Among various methods now available to isolate distinct cell populations or even single cells for DNA/RNA and proteomic analysis, laser capture microdissection (LCM) offers a unique opportunity to study cells in their topological contexts. This chapter focuses on the preparation of LCM membrane slides, tissue staining and laser microdissection of cells of interest from frozen or formalin-fixed, paraffin-embedded glioblastoma tissue.

We evaluated the importance of tumor cell selection for generating gene signatures in non-small cell lung cancer. Tumor and nontumor tissue from macroscopically dissected (Macro) surgical specimens (31 pairs from 32 subjects) was homogenized, extracted, amplified, and hybridized to microarrays. Adjacent scout sections were histologically mapped; sets of approximately 1000 tumor cells and nontumor cells (alveolar or bronchial) were procured by laser capture microdissection (LCM). Within histological strata, LCM and Macro specimens exhibited approximately 67% to 80% nonoverlap in differentially expressed (DE) genes. In a representative subset, LCM uniquely identified 300 DE genes in tumor versus nontumor specimens, largely attributable to cell selection; 382 DE genes were common to Macro, Macro with preamplification, and LCM platforms. RT-qPCR validation in a 33-gene subset was confirmatory (ρ = 0.789 to 0.964, P = 0.0013 to 0.0028). Pathway analysis of LCM data suggested alterations in known cancer pathways (cell growth, death, movement, cycle, and signaling components), among others (eg, immune, inflammatory). A unique nine-gene LCM signature had higher tumor-nontumor discriminatory accuracy (100%) than the corresponding Macro signature (87%). Comparison with Cancer Genome Atlas data sets (based on homogenized Macro tissue) revealed both substantial overlap and important differences from LCM specimen results. Thus, cell selection via LCM enhances expression profiling precision, and confirms both known and under-appreciated lung cancer genes and pathways.

Background and Objectives: The presence of endometrial-like tissue outside the uterine cavity is a key feature of endometriosis. Although endometriotic lesions appear to be histologically quite similar to the eutopic endometrium, detailed studies comparing both tissues are required because their inner and surrounding cellular arrangement is distinct. Thus, comparison between tissues might require methods, such as laser capture microdissection (LCM), that allow for precise selection of an area and its specific cell populations. However, it is known that the efficient use of LCM depends on the type of studied tissue and on the choice of an adequate protocol. Recent studies have reported the use of LCM in endometriosis studies. The main objective of the present study is to establish a standardized protocol to obtain good-quality microdissected material from eutopic or ectopic endometrium. Materials and Methods: The main methodological steps involved in the processing of the lesion samples for LCM were standardized to yield material of good quality to be further used in molecular techniques. Results: We obtained satisfactory results regarding the yields and integrity of RNA and protein obtained from LCM-processed endometriosis tissues. Conclusion: LCM can provide more precise analysis of endometriosis biopsies, provided that key steps of the methodology are followed.

Glioblastomas are heterogeneous tumors composed of a necrotic and tumor core and an invasive periphery.

Previous studies of brain and peripheral tissues in schizophrenia patients have indicated impaired energy supply to the brain. A number of studies have also demonstrated dysfunction of the microvasculature in schizophrenia patients. Together these findings are consistent with a hypothesis of blood-brain barrier dysfunction in schizophrenia. In this study, we have investigated the cerebral vascular endothelium of schizophrenia patients at the level of transcriptomics.

The acquisition of reliable tissue-specific RNA sequencing data from human skin biopsy represents a major advance in research. However, the complexity of the process of isolation of specific layers from fresh-frozen human specimen by laser capture microdissection, the abundant presence of skin nucleases and RNA instability remain relevant methodological challenges. We developed and optimized a protocol to extract RNA from layers of human skin biopsies and to provide satisfactory quality and amount of mRNA sequencing data.

