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Project description:BackgroundMedulloblastoma (MB) is a malignant brain tumor in childhood. It comprises 4 subgroups with different clinical behaviors. The aim of this study was to characterize the transcriptomic landscape of MB, both at the level of individual tumors as well as in large patient cohorts.MethodsWe used a combination of single-cell transcriptomics, cell culture models and biophysical methods such as nanoparticle tracking analysis and electron microscopy to investigate intercellular communication in the MB tumor niche.ResultsTumor cells of the sonic hedgehog (SHH)-MB subgroup show a differentiation blockade. These cells undergo extensive metabolic reprogramming. The gene expression profiles of individual tumor cells show a partial convergence with those of tumor-associated glial and immune cells. One possible cause is the transfer of extracellular vesicles (EVs) between cells in the tumor niche. We were able to detect EVs in co-culture models of MB tumor cells and oligodendrocytes. We also identified a gene expression signature, EVS, which shows overlap with the proteome profile of large oncosomes from prostate cancer cells. This signature is also present in MB patient samples. A high EVS expression is one common characteristic of tumors that occur in high-risk patients from different MB subgroups or subtypes.ConclusionsWith EVS, our study uncovered a novel gene expression signature that has a high prognostic significance across MB subgroups.
| S-EPMC8041350 | biostudies-literature
Project description:Background: Medulloblastoma (MB) is a malignant brain tumor in childhood. It comprises four subgroups with different clinical behaviors. The aim of this study was to characterize the transcriptomic landscape of MB, both at the level of individual tumors as well as in large patient cohorts. Methods: We used a combination of single-cell transcriptomics, cell culture models and biophysical methods such as nanoparticle tracking analysis (NTA) and electron microscopy (EM), to investigate intercellular communication in the MB tumor niche. Results: Tumor cells of the SHH-MB subgroup show a differentiation blockade. These cells undergo extensive metabolic reprogramming. The gene expression profiles of individual tumor cells show a partial convergence with those of tumor-associated glial and immune cells. One possible cause is the transfer of extracellular vesicles (EVs) between cells in the tumor niche. We were able to detect EVs in co-culture models of MB tumor cells and oligodendrocytes. We also identified a gene expression signature, EVS, which shows overlap with the proteome profile of large oncosomes from prostate cancer cells. This signature is also present in MB patient samples. A high EVS expression is one common characteristic of tumors that occur in high-risk patients from otherwise very different MB subgroups or subtypes. Conclusions: With EVS, our study uncovered a novel gene expression signature that has a high prognostic significance across MB subgroups.
2020-12-11 | GSE159763 | GEO
Project description:Background: Medulloblastoma (MB) is a malignant brain tumor in childhood. It comprises four subgroups with different clinical behaviors. The aim of this study was to characterize the transcriptomic landscape of MB, both at the level of individual tumors as well as in large patient cohorts. Methods: We used a combination of single-cell transcriptomics, cell culture models and biophysical methods such as nanoparticle tracking analysis (NTA) and electron microscopy (EM), to investigate intercellular communication in the MB tumor niche. Results: Tumor cells of the SHH-MB subgroup show a differentiation blockade. These cells undergo extensive metabolic reprogramming. The gene expression profiles of individual tumor cells show a partial convergence with those of tumor-associated glial and immune cells. One possible cause is the transfer of extracellular vesicles (EVs) between cells in the tumor niche. We were able to detect EVs in co-culture models of MB tumor cells and oligodendrocytes. We also identified a gene expression signature, EVS, which shows overlap with the proteome profile of large oncosomes from prostate cancer cells. This signature is also present in MB patient samples. A high EVS expression is one common characteristic of tumors that occur in high-risk patients from otherwise very different MB subgroups or subtypes. Conclusions: With EVS, our study uncovered a novel gene expression signature that has a high prognostic significance across MB subgroups.
2020-12-11 | GSE127997 | GEO
Project description:An extracellular vesicle-related gene expression signature identifies high-risk patients in medulloblastoma
| PRJNA671503 | ENA
Project description:(bulk RNAseq) An extracellular vesicle-related gene expression signature identifies high-risk patients in medulloblastoma
| PRJNA670439 | ENA
Project description:(single-cell RNAseq) An extracellular vesicle-related gene expression signature identifies high-risk patients in medulloblastoma
| PRJNA526024 | ENA
Project description:Identifying molecular characteristics that are associated with aggressive cancer phenotypes through gene expression profiling can help predict treatment responses and clinical outcomes. Claudins are deregulated in colorectal cancer (CRC). In CRC, increased claudin-1 expression results in epithelial-to-mesenchymal transition and metastasis, while claudin-7 functions as a tumor suppressor. In this study, we have developed a molecular signature based on claudin-1 and claudin-7 associated with poor patient survival and chemoresistance. This signature was validated using an integrated approach including publicly available datasets and CRC samples from patients who either responded or did not respond to standard-of-care treatment, CRC cell lines, and patient-derived rectal and colon tumoroids. Transcriptomic analysis from a patient dataset initially yielded 23 genes that were differentially expressed along with higher claudin-1 and decreased claudin-7. From this analysis, we selected a claudins-associated molecular signature including PIK3CA, SLC6A6, TMEM43, and ASAP-1 based on their importance in CRC. The upregulation of these genes and their protein products was validated using multiple CRC patient datasets, in vitro chemoresistant cell lines, and patient-derived tumoroid models. Additionally, blocking these genes improved 5-FU sensitivity in chemoresistant CRC cells. Our findings propose a new claudin-based molecular signature that associates with poor prognosis as well as characteristics of treatment-resistant CRC including chemoresistance, metastasis, and relapse.
