NPJ Precis Oncol. 2025 Feb 24;9(1):50. doi: 10.1038/s41698-025-00834-8.

ABSTRACT

Disulfidptosis, a newly discovered cell death mode distinct from other programmed cell death in lung and kidney cancer cells, is defined as extensive disulfide bonds to actin cytoskeleton proteins, leading to actin contraction and cytoskeletal disruption cell death. New cell death pattern discoveries often drive advances in tumor research. Therefore, the present study attempted to decipher the manifestation and importance of disulfidptosis in pan-cancer. Combining Clinical specimen immunofluorescence staining, single-cell analyses, and spatial transcriptome analyses, we demonstrated the manifestation of disulfidptosis in pan-cancer. Multi-omics analysis has revealed that genomic variants and DNA methylation in DRGs can affect the prognosis of patients with pan-cancer. The nomogram based on the DRGs Score model could accurately predict the prognosis of patients with pan-cancer. PF-562271, EHT-1864, and IPA-3 are potential therapeutic agents targeting disulfidptosis. Collectively, this study deciphered for the first time the importance of disulfidptosis for pan-cancer and developed the DRGs Score model that can assist clinicians in accurately predicting the prognosis and guiding individualized treatment of pan-cancer patients.

PMID:39994355 | DOI:10.1038/s41698-025-00834-8

Cell Metab. 2025 Jan 28:S1550-4131(24)00495-9. doi: 10.1016/j.cmet.2024.12.013. Online ahead of print.

ABSTRACT

Immune checkpoint blockade (ICB) therapy has revolutionized cancer treatment but remains effective in only a subset of patients. Emerging evidence suggests that the gut microbiome and its metabolites critically influence ICB efficacy. In this study, we performed a multi-omics analysis of fecal microbiomes and metabolomes from 165 patients undergoing anti-programmed cell death protein 1 (PD-1)/programmed death ligand 1 (PD-L1) therapy, identifying microbial and metabolic entities associated with treatment response. Integration of data from four public metagenomic datasets (n = 568) uncovered cross-cohort microbial and metabolic signatures, validated in an independent cohort (n = 138). An integrated predictive model incorporating these features demonstrated robust performance. Notably, we characterized five response-associated enterotypes, each linked to specific bacterial taxa and metabolites. Among these, the metabolite phenylacetylglutamine (PAGln) was negatively correlated with response and shown to attenuate anti-PD-1 efficacy in vivo. This study sheds light on the interplay among the gut microbiome, the gut metabolome, and immunotherapy response, identifying potential biomarkers to improve treatment outcomes.

PMID:39909032 | DOI:10.1016/j.cmet.2024.12.013