Laser capture microdissection (LCM) enables precise dissection and collection of individual cell types from complex tissues. When applied to plant cells, and especially to woody tissues, LCM requires extensive optimization to overcome such factors as rigid cell walls, large central vacuoles, intercellular spaces, and technical issues with thickness and flatness of the sections. Here we present an optimized protocol for the laser-assisted microdissection of developing xylem from mature trees: a gymnosperm (Norway spruce, Picea abies) and an angiosperm (aspen, Populus tremula) tree. Different cell types of spruce and aspen wood (i.e., ray cells, tracheary elements, and fibers) were successfully microdissected from tangential, cross and radial cryosections of the current year's growth ring. Two approaches were applied to achieve satisfactory flatness and anatomical integrity of the spruce and aspen specimens. The commonly used membrane slides were ineffective as a mounting surface for the wood cryosections. Instead, in the present protocol we use glass slides, and introduce a glass slide sandwich assembly for the preparation of aspen sections. To ascertain that not only the anatomical integrity of the plant tissue, but also the molecular features were not compromised during the whole LCM procedure, good quality total RNA could be extracted from the microdissected cells. This showed the efficiency of the protocol and established that our methodology can be integrated in transcriptome analyses to elucidate cell-specific molecular events regulating wood formation in trees.

Cell-specific molecular investigations of the human brain are essential for understanding the neurobiology of diseases, but are hindered by postmortem conditions and technical challenges. To address these issues we developed a multi-label fluorescence in situ hybridization protocol and a novel optical filter device to identify cell types and control for tissue autofluorescence. We show that these methods can be used with laser-capture microdissection for human brain tissue cell-specific molecular analysis.

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

Laser capture microdissection (LCM) coupled to label-free quantitative mass spectrometry is a viable strategy to identify biomarkers from infected tissues. In this study, LCM was employed to take a "snapshot" of proteins produced in vivo during Coccidiodies spp. infection in human lungs. Proteomic analysis of LCM lung sections revealed hundreds of hosts and Coccidioidal proteins. Twenty-seven highly abundant Coccidioides spp. proteins were identified which do not share significant sequence orthology with human proteins. Three of the 27 Coccidioidal proteins are also potential Coccidoides-specific biomarkers, as they also do not share sequence homology to any other pathogenic fungus or microbe. Gene ontology analysis of the 27 biomarker candidate proteins revealed enriched hydrolase activity and increased purine and carbohydrate metabolism functions. Finally, we provide proteomic evidence that all 27 biomarker candidates are produced by the fungus when grown in vitro in a media- and growth-phase dependent manner.

Cell⁻cell communication is vital to multicellular organisms, and distinct types of cellular protrusions play critical roles during development, cell signaling, and the spreading of pathogens and cancer. The differences in the structure and protein composition of these different types of protrusions and their specific functions have not been elucidated due to the lack of a method for their specific isolation and analysis. In this paper, we described, for the first time, a method to specifically isolate distinct protrusion subtypes, based on their morphological structures or fluorescent markers, using laser capture microdissection (LCM). Combined with a unique fixation and protein extraction protocol, we pushed the limits of microproteomics and demonstrate that proteins from LCM-isolated protrusions can successfully and reproducibly be identified by mass spectrometry using ultra-high field Orbitrap technologies. Our method confirmed that different types of protrusions have distinct proteomes and it promises to advance the characterization and the understanding of these unique structures to shed light on their possible role in health and disease.

The etiology of Type 1 Diabetes (T1D) remains elusive. Enzymatically isolated and cultured (EIC) islets cannot fully reflect the natural protein composition and disease process of in vivo islets, because of the stress from isolation procedures. In order to study islet protein composition in conditions close to the natural environment, we performed proteomic analysis of EIC islets, and laser capture microdissected (LCM) human islets and acinar tissue from fresh-frozen pancreas sections of three cadaveric donors. 1104 and 706 proteins were identified from 6 islets equivalents (IEQ) of LCM islets and acinar tissue, respectively. The proteomic profiles of LCM islets were reproducible within and among cadaveric donors. The endocrine hormones were only detected in LCM islets, whereas catalytic enzymes were significantly enriched in acinar tissue. Furthermore, high overlap (984 proteins) and similar function distribution were found between LCM and EIC islets proteomes, except that EIC islets had more acinar contaminants and stress-related signal transducer activity proteins. The comparison among LCM islets, LCM acinar tissue and EIC islets proteomes indicates that LCM combined with proteomic methods enables accurate and unbiased profiling of islet proteome from frozen pancreata. This paves the way for proteomic studies on human islets during the progression of T1D.

