Related Articles

Purpose

Identifying genes differentially expressed in non-dysplastic Barrett’s esophagus (BE) from those expressed in high grade dysplasia (HGD) should be of value in improving our understanding of this transition and may yield new diagnostic and/or prognostic markers. The aim of this study was to determine the differential transcriptome of HGD compared with non-dysplastic BE through gene microarray analysis of epithelial cells microdissected from archival tissue specimens.

Experimental Design

Laser capture microdissection (LCM) was used to isolate epithelial cells from adjacent inflammatory and stromal cells. Epithelial mRNA was extracted from areas of non-dysplastic BE and HGD in matched biopsies from 11 patients. mRNA was reverse transcribed and applied on Affymetrix cDNA microarray chips customized for formalin-exposed tissue. For a subset of these genes, differential gene expression was confirmed by RT-PCR and immunohistochemistry.

Results

There were 131 genes over-expressed by at least 2.5-fold in HGD versus non-dysplastic BE and 16 genes that were under-expressed by at least 2.5-fold. Among the over-expressed genes are several previously demonstrated to be increased in the neoplastic progression of BE, as well as novel genes such as lipocalin-2, S100A9, matrix metallopeptidase 12, secernin 1 and topoisomerase IIα. Genes decreased in dysplastic epithelium include MUC5AC, trefoil factor1 (TFF1), meprin A and CD13. RT-PCR validated the changes in expression in 24 of 28 selected genes. Immunohistochemistry confirmed increased protein expression for topoisomerase IIα, S100A9 and lipocalin-2 and decreased expression of TFF1 across the spectrum of BE associated dysplasia from non-dysplastic BE through adenocarcinoma.

Conclusions

This is the first study to identify epithelial genes differentially expressed in HGD versus non-dysplastic BE in matched patient samples. The genes identified include several previously implicated in the pathogenesis of Barrett’s-associated dysplasia and new candidates for further investigation.

Background

Gastric cancer samples obtained by histologic macrodissection contain a relatively high stromal content that may significantly influence gene expression profiles. Differences between the gene expression signature derived from macrodissected gastric cancer samples and the signature obtained from isolated gastric cancer epithelial cells from the same biopsies using laser-capture microdissection (LCM) were evaluated for their potential experimental biases.

Methods

RNA was isolated from frozen tissue samples of gastric cancer biopsies from 20 patients using both histologic macrodissection and LCM techniques. RNA from LCM was subject to an additional round of T7 RNA amplification. Expression profiling was performed using Affymetrix HG-U133A arrays. Genes identified in the expression signatures from each tissue processing method were compared to the set of genes contained within chromosomal regions found to harbor copy number aberrations in the tumor samples by array CGH and to proteins previously identified as being overexpressed in gastric cancer.

Results

Genes shown to have increased copy number in gastric cancer were also found to be overexpressed in samples obtained by macrodissection (LS P value < 10-5), but not in array data generated using microdissection. A set of 58 previously identified genes overexpressed in gastric cancer was also enriched in the gene signature identified by macrodissection (LS P < 10-5), but not in the signature identified by microdissection (LS P = 0.013). In contrast, 66 genes previously reported to be underexpressed in gastric cancer were enriched in the gene signature identified by microdissection (LS P < 10-5), but not in the signature identified by macrodissection (LS P = 0.89).

Conclusions

The tumor sampling technique biases the microarray results. LCM may be a more sensitive collection and processing method for the identification of potential tumor suppressor gene candidates in gastric cancer using expression profiling.

Background

Laser-capture microdissection (LCM) that enables the isolation of specific cell populations from complex tissues under morphological control is increasingly used for subsequent gene expression studies in cell biology by methods such as real-time quantitative PCR (qPCR), microarrays and most recently by RNA-sequencing. Challenges are i) to select precisely and efficiently cells of interest and ii) to maintain RNA integrity. The mammary gland which is a complex and heterogeneous tissue, consists of multiple cell types, changing in relative proportion during its development and thus hampering gene expression profiling comparison on whole tissue between physiological stages. During lactation, mammary epithelial cells (MEC) are predominant. However several other cell types, including myoepithelial (MMC) and immune cells are present, making it difficult to precisely determine the specificity of gene expression to the cell type of origin. In this work, an optimized reliable procedure for producing RNA from alveolar epithelial cells isolated from frozen histological sections of lactating goat, sheep and cow mammary glands using an infrared-laser based Arcturus Veritas LCM (Applied Biosystems®) system has been developed. The following steps of the microdissection workflow: cryosectioning, staining, dehydration and harvesting of microdissected cells have been carefully considered and designed to ensure cell capture efficiency without compromising RNA integrity.

