression differed between unfused and fused suture-derived cells, as did expression in each osteogenic medium. When compared to expression in the explant tissue of origin, neither medium induced a level or profile of gene expression similar to that seen in vivo. Overall, our results demonstrate that cells from the same suture that are isolated during different stages of morphogenesis in vivo, despite being de-differentiated to a similar level in vitro, respond uniquely and differently to each osteogenic medium. Further, we suggest that neither cell culture medium recapitulates differentiation via activation of the same genetic cascades as occurs in vivo.

Gene expression profiling of breast cancer

DNA microarray platforms for gene expression profiling were invented relatively recently, and breast cancer has been among the earliest and most intensely studied diseases using this technology. The molecular signatures so identified help reveal the biologic spectrum of breast cancers, provide diagnostic tools as well as prognostic and predictive gene signatures, and may identify new therapeutic targets. Data are best presented in an open access format to facilitate external validation, the most crucial step in identifying robust, reproducible gene signatures suitable for clinical translation. Clinically practical applications derived from full expression profile studies already in use include reduced versions of microarrays representing key discriminatory genes and therapeutic targets, quantitative polymerase chain reaction assays, or immunohistochemical surrogate panels (suitable for application to standard pathology blocks). Prospective trials are now underway to determine the value of such tools for clinical decision making in breast cancer; these efforts may serve as a model for using such approaches in other tumor types.

High-sensitivity detection methods for low-abundance RNA species: applications for functional genomics research

Gene expression analysis has facilitated a more complete understanding of the molecular biology of cellular processes and how variations of RNA expression are useful for the classification of various diseases. Furthermore, recent analysis of a variety of noncoding RNAs, such as microRNAs, has demonstrated that these RNAs play an important role in many cellular events, including cell differentiation and death, and may also serve as biological markers for disease. Besides helping in the understanding of diseases, RNA analysis is used in drug discovery, patient prognosis and treatment evaluation. One obstacle left to overcome is the amount of material required for the analysis, particularly when trying to extract information from precious, limited, clinical samples. Here we review the many approaches scientists take to either amplify the amount of RNA or amplify the signal generated from small amounts of RNA.

Structural model of the Plasmodium CDK, Pfmrk, a novel target for malaria therapeutics

Malaria, with 300-500 million clinical cases resulting in 1-3 million fatalities a year, is one of the most deadly tropical diseases. As current antimalarial therapeutics become increasingly ineffective due to parasitic resistance, there exists an urgent need to develop and pursue new therapeutic strategies. Recent genome sequencing and molecular cloning projects have identified several enzymes from Plasmodium (P.) falciparum that may represent novel drug targets, including a family of proteins that are homologous to the mammalian cyclin-dependent kinases (CDKs). CDKs are essential for the control of the mammalian cell cycle and, based on the conservation of the CDKs across species, the plasmodial CDKs are expected to play a crucial role in parasitic growth. Here we present a 3D structural model of Pfmrk, a putative human CDK activating kinase (CAK) homolog in P. falciparum. Notable features of the present structural model include: (1) parameterization of the Mg2+ hexacoordination system using ab initio quantum chemical calculations to accurately represent the ATP-kinase interaction; and (2) comparison between the docking scores and measured binding affinities for a series of oxindole-based Pfmrk inhibitors of known activity. Detailed analysis of inhibitor-Pfmrk binding interactions enabled us to identify specific residues (viz. Met66, Met75, Met91, Met94 and Phe143) within the Pfmrk binding pocket that may play an important role in inhibitor binding affinity and selectivity. The availability of this Pfmrk structural model, together with insights gained from analysis of ligand-receptor interactions, should promote the rational design of potent and selective Pfmrk inhibitors as antimalarial therapeutics.

Plasticity of the systemic inflammatory response to acute infection during critical illness: development of the riboleukogram

Background

Diagnosis of acute infection in the critically ill remains a challenge. We hypothesized that circulating leukocyte transcriptional profiles can be used to monitor the host response to and recovery from infection complicating critical illness.

