Aberrant T-cell antigen expression in classical Hodgkin lymphoma is associated with decreased event-free survival and overall survival.

Hodgkin/Reed-Sternberg (HRS) cells of classical Hodgkin lymphoma (cHL) rarely express T-cell-associated antigens (TCA), but the clinical significance of this finding is uncertain. Fifty cHLs expressing any TCA on the HRS cells (TCA-cHL) were identified in two cohorts (National Cancer Institute, n = 38; Basel, n = 12). Diagnostic pathology data were examined in all cases with additional T-cell receptor γ rearrangements (TRG@) polymerase chain reaction (PCR) in a subset of cases. The outcome data were compared with a cohort of cHLs negative for TCA (n = 272). Primary end points examined were event-free survival (EFS) and overall survival (OS). The median age in the TCA-cHL group was 40 years (range, 10-85 years). Seventy percent presented in low stage (stage I/II) at presentation with nodular sclerosis (NS) histology predominating in 80% of cases. Among the TCA, CD4 and CD2 were most commonly expressed, seen in 80.4% and 77.4% of cases, respectively. TRG@ PCR was negative for clonal rearrangements in 29 of 31 cases. During a median follow up of 113 months, TCA expression predicted shorter OS (adjusted hazard ratio [HRadj] = 3.32 [95% confidence interval (CI): 1.61, 6.84]; P = .001) and EFS (HRadj = 2.55 [95% CI: 1.45, 4.49]; P = .001). TCA-cHL often display NS histology, lack T-cell genotype, and are independently associated with significantly shorter OS and EFS compared with TCA-negative cHLs.

Viral expression and molecular profiling in liver tissue versus microdissected hepatocytes in hepatitis B virus-associated hepatocellular carcinoma.

BACKGROUND: The molecular mechanisms whereby hepatitis B virus (HBV) induces hepatocellular carcinoma (HCC) remain elusive. We used genomic and molecular techniques to investigate host-virus interactions by studying multiple areas of the same liver from patients with HCC. METHODS: We compared the gene signature of whole liver tissue (WLT) versus laser capture-microdissected (LCM) hepatocytes along with the intrahepatic expression of HBV. Gene expression profiling was performed on up to 17 WLT specimens obtained at various distances from the tumor center from individual livers of 11 patients with HCC and on selected LCM samples. HBV markers in liver and serum were determined by real-time polymerase chain reaction (PCR) and confocal immunofluorescence. RESULTS: Analysis of 5 areas of the liver showed a sharp change in gene expression between the immediate perilesional area and tumor periphery that correlated with a significant decrease in the intrahepatic expression of HB surface antigen (HBsAg). The tumor was characterized by a large preponderance of down-regulated genes, mostly involved in the metabolism of lipids and fatty acids, glucose, amino acids and drugs, with down-regulation of pathways involved in the activation of PXR/RXR and PPARα/RXRα nuclear receptors, comprising PGC-1α and FOXO1, two key regulators critically involved not only in the metabolic functions of the liver but also in the life cycle of HBV, acting as essential transcription factors for viral gene expression. These findings were confirmed by gene expression of microdissected hepatocytes. Moreover, LCM of malignant hepatocytes also revealed up-regulation of unique genes associated with cancer and signaling pathways, including two novel HCC-associated cancer testis antigen genes, NUF2 and TTK. CONCLUSIONS: Integrated gene expression profiling of whole liver tissue with that of microdissected hepatocytes demonstrated that HBV-associated HCC is characterized by a metabolism switch-off and by a significant reduction in HBsAg. LCM proved to be a critical tool to validate gene signatures associated with HCC and to identify genes that may play a role in hepatocarcinogenesis, opening new perspectives for the discovery of novel diagnostic markers and therapeutic targets.

Deletion of the olfactomedin 4 gene is associated with progression of human prostate cancer.