Results

The best results were obtained when staining 8 μm-thick sections with Cresyl violet® (Ambion, Applied Biosystems®) and capturing microdissected cells during less than 2 hours before RNA extraction. In addition, particular attention was paid to animal preparation before biopsies or slaughtering (milking) and freezing of tissue blocks which were embedded in a cryoprotective compound before being immersed in isopentane. The amount of RNA thus obtained from ca.150 to 250 acini (300,000 to 600,000 μm2) ranges between 5 to 10 ng. RNA integrity number (RIN) was ca. 8.0 and selectivity of this LCM protocol was demonstrated through qPCR analyses for several alveolar cell specific genes, including LALBA (α-lactalbumin) and CSN1S2 (αs2-casein), as well as Krt14 (cytokeratin 14), CD3e and CD68 which are specific markers of MMC, lymphocytes and macrophages, respectively.

Conclusions

RNAs isolated from MEC in this manner were of very good quality for subsequent linear amplification, thus making it possible to establish a referential gene expression profile of the healthy MEC, a useful platform for tumor biomarker discovery.

Laser capture microdissection (LCM) is a versatile computer-assisted dissection method that permits collection of tissue samples with a remarkable level of anatomical resolution. LCM’s application to the study of human brain pathology is growing, although it is still relatively underutilized, compared with other areas of research. The present study examined factors that affect the utility of LCM, as performed with an Arcturus Veritas, in the study of gene expression in the human brain using frozen tissue sections. LCM performance was ascertained by determining cell capture efficiency and the quality of RNA extracted from human brain tissue under varying conditions. Among these, the relative humidity of the laboratory where tissue sections are stained, handled, and submitted to LCM had a profound effect on the performance of the instrument and on the quality of RNA extracted from tissue sections. Low relative humidity in the laboratory, i.e., 6–23%, was conducive to little or no degradation of RNA extracted from tissue following staining and fixation and to high capture efficiency by the LCM instrument. LCM settings were optimized as described herein to permit the selective capture of astrocytes, oligodendrocytes, and noradrenergic neurons from tissue sections containing the human locus coeruleus, as determined by the gene expression of cell-specific markers. With due regard for specific limitations, LCM can be used to evaluate the molecular pathology of individual cell types in post-mortem human brain.

Background

Gene expression profiling by microarray analysis of cells enriched by laser capture microdissection (LCM) faces several technical challenges. Frozen sections yield higher quality RNA than paraffin-imbedded sections, but even with frozen sections, the staining methods used for histological identification of cells of interest could still damage the mRNA in the cells. To study the contribution of staining methods to degradation of results from gene expression profiling of LCM samples, we subjected pellets of the mouse plasma cell tumor cell line TEPC 1165 to direct RNA extraction and to parallel frozen sectioning for LCM and subsequent RNA extraction. We used microarray hybridization analysis to compare gene expression profiles of RNA from cell pellets with gene expression profiles of RNA from frozen sections that had been stained with hematoxylin and eosin (H&E), Nissl Stain (NS), and for immunofluorescence (IF) as well as with the plasma cell-revealing methyl green pyronin (MGP) stain. All RNAs were amplified with two rounds of T7-based in vitro transcription and analyzed by two-color expression analysis on 10-K cDNA microarrays.

Results

The MGP-stained samples showed the least introduction of mRNA loss, followed by H&E and immunofluorescence. Nissl staining was significantly more detrimental to gene expression profiles, presumably owing to an aqueous step in which RNA may have been damaged by endogenous or exogenous RNAases.

Conclusion

RNA damage can occur during the staining steps preparatory to laser capture microdissection, with the consequence of loss of representation of certain genes in microarray hybridization analysis. Inclusion of RNAase inhibitor in aqueous staining solutions appears to be important in protecting RNA from loss of gene transcripts.

Introduction:

Laser capture microdissection (LCM) facilitates procurement of defined cell populations for study in the context of histopathology. The morphologic assessment step in the LCM procedure is time consuming and tedious, thus restricting the utility of the technology for large applications.

Results:

Here, we describe the use of Spatially Invariant Vector Quantization (SIVQ) for histological analysis and LCM. Using SIVQ, we selected vectors as morphologic predicates that were representative of normal epithelial or cancer cells and then searched for phenotypically similar cells across entire tissue sections. The selected cells were subsequently auto-microdissected and the recovered RNA was analyzed by expression microarray. Gene expression profiles from SIVQ–LCM and standard LCM–derived samples demonstrated highly congruous signatures, confirming the equivalence of the differing microdissection methods.

