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Alek Nacev1, Skye H Kim2, Jaime Rodriguez-Canales2, Michael A Tangrea2, Benjamin Shapiro1, Michael R Emmert-Buck21Fischell Department of Bioengineering, University of Maryland, College Park, MD; 2Pathogenetics Unit, Laboratory of Pathology, Center for Cancer Research National Cancer Institute, National Institutes of Health, Bethesda, MD, USAAbstract: A nanoparticle delivery system termed dynamic magnetic shift (DMS) has the potential to more effectively treat metastatic cancer by equilibrating therapeutic magnetic nanoparticles throughout tumors. To evaluate the feasibility of DMS, histological liver sections from autopsy cases of women who died from breast neoplasms were studied to measure vessel number, size, and spatial distribution in both metastatic tumors and normal tissue. Consistent with prior studies, normal tissue had a higher vascular density with a vessel-to-nuclei ratio of 0.48 ± 0.14 (n = 1000), whereas tumor tissue had a ratio of 0.13 ± 0.07 (n = 1000). For tumors, distances from cells to their nearest blood vessel were larger (average 43.8 µm, maximum 287 µm, n ≈ 5500) than normal cells (average 5.3 µm, maximum 67.8 µm, n ≈ 5500), implying that systemically delivered nanoparticles diffusing from vessels into surrounding tissue would preferentially dose healthy instead of cancerous cells. Numerical simulations of magnetically driven particle transport based on the autopsy data indicate that DMS would correct the problem by increasing nanoparticle levels in hypovascular regions of metastases to that of normal tissue, elevating the time-averaged concentration delivered to the tumor for magnetic actuation versus diffusion alone by 1.86-fold, and increasing the maximum concentration over time by 1.89-fold. Thus, DMS may prove useful in facilitating therapeutic nanoparticles to reach poorly vascularized regions of metastatic tumors that are not accessed by diffusion alone.Keywords: cancer, metastases, vasculature, drug delivery, magnetic, nanoparticles

Immunohistochemical (IHC) staining is an established technique for visualizing proteins in tissue sections for research studies and clinical applications. IHC is increasingly used as a targeting strategy for procurement of labeled cells via tissue microdissection, including immunodissection, computer-aided laser dissection (CALD), expression microdissection (xMD), and other techniques. The initial antigen retrieval (AR) process increases epitope availability and improves staining characteristics; however, the procedure can damage DNA. To better understand the effects of AR on DNA quality and quantity in immunodissected samples, both clinical specimens ( KRAS gene mutation positive cases) and model system samples (lung cancer patient-derived xenograft tissue) were subjected to commonly employed AR methods (heat induced epitope retrieval [HIER], protease digestion) and the effects on DNA were assessed by Qubit, fragment analysis, quantitative PCR, digital droplet PCR (ddPCR), library preparation, and targeted sequencing. The data showed that HIER resulted in optimal IHC staining characteristics, but induced significant damage to DNA, producing extensive fragmentation and decreased overall yields. However, neither of the AR methods combined with IHC prevented ddPCR amplification of small amplicons and gene mutations were successfully identified from immunodissected clinical samples. The results indicate for the first time that DNA recovered from immunostained slides after standard AR and IHC processing can be successfully employed for genomic mutation analysis via ddPCR and next-generation sequencing (NGS) short-read methods.

Improving the utilization of tumor tissue from diagnostic biopsies is an unmet medical need. This is especially relevant today in the rapidly evolving precision oncology field where tumor genotyping is often essential for the indication of many advanced and targeted therapies. National Comprehensive Cancer Network (NCCN) guidelines now mandate molecular testing for clinically actionable targets in certain malignancies. Utilizing advanced stage lung cancer as an example, an improved genotyping approach for solid tumors is possible. The strategy involves optimization of the microdissection process and analysis of a large number of identical target cells from formalin-fixed paraffin-embedded (FFPE) specimens sharing similar characteristics, in other words, single-cell subtype analysis. The shared characteristics can include immunostaining status, cell phenotype, and/or spatial location within a histological section. Synergy between microdissection and droplet digital PCR (ddPCR) enhances the molecular analysis. We demonstrate here a methodology that illustrates genotyping of a solid tumor from a small tissue biopsy sample in a time- and cost-efficient manner, using immunostain targeting as an example., (© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

