Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1096238 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Gliomas and brain metastases (BrM) are associated with poor prognosis, necessitating a deeper understanding of brain tumor biology and the development of effective therapeutic strategies. While our group and others have demonstrated microbial presence in various tumors, recent controversies regarding cancer-type-specific intra-tumoral microbiota emphasize the importance of rigorous, orthogonal validation. This prospective, multi-institutional study included a total of 243 samples from 221 patients, comprising 168 glioma and BrM samples and 75 non-cancerous or tumor-adjacent tissues. Using stringent fluorescent in situ hybridization, immunohistochemistry, and high-resolution spatial imaging, we detected intracellular bacterial 16S rRNA and lipopolysaccharides in both glioma and BrM samples, localized to tumor, immune, and stromal cells. Custom 16S and metagenomic sequencing workflows identified taxa associated with intra-tumoral bacterial signals in the tumor microenvironment; however, standard culture methods did not yield readily cultivable microbiota. Spatial analyses revealed significant correlations between bacterial 16S signals and anti-microbial and immunometabolic signatures at regional, neighborhood, and cellular levels. Furthermore, intra-tumoral 16S bacterial signals showed sequence overlap with matched oral and gut microbiota, suggesting a possible connection with distant communities. Together, these findings introduce microbial elements as a component of the brain tumor microenvironment and lay the foundation for future mechanistic and translational studies.
2025-08-13 | GSE305393 | GEO
Project description:Gliomas and brain metastases (BrM) are associated with poor prognosis, necessitating a deeper understanding of brain tumor biology and the development of effective therapeutic strategies. While our group and others have demonstrated microbial presence in various tumors, recent controversies regarding cancer-type-specific intra-tumoral microbiota emphasize the importance of rigorous, orthogonal validation. This prospective, multi-institutional study included a total of 243 samples from 221 patients, comprising 168 glioma and BrM samples and 75 non-cancerous or tumor-adjacent tissues. Using stringent fluorescent in situ hybridization, immunohistochemistry, and high-resolution spatial imaging, we detected intracellular bacterial 16S rRNA and lipopolysaccharides in both glioma and BrM samples, localized to tumor, immune, and stromal cells. Custom 16S and metagenomic sequencing workflows identified taxa associated with intra-tumoral bacterial signals in the tumor microenvironment; however, standard culture methods did not yield readily cultivable microbiota. Spatial analyses revealed significant correlations between bacterial 16S signals and anti-microbial and immunometabolic signatures at regional, neighborhood, and cellular levels. Furthermore, intra-tumoral 16S bacterial signals showed sequence overlap with matched oral and gut microbiota, suggesting a possible connection with distant communities. Together, these findings introduce microbial elements as a component of the brain tumor microenvironment and lay the foundation for future mechanistic and translational studies.
2025-08-12 | GSE305267 | GEO
Project description:Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive disease with limited therapeutic options. The diversity and composition of intra-tumoral microbiota are associated with PDAC outcomes, and modulating the tumor microbiota has the potential to influence tumor growth and host-immune response. Here, we explore whether intervention with butyrate-producing probiotic can limit PDAC progression. By analyzing TCGA (PAAD) dataset, we found that tumoral butyrate-producing microbiota links to better prognosis and less aggressive features of PDAC. Intervention with Clostridium butyricum or its metabolite butyrate triggered superoxidative stress and intracellular lipid accumulation, which enhanced ferroptosis susceptibility of PDAC. Our study reveals a novel antitumor mechanism of butyrate, and suggests the therapeutic potential of butyrate-producing probiotics in PDAC.
2025-03-15 | GSE227418 | GEO
Project description:<p>Triple-negative breast cancer (TNBC) presents significant challenges to female</p><p>health owing to the lack of therapeutic targets and its poor prognosis. In recent</p><p>years, in the field of molecular pathology, there has been a growing focus on the</p><p>role of intra-tumoral microbial communities and metabolic alterations in tumor</p><p>cells. However, the precise mechanism through which microbiota and their</p><p>metabolites influence TNBC remains unclear and warrants further investigation.</p><p>In this study, we analyzed the microbial community composition in various</p><p>subtypes of breast cancer through 16S rRNA MiSeq sequencing of formalin-fixed,</p><p>paraffin-embedded (FFPE) tissue samples. Notably, Turicibacter, a microbe</p><p>associated with cancer response, exhibited a significantly higher abundance in</p><p>TNBC. Similarly, mass spectrometry-based metabolomic analysis revealed</p><p>substantial differences in specific metabolites, such as nutriacholic,</p><p>pregnanetriol, and cortol. Furthermore, we observed significant correlations</p><p>between the intra-tumoral</p>
2025-10-12 | MTBLS13119 | MetaboLights
Project description:Melanoma brain metastasis (MBM) response to treatment varies greatly among patients, affecting overall prognosis and survival. This study aims to provide a comprehensive multi-omics overview of MBM by investigating tumor tissue composition at spatial, proteomic and transcriptomic levels, elucidating the spatial tumor landscape, characterizing tumor tissue cell populations and identifying enriched signaling pathways in the MBM tumor tissue. We found higher inter-tumoral heterogeneity than intra-tumoral heterogeneity in MBM at the protein and transcriptional levels. The treatment-naive patient exhibited high intra-tumoral heterogeneity (ITH) compared to patient who received treatment, with ITH levels varying across neighboring regions in all patient tumors. Significant global protein and cell type enrichment associated with malignant cells, macrophages, CAFs, and immune cells was observed in MBM using cellular deconvolution and tumor microenvironment (TME) analysis. The presence of MBM cell-type specific gene signatures, and enriched pathways identified using ST and bulk-seq provide an essential framework for understanding tumor composition and potential treatment-related effects in each MBM patient tumor. Taken together, our results provide a comprehensive spatial and molecular view of intra-tumoral and inter-tumoral heterogeneity in MBM, potentially guiding personalized treatment strategies in MBM therapy.