Conclusion:

SIVQ–LCM improves the work-flow of microdissection in two significant ways. First, the process is transformative in that it shifts the pathologist's role from technical execution of the entire microdissection to a limited-contact supervisory role, enabling large-scale extraction of tissue by expediting subsequent semi-autonomous identification of target cell populations. Second, this work-flow model provides an opportunity to systematically identify highly constrained cell populations and morphologically consistent regions within tissue sections. Integrating SIVQ with LCM in a single environment provides advanced capabilities for efficient and high-throughput histological-based molecular studies.

Background

To discover prostate cancer biomarkers, we profiled gene expression in benign and malignant cells laser capture microdissected (LCM) from prostate tissues and metastatic prostatic adenocarcinomas. Here we present methods developed, optimized, and validated to obtain high quality gene expression data.

Results

RNase inhibitor was included in solutions used to stain frozen tissue sections for LCM, which improved RNA quality significantly. Quantitative PCR assays, requiring minimal amounts of LCM RNA, were developed to determine RNA quality and concentration. SuperScript II™ reverse transcriptase was replaced with SuperScript III™, and SpeedVac concentration was eliminated to optimize linear amplification. The GeneChip® IVT labeling kit was used rather than the Enzo BioArray™ HighYield™ RNA transcript labeling kit since side-by-side comparisons indicated high-end signal saturation with the latter. We obtained 72 μg of labeled complementary RNA on average after linear amplification of about 2 ng of total RNA.

Conclusion

Unsupervised clustering placed 5/5 normal and 2/2 benign prostatic hyperplasia cases in one group, 5/7 Gleason pattern 3 cases in another group, and the remaining 2/7 pattern 3 cases in a third group with 8/8 Gleason pattern 5 cases and 3/3 metastatic prostatic adenocarcinomas. Differential expression of alpha-methylacyl coenzyme A racemase (AMACR) and hepsin was confirmed using quantitative PCR.

The ability to reliably analyze cellular and molecular profiles of normal or diseased tissues is frequently complicated by the inherent heterogeneous nature of tissues. Laser Capture Microdissection (LCM) is an innovative technique that allows the isolation and enrichment of pure subpopulations of cells from tissues under direct microscopic examination. Material obtained by LCM can be used for downstream assays including gene microarrays, western blotting, cDNA library generation and DNA genotyping. We describe a series of LCM protocols for cell collection, RNA extraction and qPCR gene expression analysis. Using reagents we helped develop commercially, we focus on two LCM approaches: laser cutting and laser capture. Reagent calculations have been pre-determined for 10 samples using the new PREXCEL-Q assay development and project management software. One can expect the entire procedure for laser cutting coupled to qPCR to take approximately 12.5–15 h, and laser capture coupled to qPCR to take approximately 13.5–17.5 h.

Background

Laser capture microdissection (LCM) has successfully isolated pure cell populations from tissue sections and the combination of LCM with standard genomic and proteomic methods has revolutionized molecular analysis of complex tissue. However, the quantity and quality of material recovered after LCM is often still limited for analysis by using whole genomic and proteomic approaches. To procure high quality and quantity of RNA after LCM, we optimized the procedures on tissue preparations and applied the approach for cell type-specific miRNA expression profiling in colorectal tumors.

Results

We found that the ethanol fixation of tissue sections for 2 hours had the maximum improvement of RNA quality (1.8 fold, p = 0.0014) and quantity (1.5 fold, p = 0.066). Overall, the quality (RNA integrity number, RIN) for the microdissected colorectal tissues was 5.2 ± 1.5 (average ± SD) for normal (n = 43), 5.7 ± 1.1 for adenomas (n = 14) and 7.2 ± 1.2 for carcinomas (n = 44). We then compared miRNA expression profiles of 18 colorectal tissues (6 normal, 6 adenomas and 6 carcinomas) between LCM selected epithelial cells versus stromal cells using Agilent miRNA microarrays. We identified 51 differentially expressed miRNAs (p <= 0.001) between these two cell types. We found that the miRNAs in the epithelial cells could differentiate adenomas from normal and carcinomas. However, the miRNAs in the stromal and mixed cells could not separate adenomas from normal tissues. Finally, we applied quantitative RT-PCR to cross-verify the expression patterns of 7 different miRNAs using 8 LCM-selected epithelial cells and found the excellent correlation of the fold changes between the two platforms (R = 0.996).

