Evidence map›Paper›PMID 38365923›Full record

ArticleScientific reports2024

Integration of basement membrane-related genes in a risk signature for prognosis in clear cell renal cell carcinoma.

Bowen Xia, Jingwei Wang, Dongxu Zhang, Xiaopeng Hu

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 citing papers in PubMed.

  1. Article
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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

4 authors.

Bowen Xia *Department of Urology, Beijing Chao-Yang Hospital, Capital Medical University, No. 8 Worker's Stadium, Chaoyang District, Beijing, 100020, China.
Jingwei Wang *Department of Occupational Medicine and Toxicology, Clinical Center for Interstitial Lung Diseases, Beijing Institute of Respiratory Medicine, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100020, China.
Dongxu ZhangDepartment of Urology, Beijing Chao-Yang Hospital, Capital Medical University, No. 8 Worker's Stadium, Chaoyang District, Beijing, 100020, China.
Xiaopeng HuDepartment of Urology, Beijing Chao-Yang Hospital, Capital Medical University, No. 8 Worker's Stadium, Chaoyang District, Beijing, 100020, China. xiaopeng_hu@sina.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clear cell renal cell carcinoma (ccRCC) is characterized by high heterogeneity and recurrence rates, posing significant challenges for stratification and treatment. Basement membrane-related genes (BMGs) play a crucial role in tumor initiation and progression. Clinical and transcriptomic data of ccRCC patients were extracted from TCGA and GEO databases. We employed univariate regression and LASSO-Cox stepwise regression analysis to construct a BMscore model based on BMGs expression level. A nomogram combining clinical features and BMscore was constructed to predict individual survival probabilities. Further enrichment analysis and immune-related analysis were conducted to explore the enriched pathways and immune features associated with BMGs. High-risk individuals predicted by BMscore exhibited poorer overall survival, which was consistent with the validation dataset. BMscore was identified as an independent risk factor for ccRCC. Functional analysis revealed that BMGs were related to cell-matrix and tumor-associated signaling pathways. Immune profiling suggests that BMGs play a key role in immune interactions and the tumor microenvironment. BMGs serve as a novel prognostic predictor for ccRCC and play a role in the immune microenvironment and treatment response. Targeting the BM may represent an alternative therapeutic approach for ccRCC.

Indexed as

CarcinomaCarcinoma, Renal CellKidney NeoplasmsBasement MembraneHumansPrognosisRisk FactorsTumor MicroenvironmentBasement membraneBasement membrane-related genesGene signaturePrognosisRenal clear cell carcinoma

Identifiers

PMID38365923
PMCPMC10873511

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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.