ReviewNPJ precision oncology2026
Artificial intelligence-assisted spatial omics-based biomimetic nanoplatform for intelligent and precise intervention in the immunosuppressive core region of ovarian cancer.
Review in NPJ precision oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Review
- Deciphering mitochondrial metabolic vulnerabilities in ovarian clear cell carcinoma with mass spectrometry-based clinical proteomics.Expert review of proteomicsReview
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
Ovarian cancer (OC) ranks among the most aggressive malignancies of the female reproductive system. The immunosuppressive tumor microenvironment (TME) and pronounced spatial heterogeneity significantly restrict the efficacy of immunotherapy. Recent advances in single-cell omics and spatial transcriptomics (ST) have enabled the identification of immunosuppressive core regions within the TME at molecular and spatial levels. These regions often contain "exclusion structures" composed of regulatory T cells (Tregs), tumor-associated macrophages (TAMs), and myeloid-derived suppressor cells (MDSCs) in hypoxia-enriched niches. To achieve precise therapeutic modulation of these core microregions, researchers have developed biomimetic nanodrug platforms such as cell membrane-coated systems and exosome-based carriers. These platforms deliver immunoregulatory agents targeting programmed death-ligand 1 (PD-L1), transforming growth factor-beta (TGF-β), and colony-stimulating factor 1 receptor (CSF1R), with enhanced efficiency and adaptability through multi-responsive mechanisms. The paper provides a comprehensive review of the spatial organization mechanisms, omics-based identification methods, and signaling network pathways that define the immunosuppressive core regions in OC. It also summarizes the design principles and adaptive strategies of biomimetic platforms and introduces an artificial intelligence (AI)-assisted closed-loop therapeutic framework encompassing identification, delivery, and feedback to support individualized and precise immunotherapy. Although the approach demonstrates strong potential for multidimensional integration, several challenges remain, including the standardization of spatial atlases, the stability of delivery systems, and cross-platform compatibility, all of which require further technological advancement.
Identifiers
What Socratic 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 Socratic graph.