A gene expression profile that predicts circulating tumor cell presence in breast cancer patients
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Molloy TJ
PROVIDER: S-ECPF-GEOD-31364 | biostudies-other | 2012
REPOSITORIES: biostudies-other
Similar Datasets
Project description:The detection of circulating tumor cells (CTCs) in the peripheral blood and microarray gene expression profiling of the primary tumor are two promising new technologies able to provide valuable prognostic data for patients with breast cancer. Meta-analyses of several established prognostic breast cancer gene expression profiles in large patient cohorts have demonstrated that despite sharing few genes, their delineation of patients into "good prognosis" or "poor prognosis" are frequently very highly correlated, and combining prognostic profiles does not increase prognostic power. In the current study, we aimed to develop a novel profile which provided independent prognostic data by building a signature predictive of CTC status rather than outcome. Microarray gene expression data from an initial training cohort of 72 breast cancer patients for which CTC status had been determined in a previous study using a multimarker QPCR-based assay was used to develop a CTC-predictive profile. The generated profile was validated in two independent datasets of 49 and 123 patients and confirmed to be both predictive of CTC status, and independently prognostic. Importantly, the "CTC profile" also provided prognostic information independent of the well-established and powerful '70-gene' prognostic breast cancer signature. This profile therefore has the potential to not only add prognostic information to currently-available microarray tests but in some circumstances even replace blood-based prognostic CTC tests at time of diagnosis for those patients already undergoing testing by multigene assays.
| S-EPMC3285692 | biostudies-literature
Project description:Development of a primary tumor gene expression profile that can predict the presence of circulating tumor cells in the blood of breast cancer patients. The detection of circulating tumor cells (CTCs) in the peripheral blood and microarray gene expression profiling of the primary tumor are two promising new technologies able to provide valuable prognostic data for patients with breast cancer. In the current study, we aimed to develop a novel profile which provided independent prognostic data by building a signature predictive of CTC status rather than outcome.
2012-04-12 | GSE31364 | GEO
Project description:Development of a primary tumor gene expression profile that can predict the presence of circulating tumor cells in the blood of breast cancer patients. The detection of circulating tumor cells (CTCs) in the peripheral blood and microarray gene expression profiling of the primary tumor are two promising new technologies able to provide valuable prognostic data for patients with breast cancer. In the current study, we aimed to develop a novel profile which provided independent prognostic data by building a signature predictive of CTC status rather than outcome. Seventy-two primary breast cancer tumor have been analyzed against a breast cancer reference pool.
2012-04-11 | E-GEOD-31364 | biostudies-arrayexpress
Project description:BackgroundCirculating tumor cells (CTCs) have been associated with prognosis especially in breast cancer and have been proposed as a liquid biopsy for repeated follow up examinations. Molecular characterization of CTCs is difficult to address since they are very rare and the amount of available sample is very limited.MethodsWe quantified by RT-qPCR CK-19, MAGE-A3, HER-2, TWIST1, hTERT α+β+, and mammaglobin gene transcripts in immunomagnetically positively selected CTCs from 92 breast cancer patients, and 28 healthy individuals. We also compared our results with the CellSearch system in 33 of these patients with early breast cancer.ResultsRT-qPCR is highly sensitive and specific and can detect the expression of each individual gene at the one cell level. None of the genes tested was detected in the group of healthy donors. In 66 operable breast cancer patients, CK-19 was detected in 42.4%, HER-2 in 13.6%, MAGE-A3 in 21.2%, hMAM in 13.6%, TWIST-1 in 42.4%, and hTERT α+β+ in 10.2%. In 26 patients with verified metastasis, CK-19 was detected in 53.8%, HER-2 in 19.2%, MAGE-A3 in 15.4%, hMAM in 30.8%, TWIST-1 in 38.5% and hTERT α+β+in 19.2%. Our preliminary data on the comparison between RT-qPCR and CellSearch in 33 early breast cancer patients showed that RT-qPCR gives more positive results in respect to CellSearch.ConclusionsMolecular characterization of CTCs has revealed a remarkable heterogeneity of gene expression between breast cancer patients. In a small percentage of patients, CTCs were positive for all six genes tested, while in some patients only one of these genes was expressed. The clinical significance of these findings in early breast cancer remains to be elucidated when the clinical outcome for these patients is known.
