OMICS. 2025 Aug 19. doi: 10.1177/15578100251366980. Online ahead of print.

ABSTRACT

Ferroptosis, an iron-dependent form of oxidative cell death, plays a critical role in cancer progression and immune regulation. However, the functional connections of ferroptosis with specific immune cell types remain poorly defined, limiting the future possibilities to harness ferroptosis for cancer biology, diagnosis, and treatment. To address this knowledge gap, we conducted an integrated transcriptomic analysis to investigate ferroptosis-related immune dynamics in gastric cancer (GC). We utilized GC datasets from The Cancer Genome Atlas-stomach adenocarcinoma (n = 412) and the GSE66229 (n = 300) that were clustered into three GC immune subtypes based on single-sample Gene Set Enrichment Analysis scores of 29 immune gene sets. Bulk RNA-seq analysis revealed that the immune-inflamed subtype (HIS) of tumor samples in both GC datasets exhibited the highest ferroptosis enrichment and showed a positive correlation with activated mast cells and neutrophils. Given the regulatory role of mast cells in the tumor microenvironment (TME), particularly in recruiting neutrophils, we further examined their link to ferroptosis. In a fibroblast-mast cell coculture RNA-seq data (GSE223179), fibroblasts exhibited increased ferroptosis enrichment, supporting a mast cell-mediated influence. Single-cell RNA-seq data confirmed stronger interactions between mast cells and fibroblasts in GC compared to normal tissues. Specifically, they revealed a positive correlation between mast cell activity and ferroptosis enrichment in tumor-associated fibroblasts. In conclusion, these findings suggest that mast cells may promote ferroptosis in the TME through paracrine signaling, possibly via annexin and cyclophilin A. By uncovering this novel pathophysiological axis, our study reveals a previously unrecognized role of mast cells in regulating ferroptosis within the TME. The findings call for translational and experimental medical research and have potential implications for innovation toward GC diagnostics and therapeutics.

PMID:40831393 | DOI:10.1177/15578100251366980

Sci Prog. 2025 Jul-Sep;108(3):368504251362350. doi: 10.1177/00368504251362350. Epub 2025 Aug 19.

ABSTRACT

Breast cancer recurrence remains a major cause of mortality, with up to 30% of early-stage patients relapsing as incurable metastatic disease. Conventional surveillance with imaging and serum markers (CA15-3, CEA) lacks the sensitivity and specificity to detect minimal residual disease. This narrative review examines non-invasive biomarkers such as circulating tumor DNA (ctDNA), circulating tumor cells (CTCs) and exosomes and the technologies enhancing their performance. Droplet digital PCR and next-generation sequencing detect ctDNA at allele frequencies below 0.1%, identifying molecular relapse a median of 10-12 months before radiologic progression. Microfluidic and affinity-based platforms isolate CTCs with over 75% sensitivity in metastatic settings. Nanoengineered sensors and standardized workflows improve exosome isolation, revealing miRNA and protein signatures predictive of recurrence. Proteomic and metabolomic profiling identify dysregulated metabolic pathways and protein networks, offering functional insights that complement molecular assays. Integrative multi-omics approaches merge genomic, transcriptomic, proteomic and metabolomic data; machine-learning frameworks detect subtle patterns and correlations, enabling dynamic, personalized surveillance. By detecting molecular and functional biomarkers early, clinicians can tailor therapy, monitor treatment response and intervene promptly. Challenges include low analyte abundance, assay variability, high costs and lack of standardized protocols, limiting clinical adoption. Prospective validation in large cohorts is critical. We highlight ongoing clinical trials such as ctDNA-guided adjuvant therapy and CTC-driven stratification studies that aim to establish clinical utility. Non-invasive biomarker platforms could shift breast cancer follow-up from reactive detection to proactive intervention, ultimately improving survival and quality of life through personalized, real-time monitoring.

PMID:40831186 | PMC:PMC12368403 | DOI:10.1177/00368504251362350