Conclusions

Our study demonstrates the feasibility and potential power of discovering cell type-specific miRNA biomarkers in complex tissue using combination of LCM with genome-wide miRNA analysis.

Background

The intestinal mucosa is the compartment that sustains the most severe injury in response to radiation and is therefore of primary interest. The use of whole gut extracts for analysis of gene expression may confound important changes in the mucosa. On the other hand, laser capture microdissection (LCM) is hampered by the unstable nature of RNA and by a more complicated collection process. This study assessed, in parallel samples from a validated radiation model, the indications for use of LCM for intestinal gene expression analysis.

Methodology/Principal Findings

RNA was extracted from mouse whole intestine and from mucosa by LCM at baseline and 4 h, 24 h, and 3.5 d after total body irradiation and subjected to microarray analysis. Among mucosal genes that were altered > = 2-fold, less than 7% were present in the whole gut at 4 and 24 h, and 25% at 3.5 d. As expected, pathway analysis of mucosal LCM samples showed that radiation activated the coagulation system, lymphocyte apoptosis, and tight junction signaling, and caused extensive up-regulation of cell cycle and DNA damage repair pathways. Using similar stringent criteria, regulation of these pathways, with exception of the p53 pathway, was undetectable in the whole gut. Radiation induced a dramatic increase of caspase14 and ectodysplasin A2 receptor (Eda2r), a TNFα receptor, in both types of samples.

Conclusions/Significance

LCM-isolated mucosal specimens should be used to study cellular injury, cell cycle control, and DNA damage repair pathways. The remarkable increase of caspase14 and Eda2r suggests a novel role for these genes in regulating intestinal radiation injury. Comparative gene expression data from complex tissues should be interpreted with caution.

Epithelial–mesenchymal interactions (EMIs) are critical for tooth development. Molecular mechanisms mediating these interactions in root formation is not well understood. Laser capture microdissection (LCM) and subsequent microarray analyses enable large scale in situ molecular and cellular studies of root formation but to date have been hindered by technical challenges of gaining intact histological sections of non-decalcified mineralized teeth or jaws with well-preserved RNA. Here,we describe a new method to overcome this obstacle that permits LCM of dental epithelia,adjacent mesenchyme,odontoblasts and cementoblasts from mouse incisors and molars during root development. Using this method,we obtained RNA samples of high quality and successfully performed microarray analyses. Robust differences in gene expression,as well as genes not previously associated with root formation,were identified. Comparison of gene expression data from microarray with real-time reverse transcriptase polymerase chain reaction (RT-PCR) supported our findings. These genes include known markers of dental epithelia,mesenchyme,cementoblasts and odontoblasts,as well as novel genes such as those in the fibulin family. In conclusion,our new approach in tissue preparation enables LCM collection of intact cells with well-preserved RNA allowing subsequent gene expression analyses using microarray and RT-PCR to define key regulators of tooth root development.

Purpose

To test the hypothesis that expression of Na+/K+-ATPase subunits in the lacrimal glands (LGs) of rabbits with induced autoimmune dacryoadenitis (IAD) changes.

Methods

LGs were obtained from adult female rabbits with IAD and age-matched female control rabbits. The LGs were processed for laser capture microdissection (LCM), real time RT–PCR, western blot, and immunofluorescence for the detection of mRNA and proteins of the α1, α2, β1, β2, and β3 subunits of Na+/K+-ATPase.

Results

In the rabbits with IAD, mRNA levels of α1, β1, and β3 from whole LGs were significantly lower. In samples of acini and epithelial cells from various duct segments, collected by LCM, mRNA levels of α1, β1, β2, and β3 were significantly lower in the rabbits with IAD, although mRNA for α2 could not be detected. However, western blots demonstrated that all five subunits were significantly higher in the rabbits with IAD, although their distribution patterns were similar to those of the control rabbits, as demonstrated by immunofluorescence.

Conclusions

The data presented herein demonstrated significant changes in mRNA and protein expressions of Na+/K+-ATPase subunits in rabbits with IAD, suggesting that these changes may play a role in the pathogenesis of Sjögren’s syndrome and altered LG secretion, as observed in these animals.

Background

Successful achievement of early folliculogenesis is crucial for female reproductive function. The process is finely regulated by cell-cell interactions and by the coordinated expression of genes in both the oocyte and in granulosa cells. Despite many studies, little is known about the cell-specific gene expression driving early folliculogenesis. The very small size of these follicles and the mixture of types of follicles within the developing ovary make the experimental study of isolated follicular components very difficult.

