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Search Results: 1 - 10 of 408998 matches for " Laura J Van't Veer "
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A Prognostic Gene Expression Profile That Predicts Circulating Tumor Cell Presence in Breast Cancer Patients
Timothy J. Molloy, Paul Roepman, Bj?rn Naume, Laura J. van't Veer
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0032426
Abstract: 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.
A comparison of univariate and multivariate gene selection techniques for classification of cancer datasets
Carmen Lai, Marcel JT Reinders, Laura J van't Veer, Lodewyk FA Wessels
BMC Bioinformatics , 2006, DOI: 10.1186/1471-2105-7-235
Abstract: 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 r?nge of classifiers. Our conclusions are based on seven gene expression datasets, across several cancer types.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.Gene expression microarrays enable the measurement of the activity levels of thousands of genes on a single glass slide. The number of genes (features) is in the order of thousands while the number of arrays is usually limited to several hundreds, due to the high cost associated with the procedure and the sample availability. In classification tasks a reduction of the feature space is usually performed [1,2]. On the one hand it decreases the complexity of the classification task and thus improves the classification Performance [3-7]. This is especially true when the classifiers employed are sensitive to noise. On the other hand it identifies relevant genes that can be potential biomarkers for the problem under study, and can be used in the clinic or for further studies, e.g. as targets for new types of therapies.A widely used search strategy employs a criterion to evaluate the informativeness of each gene individually. We refer to this approach as univariate gene selection. Several criteria have been proposed in the literature, e.g. Golub et al. [8] introduced the signal-to-noise-ratio (SNR), also employed in [9,10]. Bendor et
Biological Functions of the Genes in the Mammaprint Breast Cancer Profile Reflect the Hallmarks of Cancer
Sun Tian,Paul Roepman,Laura J vant Veer,Rene Bernards
Biomarker Insights , 2010,
Gene Co-Expression Modules as Clinically Relevant Hallmarks of Breast Cancer Diversity
Denise M. Wolf, Marc E. Lenburg, Christina Yau, Aaron Boudreau, Laura J. vant Veer
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0088309
Abstract: Co-expression modules are groups of genes with highly correlated expression patterns. In cancer, differences in module activity potentially represent the heterogeneity of phenotypes important in carcinogenesis, progression, or treatment response. To find gene expression modules active in breast cancer subpopulations, we assembled 72 breast cancer-related gene expression datasets containing ~5,700 samples altogether. Per dataset, we identified genes with bimodal expression and used mixture-model clustering to ultimately define 11 modules of genes that are consistently co-regulated across multiple datasets. Functionally, these modules reflected estrogen signaling, development/differentiation, immune signaling, histone modification, ERBB2 signaling, the extracellular matrix (ECM) and stroma, and cell proliferation. The Tcell/Bcell immune modules appeared tumor-extrinsic, with coherent expression in tumors but not cell lines; whereas most other modules, interferon and ECM included, appeared intrinsic. Only four of the eleven modules were represented in the PAM50 intrinsic subtype classifier and other well-established prognostic signatures; although the immune modules were highly correlated to previously published immune signatures. As expected, the proliferation module was highly associated with decreased recurrence-free survival (RFS). Interestingly, the immune modules appeared associated with RFS even after adjustment for receptor subtype and proliferation; and in a multivariate analysis, the combination of Tcell/Bcell immune module down-regulation and proliferation module upregulation strongly associated with decreased RFS. Immune modules are unusual in that their upregulation is associated with a good prognosis without chemotherapy and a good response to chemotherapy, suggesting the paradox of high immune patients who respond to chemotherapy but would do well without it. Other findings concern the ECM/stromal modules, which despite common themes were associated with different sites of metastasis, possibly relating to the “seed and soil” hypothesis of cancer dissemination. Overall, co-expression modules provide a high-level functional view of breast cancer that complements the “cancer hallmarks” and may form the basis for improved predictors and treatments.
