Gene expression profiling of single cells on large-scale oligonucleotide arrays

Simultaneous Isolation and Amplification of mRNA and Genomic DNA of a Single Cell

Many biological or pathological processes are driven by cells difficult to identify or isolate, i.e., rare cells. Very often, these cells have elusive biology. Therefore, their detailed characterization is of utmost importance. There are many approaches that allow analysis of few or even many targets within one class of biomacromolecules/analytes (e.g., DNA, RNA, proteins, etc.) in single cells. However, due to rarity of the cells of interest, there is a great need to comprehensively analyze multiple analytes within these cells, in other words to perform multi-omics analysis. In this chapter, I describe a method to isolate, separate, and amplify total mRNA and genomic DNA of a single cells, using whole transcriptome (WTA) and whole genome amplification (WGA). These WTA and WGA products enable simultaneous analysis of transcriptome and genome of a single cell using various downstream high-throughput approaches.

Ex vivo expansion of lung cancer-derived disseminated cancer cells from lymph nodes identifies cells associated with metastatic progression

The cellular basis of the apparent aggressiveness in lung cancer is poorly understood but likely associated with functional or molecular features of disseminated cancer cells (DCCs). DCCs from epithelial cancers are mostly detected by antibodies directed against histogenetic markers such as cytokeratin or EpCAM. It has been argued that marker-negative metastatic founder cells might escape detection. We therefore used ex vivo sphere formation for functional detection of candidate metastasis founders. We generated cell suspensions from 199 LN samples of 131 lung cancer patients and placed them into non-adherent cell culture. Sphere formation was associated with detection of DCCs using EpCAM immunocytology and with significantly poorer prognosis. The prognostic impact of sphere formation was strongly associated with high numbers of EpCAM-positive DCCs and aberrant genotypes of expanded spheres. We also noted sphere formation in patients with no evidence of lymphatic spread, however such spheres showed infrequent expression of signature genes associated with spheres from EpCAM-positive samples and displayed neither typical lung cancer mutations (KRAS, TP53, ERBB1) nor copy number variations, but might be linked to disease progression >5 years post curative surgery. We conclude that EpCAM identifies relevant disease-driving DCCs, that such cells can be expanded for model generation and that further research is needed to clarify the functional and prognostic role of rare EpCAM-negative sphere forming cells.

Interleukin-6 trans-signaling is a candidate mechanism to drive progression of human DCCs during clinical latency

Although thousands of breast cancer cells disseminate and home to bone marrow until primary surgery, usually less than a handful will succeed in establishing manifest metastases months to years later. To identify signals that support survival or outgrowth in patients, we profile rare bone marrow-derived disseminated cancer cells (DCCs) long before manifestation of metastasis and identify IL6/PI3K-signaling as candidate pathway for DCC activation. Surprisingly, and similar to mammary epithelial cells, DCCs lack membranous IL6 receptor expression and mechanistic dissection reveals IL6 trans-signaling to regulate a stem-like state of mammary epithelial cells via gp130. Responsiveness to IL6 trans-signals is found to be niche-dependent as bone marrow stromal and endosteal cells down-regulate gp130 in premalignant mammary epithelial cells as opposed to vascular niche cells. PIK3CA activation renders cells independent from IL6 trans-signaling. Consistent with a bottleneck function of microenvironmental DCC control, we find PIK3CA mutations highly associated with late-stage metastatic cells while being extremely rare in early DCCs. Our data suggest that the initial steps of metastasis formation are often not cancer cell-autonomous, but also depend on microenvironmental signals.

Metastatic dissemination in breast cancer patients occurs early in malignant transformation, raising questions about how disseminated cancer cells (DCC) progress at distant sites. Here, the authors show that DCCs in bone marrow are activated via IL6-trans-signaling and thereby acquire stemness traits relevant for metastasis formation.

Tumor Cell Invasion in Glioblastoma

Glioblastoma (GBM) is a particularly devastating tumor with a median survival of about 16 months. Recent research has revealed novel insights into the outstanding heterogeneity of this type of brain cancer. However, all GBM subtypes share the hallmark feature of aggressive invasion into the surrounding tissue. Invasive glioblastoma cells escape surgery and focal therapies and thus represent a major obstacle for curative therapy. This review aims to provide a comprehensive understanding of glioma invasion mechanisms with respect to tumor-cell-intrinsic properties as well as cues provided by the microenvironment. We discuss genetic programs that may influence the dissemination and plasticity of GBM cells as well as their different invasion patterns. We also review how tumor cells shape their microenvironment and how, vice versa, components of the extracellular matrix and factors from non-neoplastic cells influence tumor cell motility. We further discuss different research platforms for modeling invasion. Finally, we highlight the importance of accounting for the complex interplay between tumor cell invasion and treatment resistance in glioblastoma when considering new therapeutic approaches.

Targeted transcript quantification in single disseminated cancer cells after whole transcriptome amplification

Gene expression analysis of rare or heterogeneous cell populations such as disseminated cancer cells (DCCs) requires a sensitive method allowing reliable analysis of single cells. Therefore, we developed and explored the feasibility of a quantitative PCR (qPCR) assay to analyze single-cell cDNA pre-amplified using a previously established whole transcriptome amplification (WTA) protocol. We carefully selected and optimized multiple steps of the protocol, e.g. re-amplification of WTA products, quantification of amplified cDNA yields and final qPCR quantification, to identify the most reliable and accurate workflow for quantitation of gene expression of the ERBB2 gene in DCCs. We found that absolute quantification outperforms relative quantification. We then validated the performance of our method on single cells of established breast cancer cell lines displaying distinct levels of HER2 protein. The different protein levels were faithfully reflected by transcript expression across the tested cell lines thereby proving the accuracy of our approach. Finally, we applied our method to breast cancer DCCs of a patient undergoing anti-HER2-directed therapy. Here, we were able to measure ERBB2 expression levels in all HER2-protein-positive DCCs. In summary, we developed a reliable single-cell qPCR assay applicable to measure distinct levels of ERBB2 in DCCs.

