Evidence map›Paper›PMID 24318988›Full record

SynthesisTumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine2014

FUT11 as a potential biomarker of clear cell renal cell carcinoma progression based on meta-analysis of gene expression data.

Elżbieta Zodro, Marcin Jaroszewski, Agnieszka Ida, Tomasz Wrzesiński, Zbigniew Kwias, Hans Bluyssen, Joanna Wesoly

Open access · hybridAbstract readMeta-Analysis
In one paragraph

Synthesis in Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
1.2field-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

29 citing papers in PubMed, 40 citations in OpenAlex.

  1. Article
  2. Review
  3. Glycosylation in kidney diseases.Precision clinical medicine · 2025
    Review
  4. Article
  5. ProteinMolecules (Basel, Switzerland) · 2025
    Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Aberrant Protein Glycosylation in Brain Cancers, with Emphasis on Glioblastoma.Advances in experimental medicine and biology · 2022
    Article
  14. Fucosylation in Urological Cancers.International journal of molecular sciences · 2021
    Review
  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

7 authors at 2 institutions in 1 country.

Elżbieta ZodroLaboratory of High Throughput Technologies, Institute of Biotechnology and Molecular Biology, Faculty of Biology, Adam Mickiewicz University, Umultowska 89, 61-614, Poznań, Poland.
Marcin Jaroszewski
Agnieszka Ida
Tomasz Wrzesiński
Zbigniew Kwias
Hans Bluyssen
Joanna Wesoly
Adam Mickiewicz University in Poznań · PLPoznan University of Medical Sciences · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, we provide a comprehensive summary of available clear cell renal cell carcinoma (ccRCC) microarray data in the form of meta-analysis of genes differentially regulated in tumors as compared to healthy tissue, using effect size to measure the strength of a relationship between the disease and gene expression. We identified 725 differentially regulated genes, with a number of interesting targets, such as TMEM213, SMIM5, or ATPases: ATP6V0A4 and ATP6V1G3, of which limited or no information is available in terms of their function in ccRCC pathology. Downregulated genes tended to represent pathways related to tissue remodeling, blood clotting, vasodilation, and energy metabolism, while upregulated genes were classified into pathways generally deregulated in cancers: immune system response, inflammatory response, angiogenesis, and apoptosis. One hundred fifteen deregulated genes were included in network analysis, with EGLN3, AP-2, NR3C1, HIF1A, and EPAS1 (gene encoding HIF2-α) as points of functional convergence, but, interestingly, 610 genes failed to join previously identified molecular networks. Furthermore, we validated the expression of 14 top deregulated genes in independent sample set of 32 ccRCC tumors by qPCR and tested if it could serve as a marker of disease progression. We found a correlation of high fucosyltransferase 11 (FUT11) expression with non-symptomatic course of the disease, which suggests that FUT11's expression might be potentially used as a biomarker of disease progression.

Indexed as

TranscriptomeBiomarkers, TumorCarcinoma, Renal CellDisease ProgressionFucosyltransferasesHumansKidney NeoplasmsOligonucleotide Array Sequence AnalysisPolymerase Chain ReactionBiomarkers, TumorFucosyltransferasesFUT11 protein, human

Identifiers

PMID24318988
PMCPMC3967067
OpenAlexW2068245157

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.