ArticleScientific reports2019
Assessing the reliability of gene expression measurements in very-low-numbers of human monocyte-derived macrophages.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed.
- Review
- Inflammatory Breast Cancer: The Secretome of HCMVFrontiers in oncology · 2022Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tumor-derived primary cells are essential for in vitro and in vivo studies of tumor biology. The scarcity of this cellular material limits the feasibility of experiments or analyses and hence hinders basic and clinical research progress. We set out to determine the minimum number of cells that can be analyzed with standard laboratory equipment and that leads to reliable results, unbiased by cell number. A proof-of-principle study was conducted with primary human monocyte-derived macrophages, seeded in decreasing number and constant cell density. Gene expression of cells stimulated to acquire opposite inflammatory states was analyzed by quantitative PCR. Statistical analysis indicated the lack of significant difference in the expression profile of cells cultured at the highest (100,000 cells) and lowest numbers (3,610 cells) tested. Gene Ontology, pathway enrichment and network analysis confirmed the reliability of the data obtained with the lowest cell number. This statistical and computational analysis of gene expression profiles indicates that low cell number analysis is as dependable and informative as the analysis of a larger cell number. Our work demonstrates that it is possible to employ samples with a scarce number of cells in experimental studies and encourages the application of this approach on other cell types.
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