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Biomedical subjects

Laura J van't Veer

Publications and source records attributed to Laura J van't Veer.

At least 19 recordsLinked to original sources
PubMed2007

Gene-expression and immunohistochemical study of specific T-cell subsets and accessory cell types in the transformation and prognosis of follicular lymphoma.

PURPOSE: Despite the generally favorable clinical course in follicular lymphoma (FL), a minority of patients have a poor prognosis-with death within 3 years of diagnosis-most often due to transformation to aggressive disease. PATIENTS AND METHODS: In this study, we analyzed the potential of predicting early transformation on the basis of gene expression and immunologic parameters in FL biopsy samples taken at diagnosis. RESULTS: At the gene-expression level, FL is a highly uniform disease at the time of diagnosis, precluding the detection of sufficiently validated prognostic gene-expression profiles suitable for a clinical setting. Combinations of differentially expressed genes indicate that immunologic mechanisms play a differential role in the risk of early transformation. Using immunohistochemistry for specific cell populations, the spatial distribution to neoplastic follicles and the activation of CD4-positive T-helper cells (P = .002) and specifically T-helper 1 (P = .004) were shown to be highly discriminatory to predict early transformation. A role for functional modulation of follicular dendritic cells could also be supported (P = .04). Other cell populations, including CD68-positive macrophages and regulatory T cells, were not differentially present. CONCLUSION: These results support the identification of FL as an immunologically functional disease in which an interaction of the tumor cells and the functional composition of the microenvironment determines the clinical behavior.

Adult↗
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

A comparison of univariate and multivariate gene selection techniques for classification of cancer datasets.

BACKGROUND: Gene selection is an important step when building predictors of disease state based on gene expression data. Gene selection generally improves performance and identifies a relevant subset of genes. Many univariate and multivariate gene selection approaches have been proposed. Frequently the claim is made that genes are co-regulated (due to pathway dependencies) and that multivariate approaches are therefore per definition more desirable than univariate selection approaches. Based on the published performances of all these approaches a fair comparison of the available results can not be made. This mainly stems from two factors. First, the results are often biased, since the validation set is in one way or another involved in training the predictor, resulting in optimistically biased performance estimates. Second, the published results are often based on a small number of relatively simple datasets. Consequently no generally applicable conclusions can be drawn. RESULTS: In this study we adopted an unbiased protocol to perform a fair comparison of frequently used multivariate and univariate gene selection techniques, in combination with a ränge of classifiers. Our conclusions are based on seven gene expression datasets, across several cancer types. CONCLUSION: Our experiments illustrate that, contrary to several previous studies, in five of the seven datasets univariate selection approaches yield consistently better results than multivariate approaches. The simplest multivariate selection approach, the Top Scoring method, achieves the best results on the remaining two datasets. We conclude that the correlation structures, if present, are difficult to extract due to the small number of samples, and that consequently, overly-complex gene selection algorithms that attempt to extract these structures are prone to overtraining.

Algorithms↗
PubMed2005

Pulmonary squamous cell carcinoma following head and neck squamous cell carcinoma: metastasis or second primary?

PURPOSE: To distinguish a metastasis from a second primary tumor in patients with a history of head and neck squamous cell carcinoma and subsequent pulmonary squamous cell carcinoma. EXPERIMENTAL DESIGN: For 44 patients with a primary squamous cell carcinoma of the head and neck followed by a squamous cell carcinoma of the lung, clinical data, histology, and analysis of loss of heterozygosity (LOH) were used to differentiate metastases from second primary tumors. RESULTS: Clinical evaluation suggested 38 patients with metastases and 6 with second primaries. We developed a novel interpretation strategy based on biological insight and on our observation that multiple LOH on different chromosome arms are not independent. LOH analysis indicated metastatic disease in 19 cases and second primary squamous cell carcinoma in 24 cases. In one case, LOH analysis was inconclusive. For 25 patients, LOH supported the clinical scoring, and in 18 cases, it did not. These 18 discordant cases were all considered to be second primary tumors by LOH analysis. CONCLUSIONS: A considerable number of squamous cell lung lesions (50% in this study), clinically interpreted as metastases, are suggested to be second primaries by LOH analysis. For these patients, a surgical approach with curative intent may be justified.

Adult↗
PubMed2005

A protocol for building and evaluating predictors of disease state based on microarray data.