The olfactomedin 4 (OLFM4) gene is located on chromosome 13q14.3, which frequently is deleted in human prostate cancer. However, direct genetic evidence of OLFM4 gene alteration in human prostate cancer has not yet been obtained. In this study, we investigated the genetics, protein expression, and functions of the OLFM4 gene in human prostate cancer. We found overall 25% deletions within the OLFM4 gene in cancerous epithelial cells compared with adjacent normal epithelial cells that were microdissected from 31 prostate cancer specimens using laser-capture microdissection and genomic DNA sequencing. We found 28% to 45% hemizygous and 15% to 57% homozygous deletions of the OLFM4 gene via fluorescence in situ hybridization analysis from 44 different prostate cancer patient samples. Moreover, homozygous deletion of the OLFM4 gene significantly correlated with advanced prostate cancer. By using immunohistochemical analysis of 162 prostate cancer tissue array samples representing a range of Gleason scores, we found that OLFM4 protein expression correlated inversely with advanced prostate cancer, consistent with the genetic results. We also showed that a truncated mutant of OLFM4 that lacks the olfactomedin domain eliminated suppression of PC-3 prostate cancer cell growth. Together, our findings indicate that OLFM4 is a novel candidate tumor-suppressor gene for chromosome 13q and may shed new light on strategies that could be used for the diagnosis, prognosis, and treatment of prostate cancer patients.

High molecular weight polyethylene glycol cellular distribution and PEG-associated cytoplasmic vacuolation is molecular weight dependent and does not require conjugation to proteins.

Conjugation of therapeutic proteins with high molecular weight polyethylene glycols (HMW PEGs) is used to extend the half-life of biologics. To evaluate the effects of HMW PEGs in animals, we used an immunohistochemical procedure to study the tissue distribution and toxicity of unconjugated HMW PEGs in rats given 100 mg/kg (10K)PEG, (20K)PEG, or (40K)PEG intravenously. Both the PEG cellular distribution and the histology were different between groups. In (10K)PEG and (20K)PEG groups, PEG immunoreactivity was most prominent in the renal tubule epithelium and in alveolar macrophages and hepatic Kupffer cells and cellular vacuolation was absent. In contrast, rats given (40K)PEG had strong PEG immunoreactivity in splenic subcapsular red pulp macrophages, renal interstitial macrophages, and choroid plexus epithelial cells that was frequently associated with cytoplasmic vacuolation. While the vacuolation appeared to be an adaptive response, there was focal renal tubular epithelial degeneration associated with strong PEG immunoreactivity in one rat given (40K)PEG. These data indicate that both the tissue distribution and the vacuolation observed with unconjugated HMW PEGs are markedly influenced by the molecular weight of the PEG and that when vacuolation is observed it is likely an adaptive change that is associated with PEG cytoplasmic immunoreactivity.

Pathologist-trained machine learning classifiers developed to quantitate celiac disease features differentiate endoscopic biopsies according to modified marsh score and dietary intervention response.

BACKGROUND: Histologic evaluation of the mucosal changes associated with celiac disease is important for establishing an accurate diagnosis and monitoring the impact of investigational therapies. While the Marsh-Oberhuber classification has been used to categorize the histologic findings into discrete stages (i.e., Type 0-3c), significant variability has been documented between observers using this ordinal scoring system. Therefore, we evaluated whether pathologist-trained machine learning classifiers can be developed to objectively quantitate the pathological changes of villus blunting, intraepithelial lymphocytosis, and crypt hyperplasia in small intestine endoscopic biopsies. METHODS: A convolutional neural network (CNN) was trained and combined with a secondary algorithm to quantitate intraepithelial lymphocytes (IEL) with 5 classes on CD3 immunohistochemistry whole slide images (WSI) and used to correlate feature outputs with ground truth modified Marsh scores in a total of 116 small intestine biopsies. RESULTS: Across all samples, median %CD3 counts (positive cells/enterocytes) from villous epithelium (VE) increased with higher Marsh scores (Type 0%CD3 VE = 13.4; Type 1-3%CD3 VE = 41.9, p < 0.0001). Indicators of villus blunting and crypt hyperplasia were also observed (Type 0-2 villous epithelium/lamina propria area ratio = 0.81; Type 3a-3c villous epithelium/lamina propria area ratio = 0.29, p < 0.0001), and Type 0-1 crypt/villous epithelial area ratio = 0.59; Type 2-3 crypt/villous epithelial area ratio = 1.64, p < 0.0001). Using these individual features, a combined feature machine learning score (MLS) was created to evaluate a set of 28 matched pre- and post-intervention biopsies captured before and after dietary gluten restriction. The disposition of the continuous MLS paired biopsy result aligned with the Marsh score in 96.4% (27/28) of the cohort. CONCLUSIONS: Machine learning classifiers can be developed to objectively quantify histologic features and capture additional data not achievable with manual scoring. Such approaches should be further investigated to improve biopsy evaluation, especially for clinical trials.

