Trial reportPLoS medicine2017
Contribution of systemic and somatic factors to clinical response and resistance to PD-L1 blockade in urothelial cancer: An exploratory multi-omic analysis.
Trial report in PLoS medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02108652 (A Phase II, Multicenter, Single-Arm Study of Atezolizumab in Patients With Locally Advanced or Metastatic Urothelial Bladder Cancer), which is not on this map. Cited by 224 papers, 6 of them syntheses 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.
A Phase II, Multicenter, Single-Arm Study of Atezolizumab in Patients With Locally Advanced or Metastatic Urothelial Bladder Cancer
Who cites it
224 citing papers in PubMed, 6 syntheses or guidelines pooled it, 365 citations in OpenAlex.
- Predicting immunotherapy response of advanced bladder cancer through a meta-analysis of six independent cohorts.Nature communications · 2025Pooled it
- Transcriptomic datasets of cancer patients treated with immune-checkpoint inhibitors: a systematic review.Journal of translational medicine · 2022Pooled it
- Meta-analysis of tumor- and T cell-intrinsic mechanisms of sensitization to checkpoint inhibition.Cell · 2021Pooled it
- Emerging Blood-Based Biomarkers for Predicting Response to Checkpoint Immunotherapy in Non-Small-Cell Lung Cancer.Frontiers in immunology · 2020Pooled it
- Molecular Biomarkers of Response to PD-1/ PD-L1 Immune Checkpoint Blockade in Advanced Bladder Cancer.Bladder cancer (Amsterdam, Netherlands) · 2019Pooled it
- The Predictive Value of Tumor Mutation Burden on Efficacy of Immune Checkpoint Inhibitors in Cancers: A Systematic Review and Meta-Analysis.Frontiers in oncology · 2019Pooled it
- Neoadjuvant or concurrent atezolizumab with chemoradiation for locally advanced cervical cancer: a randomized phase I trial.Nature communications · 2025Trial
- Trial
- High Response Rate and Durability Driven by HLA Genetic Diversity in Patients with Kidney Cancer Treated with Lenvatinib and Pembrolizumab.Molecular cancer research : MCR · 2021Trial
- Pan-cancer analysis of longitudinal metastatic tumors reveals genomic alterations and immune landscape dynamics associated with pembrolizumab sensitivity.Nature communications · 2021Trial
- Randomized Phase II Trial of Nivolumab Versus Nivolumab and Ipilimumab for Recurrent or Persistent Ovarian Cancer: An NRG Oncology Study.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2020Trial
- PD-1 Blockade in Advanced Adrenocortical Carcinoma.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2020Trial
- The Immune Checkpoint Inhibitors Journey: From Early Promise to Lasting Impact.Journal of immunotherapy and precision oncology · 2026Review
- Clinical translation of senescence-related pan-cancer multi-omics: tools for assessment and immunotherapy prediction.Cancer gene therapy · 2026Article
- Generalizable AI predicts immunotherapy outcomes across cancers and treatments.Nature medicine · 2026Article
- ICIsAtlas reveals a suppressive NK cell niche in pan-cancer immunotherapy profiles.Communications biology · 2026Article
- Review
- AGPAT3 reshapes tumor cell vulnerability to IFNγ-mediated ferroptosis and enhances immunotherapy efficacy through lipid remodeling.Journal for immunotherapy of cancer · 2026Article
- TCR sequencing in cancer immunology and immunotherapy: what, when, where, why, and how.Journal for immunotherapy of cancer · 2026Review
- Harnessing Anoikis-Related Gene Signatures for Immunotherapy Precision: A Machine Learning-Driven Predictive and Prognostic Model.ACS omega · 2026Article
164 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
21 authors at 5 institutions in 1 country.
Funding
Abstract
backgroundInhibition of programmed death-ligand 1 (PD-L1) with atezolizumab can induce durable clinical benefit (DCB) in patients with metastatic urothelial cancers, including complete remissions in patients with chemotherapy refractory disease. Although mutation load and PD-L1 immune cell (IC) staining have been associated with response, they lack sufficient sensitivity and specificity for clinical use. Thus, there is a need to evaluate the peripheral blood immune environment and to conduct detailed analyses of mutation load, predicted neoantigens, and immune cellular infiltration in tumors to enhance our understanding of the biologic underpinnings of response and resistance. METHODS AND
findingsThe goals of this study were to (1) evaluate the association of mutation load and predicted neoantigen load with therapeutic benefit and (2) determine whether intratumoral and peripheral blood T cell receptor (TCR) clonality inform clinical outcomes in urothelial carcinoma treated with atezolizumab. We hypothesized that an elevated mutation load in combination with T cell clonal dominance among intratumoral lymphocytes prior to treatment or among peripheral T cells after treatment would be associated with effective tumor control upon treatment with anti-PD-L1 therapy. We performed whole exome sequencing (WES), RNA sequencing (RNA-seq), and T cell receptor sequencing (TCR-seq) of pretreatment tumor samples as well as TCR-seq of matched, serially collected peripheral blood, collected before and after treatment with atezolizumab. These parameters were assessed for correlation with DCB (defined as progression-free survival [PFS] >6 months), PFS, and overall survival (OS), both alone and in the context of clinical and intratumoral parameters known to be predictive of survival in this disease state. Patients with DCB displayed a higher proportion of tumor-infiltrating T lymphocytes (TIL) (n = 24, Mann-Whitney p = 0.047). Pretreatment peripheral blood TCR clonality below the median was associated with improved PFS (n = 29, log-rank p = 0.048) and OS (n = 29, log-rank p = 0.011). Patients with DCB also demonstrated more substantial expansion of tumor-associated TCR clones in the peripheral blood 3 weeks after starting treatment (n = 22, Mann-Whitney p = 0.022). The combination of high pretreatment peripheral blood TCR clonality with elevated PD-L1 IC staining in tumor tissue was strongly associated with poor clinical outcomes (n = 10, hazard ratio (HR) (mean) = 89.88, HR (median) = 23.41, 95% CI [2.43, 506.94], p(HR > 1) = 0.0014). Marked variations in mutation loads were seen with different somatic variant calling methodologies, which, in turn, impacted associations with clinical outcomes. Missense mutation load, predicted neoantigen load, and expressed neoantigen load did not demonstrate significant association with DCB (n = 25, Mann-Whitney p = 0.22, n = 25, Mann-Whitney p = 0.55, and n = 25, Mann-Whitney p = 0.29, respectively). Instead, we found evidence of time-varying effects of somatic mutation load on PFS in this cohort (n = 25, p = 0.044). A limitation of our study is its small sample size (n = 29), a subset of the patients treated on IMvigor 210 (NCT02108652). Given the number of exploratory analyses performed, we intend for these results to be hypothesis-generating.
conclusionsThese results demonstrate the complex nature of immune response to checkpoint blockade and the compelling need for greater interrogation and data integration of both host and tumor factors. Incorporating these variables in prospective studies will facilitate identification and treatment of resistant patients.
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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.