Definition and research guide
This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.
Content available: 4 complete abstracts (785 words), 10 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.
Definition
Techniques using a laser to cut away and harvest a specific cell or cluster of cells from a tissue section while viewing it under the microscope.
Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.
Also known as: Capture Microdissection, Laser; Capture Microdissections, Laser; Laser Capture Microdissections; Microdissection, Laser Capture; Microdissections, Laser Capture.
Where it fits in the MeSH classification
- Broader topics
- Microdissection
Research landscape
PubMed indexes 1,366 records tagged with the MeSH heading “Laser Capture Microdissection” (counts retrieved 2026-11-04). 310 of them (22.7%) were published from 2020 onward, and the busiest period so far is 2010-2019 with 1,062 records.
Reviews account for 61 records (4.5%) and meta-analyses for 1. Randomized controlled trials number 2 (0.1%) as a share of all records on the topic. Randomized trials make up only a small share of this literature, so much of what is known comes from laboratory, observational or descriptive work.
Show the data
| Period | Records |
|---|---|
| through 1999 | 0 |
| 2000-2009 | 2 |
| 2010-2019 | 1,062 |
| 2020 onward | 310 |
Publication-type chart data
| Type | Records | Share |
|---|---|---|
| Reviews | 61 | 4.5% |
| Meta-analyses | 1 | 0.1% |
| Randomized controlled trials | 2 | 0.1% |
Method: PubMed query "Laser Capture Microdissection"[MeSH Terms] with publication-type and date filters, retrieved 2026-11-04.
Reading the evidence in diagnostics and medical technology
A test or device is judged by how well it detects a condition, how often it gives false alarms or misses cases, and whether using it improves outcomes for people. Accuracy depends on who is tested and how common the condition is, so a test that performs well in a specialist hospital can perform differently in the community. Check the reference standard, the population studied, the sensitivity and specificity and whether results were confirmed in a separate group.
Evidence from open-access studies
These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.
| Study / authors | Year | Source label / design | Europe PMC citations | Licence / source |
|---|---|---|---|---|
| Laser capture microscopy coupled with Smart-seq2 for precise spatial transcriptomic profiling | 2016 | Research article Design not recorded in structured metadata | 279 | cc by PMID 27387371 · DOI · PMC4941116 |
| Gene expression profiling of single cells from archival tissue with laser-capture microdissection and Smart-3SEQ | 2019 | Research article Design not recorded in structured metadata | 129 | cc by PMID 31519740 · DOI · PMC6836736 |
| A powerful method for transcriptional profiling of specific cell types in eukaryotes: laser-assisted microdissection and RNA sequencing | 2012 | Research article Design not recorded in structured metadata | 84 | cc by PMID 22291893 · DOI · PMC3266888 |
| Histo-LCM-Hi-C Reveals 3D Chromatin Conformations of Spatially Localized Rare Cells in Tissues at High Resolution | 2026 | Research article Design not recorded in structured metadata | 3 | cc by PMID 41026875 · DOI · PMC13437044 |
Laser capture microscopy coupled with Smart-seq2 for precise spatial transcriptomic profiling [1]
Abstract reading summary — source excerpts
- Opening excerpt
- Laser capture microscopy (LCM) coupled with global transcriptome profiling could enable precise analyses of cell populations without the need for tissue dissociation, but has so far required relatively large numbers of cells.
- Closing excerpt
- Importantly, we demonstrate that LCM-seq can provide biological insight on highly similar neuronal populations, including motor neurons isolated from different levels of the mouse spinal cord, as well as human midbrain dopamine neurons of the substantia nigra compacta and the ventral tegmental area.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (138 words)
Laser capture microscopy (LCM) coupled with global transcriptome profiling could enable precise analyses of cell populations without the need for tissue dissociation, but has so far required relatively large numbers of cells. Here we report a robust and highly efficient strategy for LCM coupled with full-length mRNA-sequencing (LCM-seq) developed for single-cell transcriptomics. Fixed cells are subjected to direct lysis without RNA extraction, which both simplifies the experimental procedures as well as lowers technical noise. We apply LCM-seq on neurons isolated from mouse tissues, human post-mortem tissues, and illustrate its utility down to single captured cells. Importantly, we demonstrate that LCM-seq can provide biological insight on highly similar neuronal populations, including motor neurons isolated from different levels of the mouse spinal cord, as well as human midbrain dopamine neurons of the substantia nigra compacta and the ventral tegmental area.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 27387371 · DOI · PMC4941116
Gene expression profiling of single cells from archival tissue with laser-capture microdissection and Smart-3SEQ [2]
Abstract reading summary — source excerpts
- Opening excerpt
- RNA sequencing (RNA-seq) is a sensitive and accurate method for quantifying gene expression.
