Evidence map›Paper›PMID 28406230›Full record

Trial reportScientific reports2017

Meta-signature LncRNAs serve as novel biomarkers for colorectal cancer: integrated bioinformatics analysis, experimental validation and diagnostic evaluation.

Meiyu Dai, Xiaoli Chen, Shanying Mo, Jinwan Li, Zhizhuo Huang, Shifeng Huang, Junyi Xu, Baoyu He, Yan Zou, Jingfan Chen and 1 more

Abstract readClinical TrialValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing 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

38 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Review
  11. Review
  12. Novel Diagnostic Biomarkers in Colorectal Cancer.International journal of molecular sciences · 2022
    Review
  13. Review
  14. Review
  15. Article
  16. Review
  17. Article
  18. Review
  19. 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

11 authors.

Meiyu DaiMedical Science Laboratory, the Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, Guangxi 545005, China.
Xiaoli ChenMedical Science Laboratory, the Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, Guangxi 545005, China.
Shanying MoMedical Science Laboratory, the Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, Guangxi 545005, China.
Jinwan LiMedical Science Laboratory, the Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, Guangxi 545005, China.
Zhizhuo HuangMedical Science Laboratory, the Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, Guangxi 545005, China.
Shifeng HuangDepartment of General Surgery, the Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, Guangxi 545005, China.
Junyi XuDepartment of General Surgery, the Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, Guangxi 545005, China.
Baoyu HeMedical Science Laboratory, the Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, Guangxi 545005, China.
Yan ZouMedical Science Laboratory, the Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, Guangxi 545005, China.
Jingfan ChenDepartment of General Surgery, the Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, Guangxi 545005, China.
Shengming DaiMedical Science Laboratory, the Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, Guangxi 545005, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study is to explore the differentially expressed lncRNAs, which may have potential biological function and diagnostic value in colorectal cancer (CRC). Through integrated data mining, we finally identified nine differentially expressed lncRNAs and their potential mRNA targets. After a series of bioinformatics analyses, we screened significant pathways and GO terms that are related to the up-regulated and down-regulated transcripts respectively. Meanwhile, the nine lncRNAs were validated in 30 paired tissues and cell lines by qRT-PCR and the results were basically consistent with the microarray data. We also tested the nine lncRNAs in the serum of 30 CRC patients matched with the CRC tissue, 30 non-cancer patients and 30 health controls. Finally, we found that BLACAT1 was significant for the diagnosis of CRC. The area under the curve (AUC), sensitivity and specificity were 0.858 (95% CI: 0.765-0.951), 83.3% and 76.7% respectively between CRC patients and health controls. Moreover, BLACAT1 also had distinct value to discriminate CRC from other non-cancer diseases. The results indicated that the differentially expressed lncRNAs and their potential target transcripts could be considered as potential therapeutic targets for CRC patients. Meanwhile, lncRNA BLACAT1 might represent a new supplementary biomarker for the diagnosis of CRC.

Indexed as

Computational BiologyGene Expression ProfilingGene Expression Regulation, NeoplasticAdultAgedAged, 80 and overBiomarkers, TumorColorectal NeoplasmsFemaleHumansMaleMiddle AgedRNA, Long NoncodingRNA, NeoplasmBiomarkers, Tumorlong noncoding RNA BLACAT1, humanRNA, Long NoncodingRNA, Neoplasm

Identifiers

PMID28406230
PMCPMC5390272

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.