ArticlePloS one2016
High-Throughput Microdissection for Next-Generation Sequencing.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- A Comparison of Tools That Identify Tumor Cells by Inferring Copy Number Variations from Single-Cell Experiments in Pancreatic Ductal Adenocarcinoma.Biomedicines · 2024Article
- Expression Microdissection for the Analysis of miRNA in a Single-Cell Type.Laboratory investigation; a journal of technical methods and pathology · 2023Article
- Effect of Antigen Retrieval on Genomic DNA From Immunodissected Samples.The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society · 2022Article
- Bile acid-activated macrophages promote biliary epithelial cell proliferation through integrin αvβ6 upregulation following liver injury.The Journal of clinical investigation · 2021Article
- xMD-miRNA-seq to generate near in vivo miRNA expression estimates in colon epithelial cells.Scientific reports · 2018Article
- Cell-type specific expression of oncogenic and tumor suppressive microRNAs in the human prostate and prostate cancer.Scientific reports · 2018Article
- Computer-Aided Laser Dissection: A Microdissection Workflow Leveraging Image Analysis Tools.Journal of pathology informatics · 2018Article
- High Throughput Sequencing: An Overview of Sequencing Chemistry.Indian journal of microbiology · 2016Review
- Tumor Heterogeneity, Single-Cell Sequencing, and Drug Resistance.Pharmaceuticals (Basel, Switzerland) · 2016Review
- Necessity of Microdissecting Different Tumor Components in Pulmonary Tumor Pyrosequencing.BioMed research international · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.