Global and targeted approaches to single-cell transcriptome characterization

Analysing transcriptomes of cell populations is a standard molecular biology approach to understand how cells function. Recent methodological development has allowed performing similar experiments on single cells. This has opened up the possibility to examine samples with limited cell number, such as cells of the early embryo, and to obtain an understanding of heterogeneity within populations such as blood cell types or neurons. There are two major approaches for single-cell transcriptome analysis: quantitative reverse transcription PCR (RT-qPCR) on a limited number of genes of interest, or more global approaches targeting entire transcriptomes using RNA sequencing. RT-qPCR is sensitive, fast and arguably more straightforward, while whole-transcriptome approaches offer an unbiased perspective on a cell's expression status.

W. A. H, Lewis RJ, Vetter I. Transcriptomics in pain research: insights from new and old technologies

Physiological and pathological pain involves a complex interplay of multiple cell types and signaling pathways.

Mice produced by mitotic reprogramming of sperm injected into haploid parthenogenotes

Sperm are highly differentiated and the activities that reprogram them for embryonic development during fertilization have historically been considered unique to the oocyte. We here challenge this view and demonstrate that mouse embryos in the mitotic cell cycle can also directly reprogram sperm for full-term development. Developmentally incompetent haploid embryos (parthenogenotes) injected with sperm developed to produce healthy offspring at up to 24% of control rates, depending when in the embryonic cell cycle injection took place. This implies that most of the first embryonic cell cycle can be bypassed in sperm genome reprogramming for full development. Remodelling of histones and genomic 5′-methylcytosine and 5′-hydroxymethylcytosine following embryo injection were distinct from remodelling in fertilization and the resulting 2-cell embryos consistently possessed abnormal transcriptomes. These studies demonstrate plasticity in the reprogramming of terminally differentiated sperm nuclei and suggest that different epigenetic pathways or kinetics can establish totipotency.

It is unclear what regulates gamete reprogramming competence. Here, the authors inject sperm into parthenogenetic embryos, generating viable offspring and show that mouse embryos in the mitotic cell cycle can reprogram sperm for full term development.

Factors affecting the gene expression of in vitro cultured human preimplantation embryos

STUDY QUESTION

What is the relative effect of common environmental and biological factors on transcriptome changes during human preimplantation development?

SUMMARY ANSWER

Developmental stage and maternal age had a larger effect on the global gene expression profile of human preimplantation embryos than the culture medium or oxygen concentration used in in vitro culture.

WHAT IS KNOWN ALREADY

Studies on mouse and bovine embryos have shown that different conditions in the in vitro culture of embryos can lead to changes in transcriptome profiles. For humans, an effect of developmental stage on the transcriptome profile of embryos has been demonstrated, but studies on the effect of maternal age or culture conditions are lacking.

STUDY DESIGN, SIZE, DURATION

Donated, good quality, day 4 cryopreserved human preimplantation embryos (N = 89) were randomized to be cultured in one of two culture media (G5 medium or HTF medium) and one of two oxygen concentrations (5% or 20%), with stratification for maternal age. Next to these variables, developmental stage after culture was taken into account in the analysis.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Embryos that developed to morula or blastocyst stage during these 2 days whose amplified mRNA passed our quality control criteria for microarray hybridization were individually examined for genome-wide gene expression (N = 37).

MAIN RESULTS AND THE ROLE OF CHANCE

Based on the number of differentially expressed genes (DEGs), developmental stage (3519 DEGs) and maternal age (1258 DEGs) had a larger effect on the global gene expression profile of human preimplantation embryos than either tested culture medium (596 DEGs) or oxygen concentration (492 DEGs) used during in vitro culture. Interactions between the factors were found, indicating that culture conditions might have a different effect depending on the developmental stage or the maternal age of the embryos. Affected pathways included metabolism, cell cycle processes and oxidative phosphorylation.

LIMITATIONS, REASONS FOR CAUTION

Culture of embryos for only 2 days might have limited the effect on global gene expression by the investigated culture conditions. Earlier stages of development (Day 0 until Day 4) were not analyzed and these embryos might respond differently to the experimental conditions. The freezing and thawing procedures might have had an effect on gene expression. RT-PCR validation was not performed due to scarcity of the material.

WIDER IMPLICATIONS OF THE FINDINGS

Our results show that when studying gene expression in single human preimplantation embryos under various experimental conditions, one should take into account the confounding effect of biological variables, such as developmental stage and maternal age. This makes these experiments different from gene expression experiments where these variables can be tightly controlled, for example when using cell lines.

STUDY FUNDING/COMPETING INTERESTS

This study received no external funding and there were no competing interests.