The Prognostic Implications of Macrophages Expressing Proliferating Cell Nuclear Antigen in Breast Cancer Depend on Immune Context
Michael J. Campbell, Denise Wolf, Rita A. Mukhtar, Vickram Tandon, Christina Yau, Alfred Au, Frederick Baehner, Laura vant Veer, Donald Berry, Laura J. Esserman
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0079114
Abstract: Tumor associated macrophages (TAMs) are recruited from the circulation to the tumor site, and can undergo a spectrum of phenotypic changes, with two contrasting activation states described in the literature: the M1 and M2 phenotypes. We previously identified a population of TAMs that express proliferating cell nuclear antigen (PCNA) and are associated with high grade, hormone receptor negative breast cancers and poor outcomes. In the present exploratory study we again found that high PCNA+ TAM counts in pre-treatment tumor biopsies (102 invasive breast cancer cases from the I-SPY 1 Trial, a prospective neoadjuvant trial with serial core biopsies and gene array data) were associated with high grade, hormone receptor negativity, and decreased recurrence free survival. We explored the association of these PCNA+ TAMs with the expression of M1 and M2 related genes and, contrary to expectation, observed that high PCNA+ TAM levels were associated with more M1- than M2-related genes. An immune gene signature, derived from cytotoxic T cell and MHC Class II genes (Tc/ClassII), was developed and we found that high PCNA+ TAM counts, in the context of a low Tc/ClassII signature score, were associated with significantly worse recurrence free survival in all cases and in hormone receptor negative only cases. We observed similar results using a gene signature-proxy for PCNA+ TAMs in a larger independent set of 425 neoadjuvant-treated breast cancer cases. The results of this exploratory study indicate that high numbers of PCNA+ TAMs, in the absence of an anti-tumor immune microenvironment (as indicated by a low Tc/ClassII signature score), are associated with poor outcomes in breast cancer patients treated with neoadjuvant chemotherapy. This, along with the observation that PCNA+ TAMs were associated predominantly with M1-related genes, may provide new insights into the role of the immune microenvironment in breast cancer.
Gene Expression Profiles from Formalin Fixed Paraffin Embedded Breast Cancer Tissue Are Largely Comparable to Fresh Frozen Matched Tissue
Lorenza Mittempergher,Jorma J. de Ronde,Marja Nieuwland,Ron M. Kerkhoven,Iris Simon,Emiel J. Th. Rutgers,Lodewyk F. A. Wessels,Laura J. Van't Veer
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0017163
Abstract: Formalin Fixed Paraffin Embedded (FFPE) samples represent a valuable resource for cancer research. However, the discovery and development of new cancer biomarkers often requires fresh frozen (FF) samples. Recently, the Whole Genome (WG) DASL (cDNA-mediated Annealing, Selection, extension and Ligation) assay was specifically developed to profile FFPE tissue. However, a thorough comparison of data generated from FFPE RNA and Fresh Frozen (FF) RNA using this platform is lacking. To this end we profiled, in duplicate, 20 FFPE tissues and 20 matched FF tissues and evaluated the concordance of the DASL results from FFPE and matched FF material.
