Evidence map›Paper›PMID 24709885›Full record

Trial reportPloS one2014

Identification of a circulating microRNA signature for colorectal cancer detection.

Jia Wang, Sheng-kai Huang, Mei Zhao, Mei Yang, Jia-ling Zhong, Yu-yu Gu, Hua Peng, Yi-qun Che, Chang-zhi Huang

Abstract readClinical Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 103 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
103citing papers in PubMed, 9 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

103 citing papers in PubMed, 9 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Pooled it
  8. Pooled it
  9. Predictive power of circulating miRNAs in detecting colorectal cancer.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2015
    Pooled it
  10. Review
  11. Article
  12. Review
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Review
  20. Review

43 more citing papers are in PubMed but not listed here.

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

9 authors.

Jia WangDepartment of Etiology and Carcinogenesis, State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Sheng-kai HuangDepartment of Etiology and Carcinogenesis, State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Mei ZhaoDepartment of Etiology and Carcinogenesis, State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Mei YangDepartment of Etiology and Carcinogenesis, State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jia-ling ZhongDepartment of Etiology and Carcinogenesis, State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yu-yu GuDepartment of Etiology and Carcinogenesis, State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Hua PengDepartment of Etiology and Carcinogenesis, State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yi-qun CheDepartment of Clinical Laboratory, Cancer Institute & Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Chang-zhi HuangDepartment of Etiology and Carcinogenesis, State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prognosis of patients with colorectal cancer (CRC) is generally poor because of the lack of simple, convenient, and noninvasive tools for CRC detection at the early stage. The discovery of microRNAs (miRNAs) and their different expression profiles among different kinds of diseases has opened a new avenue for tumor diagnosis. We built a serum microRNA expression profile signature and tested its specificity and sensitivity as a biomarker in the diagnosis of CRC. We also studied its possible role in monitoring the progression of CRC. We conducted a two phase case-control test to identify serum miRNAs as biomarkers for CRC diagnosis. Using quantitative reverse transcription polymerase chain reactions, we tested ten candidate miRNAs in a training set (30 CRCs vs 30 controls). Risk score analysis was used to evaluate the diagnostic value of the serum miRNA profiling system. Other independent samples, including 83 CRCs and 59 controls, were used to validate the diagnostic model. In the training set, six serum miRNAs (miR-21, let-7g, miR-31, miR-92a, miR-181b, and miR-203) had significantly different expression levels between the CRCs and healthy controls. Risk score analysis demonstrated that the six-miRNA-based biomarker signature had high sensitivity and specificity for distinguishing the CRC samples from cancer-free controls. The areas under the receiver operating characteristic (ROC) curve of the six-miRNA signature profiles were 0.900 and 0.923 for the two sets of serum samples, respectively. However, for the same serum samples, the areas under the ROC curve used by the tumor markers carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) were only 0.649 and 0.598, respectively. The expression levels of the six serum miRNAs were also correlated with CRC progression. Thus, the identified six-miRNA signature can be used as a noninvasive biomarker for the diagnosis of CRC, with relatively high sensitivity and specificity.

Indexed as

Models, BiologicalAgedBiomarkers, TumorColorectal NeoplasmsFemaleGene Expression Regulation, NeoplasticHumansMaleMicroRNAsMiddle AgedRNA, NeoplasmBiomarkers, TumorMicroRNAsRNA, Neoplasm

Identifiers

PMID24709885
PMCPMC3977854

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.