Breast tumor gene expression profiling for assessment of sufficient tumor cells for microarray diagnostic
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Roepman P
PROVIDER: S-ECPF-GEOD-16201 | biostudies-other | 2009
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Gene expression profiling of breast cancer primary tumor was performed to identify gene expression that is related to the presence of sufficient tumor cells. These gene profile can be used for identification of tumor samples that are eligible for microarray diagnostics.
2009-08-17 | GSE16201 | GEO
Project description:Gene expression profiling of breast cancer primary tumor was performed to identify gene expression that is related to the presence of sufficient tumor cells. These gene profile can be used for identification of tumor samples that are eligible for microarray diagnostics. A cohort of 403 early-stage primary breast cancer tumors was analyzed against a breast cancer reference pool
2010-05-07 | E-GEOD-16201 | biostudies-arrayexpress
Project description:BackgroundMicroarray diagnostics of tumour samples is based on measurement of prognostic and/or predictive gene expression profiles. Typically, diagnostic profiles have been developed using bulk tumour samples with a sufficient amount of tumour cells (usually >50%). Consequentially, a diagnostic results depends on the minimal percentage of tumour cells within a sample. Currently, tumour cell percentage is assessed by conventional histopathological review. However, even for experienced pathologists, such scoring remains subjective and time consuming and can lead to ambiguous results.MethodsIn this study we investigated whether we could use transcriptional activity of a specific set of genes instead of histopathological review to identify samples with sufficient tumour cell content. Genome-wide gene expression measurements were used to develop a transcriptional gene profile that could accurately assess a sample's tumour cell percentage.ResultsSupervised analysis across 165 breast tumour samples resulted in the identification of a set of 13 genes which expression correlated with presence of tumour cells. The developed gene profile showed a high performance (AUC 0.92) for identification of samples that are suitable for microarray diagnostics. Validation on 238 additional breast tumour samples indicated a robust performance for correct classification with an overall accuracy of 91 percent and a kappa score of 0.63 (95%CI 0.47-0.73).ConclusionThe developed 13-gene profile provides an objective tool for assessment whether a breast cancer sample contains sufficient tumour cells for microarray diagnostics. It will improve the efficiency and throughput for diagnostic gene expression profiling as it no longer requires histopathological analysis for initial tumour percentage scoring. Such profile will also be very use useful for assessment of tumour cell percentage in biopsies where conventional histopathology is difficult, such as fine needle aspirates.
| S-EPMC2732639 | biostudies-literature
Project description:CTCs are the purpoted intermediates of metastatic dissemination and are likely to contain cellular clones responsible for disease progression representing a preferred source for identification of druggable targets. Unfortunately a molecular characterization of CTCs is seriously hampered by their low numbers even in metastatic patients and by the elevated contamination of isolated CTCs with leukocytes. With the final goal of providing a reliable assay allowing to obtain valuable information on CTC features in the clinical setting, we have developed a method based on capture with beads linked to EpCAM and to MUC1 exploiting a commercially available kit and performing an extensive gene expression profiling with the DASL platform. For spike-in experiments, low pre-defined numbers of cells derived from established breast cancer cell lines (MCF7 and MDA-MB-468) were spiked into 5 mL of whole blood of healthy donor and captured using AdnaTest EMT-1/StemCell Select kit. Total RNA isolated from the captured cells together with total RNA isolated from the same in vitro cultered cells was processed in duplicate or triplicate onto Illumina Whole-Genome DASL HT platform. Finally, gene expression profiling was carried out on CTCs isolated from blood of 7 patients with advanced breast cancer. According with the characteristics of the study, data normalization was not applicable
| S-ECPF-GEOD-55470 | biostudies-other
Project description:Circulating tumor cells (CTCs) are cancer cells that are released from a tumor into the bloodstream. The presence of CTCs in peripheral blood has been associated with metastasis formation in patients with breast cancer. Therefore, the molecular characterization of CTCs may improve diagnostics and support treatment decisions. We performed gene expression profiling to evaluate the enriched CTCs and peripheral blood mononuclear cells (PBMCs) of breast cancer patients using an expression panel of 55 breast cancer-associated genes. The study revealed several significantly differentially expressed genes in the CTC-positive samples, including a few that were exclusively expressed in these cells. However, the expression of these genes was barely detectable in the PBMC samples. Some genes were differentially expressed in PBMCs, and the expression of these genes was correlated with tumor grade and the formation of metastasis. In this study, we have shown that the enriched CTCs of breast cancer patients overexpress genes involved in proteolytic degradation of the extracellular matrix (ECM) as well as genes that play important roles in the epithelial-mesenchymal transition (EMT) process that may occur in these cells.
