Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA213714 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Specific extracellular matrix remodeling signature of colon hepatic metastases [HG-U133B]
| PRJNA263827 | ENA
Project description:To identify genes implicated in metastatic colonization of the liver in colorectal cancer, we collected pairs of primary tumors and hepatic metastases before chemotherapy in 13 patients. We compared mRNA expression in the pairs of patients to identify genes deregulated during metastatic evolution. We then validated the identified genes using data obtained by different groups. The 33-gene signature was able to classify 87% of hepatic metastases, 98% of primary tumors, 97% of normal colon mucosa, and 95% of normal liver tissues in six datasets obtained using five different microarray platforms. The identified genes are specific to colon cancer and hepatic metastases since other metastatic locations and hepatic metastases originating from breast cancer were not classified by the signature. Gene Ontology term analysis showed that 50% of the genes are implicated in extracellular matrix remodeling, and more precisely in cell adhesion, extracellular matrix organization and angiogenesis. Because of the high efficiency of the signature to classify colon hepatic metastases, the identified genes represent promising targets to develop new therapies that will specifically affect hepatic metastasis microenvironment. 57 samples of patients with stage IV colorectal cancer. We compared using Affymetrix chips gene expression profiles between primary tumors and hepatic metastases
2013-09-01 | E-GEOD-49355 | biostudies-arrayexpress
Project description:To identify genes implicated in metastatic colonization of the liver in colorectal cancer, we collected pairs of primary tumors and hepatic metastases before chemotherapy in 13 patients. We compared mRNA expression in the pairs of patients to identify genes deregulated during metastatic evolution. We then validated the identified genes using data obtained by different groups. The 33-gene signature was able to classify 87% of hepatic metastases, 98% of primary tumors, 97% of normal colon mucosa, and 95% of normal liver tissues in six datasets obtained using five different microarray platforms. The identified genes are specific to colon cancer and hepatic metastases since other metastatic locations and hepatic metastases originating from breast cancer were not classified by the signature. Gene Ontology term analysis showed that 50% of the genes are implicated in extracellular matrix remodeling, and more precisely in cell adhesion, extracellular matrix organization and angiogenesis. Because of the high efficiency of the signature to classify colon hepatic metastases, the identified genes represent promising targets to develop new therapies that will specifically affect hepatic metastasis microenvironment. 57 samples of patients with stage IV colorectal cancer. We compared using Affymetrix chips gene expression profiles between primary tumors and hepatic metastases
2014-10-15 | E-GEOD-62321 | biostudies-arrayexpress
Project description:To identify genes implicated in metastatic colonization of the liver in colorectal cancer, we collected pairs of primary tumors and hepatic metastases before chemotherapy in 13 patients. We compared mRNA expression in the pairs of patients to identify genes deregulated during metastatic evolution. We then validated the identified genes using data obtained by different groups. The 33-gene signature was able to classify 87% of hepatic metastases, 98% of primary tumors, 97% of normal colon mucosa, and 95% of normal liver tissues in six datasets obtained using five different microarray platforms. The identified genes are specific to colon cancer and hepatic metastases since other metastatic locations and hepatic metastases originating from breast cancer were not classified by the signature. Gene Ontology term analysis showed that 50% of the genes are implicated in extracellular matrix remodeling, and more precisely in cell adhesion, extracellular matrix organization and angiogenesis. Because of the high efficiency of the signature to classify colon hepatic metastases, the identified genes represent promising targets to develop new therapies that will specifically affect hepatic metastasis microenvironment.
2013-09-01 | GSE49355 | GEO
Project description:To identify genes implicated in metastatic colonization of the liver in colorectal cancer, we collected pairs of primary tumors and hepatic metastases before chemotherapy in 13 patients. We compared mRNA expression in the pairs of patients to identify genes deregulated during metastatic evolution. We then validated the identified genes using data obtained by different groups. The 33-gene signature was able to classify 87% of hepatic metastases, 98% of primary tumors, 97% of normal colon mucosa, and 95% of normal liver tissues in six datasets obtained using five different microarray platforms. The identified genes are specific to colon cancer and hepatic metastases since other metastatic locations and hepatic metastases originating from breast cancer were not classified by the signature. Gene Ontology term analysis showed that 50% of the genes are implicated in extracellular matrix remodeling, and more precisely in cell adhesion, extracellular matrix organization and angiogenesis. Because of the high efficiency of the signature to classify colon hepatic metastases, the identified genes represent promising targets to develop new therapies that will specifically affect hepatic metastasis microenvironment.
