Evidence map›Paper›PMID 31133033›Full record

ArticleJournal of translational medicine2019

Comprehensive characterization of immune- and inflammation-associated biomarkers based on multi-omics integration in kidney renal clear cell carcinoma.

Enyang Zhao, Lihong Li, Wenfu Zhang, Wanhui Wang, Yunhui Chan, Bosen You, Xuedong Li

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

13 citing papers in PubMed, 26 citations in OpenAlex.

  1. Article
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  3. Expression and clinical significance of DOK3 in renal clear cell carcinoma.The Journal of international medical research · 2023
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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.

Enyang ZhaoDepartment of Urinary Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150006, Heilongjiang, People's Republic of China.
Lihong LiDepartment of Urinary Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150006, Heilongjiang, People's Republic of China.
Wenfu ZhangDepartment of Urinary Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150006, Heilongjiang, People's Republic of China.
Wanhui WangDepartment of Urinary Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150006, Heilongjiang, People's Republic of China.
Yunhui ChanDepartment of Urinary Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150006, Heilongjiang, People's Republic of China.
Bosen YouDepartment of Urinary Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150006, Heilongjiang, People's Republic of China.
Xuedong LiDepartment of Urinary Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150006, Heilongjiang, People's Republic of China. 13604803553@163.com.
Harbin Medical University · CNSecond Affiliated Hospital of Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundKidney renal clear cell carcinoma (KIRC) is the most common type of kidney cancer in adults, and it is responsible for approximately 90-95% of cases. Although extensive evidence has suggested that many immune- and inflammation-related genes could serve as effective biomarkers in KIRC, the potential associations among immune-, inflammation- and KIRC-related genes has not been sufficiently understood.

methodsHere, we integrated multiple levels of data to construct an immune-, inflammation- or KIRC-directed neighbour network (IIKDN network) and a KIRC-related gene-directed network (KIRCD network).

resultsOur analysis suggested that immune- and inflammation-related genes in the network have special topological characteristics and expression patterns related to KIRC. We further identified five core clusters that showed a tighter network structure and stronger correlation of expression from the KIRCD network. Specifically, multiple-level molecular characteristics were systematically portrayed, including somatic mutation, copy-number variant and DNA methylation for the genes in five core clusters. We discovered that the genes showed strong correlation with respect to the expression and methylation levels in these five core clusters. These five core clusters could become special prognostic biomarkers for KIRC, and functional analysis showed that they were associated with activation of the immune and inflammation systems and cancer progression.

conclusionsOur findings highlighted the novel role of the immune and inflammation genes in KIRC.

Indexed as

Systems IntegrationAdultBiomarkers, TumorCarcinoma, Renal CellComputational BiologyDatabases, GeneticDNA MethylationGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksGenomicsHumansImmunityInflammationKidney NeoplasmsMetabolomicsBiomarkers, TumorDNA methylationImmuneInflammationKidney renal clear cell carcinomaMulti-omics molecularNetwork modules

Identifiers

PMID31133033
PMCPMC6537414
OpenAlexW2947073516

What OpenQuestion holds

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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.