The recently developed laser capture microdissection (LCM) technique coupled with microarray experiments is a promising way to address the molecular profile of pure cell populations. However, one main challenge was to preserve the RNA quality during the isolation of single cells or groups of cells and also to obtain sufficient amounts of RNA.

Using a new LCM method, we describe here the separate expression profiles of oocytes and follicular cells during the first stages of sheep folliculogenesis.

Results

We developed a new tissue fixation protocol ensuring efficient single cell capture and RNA integrity during the microdissection procedure. Enrichment in specific cell types was controlled by qRT-PCR analysis of known genes: six oocyte-specific genes (SOHLH2, MAEL, MATER, VASA, GDF9, BMP15) and three granulosa cell-specific genes (KL, GATA4, AMH).

A global gene expression profile for each follicular compartment during early developmental stages was identified here for the first time, using a bovine Affymetrix chip. Most notably, the granulosa cell dataset is unique to date. The comparison of oocyte vs. follicular cell transcriptomes revealed 1050 transcripts specific to the granulosa cell and 759 specific to the oocyte.

Functional analyses allowed the characterization of the three main cellular events involved in early folliculogenesis and confirmed the relevance and potential of LCM-derived RNA.

Conclusions

The ovary is a complex mixture of different cell types. Distinct cell populations need therefore to be analyzed for a better understanding of their potential interactions. LCM and microarray analysis allowed us to identify novel gene expression patterns in follicular cells at different stages and in oocyte populations.

Genetically modified mice susceptible to atherosclerosis are widely used in atherosclerosis research. Although the atherosclerotic lesions in these animals show similarities to those in humans, comprehensive expression profile analysis of these lesions is limited by their very small size. In this communication, we have developed an approach to analyze global gene expression in mouse lesions by a combination of (a) laser capture microdissection (LCM) to isolate RNA from specific lesions, (b) an efficient RNA amplification method that reliably yields sufficient quantities of high quality cRNA for quantitative real-time PCR (qPCR), as well as for microarray analysis. The RNA passed multiple quality controls and the expression profile observed in lesional cells compared with the whole artery encompasses genes that are characteristic of a macrophage/foam cell population. We believe that this method represents a useful new tool for the unbiased analysis of global gene expression of specific sub-regions in atherosclerotic lesions in different rodent models.

AIM: To develop a method of labeling and micro-dissecting mouse Kupffer cells within an extraordinarily short period of time using laser capture microdissection (LCM).

METHODS: Tissues are complex structures comprised of a heterogeneous population of interconnected cells. LCM offers a method of isolating a single cell type from specific regions of a tissue section. LCM is an essential approach used in conjunction with molecular analysis to study the functional interaction of cells in their native tissue environment. The process of labeling and acquiring cells by LCM prior to mRNA isolation can be elaborate, thereby subjecting the RNA to considerable degradation. Kupffer cell labeling is achieved by injecting India ink intravenously, thus circumventing the need for in vitro staining. The significance of this novel approach was validated using a cholestatic liver injury model.

RESULTS: mRNA extracted from the microdissected cell population displayed marked increases in colony-stimulating factor-1 receptor and Kupffer cell receptor message expression, which demonstrated Kupffer cell enrichment. Gene expression by Kupffer cells derived from bile-duct-ligated, versus sham-operated, mice was compared. Microarray analysis revealed a significant (2.5-fold, q value < 10) change in 493 genes. Based on this fold-change and a standardized PubMed search, 10 genes were identified that were relevant to the ability of Kupffer cells to suppress liver injury.

CONCLUSION: The methodology outlined herein provides an approach to isolating high quality RNA from Kupffer cells, without altering the tissue integrity.

Expression profiling of restricted neural populations using microarrays can facilitate neuronal classification and provide insight into the molecular bases of cellular phenotypes. Due to the formidable heterogeneity of intermixed cell types that make up the brain, isolating cell types prior to microarray processing poses steep technical challenges that have been met in various ways. These methodological differences have the potential to distort cell-type-specific gene expression profiles insofar as they may insufficiently filter out contaminating mRNAs or induce aberrant cellular responses not normally present in vivo. Thus we have compared the repeatability, susceptibility to contamination from off-target cell-types, and evidence for stress-responsive gene expression of five different purification methods - Laser Capture Microdissection (LCM), Translating Ribosome Affinity Purification (TRAP), Immunopanning (PAN), Fluorescence Activated Cell Sorting (FACS), and manual sorting of fluorescently labeled cells (Manual). We found that all methods obtained comparably high levels of repeatability, however, data from LCM and TRAP showed significantly higher levels of contamination than the other methods. While PAN samples showed higher activation of apoptosis-related, stress-related and immediate early genes, samples from FACS and Manual studies, which also require dissociated cells, did not. Given that TRAP targets actively translated mRNAs, whereas other methods target all transcribed mRNAs, observed differences may also reflect translational regulation.

