Evidence map›Paper›PMID 26951510›Full record

ArticleTumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine2016

The conglomeration of diagnostic, prognostic and therapeutic potential of serum miR-199a and its association with clinicopathological features in epithelial ovarian cancer.

Mariyam Zuberi, Imran Khan, Gauri Gandhi, P C Ray, Alpana Saxena

Abstract read
PubMed Publisher
In one paragraph

Article in Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 4 pooled it
1.8field-weighted citation impact, top 17% of its field
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

21 citing papers in PubMed, 4 syntheses or guidelines pooled it, 28 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Review
  6. The Role of microRNA in the Prognosis and Diagnosis of Ovarian Cancer.International journal of molecular sciences · 2025
    Review
  7. Review
  8. Review
  9. Review
  10. Article
  11. Review
  12. The Role of microRNAs in Epithelial Ovarian Cancer Metastasis.International journal of molecular sciences · 2020
    Review
  13. Article
  14. Article
  15. Circulating non-coding RNAs in recurrent and metastatic ovarian cancer.Cancer drug resistance (Alhambra, Calif.) · 2019
    Review
  16. Review
  17. Article
  18. Article
  19. A Pilot Study of Circulating MicroRNA-125b as a Diagnostic and Prognostic Biomarker for Epithelial Ovarian Cancer.International journal of gynecological cancer : official journal of the International Gynecological Cancer Society · 2017
    Article
  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

5 authors at 3 institutions in 2 countries.

Mariyam ZuberiDepartment of Biochemistry, Maulana Azad Medical College, New Delhi, 110002, India.
Imran KhanDepartment of Surgery, University of Illinois at Chicago, Chicago, IL, USA.
Gauri GandhiDepartment of Gynaecology and Obstetrics, Lok Nayak Hospital, New Delhi, 110002, India.
P C RayDepartment of Biochemistry, Maulana Azad Medical College, New Delhi, 110002, India.
Alpana SaxenaDepartment of Biochemistry, Maulana Azad Medical College, New Delhi, 110002, India. alpanasaxena@hotmail.com.
Maulana Azad Medical College · INLok Nayak Jai Prakash Narayan Hospital · INUniversity of Illinois Chicago · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epithelial ovarian cancer (EOC) is the most lethal cause of morbidity and mortality worldwide. miRNA deregulation evinces a remarkable role in ovarian cancer tumorigenesis. miRNA-199a (miR-199a) is known to be involved in cancer development and progression. Although miR-199a has been studied in various cell types, its correlation with clinicopathological features in EOC has not been documented. In this study, we identified the clinicopathological hallmarks which might be perturbed due to the downregulation of serum miR-199a in EOC. Seventy serum samples from histopathologically confirmed EOC patients and 70 controls were collected. Total RNA from serum was isolated by Trizol method, polyadenylated and reverse transcribed into cDNA. Expression level of miR-199a was detected by using miRNA qRT-PCR. Relative expression was determined with matched controls using U6 snRNA as reference. Level of miR-199a expression was compared with distinct clinicopathological features. Expression of miR-199a was found to be significantly downregulated in comparison with matched normal controls. The expression level of miR-199a was found to be significantly associated with tumor stage, lymph node metastasis, and distal metastasis. Receiver operating characteristic (ROC) curve for diagnostic potential yielded significant area under the curve (AUC) with a considerable sensitivity and specificity. ROC curves for prognosis yielded significant AUCs for histological grade, distal metastasis, lymph node status, and survival. Our findings suggest that miR-199a downregulation might be a potential indicator for disease progression promoting the aggressive tumor progression and be identified as a diagnostic marker to predict the prognosis and survival in EOC patients.

Indexed as

AdultAgedArea Under CurveBiomarkers, TumorCarcinoma, Ovarian EpithelialDown-RegulationFemaleHumansKaplan-Meier EstimateMicroRNAsMiddle AgedNeoplasms, Glandular and EpithelialOvarian NeoplasmsPolymerase Chain ReactionPrognosisROC CurveBiomarkers, TumorMicroRNAsmirn199 microRNA, humanbiomarkerdiagnosisEpithelial ovarian cancermicroRNA-199aprognosisserum

Identifiers

PMID26951510
OpenAlexW2294462175

What OpenQuestion holds

Textmetadata
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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.