Methodology/Principal Findings

A translational research approach was employed. Fifteen mice underwent intratracheal injections of live P. aeruginosa, P. aeruginosa endotoxin, live S. pneumoniae, or normal saline. At 24 hours after injury, GeneChip microarray analysis of circulating buffy coat RNA identified 219 genes that distinguished between the pulmonary insults and differences in 7-day mortality. Similarly, buffy coat microarray expression profiles were generated from 27 mechanically ventilated patients every two days for up to three weeks. Significant heterogeneity of VAP microarray profiles was observed secondary to patient ethnicity, age, and gender, yet 85 genes were identified with consistent changes in abundance during the seven days bracketing the diagnosis of VAP. Principal components analysis of these 85 genes appeared to differentiate between the responses of subjects who did versus those who did not develop VAP, as defined by a general trajectory (riboleukogram) for the onset and resolution of VAP. As patients recovered from critical illness complicated by acute infection, the riboleukograms converged, consistent with an immune attractor.

Conclusions/Significance

Here we present the culmination of a mouse pneumonia study, demonstrating for the first time that disease trajectories derived from microarray expression profiles can be used to quantitatively track the clinical course of acute disease and identify a state of immune recovery. These data suggest that the onset of an infection-specific transcriptional program may precede the clinical diagnosis of pneumonia in patients. Moreover, riboleukograms may help explain variance in the host response due to differences in ethnic background, gender, and pathogen. Prospective clinical trials are indicated to validate our results and test the clinical utility of riboleukograms.

Unravelling the molecular control of calvarial suture fusion in children with craniosynostosis

BACKGROUND

Craniosynostosis, the premature fusion of calvarial sutures, is a common craniofacial abnormality. Causative mutations in more than 10 genes have been identified, involving fibroblast growth factor, transforming growth factor beta, and Eph/ephrin signalling pathways. Mutations affect each human calvarial suture (coronal, sagittal, metopic, and lambdoid) differently, suggesting different gene expression patterns exist in each human suture. To better understand the molecular control of human suture morphogenesis we used microarray analysis to identify genes differentially expressed during suture fusion in children with craniosynostosis. Expression differences were also analysed between each unfused suture type, between sutures from syndromic and non-syndromic craniosynostosis patients, and between unfused sutures from individuals with and without craniosynostosis.

RESULTS

We identified genes with increased expression in unfused sutures compared to fusing/fused sutures that may be pivotal to the maintenance of suture patency or in controlling early osteoblast differentiation (i.e. RBP4, GPC3, C1QTNF3, IL11RA, PTN, POSTN). In addition, we have identified genes with increased expression in fusing/fused suture tissue that we suggest could have a role in premature suture fusion (i.e. WIF1, ANXA3, CYFIP2). Proteins of two of these genes, glypican 3 and retinol binding protein 4, were investigated by immunohistochemistry and localised to the suture mesenchyme and osteogenic fronts of developing human calvaria, respectively, suggesting novel roles for these proteins in the maintenance of suture patency or in controlling early osteoblast differentiation. We show that there is limited difference in whole genome expression between sutures isolated from patients with syndromic and non-syndromic craniosynostosis and confirmed this by quantitative RT-PCR. Furthermore, distinct expression profiles for each unfused suture type were noted, with the metopic suture being most disparate. Finally, although calvarial bones are generally thought to grow without a cartilage precursor, we show histologically and by identification of cartilage-specific gene expression that cartilage may be involved in the morphogenesis of lambdoid and posterior sagittal sutures.

CONCLUSION

This study has provided further insight into the complex signalling network which controls human calvarial suture morphogenesis and craniosynostosis. Identified genes are candidates for targeted therapeutic development and to screen for craniosynostosis-causing mutations.

