Lodewyk F A Wessels

Netherlands Cancer Institute, Amsterdamo, North Holland, Netherlands

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Publications (174)1416.11 Total impact

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    ABSTRACT: Breast cancers with BRCA1 germline mutation have a characteristic DNA copy number (CN) pattern. We developed a test that assigns CN profiles to be 'BRCA1-like' or 'non-BRCA1-like', which refers to resembling a BRCA1-mutated tumor or resembling a tumor without a BRCA1 mutation, respectively. Approximately one third of the BRCA1-like breast cancers have a BRCA1 mutation, one third has hypermethylation of the BRCA1 promoter and one third has an unknown reason for being BRCA1-like. This classification is indicative of patients' response to high dose alkylating and platinum containing chemotherapy regimens, which targets the inability of BRCA1 deficient cells to repair DNA double strand breaks. We investigated whether this classification can be reliably obtained with next generation sequencing and copy number platforms other than the bacterial artificial chromosome (BAC) array Comparative Genomic Hybridization (aCGH) on which it was originally developed. We investigated samples from 230 breast cancer patients for which a CN profile had been generated on two to five platforms, comprising low coverage CN sequencing, CN extraction from targeted sequencing panels (CopywriteR), Affymetrix SNP6.0, 135K/720K oligonucleotide aCGH, Affymetrix Oncoscan FFPE (MIP) technology, 3K BAC and 32K BAC aCGH. Pairwise comparison of genomic position-mapped profiles from the original aCGH platform and other platforms revealed concordance. For most cases, biological differences between samples exceeded the differences between platforms within one sample. We observed the same classification across different platforms in over 80% of the patients and kappa values of at least 0.36. Differential classification could be attributed to CN profiles that were not strongly associated to one class. In conclusion, we have shown that the genomic regions that define our BRCA1-like classifier are robustly measured by different CN profiling technologies, providing the possibility to retro- and prospectively investigate BRCA1-like classification across a wide range of CN platforms. Copyright © 2015. Published by Elsevier B.V.
    Molecular oncology 03/2015; DOI:10.1016/j.molonc.2015.03.002 · 5.94 Impact Factor
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    ABSTRACT: Retroviruses and DNA transposons are an important part of molecular biologists' toolbox. The applications of these elements range from functional genomics to oncogene discovery and gene therapy. However, these elements do not integrate uniformly across the genome, which is an important limitation to their use. A number of genetic and epigenetic factors have been shown to shape the integration preference of these elements. Insight into integration bias can significantly enhance the analysis and interpretation of results obtained using these elements. For three different applications, we outline how bias can affect results, and can potentially be addressed.
    03/2015; DOI:10.4161/2159256X.2014.992694
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    ABSTRACT: Pan- or multi-drug resistance is a central problem in clinical oncology. Here we use a genetically engineered mouse model of BRCA2-associated hereditary breast cancer to study drug resistance to several types of chemotherapy and PARP inhibition. We found that multi-drug resistance was strongly associated with an EMT-like sarcomatoid phenotype and high expression of the Abcb1b gene, which encodes the drug efflux transporter P-glycoprotein. Inhibition of P-glycoprotein could partly re-sensitize sarcomatoid tumors to the PARP inhibitor olaparib, docetaxel and doxorubicin. We propose that multi-drug resistance is a multi-factorial process and that mouse models are useful to unravel this. Copyright © 2014, American Association for Cancer Research.
    Cancer Research 12/2014; 75(4). DOI:10.1158/0008-5472.CAN-14-0839 · 9.28 Impact Factor
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    ABSTRACT: Here we describe a conditional piggyBac transposition system in mice and report the discovery of large sets of new cancer genes through a pancreatic insertional mutagenesis screen. We identify Foxp1 as an oncogenic transcription factor that drives pancreatic cancer invasion and spread in a mouse model and correlates with lymph node metastasis in human patients with pancreatic cancer. The propensity of piggyBac for open chromatin also enabled genome-wide screening for cancer-relevant noncoding DNA, which pinpointed a Cdkn2a cis-regulatory region. Histologically, we observed different tumor subentities and discovered associated genetic events, including Fign insertions in hepatoid pancreatic cancer. Our studies demonstrate the power of genetic screening to discover cancer drivers that are difficult to identify by other approaches to cancer genome analysis, such as downstream targets of commonly mutated human cancer genes. These piggyBac resources are universally applicable in any tissue context and provide unique experimental access to the genetic complexity of cancer.