Single-cell transcriptogenomics reveals transcriptional exclusion of ENU-mutated alleles

Recently, great progress has been made in single cell genomics and transcriptomics. Here, we present an integrative method, termed single-cell transcriptogenomics (SCTG), in which whole exome sequencing and RNA-seq is performed concurrently on single cells. This methodology enables one to track germline and somatic variants directly from the genome to the transcriptome in individual cells. Mouse embryonic fibroblasts were treated with the powerful mutagen ethylnitrosourea (ENU) and subjected to SCTG. Interestingly, while germline variants were found to be transcribed in an allelically balanced fashion, a significantly different pattern of allelic exclusion was observed for ENU-mutant variants. These results suggest that the adverse effects of induced mutations, in contrast to germline variants, may be mitigated by allelically biased transcription. They also illustrate how SCTG can be instrumental in the direct assessment of phenotypic consequences of genomic variants.

Evaluation and validation of a robust single cell RNA-amplification protocol through transcriptional profiling of enriched lung cancer initiating cells

BACKGROUND

Although profiling of RNA in single cells has broadened our understanding of development, cancer biology and mechanisms of disease dissemination, it requires the development of reliable and flexible methods. Here we demonstrate that the EpiStem RNA-Amp™ methodology reproducibly generates microgram amounts of cDNA suitable for RNA-Seq, RT-qPCR arrays and Microarray analysis.

RESULTS

Initial experiments compared amplified cDNA generated by three commercial RNA-Amplification protocols (Miltenyi μMACS™ SuperAmp™, NuGEN Ovation® One-Direct System and EpiStem RNA-Amp™) applied to single cell equivalent levels of RNA (25-50 pg) using Affymetrix arrays. The EpiStem RNA-Amp™ kit exhibited the highest sensitivity and was therefore chosen for further testing. A comparison of Affymetrix array data from RNA-Amp™ cDNA generated from single MCF7 and MCF10A cells to reference controls of unamplified cDNA revealed a high degree of concordance. To assess the flexibility of the amplification system single cell RNA-Amp™ cDNA was also analysed using RNA-Seq and high-density qPCR, and showed strong cross-platform correlations. To exemplify the approach we used the system to analyse RNA profiles of small populations of rare cancer initiating cells (CICs) derived from a NSCLC patient-derived xenograft. RNA-Seq analysis was able to identify transcriptional differences in distinct subsets of CIC, with one group potentially enriched for metastasis formation. Pathway analysis revealed that the distinct transcriptional signatures demonstrated in the CIC subpopulations were significantly correlated with published stem-cell and epithelial-mesenchymal transition signatures.

CONCLUSIONS

The combined results confirm the sensitivity and flexibility of the RNA-Amp™ method and demonstrate the suitability of the approach for identifying clinically relevant signatures in rare, biologically important cell populations.

Combined genome and transcriptome analysis of single disseminated cancer cells from bone marrow of prostate cancer patients reveals unexpected transcriptomes

Bone is the most frequent site of metastasis in prostate cancer and patients with bone metastases are deemed incurable. Targeting prostate cancer cells that disseminated to the bone marrow before surgery and before metastatic outgrowth may therefore prevent lethal metastasis. This prompted us to directly analyze the transcriptome of disseminated cancer cells (DCC) isolated from patients with nonmetastatic (UICC stage M0) prostate cancer. We screened 105 bone marrow samples of patients with M0-stage prostate cancer and 18 bone marrow samples of patients without malignancy for the presence of EpCAM(+) single cells. In total, we isolated 270 cells from both groups by micromanipulation and globally amplified their mRNA. We used targeted transcriptional profiling to unambiguously identify DCCs for subsequent in-depth analysis. Transcriptomes of all cells were examined for the expression of EPCAM, KRT8, KRT18, KRT19, KRT14, KRT6a, KRT5, KLK3 (PSA), MAGEA2, MAGEA4, PTPRC (CD45), CD33, CD34, CD19, GYPC, SCL4A1 (band 3), and HBA2. Using these transcripts, we found it impossible to reliably identify true DCCs. We then applied combined genome and transcriptome analysis of single cells and found that EpCAM(+) cells from controls expressed transcripts thought to be epithelial-specific, whereas true DCCs may express hematopoietic transcripts. These results point to an unexpected transcriptome plasticity of epithelial cancer cells in bone marrow and question common transcriptional criteria to identify DCCs.

Single-cell RNA-seq: advances and future challenges

Phenotypically identical cells can dramatically vary with respect to behavior during their lifespan and this variation is reflected in their molecular composition such as the transcriptomic landscape. Single-cell transcriptomics using next-generation transcript sequencing (RNA-seq) is now emerging as a powerful tool to profile cell-to-cell variability on a genomic scale. Its application has already greatly impacted our conceptual understanding of diverse biological processes with broad implications for both basic and clinical research. Different single-cell RNA-seq protocols have been introduced and are reviewed here—each one with its own strengths and current limitations. We further provide an overview of the biological questions single-cell RNA-seq has been used to address, the major findings obtained from such studies, and current challenges and expected future developments in this booming field.

Single cell analysis of cancer genomes

Genomic studies have provided key insights into how cancers develop, evolve, metastasize and respond to treatment. Cancers result from an interplay between mutation, selection and clonal expansions. In solid tumours, this Darwinian competition between subclones is also influenced by topological factors. Recent advances have made it possible to study cancers at the single cell level. These methods represent important tools to dissect cancer evolution and provide the potential to considerably change both cancer research and clinical practice. Here we discuss state-of-the-art methods for the isolation of a single cell, whole-genome and whole-transcriptome amplification of the cell's nucleic acids, as well as microarray and massively parallel sequencing analysis of such amplification products. We discuss the strengths and the limitations of the techniques, and explore single-cell methodologies for future cancer research, as well as diagnosis and treatment of the disease.

