Project description:We report that metastasis in an autochthonous mouse model of sarcoma is driven by a single clone in the primary tumor. We performed RNA-seq comparing the gene expression profiles of the metastatic clones (MC) to matched non-metastatic clones (non-MC) from the same tumor for multiple tumors. RNA from lung metastases (Lung-Met) of matched tumors are sequenced as well.
Project description:A model of tumor metastasis based on v-src transformed immortalized cell lines was developed. The model consists of highly metastatic PR9692 cell line and a derived clone PR9692-E9 which has lost the metastatic abilities. Introduction of exogenous EGR1 gene into the non-metastasizing PR9692-E9 cells completely restores the metastatic potential. Revealed changes in gene expression provide insight into the molecular mechanisms contolling metastatic behavior of sarcoma cells. Comparison of expression profiles obtained from highly metastatic PR9692 cell line, derived non-metastatic clone PR9692-E9 and non-metastatic PR9692-E9 cells infected with replication-defective retroviral vector SFCVneo-EGR1 containing full length cDNA of EGR1. For each condition three biological replicates were analyzed.
Project description:A model of tumor metastasis based on v-src transformed immortalized cell lines was developed. The model consists of highly metastatic PR9692 cell line and a derived clone PR9692-E9 which has lost the metastatic abilities. Introduction of exogenous EGR1 gene into the non-metastasizing PR9692-E9 cells completely restores the metastatic potential. Revealed changes in gene expression provide insight into the molecular mechanisms contolling metastatic behavior of sarcoma cells.
Project description:To identify genes that mediate lung metastasis in breast cancer, we compared expression profiles of metastatic versus non-metastatic mammary tumors in MMTV-Wnt1 transgenic mice. A subset of biologically relevant genes with statistically significant changes was selected for validation. These genes include Alox15, Ptn, Ror2, Sox9, Jag2 and Runx2. These genes encode proteins that play important roles in the immune and inflammatory responses as well as osteogenesis and skeletal morphogenesis.
Project description:We hypothesize that there is a gene signature which will improve our ability to predict development of metastatic disease in STS patients. The objective of this study was to determine the feasibility of using cDNA microarray and quantitative real-time PCR (qRT-PCR) analysis to determine gene expression patterns in metastatic versus non-metastatic canine STSs, given the inherent heterogeneity of this group of tumors. Five STSs from dogs with metastatic disease were evaluated in comparison to eight STSs from dogs without metastasis. Tumor RNA was extracted, processed and labeled for application to the Affymetrix Canine Genechip 2.0 Array. Array fluorescence was normalized using D-Chip software and data analysis was performed with JMP/Genomics. Differential gene expression was validated using qRT-PCR. Over 200 genes were differentially expressed at a false discovery rate of 5%. Differential gene expression was validated for five genes upregulated in metastatic tumors. Quantitative RT-PCR confirmed increased relative expression of all five genes of interest in the metastatic STSs. Our results demonstrate that microarray and qRT-PCR are feasible methods for comparing gene signatures in canine STSs. Further evaluation of differences in gene expression between metastatic and non-metastatic STSs is likely to identify genes important in the development of metastatic disease and improve our ability to prognosticate for individual patients. Comparison of metastatic and non-metastatic (defined as no metastasis for at least one year) untreated tumor biopsies.
Project description:Ewing’s sarcoma (ES) is a highly aggressive bone tumor, and the second most prevalent pediatric bone malignancy. The presence of metastasis at diagnosis decreases the three-year survival rate to 20% and contributes to diminished prognosis. Researches are indispensable for the early characterization of the disease and prediction of metastatic-prone patients, through biomarkers identification. Moreover, there is currently no available data on ES utilizing non-biopsy samples, such as plasma. This study utilizes a proteomic analysis of Ewing's sarcoma patient’s plasma samples and biopsies. Initially, the ES group was compared with the control counterpart. In a next step, the ES arm was further stratified into either initially metastatic and non-metastatic, or poor and good chemotherapy responder groups to identify protein expression profiles that can predict metastatic proneness and chemotherapy response, respectively.
Project description:We hypothesize that there is a gene signature which will improve our ability to predict development of metastatic disease in STS patients. The objective of this study was to determine the feasibility of using cDNA microarray and quantitative real-time PCR (qRT-PCR) analysis to determine gene expression patterns in metastatic versus non-metastatic canine STSs, given the inherent heterogeneity of this group of tumors. Five STSs from dogs with metastatic disease were evaluated in comparison to eight STSs from dogs without metastasis. Tumor RNA was extracted, processed and labeled for application to the Affymetrix Canine Genechip 2.0 Array. Array fluorescence was normalized using D-Chip software and data analysis was performed with JMP/Genomics. Differential gene expression was validated using qRT-PCR. Over 200 genes were differentially expressed at a false discovery rate of 5%. Differential gene expression was validated for five genes upregulated in metastatic tumors. Quantitative RT-PCR confirmed increased relative expression of all five genes of interest in the metastatic STSs. Our results demonstrate that microarray and qRT-PCR are feasible methods for comparing gene signatures in canine STSs. Further evaluation of differences in gene expression between metastatic and non-metastatic STSs is likely to identify genes important in the development of metastatic disease and improve our ability to prognosticate for individual patients.
Project description:19 non-metastatic breast cancers (controls) and 19 breast cancers showing metastases or metastatic relapse within 5 years (cases) were extracted from a multi-institutional case series of 123 breast cancer patients . Cases and controls were analyzed for DNA methylation over 56 genes by the MethDet assay [1]using a dedicated microarray (MethDet56). 1. Levenson VV, Melnikov AA: The MethDet: a technology for biomarker development. Expert Rev Mol Diagn 2011, 11:807-812.
Project description:Metastasis to lymph nodes is an early and prognostically important event in the progression of many human cancers, and is associated with expression of vascular endothelial growth factor-D (VEGF-D). Changes to lymph node vasculature occur during metastasis, and may establish a metastatic niche capable of attracting and supporting tumor cells. We used microarrays to characterise the molecular profiles of endothelial cells from lymph nodes draining metastatic (VEGF-D-overexpressing) and non-metastatic tumors, and to identify differentially-expressed genes that might have therapeutic or prognostic potential. Draining lymph nodes of metastatic (VEGF-D-overexpressing) or non-metastatic tumors were pooled from 1-5 mice and enzymatically digested. Lymph nodes draining metastatic tumors were included for the analysis only if macroscopically enlarged, indicating the presence of metastatic cells. After digestion, tumor cells and leukocytes were depleted via immunomagnetic selection, and the resulting lymph node stromal cells were cultured briefly. Podoplanin was then used as a positive immunomagnetic selection marker to enrich for lymphatic and other endothelial cells in the lymph node. RNA was isolated from biological duplicate lymph node endothelial cell (LN EC) preparations and analysed by microarray.
Project description:Feline mammary carcinoma (FMC) is a common cancer found in female cats. Early detection is necessary to prevent both local and distant metastasis and increase survival times. However, the available protein biomarkers involved in non-metastatic FMC (NmFMC) and metastatic FMC (mFMC) are limited. The purpose of this study was to identify serum peptidome profiles in NmFMC and mFMC using liquid chromatography-tandem mass spectrometry.