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    ABSTRACT: To identify factors preferentially necessary for driving tumor expansion, we performed parallel in vitro and in vivo negative-selection short hairpin RNA (shRNA) screens. Melanoma cells harboring shRNAs targeting several DNA damage response (DDR) kinases had a greater selective disadvantage in vivo than in vitro, indicating an essential contribution of these factors during tumor expansion. In growing tumors, DDR kinases were activated following hypoxia. Correspondingly, depletion or pharmacologic inhibition of DDR kinases was toxic to melanoma cells, including those that were resistant to BRAF inhibitor, and this could be enhanced by angiogenesis blockade. These results reveal that hypoxia sensitizes melanomas to targeted inhibition of the DDR and illustrate the utility of in vivo shRNA dropout screens for the identification of pharmacologically tractable targets.
    Cell Reports 11/2014; 9(4):1375. DOI:10.1016/j.celrep.2014.10.024 · 7.21 Impact Factor
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    ABSTRACT: Cell migration is crucial in development, tissue repair and immunity and frequently aberrant in pathological processes including tumor metastasis. Focal adhesions (FAs) are integrin-based adhesion complexes that form the link between the cytoskeleton and the extracellular matrix and are thought to orchestrate cell migration. Understanding the regulation of FAs by (oncogenic) signaling pathways may identify strategies to target pathological cell migration. Here we describe the development of a robust FA tracker that enables the automatic, multi-parametric analysis of FA dynamics, morphology and composition from time-lapse image series generated by total internal reflection fluorescence (TIRF) microscopy. In control prostate carcinoma cells, this software recapitulates previous findings that relate morphological characteristics of FAs to their lifetime and their cellular location. We then investigated how FAs are altered when cell migration is induced by the metastasis-promoting hormone HGF and subsequently inhibited by activation of the small GTPase Rap1. We performed a detailed analysis of individual FA parameters, which identified FA size, sliding and intensity as primary targets of Rap1. HGF did not have strong effects on any of the FA parameters within the first hours of its addition. Subsequent Bayesian network inference (BNI), using all measured parameters as input, revealed little correlation between changes in cell migration and FA characteristics in this prostate carcinoma cell line. Instead BNI indicated a concerted coordination of cell size and FA parameters. Thus our results did not reveal a direct relation between the regulation of cell migration and the regulation of FA dynamics. Copyright © 2014 Elsevier Inc. All rights reserved.
    Experimental Cell Research 10/2014; DOI:10.1016/j.yexcr.2014.10.012 · 3.37 Impact Factor
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    ABSTRACT: RIP140 is a transcriptional coregulator involved in energy homeostasis, ovulation and mammary gland development. Although conclusive evidence is lacking, reports have implicated a role for RIP140 in breast cancer. Here, we explored the mechanistic role of RIP140 in breast cancer and its involvement in Estrogen Receptor alpha (ERα) transcriptional regulation of gene expression. Using ChIP-seq analysis, we demonstrate that RIP140 shares over 80% of its binding sites with ERα, colocalizing with its interaction partners FOXA1, GATA3, p300, CBP and p160 family members at H3K4me1-demarcated enhancer regions. RIP140 is required for ERα-complex formation, ERα-mediated gene expression and ERα-dependent breast cancer cell proliferation. Genes affected following RIP140 silencing could be used stratify tamoxifen-treated breast cancer cohorts, based on clinical outcome. Importantly, this gene signature was only effective in endocrine treated conditions. Cumulatively, our data suggests that RIP140 plays an important role in ERα-mediated transcriptional regulation in breast cancer and response to tamoxifen treatment.
