Evidence map›Paper›PMID 35422048›Full record

ArticleWorld journal of surgical oncology2022

Prediction of overall survival based upon a new ferroptosis-related gene signature in patients with clear cell renal cell carcinoma.

Zhuolun Sun, Tengcheng Li, Chutian Xiao, Shaozhong Zou, Mingxiao Zhang, Qiwei Zhang, Zhenqing Wang, Hailun Zhan, Hua Wang

Abstract read
In one paragraph

Article in World journal of surgical oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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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

9 authors.

Zhuolun Sun *Department of Urology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510630, China.
Tengcheng Li *Department of Urology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510630, China.
Chutian XiaoDepartment of Urology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510630, China.
Shaozhong ZouCollege of Life Science and Technology, Jinan University, Guangzhou, 510630, China.
Mingxiao ZhangDepartment of Urology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510630, China.
Qiwei ZhangDepartment of Thoracic Surgery, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518107, China.
Zhenqing WangDepartment of Urology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510630, China.
Hailun ZhanDepartment of Urology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510630, China. hailunzhan@aliyun.com.
Hua WangDepartment of Urology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510630, China. wangh49@mail2.sysu.edu.cn.

Funding

National Natural Science Foundation of China 81902617
6 · The paper itself

Abstract

backgroundClear cell renal cell carcinoma (ccRCC) is the most common and lethal renal cell carcinoma (RCC) histological subtype. Ferroptosis is a newly discovered programmed cell death and serves an essential role in tumor occurrence and development. The purpose of this study is to analyze ferroptosis-related gene (FRG) expression profiles and to construct a multi-gene signature for predicting the prognosis of ccRCC patients.

methodsRNA-sequencing data and clinicopathological data of ccRCC patients were downloaded from The Cancer Genome Atlas (TCGA). Differentially expressed FRGs between ccRCC and normal tissues were identified using 'limma' package in R. GO and KEGG enrichment analyses were conducted to elucidate the biological functions and pathways of differentially expressed FRGs. Consensus clustering was used to investigate the relationship between the expression of FRGs and clinical phenotypes. Univariate and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis were used to screen genes related to prognosis and construct the optimal signature. Then, a nomogram was established to predict individual survival probability by combining clinical features and prognostic signature.

resultsA total of 19 differentially expressed FRGs were identified. Consensus clustering identified two clusters of ccRCC patients with distinguished prognostic. Functional analysis revealed that metabolism-related pathways were enriched, especially lipid metabolism. A 7-gene ferroptosis-related prognostic signature was constructed to stratify the TCGA training cohort into high- and low-risk groups where the prognosis was significantly worse in the high-risk group. The signature was identified as an independent prognostic indicator for ccRCC. These findings were validated in the testing cohort, the entire cohort, and the International Cancer Genome Consortium (ICGC) cohort. We further demonstrated that the signature-based risk score was highly associated with the ccRCC progression. Further stratified survival analysis showed that the high-risk group had a significantly lower overall survival (OS) rate than those in the low-risk group. Moreover, we constructed a nomogram that had a strong ability to forecast the OS of the ccRCC patients.

conclusionsWe constructed a ferroptosis-related prognostic signature, which might provide a reliable prognosis assessment tool for the clinician to guide clinical decision-making and outcomes research.

Indexed as

Carcinoma, Renal CellFerroptosisKidney NeoplasmsBiomarkers, TumorFemaleGene Expression Regulation, NeoplasticHumansMalePrognosisBiomarkers, TumorBioinformaticsClear cell renal cell carcinomaFerroptosisNomogramPrognostic signature

Identifiers

PMID35422048
PMCPMC9008912

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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.