The evolutionary progression from primary to metastatic prostate cancer is largely uncharted, and the implications for liquid biopsy are unexplored. We infer detailed reconstructions of tumor phylogenies in ten prostate cancer patients with fatal disease, and investigate them in conjunction with histopathology and tumor DNA extracted from blood and cerebrospinal fluid. Substantial evolution occurs within the prostate, resulting in branching into multiple spatially intermixed lineages. One dominant lineage emerges that initiates and drives systemic metastasis, where polyclonal seeding between sites is common. Routes to metastasis differ between patients, and likely genetic drivers of metastasis distinguish the metastatic lineage from the lineage that remains confined to the prostate within each patient. Body fluids capture features of the dominant lineage, and subclonal expansions that occur in the metastatic phase are non-uniformly represented. Cerebrospinal fluid analysis reveals lineages not detected in blood-borne DNA, suggesting possible clinical utility.

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., Competing Interests: There are no conflicts of interest.

There is limited data on the molecular mechanisms whereby hepatitis D virus (HDV) promotes liver cancer. Therefore, serum and liver specimens obtained at the time of liver transplantation from well-characterized patients with HDV-HCC ( n = 5) and with non-HCC HDV cirrhosis ( n = 7) were studied using an integrated genomic approach. Transcriptomic profiling was performed using laser capture-microdissected (LCM) malignant and nonmalignant hepatocytes, tumorous and nontumorous liver tissue from patients with HDV-HCC, and liver tissue from patients with non-HCC HDV cirrhosis. HDV-HCC was also compared with hepatitis B virus (HBV) HBV-HCC alone, and hepatitis C virus (HCV) HCV-HCC. HDV malignant hepatocytes were characterized by an enrichment of upregulated transcripts associated with pathways involved in cell-cycle/DNA replication, damage, and repair (Sonic Hedgehog, GADD45, DNA-damage-induced 14-3-3σ, cyclins and cell-cycle regulation, cell cycle: G 2 -M DNA-damage checkpoint regulation, and hereditary breast cancer). Moreover, a large network of genes identified functionally relate to DNA repair, cell cycle, mitotic apparatus, and cell division, including 4 cancer testis antigen genes, attesting to the critical role of genetic instability in this tumor. Besides being overexpressed, these genes were also strongly coregulated. Gene coregulation was high not only when compared with nonmalignant hepatocytes, but also to malignant hepatocytes from HBV-HCC alone or HCV-HCC. Activation and coregulation of genes critically associated with DNA replication, damage, and repair point to genetic instability as an important mechanism of HDV hepatocarcinogenesis. This specific HDV-HCC trait emerged also from the comparison of the molecular pathways identified for each hepatitis virus-associated HCC. Despite the dependence of HDV on HBV, these findings suggest that HDV and HBV promote carcinogenesis by distinct molecular mechanisms. Implications: This study identifies a molecular signature of HDV-associated hepatocellular carcinoma and suggests the potential for new biomarkers for early diagnostics. Mol Cancer Res; 16(9); 1406-19. ©2018 AACR ., (©2018 American Association for Cancer Research.)

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.

Laser microdissection (LM) offers a relatively rapid and precise method of isolating and removing specified cells from complex tissues for subsequent analysis of their RNA, DNA, protein or metabolite content, thereby allowing assessment of the role of different cell types in the normal physiological or disease processes being studied. In this unit, protocols for the preparation of mammalian frozen tissues, fixed tissues, and cytologic specimens for LM, including tissue freezing, tissue processing and paraffin embedding, histologic sectioning, cell processing, hematoxylin and eosin staining, immunohistochemistry, and image-guided cell targeting are presented. Also provided are recipes for generating lysis buffers for the recovery of nucleic acids and proteins. The Commentary section addresses the types of specimens that can be utilized for LM and approaches to staining of specimens for cell visualization. Emphasis is placed on the preparation of tissue or cytologic specimens as this is critical to effective LM., (Copyright © 2015 John Wiley & Sons, Inc.)