BEX2 is overexpressed in a subset of primary breast cancers and mediates nerve growth factor/nuclear factor-kappaB inhibition of apoptosis in breast cancer cell lines

We have identified a novel subtype of estrogen receptor (ER)-positive breast cancers with improved outcome after tamoxifen treatment and characterized by overexpression of the gene BEX2. BEX2 and its homologue BEX1 have highly correlated expression and are part of a cluster enriched for ER response and apoptosis genes. BEX2 expression is induced after estradiol (E2) treatment with a peak at 3 h, suggesting BEX2 is an estrogen-regulated gene. BEX2 belongs to a family of genes, including BEX1, NGFRAP1 (alias BEX3), BEXL1 (alias BEX4), and NGFRAP1L1 (alias BEX5). Both BEX1 and NGFRAP1 interact with p75NTR and modulate nerve growth factor (NGF) signaling through nuclear factor-kappaB (NF-kappaB) to regulate cell cycle, apoptosis, and differentiation in neural tissues. In breast cancer cells, NGF inhibits C2-induced apoptosis through binding of p75NTR and NF-kappaB activation. Here, we show that BEX2 expression is necessary and sufficient for the NGF-mediated inhibition (through NF-kappaB activation) of C2-induced apoptosis. We also show that BEX2 modulates apoptosis of breast cancer cells in response to E2 (50 nmol/L) and tamoxifen (5 and 10 micromol/L). Furthermore, BEX2 overexpression enhances the antiproliferative effect of tamoxifen at pharmacologic dose (1 micromol/L). These data suggest that a NGF/BEX2/NF-kappaB pathway is involved in regulating apoptosis in breast cancer cells and in modulating response to tamoxifen in primary tumors.

A role for neurotensin in bicalutamide resistant prostate cancer cells

BACKGROUND

Anti-androgens are administered as a principal treatment for prostate cancer. Aggressive hormone refractory disease is characterized in some cases by the development of a neuroendocrine phenotype. However little attention has been paid to resistance pathways selected for by long-term treatment with non-steroidal anti-androgens.

METHODS

Using a resistant sub-line, LNCaP-Bic, we performed a comparative gene expression profiling using cDNA microarrays and target validation by qRT-PCR. Targets were then explored using cell proliferation, cell cycle analysis and in vitro invasion assays using siRNA technology.

RESULTS

Neurotensin/Neuromedin N (NTS) was upregulated in the LNCaP-Bic line at both the transcript and protein level. The resistant line was found to have an increased proliferation rate, more rapid cell cycle progression and increased invasiveness through Matrigel. Each phenotypic difference could be reduced using siRNA knockdown of NT.

CONCLUSION

Increased expression of NT in bicalutamide resistant prostate cancer cells induces cell proliferation and invasion suggesting that this peptide may contribute to the development of bicalutamide resistant prostate cancer.

Evaluation of global RNA amplification and its use for high-throughput transcript analysis of laser-microdissected endosperm

Laser microdissection (LM) provides a useful method for isolating specific cells or tissues from biological samples. Here, we adapted microdissection protocols to allow high-resolution transcript analysis of different tissues from developing Arabidopsis seed. Sufficient RNA ( approximately 50 ng) was extracted from endosperm tissue for RT-PCR. However, to obtain enough RNA for microarray analyses, it was necessary to amplify the RNA. PCR- and IVT-based amplification methods were investigated and several important technical aspects of amplification were identified (such as target truncation and alterations in signal intensity). We found that when starting from only 50 ng of RNA, amplification methods based on PCR and IVT produced sufficient product for reliable microarray hybridizations, with two-round IVT giving the best results. Microarray analyses, using endosperm-derived RNA amplified by two-round IVT, reproducibly identified endosperm enriched marker genes. Thus, when combined with RNA-amplification protocols, LM is a robust and reliable technique for high-throughput tissue-specific gene expression analysis.

A consensus prognostic gene expression classifier for ER positive breast cancer

BACKGROUND

A consensus prognostic gene expression classifier is still elusive in heterogeneous diseases such as breast cancer.

RESULTS

Here we perform a combined analysis of three major breast cancer microarray data sets to hone in on a universally valid prognostic molecular classifier in estrogen receptor (ER) positive tumors. Using a recently developed robust measure of prognostic separation, we further validate the prognostic classifier in three external independent cohorts, confirming the validity of our molecular classifier in a total of 877 ER positive samples. Furthermore, we find that molecular classifiers may not outperform classical prognostic indices but that they can be used in hybrid molecular-pathological classification schemes to improve prognostic separation.

