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Biomedical subjects

Marc J van de Vijver

Publications and source records attributed to Marc J van de Vijver.

18 recordsLinked to original sources
PubMed2006

Gene expression profiles of primary breast carcinomas from patients at high risk for local recurrence after breast-conserving therapy.

PURPOSE: Several risk factors for local recurrence of breast cancer after breast-conserving therapy (BCT) have been identified. The identification of additional risk factors would be very useful in guiding optimal therapy and also in improving understanding of the mechanisms underlying local recurrence. We used cDNA microarray analysis to identify gene expression profiles associated with local recurrence. EXPERIMENTAL DESIGN: Using 18K cDNA microarrays, gene expression profiles were obtained from 50 patients who underwent BCT. Of these 50 patients, 19 developed a local recurrence; the remaining 31 patients were selected as controls as they were free of local recurrence at least 11 years after treatment. For 9 of 19 patients, the local recurrence was also available for gene expression profiling. Unsupervised and supervised methods of classification were used to separate patients in groups corresponding to disease outcome and to study the overall gene expression pattern of primary tumors and their recurrences. RESULTS: Hierarchical clustering of patients did not show any grouping reflecting local recurrence status. Supervised analysis revealed no significant set of genes that was able to distinguish recurring tumors from nonrecurring tumors. Paired-data analysis of primary tumors and local recurrences showed a remarkable similarity in gene expression profile between primary tumors and their recurrences. CONCLUSIONS: No significant differences in gene expression between primary breast cancer tumors in patients with or without local recurrence after BCT were identified. Furthermore, analyses of primary tumors and local recurrences show a preservation of the overall gene expression pattern in the local recurrence, even after radiotherapy.

Adult↗
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

Technology Insight: tuning into the genetic orchestra using microarrays--limitations of DNA microarrays in clinical practice.

Scientific advances in the field of genetics and gene-expression profiling have revolutionized the concept of patient-tailored treatment. Analysis of differential gene-expression patterns across thousands of biological samples in a single experiment (as opposed to hundreds to thousands of experiments measuring the expression of one gene at a time), and extrapolation of these data to answer clinically pertinent questions such as those relating to tumor metastatic potential, can help define the best therapeutic regimens for particular patient subgroups. The use of microarrays provides a powerful technology, allowing in-depth analysis of gene-expression profiles. Currently, microarray technology is in a transition phase whereby scientific information is beginning to guide clinical practice decisions. Before microarrays qualify as a useful clinical tool, however, they must demonstrate reliability and reproducibility. The high-throughput nature of microarray experiments imposes numerous limitations, which apply to simple issues such as sample acquisition and data mining, to more controversial issues that relate to the methods of biostatistical analysis required to analyze the enormous quantities of data obtained. Methods for validating proposed gene-expression profiles and those for improving trial designs represent some of the recommendations that have been suggested. This Review focuses on the limitations of microarray analysis that are continuously being recognized, and discusses how these limitations are being addressed.

Clinical Trials as Topic↗
PubMed2006

Classification of ductal carcinoma in situ by gene expression profiling.

INTRODUCTION: Ductal carcinoma in situ (DCIS) is characterised by the intraductal proliferation of malignant epithelial cells. Several histological classification systems have been developed, but assessing the histological type/grade of DCIS lesions is still challenging, making treatment decisions based on these features difficult. To obtain insight in the molecular basis of the development of different types of DCIS and its progression to invasive breast cancer, we have studied differences in gene expression between different types of DCIS and between DCIS and invasive breast carcinomas. METHODS: Gene expression profiling using microarray analysis has been performed on 40 in situ and 40 invasive breast cancer cases. RESULTS: DCIS cases were classified as well- (n = 6), intermediately (n = 18), and poorly (n = 14) differentiated type. Of the 40 invasive breast cancer samples, five samples were grade I, 11 samples were grade II, and 24 samples were grade III. Using two-dimensional hierarchical clustering, the basal-like type, ERB-B2 type, and the luminal-type tumours originally described for invasive breast cancer could also be identified in DCIS. CONCLUSION: Using supervised classification, we identified a gene expression classifier of 35 genes, which differed between DCIS and invasive breast cancer; a classifier of 43 genes could be identified separating between well- and poorly differentiated DCIS samples.

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

Biological variables and prognosis of DCIS.