Methylation profiling of mediastinal gray zone lymphoma reveals a distinctive signature with elements shared by classical Hodgkin's lymphoma and primary mediastinal large B-cell lymphoma.

BACKGROUND: Mediastinal gray zone lymphoma is a newly recognized entity with transitional morphological and immunophenotypic features between the nodular sclerosis subtype of Hodgkin's lymphoma and primary mediastinal large B-cell lymphoma. Diagnostic criteria for mediastinal gray zone lymphoma are still challenging, and the optimal therapy is as yet undetermined. Epigenetic changes have been implicated in the loss of the B-cell program in classical Hodgkin's lymphoma, and might provide a basis for the immunophenotypic alterations seen in mediastinal gray zone lymphoma. DESIGN AND METHODS: We performed a large-scale DNA methylation analysis of microdissected tumor cells to investigate the biological underpinnings of mediastinal gray zone lymphoma and its association with the related entities classical Hodgkin's lymphoma and primary mediastinal large B-cell lymphoma, making comparisons with the presumptively less related diffuse large B-cell lymphoma. RESULTS: Principal component analysis demonstrated that mediastinal gray zone lymphoma has a distinct epigenetic profile intermediate between classical Hodgkin's lymphoma and primary mediastinal large B-cell lymphoma but remarkably different from that of diffuse large B-cell lymphoma. Analysis of common hypo- and hypermethylated CpG targets in mediastinal gray zone lymphoma, classical Hodgkin's lymphoma, primary mediastinal large B-cell lymphoma and diffuse large B-cell lymphoma was performed and confirmed the findings of the principal component analysis. Based on the epigenetic profiles we were able to establish class prediction models utilizing genes such as HOXA5, MMP9, EPHA7 and DAPK1 which could distinguish between mediastinal gray zone lymphoma, classical Hodgkin's lymphoma and primary mediastinal large B-cell lymphoma with a final combined prediction of 100%. CONCLUSIONS: Our data confirm a close relationship between mediastinal gray zone lymphoma and both classical Hodgkin's lymphoma and primary mediastinal large B-cell lymphoma. However, important differences were observed as well, allowing a clear distinction from both parent entities. Thus, mediastinal gray zone lymphoma cannot be assigned to either classical Hodgkin's lymphoma or primary mediastinal large B-cell lymphoma, validating the decision to create an intermediate category in the World Health Organization classification.

Human intestinal tissue and cultured colonic cells contain globotriaosylceramide synthase mRNA and the alternate Shiga toxin receptor globotetraosylceramide.

Escherichia coli O157:H7 and other Shiga toxin (Stx)-producing E. coli (STEC) bacteria are not enteroinvasive but can cause hemorrhagic colitis. In some STEC-infected individuals, a life-threatening sequela of infection called the hemolytic uremic syndrome may develop that can lead to kidney failure. This syndrome is linked to the production of Stx by the infecting organism. For Stx to reach the kidney, the toxin must first penetrate the colonic epithelial barrier. However, the Stx receptor, globotriaosylceramide (Gb3), has been thought to be absent from human intestinal epithelial cells. Thus, the mechanisms by which the toxin associates with and traverses through the intestine en route to the kidneys have been puzzling aspects of STEC pathogenesis. In this study, we initially determined that both types of Stx made by STEC, Stx1 and Stx2, do in fact bind to colonic epithelia in fresh tissue sections and to a colonic epithelial cell line (HCT-8). We also discovered that globotetraosylceramide (Gb4), a lower-affinity toxin receptor derived from Gb3, is readily detectable on the surfaces of human colonic tissue sections and HCT-8 cells. Furthermore, we found that Gb3 is present on a fraction of HCT-8 cells, where it presumably functions to bind and internalize Stx1 and Stx2. In addition, we established by quantitative real-time PCR (qRT-PCR) that both fresh colonic epithelial sections and HCT-8 cells express Gb3 synthase mRNA. Taken together, our data suggest that Gb3 may be present in small quantities in human colonic epithelia, where it may compete for Stx binding with the more abundantly expressed glycosphingolipid Gb4.

Cross-Platform Comparison of Computer-assisted Image Analysis Quantification of In Situ mRNA Hybridization in Investigative Pathology.

