Evidence map›Paper›PMID 36091132›Full record

ArticleFrontiers in oncology2022

Establishing a prognostic model of ferroptosis- and immune-related signatures in kidney cancer: A study based on TCGA and ICGC databases.

Zhijun Han, Hao Wang, Jing Long, Yanning Qiu, Xiao-Liang Xing

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 41% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
  2. 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 3 institutions in 1 country.

Zhijun HanDepartment of Urology, Department of Ultrasonography, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, China.
Hao WangHunan Provincial Key Laboratory for Synthetic Biology of Traditional Chinese Medicine, Hunan University of Medicine, Huaihua, China.
Jing LongDepartment of Urology, Department of Ultrasonography, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, China.
Yanning QiuFirst College for Clinical Medicine, Xinjiang Medical University, Urumqi, China.
Xiao-Liang XingHunan Provincial Key Laboratory for Synthetic Biology of Traditional Chinese Medicine, Hunan University of Medicine, Huaihua, China.
University of South China · CNZhuzhou Central Hospital · CNXinjiang Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Kidney cancer (KC) is one of the most challenging cancers due to its delayed diagnosis and high metastasis rate. The 5-year survival rate of KC patients is less than 11.2%. Therefore, identifying suitable biomarkers to accurately predict KC outcomes is important and urgent. Methods: Corresponding data for KC patients were obtained from the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) databases. Systems biology/bioinformatics/computational approaches were used to identify suitable biomarkers for predicting the outcome and immune landscapes of KC patients. Results: We found two ferroptosis- and immune-related differentially expressed genes (FI-DEGs) ( Conclusions: Our present study indicated that

Indexed as

ferroptosisimmunekidney canceroverall survivalprognosis

Identifiers

PMID36091132
PMCPMC9459019
OpenAlexW4293207332

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.