Evidence map›Paper›PMID 39708127›Full record

ArticleCancer immunology, immunotherapy : CII2024

Integration of bulk and single-cell RNA-seq reveals prognostic gene signatures in patients with bladder cancer treated with immune checkpoint inhibitors.

Mina Cho, Hyun Chang, Ju Han Kim

Abstract read
In one paragraph

Article in Cancer immunology, immunotherapy : CII, 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

3 authors.

Mina ChoDivision of Biomedical Informatics, Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul, 03080, Republic of Korea.
Hyun ChangMedical Oncology and Hematology, College of Medicine, International St Mary's Hospital, Catholic Kwandong University, Incheon, 22711, Republic of Korea. hchang7766@gmail.com.
Ju Han KimDivision of Biomedical Informatics, Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul, 03080, Republic of Korea. juhan@snu.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immune checkpoint inhibitors have significantly advanced research in oncology and are used to successfully treat patients with bladder cancer (BC). However, as the benefits of programmed death-1/ programmed death-ligand-1 blockade immunotherapy do not extend to all patients with BC, biomarkers are required to improve prognostic stratification. This study aims to identify reliable biomarkers to enhance the prediction of treatment outcomes. Bulk RNA expression data from a BC cohort (GSE176307) receiving ICI and single-cell sequencing data from patients with BC (GSE135337) were collected. We identified differentially expressed genes (DEGs) within cells that were associated with favorable survival outcomes and developed a predictive bladder cancer gene signature (BC-GS). Subsequently, we performed pathway enrichment analysis using the Reactome database. We used two independent datasets to validate the BC-GS. Patients with low BC-GS had a significantly shorter overall survival (OS) than those with high BC-GS (p < 0.05, p < 0.001, respectively). Additionally, patients with a concurrently low BC-GS score and low tumor mutation burden (TMB) in GSE176307 and the two validation datasets exhibited an increased risk of death. Genes in the BC-GS were predominantly involved in CD8

Indexed as

Biomarkers, TumorImmune Checkpoint InhibitorsRNA-SeqSingle-Cell AnalysisUrinary Bladder NeoplasmsAgedFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMalePrognosisSingle-Cell Gene Expression AnalysisTranscriptomeBiomarkers, TumorImmune Checkpoint InhibitorsBladder cancerBladder cancer gene signatureImmune checkpoint inhibitorsTumor microenvironmentTumor mutation burden

Identifiers

PMID39708127
PMCPMC11663206

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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.