Although availability of automated platforms has proliferated, there is no standard practice for computer-assisted generation of scores for mRNA in situ hybridization (ISH) visualized by brightfield microscopic imaging on tissue sections. To address this systematically, an ISH for peptidylprolyl isomerase B (PPIB) (cyclophilin B) mRNA was optimized and applied to a tissue microarray of archival non-small cell lung carcinoma cases, and then automated image analysis for PPIB was refined across 4 commercially available software platforms. Operator experience and scoring results from ImageScope, HALO, CellMap, and Developer XD were systematically compared with each other and to manual pathologist scoring. Markup images were compared and contrasted for accuracy, the ability of the platform to identify cells, and the ease of visual assessment to determine appropriate interpretation. Comparing weighted scoring approaches using H-scores (Developer XD, ImageScope, and manual scoring) a correlation was observed (R value=0.7955), and association between the remaining 2 approaches (HALO and CellMap) was of similar value. ImageScope showed the highest R value in comparison with manual scoring (0.7377). Mean-difference plots showed that HALO produced the highest relative normalized values, suggesting higher relative sensitivity. ImageScope overestimated PPIB ISH signal at the high end of the range scores; however, this tendency was not observed in other platforms. HALO emerged with the highest number of favorable observations, no apparent systematic bias in score generation compared with the other methods, and potentially higher sensitivity to detect ISH. HALO may serve as a tool to empower teams of investigative pathology laboratory scientists to assist pathologists readily with quantitative scoring of ISH.

The usefulness of the detection of GSTP1 methylation in urine as a biomarker in the diagnosis of prostate cancer.

PURPOSE: Prostate cancer has a unique set of problems associated with its early detection and diagnosis that might be aided by the addition of molecular markers, such as DNA hypermethylation. DNA methylation is an important epigenetic mechanism of gene regulation that has a critical role in normal developmental processes. Aberrant DNA methylation is a hallmark of carcinogenesis and GSTP1 hypermethylation is the most common molecular alteration in human prostate cancer. To our knowledge the clinical usefulness of the detection of gene methylation is yet to be established. MATERIALS AND METHODS: We evaluated GSTP1 hypermethylation in urine collected after prostatic massage and in core needle biopsies from 100 men referred for diagnostic biopsy. RESULTS: Methylation of GSTP1 in urine specimens had 75% sensitivity and 98% specificity for prostate cancer. GSTP1 methylation in the biopsy had 88% specificity and 91% sensitivity. Interestingly we observed a higher frequency of GSTP1 methylation in the urine of men with stage III vs II disease (100% vs 20%, p = 0.05). CONCLUSIONS: This study suggests that the detection of GSTP1 methylation in prediagnostic urine may improve the specificity of PSA and help distinguish men with prostate cancer from those with benign prostatic hyperplasia. This finding should be further explored in a larger, prospective screening trial.

Computer-Aided Laser Dissection: A Microdissection Workflow Leveraging Image Analysis Tools.

INTRODUCTION: The development and application of new molecular diagnostic assays based on next-generation sequencing and proteomics require improved methodologies for procurement of target cells from histological sections. Laser microdissection can successfully isolate distinct cells from tissue specimens based on visual selection for many research and clinical applications. However, this can be a daunting task when a large number of cells are required for molecular analysis or when a sizeable number of specimens need to be evaluated. MATERIALS AND METHODS: To improve the efficiency of the cellular identification process, we describe a microdissection workflow that leverages recently developed and open source image analysis algorithms referred to as computer-aided laser dissection (CALD). CALD permits a computer algorithm to identify the cells of interest and drive the dissection process. RESULTS: We describe several "use cases" that demonstrate the integration of image analytic tools probabilistic pairwise Markov model, ImageJ, spatially invariant vector quantization (SIVQ), and eSeg onto the ThermoFisher Scientific ArcturusXT and Leica LMD7000 microdissection platforms. CONCLUSIONS: The CALD methodology demonstrates the integration of image analysis tools with the microdissection workflow and shows the potential impact to clinical and life science applications.

Tumor-associated endothelial cells display GSTP1 and RARbeta2 promoter methylation in human prostate cancer.