Cancers emerge from an ongoing Darwinian evolutionary process, often leading to multiple competing subclones within a single primary tumour. This evolutionary process culminates in the formation of metastases, which is the cause of 90% of cancer-related deaths. However, despite its clinical importance, little is known about the principles governing the dissemination of cancer cells to distant organs. Although the hypothesis that each metastasis originates from a single tumour cell is generally supported, recent studies using mouse models of cancer demonstrated the existence of polyclonal seeding from and interclonal cooperation between multiple subclones. Here we sought definitive evidence for the existence of polyclonal seeding in human malignancy and to establish the clonal relationship among different metastases in the context of androgen-deprived metastatic prostate cancer. Using whole-genome sequencing, we characterized multiple metastases arising from prostate tumours in ten patients. Integrated analyses of subclonal architecture revealed the patterns of metastatic spread in unprecedented detail. Metastasis-to-metastasis spread was found to be common, either through de novo monoclonal seeding of daughter metastases or, in five cases, through the transfer of multiple tumour clones between metastatic sites. Lesions affecting tumour suppressor genes usually occur as single events, whereas mutations in genes involved in androgen receptor signalling commonly involve multiple, convergent events in different metastases. Our results elucidate in detail the complex patterns of metastatic spread and further our understanding of the development of resistance to androgen-deprivation therapy in prostate cancer.

The protein product of the Multiple Endocrine Neoplasia Type I (MEN1) gene is thought to be involved in predominantly nuclear functions; however, immunohistochemical (IHC) analysis data on cellular localization are conflicting. To further investigate menin expression, we analyzed human pancreas (an MEN1 target organ) using IHC analyses and 6 antibodies raised against full-length menin or its peptides. In 10 normal pancreas specimens, 2 independently raised antibodies showed unexpected cytoplasmic immunoreactivity in peripheral cells in each islet examined (over 100 total across all 10 patients). The staining exhibited a distinct punctate pattern and subsequent immunoelectron microscopy indicated the target antigen was in secretory granules. Exocrine pancreas and pancreatic stroma were not immunoreactive. In MEN1 patients, unaffected islets stained similar to those in normal samples but with a more peripheral location of positive cells, whereas hyperplastic islets and tumorlets showed increased and diffuse cytoplasmic staining, respectively. Endocrine tumors from MEN1 patients were negative for menin, consistent with a 2-hit loss of a tumor suppressor gene. Secretory granule localization of menin in a subset of islet cells suggests a function of the protein unique to a target organ of familial endocrine neoplasia, although the IHC data must be interpreted with some caution because of the possibility of antibody cross-reaction. The identity, cellular trafficking, and role of this putative secretory granule-form of menin warrant additional investigation.

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.

The development of prognostic and diagnostic biomarkers, such as those from gene expression studies, requires independent validation in clinical specimens. Immunohistochemical analysis on tissue microarrays (TMAs) of formalin-fixed paraffin-embedded tissue is often used to increase the statistical power, and it is used more often than in situ hybridization, which can be technically limiting. Herein, we introduce a method for performing quantitative gene expression analysis across a TMA using an adaptation of 2D-RT-qPCR, a recently developed technology for measuring transcript levels in a histologic section while maintaining 2-dimensional positional information of the tissue sample. As a demonstration of utility, a TMA with tumor and normal human prostate samples was used to validate expression profiles from previous array-based gene discovery studies of prostate cancer. The results show that 2D-RT-qPCR expands the utility of TMAs to include sensitive and accurate gene expression measurements.

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., (Copyright © 2013 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

In a recent study, a unique gene expression signature was observed when comparing esophageal squamous cell carcinoma (ESCC) epithelial cells to normal esophageal epithelial cells using laser capture microdissection (LCM) and cDNA microarray technology. To validate the expression of several intriguing genes from that study (KRT17, cornulin, CD44, and EpCAM), we employed two new technologies, expression microdissection (xMD) for high-throughput microdissection facilitating protein analysis and RNAscope for the evaluation of low abundant transcripts in situ. For protein measurements, xMD technology was utilized to specifically procure sufficient tumor and normal epithelium from frozen human tissue for immunoblot analysis of KRT17 (CK17) and cornulin. A novel in situ hybridization method (RNAscope) was used to determine the transcript level of two relatively low expressed genes, CD44 and EpCAM in both individual formalin-fixed paraffin-embedded (FFPE) tissue sections and in an ESCC tissue microarray (TMA). The results successfully confirmed the initial expression pattern observed for all four genes, potentially implicating them in the pathogenesis of ESCC. Additionally, the study provides important methodological information on the overall process of candidate gene validation.

