ReviewDer Pathologe2020
[RNA in situ hybridization: technology, potential, and fields of application].
Review in Der Pathologe, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
4 citing papers in PubMed, 15 citations in OpenAlex.
- Measuring the Senescence-Associated Secretory Phenotype.Biomedicines · 2025Review
- Spatio-temporal expression patterns of glycine-rich beta proteins and cysteine-rich beta proteins in setae development of Gekko japonicus.BMC genomics · 2024Article
- European Society of Toxicologic Pathology (Pathology 2.0 Molecular Pathology Special Interest Group): Review of In Situ Hybridization Techniques for Drug Research and Development.Toxicologic pathology · 2023Review
- Non-Specific Binding, a Limitation of the Immunofluorescence Method to Study Macrophages In Situ.Genes · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Significant improvements in the technology of RNA in situ hybridization (RNA-ISH) in the past five decades have opened up novel fields of its application as a valuable and an attractive adjunct to the portfolio of pathologist's daily routine diagnostic practice.In contrast to the former methodology, the current bDNA-based technology is not only easier to handle but also considerably more sensitive, enabling single-target molecule detection in formalin-fixed and paraffin-embedded tissue specimens without significant effort by both the lab and the evaluating pathologist, as assays can be run on standard automated staining devices and evaluated by light microscopy. Compared to molecular methods like RT-PCR and whole-genome analysis, RNA-ISH maintains tissue integrity thus offering the invaluable advantage of localization of target cells especially in relation to secreted proteins and expression of the target sequence in multiple cell types. The first clinical trials implementing RNA-ISH for patient stratification and selection are in progress and already led to the first drug approvals based on its use as a CDx test.In addition to its role as a complementary method for the establishment of novel IHC procedures or as an addition or replacement to IHC in the standard routine portfolio, RNA-ISH has gained special importance for its capacity to detect noncoding RNA species or mutation or splice variants, where no alternative procedures are available. This more complex application requires development of standardized procedures and involvement of the pathologist during assay establishment and for routine specimen evaluation.The present article reviews the development of RNA-ISH from its early uses to its current applications in research and diagnostics based on the authors' considerable experience of applying it as tool in a biopharmaceutical research organization.
Indexed as
Identifiers
What OpenQuestion holds
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.