- Closing excerpt
- In particular, Smart-3SEQ's compatibility with FFPE tissue unlocks an enormous number of archived clinical samples; combined with LCM it allows unprecedented studies of small cell populations and single cells isolated by their in situ context.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (160 words)
RNA sequencing (RNA-seq) is a sensitive and accurate method for quantifying gene expression. Small samples or those whose RNA is degraded, such as formalin-fixed paraffin-embedded (FFPE) tissue, remain challenging to study with nonspecialized RNA-seq protocols. Here, we present a new method, Smart-3SEQ, that accurately quantifies transcript abundance even with small amounts of total RNA and effectively characterizes small samples extracted by laser-capture microdissection (LCM) from FFPE tissue. We also obtain distinct biological profiles from FFPE single cells, which have been impossible to study with previous RNA-seq protocols, and we use these data to identify possible new macrophage phenotypes associated with the tumor microenvironment. We propose Smart-3SEQ as a highly cost-effective method to enable large gene expression profiling experiments unconstrained by sample size and tissue availability. In particular, Smart-3SEQ's compatibility with FFPE tissue unlocks an enormous number of archived clinical samples; combined with LCM it allows unprecedented studies of small cell populations and single cells isolated by their in situ context.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 31519740 · DOI · PMC6836736
A powerful method for transcriptional profiling of specific cell types in eukaryotes: laser-assisted microdissection and RNA sequencing [3]
Abstract reading summary — source excerpts
- Opening excerpt
- The acquisition of distinct cell fates is central to the development of multicellular organisms and is largely mediated by gene expression patterns specific to individual cells and tissues.
- Closing excerpt
- Finally, we performed a de novo assembly of the transcriptome and show that the method is suitable for studying individual cell types of organisms lacking reference sequence information, demonstrating that this approach can be applied to most eukaryotic organisms.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (252 words)
The acquisition of distinct cell fates is central to the development of multicellular organisms and is largely mediated by gene expression patterns specific to individual cells and tissues. A spatially and temporally resolved analysis of gene expression facilitates the elucidation of transcriptional networks linked to cellular identity and function. We present an approach that allows cell type-specific transcriptional profiling of distinct target cells, which are rare and difficult to access, with unprecedented sensitivity and resolution. We combined laser-assisted microdissection (LAM), linear amplification starting from <1 ng of total RNA, and RNA-sequencing (RNA-Seq). As a model we used the central cell of the Arabidopsis thaliana female gametophyte, one of the female gametes harbored in the reproductive organs of the flower. We estimated the number of expressed genes to be more than twice the number reported previously in a study using LAM and ATH1 microarrays, and identified several classes of genes that were systematically underrepresented in the transcriptome measured with the ATH1 microarray. Among them are many genes that are likely to be important for developmental processes and specific cellular functions. In addition, we identified several intergenic regions, which are likely to be transcribed, and describe a considerable fraction of reads mapping to introns and regions flanking annotated loci, which may represent alternative transcript isoforms. Finally, we performed a de novo assembly of the transcriptome and show that the method is suitable for studying individual cell types of organisms lacking reference sequence information, demonstrating that this approach can be applied to most eukaryotic organisms.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 22291893 · DOI · PMC3266888
Histo-LCM-Hi-C Reveals 3D Chromatin Conformations of Spatially Localized Rare Cells in Tissues at High Resolution [4]
Abstract reading summary — source excerpts
- Opening excerpt
- Understanding chromatin structure is essential to delineate the mechanisms underlying genomic processes.
- Closing excerpt
- We anticipate that this method will prove to be an indispensable technique in the growing repertoire of methodologies for characterizing the genomic properties of cells within their native environment.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (235 words)
Understanding chromatin structure is essential to delineate the mechanisms underlying genomic processes. However, while methods to obtain such information from cells in vitro are widely available, there is presently a significant lack of techniques that can acquire these data from cells in tissue. Such a capability is critical to determine the dependence of the local tissue environment on cell function. Further, this ability is particularly necessary for cells that constitute a significant minority of the total tissue population, as they are often obscured in data dominated by more abundant cell types. Here, we developed a high-throughput chromosome conformation capture (Hi-C)-based method, Histological laser capture microdissection Hi-C (Histo-LCM-Hi-C), to enable the characterization of chromatin architecture of phenotype-defined, spatially localized cells within intact tissue sections from as few as ∼ 300 cells. We demonstrated the effectiveness of this approach by generating the first 3D Hi-C map of liver-resident macrophages, the Kupffer cells (KCs), a minor cell population in the normal liver. As expected, owing to their relative rarity, these KC maps were significantly different from those obtained from the whole liver, revealing distant contacts between putative enhancers and genes involved in key KC functions, as well as significant differences from those of in vitro induced bone marrow-derived macrophages. We anticipate that this method will prove to be an indispensable technique in the growing repertoire of methodologies for characterizing the genomic properties of cells within their native environment.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 41026875 · DOI · PMC13437044
Key reviews and meta-analyses
The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.