Expression microdissection (xMD) is a high-throughput, operator-independent technology that enables the procurement of specific cell populations from tissue specimens. In this method, histological sections are first stained for cellular markers via either chemical or immuno-guided methods, placed in close contact with an ethylene vinyl acetate (EVA) film, and exposed to a light source. The focal, transient heating of the stained cells or subcellular structures melts the EVA film selectively to the targets for procurement. In this report, we introduce a custom-designed flashcube system that permits consistent and reproducible microdissection of nuclei across an FFPE rat brain tissue section in milliseconds. In addition, we present a method to efficiently recover and combine captured proteins from multiple xMD films. Both light and scanning electron microscopy demonstrated captured nuclear structures. Shotgun proteomic analysis of the samples showed a significant enrichment in nuclear localized proteins, with an average 25% of recovered proteins localized to the nucleus, versus 15% for whole tissue controls (p < 0.001). Targeted mass spectrometry using multiple reaction monitoring (MRM) showed more impressive data, with a 3-fold enrichment in histones, and a concurrent depletion of proteins localized to the cytoplasm, cytoskeleton, and mitochondria. These data demonstrate that the flashcube-xMD technology is applicable to the proteomic study of a broad range of targets in molecular pathology.

The oxytocin (Oxt) and vasopressin (Avp) magnocellular neurons (MCNs) in the hypothalamus are the only neuronal phenotypes that are present in the supraoptic nucleus (SON), and are characterized by their robust and selective expression of either the Oxt or Avp genes. In this paper, we take advantage of the differential expression of these neuropeptide genes to identify and isolate these two individual phenotypes from the rat SON by laser capture microdissection (LCM), and to analyze the differential expression of several of their transcription factor mRNAs by qRT-PCR. We identify these neuronal phenotypes by stereotaxically injecting recombinant Adeno-Associated Viral (rAAV) vectors which contain cell-type specific Oxt or Avp promoters that drive expression of EGFP selectively in either the Oxt or Avp MCNs into the SON. The fluorescent MCNs are then dissected by LCM using a novel Cap Road Map protocol described in this paper, and the purified MCNs are extracted for their RNAs. qRT-PCR of these RNAs show that some transcription factors (RORA and c-jun) are differentially expressed in the Oxt and Avp MCNs.

The classic tumor clonal evolution theory postulates that cancers change over time to produce unique molecular subclones within a parent neoplasm, presumably including regional differences in gene expression. More recently, however, this notion has been challenged by studies showing that tumors maintain a relatively stable transcript profile. To examine these competing hypotheses, we microdissected discrete subregions containing approximately 3000 to 8000 cells (500 to 1500 μm in diameter) from ex vivo esophageal squamous cell carcinoma (ESCC) specimens and analyzed transcriptomes throughout three-dimensional tumor space. Overall mRNA profiles were highly similar in all 59 intratumor comparisons, in distinct contrast to the markedly different global expression patterns observed in other dissected cell populations. For example, normal esophageal basal cells contained 1918 and 624 differentially expressed genes at a greater than twofold level (95% confidence level of <5% false positives), compared with normal differentiated esophageal cells and ESCC, respectively. In contrast, intratumor regions had only zero to four gene changes at a greater than twofold level, with most tumor comparisons showing none. The present data indicate that, when analyzed using a standard array-based method at this level of histological resolution, ESCC contains little regional mRNA heterogeneity., (Copyright © 2013 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

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.

Collective cell behaviors in migration and force generation were studied at the mesoscopic-level using cells grown in a 3D extracellular matrix (ECM) simulating tissues. Magnetic resonance imaging (MRI) was applied to investigate dynamic cell mechanics at this level. MDCK, NBT2, and MEF cells were embedded in 3D ECM, forming clusters that then migrated and generated forces affecting the ECM. The cells demonstrated MRI contrast due to iron accumulation in the clusters. Timelapse-MRI enabled the measurement of dynamic stress fields generated by the cells, as well as simultaneous monitoring of the cell distribution and ECM deformation/remodeling. We found cell clusters embedded in the 3D ECM can exert translational forces to pull and push, as well as torque, their surroundings. We also observed that the sum of forces generated by multiple cell clusters may result in macroscopic deformation. In summary, MRI can be used to image cell-ECM interactions mesoscopically.