Based on current knowledge, biological factors that have been investigated in ductal carcinoma in situ (DCIS) include histology of these lesions, the impact of margin status on local recurrence, and several genetic alterations. Optimal integration of these factors in guiding optimal therapy is of great importance, since the incidence of DCIS is rising as a result of population-based mammographic screening. Mastectomy will almost always cure patients with DCIS but represents overtreatment for many. Less extensive treatment options should combine an optimal cosmetic result with the same safety for outcome of disease as mastectomy. To guide such optimal treatment, histological classification is not sufficient and additional biological factors are being investigated for their ability to predict outcome for individual patients with DCIS. In this review, the histological classification of DCIS is described and in addition the emerging knowledge on genetic alterations is summarised. For clinical management of DCIS patients, genetic or other biological factors should be identified that can predict the risk of progression of DCIS to invasive breast cancer and distant metastases. At present, insufficient knowledge on prognostic and predictive factors in DCIS is available. Research in this area is hampered by the difficulties in obtaining DCIS tumour tissue, as the tumour cells grow in the lumen of pre-existing ducts and lobules. As the recurrence rates are relatively low and the most relevant clinical endpoint, distant metastases, is indeed very rare, large numbers of patients (hundreds to a few thousand) need to be studied. Integration of translational studies into clinical trials aimed at optimising the treatment of DCIS are required to achieve this goal.

Biomarkers, Tumor↗
PubMed2005

Changes in gene expression associated with response to neoadjuvant chemotherapy in breast cancer.

PURPOSE: At present, clinically useful markers predicting response of primary breast carcinomas to either doxorubicin-cyclophosphamide (AC) or doxorubicin-docetaxel (AD) are lacking. We investigated whether gene expression profiles of the primary tumor could be used to predict treatment response to either of those chemotherapy regimens. PATIENTS AND METHODS: Within a single-institution, randomized, phase II trial, patients with locally advanced breast cancer received six courses of either AC (n = 24) or AD (n = 24) neoadjuvant chemotherapy. Gene expression profiles were generated from core-needle biopsies obtained before treatment and correlated with the response of the primary tumor to the chemotherapy administered. Additionally, pretreatment gene expression profiles were compared with those in tumors remaining after chemotherapy. RESULTS: Ten (20%) of 48 patients showed a (near) pathologic complete remission of the primary tumor after treatment. No gene expression pattern correlating with response could be identified for all patients or for the AC or AD groups separately. The comparison of the pretreatment biopsy and the tumor excised after chemotherapy revealed differences in gene expression in tumors that showed a partial remission but not in tumors that did not respond to chemotherapy. CONCLUSION: No gene expression profile predicting the response of primary breast carcinomas to AC- or AD-based neoadjuvant chemotherapy could be detected in this interim analysis. More subtle differences in gene expression are likely to be present but can only be reliably identified by studying a larger group of patients. Response of a breast tumor to neoadjuvant chemotherapy results in alterations in gene expression.

Adult↗
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↗
PubMed2004

Predicting early failure after adjuvant chemotherapy in high-risk breast cancer patients with extensive lymph node involvement.

PURPOSE: There is limited knowledge of risk factors for breast cancer recurrence within 2 years. This study aimed to predict early failure and identify high-risk patients for prognostic and therapeutic purposes. EXPERIMENTAL DESIGN: We studied 739 patients from a randomized trial who were <56 years of age and had >/=4 or more positive lymph nodes, no distant metastases, and no previous other malignancies. After complete surgical treatment, patients received conventional-dose anthracycline-based chemotherapy or a high-dose scheme of anthracycline-based plus alkylating chemotherapy. We assessed clinical and (immuno)histological parameters to predict recurrence within 2 years. RESULTS: Early failure occurred in 19% (n = 137). Median survival after early failure was limited to 0.7 year. Estrogen and progesterone receptor negativity and visceral relapse predicted poor prognosis. Early failure was associated with young age, large tumors, high histological grade, angio-invasion, apical node metastasis, and >/=10 involved nodes. Estrogen receptor, progesterone receptor, and p27 negativity; HER2 overexpression; and p53 positivity also predicted early failure. The surgical or chemotherapy regimen and histological type did not. The same parameters except tumor size were associated with early death. Grade III, >/=10 involved nodes, and estrogen receptor negativity were independently associated with early failure and together identified a subset of patients (7%) with 3-fold increased early failure and 5-fold increased early death. CONCLUSIONS: Early failure is associated with poor survival. The combination of three commonly determined parameters constitutes a strong predictive model for early failure and death.

Adult↗
PubMed2004

Different mechanisms of chromosome 16 loss of heterozygosity in well- versus poorly differentiated ductal breast cancer.

