ReviewClinical and translational medicine2025
Cancer therapy resistance from a spatial-omics perspective.
Review in Clinical and translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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
13 citing papers in PubMed.
- Advances in deciphering intratumoral versus peritumoral heterogeneity of infiltrating lymphocytes in pancreatic cancer: a spatial perspective.Translational oncology · 2026Review
- Pharmacologic Resistance in Soft Tissue Sarcomas: Mechanisms, Biomarkers, and Translational Therapeutic Strategies.Cancers · 2026Review
- Artificial Intelligence for Spatial Immunometabolic Analysis of the Tumor Microenvironment: Current Evidence and Future Directions.Current issues in molecular biology · 2026Review
- Transforming Gastric Biopsy Diagnostics: Integrating Omics Technologies and Artificial Intelligence.Biomedicines · 2026Article
- CA9+ cancer-associated fibroblasts cooperate with SPP1+ tumor-associated macrophages driving immune resistance in triple-negative breast cancer.Cellular and molecular life sciences : CMLS · 2026Article
- Tumor heterogeneity as a driver of drug resistance and its implications for personalized therapy.Cancer drug resistance (Alhambra, Calif.) · 2026Review
- Multiomics Characterization of GCSH + Macrophages Reveals Therapeutic Vulnerabilities and Immune-Metabolic Crosstalk in Triple-Negative Breast Cancer.Human mutation · 2026Article
- Harnessing transcriptomics for discovery of natural products to overcome acquired cancer resistance.Archives of pharmacal research · 2026Review
- Harnessing cellular immunotherapy for cholangiocarcinoma: an integrated roadmap for overcoming resistance.Frontiers in immunology · 2026Review
- Tumor-immune crosstalk in lung cancer: emerging roles of long non-coding RNAs.Frontiers in immunology · 2026Review
- Cancer therapy resistance from a spatial-omics perspective.Clinical and translational medicine · 2025Review
- Terminally exhausted CD8Frontiers in immunology · 2025Review
- Metabolic collusion driving immune evasion in cholangiocarcinoma: unmasking the dual control of the immuno-metabolic microenvironment.Frontiers in immunology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Cancer therapy resistance (CTR) remains a significant challenge in oncology. Traditional methods like imaging, liquid biopsies and conventional omics analyses provide valuable insights, but lack the spatial resolution to fully characterise heterogeneity of tumour and the tumour microenvironment (TME). Recent advancements in spatial omics technologies offer unprecedented insights into the spatial organisation of tumours and TME. In this review, we summarise current methodologies for CTR research and highlight how spatial omics technologies and computational methods are revolutionising our understanding of CTR mechanisms. We also summarise recent studies leveraging spatial omics to uncover novel insights into CTR across various cancer types and therapies and discuss future opportunities.
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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.