The purpose of this study was to examine solid tumor heterogeneity on a cellular basis using tissue proteomics that relies on a functional relationship between Laser Capture Microdissection (LCM) and biological mass spectrometry (MS). With the use of LCM, homogeneous regions of cells exhibiting uniform histology were isolated and captured from fresh frozen tissue specimens, which were obtained from a human lymph node containing breast carcinoma metastasis. Six specimens ∼50 000 cell each (three from tumor proper and three from tumor stroma) were collected by LCM. Specimens were processed directly on LCM caps, using sonication in buffered methanol to lyse captured cells, solubilize, and digest extracted proteins. Prepared samples were analyzed by LC/MS/MS resulting in more than 500 unique protein identifications. Decoy database searching revealed a false-positive rate between 5 and 10%. Subcellular localization analysis for stromal cells revealed plasma membrane 14%, cytoplasm 39%, nucleus 11%, extracellular space 27%, and unknown 9%; and tumor cell results were 5%, 58%, 26%, 4%, and 7%, respectively. Western blot analysis confirmed specific linkage of validated proteins to underlying pathology and their potential role in solid tumor heterogeneity. With continued research and optimization of this method including analysis of additional clinical specimens, this approach may lead to an improved understanding of tumor heterogeneity, and serve as a platform for solid tumor biomarker discovery.

An important need of many cancer research projects is the availability of high-quality, appropriately selected tissue. Tissue biorepositories are organized to collect, process, store, and distribute samples of tumor and normal tissue for further use in fundamental and translational cancer research. This, in turn, provides investigators with an invaluable resource of appropriately examined and characterized tissue specimens and linked patient information. Human tissues, in particular, tumor tissues, are complex structures composed of heterogeneous mixtures of morphologically and functionally distinct cell types. It is essential to analyze specific cell types to identify and define accurately the biologically important processes in pathologic lesions. Laser capture microdissection (LCM) is state-of-the-art technology that provides the scientific community with a rapid and reliable method to isolate a homogeneous population of cells from heterogeneous tissue specimens, thus providing investigators with the ability to analyze DNA, RNA, and protein accurately from pure populations of cells. This is particularly well-suited for tumor cell isolation, which can be captured from complex tissue samples. The combination of LCM and a tissue biorepository offers a comprehensive means by which researchers can use valuable human biospecimens and cutting-edge technology to facilitate basic, translational, and clinical research. This review provides an overview of LCM technology with an emphasis on the applications of LCM in the setting of a tissue biorepository, based on the author's extensive experience in LCM procedures acquired at Fox Chase Cancer Center and Hollings Cancer Center.

Objective

The transcriptional profile of gastric epithelial cell lines cocultured with Helicobacter pylori and the global gene expression of whole gastric mucosa has been described previously. We aimed to overcome limitations of previous studies by determining the effects of H pylori eradication on the transcriptome of purified human gastric epithelium using each patient as their own control.

Design

Laser capture microdissection (LCM) was used to extract mRNA from paraffin‐embedded antral epithelium from 10 patients with peptic ulcer disease, before and after H pylori eradication. mRNA was reverse transcribed and applied on to Affymetrix cDNA microarray chips customised for formalin‐fixed tissue. Differentially expressed genes were identified and a subset validated by real‐time polymerase chain reaction (PCR).

Results

A total of 13 817 transcripts decreased and 9680 increased after H pylori eradication. Applying cut‐off criteria (p<0.02, fold‐change threshold 2.5) reduced the sample to 98 differentially expressed genes. Genes detected included those previously implicated in H pylori pathophysiology such as interleukin 8, chemokine ligand 3, β defensin and somatostatin, as well as novel genes such as GDDR (TFIZ1), chemokine receptors 7 and 8, and gastrokine.

Conclusions

LCM of archival specimens has enabled the identification of gastric epithelial genes whose expression is considerably altered after H pylori eradication. This study has confirmed the presence of genes previously implicated in the pathogenesis of H pylori, as well as highlighted novel candidates for further investigation.