CONCLUSION

The prognostic molecular classifier presented here is the first to be valid in over 877 ER positive breast cancer samples and across three different microarray platforms. Larger multi-institutional studies will be needed to fully determine the added prognostic value of molecular classifiers when combined with standard prognostic factors.

Improvement in the reproducibility and accuracy of DNA microarray quantification by optimizing hybridization conditions

Background

DNA microarrays, which have been increasingly used to monitor mRNA transcripts at a global level, can provide detailed insight into cellular processes involved in response to drugs and toxins. This is leading to new understandings of signaling networks that operate in the cell, and the molecular basis of diseases. Custom printed oligonucleotide arrays have proven to be an effective way to facilitate the applications of DNA microarray technology. A successful microarray experiment, however, involves many steps: well-designed oligonucleotide probes, printing, RNA extraction and labeling, hybridization, and imaging. Optimization is essential to generate reliable microarray data.

Results

Hybridization and washing steps are crucial for a successful microarray experiment. By following the hybridization and washing conditions recommended by an oligonucleotide provider, it was found that the expression ratios were compressed greater than expected and data analysis revealed a high degree of non-specific binding. A series of experiments was conducted using rat mixed tissue RNA reference material (MTRRM) and other RNA samples to optimize the hybridization and washing conditions. The optimized hybridization and washing conditions greatly reduced the non-specific binding and improved the accuracy of spot intensity measurements.

Conclusion

The results from the optimized hybridization and washing conditions greatly improved the reproducibility and accuracy of expression ratios. These experiments also suggested the importance of probe designs using better bioinformatics approaches and the need for common reference RNA samples for platform performance evaluation in order to fulfill the potential of DNA microarray technology.

A gene-expression signature to predict survival in breast cancer across independent data sets

Prognostic signatures in breast cancer derived from microarray expression profiling have been reported by two independent groups. These signatures, however, have not been validated in external studies, making clinical application problematic. We performed microarray expression profiling of 135 early-stage tumors, from a cohort representative of the demographics of breast cancer. Using a recently proposed semisupervised method, we identified a prognostic signature of 70 genes that significantly correlated with survival (hazard ratio (HR): 5.97, 95% confidence interval: 3.0-11.9, P = 2.7e-07). In multivariate analysis, the signature performed independently of other standard prognostic classifiers such as the Nottingham Prognostic Index and the 'Adjuvant!' software. Using two different prognostic classification schemes and measures, nearest centroid (HR) and risk ordering (D-index), the 70-gene classifier was also found to be prognostic in two independent external data sets. Overall, the 70-gene set was prognostic in our study and the two external studies which collectively include 715 patients. In contrast, we found that the two previously described prognostic gene sets performed less optimally in external validation. Finally, a common prognostic module of 29 genes that associated with survival in both our cohort and the two external data sets was identified. In spite of these results, further studies that profile larger cohorts using a single microarray platform, will be needed before prospective clinical use of molecular classifiers can be contemplated.

Prognostic gene expression signatures can be measured in tissues collected in RNAlater preservative

Gene expression signatures have the ability to serve in both prognostic and predictive capacities in patient management. The use of RNA as the starting material and the lability of this analyte, however, dictate that tissues must be snap-frozen or stored in a solution that can maintain the integrity of the RNA. We compared pairs of snap-frozen and RNAlater preservative-suspended tissue from 30 such paired lymph node-negative breast tumors and 21 such paired Dukes' B colon tumors. We assessed the correlation of gene expression profiles and prediction of recurrence based on two prognostic algorithms. Tissues stored in RNAlater preservative generated expression profiles with excellent correlation (average Pearson correlation coefficients of 0.97 and 0.94 for the breast and colon tumor pairs, respectively) compared to those produced by tissues that were snap-frozen. The correlation in the prediction of recurrence was 97% and 95% for the breast and colon tumor pairs, respectively, between these two types of tissue handling protocols. This novel finding demonstrates that prognostic signatures can be obtained from RNAlater preservative-suspended tissues, an important step in bringing gene expression signatures to the clinic.

