ReviewCancer metastasis reviews2025
Spatial proteomics for investigating solid tumor resistance mechanisms.
Review in Cancer metastasis reviews, 2025. 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.
- Crosstalk between innate immune signaling pathways and integrated TLR, NLRP3 inflammasome, cGAS-STING, and NF-κB networks in sepsis.Frontiers in cell and developmental biology · 2026Review
- Spatial AI in cancer: mapping immune evasion topology through multi-modal omics and deep learning.Frontiers in oncology · 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
9 authors.
Funding
Abstract
Spatial proteomics technologies have been pivotal in profiling tumor immune microenvironments at single-cell resolution, advancing our understanding of cancer biology, identifying key cell populations in solid tumors, and predicting treatment responses. Although immune checkpoint and molecular inhibitors have revolutionized cancer care, resistance mechanisms remain a major therapeutic challenge that hinder productive responses in a notable fraction of cancer patients. In this review, we outline current spatial proteomics and computational analysis tools for studying the tumor immune microenvironment and discuss how spatial proteomics techniques have helped elucidate cancer resistance mechanisms across multiple tumor types. In this process, we highlight the importance of investigating immunosuppressive cell populations that can mediate cancer resistance, specifically with regard to their localization, protein signatures, and surrounding interactions. Finally, we provide a look ahead at future applications of artificial intelligence/machine learning and multi-omics approaches that will help further propel our understanding of cancer resistance mechanisms through spatial biology research.
Indexed as
Identifiers
41060425What 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.