The discovery of effective cancer biomarkers is essential for the development of both advanced molecular diagnostics and new therapies/medications. Finding and exploiting useful clinical biomarkers for cancer patients is fundamentally linked to improving outcomes. Towards these aims, the heterogeneous nature of tumors represents a significant problem. Thus, methods establishing an effective functional linkage between laser capture microdissection (LCM) and mass spectrometry (MS) provides for an enhanced molecular profiling of homogenous, specifically targeted cell populations from solid tumors. Utilizing frozen tissue avoids molecular degradation and bias that can be induced by other preservation techniques. Since clinical samples are often of a small quantity, tissue losses must be minimized. Therefore, all steps are carried out in the same single tube. Proteins are identified through peptide sequencing and subsequent matching against a specific proteomic database. Using such an approach enhances clinical biomarker discovery in the following ways. First, LCM allows for the complexity of a solid tumor to be reduced. Second, MS provides for the profiling of proteins, which are the ultimate bio-effectors. Third, by selecting for tumor proper or microenvironment-specific cells from clinical samples, the heterogeneity of individual solid tumors is directly addressed. Finally, since proteins are the targets of most pharmaceuticals, the enriched protein data streams can then be further analyzed for potential biomarkers, drug targets, pathway elucidation, as well as an enhanced understanding of the various pathologic processes under study. Within this context, the following method illustrates in detail a synergy between LCM and MS for an enhanced molecular profiling of solid tumors and clinical biomarker discovery.

Background: Esophageal squamous cell carcinoma (ESCC), the predominant histological subtype of esophageal cancer, is characterized by high mortality. Previous work identified important mRNA expression differences between normal and tumor cells; however, to date there are limited ex vivo studies examining expression changes occurring during normal esophageal squamous cell differentiation versus those associated with tumorigenesis. In this study, we used a unique tissue microdissection strategy and microarrays to measure gene expression profiles associated with cell differentiation versus tumorigenesis in twelve cases of patient-matched normal basal squamous epithelial cells (NB), normal differentiated squamous epithelium (ND), and squamous cell cancer. Class comparison and pathway analysis were used to compare NB versus tumor in a search for unique therapeutic targets., Results: As a first step towards this goal, gene expression profiles and pathways were evaluated. Overall, ND expression patterns were markedly different from NB and tumor; whereas, tumor and NB were more closely related. Tumor showed a general decrease in differentially expressed genes relative to NB as opposed to ND that exhibited the opposite trend. FSH and IgG networks were most highly dysregulated in normal differentiation and tumorigenesis, respectively. DNA repair pathways were generally elevated in NB and tumor relative to ND indicating involvement in both normal and pathological growth. PDGF signaling pathway and 12 individual genes unique to the tumor/NB comparison were identified as therapeutic targets, and 10 associated ESCC gene-drug pairs were identified. We further examined the protein expression level and the distribution patterns of four genes: ODC1, POSTN, ASPA and IGF2BP3. Ultimately, three genes (ODC1, POSTN, ASPA) were verified to be dysregulated in the same pattern at both the mRNA and protein levels., Conclusions: These data reveal insight into genes and molecular pathways mediating ESCC development and provide information potentially useful in designing novel therapeutic interventions for this tumor type.

Introduction: The advent of digital slides offers new opportunities within the practice of pathology such as the use of image analysis techniques to facilitate computer aided diagnosis (CAD) solutions. Use of CAD holds promise to enable new levels of decision support and allow for additional layers of quality assurance and consistency in rendered diagnoses. However, the development and testing of prostate cancer CAD solutions requires a ground truth map of the cancer to enable the generation of receiver operator characteristic (ROC) curves. This requires a pathologist to annotate, or paint, each of the malignant glands in prostate cancer with an image editor software - a time consuming and exhaustive process. Recently, two CAD algorithms have been described: probabilistic pairwise Markov models (PPMM) and spatially-invariant vector quantization (SIVQ). Briefly, SIVQ operates as a highly sensitive and specific pattern matching algorithm, making it optimal for the identification of any epithelial morphology, whereas PPMM operates as a highly sensitive detector of malignant perturbations in glandular lumenal architecture., Methods: By recapitulating algorithmically how a pathologist reviews prostate tissue sections, we created an algorithmic cascade of PPMM and SIVQ algorithms as previously described by Doyle el al. [1] where PPMM identifies the glands with abnormal lumenal architecture, and this area is then screened by SIVQ to identify the epithelium., Results: The performance of this algorithm cascade was assessed qualitatively (with the use of heatmaps) and quantitatively (with the use of ROC curves) and demonstrates greater performance in the identification of malignant prostatic epithelium., Conclusion: This ability to semi-autonomously paint nearly all the malignant epithelium of prostate cancer has immediate applications to future prostate cancer CAD development as a validated ground truth generator. In addition, such an approach has potential applications as a pre-screening/quality assurance tool.