Scanning microarrays at multiple intensities enhances discovery of differentially expressed genes

MOTIVATION

Scanning parameters are often overlooked when optimizing microarray experiments. A scanning approach that extends the dynamic data range by acquiring multiple scans of different intensities has been developed.

RESULTS

Data from each of three scan intensities (low, medium, high) were analyzed separately using multiple scan and linear regression approaches to identify and compare the sets of genes that exhibit statistically significant differential expression. In the multiple scan approach only one-third of the differentially expressed genes were shared among the three intensities, and each scan intensity identified unique sets of differentially expressed genes. The set of differentially expressed genes from any one scan amounted to < 70% of the total number of genes identified in at least one scan. The average signal intensity of genes that exhibited statistically significant changes in expression was highest for the low-intensity scan and lowest for the high-intensity scan, suggesting that low-intensity scans may be best for detecting expression differences in high-signal genes, while high-intensity scans may be best for detecting expression differences in low-signal genes. Comparison of the differentially expressed genes identified in the multiple scan and linear regression approaches revealed that the multiple scan approach effectively identifies a subset of statistically significant genes that linear regression approach is unable to identify. Quantitative RT-PCR (qRT-PCR) tests demonstrated that statistically significant differences identified at all three scan intensities can be verified.

AVAILABILITY

The data presented can be viewed at http://www.ncbi.nlm.nih.gov/geo/ under GEO accession no. GSE3017.

Options available for profiling small samples: a review of sample amplification technology when combined with microarray profiling

The possibility of performing microarray analysis on limited material has been demonstrated in a number of publications. In this review we approach the technical aspects of mRNA amplification and several important implicit consequences, for both linear and exponential procedures. Amplification efficiencies clearly allow profiling of extremely small samples. The conservation of transcript abundance is the most important issue regarding the use of sample amplification in combination with microarray analysis, and this aspect has generally been found to be acceptable, although demonstrated to decrease in highly diluted samples. The fact that variability and discrepancies in microarray profiles increase with minute sample sizes has been clearly documented, but for many studies this does appear to have affected the biological conclusions. We suggest that this is due to the data analysis approach applied, and the consequence is the chance of presenting misleading results. We discuss the issue of amplification sensitivity limits in the light of reports on fidelity, published data from reviewed articles and data analysis approaches. These are important considerations to be reflected in the design of future studies and when evaluating biological conclusions from published microarray studies based on extremely low input RNA quantities.

PCR inhibition by reverse transcriptase leads to an overestimation of amplification efficiency

This study addresses the problem of PCR inhibition by reverse transcriptase. It has been shown that the inhibition occurs mostly when a small amount of RNA is taken for RT reaction, and it is more visible for rarely expressed transcripts. We show here that the inhibition takes place regardless of what amount of template is utilized for RT. The inhibition possesses a global nature, i.e. the amplification of any given transcript may be compromised with different levels of inhibition. The process of inhibition also explains wrongfully derived PCR amplification efficiencies, sometimes more than 100%, when the sequential dilutions of unpurified RT sample are utilized to build the calibration curve. The RT influences PCR not only by inhibiting it. When microgram(s) of RNA are taken for RT reaction, reverse transcriptase may cause overamplification of some transcripts under certain PCR conditions. The possible mechanism of RT influence on PCR is presented, and a purification method is implemented to remove the effects of RT on PCR.

Utility of lab-on-a-chip technology for high-throughput nucleic acid and protein analysis

On-chip electrophoresis can provide size separations of nucleic acids and proteins similar to more traditional slab gel electrophoresis. Lab-on-a-chip (LoaC) systems utilize on-chip electrophoresis in conjunction with sizing calibration, sensitive detection schemes, and sophisticated data analysis to achieve rapid analysis times (<120 s). This work describes the utility of LoaC systems to enable and augment systems biology investigations. RNA quality, as assessed by an RNA integrity number score, is compared to existing quality control (QC) measurements. High-throughput DNA analysis of multiplex PCR samples is used to stratify gene sets for disease discovery. Finally, the applicability of a high-throughput LoaC system for assessing protein purification is demonstrated. The improvements in workflow processes, speed of analysis, data accuracy and reproducibility, and automated data analysis are illustrated.