| S-EPMC4839342 | biostudies-literature
Project description:Circulating tumor cells (CTCs) are prognostic in all stages of breast cancer. However, since they are extremely rare, little is known about the molecular nature of these cells. We report a novel strategy for the isolation and expression profiling of pure populations of CTCs derived from peripheral blood. We developed a method to isolate CTCs based on immunomagnetic capture followed by fluorescence-activated cell sorting (IE/FACS). After assay validation using the BT474 cell line spiked into blood samples in vitro, RNA from CTCs isolated from the blood of five metastatic breast cancer (MBC) patients was linearly amplified and subjected to gene expression profiling via cDNA microarrays. We isolated a range of 9-993 captured CTCs from five MBC patients' blood and profiled their RNA in comparison to a diverse panel of primary breast tumors (n = 55). Unsupervised hierarchical clustering revealed that CTC profiles clustered with more aggressive subtypes of primary breast tumors and were readily distinguishable from peripheral blood (PB) and normal epithelium. Differential expression analysis revealed CTCs to have downregulated apoptosis, and they were distinguishable from PB by the relative absence of immune-related signals. As expected, CTCs from MBC had significantly higher risk of recurrence scores than primary tumors (p = 0.0073). This study demonstrates that it is feasible to isolate CTCs from PB with high purity through IE/FACS and profile them via gene expression analysis. Our approach may inform the discovery of therapeutic predictors and be useful for real-time identification of emerging resistance mechanisms in MBC patients.
| S-EPMC4698170 | biostudies-literature
Project description:IntroductionThe importance of the tumor microenvironment in breast cancer has been increasingly recognized. Critical molecular changes in the tumor stroma accompanying cancer progression, however, remain largely unknown. We conducted a comparative analysis of global gene expression changes in the stromal and epithelial compartments during breast cancer progression from normal to preinvasive to invasive ductal carcinoma.MethodsWe combined laser capture microdissection and gene expression microarrays to analyze 14 patient-matched normal epithelium, normal stroma, tumor epithelium and tumor-associated stroma specimens. Differential gene expression and gene ontology analyses were performed.ResultsTumor-associated stroma undergoes extensive gene expression changes during cancer progression, to a similar extent as that seen in the malignant epithelium. Highly upregulated genes in the tumor-associated stroma include constituents of the extracellular matrix and matrix metalloproteases, and cell-cycle-related genes. Decreased expression of cytoplasmic ribosomal proteins and increased expression of mitochondrial ribosomal proteins were observed in both the tumor epithelium and the stroma. The transition from preinvasive to invasive growth was accompanied by increased expression of several matrix metalloproteases (MMP2, MMP11 and MMP14). Furthermore, as observed in malignant epithelium, a gene expression signature of histological tumor grade also exists in the stroma, with high-grade tumors associated with increased expression of genes involved in immune response.ConclusionsOur results suggest that the tumor microenvironment participates in tumorigenesis even before tumor cells invade into stroma, and that it may play important roles in the transition from preinvasive to invasive growth. The immune cells in the tumor stroma may be exploited by the malignant epithelial cells in high-grade tumors for aggressive invasive growth.