The prognostic significance of tumour cell detection in the peripheral blood versus the bone marrow in 733 early-stage breast cancer patients
Timothy J Molloy, Astrid J Bosma, Lars O Baumbusch, Marit Synnestvedt, Elin Borgen, Hege Russnes, Ellen Schlichting, Laura J van't Veer, Bj?rn Naume
Breast Cancer Research , 2011, DOI: 10.1186/bcr2898
Abstract: We assayed CTCs and DTCs at primary surgery in 733 stage I or II breast cancer patients with a median follow-up time of 7.6 years. CTCs were detected in samples of peripheral blood mononuclear cells previously stored in liquid-nitrogen using a previously-developed multi-marker quantitative PCR (QPCR)-based assay. DTCs were detected in bone marrow samples by immunocytochemical analysis using anti-cytokeratin antibodies.CTCs were detected in 7.9% of patients, while DTCs were found in 11.7%. Both CTC and DTC positivity predicted poor metastasis-free survival (MFS) and breast cancer-specific survival (BCSS); MFS hazard ratio (HR) = 2.4 (P < 0.001)/1.9 (P = 0.006), and BCSS HR = 2.5 (P < 0.001)/2.3 (P = 0.01), for CTC/DTC status, respectively). Multivariate analyses demonstrated that CTC status was an independent prognostic variable for both MFS and BCSS. CTC status also identified a subset of patients with significantly poorer outcome among low-risk node negative patients that did not receive adjuvant systemic therapy (MFS HR 2.3 (P = 0.039), BCSS HR 2.9 (P = 0.017)). Using both tests provided increased prognostic information and indicated different relevance within biologically dissimilar breast cancer subtypes.These results support the use of CTC analysis in early breast cancer to generate clinically useful prognostic information.In recent years breast cancer survival rates have been steadily increasing, partly due to earlier diagnoses as a result of increased awareness and widespread mammography screening programmes. Despite these advances, approximately one-third of patients will develop distant metastasis, which represents the terminal step in the progression of the disease. The relative paucity of accurate prognostic tests has made it difficult to identify these high-risk patients to allow for more optimized adjuvant treatment decisions. Similarly, many patients at low risk of developing disseminated disease undergo toxic adjuvant chemotherapy treatments that are
The contribution of CHEK2 to the TP53-negative Li-Fraumeni phenotype
Marielle WG Ruijs, Annegien Broeks, Fred H Menko, Margreet GEM Ausems, Anja Wagner, Rogier Oldenburg, Hanne Meijers-Heijboer, Laura J van't Veer, Senno Verhoef
Hereditary Cancer in Clinical Practice , 2009, DOI: 10.1186/1897-4287-7-4
Abstract: We have screened 65 Dutch TP53-negative LFS/LFL candidate patients for CHEK2 germline mutations to determine their contribution to the LFS/LFL phenotype.We identified six index patients with a CHEK2 sequence variant, four with the c.1100delC variant and two sequence variants of unknown significance, p.Phe328Ser and c.1096-?_1629+?del.Our data show that CHEK2 is not a major LFS susceptibility gene in the Dutch population. However, CHEK2 might be a factor contributing to individual tumour development in TP53-negative cancer-prone families.Li-Fraumeni syndrome (LFS) is a rare autosomal dominant cancer syndrome predisposing for bone and soft tissue sarcoma, breast cancer, brain tumour, adrenocortical carcinoma and leukaemia [1]. The classical LFS criteria are: a proband with sarcoma aged under 45 years and a first-degree relative with any cancer aged under 45 years, plus a first or second-degree relative in the same lineage with any cancer under the age of 45 years or sarcoma at any age [2]. In addition, Li-Fraumeni-like syndrome (LFL) criteria have been formulated as a proband with any childhood tumour or a sarcoma, brain tumour or adrenocortical tumour diagnosed under 45 years of age and a first or second-degree relative in the same lineage with a typical LFS tumour at any age, plus a first or second-degree relative in the same lineage younger than 60 years with any cancer [3]. Less stringent LFL criteria were formulated by Eeles et al. as two first or second-degree relatives with typical LFS-extended tumours (classical LFS tumours plus melanoma, prostate cancer and pancreatic cancer) at any age [4]. The Chompret criteria for TP53 germline mutation testing have been updated in 2008 as: (1) a proband with a tumour belonging to the LFS tumour spectrum (sarcomas, brain tumours, pre-menopausal breast cancer, adrenocortical carcinoma, leukaemia, lung bronchoalveolar cancer) cancer before 46 years of age and at least one first or second-degree relative with an LFS tumour be
ATBF1 and NQO1 as candidate targets for allelic loss at chromosome arm 16q in breast cancer: Absence of somatic ATBF1 mutations and no role for the C609T NQO1 polymorphism