Limitations of mRNA amplification from small-size cell samples

Background

Global mRNA amplification has become a widely used approach to obtain gene expression profiles from limited material. An important concern is the reliable reflection of the starting material in the results obtained. This is especially important with extremely low quantities of input RNA where stochastic effects due to template dilution may be present. This aspect remains under-documented in the literature, as quantitative measures of data reliability are most often lacking. To address this issue, we examined the sensitivity levels of each transcript in 3 different cell sample sizes. ANOVA analysis was used to estimate the overall effects of reduced input RNA in our experimental design. In order to estimate the validity of decreasing sample sizes, we examined the sensitivity levels of each transcript by applying a novel model-based method, TransCount.

Results

From expression data, TransCount provided estimates of absolute transcript concentrations in each examined sample. The results from TransCount were used to calculate the Pearson correlation coefficient between transcript concentrations for different sample sizes. The correlations were clearly transcript copy number dependent. A critical level was observed where stochastic fluctuations became significant. The analysis allowed us to pinpoint the gene specific number of transcript templates that defined the limit of reliability with respect to number of cells from that particular source. In the sample amplifying from 1000 cells, transcripts expressed with at least 121 transcripts/cell were statistically reliable and for 250 cells, the limit was 1806 transcripts/cell. Above these thresholds, correlation between our data sets was at acceptable values for reliable interpretation.

Conclusion

These results imply that the reliability of any amplification experiment must be validated empirically to justify that any gene exists in sufficient quantity in the input material. This finding has important implications for any experiment where only extremely small samples such as single cell analyses or laser captured microdissected cells are available.

Transit tumor retrieval preserves RNA fidelity and obviates snap-freezing

Genetic expression profiling is enabling investigators to discover new diagnostic and possibly therapeutic pathways in sarcoma biology. To draw substantial conclusions from these molecular analyses, adequate tissue samples must be accrued. Beyond cohort size, the most variable and limiting aspect of doing gene expression analyses on fresh human tissue is the preservation of labile ribonucleic acids extracted from clinical specimens. We have developed a novel retrieval protocol that is readily amenable to the clinical constraints placed on surgeons and pathologists that minimizes variables that can corrupt ribonucleic acid fidelity. We evaluate critically genomic message integrity of mesenchymal tumors derived from transcontinental inter-institutional collaboration. Intact total ribonucleic acid was isolated and assessed for quality and quantity. Ribosomal RNA integrity was quantified using a bioanalyzer. Ribonucleic acid from 42 mesenchymal tumors was isolated and quantified, with selected samples amplified. The mean ribosomal ratios for collaborative institutions ranged from 1.0 to 1.18. Samples remained at 4 degrees C before processing from 1 to 17 days. Tumors stabilized using this protocol retained total ribonucleic acid integrity suitable for amplification and genomic expression analysis regardless of the institutional source or preprocessing duration, enabling a potential consortium of investigators to collaborate in the expression profiling of sarcomas.

LEVEL OF EVIDENCE

Diagnostic study, Level III-3 (no consistently applied gold standard). See the Guidelines for Authors for a complete description of levels of evidence.