BACKGROUND: A functional blood supply is essential for tumor growth and proliferation. However, the mechanism of blood vessel recruitment to the tumor is still poorly understood. Ideally, a thorough molecular assessment of blood vessel cells would be critical in our comprehension of this process. Yet, to date, there is little known about the molecular makeup of the endothelial cells of tumor-associated blood vessels, due in part to the difficulty of isolating a pure population of endothelial cells from the heterogeneous tissue environment. METHODS: Here we describe the use of a recently developed technique, Expression Microdissection, to isolate endothelial cells from the tumor microenvironment. The methylation status of the dissected samples was evaluated for GSTP1 and RARbeta2 promoters via the QMS-PCR method. RESULTS: Comparing GSTP1 and RARbeta2 promoter methylation data, we show that 100% and 88% methylation is detected, respectively, in the tumor areas, both in epithelium and endothelium. Little to no methylation is observed in non-tumor tissue areas. CONCLUSION: We applied an accurate microdissection technique to isolate endothelial cells from tissues, enabling DNA analysis such as promoter methylation status. The observations suggest that epigenetic alterations may play a role in determining the phenotype of tumor-associated vasculature.

High-Throughput Microdissection for Next-Generation Sequencing.

Precision medicine promises to enhance patient treatment through the use of emerging molecular technologies, including genomics, transcriptomics, and proteomics. However, current tools in surgical pathology lack the capability to efficiently isolate specific cell populations in complex tissues/tumors, which can confound molecular results. Expression microdissection (xMD) is an immuno-based cell/subcellular isolation tool that procures targets of interest from a cytological or histological specimen. In this study, we demonstrate the accuracy and precision of xMD by rapidly isolating immunostained targets, including cytokeratin AE1/AE3, p53, and estrogen receptor (ER) positive cells and nuclei from tissue sections. Other targets procured included green fluorescent protein (GFP) expressing fibroblasts, in situ hybridization positive Epstein-Barr virus nuclei, and silver stained fungi. In order to assess the effect on molecular data, xMD was utilized to isolate specific targets from a mixed population of cells where the targets constituted only 5% of the sample. Target enrichment from this admixed cell population prior to next-generation sequencing (NGS) produced a minimum 13-fold increase in mutation allele frequency detection. These data suggest a role for xMD in a wide range of molecular pathology studies, as well as in the clinical workflow for samples where tumor cell enrichment is needed, or for those with a relative paucity of target cells.

SIVQ-LCM protocol for the ArcturusXT instrument.

SIVQ-LCM is a new methodology that automates and streamlines the more traditional, user-dependent laser dissection process. It aims to create an advanced, rapidly customizable laser dissection platform technology. In this report, we describe the integration of the image analysis software Spatially Invariant Vector Quantization (SIVQ) onto the ArcturusXT instrument. The ArcturusXT system contains both an infrared (IR) and ultraviolet (UV) laser, allowing for specific cell or large area dissections. The principal goal is to improve the speed, accuracy, and reproducibility of the laser dissection to increase sample throughput. This novel approach facilitates microdissection of both animal and human tissues in research and clinical workflows.

Optimal molecular profiling of tissue and tissue components: defining the best processing and microdissection methods for biomedical applications.

Isolation of well-preserved pure cell populations is a prerequisite for sound studies of the molecular basis of any tissue-based biological phenomenon. This updated chapter reviews current methods for obtaining anatomically specific signals from molecules isolated from tissues, a basic requirement for productive linking of phenotype and genotype. The quality of samples isolated from tissue and used for molecular analysis is often glossed over or omitted from publications, making interpretation and replication of data difficult or impossible. Fortunately, recently developed techniques allow life scientists to better document and control the quality of samples used for a given assay, creating a foundation for improvement in this area. Tissue processing for molecular studies usually involves some or all of the following steps: tissue collection, gross dissection/identification, fixation, processing/embedding, storage/archiving, sectioning, staining, microdissection/annotation, and pure analyte labeling/identification and quantification. We provide a detailed comparison of some current tissue microdissection technologies and provide detailed example protocols for tissue component handling upstream and downstream from microdissection. We also discuss some of the physical and chemical issues related to optimal tissue processing and include methods specific to cytology specimens. We encourage each laboratory to use these as a starting point for optimization of their overall process of moving from collected tissue to high-quality, appropriately anatomically tagged scientific results. Improvement in this area will significantly increase life science quality and productivity. The chapter is divided into introduction, materials, protocols, and notes subheadings. Because many protocols are covered in each of these sections, information relating to a single protocol is not contiguous. To get the greatest benefit from this chapter, readers are advised to read through the entire chapter first, identify protocols appropriate to their laboratory for each step in their workflow, and then reread entries in each section pertaining to each of these single protocols.

