ArticleCancer medicine2020
An immune relevant signature for predicting prognoses and immunotherapeutic responses in patients with muscle-invasive bladder cancer (MIBC).
Article in Cancer medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
46 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The miRNA-immune axis in bladder cancer: systematic evidence for a new era of immunotherapy precision.Frontiers in immunology · 2025Pooled it
- Biomarkers for Recurrence and Prognosis in Metastatic Urothelial Cancer: Emerging Clinical Applications.Journal of Cancer · 2026Review
- Integration of Single-cell and bulk RNA sequencing data uncovers lymphatic metastasis-related prognostic genes and a predictive model in bladder cancer.Scientific reports · 2025Article
- Integrated machine learning and single-cell analysis reveal the prognostic and therapeutic potential of SUMOylation-related genes in ovarian cancer.Frontiers in immunology · 2025Article
- Prediction of bladder cancer prognosis and immune microenvironment assessment using machine learning and deep learning models.Heliyon · 2024Article
- Silencing immune-infiltrating biomarker CCDC80 inhibits malignant characterization and tumor formation in gastric cancer.BMC cancer · 2024Article
- Transcriptome Analysis Reveals Distinct Patterns Between the Invasive and Noninvasive Pituitary Neuroendocrine Tumors.Journal of the Endocrine Society · 2024Article
- Identification of an inflammation-related risk signature for prognosis and immunotherapeutic response prediction in bladder cancer.Scientific reports · 2024Article
- Prediction of immunotherapy response of bladder cancer with a pyroptosis-related signature indicating tumor immune microenvironment.Frontiers in pharmacology · 2024Article
- Single-Cell Sequencing Combined with Transcriptome Sequencing Constructs a Predictive Model of Key Genes in Multiple Sclerosis and Explores Molecular Mechanisms Related to Cellular Communication.Journal of inflammation research · 2024Article
- A transcriptome study of p53-pathway related prognostic gene signature set in bladder cancer.Heliyon · 2023Article
- Development of a Molecular-Subtype-Associated Immune Prognostic Signature That Can Be Recognized by MRI Radiomics Features in Bladder Cancer.Bioengineering (Basel, Switzerland) · 2023Article
- Article
- Identifying novel biomarkers associated with bladder cancer treatment outcomes.Frontiers in oncology · 2023Review
- Distinct tumor microenvironment landscapes of rectal cancer for prognosis and prediction of immunotherapy response.Cellular oncology (Dordrecht, Netherlands) · 2022Article
- Prognostic significance and immune characteristics of CMTM4 in hepatocellular carcinoma.BMC cancer · 2022Article
- Identification of the Tumor Infiltrating Lymphocytes (TILs) Landscape in Pure Squamous Cell Carcinoma of the Bladder.Cancers · 2022Article
- Article
- A single-sample mRNA molecular classification of bladder cancer predicting prognosis and response to immunotherapy.Translational andrology and urology · 2022Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Immune checkpoint inhibitors (ICIs) are novel treatments that significantly improve the survival time of MIBC patients, but immunotherapeutic responses are different among MIBC patients. Therefore, it is urgent to find predictive biomarkers that can accurately identify MIBC patients who are sensitive to ICIs. In this study, we computed the relative abundances of 24 immune cells based on the expression profiles of MIBC patients using single-sample gene set enrichment analysis (ssGSEA). Unsupervised clustering analysis of the 24 immune cells was performed to classify MIBC patients into different immune-infiltrating groups. Genome (gene mutation and copy number variation), transcriptome (mRNA, lncRNA, and miRNA), and functional enrichment were found to be heterogeneous among different immune-infiltrating groups. We identified 282 differentially expressed genes (DEGs) associated with immune infiltration by comparing the expression profiles of patients with different immune infiltration profiles, and 20 core prognostic DEGs were identified by univariate Cox regression analysis. An immune-relevant gene signature (TIM signature) consisting of nine key prognostic DEGs (CCDC80, CD3D, CIITA, FN1, GBP4, GNLY, SPINK1, UBD, and VIM) was constructed using least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Receiver operating characteristic (ROC) curves and subgroup analysis confirmed that the TIM signature was an ideal biomarker for predicting the prognosis of MIBC patients. Its value in predicting immunotherapeutic responses was also validated in The Cancer Genome Atlas (TCGA) cohort (AUC = 0.69, 95% CI = 0.63-0.74) and the IMvigor210 cohort (AUC = 0.64, 95% = 0.55-0.74). The TIM signature demonstrates a powerful ability to distinguish MIBC patients with different prognoses and immunotherapeutic responses, but more prospective studies are needed to assess its reliability in the future.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.