Objective: In the past decade molecular diagnostics has changed the clinical management of lung adenocarcinoma patients. Molecular diagnostics, however, is largely dependent on the quantity and quality of the tumor DNA that is retrieved from the tissue or cytology samples. Frequently, patients are diagnosed on cytology specimens where the tumor cells are scattered within the cell block, making selecting for tumor enrichment difficult. In the past we have used laser capture microdissection (LCM) to select for pure populations of tumor cells to increase the sensitivity of molecular assays. This study explores several methods for semiautomated computer-guided LCM., Study Design: Hematoxylin and eosin- or TTF-1-immunostained slides from a pleural effusion cell block with metastatic lung adenocarcinoma were used for LCM with either AutoScan or a recently described pattern-matching algorithm, spatially invariant vector quantization (SIVQ), to define morphologic predicates (vectors) to select cells of interest., Results: We retrieved pure populations of tumor cells using both algorithm-guided LCM approaches with slight variations in cellular retrievals. Both methods were semiautomated, requiring minimum technical supervision., Conclusion: In this study we demonstrate the first semiautomated, computer-guided LCM of a cytology specimen using SIVQ and AutoScan, a first step towards the long-term goal of integrating LCM into the clinical cytology-molecular workflow., (Copyright © 2012 S. Karger AG, Basel.)

The integration of pathology with molecular biology is vital if we are to enhance the translational value of cancer research. Pathology represents a bridge between medicine and basic biology, it remains the gold standard for cancer diagnosis, and it plays an important role in discovery studies. In the past, pathology and cancer research were closely associated; however, the molecular biology revolution has shifted the focus of investigators toward the molecular alterations of tumors. The reductionist approach taken in molecular studies is producing great insight into the inner workings of neoplasia, but it can also minimize the importance of histopathology and of understanding the disease as a whole. In turn, pathologists can underestimate the role of molecular studies in developing new ancillary techniques for clinical diagnosis. A multidisciplinary approach that integrates pathology and molecular biology within a translational research system is needed. This process will require overcoming cultural barriers and can be achieved through education, a more effective incorporation of pathology into biological research, and conversely an integration of biological research into the pathology laboratory., (Copyright © 2011 WILEY Periodicals, Inc.)

Measurement of mRNA levels across tissue samples facilitates an understanding of how genes function and what their roles are in disease. Quantifying low-abundance mRNA requires a workflow that preserves spatial information, isolates RNA, and performs reverse-transcriptase quantitative polymerase chain reaction (RT-qPCR). This is complex because these steps are typically performed in three separate platforms. In the present study, we describe two-dimensional RT-qPCR (2D-RT-qPCR), a method that quantifies RNA across tissues sections in a single integrated platform. The method uses the grid format of a multi-well plate to macrodissect tissue sections and preserve the spatial location of the RNA; this also eliminates the need for physical homogenization of the tissue. A new lysis and nucleic acid purification protocol is performed in the same multi-well plate, followed by RT-qPCR. The feasibility 2D-RT-qPCR was demonstrated on a variety of tissue types. Potential applications of the technology as a high-throughput tissue analysis platform are discussed.

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.

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.

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.

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.

Current technologies for measuring protein expression across a tissue section are based on MS or in situ detection such as immunohistochemistry. However, due to the inherent molecular complexity of tissue samples and the large dynamic range of protein expression in cells, current approaches are often unable to measure moderate- and low-abundant proteins. In addition, they do not provide information on the physico-chemical properties of the proteins studied. To address these problems, we are developing a new pre-analytic methodology termed layered electrophoretic transfer (LET) that selectively separates and processes proteins from an intact tissue section without compromising important two-dimensional histological information. LET offers two potential advantages over standard techniques: (i) A reduced complexity of the tissue proteome for subsequent analysis; (ii) An opportunity to assess the biochemical status of proteins as they exist in situ. As an initial proof-of-concept, we demonstrate here that the protein content from a mixture of molecular weight standards, human tissue lysates, and tissue sections can be successfully transferred and separated using LET, and further demonstrate that the method can be coupled with immunoblotting or MS for downstream measurements. LET technology represents a new pre-analytic tool for interrogating the proteome in tissue sections while preserving valuable spatial information., (Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Introduction: The increasing availability of whole slide imaging (WSI) data sets (digital slides) from glass slides offers new opportunities for the development of computer-aided diagnostic (CAD) algorithms. With the all-digital pathology workflow that these data sets will enable in the near future, literally millions of digital slides will be generated and stored. Consequently, the field in general and pathologists, specifically, will need tools to help extract actionable information from this new and vast collective repository., Methods: To address this limitation, we designed and implemented a tool (dCORE) to enable the systematic capture of image tiles with constrained size and resolution that contain desired histopathologic features., Results: In this communication, we describe a user-friendly tool that will enable pathologists to mine digital slides archives to create image microarrays (IMAs). IMAs are to digital slides as tissue microarrays (TMAs) are to cell blocks. Thus, a single digital slide could be transformed into an array of hundreds to thousands of high quality digital images, with each containing key diagnostic morphologies and appropriate controls. Current manual digital image cut-and-paste methods that allow for the creation of a grid of images (such as an IMA) of matching resolutions are tedious., Conclusion: The ability to create IMAs representing hundreds to thousands of vetted morphologic features has numerous applications in education, proficiency testing, consensus case review, and research. Lastly, in a manner analogous to the way conventional TMA technology has significantly accelerated in situ studies of tissue specimens use of IMAs has similar potential to significantly accelerate CAD algorithm development.

