Evidence map›Paper›PMID 40155904›Full record

ArticleBMC cancer2025

Identification and validation of molecular subtypes and prognostic models in patients with kidney cancer based on differential genes based on B cells: a multiomics analysis.

Jiaao Sun, Shiyan Song, Qiancheng Ma, Feng Chen, Xiaochi Chen, Guangzhen Wu

Abstract read
In one paragraph

Article in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

6 authors.

Jiaao Sun *First Affiliated Hospital of Dalian Medical University, Dalian, China.
Shiyan Song *First Affiliated Hospital of Dalian Medical University, Dalian, China.
Qiancheng MaFirst Affiliated Hospital of Dalian Medical University, Dalian, China.
Feng ChenFirst Affiliated Hospital of Dalian Medical University, Dalian, China. dmuchenfeng@163.com.
Xiaochi ChenFirst Affiliated Hospital of Dalian Medical University, Dalian, China. chenxiaochi1216@163.com.
Guangzhen WuFirst Affiliated Hospital of Dalian Medical University, Dalian, China. wuguang0613@hotmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundB cells play a variety of complex roles in cancer, both promoting cancer progression and enhancing anti-tumor immune responses, but their mechanism of action in kidney cancer has not been elucidated.

resultsWe collected kidney cancer sample data from the GEO database and TCGA database, mapped the single-cell landscape inside kidney cancer tissue, identified 25 B-cell-related genes, and based on this, identified related molecular subtypes of kidney cancer patients, and explored their internal microenvironment characteristics. Finally, we constructed a 6-gene biological prognostic model that can be used to predict survival in patients with renal cancer, and we further validated the predictive performance of the model based on imaging omics. It is worth mentioning that the structural patterns and functional sites of 6 model gene transcription proteins were also mined.

conclusionsOverall, we explored for the first time the profound role of B cells in kidney cancer and developed a bio-predictive model based on B cell-related genes, providing scientific guidance for personalized treatment of kidney cancer patients.

Indexed as

Biomarkers, TumorB-LymphocytesKidney NeoplasmsGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMultiomicsPrognosisTumor MicroenvironmentBiomarkers, TumorB cellImmune microenvironmentMultiomicsPrognostic modelRenal carcinoma

Identifiers

PMID40155904
PMCPMC11951520

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.