Single-cell and spatial omics in urologic cancer immunotherapy: bibliometric and registry mapping with an exploratory full-text assessment
Abstract
BackgroundSingle-cell and spatial omics can inform research on immunotherapy response and resistance. We mapped publication activity and ClinicalTrials.gov study designs and explored evidence types in a targeted full-text subset of urologic cancer studies.MethodsWeb of Science Core Collection and Scopus records published in 2008–2025 were locked on 13 July 2026. Revision-stage eligibility reconciliation retained 538 records; 466 native Web of Science records supplied temporal-analysis inputs. A targeted full-text assessment was supplemented by a random audit of 100 previously non-selected records and independent reassessment of 40 selected studies. Evidence classes included treatment-exposed human data, association replication, computational proxies, experimental mechanisms, and prognosis. ClinicalTrials.gov records were analyzed separately.ResultsThe 538-record corpus included 440 publications from 2023–2025 (81.8%). The targeted assessment included 122 original studies among 135 assessed reports. In the random audit, 15/100 records were C1 or C2b: three C1 and 12 C2b. One C1 report contained cell-level descriptive evidence without a patient-level marker–outcome analysis. The initial evidence-class agreement was 92/100 (Cohen’s kappa, 0.890) in this audit and 31/40 (kappa, 0.682) in the selected-study reassessment. Public-cohort reuse and exploratory analyses limited clinical interpretation. Of 10 ClinicalTrials.gov records, one had a verified reported omics component, eight documented planned or ongoing components, and one was withdrawn without accrual.ConclusionBibliometric activity increased in the retained corpus. The random audit identified treatment-related reports missed by targeted retrieval, limiting claims about evidence completeness. Cell-level descriptions, patient-level associations, and locked-model validation require separate interpretation. Neither selected-study proportions nor bibliometric attention establishes field-wide clinical maturity. Registry plans require component-specific verification of implementation and reporting.
Related
- Volumetric analysis and MRI radiomics for response assessment in canine glioma immunotherapy: an exploratory feasibility study
- Early Assessment of Circulating Tumor Cells and Their PD-L1 Expression as Predictive Biomarkers in Metastatic Non-Small Cell Lung Cancer Patients Treated with Immunotherapy: An Exploratory Study
- An Exploratory Study: Can Vision-Enabled Large Language Models Interpret Selected Static Urologic Images?
- Global trends and knowledge evolution of tertiary lymphoid structures in cancer immunotherapy: a bibliometric and visualization analysis
- Circulating and tumor microenvironment immunomarkers associate with immunotherapy efficacy in advanced bladder urothelial carcinoma: an exploratory multicenter study integrating genomic and immunophenotypic profiling
BibTeX
@article{zhou2026singlecell,
title = {{Single-cell and spatial omics in urologic cancer immunotherapy: bibliometric and registry mapping with an exploratory full-text assessment}},
author = {Danhong Zhou and Junhua Li and Chenhao Tang and Yanbin Wang and Chen Song},
journal = {Frontiers in Pharmacology},
year = {2026},
month = nov,
doi = {10.3389/fphar.2026.2004169},
url = {https://www.frontiersin.org/articles/10.3389/fphar.2026.2004169},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Single-cell and spatial omics in urologic cancer immunotherapy: bibliometric and registry mapping with an exploratory full-text assessment
AU - Danhong Zhou
AU - Junhua Li
AU - Chenhao Tang
AU - Yanbin Wang
AU - Chen Song
PY - 2026
DA - 2026/11/03
JO - Frontiers in Pharmacology
DO - 10.3389/fphar.2026.2004169
UR - https://www.frontiersin.org/articles/10.3389/fphar.2026.2004169
AB - BackgroundSingle-cell and spatial omics can inform research on immunotherapy response and resistance. We mapped publication activity and ClinicalTrials.gov study designs and explored evidence types in a targeted full-text subset of urologic cancer studies.MethodsWeb of Science Core Collection and Scopus records published in 2008–2025 were locked on 13 July 2026. Revision-stage eligibility reconciliation retained 538 records; 466 native Web of Science records supplied temporal-analysis inputs. A targeted full-text assessment was supplemented by a random audit of 100 previously non-selected records and independent reassessment of 40 selected studies. Evidence classes included treatment-exposed human data, association replication, computational proxies, experimental mechanisms, and prognosis. ClinicalTrials.gov records were analyzed separately.ResultsThe 538-record corpus included 440 publications from 2023–2025 (81.8%). The targeted assessment included 122 original studies among 135 assessed reports. In the random audit, 15/100 records were C1 or C2b: three C1 and 12 C2b. One C1 report contained cell-level descriptive evidence without a patient-level marker–outcome analysis. The initial evidence-class agreement was 92/100 (Cohen’s kappa, 0.890) in this audit and 31/40 (kappa, 0.682) in the selected-study reassessment. Public-cohort reuse and exploratory analyses limited clinical interpretation. Of 10 ClinicalTrials.gov records, one had a verified reported omics component, eight documented planned or ongoing components, and one was withdrawn without accrual.ConclusionBibliometric activity increased in the retained corpus. The random audit identified treatment-related reports missed by targeted retrieval, limiting claims about evidence completeness. Cell-level descriptions, patient-level associations, and locked-model validation require separate interpretation. Neither selected-study proportions nor bibliometric attention establishes field-wide clinical maturity. Registry plans require component-specific verification of implementation and reporting.
SN - 1663-9812
ER -