Anne-Marie Cleton-Jansen, Ronald van Eijk, Marcel Lombaerts, Marjanka K Schmidt, Laura J Van't Veer, Katja Philippo, Rhyenne ME Zimmerman, Johannes L Peterse, Vincent TBHM Smit, Tom van Wezel, Cees J Cornelisse
BMC Cancer , 2008, DOI: 10.1186/1471-2407-8-105
Abstract: A cDNA microarray for the 16q region was constructed and analyzed using RNA samples from 39 breast tumors with known LOH status at 16q.Five genes were identified to show lower expression in tumors with LOH at 16q compared to tumors without LOH. The genes for NAD(P)H dehydrogenase quinone (NQO1) and AT-binding transcription factor 1 (ATBF1) were further investigated given their functions as potential TSGs. NQO1 has been implicated in carcinogenesis due to its role in quinone detoxification and in stabilization of p53. One inactive polymorphic variant of NQO1 encodes a product showing reduced enzymatic activity. However, we did not find preferential targeting of the active NQO1 allele in tumors with LOH at 16q. Immunohistochemical analysis of 354 invasive breast tumors revealed that NQO1 protein expression in a subset of breast tumors is higher than in normal epithelium, which contradicts its proposed role as a tumor suppressor gene.ATBF1 has been suggested as a target for LOH at 16q in prostate cancer. We analyzed the entire coding sequence in 48 breast tumors, but did not identify somatic sequence changes. We did find several in-frame insertions and deletions, two variants of which were reported to be somatic pathogenic mutations in prostate cancer. Here, we show that these variants are also present in the germline in 2.5% of 550 breast cancer patients and 2.9% of 175 healthy controls. This indicates that the frequency of these variants is not increased in breast cancer patients. Moreover, there is no preferential LOH of the wildtype allele in breast tumors.Two likely candidate TSGs at 16q in breast cancer, NQO1 and ATBF1, were identified here as showing reduced expression in tumors with 16q LOH, but further analysis indicated that they are not target genes of LOH. Furthermore, our results call into question the validity of the previously reported pathogenic variants of the ATBF1 gene.Chromosome arm 16q is one of the regions most frequently involved in loss of heter
A comprehensive analysis of prognostic signatures reveals the high predictive capacity of the Proliferation, Immune response and RNA splicing modules in breast cancer
Fabien Reyal, Martin H van Vliet, Nicola J Armstrong, Hugo M Horlings, Karin E de Visser, Marlen Kok, Andrew E Teschendorff, Stella Mook, Laura van 't Veer, Carlos Caldas, Remy J Salmon, Marc Vijver, Lodewyk FA Wessels
Breast Cancer Research , 2008, DOI: 10.1186/bcr2192
Abstract: We performed a comprehensive analysis of the performance of nine gene expression signatures on seven different breast cancer datasets. To better characterize the functional processes associated with these signatures, we enlarged each signature by including all probes with a significant correlation to at least one of the genes in the original signature. The enrichment of functional groups was assessed using four ontology databases.The classification performance of the nine gene expression signatures is very similar in terms of assigning a sample to either a poor outcome group or a good outcome group. Nevertheless the concordance in classification at the sample level is low, with only 50% of the breast cancer samples classified in the same outcome group by all classifiers. The predictive accuracy decreases with the number of poor outcome assignments given to a sample. The best classification performance was obtained for the group of patients with only good outcome assignments. Enrichment analysis of the enlarged signatures revealed 11 functional modules with prognostic ability. The combination of the RNA-splicing and immune modules resulted in a classifier with high prognostic performance on an independent validation set.The study revealed that the nine signatures perform similarly but exhibit a large degree of discordance in prognostic group assignment. Functional analyses indicate that proliferation is a common cellular process, but that other functional categories are also enriched and show independent prognostic ability. We provide new evidence of the potentially promising prognostic impact of immunity and RNA-splicing processes in breast cancer.Breast cancer is composed of distinct diseases with different outcomes. Clinical and pathological factors are currently employed to determine the prognosis of patients. The Saint-Gallen guidelines [1], National Institute of Health guidelines [2] and Nottingham Prognostic Index guidelines [3] as well as the AdjuvantOnline!
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