- Research article Laser capture microdissection: Big data from small samples [5]
- Research article Laser-assisted microdissection in translational research: theory, technical considerations, and future applications [6]
- Research article Laser capture microdissection: techniques and applications in liver diseases [7]
- Research article Laser capture microdissection for the investigative pathologist [8]
- Research article Advances in Spatial Multi-Omics: A Review of Multi-Modal Mass Spectrometry Imaging and Laser Capture Microdissection-LCMS Integration [9]
- Research article Laser Capture Microdissection in the Spatial Analysis of Epigenetic Modifications in Skin: A Comprehensive Review [10]
References
- Nichterwitz S, Chen G, Aguila Benitez J, Yilmaz M, Storvall H, Cao M, et al.. Laser capture microscopy coupled with Smart-seq2 for precise spatial transcriptomic profiling. . 2016. PMID 27387371 · DOI · PMC4941116
- Foley JW, Zhu C, Jolivet P, Zhu SX, Lu P, Meaney MJ, et al.. Gene expression profiling of single cells from archival tissue with laser-capture microdissection and Smart-3SEQ. . 2019. PMID 31519740 · DOI · PMC6836736
- Schmid MW, Schmidt A, Klostermeier UC, Barann M, Rosenstiel P, Grossniklaus U. A powerful method for transcriptional profiling of specific cell types in eukaryotes: laser-assisted microdissection and RNA sequencing. . 2012. PMID 22291893 · DOI · PMC3266888
- Liu Y, Chen M, Liu X, Xu Z, Li X, Guo Y, et al.. Histo-LCM-Hi-C Reveals 3D Chromatin Conformations of Spatially Localized Rare Cells in Tissues at High Resolution. . 2026. PMID 41026875 · DOI · PMC13437044
- Datta S, Malhotra L, Dickerson R, Chaffee S, Sen CK, Roy S. Laser capture microdissection: Big data from small samples. Histol Histopathol. 2015. PMID 25892148 · DOI · PMC4665617
- Cheng L, Zhang S, MacLennan GT, Williamson SR, Davidson DD, Wang M, et al.. Laser-assisted microdissection in translational research: theory, technical considerations, and future applications. Appl Immunohistochem Mol Morphol. 2013. PMID 22495368 · DOI
- Aguilar-Bravo B, Sancho-Bru P. Laser capture microdissection: techniques and applications in liver diseases. Hepatol Int. 2019. PMID 30600479 · DOI
- Liu H, McDowell TL, Hanson NE, Tang X, Fujimoto J, Rodriguez-Canales J. Laser capture microdissection for the investigative pathologist. Vet Pathol. 2014. PMID 24227008 · DOI
- Lukowski JK, Cho BK, Calderon AZ, Dianati B, Stumpo K, Snyder S, et al.. Advances in Spatial Multi-Omics: A Review of Multi-Modal Mass Spectrometry Imaging and Laser Capture Microdissection-LCMS Integration. Proteomics. 2025. PMID 40351101 · DOI
- Bhamidipati T, Sinha M, Sen CK, Singh K. Laser Capture Microdissection in the Spatial Analysis of Epigenetic Modifications in Skin: A Comprehensive Review. Oxid Med Cell Longev. 2022. PMID 35186184 · DOI · PMC8850045
About this article
- Sources
- NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
- Verification
- Every reference was resolved against PubMed on 2026-11-04; title, year and DOI matched.
- Review state
- automated source verified; no human expert review has been recorded yet.
- Version
- 1, last updated 2026-11-04.
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Evidence strength
EvidenceHelix's computed view of the study designs behind this topic: how common meta-analyses, randomized trials and reviews are, how recent the literature is, and a plain-language reading. It describes the design mix of the literature. It is not a quality appraisal of any study, and it is not medical advice.