Molecular profiling of single Sca-1+/CD34+,- cells--the putative murine lung stem cells

Murine bronchioalveolar stem cells play a key role in pulmonary epithelial maintenance and repair but their molecular profile is poorly described so far. In this study, we used antibodies directed against Sca-1 and CD34, two markers originally ascribed to pulmonary cells harboring regenerative potential, to isolate single putative stem cells from murine lung tissue. The mean detection rate of positive cells was 8 per 10⁶ lung cells. We then isolated and globally amplified the mRNA of positive cells to analyze gene expression in single cells. The resulting amplicons were then used for molecular profiling by transcript specific polymerase chain reaction (PCR) and global gene expression analysis using microarrays. Single marker-positive cells displayed a striking heterogeneity for the expression of epithelial and mesenchymal transcripts on the single cell level. Nevertheless, they could be subdivided into two cell populations: Sca-1⁺/CD34⁻ and Sca-1⁺/CD34⁺ cells. In these subpopulations, transcripts of the epithelial marker Epcam (CD326) were exclusively detected in Sca-1⁺/CD34⁻ cells (p = 0.03), whereas mRNA of the mesenchymal marker Pdgfrα (CD140a) was detected in both subpopulations and more frequently in Sca-1⁺/CD34⁺ cells (p = 0.04). FACS analysis confirmed the existence of a Pdgfrα positive subpopulation within Epcam⁺/Sca-1⁺/CD34⁻ epithelial cells. Gene expression analysis by microarray hybridization identified transcripts differentially expressed between the two cell types as well as between epithelial reference cells and Sca-1⁺/CD34⁺ single cells, and selected transcripts were validated by quantitative PCR. Our results suggest a more mesenchymal commitment of Sca-1⁺/CD34⁺ cells and a more epithelial commitment of Sca-1⁺/CD34⁻ cells. In summary, the study shows that single cell analysis enables the identification of novel molecular markers in yet poorly characterized populations of rare cells. Our results could further improve our understanding of Sca-1⁺/CD34^+,− cells in the biology of the murine lung.

High-Throughput Single-Cell Analysis for Wound Healing Applications

SIGNIFICANCE

Wound repair is a complex biological process that integrates multiple physiologic pathways to restore skin homeostasis after a wide array of gross and anatomical insults. As such, a scientific examination of the wound typically requires broad sampling of numerous factors and is commonly achieved through DNA microarray analysis.

CRITICAL ISSUES

In the last several years, it has become increasingly evident that the granularity afforded by such traditional population-based assays may be insufficient to capture the complex relationships in heterogeneous processes such as those associated with wound healing and stem cell biology.

RECENT ADVANCES

Several emerging technologies have recently become available that permit high-throughput single-cell gene expression analysis in a manner which provides novel insights into the relationships of complex tissue. The most prominent among these employs microfluidic-based devices to achieve a high-resolution analysis of tissue samples.

FUTURE DIRECTIONS

The intrinsically heterogeneous nature of injured tissue, in conjunction with its temporal dynamics, makes wound repair and tissue regeneration an attractive target for high-throughput single-cell analysis. Given the staggering costs associated with chronic and non-healing wounds, the development of predictive and diagnostic tools using this technology would likely be attractive to healthcare providers.

Single circulating tumor cell profiling: a new perspective for targeted therapy?

Evaluation of: Powell AA, Talasaz AH, Zhang H et al. Single cell profiling of circulating tumor cells: transcriptional heterogeneity and diversity from breast cancer cell lines. PLoS ONE 7(5), e33788 (2012). Circulating tumor cells (CTCs) may represent a possible useful tool to better define the prognosis of patients. The presence of CTCs can help to predict an increased risk for disease relapse, and they might be an early marker for treatment efficacy that could help in deciding treatment continuation. Cancer metastasis occurs when cells, shed from the primary tumor, enter the circulation and begin to grow in distant locations around the body. In metastatic stages, shed cells may differ from those of the primary tumor, as the tumor phenotype can change during the course of the disease. It is important to identify relevant targets expressed on these cells to provide clinical information on therapy choice, efficacy and drug resistance. Many efforts are now devoted to the characterization of the single cell. This article focuses on the possibility of profiling single CTCs in patients with breast cancer.

Single cell transcriptomic analysis of prostate cancer cells

Background

The ability to interrogate circulating tumor cells (CTC) and disseminated tumor cells (DTC) is restricted by the small number detected and isolated (typically <10). To determine if a commercially available technology could provide a transcriptomic profile of a single prostate cancer (PCa) cell, we clonally selected and cultured a single passage of cell cycle synchronized C4-2B PCa cells. Ten sets of single, 5-, or 10-cells were isolated using a micromanipulator under direct visualization with an inverted microscope. Additionally, two groups of 10 individual DTC, each isolated from bone marrow of 2 patients with metastatic PCa were obtained. RNA was amplified using the WT-Ovation™ One-Direct Amplification System. The amplified material was hybridized on a 44K Whole Human Gene Expression Microarray. A high stringency threshold, a mean Alexa Fluor® 3 signal intensity above 300, was used for gene detection. Relative expression levels were validated for select genes using real-time PCR (RT-qPCR).