    Cancer Research 08/2014; 74(19). DOI:10.1158/0008-5472.CAN-13-3429 · 9.28 Impact Factor
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    ABSTRACT: Recent observations connected DNA cytosine deaminase APOBEC3B to the genetic evolution of breast cancer. We addressed whether APOBEC3B is associated with breast cancer clinical outcomes. APOBEC3B messenger RNA (mRNA) levels were related in 1,491 primary breast cancers to disease-free (DFS), metastasis-free (MFS), and overall survival (OS). For independent validation, APOBEC3B mRNA expression was associated with patient outcome data in five additional cohorts (over 3,500 breast cancer cases). In univariate Cox regression analysis, increasing APOBEC3B expression as a continuous variable was associated with worse DFS, MFS, and OS (hazard ratio [HR] = 1.20, 1.21, and 1.24, respectively; all P < .001). Also, in untreated ER-positive (ER+), but not in ER-, lymph-node-negative patients, high APOBEC3B levels were associated with a poor DFS (continuous variable: HR = 1.29, P = .001; dichotomized at the median level, HR = 1.66, P = .0002). This implies that APOBEC3B is a marker of pure prognosis in ER + disease. These findings were confirmed in the analyses of five independent patient sets. In these analyses, APOBEC3B expression dichotomized at the median level was associated with adverse outcomes (METABRIC discovery and validation, 788 and 706 ER + cases, disease-specific survival (DSS), HR = 1.77 and HR = 1.77, respectively, both P < .001; Affymetrix dataset, 754 ER + cases, DFS, HR = 1.57, P = 2.46E-04; NKI295, 181 ER + cases, DFS, HR = 1.72, P = .054; and BIG 1-98, 1,219 ER + cases, breast-cancer-free interval (BCFI), HR = 1.42, P = 0.0079). APOBEC3B is a marker of pure prognosis and poor outcomes for ER + breast cancer, which strongly suggests that genetic aberrations induced by APOBEC3B contribute to breast cancer progression.
    08/2014; 8(6). DOI:10.1007/s12672-014-0196-8
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    ABSTRACT: Lymph-node metastasis (LNM) predict high recurrence rates in breast cancer patients. Systemic treatment aims to eliminate (micro)metastatic cells. However decisions regarding systemic treatment depend largely on clinical and molecular characteristics of primary tumours. It remains, however, unclear to what extent metastases resemble the cognate primary breast tumours, especially on a genomic level, and as such will be eradicated by the systemic therapy chosen. In this study we used high-resolution aCGH to investigate DNA copy number differences between primary breast cancers and their paired LNMs. To date, no recurrent LNM-specific genomic aberrations have been identified using array comparative genomic hybridization (aCGH) analysis. In our study we employ a high-resolution platform and we stratify on different breast cancer subtypes, both aspects that might have underpowered previously performed studies.To test the possibility that genomic instability in triple-negative breast cancers (TNBCs) might cause increased random and potentially also recurrent copy number aberrations (CNAs) in their LNMs, we studied 10 primary TNBC-LNM pairs and 10 ER-positive (ER+) pairs and verified our findings adding additionally 5 TNBC-LNM and 22 ER+-LNM pairs. We found that all LNMs clustered nearest to their matched tumour except for two cases, of which one was due to the presence of two distinct histological components in one tumour. We found no significantly altered CNAs between tumour and their LNMs in the entire group or in the subgroups. Within the TNBC subgroup, no absolute increase in CNAs was found in the LNMs compared to their primary tumours, suggesting that increased genomic instability does not lead to more CNAs in LNMs. Our findings suggest a high clonal relationship between primary breast tumours and its LNMs, at least prior to treatment, and support the use of primary tumour characteristics to guide adjuvant systemic chemotherapy in breast cancer patients.
    PLoS ONE 08/2014; 9(8):e103177. DOI:10.1371/journal.pone.0103177 · 3.53 Impact Factor
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    ABSTRACT: Tamoxifen is one of the most widely used endocrine agents for the treatment of estrogen receptor α (ERα)-positive breast cancer. Although effective in most patients, resistance to tamoxifen is a clinically significant problem and the mechanisms responsible remain elusive. To address this problem, we performed a large scale loss-of-function genetic screen in ZR-75-1 luminal breast cancer cells to identify candidate resistance genes. In this manner, we found that loss of function in the deubiquitinase USP9X prevented proliferation arrest by tamoxifen, but not by the ER downregulator fulvestrant. RNAi-mediated attenuation of USP9X was sufficient to stabilize ERα on chromatin in the presence of tamoxifen, causing a global tamoxifen-driven activation of ERα-responsive genes. Using a gene signature defined by their differential expression after USP9X attenuation in the presence of tamoxifen, we were able to define patients with ERα-positive breast cancer experiencing a poor outcome after adjuvant treatment with tamoxifen. The signature was specific in its lack of correlation with survival in patients with breast cancer who did not receive endocrine therapy. Overall, our findings identify a gene signature as a candidate biomarker of response to tamoxifen in breast cancer. Cancer Res; 74(14); 3810-20. ©2014 AACR.
