ReviewOncology reviews2026
Addressing unmet clinical needs in treatment-resistant breast cancer: expanding the diagnostic-prognostic landscape through next-generation inflammatory signatures.
Review in Oncology reviews, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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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.
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0 citing papers in PubMed.
No citing paper in PubMed yet.
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Authors and funding
1 author.
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Abstract
Treatment-resistant breast cancer remains a major clinical challenge because conventional clinicopathological and molecular biomarkers incompletely capture the dynamic interactions between tumour cells, immunity, inflammation, and the systemic host response. Next-generation inflammatory signatures offer an opportunity to expand the diagnostic-prognostic landscape by integrating cellular, molecular, immune, and thromboinflammatory indicators with established tumour characteristics. This narrative review critically examines emerging evidence for neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, systemic immune-inflammation index, systemic inflammation response index, C-reactive protein, cytokines, tumour-associated macrophages, myeloid-derived suppressor cells, neutrophil extracellular traps, coagulation biomarkers, and liquid-biopsy-derived measures in treatment-resistant breast cancer. Particular attention is given to sources of heterogeneity, including population characteristics, tumour subtype, treatment exposure, comorbid inflammation, sampling time, specimen processing, analytical platforms, and inconsistent biomarker thresholds. The review further evaluates the transition from biomarker discovery to clinical decision support, highlighting the need for prospective multicentre validation, standardised analytical procedures, external validation of computational models, and integration with molecular subtyping, circulating tumour DNA, imaging, and immune profiling. Rather than interpreting inflammation as a static prognostic variable, longitudinal inflammatory trajectories may provide earlier signals of biological treatment resistance and complement conventional measures of disease progression. Future research should establish clinically actionable inflammatory combinations and evaluate biomarker-guided anti-inflammatory strategies alongside standard therapies. Ultimately, integrating inflammatory phenotypes with tumour molecular characteristics may facilitate earlier recognition of resistance and more precise, dynamic, and equitable breast cancer management.
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