Gene expression data are most useful if they can be associated with specific cell types. This is particularly so in an organ such as the brain, where many different cell types lie in close proximity to each other. We used zebra finches (Taeniopygia guttata), fluorescent tracers and laser capture microdissection (LCM) to collect projection neurons and their RNAs from two interspersed populations from the same animal. RNA amplified from each cell class was reverse transcribed, fluorescently labeled, and hybridized to cDNA microarrays of genes expressed in the zebra finch brain. We applied strict fold-expression criteria, supplemented by statistical analysis, to single out genes that showed the most extreme and consistent differential expression between the two cell classes. Confirmation of the true expression pattern of these genes was made by in situ hybridization and Taqman quantitative PCR (qPCR). High quality RNA was obtained, too, from backfilled neurons birth-dated with bromodeoxyuridine (BrdU). We also quantified changes in the levels of three genes after singing behavior using qPCR. Thus, we have brought together a combination of techniques allowing for the molecular profiling of intermingled populations of projection neurons of known connectivity, age and experience, which should constitute a powerful tool for CNS research.

Identifying neuronal molecular markers with restricted patterns of expression is a crucial step in dissecting the numerous pathways and functions of the brain. While the dorsomedial nucleus of the hypothalamus (DMH) has been implicated in a host of physiological processes, current functional studies have been limited by the lack of molecular markers specific for DMH. Identification of such markers would facilitate the development of mouse models with DMH-specific genetic manipulations. Here we used a combination of laser-capture microdissection (LCM) and gene expression profiling to identify genes that are highly expressed within the DMH relative to adjacent hypothalamic regions. Six of the most highly expressed of these genes, Gpr50, 4930511J11Rik, Pcsk5, Grp, Sulf1, and Rorβ, were further characterized by real-time polymerase chain reaction (PCR) analysis and in situ hybridization histochemistry. The genes identified in this article will provide the basis for future gene-targeted approaches for studying DMH function.

We describe a pipeline for optimized and streamlined multiplexed immunofluorescence-guided laser capture microdissection allowing the harvest of individual cells based on their phenotype and tissue localization for transcriptomic analysis with next-generation RNA sequencing. Here, we analyze transcriptomes of CD3+ T cells, CD14+ monocytes/macrophages, and melanoma cells in non-dissociated metastatic melanoma tissue. While this protocol is described for melanoma tissues, we successfully applied it to human tonsil, skin, and breast cancer tissues as well as mouse lung tissues. For complete details on the use and execution of this protocol, please refer to Martinek et al. (2022).

Mandibular condylar cartilage (MCC) is a multizonal heterogeneous fibrocartilage consisting of fibrous (FZ), proliferative (PZ), mature (MZ), and hypertrophic (HZ) zones. Gross sampling of the whole tissue may conceal some important information and compromise the validity of the molecular analysis. Laser capture microdissection (LCM) technology allows isolating zonal (homogenous) cell populations and consequently generating more accurate molecular and genetic data, but the challenges during tissue preparation and microdissection procedures are to obtain acceptable tissue section morphology that allows histological identification of the desirable cell type and to minimize RNA degradation. Therefore, our aim is to optimize an LCM protocol for isolating four homogenous zone-specific cell populations from their respective MCC zones while preserving the quality of RNA recovered. MCC and FCC (femoral condylar cartilage) specimens were harvested from 5-week-old Sprague-Dawley male rats. Formalin-fixed and frozen unfixed tissue sections were prepared and compared histologically. Additional specimens were microdissected to prepare LCM samples from FCC and each MCC zone individually. Then, to evaluate LCM-RNA integrity, 3'/m ratios of glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and beta-actin (β-Actin) using quantitative reverse transcription-polymerase chain reaction (qRT-PCR) were calculated. Both fixed and unfixed tissue sections allowed reliable identification of MCC zones. The improved morphology of the frozen sections of our protocol has extended the range of cell types to be isolated. Under the empirically set LCM parameters, four homogeneous cell populations were efficiently isolated from their respective zones. The 3'/m ratio means of GAPDH and β-Actin ranged between 1.11-1.56 and 1.41-2.12, respectively. These values are in line with the reported quality control requirements. The present study shows that the optimized LCM protocol could allow isolation of four homogenous zone-specific cell populations from MCC, meanwhile preserving RNA integrity to meet the high quality requirements for subsequent molecular analyses. Thereby, accurate molecular and genetic data could be generated.