Efforts to unravel the mechanisms underlying taste sensation (gustation) have largely focused on rodents. Here we present the first comprehensive characterization of gene expression in primate taste buds. Our findings reveal unique new insights into the biology of taste buds. We generated a taste bud gene expression database using laser capture microdissection (LCM) procured fungiform (FG) and circumvallate (CV) taste buds from primates. We also used LCM to collect the top and bottom portions of CV taste buds. Affymetrix genome wide arrays were used to analyze gene expression in all samples. Known taste receptors are preferentially expressed in the top portion of taste buds. Genes associated with the cell cycle and stem cells are preferentially expressed in the bottom portion of taste buds, suggesting that precursor cells are located there. Several chemokines including CXCL14 and CXCL8 are among the highest expressed genes in taste buds, indicating that immune system related processes are active in taste buds. Several genes expressed specifically in endocrine glands including growth hormone releasing hormone and its receptor are also strongly expressed in taste buds, suggesting a link between metabolism and taste. Cell type-specific expression of transcription factors and signaling molecules involved in cell fate, including KIT, reveals the taste bud as an active site of cell regeneration, differentiation, and development. IKBKAP, a gene mutated in familial dysautonomia, a disease that results in loss of taste buds, is expressed in taste cells that communicate with afferent nerve fibers via synaptic transmission. This database highlights the power of LCM coupled with transcriptional profiling to dissect the molecular composition of normal tissues, represents the most comprehensive molecular analysis of primate taste buds to date, and provides a foundation for further studies in diverse aspects of taste biology.

Background

The methods used for sample selection and processing can have a strong influence on the expression values obtained through microarray profiling. Laser capture microdissection (LCM) provides higher specificity in the selection of target cells compared to traditional bulk tissue selection methods, but at an increased processing cost. The benefit gained from the higher tissue specificity realized through LCM sampling is evaluated in this study through a comparison of microarray expression profiles obtained from same-samples using bulk and LCM processing.

Methods

Expression data from ten lung adenocarcinoma samples and six adjacent normal samples were acquired using LCM and bulk sampling methods. Expression values were evaluated for correlation between sample processing methods, as well as for bias introduced by the additional linear amplification required for LCM sample profiling.

Results

The direct comparison of expression values obtained from the bulk and LCM sampled datasets reveals a large number of probesets with significantly varied expression. Many of these variations were shown to be related to bias arising from the process of linear amplification, which is required for LCM sample preparation. A comparison of differentially expressed genes (cancer vs. normal) selected in the bulk and LCM datasets also showed substantial differences. There were more than twice as many down-regulated probesets identified in the LCM data than identified in the bulk data. Controlling for the previously identified amplification bias did not have a substantial impact on the differences identified in the differentially expressed probesets found in the bulk and LCM samples.

Conclusion

LCM-coupled microarray expression profiling was shown to uniquely identify a large number of differentially expressed probesets not otherwise found using bulk tissue sampling. The information gain realized from the LCM sampling was limited to differential analysis, as the absolute expression values obtained for some probesets using this study's protocol were biased during the second round of amplification. Consequently, LCM may enable investigators to obtain additional information in microarray studies not easily found using bulk tissue samples, but it is of critical importance that potential amplification biases are controlled for.

The progression from preinvasive lesion to invasive carcinoma is a critical step contributing to breast cancer lethality. We identified down-regulation of milk fat globule-EGF factor 8 (MFG-E8) as a contributor to breast cancer progression using microarray analysis of laser capture microdissected (LCM) tissues. We first identified MFG-E8 down-regulation in invasive lesions in transgenic mammary tumor models, which were confirmed in LCM-isolated human invasive ductal carcinomas compared with patient-matched normal tissues. In situ analyses of MFG-E8 expression in estrogen receptor (ER) positive cases confirmed its down-regulation during breast cancer progression and small inhibitory MFG-E8 RNAs accelerated ER+ breast cancer cell proliferation. MFG-E8 also decreased in erbB2+ human cancers and erbB2 transgenic mice lacking MFG-E8 showed accelerated tumor formation. In contrast, MFG-E8 expression was present at high levels in triple negative (ER-, PgR-, erbB2-) breast cancers, cell lines and patient sera. Knockdown, ChIP and reporter assays all showed that p63 regulates MFG-E8 expression, and MFG-E8 knockdowns sensitized triple negative breast cancers to cisplatin treatment. Taken together, our results show that MFG-E8 is expressed in triple negative breast cancers as a target gene of the p63 pathway, but may serve a suppressive function in ER+ and erbB2+ breast cancers. Its potential use as a serum biomarker that contributes to the pathogenesis of triple negative breast cancers urges continued evaluation of its differential functions.

