Biomedical subjects

Dimitry S A Nuyten

Publications and source records attributed to Dimitry S A Nuyten.

6 recordsLinked to original sources

PubMed2006

Concordance among gene-expression-based predictors for breast cancer.

BACKGROUND: Gene-expression-profiling studies of primary breast tumors performed by different laboratories have resulted in the identification of a number of distinct prognostic profiles, or gene sets, with little overlap in terms of gene identity. METHODS: To compare the predictions derived from these gene sets for individual samples, we obtained a single data set of 295 samples and applied five gene-expression-based models: intrinsic subtypes, 70-gene profile, wound response, recurrence score, and the two-gene ratio (for patients who had been treated with tamoxifen). RESULTS: We found that most models had high rates of concordance in their outcome predictions for the individual samples. In particular, almost all tumors identified as having an intrinsic subtype of basal-like, HER2-positive and estrogen-receptor-negative, or luminal B (associated with a poor prognosis) were also classified as having a poor 70-gene profile, activated wound response, and high recurrence score. The 70-gene and recurrence-score models, which are beginning to be used in the clinical setting, showed 77 to 81 percent agreement in outcome classification. CONCLUSIONS: Even though different gene sets were used for prognostication in patients with breast cancer, four of the five tested showed significant agreement in the outcome predictions for individual patients and are probably tracking a common set of biologic phenotypes.

Analysis of Variance↗

PubMed2006

Genetic regulators of large-scale transcriptional signatures in cancer.

Gene expression signatures encompassing dozens to hundreds of genes have been associated with many important parameters of cancer, but mechanisms of their control are largely unknown. Here we present a method based on genetic linkage that can prospectively identify functional regulators driving large-scale transcriptional signatures in cancer. Using this method we show that the wound response signature, a poor-prognosis expression pattern of 512 genes in breast cancer, is induced by coordinate amplifications of MYC and CSN5 (also known as JAB1 or COPS5). This information enabled experimental recapitulation, functional assessment and mechanistic elucidation of the wound signature in breast epithelial cells.

Breast Neoplasms↗

PubMed2006

Predicting a local recurrence after breast-conserving therapy by gene expression profiling.

INTRODUCTION: To tailor local treatment in breast cancer patients there is a need for predicting ipsilateral recurrences after breast-conserving therapy. After adequate treatment (excision with free margins and radiotherapy), young age and incompletely excised extensive intraductal component are predictors for local recurrence, but many local recurrences can still not be predicted. Here we have used gene expression profiling by microarray analysis to identify gene expression profiles that can help to predict local recurrence in individual patients. METHODS: By using previously established gene expression profiles with proven value in predicting metastasis-free and overall survival (wound-response signature, 70-gene prognosis profile and hypoxia-induced profile) and training towards an optimal prediction of local recurrences in a training series, we establish a classifier for local recurrence after breast-conserving therapy. RESULTS: Validation of the different gene lists shows that the wound-response signature is able to separate patients with a high (29%) or low (5%) risk of a local recurrence at 10 years (sensitivity 87.5%, specificity 75%). In multivariable analysis the classifier is an independent predictor for local recurrence. CONCLUSION: Our findings indicate that gene expression profiling can identify subgroups of patients at increased risk of developing a local recurrence after breast-conserving therapy.

Adult↗

PubMed2006

Gene expression programs in response to hypoxia: cell type specificity and prognostic significance in human cancers.

BACKGROUND: Inadequate oxygen (hypoxia) triggers a multifaceted cellular response that has important roles in normal physiology and in many human diseases. A transcription factor, hypoxia-inducible factor (HIF), plays a central role in the hypoxia response; its activity is regulated by the oxygen-dependent degradation of the HIF-1alpha protein. Despite the ubiquity and importance of hypoxia responses, little is known about the variation in the global transcriptional response to hypoxia among different cell types or how this variation might relate to tissue- and cell-specific diseases. METHODS AND FINDINGS: We analyzed the temporal changes in global transcript levels in response to hypoxia in primary renal proximal tubule epithelial cells, breast epithelial cells, smooth muscle cells, and endothelial cells with DNA microarrays. The extent of the transcriptional response to hypoxia was greatest in the renal tubule cells. This heightened response was associated with a uniquely high level of HIF-1alpha RNA in renal cells, and it could be diminished by reducing HIF-1alpha expression via RNA interference. A gene-expression signature of the hypoxia response, derived from our studies of cultured mammary and renal tubular epithelial cells, showed coordinated variation in several human cancers, and was a strong predictor of clinical outcomes in breast and ovarian cancers. In an analysis of a large, published gene-expression dataset from breast cancers, we found that the prognostic information in the hypoxia signature was virtually independent of that provided by the previously reported wound signature and more predictive of outcomes than any of the clinical parameters in current use. CONCLUSIONS: The transcriptional response to hypoxia varies among human cells. Some of this variation is traceable to variation in expression of the HIF1A gene. A gene-expression signature of the cellular response to hypoxia is associated with a significantly poorer prognosis in breast and ovarian cancer.

Adult↗

PubMed2005

Determination of stromal signatures in breast carcinoma.

Many soft tissue tumors recapitulate features of normal connective tissue. We hypothesize that different types of fibroblastic tumors are representative of different populations of fibroblastic cells or different activation states of these cells. We examined two tumors with fibroblastic features, solitary fibrous tumor (SFT) and desmoid-type fibromatosis (DTF), by DNA microarray analysis and found that they have very different expression profiles, including significant differences in their patterns of expression of extracellular matrix genes and growth factors. Using immunohistochemistry and in situ hybridization on a tissue microarray, we found that genes specific for these two tumors have mutually specific expression in the stroma of nonneoplastic tissues. We defined a set of 786 gene spots whose pattern of expression distinguishes SFT from DTF. In an analysis of DNA microarray gene expression data from 295 previously published breast carcinomas, we found that expression of this gene set defined two groups of breast carcinomas with significant differences in overall survival. One of the groups had a favorable outcome and was defined by the expression of DTF genes. The other group of tumors had a poor prognosis and showed variable expression of genes enriched for SFT type. Our findings suggest that the host stromal response varies significantly among carcinomas and that gene expression patterns characteristic of soft tissue tumors can be used to discover new markers for normal connective tissue cells.

Breast Neoplasms↗

PubMed2005

Robustness, scalability, and integration of a wound-response gene expression signature in predicting breast cancer survival.

Based on the hypothesis that features of the molecular program of normal wound healing might play an important role in cancer metastasis, we previously identified consistent features in the transcriptional response of normal fibroblasts to serum, and used this "wound-response signature" to reveal links between wound healing and cancer progression in a variety of common epithelial tumors. Here, in a consecutive series of 295 early breast cancer patients, we show that both overall survival and distant metastasis-free survival are markedly diminished in patients whose tumors expressed this wound-response signature compared to tumors that did not express this signature. A gene expression centroid of the wound-response signature provides a basis for prospectively assigning a prognostic score that can be scaled to suit different clinical purposes. The wound-response signature improves risk stratification independently of known clinico-pathologic risk factors and previously established prognostic signatures based on unsupervised hierarchical clustering ("molecular subtypes") or supervised predictors of metastasis ("70-gene prognosis signature").

Breast Neoplasms↗