Loss of heterozygosity (LOH) at the long arm of chromosome 16 is a frequent genetic alteration in breast cancer. It can occur by physical loss of part of or the entire chromosomal arm, resulting in a decrease in copy number or loss followed by mitotic recombination. Comparative genomic hybridization (CGH) demonstrated that well-differentiated breast tumors showed significantly more physical loss of 16q than did poorly differentiated ones and that this difference was already discernable in the preinvasive stage. However, polymorphic markers detected no difference in the frequency of 16q LOH between invasive tumors of different histological grade. Here, by combining data on LOH (n=52), fluorescence in situ hybridization (n=18) with chromosome 16-specific probes, and CGH (n=34), we show a preference in well-differentiated grade I tumors for physical loss of chromosome arm 16q, whereas in poorly differentiated grade III tumors LOH is accompanied by mitotic recombination. This clarifies the discrepancies observed between CGH and LOH for 16q in breast cancer. These different somatic genetic mechanisms may reflect the presence of multiple tumor suppressor genes that are the target of LOH at chromosome arm 16q.

Breast Neoplasms↗
PubMed2004

A distinct phenotype characterizes tumors from a putative genetic trait involving chondrosarcoma and breast cancer occurring in the same patient.

Recently, we documented an increased risk for the occurrence of breast- and cartilaginous tumors in the same patient, statistically pointing towards a potential genetic trait. This trait is most probably not associated with mutations in the two major hereditary breast cancer genes since no cases of enchondroma or chondrosarcoma were found in Dutch BRCA1 and BRCA2 families. We were able to collect and review the tumor tissue samples from 34 patients with both breast- and cartilaginous tumors and compared histopathological and immunohistochemical features of these tumors with controls. Breast cancer controls were available from literature data generated to compare familial breast cancers with nonselected cases. Clinical markers for chondrosarcoma controls were collected from the Netherlands Committee of Bone Tumors. Immunohistochemical data on chondro-tumor controls were available from our own files. Breast tumors of patients with cartilaginous sarcomas showed a significantly higher mitotic count (P=0.001), contained less lymphocyte infiltrate (P=0.025) and less nuclear pleomorphism. Remarkably, all cartilaginous tumors are of one common histological category originating centrally (P=0.014). Estrogen receptor and p53 expression were significantly higher (P<0.001) in breast cancer associated with chondro-tumors. p21 staining was more often negative in chondro-tumors associated with breast cancer. In seven cases of breast cancer, we found a slight decrease in CHEK2 expression. However, we could not identify the CHEK2 1100delC mutation in these cases nor in cases with normal CHEK2 expression. Hierarchical cluster analysis of all parameters within chondro-tumor-associated breast cancer specimens revealed two different subgroups, the largest one associated with estrogen receptor-positive breast cancer, which may distinguish sporadic cases from those belonging to the potential genetic trait. These distinct phenotypic findings support the existence of a new hitherto unrecognized syndrome, characterized by an increased risk to develop both breast cancer and centrally originating cartilaginous tumors.

Adenocarcinoma↗
PubMed2003

Association of C-MYC amplification with progression from the in situ to the invasive stage in C-MYC-amplified breast carcinomas.

Human carcinoma in situ of the breast already demonstrates genomic changes found in invasive lesions. However, no specific genetic alterations have previously been identified that are associated with progression from the in situ to the invasive stage. By comparative genomic hybridization (CGH) and fluorescence in situ hybridization (FISH) analysis of an invasive breast carcinoma with a large associated in situ component, high-level amplification of C-MYC was found in the invasive component only. To determine the frequency of this correlation in a panel of 188 invasive breast carcinomas, 18 additional cases with C-MYC amplification were identified. Nine of these cases had a detectable adjacent in situ component. FISH analysis demonstrated increased (>5) C-MYC signals per nucleus in seven invasive components and increased (>4) C-MYC/centromere 8 signal ratios in five of these. None of the associated in situ components demonstrated these increases. The minimal amplified region was defined at 8q24.13-8qter. C-MYC amplification was correlated with overexpression of C-MYC and two of its target genes, TERT and FBL. Thus, C-MYC amplification is the first identified genetic alteration that is associated with progression from the in situ to the invasive stage of breast carcinoma.

Adult↗
PubMed2002

A gene-expression signature as a predictor of survival in breast cancer.

