Evidence map›Paper›PMID 38728235›Full record

ArticleAging2024

Construction of exosome-related genes risk model in kidney cell carcinoma predicts prognosis and immune therapy response.

Chao Gao, Wei Huang, Qiang Su, Jingxian Li, Wei Wang, Yuanjiong Qi, E Du, Zhihong Zhang

Abstract read
In one paragraph

Article in Aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Chao GaoTianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China.
Wei HuangTianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China.
Qiang SuTianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China.
Jingxian LiTianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China.
Wei WangTianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China.
Yuanjiong QiTianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China.
E DuTianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China.
Zhihong ZhangTianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Renal cell carcinoma (RCC) is one of the most prevalent types of urological cancer. Exosomes are vesicles derived from cells and have been found to promote the development of RCC, but the potential biomarker and molecular mechanism of exosomes on RCC remain ambiguous. Here, we first screened differentially expressed exosome-related genes (ERGs) by analyzing The Cancer Genome Atlas (TCGA) database and exoRBase 2.0 database. We then determined prognosis-related ERGs (PRERGs) by univariate Cox regression analysis. Gene Dependency Score (gDS), target development level, and pathway correlation analysis were utilized to examine the importance of PRERGs. Machine learning and lasso-cox regression were utilized to screen and construct a 5-gene risk model. The risk model showed high predictive accuracy for the prognosis of patients and proved to be an independent prognostic factor in three RCC datasets, including TCGA-KIRC, E-MTAB-1980, and TCGA-KIRP datasets. Patients with high-risk scores showed worse outcomes in different clinical subgroups, revealing that the risk score is robust. In addition, we found that immune-related pathways are highly enriched in the high-risk group. Activities of immune cells were distinct in high-/low-risk groups. In independent immune therapeutic cohorts, high-risk patients show worse immune therapy responses. In summary, we identified several exosome-derived genes that might play essential roles in RCC and constructed a 5-gene risk signature to predict the prognosis of RCC and immune therapy response.

Indexed as

Carcinoma, Renal CellExosomesKidney NeoplasmsBiomarkers, TumorDatabases, GeneticFemaleGene Expression Regulation, NeoplasticHumansImmunotherapyMalePrognosisRisk AssessmentRisk FactorsBiomarkers, Tumorclinical modelexosomemachine learningprognosisRCC

Identifiers

PMID38728235
PMCPMC11132023

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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.