Integrated spatial multi‐omics profiling of Fusobacterium nucleatum in breast cancer unveils its role in tumour microenvironment modulation and cancer progression

Clinical and Translational Medicine, Journal Year: 2025, Volume and Issue: 15(3)

Published: March 1, 2025

Abstract Tumour‐associated microbiota are integral components of the tumour microenvironment (TME). However, previous studies on intratumoral primarily rely bulk tissue analysis, which may obscure their spatial distribution and localized effects. In this study, we applied in situ spatial‐profiling technology to investigate breast cancer interactions with local TME. Using 5R 16S rRNA gene sequencing RNAscope FISH/CISH patients’ tissue, identified significant heterogeneity microbiota, Fusobacterium nucleatum ( F. ) predominantly cell‐rich areas. GeoMx digital profiling (DSP) revealed that regions colonized by exhibit influence expression RNAs proteins involved proliferation, migration invasion. vitro indicated co‐culture significantly stimulates proliferation cells. Integrative multi‐omics transcriptomic analyses highlighted MAPK signalling pathways as key altered pathways. By intersecting these datasets, VEGFD PAK1 emerged critical upregulated ‐positive regions, showing strong positive correlations pathway proteins. Moreover, upregulation was confirmed experiments, knockdown reduced ‐induced migration. conclusion, heterogeneity, colonization markedly altering cell protein promote progression These findings provide novel perspectives role cancer, identify potential therapeutic targets, lay foundation for future treatments. Key points Intratumoral exhibits within tissues. alters The is a mediator targets mitigate progression.

Language: Английский

Identification of key programmed cell death genes for predicting prognosis and treatment sensitivity in colorectal cancer

Frontiers in Oncology, Journal Year: 2024, Volume and Issue: 14

Published: Nov. 13, 2024

Colorectal cancer (CRC) ranks third in global incidence and second mortality. However, a comprehensive predictive model for CRC prognosis, immunotherapy response, drug sensitivity is still lacking. Various types of programmed cell death (PCD) are crucial occurrence, progression, treatment, indicating their potential as valuable predictors. Fourteen PCD genes were collected subjected to dimensionality reduction using regression methods identify key hub genes. Predictive models constructed validated based on bulk transcriptomes single-cell transcriptomes. Furthermore, the tumor microenvironment, profiles among patients with explored stratified by risk. A risk score incorporating FABP4, AQP8, NAT1 was developed across four independent datasets. Patients who had high-risk exhibited poorer prognosis. Unsupervised clustering algorithms used two molecular subtypes distinct features. The combined clinical features create nomogram superior performance. Additionally, scores decreased immune infiltration, higher stromal scores, reduced responsiveness first-line drugs compared low-risk patients. top ten non-clinical treating selected predicted IC50 values. Our results indicate efficacy its value predicting response immunotherapy, different CRC.

Language: Английский