| S-EPMC2687710 | biostudies-literature
Project description:Metastasis of breast cancer is the main cause of death in patients. Previous genome-wide studies have identified gene-expression patterns correlated with cancer patient outcome. However, these were derived mostly from whole tissue without respect to cell heterogeneity. In reality, only a small subpopulation of invasive cells inside the primary tumor is responsible for escaping and initiating dissemination and metastasis. When whole tissue is used for molecular profiling, the expression pattern of these cells is masked by the majority of the noninvasive tumor cells. Therefore, little information is available about the crucial early steps of the metastatic cascade: migration, invasion, and entry of tumor cells into the systemic circulation.In the past, we developed an in vivo invasion assay that can capture specifically the highly motile tumor cells in the act of migrating inside living tumors. Here, we used this assay in orthotopic xenografts of human MDA-MB-231 breast cancer cells to isolate selectively the migratory cell subpopulation of the primary tumor for gene-expression profiling. In this way, we derived a gene signature specific to breast cancer migration and invasion, which we call the Human Invasion Signature (HIS).Unsupervised analysis of the HIS shows that the most significant upregulated gene networks in the migratory breast tumor cells include genes regulating embryonic and tissue development, cellular movement, and DNA replication and repair. We confirmed that genes involved in these functions are upregulated in the migratory tumor cells with independent biological repeats. We also demonstrate that specific genes are functionally required for in vivo invasion and hematogenous dissemination in MDA-MB-231, as well as in patient-derived breast tumors. Finally, we used statistical analysis to show that the signature can significantly predict risk of breast cancer metastasis in large patient cohorts, independent of well-established prognostic parameters.Our data provide novel insights into, and reveal previously unknown mediators of, the metastatic steps of invasion and dissemination in human breast tumors in vivo. Because migration and invasion are the early steps of metastatic progression, the novel markers that we identified here might become valuable prognostic tools or therapeutic targets in breast cancer.
| S-EPMC4053118 | biostudies-literature
Project description:BackgroundSensitivity and accuracy are key points when using microarrays to detect alterations in gene expression under different conditions. Critical to the acquisition of reliable results is the preparation of the RNA. In the field of virology, when analyzing the host cell's reaction to infection, the often high representation of viral RNA (vRNA) within total RNA preparations from infected cells is likely to interfere with microarray analysis. Yet, this effect has not been investigated despite the many reports that describe gene expression profiling of virus-infected cells using microarrays.ResultsIn this study we used coronaviruses as a model to show that vRNA indeed interferes with microarray analysis, decreasing both sensitivity and accuracy. We also demonstrate that the removal of vRNA from total RNA samples, by means of virus-specific oligonucleotide capturing, significantly reduced the number of false-positive hits and increased the sensitivity of the method as tested on different array platforms.ConclusionWe therefore recommend the specific removal of vRNA, or of any other abundant 'contaminating' RNAs, from total RNA samples to improve the quality and reliability of microarray analyses.
| S-EPMC2397413 | biostudies-literature
Project description:Osteosa rcoma is an aggressive malignant neoplasm that exhibits osteoblastic differentiation and produces malignant osteoid. The aim of this study was to find feature genes associated with osteosarcoma and correlative gene functions which can distinguish cancer tissues from non-tumor tissues. Gene expression profile GSE14359 was downloaded from Gene Expression Omnibus (GEO) database, including 10 osteosarcoma samples and 2 normal samples. The differentially expressed genes (DEGs) between osteosarcoma and normal specimens were identified using limma package of R. DAVID was applied to mine osteosarcoma associated genes and analyze the GO enrichment on gene functions and KEGG pathways. Then, corresponding protein-protein interaction (PPI) network of DEGs was constructed based on the data collected from STRING datasets. Principal component of top10 DEGs and PPI network of top 20 DEGs were further analyzed. Finally, transcription factors were predicted by uploading the two groups of DEGs to TfactS database. A total of 437 genes, including 114 up-regulated genes and 323 down-regulated genes, were filtered as DEGs, of which 46 were associated with osteosarcoma by Disease Module. GO and KEGG pathway enrichment analysis showed that genes mainly affected the process of immune response and the development of skeletal and vascular system. The PPI network analysis elucidated that hemoglobin and histocompatibility proteins and enzymes, which were associated with immune response, were closely associated with osteosarcoma. Transcription factors MYC and SP1 were predicted to be significantly related to osteosarcoma. The discovery of gene functions and transcription factors has the potential to use in clinic for diagnosis of osteosarcoma in future. In addition, it will pave the way to studying mechanism and effective therapies for osteosarcoma.
| S-EPMC4565213 | biostudies-literature