2014-10-15 | GSE62321 | GEO
Project description:RNA expression data was generated as part of a colon cancer study. Samples were obtained from patients, including primary colon cancer, polyps, metastases, and matched normal mucosa (obtained from the margins of the resection). The RNA was extracted from tissue samples obtained from resections and hybridized to Affymetrix HG-U133 arrays. RNA expression data was also obtained for a few cell lines. notte-00422 Assay Type: Gene Expression Provider: Affymetrix Array Designs: HG-U133A Organism: Homo sapiens (ncbitax) Material Types: cell, total_RNA, synthetic_RNA, organism_part, whole_organism Disease States: colon cancer, colon polyp, Colon Carcinoma, colon adenocarcinoma, breast cancer, Normal, Prostate Adenocarcinoma
2015-05-02 | E-GEOD-68468 | biostudies-arrayexpress
Project description:Dissemination of primary tumors to distant anatomical sites has a substantial negative impact on patient prognosis. The liver is a common site for metastases from colorectal cancer, and patients with hepatic metastases have generally much shorter survival, raising a need to develop and implement novel strategies for targeting metastatic disease. The extracellular matrix (ECM) is a meshwork of highly crosslinked, insoluble, high molecular weight proteins maintaining tissue integrity and establishing cell-cell interactions. Emerging evidence identifies the importance of the ECM in cancer cell migration, invasion, intravasation, and metastasis. Here, we isolated the extracellular matrix from MC38 mouse liver metastases using our optimized method of mild detergent solubilization followed by biochemical enrichment. The matrices were subjected to label-free quantitative mass spectrometry analysis, revealing proteins highly abundant in the metastatic matrisome. The resulting list of differentially expressed proteins significantly predicted survival in patients with colorectal cancer but not other cancers with strong involvement of the extracellular matrix component. One of the proteins upregulated in liver metastatic ECM, Annexin A1, was not previously studied in the context of cancer-associated matrisome. Here we show that Annexin A1 was markedly upregulated in colon cancer cell lines compared to cancer cells of other origin, and also overrepresented in human primary colorectal lesions as well as hepatic metastases in comparison with their adjacent healthy tissue counterparts. In conclusion, our study provides a comprehensive ECM characterization of MC38 experimental liver metastases and proposes Annexin A1 as a putative target for this disease.
2020-05-26 | PXD013350 | Pride
Project description:Identification of early processes leading to complex tissue pathologies, such as inflammatory bowel diseases, poses a major scientific and clinical challenge that is imperative for improved diagnosis and treatment. Most studies of inflammation onset focus on cellular processes and signaling molecules, while overlooking the environment in which they take place, the continuously remodeled extracellular matrix. In this study, we used colitis models for investigating extracellular-matrix dynamics during disease onset, while treating the matrix as a complete and defined entity. Through the analysis of matrix structure, stiffness and composition, we unexpectedly revealed that even prior to the first clinical symptoms, the colon displays its own unique extracellular-matrix signature and found specific markers of clinical potential, which were also validated in human subjects. We also show that the emergence of this pre-symptomatic matrix is mediated by subclinical infiltration of immune cells bearing remodeling enzymes. Remarkably, whether the inflammation is chronic or acute, its matrix signature converges at pre-symptomatic states. We suggest that the existence of a pre-symptomatic extracellular-matrix is general and relevant to a wide range of diseases.
2020-12-02 | PXD022668 | Pride
Project description:In osteosarcoma patients, the development of metastases, often to the lungs, is the most frequent cause of death. To improve this situation, a deeper understanding of the molecular mechanisms governing osteosarcoma development and dissemination and the identification of novel drug targets for an improved treatment are needed. Towards this aim, we characterized osteosarcoma tissue samples compared to primary osteoblast cells using Affymetrix HG U133A microarrays. mRNA from 5 frozen conventional osteosarcoma and 4 osteosarcoma lung metastases tumor samples and mRNA from fresh primary osteoblast cells were extracted and hybridized to HG U133A microarrays.
2010-07-30 | E-GEOD-14359 | biostudies-arrayexpress