Results

Using this approach, 22,410, 20,423, and 17,009 probes were positive on the arrays from 10-cell pools, 5-cell pools, and single-cells, respectively. The sensitivity and specificity of gene detection on the single-cell analyses were 0.739 and 0.972 respectively when compared to 10-cell pools, and 0.814 and 0.979 respectively when compared to 5-cell pools, demonstrating a low false positive rate. Among 10,000 randomly selected pairs of genes, the Pearson correlation coefficient was 0.875 between the single-cell and 5-cell pools and 0.783 between the single-cell and 10-cell pools. As expected, abundant transcripts in the 5- and 10-cell samples were detected by RT-qPCR in the single-cell isolates, while lower abundance messages were not. Using the same stringency, 16,039 probes were positive on the patient single-cell arrays. Cluster analysis showed that all 10 DTC grouped together within each patient.

Conclusions

A transcriptomic profile can be reliably obtained from a single cell using commercially available technology. As expected, fewer amplified genes are detected from a single-cell sample than from pooled-cell samples, however this method can be used to reliably obtain a transcriptomic profile from DTC isolated from the bone marrow of patients with PCa.

Stochastic profiling of transcriptional regulatory heterogeneities in tissues, tumors and cultured cells

Single-cell variations in gene and protein expression are important during development and disease. Such cell-to-cell heterogeneities can be directly inspected one cell at a time, but global methods are usually not sensitive enough to work with the starting material of a single cell. Here we provide a detailed protocol for stochastic profiling, a method that infers single-cell regulatory heterogeneities by repeatedly sampling small collections of cells selected at random. Repeated stochastic sampling is performed by laser-capture microdissection or limiting dilution, followed by careful exponential cDNA amplification, hybridization to microarrays and statistical analysis. Stochastic profiling surveys the transcriptome for programs that are heterogeneously regulated among cellular subpopulations in their native tissue context. The protocol is readily optimized for specific biological applications and takes about 1 week to complete.

Highly parallel genome-wide expression analysis of single mammalian cells

BACKGROUND

We have developed a high-throughput amplification method for generating robust gene expression profiles using single cell or low RNA inputs.

METHODOLOGY/PRINCIPAL FINDINGS

The method uses tagged priming and template-switching, resulting in the incorporation of universal PCR priming sites at both ends of the synthesized cDNA for global PCR amplification. Coupled with a whole-genome gene expression microarray platform, we routinely obtain expression correlation values of R(2)~0.76-0.80 between individual cells and R(2)~0.69 between 50 pg total RNA replicates. Expression profiles generated from single cells or 50 pg total RNA correlate well with that generated with higher input (1 ng total RNA) (R(2)~0.80). Also, the assay is sufficiently sensitive to detect, in a single cell, approximately 63% of the number of genes detected with 1 ng input, with approximately 97% of the genes detected in the single-cell input also detected in the higher input.

CONCLUSIONS/SIGNIFICANCE

In summary, our method facilitates whole-genome gene expression profiling in contexts where starting material is extremely limiting, particularly in areas such as the study of progenitor cells in early development and tumor stem cell biology.

Single-cell and regional gene expression analysis in Alzheimer's disease

The clinical manifestations of Alzheimer's disease (AD) are secondary to the substantial loss of cortical neurons. To be effective, neuroprotective strategies will need to target the primary pathogenic mechanisms of AD prior to cell loss. The differences between neurons are largely determined by their specific repertoire of mRNAs. Thus, transcriptomic analyses that do not assume a priori etiological hypotheses are potentially powerful tools that can be used to understand the pathogenesis of complex diseases, including AD. The human brain comprises thousands of different cell types of both neuronal and non-neuronal origins. Information about individual cell-type-specific gene expression patterns will allow for a better understanding of the mechanisms that govern the progression of AD, which may lead to new therapeutic targets for prevention and treatment of the disease. This review provides an overview of the current technologies in use and the developments for single-cell extraction and transcriptome analysis. Recent transcriptome profiling studies on individual AD-afflicted brain cells are also discussed.

Multiplex molecular analysis of CTCs

Beyond enumeration, CTC characterization is expected to help guide therapeutic selection for personalized care of cancer patients. Different approaches may be used to simultaneously identify multiple CTC-specific markers for biological characterization; yet awareness of associated pitfalls is also important. We have focused this chapter on molecular profiling of CTCs following enrichment. We describe the MagSweeper technology that was specifically developed to isolate live and highly purified CTCs for pooled or single cell or pooled cell molecular analyses or for CTC growth in vitro or in vivo. However, most of what is discussed will apply to any multiplex analysis of CTCs, irrespective of the enrichment method.

Emerging applications of single-cell diagnostics

The performance of DNA sequencers (next generation sequencing) is rapidly enhanced these days, being used for genetic diagnostics. Although many phenomena could be elucidated with such massive genome data, it is still a big challenge to obtain comprehensive understanding of diseases and the relevant biology at the cellular level. In general terms, the data obtained to date are averages of ensembles of cells, but it is not certain whether the same features are the same inside an individual cell. Accordingly, important information may be masked by the averaging process. As the technologies for analyzing bio-molecular components in single cells are being developed, single cell analysis seems promising to address the current limitations due to averaging problems. Although the technologies for single cell analysis are still at the infant stage, the single cell approach has the potential to improve the accuracy of diagnosis based on knowledge of intra- and inter-cellular networks. In this review several technologies and applications (especially medical applications) of genome and transcriptome analysis or single cells are described.

