Nat Commun. 2025 Aug 22;16(1):7827. doi: 10.1038/s41467-025-63146-2.

ABSTRACT

While dysregulation of polyamine metabolism is frequently observed in cancer, it is unknown how polyamines alter the tumor microenvironment (TME) and contribute to therapeutic resistance. Analysis of polyamines in the plasma of pancreatic cancer patients reveals that spermine levels are significantly elevated and correlate with poor prognosis. Using a multi-omics approach, we identify Serpinb9 as a vulnerability in spermine metabolism in pancreatic cancer. Serpinb9, a serine protease inhibitor, directly interacts with spermine synthase (SMS), impeding its lysosome-mediated degradation and thereby augmenting spermine production and secretion. Mechanistically, the accumulation of spermine in the TME alters the metabolic landscape of immune cells, promoting CD8⁺ T cell dysfunction and pro-tumor polarization of macrophages, thus creating an immunosuppressive microenvironment. Small peptides that disrupt the Serpinb9-SMS interaction significantly enhance the efficacy of immune checkpoint blockade therapy. Together, our findings suggest that targeting spermine metabolism is a promising strategy to improve pancreatic cancer immunotherapy.

PMID:40846845 | PMC:PMC12373741 | DOI:10.1038/s41467-025-63146-2

Cancer Med. 2024 Oct;13(20):e70346. doi: 10.1002/cam4.70346.

ABSTRACT

BACKGROUND: For early detection and postoperative monitoring of upper tract urothelial carcinoma (UTUC), the traditional detection method was limited to its invasiveness and insufficient sensitivity. We aim to use urine tumour DNA (utDNA) for detecting minimal residual disease (MRD), early diagnosis and perioperative monitoring in UTUC.

METHOD: We previously established a utDNA multidimensional bioinformatic valuation model, named utLIFE, using low-coverage whole-genome sequencing and targeted deep sequencing. This prospective cohort enrolled 93 patients diagnosed with UTUC without metastasis. We collected morning urine samples on the day of surgery and the discharge day after the operation for utLIFE testing. In addition, we also enrolled 80 healthy controls to further validate the specificity of the utLIFE model in the study.

RESULTS: The utLIFE of preoperative samples could discriminate UTUC with high specificity (96.25%, 77/80), and high sensitivity (96.77%, 90/93) regardless of stage and grade. The sensitivity of utLIFE was significantly higher than urine cytology (p < 0.001) and fluorescence in situ hybridisation (FISH) (p < 0.001) (N = 19), especially in early-stage and low-grade UTUC. Postoperative utLIFE scores were significantly decreased compared with those of preoperative samples (79 vs. 36, p < 0.001), indicating its association with tumour burden. For special pathology types, utLIFE performed less well in sensitivity and perioperative alteration.

CONCLUSION: In conclusion, we established a bioinformatic utDNA valuation model, utLIFE, which was validated to be a rapid and noninvasive approach with high sensitivity for early detection and MRD monitoring for UTUC.

PMID:39440792 | PMC:PMC11497171 | DOI:10.1002/cam4.70346