MOTIVATION: Microarray gene expression data are increasingly employed to identify sets of marker genes that accurately predict disease development and outcome in cancer. Many computational approaches have been proposed to construct such predictors. However, there is, as yet, no objective way to evaluate whether a new approach truly improves on the current state of the art. In addition no 'standard' computational approach has emerged which enables robust outcome prediction. RESULTS: An important contribution of this work is the description of a principled training and validation protocol, which allows objective evaluation of the complete methodology for constructing a predictor. We review the possible choices of computational approaches, with specific emphasis on predictor choice and reporter selection strategies. Employing this training-validation protocol, we evaluated different reporter selection strategies and predictors on six gene expression datasets of varying degrees of difficulty. We demonstrate that simple reporter selection strategies (forward filtering and shrunken centroids) work surprisingly well and outperform partial least squares in four of the six datasets. Similarly, simple predictors, such as the nearest mean classifier, outperform more complex classifiers. Our training-validation protocol provides a robust methodology to evaluate the performance of new computational approaches and to objectively compare outcome predictions on different datasets.

Algorithms↗
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↗
PubMed2005

Comparative genomic hybridization profiles in human BRCA1 and BRCA2 breast tumors highlight differential sets of genomic aberrations.

BRCA1 or BRCA2 germline mutations cause approximately 30% of breast cancers within high-risk families. This represents 5% of total breast cancer incidence. Although BRCA1 and BRCA2 are both implicated in DNA repair and genome stability, it is unknown whether BRCA1 and BRCA2 are associated with similar or distinct diseases. In a previous study we reported that BRCA1-related breast carcinomas show a distinct genomic profile as determined by comparative genomic hybridization (CGH). We now hypothesize that, if functionally equivalent, mutations in BRCA1 and BRCA2 would result in similar genomic profiles in tumors. Here we report the chromosomal gains and losses as measured by CGH in 25 BRCA2-associated breast tumors and compared them with our existing 36 BRCA1 and 30 control profiles. We compared all chromosomal regions and determined the regions of differential gain or loss between tumor classes and controls. BRCA2 and control tumors have very similar genomic profiles. As a consequence, and in contrast to BRCA1-associated tumors, CGH profiles from BRCA2-associated tumors could not be distinguished from control tumors using the classification methodology as we have developed before. The largest number of significant differences existed between BRCA1 and controls, followed by BRCA1 compared with BRCA2, suggesting different tumor development pathways for BRCA1 and BRCA2.

Breast Neoplasms↗
PubMed2005

The insulin-like growth factor system in cancer prevention: potential of dietary intervention strategies.

The insulin-like growth factor (IGF) system is related to proliferation and tumor growth, and high levels of circulating IGF-I are thought to be a risk factor for several types of cancer. This review summarizes the epidemiologic evidence for an association between circulating IGF-I and cancer risk as well as the experimental evidence for a causal relation between the endocrine IGF system and tumor growth. The potential for dietary intervention to alter the IGF system and thereby cancer risk is supported by several lines of evidence. Postulated mechanisms of action are as follows: (a) reduction of levels of circulating IGF-I, which will decrease activation of the IGF-I receptor and subsequent signaling pathways; (b) increasing local IGF binding proteins, which may have IGF-dependent effects through obstruction of IGF interaction with local IGF-I receptor as well as IGF-independent effects; and (c) interference with estrogens and estrogen receptor action, which may have direct (and possibly synergistic) effects on IGF signaling. An overview is given of the epidemiologic studies on dietary determinants of circulating IGF-I. Examples of dietary factors, such as dairy protein, lycopene, and phytoestrogens, are used to illustrate the potential mode of action of dietary interventions that may act on the IGF system. In conclusion, the IGF system has every potential to serve as an intermediate for cancer (chemo)prevention studies. On the short term, more research initiatives aimed at the effects of specific food components or dietary strategies on the IGF system both in animal models and in humans are warranted.

Animals↗
PubMed2004

Gene expression profiling in follicular lymphoma to assess clinical aggressiveness and to guide the choice of treatment.

Follicular lymphoma (FL) is a disease characterized by a long clinical course marked by frequent relapses that vary in clinical aggressiveness over time. Therefore, the main dilemma at each relapse is the choice for the most effective treatment for optimal disease control and failure-free survival while at the same time avoiding overtreatment and harmful side effects. The selection for more aggressive treatment is currently based on histologic grading and clinical criteria; however, in up to 30% of all cases these methods prove to be insufficient. Using supervised classification on a training set of paired samples from patients who experienced either an indolent or aggressive disease course, a gene expression profile of 81 genes was established that could, with an accuracy of 100%, distinguish low-grade from high-grade disease. This profile accurately classified 93% of the FL samples in an independent validation set. Most important, in a third series of FL cases where histologic grading was ambiguous, precluding meaningful morphologic guidance, the 81-gene profile shows a classification accuracy of 94%. The FL stratification profile is a more reliable marker of clinical behavior than the currently used histologic grading and clinical criteria and may provide an important alternative to guide the choice of therapy in patients with FL both at presentation and at relapse.