Outer hair cells (OHCs) play an important role in frequency selectivity and signal amplification in the mammalian cochlea. Because OHCs are relatively few in number and a minority of the cells in the cochlea, separating and isolating them for applications such as cDNA library creation and proteomic studies is a challenging task. Laser Capture Microdissection (LCM) is designed to capture cells from very thin tissue sections, it can accurately isolate specific cells from large regions of tissue for RNA, DNA, and proteomic studies. Due to the constraints of cochlear anatomy, thin sections of the cochlea contain small numbers of OHCs. Therefore, we adapted the LCM technique to isolate OHCs from organ of Corti whole-mounts, each of which contain hundreds of OHCs that are simultaneously accessible and collectable. For comparison, we also used a more traditional mechanical dissection. The quality of cDNA derived from the OHCs collected with LCM and with the traditional mechanical method are compared and the merits and limitations of the techniques discussed. A similar approach can also be used to isolate large quantities of inner hair cells and selected supporting cells from the whole-mount cochlear preparation.

Laser capture microdissection (LCM) permits isolation of specific cell types and cell groups based upon morphology, anatomical landmarks and histochemical properties. This powerful technique can be used for region-specific dissection if the target structure is clearly delineated. However, it is difficult to visualize anatomical boundaries in an unstained specimen, while histological staining can complicate the microdissection process and compromise downstream processing and analysis. We now introduce a novel method in which in situ hybridization (ISH) signal is used to guide LCM on adjacent unstained sections to collect tissue from neurochemically-defined regions of the human postmortem brain to minimize sample manipulation prior to analysis. This approach was validated in nuclei that provide monoaminergic inputs to the forebrain, and likely contribute to the pathophysiology of mood disorders. This method was used successfully to carry out gene expression profiling and quantitative real-time PCR (qPCR) confirmation from the dissected material. When compared to traditional micropunch dissections, our ISH-guided LCM method provided enhanced signal intensity for mRNAs of specific monoaminergic marker genes as measured by genome-wide gene expression microarrays. Enriched expression of specific monoaminergic genes (as determined by microarrays and qPCR) was detected within appropriate anatomical locations validating the accuracy of microdissection. Together these results support the conclusion that ISH-guided LCM permits acquisition of enriched nucleus-specific RNA that can be successfully used for downstream gene expression investigations. Future studies will utilize this approach for gene expression profiling of neurochemically-defined regions of postmortem brains collected from mood disorder patients.

Background

The prostate gland represents a multifaceted system in which prostate epithelia and stroma have distinct physiological roles. To understand the interaction between stroma and glandular epithelia, it is essential to delineate the gene expression profiles of these two tissue types in prostate cancer. Most studies have compared tumor and normal samples by performing global expression analysis using a mixture of cell populations. This report presents the first study of prostate tumor tissue that examines patterns of differential expression between specific cell types using laser capture microdissection (LCM).

Methods

LCM was used to isolate distinct cell-type populations and identify their gene expression differences using oligonucleotide microarrays. Ten differentially expressed genes were then analyzed in paired tumor and non-neoplastic prostate tissues by quantitative real-time PCR. Expression patterns of the transcription factors, WT1 and EGR1, were further compared in established prostate cell lines. WT1 protein expression was also examined in prostate tissue microarrays using immunohistochemistry.

Results

The two-step method of laser capture and microarray analysis identified nearly 500 genes whose expression levels were significantly different in prostate epithelial versus stromal tissues. Several genes expressed in epithelial cells (WT1, GATA2, and FGFR-3) were more highly expressed in neoplastic than in non-neoplastic tissues; conversely several genes expressed in stromal cells (CCL5, CXCL13, IGF-1, FGF-2, and IGFBP3) were more highly expressed in non-neoplastic than in neoplastic tissues. Notably, EGR1 was also differentially expressed between epithelial and stromal tissues. Expression of WT1 and EGR1 in cell lines was consistent with these patterns of differential expression. Importantly, WT1 protein expression was demonstrated in tumor tissues and was absent in normal and benign tissues.

Conclusions

The prostate represents a complex mix of cell types and there is a need to analyze distinct cell populations to better understand their potential interactions. In the present study, LCM and microarray analysis were used to identify novel gene expression patterns in prostate cell populations, including identification of WT1 expression in epithelial cells. The relevance of WT1 expression in prostate cancer was confirmed by analysis of tumor tissue and cell lines, suggesting a potential role for WT1 in prostate tumorigenesis.