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.

Squamous cell carcinoma (SCC) is an epithelial malignancy involving many anatomical sites and is the most common cancer capable of metastatic spread. Development of early diagnosis methods and novel therapeutics are important for prevention and mortality reduction. In this effort, numerous molecular alterations have been described in SCCs. SCCs share many phenotypic and molecular characteristics, but they have not been extensively compared. This article reviews SCC as a disease, including: epidemiology, pathology, risk factors, molecular characteristics, prognostic markers, targeted therapy, and a new approach to studying SCCs. Through this comparison, several themes are apparent. For example, HPV infection is a common risk factor among the four major SCCs (NMSC, HNSC, ESCC, and NSCLC) and molecular abnormalities in cell-cycle regulation and signal transduction predominate. These data reveal that the molecular insights, new markers, and drug targets discovered in individual SCCs may shed light on this type of cancer as a whole.

The tumor microenvironment is comprised of multiple cell types arranged in a three-dimensional structure. Interactions amongst the various cell components play an important role in neoplasia, including the inflammatory reaction that occurs as part of the host response. In this study, the regional lymphocyte subpopulations and cytokine profiles associated with prostate cancer were examined using a quantitative imaging approach and expression microarray analysis. Lymphocytes were measured in four different epithelial phenotypes in prostate cancer specimens: carcinoma; prostatic intraepithelial neoplasia (PIN); benign prostate hyperplasia (BPH); and normal epithelium. The data indicate that CD8 positive, cytotoxic T lymphocytes are significantly decreased in regions adjacent to hyperplasia and carcinoma as compared to normal epithelium and PIN. In contrast the relative number of CD4 positive and CD20 positive lymphocytes did not change markedly. Parallel mRNA expression array analysis of the normal and tumor microenvironments identified a distinct cytokine profile in cancer, with 24 dysregulated genes in tumor epithelium and nine altered in tumor-associated stroma. Overall, these data indicate that the spatial distribution of CD8 positive, cytotoxic T lymphocytes is dysregulated in human prostate glands that contain cancer, and cytokine profiles are altered at the mRNA level.

Previous studies have identified several dysregulated microRNAs in esophageal squamous cell carcinoma (ESCC); however, to date there are no ex vivo analyses comparing expression levels of these regulatory molecules in esophageal squamous cell tumors versus patient-matched normal epithelium. We describe here a technical strategy to evaluate microRNAs in normal esophageal basal cells (NB), normal esophageal differentiated cells (ND), and tumor cells (T). Laser capture microdissection was used to procure target populations from five cases and 18 ESCC-associated microRNAs were measured by RT-qPCR. Five microRNAs (miR-25, miR-106b, miR-21, miR-203, and miR-145) demonstrated consistent differential expression in at least one of the three comparisons: T vs. NB, T vs. ND, or NB vs. ND. The potential regulatory role of the microRNAs in ESCC was further evaluated by correlating their expression with a matched mRNA dataset, which included the same five cases and cell populations. In conclusion, the present work demonstrates the feasibility of studying microRNA levels in precisely dissected cell populations from clinical samples, and sheds light on the molecular mechanisms associated with ESCC.