Adult↗
PubMed2004

Hard-wired genotype in metastatic breast cancer.

Recently, we showed by gene-expression profiling that the molecular program established in a human primary breast carcinoma is highly preserved in its distant metastases. According to the predominant model of metastasis, the capacity of a primary tumor to metastasize is acquired only rarely and late in tumorigenesis. Our findings challenge this common theory and imply that the metastatic nature of 'poor prognosis profile' breast carcinomas is an inherent feature, and not reserved to advantageous subpopulations.

Animals↗
PubMed2004

Excess risk for contralateral breast cancer in CHEK2*1100delC germline mutation carriers.

We detected a significant excess risk for CHEK2*1100delC mutation carriers to develop a contralateral breast tumor, OR = 6.5 (95% CI 1.5-28.8, p = 0.005). The highest percentage of mutation carriers was detected among those bilateral breast cancer patients who had received radiation treatment for their first breast tumor. These results warrant prolonged medical surveillance and may indicate a clinically important interaction between CHEK2 heterozygosity and radiation in the development of contralateral breast cancer.

Adult↗
PubMed2003

Gene expression profiles of primary breast tumors maintained in distant metastases.

It has been debated for decades how cancer cells acquire metastatic capability. It is unclear whether metastases are derived from distinct subpopulations of tumor cells within the primary site with higher metastatic potential, or whether they originate from a random fraction of tumor cells. Here we show, by gene expression profiling, that human primary breast tumors are strikingly similar to the distant metastases of the same patient. Unsupervised hierarchical clustering, multidimensional scaling, and permutation testing, as well as the comparison of significantly expressed genes within a pair, reveal their genetic similarity. Our findings suggest that metastatic capability in breast cancer is an inherent feature and is not based on clonal selection.

Breast Neoplasms↗
PubMed2003

Large genomic deletions and duplications in the BRCA1 gene identified by a novel quantitative method.

We applied a novel method to detect single or multiple exon deletions and amplifications in the BRCA1 gene. The test, called multiplex ligation-dependent probe amplification (MLPA), uses probes designed to hybridize adjacently to the target sequence. After ligation, the joined probes are amplified and quantified. Our two diagnostic laboratories have tested in the recent years 805 families by conventional PCR-based techniques, and found 116 BRCA1 and 28 BRCA2 mutation-positive families. Using MLPA, we have tested the remaining 661 noninformative breast cancer families and identified five distinct BRCA1 germ-line mutations in five families: a deletion of exon 8, a deletion of exons 20-22, a duplication of exon 13 and exons 21-23, respectively, and a triplication, encompassing exons 17-19. Genomic deletions of BRCA1 constitute a substantial fraction of mutations in Dutch breast cancer families. If MLPA had been included in our initial BRCA1 testing, 33 families with a deletion or duplication would have been identified, representing 27% of the total 121 BRCA1 mutation-positive families. The MLPA test for BRCA1 ensures a sensitive and comprehensive high-throughput screening test for genomic rearrangement and can easily be implemented in the molecular analysis of BRCA1.

Blotting, Southern↗
PubMed2003

IVS10-6T>G, an ancient ATM germline mutation linked with breast cancer.

Patients with autosomal recessive multisystemic disorder ataxia-telangiectasia are homozygous or compound heterozygous for mutations in the ataxia-telangiectasia mutated (ATM) gene. Heterozygous carriers of an ATM germline mutation have an increased susceptibility for breast cancer. The subject of this study is one particular germline mutation, the ATM exon 11 splice-site mutation IVS10-6T>G, that has been identified as being associated with an increased risk for breast cancer both in the general population and in high-risk breast cancer families. We investigated the natural history of this mutation, i.e., whether it is frequently arising de novo in a population, or whether it can be traced back to a single ancient mutational event. Genotyping of a number of polymorphic markers (two extragenic and two intragenic microsatellite loci, a single nucleotide insertion/deletion polymorphism, and a dinucleotide insertion/deletion polymorphism) was performed in 18 samples from different populations carrying the IVS10-6T>G mutation (17 unrelated breast cancer patients who were heterozygous carriers of this mutation and a single A-T patient who was homozygous for the IVS10-6T>G mutation). The same markers were also genotyped among 39 unrelated healthy individuals without this mutation. Haplotype analyses revealed one common ancestor in all mutation carriers. By means of a maximum likelihood method, we estimated the age of this mutation to be approximately 2,000 generations. We provide evidence that the IVS10-6T>G mutation occurred only once during human evolution, at least 50,000 years ago. Our results predict that this mutation could be widely distributed across Europe and, probably, the Middle East and Western Asia.

Alternative Splicing↗
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↗