The cellular heterogeneity of brain tissue presents a challenge to gene expression profiling of specific neuronal cell types. The present study employed a fluorescent neural tracer to specifically label midbrain dopamine neurons and non-dopamine cortical neurons. The labeled cells were then used to visually guide harvesting of the cells by laser capture microdissection (LCM). RNA extracted from the two populations of harvested cells was then amplified, labeled and co-hybridized to high density cDNA microarrays for two-color differential expression profiling. Many of the genes most highly enriched in the dopamine neurons were found to be genes previously known to define the dopamine neuronal phenotype. However, results from the microarray were only partially validated by quantitative RT-PCR analysis. The results indicate that LCM harvesting of specific neuronal phenotypes can be effectively guided in a complex cellular environment by specific pre-labeling of the target cell populations and underlie the importance of independent validation of microarray results.

Invadosomes are F-actin-based structures involved in extracellular matrix degradation, cell invasion, and metastasis formation. Analyzing their proteome is crucial to decipher their molecular composition, to understand their mechanisms, and to find specific elements to target them. However, the specific analysis of invadosomes is challenging, because it is difficult to maintain their integrity during isolation. In addition, classical purification methods often suffer from contaminations, which may impair data validation. To ensure the specific identification of invadosome components, we here develop a method that combines laser microdissection and mass spectrometry, enabling the analysis of subcellular structures in their native state based on low amounts of input material. Using this combinatorial method, we show that invadosomes contain specific components of the translational machinery, in addition to known marker proteins. Moreover, functional validation reveals that protein translation activity is an inherent property of invadosomes, which is required to maintain invadosome structure and activity.

The functioning of tissues is fundamentally dependent upon not only the phenotypes of the constituent cells but also their spatial organization in the tissue, as local interactions precipitate intra-cellular events that often lead to changes in expression. However, our understanding of these processes in tissues, whether healthy or diseased, is limited at present owing to the difficulty in acquiring comprehensive transcriptional programs of spatially- and phenotypically-defined cells in situ. Here we present a robust method based on immunofluorescence-guided laser capture microdissection (immuno-LCM-RNAseq) to acquire finely resolved transcriptional programs with as few as tens of cells from snap-frozen or RNAlater-treated clinical tissues sufficient to resolve even isoforms. The protocol is optimized to protect the RNA with a small molecule inhibitor, the ribonucleoside vanadyl complex (RVC), which thereby enables the typical time-consuming immunostaining and laser capture steps of this procedure during which RNA is usually severely degraded in existing approaches. The efficacy of this approach is exemplified by the characterization of differentially expressed genes between the mouse small intestine lacteal cells at the tip versus the main capillary body, including those that function in sensing and responding to local environmental cues to stimulate intra-cellular signalling. With the extensive repertoire of specific antibodies that are presently available, our method provides an unprecedented capability for the analysis of transcriptional networks and signalling pathways during development, pathogenesis, and aging of specific cell types within native tissues.

We developed a highly efficient, ultrashort immunohistochemistry-laser capture microdissection (IHC-LMD) protocol, which allows microdissection of up to 250 single cardiomyocytes. Before LMD, murine hearts are excised, snap-frozen, and cryosectioned. RNA isolated from LMD material is of high RNA quality, making it usable for gene expression analysis and RNA sequencing. Challenges and limitations of this protocol include visualization of the immunostaining and nuclei DAPI dye on the PEN slides, and timing and speed to limit RNA degradation as much as possible.