2025-07-17 | GSE275731 | GEO
Project description:Our study provides a comprehensive multiomics overview of each patient’s tumor, revealing tumor cell types, proteomics, and transcriptomic changes related to melanoma brain metastasis (MBM). Here, we have applied the HiRIEF pre-fractionation and tandem mass tags (TMT)-16plex based peptide quantification to generate proteomes of multiple neighboring regions within each MBM tumor tissue. PCA and Hierarchical clustering analysis illustrated higher inter-tumoral heterogeneity than intra-tumoral heterogeneity of MBM at the protein levels, as lesions from the same patients are grouped into a single cluster. The treatment-naive patient (P3) exhibited high intra-tumoral heterogeneity (ITH) compared to treated ones, with ITH levels varying across neighboring regions in patient tumors. Differential expression analysis highlighted enriched protein and gene clusters for all patient comparisons, including innate immune proteins, macrophage activation, T- and B-cell signaling, and key cancer pathways (e.g., epithelial-mesenchymal transition, cell adhesion, notch signaling, oxidative phosphorylation and cell cycle checkpoints). Genes involved in functional processes characteristic of MBM cell types, tumor-immune interactions, and signaling mechanisms were more highly correlated with their protein levels. Overall, our results provide a comprehensive spatial and molecular view of intra-tumoral and inter-tumoral heterogeneity in MBM.
2025-07-21 | PXD055170 | Pride
Project description:Our study provides a comprehensive multiomics overview of each patient’s tumor, revealing tumor cell types, proteomics, and transcriptomic changes related to melanoma brain metastasis (MBM). Here, we have applied the HiRIEF pre-fractionation and tandem mass tags (TMT)-16plex based peptide quantification to generate proteomes of multiple neighboring regions within each MBM tumor tissue. PCA and Hierarchical clustering analysis illustrated higher inter-tumoral heterogeneity than intra-tumoral heterogeneity of MBM at the protein levels, as lesions from the same patients are grouped into a single cluster. The treatment-naive patient (P3) exhibited high intra-tumoral heterogeneity (ITH) compared to treated ones, with ITH levels varying across neighboring regions in patient tumors. Differential expression analysis highlighted enriched protein and gene clusters for all patient comparisons, including innate immune proteins, macrophage activation, T- and B-cell signaling, and key cancer pathways (e.g., epithelial-mesenchymal transition, cell adhesion, notch signaling, oxidative phosphorylation and cell cycle checkpoints). Genes involved in functional processes characteristic of MBM cell types, tumor-immune interactions, and signaling mechanisms were more highly correlated with their protein levels. Overall, our results provide a comprehensive spatial and molecular view of intra-tumoral and inter-tumoral heterogeneity in MBM.
2025-07-21 | PXD055089 | Pride
Project description:Our study provides a comprehensive multiomics overview of each patient’s tumor, revealing tumor cell types, proteomics, and transcriptomic changes related to melanoma brain metastasis (MBM). Here, we have applied the HiRIEF pre-fractionation and tandem mass tags (TMT)-16plex based peptide quantification to generate proteomes of multiple neighboring regions within each MBM tumor tissue. PCA and Hierarchical clustering analysis illustrated higher inter-tumoral heterogeneity than intra-tumoral heterogeneity of MBM at the protein levels, as lesions from the same patients are grouped into a single cluster. The treatment-naive patient (P3) exhibited high intra-tumoral heterogeneity (ITH) compared to treated ones, with ITH levels varying across neighboring regions in patient tumors. Differential expression analysis highlighted enriched protein and gene clusters for all patient comparisons, including innate immune proteins, macrophage activation, T- and B-cell signaling, and key cancer pathways (e.g., epithelial-mesenchymal transition, cell adhesion, notch signaling, oxidative phosphorylation and cell cycle checkpoints). Genes involved in functional processes characteristic of MBM cell types, tumor-immune interactions, and signaling mechanisms were more highly correlated with their protein levels. Overall, our results provide a comprehensive spatial and molecular view of intra-tumoral and inter-tumoral heterogeneity in MBM.
2025-07-21 | PXD055172 | Pride
Project description:Genome wide DNA methylation profiling of normal and tumoral urological tissues (Prostate, Kidney and Bladder). The Illumina Infinium 450k Human DNA methylation Beadchip was used to obtain DNA methylation profiles across approximately 27,000 CpGs in urological fresh frozzen tissue samples. Samples included morphologically normal samples of each tissue and tumor samples. Kidney: 6 normal and 17 tumor samples; Bladder: 5 normal and 25 tumor samples; Prostate: 5 Normal and 25 tumor samples.
2017-03-09 | GSE52955 | GEO
Project description:The inter-patient variability of tumor proteomes has been investigated on a large scale but many tumors display also intra-tumoral heterogeneity (ITH) regarding morphological and genetic features. To what extent the local proteome of tumors intrinsically differs remains largely unknown. Here, we used hepatocellular carcinoma (HCC) as a model system, to quantify both inter- and intra-tumor heterogeneity across human patient specimens with spatial resolution. We first defined proteomic features that robustly distinguish neoplastic from the directly adjacent non-neoplastic tissue by integrating proteomic data from human patient samples and genetically defined mouse models with available gene expression data. We then demonstrated the existence of intra-tumoral variations in protein abundance that re-occur across different patient samples, and affect clinically relevant proteins, even in the absence of obvious morphological differences or genetic alterations. Our work demonstrates the suitability and the benefits of using mass spectrometry based proteomics to analyze diagnostic tumor specimens with spatial resolution
2018-01-24 | PXD007052 | Pride