Immunoguided microdissection techniques.

Over the past 15 years, laser-based microdissection has improved the precision by which scientists can procure cells of interest from a heterogeneous tissue section. However, for studies that require a large amount of material (e.g., proteomics) or for cells that are scattered and difficult to identify by standard histological stains, an immunostain-based, automated approach becomes essential. In this chapter, we discuss the use of immunohistochemistry (IHC) and immunofluorescence (IF) to guide the microdissection process via manual and software-driven auto-dissection methods. Although technical challenges still exist with these innovative approaches, we present here methods and protocols to successfully perform immuno-based microdissection on commercially available laser dissection systems.

Expression microdissection adapted to commercial laser dissection instruments.

Laser-based microdissection facilitates the isolation of specific cell populations from clinical or animal model tissue specimens for molecular analysis. Expression microdissection (xMD) is a second-generation technology that offers considerable advantages in dissection capabilities; however, until recently the method has not been accessible to investigators. This protocol describes the adaptation of xMD to commonly used laser microdissection instruments and to a commercially available handheld laser device in order to make the technique widely available to the biomedical research community. The method improves dissection speed for many applications by using a targeting probe for cell procurement in place of an operator-based, cell-by-cell selection process. Moreover, xMD can provide improved dissection precision because of the unique characteristics of film activation. The time to complete the protocol is highly dependent on the target cell population and the number of cells needed for subsequent molecular analysis.

SIVQ-aided laser capture microdissection: A tool for high-throughput expression profiling.

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.

Effect of immunohistochemistry on molecular analysis of tissue samples: implications for microdissection technologies.

Laser-based tissue microdissection is an important tool for the molecular evaluation of histological sections. The technology has continued to advance since its initial commercialization in the 1990s, with improvements in many aspects of the process. More recent developments are tailored toward an automated, operator-independent mode that relies on antibodies as targeting probes, such as immuno-laser capture microdissection or expression microdissection (xMD). Central to the utility of expression-based dissection techniques is the effect of the staining process on the biomolecules in histological sections. To investigate this issue, the authors analyzed DNA, RNA, and protein in immunostained, microdissected samples. DNA was the most robust molecule, exhibiting no significant change in quality after immunostaining but a variable 50% to 75% decrease in the total yield. In contrast, RNA in frozen and ethanol-fixed, paraffin-embedded samples was susceptible to hydrolysis and digestion by endogenous RNases during the initial steps of staining. Proteins from immunostained tissues were successfully analyzed by one-dimensional electrophoresis and mass spectrometry but were less amenable to solution phase assays. Overall, the results suggest investigators can use immunoguided microdissection methods for important analytic techniques; however, continued improvements in staining protocols and molecular extraction methods are key to further advancing the capability of these methods.

Immunoguided laser assisted microdissection techniques for DNA methylation analysis of archival tissue specimens.

Altered DNA methylation is a fundamental characteristic of carcinogenesis. The analysis of DNA methylation in tumor cells may help to better understand tumor pathogenesis and more importantly may be used as diagnostic tool with therapeutic consequences. To detect targets relevant in tumorigenesis, it is essential to separate neoplastic cells from nonneoplastic cells. An excellent method for isolating specific cells is laser-assisted microdissection (LAM). Target cell identification for immunoguided LAM (ILAM) requires immunohistochemistry (IHC). Yet, it is unclear whether IHC for ILAM influences DNA methylation. The goals of this study were to establish an optimized protocol for antigen retrieval and IHC of formalin-fixed paraffin-embedded (FFPE) specimens suitable for ILAM and to evaluate its effect on the DNA methylome using a high throughput array. Using ten archival FFPE specimens, we showed specific staining suitable for ILAM. Extracted DNA from microdissected cells of immunohistochemically or H&E-stained tissue sections showed identical DNA quality and a strong correlation (r = 0.94 to 0.98) for CpG target methylation of 1505 analyzed sites in a series of five paired samples. No differential methylation between H&E and IHC was detected in 1501 of 1505 CpG targets (99.7%; P < 0.05). These results demonstrate the validity and utility of the herein described protocol, which allows the application of ILAM for large-scale genomic and epigenetic analyses of archival tissue specimens.

Approaching solid tumor heterogeneity on a cellular basis by tissue proteomics using laser capture microdissection and biological mass spectrometry.

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 approximately 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.