Murine Colon26 cells: Primary vs. liver metastasis
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE12162 | GEO | 2008/07/23
SECONDARY ACCESSION(S): PRJNA113451
REPOSITORIES: GEO
Similar Datasets
Project description:Transcriptional profiling of mouse Colon26 cancer cells comparing control primary tumours in the colon with their liver metastases. Keywords: Metastatic variant Two-condition experiment, Colon26 primary tumours vs. their liver metastases. Biological replicates: 2 primary tumours, 2 liver metastases, independently grown and harvested. One replicate per array.
2008-07-23 | E-GEOD-12162 | biostudies-arrayexpress
Project description:We profiled primary colon cancer and liver metastatic tumours from two patients.
2020-09-16 | GSE147738 | GEO
Project description:Global gene expression analysis was performed on a panel of 23 osteosarcoma samples of primary and metastatic origin using the Applied Biosystems Gene Expression Array System. When comparing the primary tumours with the metastases, we found a significantly increased expression of genes involved in immunological processes, e.g. coding for cytokines and chemokines, in the metastatic samples, suggesting that these signal molecules play an important role in promoting metastasis. In addition, a comparison of the gene expression in primary samples from patients with or without metastases demonstrated that patients who later developed metastases had high expression of the chemokine (C-X-C motif) receptor 4 (CXCR4), similar to the metastatic samples. Increased knowledge of mechanisms and interactions between specified molecular signalling pathways in osteosarcomas could lead to a more rational strategy for development of targeted therapy. Total RNA was isolated from tumor tissue of osteosarcoma patients. Gene expression patterns of metastatic versus primary samples were compared, as well as primary samples from patients who did or did not later develop metastases.
2012-01-01 | E-GEOD-32981 | biostudies-arrayexpress
Project description:Global gene expression analysis was performed on a panel of 23 osteosarcoma samples of primary and metastatic origin using the Applied Biosystems Gene Expression Array System. When comparing the primary tumours with the metastases, we found a significantly increased expression of genes involved in immunological processes, e.g. coding for cytokines and chemokines, in the metastatic samples, suggesting that these signal molecules play an important role in promoting metastasis. In addition, a comparison of the gene expression in primary samples from patients with or without metastases demonstrated that patients who later developed metastases had high expression of the chemokine (C-X-C motif) receptor 4 (CXCR4), similar to the metastatic samples. Increased knowledge of mechanisms and interactions between specified molecular signalling pathways in osteosarcomas could lead to a more rational strategy for development of targeted therapy.
2012-01-01 | GSE32981 | GEO
Project description:We recently established an orthotopic breast cancer model of brain metastasis based on the injection of murine breast cancer cell lines into the mammary fat pad. This model is based on the use of 4T1 murine breast carcinoma cells. 4T1-derived tumors recapitulate the main steps of human breast cancer progression, including epithelial-to-mesenchymal transition and metastases to lung and lymph nodes. Bioluminescence imaging revealed the appearance of secondary lesions to the lung and lymph nodes and sporadically to the brain. Brain metastases were confirmed by macroscopic and microscopic evaluation of the brains at necropsy. We then isolated brain metastatic cells, re-injected them orthotopically in syngeneic (BALB/c) mice and isolated again cell lines from brain metastatic lesions for two rounds of selection. We obtained a cell line metastasizing to the brain with 100% penetrance (named 4T1-BM2 for Brain Metastasis, 2nd generation). In parallel we derived after two rounds of in vivo growth tumor cell lines from primary tumors (4T1-T2) and from lung metastases (4T1-LM2).
2020-08-20 | GSE54773 | GEO
Project description:The aim of our study was to identify a microRNA signature for metastatic CRC that could predict and differentiate metastatic target organ localization. Normal and cancer tissues of three different groups of CRC patients were analyzed. RNA microarray and TaqMan Array analysis were performed on 66 italian patients with or without lymph nodes and/or liver recurrences. Data obtained with the two assays, were analyzed separately and then intersected to identify a primary CRC metastatic signature. Five differentially expressed microRNAs (hsa-miR-21, -103, -93, -31 and -566) were validated by qRT-PCR on a second group of 16 american metastatic patients. In situ hybridization was performed on the 16 american patients as well as on three distinct commercial tissues microarray (TMA), containing normal adjacent colon, the primary adenocarcinoma, normal and metastatic lymph nodes and liver. Hsa-microRNA-31,-21,-93, and-103 upregulation together with hsa-miR-566 downregulation defined the CRC metastatic signature, while in situ hybridization data identified a lymphonodal invasion profile. 33 patients had colon cancer with lymph nodes metastasis only (Any T, Any N, M0) and 15 were diagnosed with colon cancer, lymph nodes and liver metastases (Any T, Any N, M1). Separate tumor samples from the primary tumor, the metastatic lymph nodes and the liver metastasis were collected.