Gene expression profile of circulating tumor cells in breast cancer by RT-qPCR

Background

Circulating tumor cells (CTCs) have been associated with prognosis especially in breast cancer and have been proposed as a liquid biopsy for repeated follow up examinations. Molecular characterization of CTCs is difficult to address since they are very rare and the amount of available sample is very limited.

Methods

We quantified by RT-qPCR CK-19, MAGE-A3, HER-2, TWIST1, hTERT α+β+, and mammaglobin gene transcripts in immunomagnetically positively selected CTCs from 92 breast cancer patients, and 28 healthy individuals. We also compared our results with the CellSearch system in 33 of these patients with early breast cancer.

Results

RT-qPCR is highly sensitive and specific and can detect the expression of each individual gene at the one cell level. None of the genes tested was detected in the group of healthy donors. In 66 operable breast cancer patients, CK-19 was detected in 42.4%, HER-2 in 13.6%, MAGE-A3 in 21.2%, hMAM in 13.6%, TWIST-1 in 42.4%, and hTERT α+β+ in 10.2%. In 26 patients with verified metastasis, CK-19 was detected in 53.8%, HER-2 in 19.2%, MAGE-A3 in 15.4%, hMAM in 30.8%, TWIST-1 in 38.5% and hTERT α⁺β⁺in 19.2%. Our preliminary data on the comparison between RT-qPCR and CellSearch in 33 early breast cancer patients showed that RT-qPCR gives more positive results in respect to CellSearch.

Conclusions

Molecular characterization of CTCs has revealed a remarkable heterogeneity of gene expression between breast cancer patients. In a small percentage of patients, CTCs were positive for all six genes tested, while in some patients only one of these genes was expressed. The clinical significance of these findings in early breast cancer remains to be elucidated when the clinical outcome for these patients is known.

Stromal upregulation of lateral epithelial adhesions: gene expression analysis of signalling pathways in prostate epithelium

Background

Stromal signalling increases the lateral cell adhesions of prostate epithelial cells grown in 3D culture. The aim of this study was to use microarray analysis to identify significant epithelial signalling pathways and genes in this process.

Methods

Microarray analysis was used to identify genes that were differentially expressed when epithelial cells were grown in 3D Matrigel culture with stromal co-culture compared to without stroma. Two culture models were employed: primary epithelial cells (ten samples) and an epithelial cell line (three experiments). A separate microarray analysis was performed on each model system and then compared to identify tissue-relevant genes in a cell line model.

Results

TGF beta signalling was significantly ranked for both model systems and in both models the TGF beta signalling gene SOX4 was significantly down regulated. Analysis of all differentially expressed genes to identify genes that were common to both models found several morphology related gene clusters; actin binding (DIAPH2, FHOD3, ABLIM1, TMOD4, MYH10), GTPase activator activity (BCR, MYH10), cytoskeleton (MAP2, MYH10, TMOD4, FHOD3), protein binding (ITGA6, CD44), proteinaceous extracellular matrix (NID2, CILP2), ion channel/ ion transporter activity (CACNA1C, CACNB2, KCNH2, SLC8A1, SLC39A9) and genes associated with developmental pathways (POFUT1, FZD2, HOXA5, IRX2, FGF11, SOX4, SMARCC1).

Conclusions

In 3D prostate cultures, stromal cells increase lateral epithelial cell adhesions. We show that this morphological effect is associated with gene expression changes to TGF beta signalling, cytoskeleton and anion activity.

Transcriptome asymmetry within mouse zygotes but not between early embryonic sister blastomeres

Transcriptome regionalization is an essential polarity determinant among metazoans, directing embryonic axis formation during normal development. Although conservation of this principle in mammals is assumed, recent evidence is conflicting and it is not known whether transcriptome asymmetries exist within unfertilized mammalian eggs or between the respective cleavage products of early embryonic divisions. We here address this by comparing transcriptome profiles of paired single cells and sub-cellular structures obtained microsurgically from mouse oocytes and totipotent embryos. Paired microsurgical spindle and remnant samples from unfertilized metaphase II oocytes possessed distinguishable profiles. Fertilization produces a totipotent 1-cell embryo (zygote) and associated spindle-enriched second polar body whose paired profiles also differed, reflecting spindle transcript enrichment. However, there was no programmed transcriptome asymmetry between sister cells within 2- or 3-cell embryos. Accordingly, there is transcriptome asymmetry within mouse oocytes, but not between the sister blastomeres of early embryos. This work places constraints on pre-patterning in mammals and provides documentation correlating potency changes and transcriptome partitioning at the single-cell level.

Development and applications of single-cell transcriptome analysis

Dissecting the relationship between genotype and phenotype is one of the central goals in developmental biology and medicine. Transcriptome analysis is a powerful strategy to connect genotype to phenotype of a cell. Here we review the history, progress, potential applications and future developments of single-cell transcriptome analysis. In combination with live cell imaging and lineage tracing, it will be possible to decipher the full gene expression network underlying physiological functions of individual cells in embryos and adults, and to study diseases.

Single-cell cDNA microarray profiling of complex biological processes of differentiation

Gene expression profiling at the single-cell level has been used to identify genes expressed in specific cell populations, in attempts to address various fundamental questions in multicellular organisms. In this article, we review the advance of single-cell cDNA amplification techniques in the last decade, and introduce a recently developed, reliable, quantitative method that is applicable to genome-wide transcriptional analyses with high-density oligonucleotide microarray and massively parallel sequencing. This method has been applied to a variety of biological studies, including developments of blastocyst inner cell mass, neurons, and primordial germ cells, to profile the molecular properties, dynamics during differentiation, and impacts of gene alterations in the individual cells in depth. These studies uncovered complex behaviors of the cells during differentiation in vivo, and identified previously unknown, transient populations that emerged in specific stages of development. These achievements clearly demonstrated that it is now more feasible to analyze gene expression in any cell type of interest in a quantitative, genome-wide manner at the single-cell resolution.

