Evidence map›Paper›PMID 39655225›Full record

ArticleFrontiers in genetics2024

Diagnostic value of 5 miRNAs combined detection for breast cancer.

Yubo Jing, Xinzhu Huang, Yiyang Wang, Junyi Wang, Yongxiang Li, Dlraba Yelihamu, Chenming Guo

Abstract read
In one paragraph

Article in Frontiers in genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 2 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

32 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. 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

7 authors.

Yubo Jing *Department of Breast Surgery, Center of Digestive and Vascular, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Xinzhu Huang *Department of Breast Surgery, Center of Digestive and Vascular, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Yiyang Wang *Department of Breast Surgery, Center of Digestive and Vascular, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Junyi WangDepartment of Breast Surgery, Center of Digestive and Vascular, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Yongxiang LiDepartment of Breast Surgery, Center of Digestive and Vascular, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Dlraba YelihamuDepartment of Breast Surgery, Center of Digestive and Vascular, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Chenming GuoDepartment of Breast Surgery, Center of Digestive and Vascular, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Breast cancer (BC) is the prevailing malignant tumor, with its prevalence and death rate steadily rising over time. BC often does not show obvious symptoms in its early stages and is difficult to distinguish from benign breast disease. We aimed to find a distinct group of miRNAs utilizing serum as a non-invasive biomarker for early BC diagnosis. Methods: Herein, we mainly include the screening stage, testing stage, and verification stage. In the screening stage, 8 miRNAs associated with BC were selected and analyzed via literature reading, and the expression of the above miRNAs in BC was further verified by bioinformatics and included in the research analysis. In the testing phase, quantitative reverse transcription polymerase chain reaction (qRT-PCR) was deployed to select the five miRNAs with the most significant expression differences in 15 BC patients and 15 benign breast controls to proceed to the next stage. In a subsequent validation phase, the five miRNAs obtained from serum samples from an additional 75 BC patients and 50 benign control patients were evaluated using RT-qPCR. The diagnostic capacity, specificity, and sensitivity of candidate miRNAs were estimated with the receiver operating characteristic (ROC) curve and area under the curve (AUC). Finally, the optimal diagnostic combination model with high sensitivity and strong specificity was constructed by using the above 5 miRNAs. Results: The BC patients reported a significant decline in mir-10b-5p, mir-133a-3p, mir-195-5p, and mir-155-3p levels in serum levels contrasted with those in benign controls. Additionally, BC patients experienced elevated mir-195-3p levels than in benign controls. We implemented ROC analysis to evaluate its diagnostic capacity for BC. We demonstrated that all five miRNAs had robust diagnostic capability, with an AUC above 0.8. We developed a conclusive diagnostic combination model consisting of these 5 miRNAs in order to enhance the diagnosis accuracy. This model demonstrated a high diagnostic value, as shown by an AUC of 0.948. Conclusion: The serum biomarker panels composed of five miRNAs identified in this study (mir-10b-5p, mir-133a-3p, mir-195-5p, mir-195-3p, and mir-155-3p) provide hope for early, non-invasive, and accurate diagnosis of BC.

Indexed as

bioinformaticsbiomarkerbreast cancerdiagnosismicroRNA

Identifiers

PMID39655225
PMCPMC11625769

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.