2014-04-01 | E-GEOD-56350 | biostudies-arrayexpress
Project description:Background: Many strategies to define subtypes and treat cancer relies on a presumption of either localized or widespread (poly)metastatic disease. We proposed an intermediate state of metastasis termed oligometastasis(es) characterized by limited metastatic progression and amenable to treatment by localized methods e.g. surgery or radiotherapy. Methods: To understand the biological basis of oligometastatic and polymetastatic progression, we analyzed microRNA expression patterns from lung tumor samples of patients with less than five metastases at first metastasis presentation and treated with metastasis-directed surgery. Results: Patients were stratified into four subgroups of oligo- and poly-metastatic progression based on the rate of metastatic progression over follow-up period. We prioritized microRNAs between the extremes of oligo- vs. poly-metastatic progression and validated their capacity to distinguish these phenotypes and predict survival in an independent validation dataset. Conclusions: Our results provide further evidence for the biological underpinnings of oligometastasis(es) and potential microRNA candidates to predict progression trajectories of patients and optimize corresponding metastasis-directed treatment. We collected tumor samples from 63 patients that (i) had between one and five metastasis(es) at first metastatic presentation and no clinical or radiologic evidence of metastases in the pleural, peritoneal, pericardial or retroperitoneal cavities,(ii) at the time of lung surgery, had every site of known metastases treated with definitive intent, and (iii) had a minimum of 16 months of follow-up after surgery was required. Total RNA were derived from FFPE metastatic tissue samples. Patient samples were subsequently classified into 3 groups: those from patients with high, intermediate and low rates of progression.
2012-06-13 | E-GEOD-38698 | biostudies-arrayexpress
Project description:RNA was extracted from the frozen localised prostate tumour (primary prostate tumours), proximal (epididymal fat) and distal (lung) metastases from Ctnnb1pc(ex3)Δ/+ Ptenpc+/- (n=3 matched; ~9-10 months)
2022-08-20 | GSE136082 | GEO
Project description:Lung metastatic potential of the 29 HNSCC was examined with tail vein metastatic assay as described previously. 1 ×10E6 HNSCC cells in a volume of 200 µL were injected into the lateral tail vein using a 30 gauge needle. Eight to 10 mice were prepared for each cell line. Mice were euthanized using carbon dioxide asphyxiation when they lost more than 15% of their pre-injection body weight or at 90 days after cell injection. Necropsy was performed, and lung was harvested. The lungs were then evaluated for the presence of lung metastases and also weighed.
2017-02-09 | GSE67275 | GEO
Project description:Background: Metastases result in 90% of all cancer deaths. Prostate cancer primary tumors evolve to become metastatic through selective alterations, such as amplification and deletion of genomic DNA. Methods: Genomic DNA copy number alterations were used to develop a gene signature that measured the metastatic potential of a prostate cancer primary tumor. We studied the genomic landscape of these alterations in 294 primary tumors and 49 metastases from 5 independent cohorts. Receiver-operating characteristic cross-validation and Kaplan-Meier survival analysis were performed to assess the accuracy of our predictive model. The signature was measured in a panel of 337 cancer cell lines from 29 different tissue origins. Results: We identified 399 copy number alterations around genes that were over-represented in metastases and predictive of whether a primary tumor will metastasize. Cross-validation analysis resulted in a predictive accuracy of 80.5% and log rank analysis of the metastatic potential score was significantly related to the endpoint of metastasis-free survival (p=0.014). The metastatic signature was observed in cell lines originating from lung, breast, colon, thyroid, rectum, pancreas and melanoma. The signature was comprised in part of genes of known or putative metastatic role — 8 solute carrier genes, 6 Cadherin family genes and 5 potassium channel genes — that function in metabolism, cell-to-cell adhesion and escape from anoikis/apoptosis. Conclusions: Somatic Copy number alterations are an independent predictor of metastatic potential. The data indicate a prognostic utility for using primary tumor genomics to assist in clinical decision making and developing therapeutics for prostate and likely other cancers. genomic DNA from 29 prostate cancer tumors with matched normals run on Affymetrix 6.0 SNP arrays.
2013-12-01 | E-GEOD-27105 | biostudies-arrayexpress