ReviewTrends in cancer2026
Spatially resolving cancer: from cell states to therapy.
Review in Trends in cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Deep Learning-Assisted Prioritization of Candidate Drug Targets in Tumors Using Spatial Multi-Omics.Biology · 2026Review
- Molecular subtyping-guided precision therapy for ESCC: biomarker-driven strategies and clinical translation pathways.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- Article
- Decoding the breast cancer microenvironment by spatial multi-omics: from architecture to clinical translation.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- Comparative Molecular Insights and Computational Modeling of Multiple Myeloma and Osteosarcoma.International journal of molecular sciences · 2026Review
- (Giga)TIME for the era of AI: virtual multiplex immunofluorescence from routine H&E for large populations.Signal transduction and targeted therapy · 2026Article
- Targeting lineage-specific heterogeneity and hypovascular-fibrotic barriers may enable precision immunotherapy in pituitary neuroendocrine tumors.Frontiers in immunology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Recent advances in spatial multi-omics technologies and analytical methods are transforming our understanding of how cancer cells and their microenvironments interact to drive critical processes such as lineage plasticity, immune evasion, and therapeutic resistance. By linking cancer cell states, lineage plasticity, clonal dynamics, oncogenic pathways, and cellular interactions to their spatial context, these innovations provide deep biological insights and reveal clinically relevant molecular programs and spatial biomarkers. This review highlights key breakthroughs in spatial profiling and computational approaches, including integration with computational pathology, multimodal data, and machine learning to uncover important biological insights. We discuss challenges in spatial multimodal data integration and emerging clinical applications, and we propose a roadmap to accelerate clinical translation and advance precision oncology through spatially resolved, actionable, molecular insights.
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.