| S-EPMC8466455 | biostudies-literature
Project description:Although extracellular vesicles (EVs) in body fluid have been considered to be ideal biomarkers for cancer diagnosis and prognosis, it is still difficult to distinguish EVs derived from tumor tissue and normal tissue. Therefore, the prognostic value of tumor-specific EVs was evaluated through related molecules in pancreatic tumor tissue. NA sequencing data of pancreatic adenocarcinoma (PAAD) were acquired from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC). EV-related genes in pancreatic cancer were obtained from exoRBase. Protein-protein interaction (PPI) network analysis was used to identify modules related to clinical stage. CIBERSORT was used to assess the abundance of immune and non-immune cells in the tumor microenvironment. A total of 12 PPI modules were identified, and the 3-PPI-MOD was identified based on the randomForest package. The genes of this model are involved in DNA damage and repair and cell membrane-related pathways. The independent external verification cohorts showed that the 3-PPI-MOD can significantly classify patient prognosis. Moreover, compared with the model constructed by pure gene expression, the 3-PPI-MOD showed better prognostic value. The expression of genes in the 3-PPI-MOD had a significant positive correlation with immune cells. Genes related to the hypoxia pathway were significantly enriched in the high-risk tumors predicted by the 3-PPI-MOD. External databases were used to verify the gene expression in the 3-PPI-MOD. The 3-PPI-MOD had satisfactory predictive performance and could be used as a prognostic predictive biomarker for pancreatic cancer.
| S-EPMC7724614 | biostudies-literature
Project description:Plasma-derived extracellular vesicles (EVs) have been extensively described as putative biomarkers in different diseases. More precisely, increased levels of EVs subpopulations are well-known to associate with obesity. The goal of this study was to identify EVs-derived biomarkers in plasma from obese patients in order to predict the development of pathological events associated with obesity. The study was performed combining two different proteomic approaches (2D-DIGE and label-free LC-MS/MS). Samples were obtained from 22 obese patients, with no associated comorbidities, and their lean-matched controls. EVs were isolated following a serial ultracentrifugation protocol. We detected 22 and 23 different regulated protein features from 2D-DIGE and label free LC-MS/MS respectively. Most of the differentially regulated proteins identified were involved in the coagulation and complement cascade. Interestingly, there was a clear up-regulation of complement C3, complement C4 and fibrinogen in obese patients following both approaches, which correlates with a pro-inflammatory and prothrombotic state of those individuals. On the other hand, we showed a down-regulation of adiponectin leading to an increased risk of suffering cardiovascular diseases. Our results suggest the relevance of considering plasma-derived-EVs proteins as a source of potential biomarkers for the development of atherothrombotic events in obesity.
2018-12-17 | PXD010404 | Pride
Project description:Most high-grade serous ovarian cancer (HGSOC) patients develop resistance to platinum-based chemotherapy and recur. Many biomarkers related to the survival and prognosis of drug-resistant patients have been delved by mining databases; however, the prediction effect of single-gene biomarker is not specific and sensitive enough. The present study aimed to develop a novel prognostic gene signature of platinum-based resistance for patients with HGSOC. The gene expression profiles were obtained from Gene Expression Omnibus and The Cancer Genome Atlas database. A total of 269 differentially expressed genes (DEGs) associated with platinum resistance were identified (P < .05, fold change >1.5). Functional analysis revealed that these DEGs were mainly involved in apoptosis process, PI3K-Akt pathway. Furthermore, we established a set of seven-gene signature that was significantly associated with overall survival (OS) in the test series. Compared with the low-risk score group, patients with a high-risk score suffered poorer OS (P < .001). The area under the curve (AUC) was found to be 0.710, which means the risk score had a certain accuracy on predicting OS in HGSOC (AUC > 0.7). Surprisingly, the risk score was identified as an independent prognostic indicator for HGSOC (P < .001). Subgroup analyses suggested that the risk score had a greater prognostic value for patients with grade 3-4, stage III-IV, venous invasion and objective response. In conclusion, we developed a seven-gene signature relating to platinum resistance, which can predict survival for HGSOC and provide novel insights into understanding of platinum resistance mechanisms and identification of HGSOC patients with poor prognosis.
| S-EPMC6997076 | biostudies-literature