Evidence map›Paper›PMID 36514337›Full record

ArticleComputational and structural biotechnology journal2023

Landscape of the intratumroal microenvironment in bladder cancer:

Zichen Bian, Jia Chen, Chang Liu, Qintao Ge, Meng Zhang, Jialin Meng, Chaozhao Liang

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. TSPAN4Frontiers in immunology · 2025
    Article
  4. Article
  5. Article
  6. 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

7 authors.

Zichen BianDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Institute of Urology & Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University, Hefei 230022, China.
Jia ChenDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Institute of Urology & Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University, Hefei 230022, China.
Chang LiuDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Institute of Urology & Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University, Hefei 230022, China.
Qintao GeDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Institute of Urology & Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University, Hefei 230022, China.
Meng ZhangDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Institute of Urology & Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University, Hefei 230022, China.
Jialin MengDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Institute of Urology & Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University, Hefei 230022, China.
Chaozhao LiangDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Institute of Urology & Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University, Hefei 230022, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: This study aims to present the landscape of the intratumoral microenvironment and by which establish a classification system that can be used to predict the prognosis of bladder cancer patients and their response to anti-PD-L1 immunotherapy. Methods: The expression profiles of 1554 bladder cancer cases were downloaded from seven public datasets. Single-sample gene set enrichment analysis (ssGSEA), univariate Cox regression analysis, and meta-analysis were employed to establish the bladder cancer immune prognostic index (BCIPI). Extensive analyses were executed to investigate the association between BCIPI and overall survival, tumor-infiltrated immunocytes, immunotherapeutic response, mutation load, Results: The results obtained from seven independent cohorts and meta-analyses suggested that the BCIPI is an effective classification system for estimating bladder cancer patients' overall survival. Patients in the BCIPI-High subgroup revealed different immunophenotypic outcomes from those in the BCIPI-Low subgroup regarding tumor-infiltrated immunocytes and mutated genes. Subsequent analysis suggested that patients in the BCIPI-High subgroup were more sensitive to anti-PD-L1 immunotherapy than those in the BCIPI-Low subgroup. Conclusions: The newly established BCIPI is a valuable tool for predicting overall survival outcomes and immunotherapeutic responses in patients with bladder cancer.

Indexed as

AJCC, American Joint Committee on CancerAnti-PD-L1, Antitumor response to atezolizumabBCG, Bacillus Calmette-GuerinBCIPI, Bladder cancer immune prognostic indexBladder cancerCNVs, Copy number variationsFDA, Food and Drug AdministrationFPKM, Fragments per kilobase per millionGenomicICI, Immune checkpoint inhibitorIHC, ImmunohistochemistryImmunotherapyMES, Mesenchymal transitionNES, Normalized enrichment scoreOverall survivalRMA, Robust multiarray averageRMS, Restricted mean survivalssGSEA, Single-sample GSEATPM, Transcripts per kilobase million

Identifiers

PMID36514337
PMCPMC9730156

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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.