| S-EPMC3224356 | 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:Previous studies have shown that pharmacogenomic modeling of circulating tumor and invasive cells (CTICs) can predict response of pancreatic ductal adenocarcinoma (PDAC) to combination chemotherapy, predominantly 5-fluorouracil-based. We hypothesized that a similar approach could be developed to predict treatment response to standard frontline gemcitabine with nab-paclitaxel (G/nab-P) chemotherapy. Gene expression profiles for responsiveness to G/nab-P were determined in cell lines and a test set of patient samples. A prospective clinical trial was conducted, enrolling 37 patients with advanced PDAC who received G/nab-P. Peripheral blood was collected prior to treatment, after two months of treatment, and at progression. The CTICs were isolated based on a phenotype of collagen invasion. The RNA was isolated, cDNA synthesized, and qPCR gene expression analyzed. Patients were most closely matched to one of three chemotherapy response templates. Circulating tumor and invasive cells' SMAD4 expression was measured serially. The CTICs were reliably isolated and profiled from peripheral blood prior to and during chemotherapy treatment. Individual patients could be matched to distinct response templates predicting differential responses to G/nab-P treatment. Progression free survival was significantly correlated to response prediction and ΔSMAD4 was significantly associated with disease progression. These findings support phenotypic profiling and ΔSMAD4 of CTICs as promising clinical tools for choosing effective therapy in advanced PDAC, and for anticipating disease progression.
| S-EPMC6315371 | biostudies-literature
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: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:CTCs in cancer patients are thought to be responsible for metastasis. Currently, there is no ex vivo model that can isolate this group of cells. We have developed an ex vivo 4D lung cancer model that forms perfusable tumor nodules and form CTCs. Gene array analyses show 2504 differentially expressed genes when comparing CTCs from the 4D model seeded with A549 cells to the same cells grown on a petri dish (2D). We compared the gene expression profile (Human OneArray v5 chip) of A549 cells, human lung cancer cell line, grown on petri dish (2D) and same cells circulating as tumor cells in our ex vivo model (4D/CTC).
| S-ECPF-GEOD-50991 | biostudies-other
Project description:Circulating tumor cells (CTCs) are cancer cells that detach from the primary tumor and intravasate into the bloodstream. Thus, non-invasive liquid biopsies are being used to analyze CTC-expressed genes to identify potential cancer biomarkers. In this regard, several studies have used gene expression changes in blood to predict the presence of CTC and, consequently, cancer. However, the CTC mRNA data has not been used to develop a generic approach that indicates the presence of multiple cancer types. In this study, we developed such a generic approach. Briefly, we designed two computational workflows, one using the raw mRNA data and deep learning (DL) and the other exploiting five hub gene ranking algorithms (Degree, Maximum Neighborhood Component, Betweenness Centrality, Closeness Centrality, and Stress Centrality) with machine learning (ML). Both workflows aim to determine the top genes that best distinguish cancer types based on the CTC mRNA data. We demonstrate that our automated, robust DL framework (DNNraw) more accurately indicates the presence of multiple cancer types using the CTC gene expression data than multiple ML approaches. The DL approach achieved average precision of 0.9652, recall of 0.9640, f1-score of 0.9638 and overall accuracy of 0.9640. Furthermore, since we designed multiple approaches, we also provide a bioinformatics analysis of the gene commonly identified as top-ranked by the different methods. To our knowledge, this is the first study wherein a generic approach has been developed to predict the presence of multiple cancer types using raw CTC mRNA data, as opposed to other models that require a feature selection step.
| S-EPMC10689793 | biostudies-literature