BACKGROUND: A more accurate means of prognostication in breast cancer will improve the selection of patients for adjuvant systemic therapy. METHODS: Using microarray analysis to evaluate our previously established 70-gene prognosis profile, we classified a series of 295 consecutive patients with primary breast carcinomas as having a gene-expression signature associated with either a poor prognosis or a good prognosis. All patients had stage I or II breast cancer and were younger than 53 years old; 151 had lymph-node-negative disease, and 144 had lymph-node-positive disease. We evaluated the predictive power of the prognosis profile using univariable and multivariable statistical analyses. RESULTS: Among the 295 patients, 180 had a poor-prognosis signature and 115 had a good-prognosis signature, and the mean (+/-SE) overall 10-year survival rates were 54.6+/-4.4 percent and 94.5+/-2.6 percent, respectively. At 10 years, the probability of remaining free of distant metastases was 50.6+/-4.5 percent in the group with a poor-prognosis signature and 85.2+/-4.3 percent in the group with a good-prognosis signature. The estimated hazard ratio for distant metastases in the group with a poor-prognosis signature, as compared with the group with the good-prognosis signature, was 5.1 (95 percent confidence interval, 2.9 to 9.0; P<0.001). This ratio remained significant when the groups were analyzed according to lymph-node status. Multivariable Cox regression analysis showed that the prognosis profile was a strong independent factor in predicting disease outcome. CONCLUSIONS: The gene-expression profile we studied is a more powerful predictor of the outcome of disease in young patients with breast cancer than standard systems based on clinical and histologic criteria.

Adult↗
PubMed2002

Gene expression profiling predicts clinical outcome of breast cancer.

Breast cancer patients with the same stage of disease can have markedly different treatment responses and overall outcome. The strongest predictors for metastases (for example, lymph node status and histological grade) fail to classify accurately breast tumours according to their clinical behaviour. Chemotherapy or hormonal therapy reduces the risk of distant metastases by approximately one-third; however, 70-80% of patients receiving this treatment would have survived without it. None of the signatures of breast cancer gene expression reported to date allow for patient-tailored therapy strategies. Here we used DNA microarray analysis on primary breast tumours of 117 young patients, and applied supervised classification to identify a gene expression signature strongly predictive of a short interval to distant metastases ('poor prognosis' signature) in patients without tumour cells in local lymph nodes at diagnosis (lymph node negative). In addition, we established a signature that identifies tumours of BRCA1 carriers. The poor prognosis signature consists of genes regulating cell cycle, invasion, metastasis and angiogenesis. This gene expression profile will outperform all currently used clinical parameters in predicting disease outcome. Our findings provide a strategy to select patients who would benefit from adjuvant therapy.

Adult↗
PubMed2002

Expression of the breast cancer resistance protein in breast cancer.

PURPOSE: The breast cancer resistance protein (BCRP) is involved in in vitro multidrug resistance and was first identified in the breast cancer cell line MCF7/AdrVp. The aim of this study was to investigate the role of BCRP in resistance of breast cancer to anthracycline treatment. EXPERIMENTAL DESIGN: BCRP mRNA was determined with real-time reverse transcription-PCR and immunostaining in nine breast cancer cell lines and in samples of 25 primary breast carcinomas and 27 patients who received preoperative anthracycline-based therapy. Tumor response to treatment and patient survival were recorded. RESULTS: In cell lines, only MCF7 and BT20 had BCRP mRNA levels coinciding with membrane-bound immunostaining. In clinical samples, BCRP expression varied widely (range, 0.01-0.86). With immunohistochemistry, BCRP was detected in vessels and normal breast epithelium but not in tumor cells. There was no difference in BCRP expression between anthracycline-naïve and treated tumor samples. BCRP expression was not associated with decreased response or survival. CONCLUSIONS: There is no indication that elevated BCRP expression in breast carcinomas confers resistance to anthracyclines. Expression was not detectable with immunohistochemistry.

ATP Binding Cassette Transporter, Subfamily G, Mem↗
PubMedDate not supplied

Multidrug resistance associated genes MRP1, MRP2 and MRP3 in primary and anthracycline exposed breast cancer.

BACKGROUND: Multidrug resistance associated proteins MRP1, MRP2 and MRP3 confer in vitro multidrug resistance. We investigated their role in breast cancer resistance to anthracycline-based chemotherapy. MATERIALS AND METHODS: Using real-time reverse transcriptase polymerase chain reaction (RT-PCR) and immunohistochemistry (IHC), the expression of MRP1 - 3 was quantified in nine breast cancer cell lines and 30 breast carcinoma samples. RESULTS: MRP1 - 3 mRNA was detectable in all breast cancer cell lines and tumor samples. No increase of expression was detected between untreated carcinoma and post-neoadjuvant anthracycline treatment tumor samples. IHC failed to detect the proteins. MRP1 - 3 expression was not associated with tumor response to treatment or with outcome. CONCLUSION: MRP1 - 3 are expressed in breast cancer cells, but are not detected with IHC. We have found no evidence linking these proteins to clinical drug resistance in a small but well-documented series of breast cancer samples.

Anthracyclines↗