Background: Esophageal squamous cell carcinomas (ESCC) are usually asymptomatic and go undetected until they are incurable. Cytological screening is one strategy to detect ESCC at an early stage and has shown promise in previous studies, although improvement in sensitivity and specificity are needed. Proteases modulate cancer progression by facilitating tumor invasion and metastasis. In the current study, matrix metalloproteinases (MMPs) were studied in a search for new early detection markers for ESCC., Methods: Protein expression levels of MMPs were measured using zymography in 24 cases of paired normal esophagus and ESCC, and in the tumor-associated stroma and tumor epithelium in one sample after laser capture microdissection (LCM). MMP-3 and MMP-10 transcripts in both the epithelium and stroma in five cases were further analyzed by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR)., Results: Gelatin zymography showed bands corresponding in size to MMP-2, MMP-3, MMP-9, and MMP-10 enzymes in each of the 24 cancer cases. MMP levels tended to be higher in tumors than paired normal tissue; however, only the 45 kDa band that corresponds to the activated form of MMP-3 and MMP-10 was strongly expressed in all 24 tumors with little or no expression in the paired normal foci. LCM-based analysis showed the 45 kDA band to be present in both the stromal and epithelial components of the tumor microenvironment, and that MMP-3 and MMP-10 mRNA levels were higher in tumors than paired normal tissues for each compartment., Conclusions: Increased levels of MMPs occur in ESCC suggesting their up-regulation is important in esophageal tumorigenesis. The up-regulated gene products have the potential to serve as early detection markers in the clinic.

The article by Roesch-Ely and colleagues in a recent issue of The Journal of Pathology describes the use of proteomic techniques to examine mucosal biopsies in patients with head and neck squamous cell cancer (HNSCC) and in corresponding control samples. The authors were able to determine the anatomical site of origin of the biopsies based on modelling of multiplex protein datasets, and to use the information to analyse field cancerization as a means of predicting tumour recurrence. Although the study included only a relatively small number of cases, and will require future validation in a larger patient cohort, the results point to the potential of proteomics to increase our understanding of cancer biology, and in this instance to offer clinical value.

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.

Handling and processing of clinical specimens during and after surgical resection may significantly skew the molecular data obtained from analysis of those samples. Minimally invasive prostatectomy was used as a model to specifically study effects of surgical ischemia on gene expression in human clinical samples. Normal prostatic urethra cup biopsies were procured from 12 patients at three time points during laparoscopic radical prostatectomy. Homogeneous cells (stroma and epithelium) were microdissected. Transcript analysis of 3 oxygen-dependent, 3 oxygen-independent, and 3 control class genes was performed using quantitative RT-PCR. Data were analyzed by relative quantitation and two-sided t-test. Patient demographic and time covariates were fit by a linear mixed model. VEGF, an oxygen-dependent gene, showed significant expression alterations across three time points in epithelium (p=0.008), but not in stroma (p=0.66). Expression levels of VHL, STAT5B, and CYPA showed significant changes at the p<0.05 level in the stroma only. Effects of age, PSA, prostate size, Gleason score, surgery type, total surgery time, total ischemia time, and estimated blood loss on VEGF expression over time were not significant at the p<0.01 level. Therefore, surgical manipulation and tissue processing methods need to be taken into account when assessing prostatic biomarkers; however, resection does not dramatically alter mRNA profiles in prostate specimens.

The capacity to rapidly and efficiently elucidate a reliable set of disease specific biomarkers is paramount to enable a future of personalized medicine. High throughput screening methods applied to human clinical samples for the discovery of diagnostic, prognostic, and therapeutic targets address this need. Although the ability to analyze either thousands of markers from one sample or one marker from thousands of samples is the current state of high throughput screening, it would be ideal to have the ability to analyze thousands of markers from thousands of samples to expedite the early discovery phase of biomarkers and their validation. This review summarizes the current state of high throughput screening of tissue specimens and discusses its applications. In addition, the rationale, difficulties, strategies, and development of new technologies to address the need for improved high throughput capabilities are discussed.

A novel approach was developed for mapping the location of target DNA in tissue sections. The method combines a high-density, multi-well plate with an innovative single-tube procedure to directly extract, amplify, and detect the DNA in parallel while maintaining the two-dimensional (2D) architecture of the tissue. A 2D map of the gene glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was created from a tissue section and shown to correlate with the spatial area of the sample. It is anticipated that this approach may be easily adapted to assess the status of multiple genes within tissue sections, yielding a molecular map that directly correlates with the histology of the sample. This will provide investigators with a new tool to interrogate the molecular heterogeneity of tissue specimens.