Identifying single-cell molecular programs by stochastic profiling

Cells within tissues can be morphologically indistinguishable yet show molecular expression patterns that are remarkably heterogeneous. Here, we describe an approach for comprehensively identifying coregulated, heterogeneously expressed genes among cells that otherwise appear identical. The technique, called “stochastic profiling”, involves the repeated, random selection of very-small cell populations via laser-capture microdissection, followed by a customized single-cell amplification procedure and transcriptional profiling. Fluctuations in the resulting gene-expression measurements are then analyzed statistically to identify transcripts that are heterogeneously co-expressed. We stochastically profiled matrix-attached human epithelial cells in a three-dimensional culture model of mammary-acinar morphogenesis. Of 4,557 transcripts, we identified 547 genes with strong cell-to-cell expression differences. Clustering of this heterogeneous subset revealed several molecular “programs” implicated in protein biosynthesis, oxidative-stress responses, and nuclear factor-κB signaling, which were independently confirmed by RNA fluorescence in situ hybridization. Thus, stochastic profiling can reveal single-cell heterogeneities without measuring individual cells explicitly.

RNA-Seq analysis to capture the transcriptome landscape of a single cell

We describe here a protocol for digital transcriptome analysis in a single mouse oocyte and blastomere using a deep-sequencing approach. In this method, individual cells are isolated and transferred into lysate buffer by mouth pipette, followed by reverse transcription carried out directly on the whole cell lysate. Free primers are removed by exonuclease I and a poly(A) tail is added to the 3' end of the first-strand cDNAs by terminal deoxynucleotidyl transferase. Single-cell cDNAs are then amplified by 20 + 9 cycles of PCR. The resulting 100-200 ng of amplified cDNAs are used to construct a sequencing library, which can be used for deep sequencing using the SOLiD system. Compared with cDNA microarray techniques, our assay can capture up to 75% more genes expressed in early embryos. This protocol can generate deep-sequencing libraries for 16 single-cell samples within 6 d.

A continuum of cell states spans pluripotency and lineage commitment in human embryonic stem cells

BACKGROUND

Commitment in embryonic stem cells is often depicted as a binary choice between alternate cell states, pluripotency and specification to a particular germ layer or extraembryonic lineage. However, close examination of human ES cell cultures has revealed significant heterogeneity in the stem cell compartment.

METHODOLOGY/PRINCIPAL FINDINGS

We isolated subpopulations of embryonic stem cells using surface markers, then examined their expression of pluripotency genes and lineage specific transcription factors at the single cell level, and tested their ability to regenerate colonies of stem cells. Transcript analysis of single embryonic stem cells showed that there is a gradient and a hierarchy of expression of pluripotency genes in the population. Even cells at the top of the hierarchy generally express only a subset of the stem cell genes studied. Many cells co-express pluripotency and lineage specific genes. Cells along the continuum show a progressively decreasing likelihood of self renewal as their expression of stem cell surface markers and pluripotency genes wanes. Most cells that are positive for stem cell surface markers express Oct-4, but only those towards the top of the hierarchy express the nodal receptor TDGF-1 and the growth factor GDF3.

SIGNIFICANCE

These findings on gene expression in single embryonic stem cells are in concert with recent studies of early mammalian development, which reveal molecular heterogeneity and a stochasticity of gene expression in blastomeres. Our work indicates that only a small fraction of the population resides at the top of the hierarchy, that lineage priming (co-expression of stem cell and lineage specific genes) characterizes pluripotent stem cell populations, and that extrinsic signaling pathways are upstream of transcription factor networks that control pluripotency.

Micrometastatic disease in breast cancer: clinical implications

The presence of bone marrow disseminated tumour cells (DTCs) was shown to predict poor clinical outcome in early breast cancer. However, peripheral blood is easier to obtain and allows for serial monitoring of minimal residual disease. Towards this aim, circulating tumour cells (CTCs) in the blood are detected using either direct methods, mainly antibody-based assays (immunocytochemistry, immunofluorescence and flow cytometry), or indirect methods, mainly nucleic acid-based assays (detection of mRNA transcripts by reverse transcriptase polymerase chain reaction, RT-PCR). The detection of CTCs using RT-PCR for CK19 was shown to be an independent prognostic factor in women with early breast cancer. Furthermore, considerable progress has been accomplished in genotyping, phenotyping and profiling micrometastatic cells. The challenge now is to integrate minimal residual disease as a prognostic and predictive tool in the management of breast cancer. This requires the standardisation of micrometastatic cell detection and characterisation, which will allow the incorporation of CTCs/DTCs into prospective clinical trials testing their clinical utility.

Gene expression analysis of RNA purified from embryonic stem cells and embryoid body-derived cells using a high-throughput microarray platform

In this unit, starting with purified RNA, experimental protocols for performing microarray expression analysis of embryonic stem cell lines compared to their corresponding differentiated embryocidal bodies are described. Methods for data analysis are suggested, with the goal of determining which genes are differentially expressed between the preparations. As an example, the use of the Affymetrix microarray expression platform is described, but alternative experimental options for analysis of RNA transcript levels are also summarized. This unit suggests quality control metrics, summarizes the critical parameters necessary for obtaining reproducible experimental results, and outlines quantitative PCR methods for validating microarray results.

