Evidence map›Paper›PMID 31159706›Full record

ArticleTechnology in cancer research & treatment

Comprehensive Analysis of lncRNA-miRNA- mRNA Network Ascertains Prognostic Factors in Patients with Colon Cancer.

Zhenzhen Gao, Peng Fu, Zhengyi Yu, Fuxi Zhen, Yanhong Gu

Open access · goldAbstract read
In one paragraph

Article in Technology in cancer research & treatment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
1.5field-weighted citation impact, top 19% 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

25 citing papers in PubMed, 32 citations in OpenAlex.

  1. Article
  2. NovelBalkan medical journal · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. Heliyon · 2023
    Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  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

5 authors at 2 institutions in 1 country.

Zhenzhen Gao1 Department of Clinical Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Peng Fu2 Department of Bone Oncology, The Second Affiliated Hospital of Jiaxing University, Jiaxing, China.
Zhengyi Yu1 Department of Clinical Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Fuxi Zhen1 Department of Clinical Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Yanhong Gu1 Department of Clinical Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.ORCID 0000-0001-5033-1770
Jiangsu Province Hospital · CNJiaxing University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNon-coding RNAs are competing endogenous RNAs in the occurrence and development of tumorigenesis; numerous microRNAs are aberrantly expressed in colon cancer tissues and play significant roles in oncogenesis development and metastasis. However, large clinical and RNA data are lacking to further confirm the exact role of these RNAs in tumors. This study aimed to ascertain differential RNA expression between colon cancer and normal colon tissues. MATERIALS AND

methodsRNA sequencing and clinical data of patients with colon cancer were procured from The Cancer Genome Atlas database; differentially expressed long non-coding RNA, differentially expressed messenger RNAs, and differentially expressed microRNAs were achieved using the limma package in edgeR to generate competing endogenous RNAs networks. Then, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were conducted with ggplot2 package, the Kaplan-Meier survival method was used to predict survival in patients with colon cancer.

resultsIn total, 1174 differentially expressed long non-coding RNAs, 2068 differentially expressed messenger RNAs, and 239 differentially expressed microRNAs were generated between 480 colon cancer and 41 normal colon tissue samples. Three competing endogenous RNA networks were established. Gene Ontology analysis indicated that the genes of the up-regulated microRNA network were involved in negative regulation of transcription, DNA-template, and those of down-regulated microRNA network were involved in transforming growth factor β receptor signaling pathways, response to hypoxia, cell migration, while Kyoto Encyclopedia of Genes and Genomes analyses of these networks turned out to be negative. Three long non-coding RNAs (AP004609.1, ARHGEF26-AS1, and LINC00491), 3 microRNAs (miRNA-141, miRNA-216a, and miRNA-193b) and 3 RNAs (ULBP2, PHLPP2, and TPM2) were detected to be associated with prognosis by the Kaplan-Meier survival analysis. Additionally, univariate and multivariate Cox regression analyses showed that the microRNA-216a of the competing endogenous RNA might be an independent prognostic factor in colon cancer.

conclusionsThis study constructed the non-coding RNA-related competing endogenous RNA networks in colon cancer and sheds lights on underlying biomarkers for colon cancer cohorts.

Indexed as

Gene Expression Regulation, NeoplasticGene Regulatory NetworksRNA InterferenceAdultAgedColonic NeoplasmsComputational BiologyGene OntologyHumansKaplan-Meier EstimateMicroRNAsMiddle AgedNeoplasm MetastasisNeoplasm StagingPrognosisRNA, Long NoncodingMicroRNAsRNA, Long NoncodingRNA, Messengercolon cancercompeting endogenous RNA networklong non-coding RNAsmicroRNAsoverall survival

Identifiers

PMID31159706
PMCPMC6552362
OpenAlexW2948815485

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.