Evidence map›Paper›PMID 40226123›Full record

ArticlePractical laboratory medicine2025

Evaluation of CircHIPK3 biomarker potential in breast cancer.

Ensiyeh Bahadoran, Davood Mohammadi, Manijeh Jalilvand, Sahar Moghbelinejad

Abstract read
In one paragraph

Article in Practical laboratory medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Large Language Models for Non-Coding RNA Biomarker Discovery in Breast Cancer.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  4. Review
  5. Review
  6. Review
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.

Ensiyeh BahadoranCellular and Molecular Research Centre, Research Institute for Prevention of Non-Communicable Diseases, Qazvin University of Medical Sciences, Qazvin, Iran.
Davood MohammadiDepartment of Surgery, School of Medicine, Qazvin University of Medical Sciences, Qazvin, Iran.
Manijeh JalilvandCellular and Molecular Research Centre, Research Institute for Prevention of Non-Communicable Diseases, Qazvin University of Medical Sciences, Qazvin, Iran.
Sahar MoghbelinejadCellular and Molecular Research Centre, Research Institute for Prevention of Non-Communicable Diseases, Qazvin University of Medical Sciences, Qazvin, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Nowadays, the investigation of circular RNAs (circRNAs) in various cancers is of great interest. In this research, we evaluated circHIPK3 biomarker potential in breast cancer (BC). Methods: The studied samples were 100 cancer and adjacent normal tissues, plasma from 95 cancer patients, 42 patients with fibroadenomatosis, and 93 healthy donors. Illumina high-throughput Hi Seq 2000 sequencing performed expression profiling on 4 pairs of cancerous and normal breast tissues. For expression confirmation, Quantitative real-time fluorescent polymerase chain reaction (qRT-PCR) was used to detect the expression level of circHIPK3. CircHIPK3 diagnostic efficacy was evaluated by the receiver operating characteristic curve (ROC). Results: Based on high-throughput sequencing and bioinformatics results circHIPK3 had the highest expression in cancer tissues ( Conclusions: CircHIPK3 is significantly upregulated in BC tissues and plasma compared to healthy controls, demonstrating high diagnostic potential with an AUC of 0.8087. The expression of circHIPK3 correlates with tumor size, indicating its relevance in the pathologic assessment of BC.

Indexed as

BiomarkerBreast cancerCircular RNALiquid biopsy

Identifiers

PMID40226123
PMCPMC11984561

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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.