Multiplex rt-PCR expression analysis of developmentally important genes in individual mouse preimplantation embryos and blastomeres

We have developed a microfluidic chip-based qualitative assay for sensitive (10 RNA copies) detection of multiple transcripts in single cells. We determined the expression patterns of 17 developmentally important genes and isoforms in individual mouse preimplantation embryos from superovulated matings and blastomeres. The ubiquitously expressed histone variant H3f3a and the transcription factor Pou5f1 generated mRNA-derived products in all analyzed (1-cell, 2-cell, 4-cell, and morula stage) embryos and in all analyzed blastomeres from 16-cell embryos, indicating a uniform reactivation of pluripotency gene expression during mouse preimplantation development. In contrast, mRNA expression of different methyltransferases for DNA methylation, methylcytosine-binding proteins for chromatin modification, and base excision repair enzymes, which may provide a mechanism for active demethylation, varied considerably between individual cells from the same embryo and even more dramatically between cells from different embryos. We conclude that at a given point in time the transcriptome encoding the reprogramming machinery and, by extrapolation, genome reprogramming differs between blastomeres. By studying the cell-to-cell variability in gene expression, we can distinguish the following two classes: mouse 16-cell embryos in which most cells express the reprogramming machinery and embryos in which most cells do not contain detectable mRNA levels of DNA and chromatin modification genes. Immunolocalization of DNMT3A, MBD3, APEX1, and LIG3 in most or all nuclei of 40-60-cell embryos is a good indicator of functional activity of genes that are activated by the 16-cell stage.

Direct genetic analysis of single disseminated cancer cells for prediction of outcome and therapy selection in esophageal cancer

The increasing use of primary tumors as surrogate markers for prognosis and therapeutic decisions neglects evolutionary aspects of cancer progression. To address this problem, we studied the precursor cells of metastases directly for the identification of prognostic and therapeutic markers and prospectively analyzed single disseminated cancer cells from lymph nodes and bone marrow of 107 consecutive esophageal cancer patients. Whole-genome screening revealed that primary tumors and lymphatically and hematogenously disseminated cancer cells diverged for most genetic aberrations. However, we identified chromosome 17q12-21, the region comprising HER2, as the most frequent gain in disseminated tumor cells that were isolated from both ectopic sites. Survival analysis demonstrated that HER2 gain in a single disseminated tumor cell but not in primary tumors conferred high risk for early death.

Space and time-resolved gene expression experiments on cultured mammalian cells by a single-cell electroporation microarray

Single-cell experiments represent the next frontier for biochemical and gene expression research. Although bulk-scale methods averaging populations of cells have been traditionally used to investigate cellular behavior, they mask individual cell features and can lead to misleading or insufficient biological results. We report on a single-cell electroporation microarray enabling the transfection of pre-selected individual cells at different sites within the same culture (space-resolved), at arbitrarily chosen time points and even sequentially to the same cells (time-resolved). Delivery of impermeant molecules by single-cell electroporation was first proven to be finely tunable by acting on the electroporation protocol and then optimized for transfection of nucleic acids into Chinese Hamster Ovary (CHO-K1) cells. We focused on DNA oligonucleotides (ODNs), short interfering RNAs (siRNAs), and DNA plasmid vectors, thus providing a versatile and easy-to-use platform for time-resolved gene expression experiments in single mammalian cells.

Circulating tumor cells in breast cancer

PURPOSE OF REVIEW

To critically review the latest findings concerning the detection and characterization of circulating tumor cells in breast cancer.

RECENT FINDINGS

Various studies have used different methods and markers for circulating tumor cell detection in breast cancer. Data on the prognostic value of circulating tumor cell monitoring by the CellSearch system are now available in patients with measurable metastatic breast cancer receiving chemotherapy, whereas no such data are still available for adjuvant or neoadjuvant settings. The detection of cytokeratin 19 mRNA-positive cells before the initiation of adjuvant chemotherapy was shown to be an independent prognostic factor for worse clinical outcome in patients with early breast cancer. Interestingly, this was mainly observed in patients with triple-negative and HER2-positive, but not estrogen receptor-positive/HER2-negative, early breast cancer. Finally, gene-expression profiling of single cells was reported to be feasible with important implications for eliminating circulating tumor cells. Pilot studies have shown that phenotyping of circulating tumor cells could be used to predict response to targeted therapies.

SUMMARY

Circulating tumor cells might become a valuable tool to refine prognosis in early and metastatic breast cancer. Circulating tumor cell phenotyping/profiling may serve as a real-time tumor biopsy for individually-tailored targeted therapies.

Polony analysis of gene expression in ES cells and blastocysts

Expression profiling of stem cells is challenging due to their small numbers and heterogeneity. The PCR colony (polony) approach has theoretical advantages as an assay for stem cells but has not been applied to small numbers of cells. An assay has been developed that is sensitive enough to detect mRNAs from small numbers of ES cells and from fractions of a single mouse blastocyst. Genes assayed include Oct3, Rex1, Nanog, Cdx2 and GLUT-1. The assay is highly sensitive so that multiple mRNAs from a single blastocyst were easily detected in the same assay. In its present version, the assay is an attractive alternative to conventional RT–PCR for profiling small populations of stem cells. The assay is also amenable to improvements that will increase its sensitivity and ability to analyze many cDNAs simultaneously.