Evidence map›Paper›PMID 35312280›Full record

ArticleACS sensors2022

Single-Molecule Sensor for High-Confidence Detection of miRNA.

Kalani M Wijesinghe, Mazhar A Kanak, J Chuck Harrell, Soma Dhakal

Abstract read
In one paragraph

Article in ACS sensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. microRNA Detection via Nanostructured Biochips for Early Cancer Diagnostics.International journal of molecular sciences · 2023
    Review
  11. Review
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Kalani M WijesingheDepartment of Chemistry, Virginia Commonwealth University, Richmond, Virginia 23284, United States.
Mazhar A KanakDivision of Transplant Surgery, Department of Surgery, Virginia Commonwealth University School of Medicine, Richmond, Virginia 23298, United States.
J Chuck HarrellDepartment of Pathology, School of Medicine, Virginia Commonwealth University, Richmond, Virginia 23298, United States.
Soma DhakalDepartment of Chemistry, Virginia Commonwealth University, Richmond, Virginia 23284, United States.ORCID 0000-0002-3734-139X

Funding

Research Supplement to Promote Diversity in Health Related ResearchUL1TR002649 · NCATS · VIRGINIA COMMONWEALTH UNIVERSITY · PI MOELLER, FREDERICK GERARD · 2018 to 2022
$19.1M
Circumventing acquired carboplatin resistance in triple-negative breast cancersR01CA246182 · NCI · VIRGINIA COMMONWEALTH UNIVERSITY · PI HARRELL, JOSHUA (CHUCK) · 2020 to 2024
$1.9M
NCATS NIH HHS UL1 TR002649NCI NIH HHS R01 CA246182
6 · The paper itself

Abstract

MicroRNAs (miRNAs) play a crucial role in regulating gene expression and have been linked to many diseases. Therefore, sensitive and accurate detection of disease-linked miRNAs is vital to the emerging revolution in early diagnosis of diseases. While the detection of miRNAs is a challenge due to their intrinsic properties such as small size, high sequence similarity among miRNAs and low abundance in biological fluids, the majority of miRNA-detection strategies involve either target/signal amplification or involve complex sensing designs. In this study, we have developed and tested a DNA-based fluorescence resonance energy transfer (FRET) sensor that enables ultrasensitive detection of a miRNA biomarker (miRNA-342-3p) expressed by triple-negative breast cancer (TNBC) cells. The sensor shows a relatively low FRET state in the absence of a target but it undergoes continuous FRET transitions between low- and high-FRET states in the presence of the target. The sensor is highly specific, has a detection limit down to low femtomolar (fM) without having to amplify the target, and has a large dynamic range (3 orders of magnitude) extending to 300 000 fM. Using this strategy, we demonstrated that the sensor allows detection of miRNA-342-3p in the miRNA-extracts from cancer cell lines and TNBC patient-derived xenografts. Given the simple-to-design hybridization-based detection, the sensing platform developed here can be used to detect a wide range of miRNAs enabling early diagnosis and screening of other genetic disorders.

Indexed as

MicroRNAsTriple Negative Breast NeoplasmsDNA ProbesFluorescence Resonance Energy TransferHumansNucleic Acid HybridizationDNA ProbesMicroRNAsMIRN342 microRNA, humanbiomarkersfluorescence resonance energy transfer (FRET)high-confidencemiRNAsingle-moleculetriple negative breast cancer (TNBC)

Identifiers

PMID35312280
PMCPMC9112324

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Registered trials

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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.