Evidence map›Paper›PMID 39754770›Full record

ArticleMicroRNA (Shariqah, United Arab Emirates)2025

A Robust NSCLC Biomarker- miR-7-5p: Its

Chandrajeet Dhara, Anindita Dhara, Saumyatika Gantayat

Abstract read
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In one paragraph

Article in MicroRNA (Shariqah, United Arab Emirates), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. 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

3 authors.

Chandrajeet DharaSchool of Biosciences, Apeejay Stya University Gurugram, Sohna-Palwal Road, Haryana-122103, India.ORCID 0000-0002-3417-2578
Anindita DharaInstitute for Pharmacology and Toxicology, Universitatklinikum Carl Gustav Carus, TU Dresden, Germany.ORCID 0000-0003-0232-6322
Saumyatika GantayatSchool of Biosciences, Apeejay Stya University Gurugram, Sohna-Palwal Road, Haryana-122103, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNA abundance as a particular biomarker for precisely identifying cancer metastases has emerged in recent years. The expression levels of miRNA are analyzed to get insights into cancer tissue detection and subtypes. Similar to other cancer types, the miRNA shows high levels of target mRNA dysregulation in association with non-small cell lung carcinoma (NSCLC). Among many promising cancer biomarkers for NSCLC, miR-7-5p has shown significant downregulation in the NSCLC tissues and targets proto-oncogenes like PAK2 and NOVA2. The expression levels of different proto-oncogenes targeting the miR-7-5p in NSCLC showed that the EGFR-mutated NSCLC has an experimental validation. The target validation of the miR-7-5p could be analyzed using SPR (Surface plasmon resonance) based sensors at a single nanoparticle level, such as Au nanocube, due to its high specificity and accountability. Despite being an accountable tool for cancer diagnosis, miRNA-based biomarkers sometimes cause poor diagnostic specificity and reproducibility due to their heterogenicity and immunogenicity in cancer detection. To overcome these shortcomings, the biomarkers need to be validated according to recent clinical studies.

Indexed as

Biomarkers, TumorCarcinoma, Non-Small-Cell LungLung NeoplasmsMicroRNAsSurface Plasmon ResonanceComputer SimulationGene Expression Regulation, NeoplasticHumansp21-Activated KinasesBiomarkers, TumorMicroRNAsMIRN7-1 microRNA, humanp21-Activated KinasesAu-Nanocubebiomarker validation.EGFRmicroRNAmiR-7-5pNSCLCSPR-based probe

Identifiers

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.