A 1 Mb minimal amplicon at 8p11-12 in breast cancer identifies new candidate oncogenes

Amplification of 8p11-12 is a well-known alteration in human breast cancers but the driving oncogene has not been identified. We have developed a high-resolution comparative genomic hybridization array covering 8p11-12 and analysed 33 primary breast tumors, 20 primary ovarian tumors and 27 breast cancer cell lines. Expression analysis of the genes in the region was carried out by using real-time quantitative PCR and/or oligo-microarray profiling. In all, 24% (8/33) of the breast tumors, 5% (1/20) of the ovary tumors and 15% (4/27) of the cell lines showed 8p11-12 amplification. We identified a 1 Mb segment of common amplification that excludes previously proposed candidate genes. Some of the amplified genes did not show overexpression, whereas for others, overexpression was not specifically attributable to amplification. The genes FLJ14299, C8orf2, BRF2 and RAB11FIP, map within the 8p11-12 minimal amplicon, two have a putative function consistent with an oncogenic role, these four genes showed a strong correlation between amplification and overexpression and are therefore the best candidate driver oncogenes at 8p12.

Defining best practice for microarray analyses in nutrigenomic studies

Microarrays represent a powerful tool for studies of diet-gene interactions. Their use is, however, associated with a number of technical challenges and potential pitfalls. The cost of microarrays continues to drop but is still comparatively high. This, coupled with the complex logistical issues associated with performing nutritional microarray studies, often means that compromises have to be made in the number and type of samples analysed. Additionally, technical variations between array platforms and analytical procedures will almost inevitably lead to differences in the transcriptional responses observed. Consequently, conflicting data may be produced, important effects may be missed and/or false leads generated (e.g. apparent patterns of differential gene regulation that ultimately prove to be incorrect or not significant). This is likely to be particularly true in the field of nutrition, in which we expect that many dietary bioactive agents at nutritionally relevant concentrations will elicit subtle changes in gene transcription that may be critically important in biological terms but will be difficult to detect reliably. Thus, great care should always be taken in designing and executing microarray studies. This article seeks to provide an overview of both the main practical and theoretical considerations in microarray use that represent potential sources of technical variation and error. Wherever possible, recommendations are made on what we propose to be the best approach. The overall aims are to provide a basic framework of advice for researchers who are new to the use of microarrays and to promote a discussion of standardisation and best practice in the field.

Be more specific! Laser-assisted microdissection of plant cells

Laser-assisted microdissection (LAM) is a powerful tool for isolating specific tissues, cell types and even organelles from sectioned biological specimen in a manner conducive to the extraction of RNA, DNA or protein. LAM, which is an established technique in many areas of biology, has now been successfully adapted for use with plant tissues. Here, we provide an overview of the processes involved in conducting a successful LAM study in plants and review recent developments that have made this technique even more desirable. We also discuss how the technology might be exploited to answer some pertinent questions in plant biology.

Genetic dissection of gene expression observed in whole blood samples of elderly Danish twins

The microarray technique is an important tool in gene expression analysis to study the activities of thousands of genes measured by their transcript levels under disease or laboratory controlled experimental conditions. Recent studies have suggested a genetic component in the variations of gene expression thus indicating the important role of genetic control over gene activities. In this study, we analyze and report the twin correlation on gene expression in whole blood samples of six female Danish twin pairs aged from 81 to 85 years. We studied the expression phenotype by treating the measured gene expression as a quantitative trait and introducing analytical approaches including the traditional twin methods in population genetics and the multivariate statistical methods. Using this combinatory approach, we were able to estimate and compare the twin correlation on the expression phenotype while accounting for systematic influence in microarray experiments. Analyses on our twin data detected a significant correlation on the expression levels of the actively regulated genes in both monozygotic and dizygotic twins, which is more pronounced in monozygotic twins. Gene ontology analysis has shown that these actively regulated genes are predominantly involved in defense and immune responses against antigenic stimulus. In conclusion, the correlation patterns revealed in our twin data provide evidence of the existence of a heritable mechanism in gene expression regulation persistently functioning even in aged subjects.

Microarrays and breast cancer clinical studies: forgetting what we have not yet learnt

This review takes a sceptical view of the impact of breast cancer studies that have used microarrays to identify predictors of clinical outcome. In addition to discussing general pitfalls of microarray experiments, we also critically review the key breast cancer studies to highlight methodological problems in cohort selection, statistical analysis, validation of results and reporting of raw data. We conclude that the optimum use of microarrays in clinical studies requires further optimisation and standardisation of methodology and reporting, together with improvements in clinical study design.