Evidence map›Paper›PMID 39507856›Full record

ArticleTranslational andrology and urology2024

Molecular signature of immune-related new survival predictions for subtype of renal cell carcinomas.

Xichen Su, Yonghe Huang, Xiaosen Wang, Li Cui

Abstract read
In one paragraph

Article in Translational andrology and urology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Xichen SuDepartment of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China.
Yonghe HuangKey Laboratory of Adolescent Health Assessment and Exercise Intervention of Ministry of Education, College of Physical Education and Health, East China Normal University, Shanghai, China.
Xiaosen WangDepartment of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China.
Li CuiDepartment of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Kidney renal papillary cell carcinoma (KIRP), kidney chromophobe (KICH), and kidney renal clear cell carcinoma (KIRC) are three most common subtypes of renal cell carcinomas (RCC), and its development is a multifaceted process that intricately involves the interplay of numerous genes. Despite recent advances in research on renal cell carcinoma, the prognosis of KIRC patients remains dismal. Therefore, there is an urgent need to explore new prognostic biomarkers and treatment strategies to help clinicians choose more effective treatment methods and accurately predict long-term efficacy. Our study aimed to systematically evaluate the gene expression profiles of three RCC subtypes, especially KIRC, and to identify survival-related biomarker. Methods: In our present study, we systematically evaluate the genes expression profile difference among three subtypes of RCC, and identify the survival-related key genes signature based on GEPIA2. GeneMANIA was used to identify the functionality-related differentially expressed genes (DEGs). Furthermore, focusing on KIRC, we intersected functionality-related and survival-related DEGs based on two datasets. Results: We ascertained five DEGs ( Conclusions: The five identified DEGs serve as potential novel prognostic biomarkers for KIRC. However, the crucial factors that lead to the downregulation and functional inactivation of these five key genes need to be explored in future studies.

Indexed as

immune-related genesimmune-related markermolecular signatureRenal cell carcinomas (RCC)

Identifiers

PMID39507856
PMCPMC11535737

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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.