Effect of Antigen Retrieval on Genomic DNA From Immunodissected Samples.

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.

Microdissection Methods Utilizing Single-Cell Subtype Analysis and the Impact on Precision Medicine.

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.

Author Correction: The evolutionary history of lethal metastatic prostate cancer.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Molecular Signature and Mechanisms of Hepatitis D Virus-Associated Hepatocellular Carcinoma.

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: G2-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.

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.

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.

Laser Microdissection.

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.

The evolutionary history of lethal metastatic prostate cancer.

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.

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.

Menin immunoreactivity in secretory granules of human pancreatic islet cells.

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.

Multiplex quantitative measurement of mRNAs from fixed tissue microarray sections.

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.

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.

Validation of esophageal squamous cell carcinoma candidate genes from high-throughput transcriptomic studies.

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.

Analysis of transcription factor mRNAs in identified oxytocin and vasopressin magnocellular neurons isolated by laser capture microdissection.

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.

Measuring collective cell movement and extracellular matrix interactions using magnetic resonance imaging.

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.

Proteomic analysis of frozen tissue samples using laser capture microdissection.

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.

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.

Three-dimensional mRNA measurements reveal minimal regional heterogeneity in esophageal squamous cell carcinoma.

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.

Semiautomated laser capture microdissection of lung adenocarcinoma cytology samples.

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.

Integration of architectural and cytologic driven image algorithms for prostate adenocarcinoma identification.

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.