    Cancer Research 07/2014; 74(14):3810-20. DOI:10.1158/0008-5472.CAN-13-1960 · 9.28 Impact Factor
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    ABSTRACT: The influence of local chromatin context on gene expression can be explored by integrating a transcription reporter at different locations in the genome as a sensor. Here we provide a detailed protocol for analyzing thousands of reporters integrated in parallel (TRIP) at a genome-wide level. TRIP is based on tagging each reporter with a unique barcode, which is used for independent reporter expression analysis and integration site mapping. Compared with previous methods for studying position effects, TRIP offers a 100-1,000-fold higher throughput in a faster and less-labor-intensive manner. The entire experimental protocol takes ∼42 d to complete, with high-throughput sequencing and data analysis requiring an additional ∼11 d. TRIP was developed by using transcription reporters in mouse embryonic stem (mES) cells, but because of its flexibility the method can be used to probe the influence of chromatin context on a variety of molecular processes in any transfectable cell line.
    Nature Protocol 06/2014; 9(6):1255-81. DOI:10.1038/nprot.2014.072 · 8.36 Impact Factor
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    ABSTRACT: Genomic information is encoded on a wide range of distance scales, ranging from tens of bases to megabases. We developed a multiscale framework to analyze and visualize the information content of genomic signals. Different types of signals, such as G+C content or DNA methylation, are characterized by distinct patterns of signal enrichment or depletion across scales spanning several orders of magnitude. These patterns are associated with a variety of genomic annotations. By integrating the information across all scales, we demonstrated improved prediction of gene expression from polymerase II chromatin immunoprecipitation sequencing (ChIP-seq) measurements, and we observed that gene expression differences in colorectal cancer are related to methylation patterns that extend beyond the single-gene scale. Our software is available at https://github.com/tknijnen/msr/.
    Nature Methods 04/2014; 11(6). DOI:10.1038/nmeth.2924 · 25.95 Impact Factor
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    ABSTRACT: There are no effective therapies for the ∼30% of human malignancies with mutant RAS oncogenes. Using a kinome-centered synthetic lethality screen, we find that suppression of the ERBB3 receptor tyrosine kinase sensitizes KRAS mutant lung and colon cancer cells to MEK inhibitors. We show that MEK inhibition results in MYC-dependent transcriptional upregulation of ERBB3, which is responsible for intrinsic drug resistance. Drugs targeting both EGFR and ERBB2, each capable of forming heterodimers with ERBB3, can reverse unresponsiveness to MEK inhibition by decreasing inhibitory phosphorylation of the proapoptotic proteins BAD and BIM. Moreover, ERBB3 protein level is a biomarker of response to combinatorial treatment. These data suggest a combination strategy for treating KRAS mutant colon and lung cancers and a way to identify the tumors that are most likely to benefit from such combinatorial treatment.
    Cell Reports 04/2014; 7(1):86-93. DOI:10.1016/j.celrep.2014.02.045 · 7.21 Impact Factor
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    ABSTRACT: Treatment of BRAF(V600E) mutant melanoma by small molecule drugs that target the BRAF or MEK kinases can be effective, but resistance develops invariably1, 2. In contrast, colon cancers that harbour the same BRAF(V600E) mutation are intrinsically resistant to BRAF inhibitors, due to feedback activation of the epidermal growth factor receptor (EGFR)3, 4. Here we show that 6 out of 16 melanoma tumours analysed acquired EGFR expression after the development of resistance to BRAF or MEK inhibitors. Using a chromatin-regulator-focused short hairpin RNA (shRNA) library, we find that suppression of sex determining region Y-box 10 (SOX10) in melanoma causes activation of TGF-β signalling, thus leading to upregulation of EGFR and platelet-derived growth factor receptor-β (PDGFRB), which confer resistance to BRAF and MEK inhibitors. Expression of EGFR in melanoma or treatment with TGF-β results in a slow-growth phenotype with cells displaying hallmarks of oncogene-induced senescence. However, EGFR expression or exposure to TGF-β becomes beneficial for proliferation in the presence of BRAF or MEK inhibitors. In a heterogeneous population of melanoma cells having varying levels of SOX10 suppression, cells with low SOX10 and consequently high EGFR expression are rapidly enriched in the presence of drug, but this is reversed when the drug treatment is discontinued. We find evidence for SOX10 loss and/or activation of TGF-β signalling in 4 of the 6 EGFR-positive drug-resistant melanoma patient samples. Our findings provide a rationale for why some BRAF or MEK inhibitor-resistant melanoma patients may regain sensitivity to these drugs after a ‘drug holiday’ and identify patients with EGFR-positive melanoma as a group that may benefit from re-treatment after a drug holiday.
    Nature 04/2014; 508(7494):118-22. DOI:10.1038/nature13121 · 42.35 Impact Factor
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    ABSTRACT: Retroviral insertional mutagenesis is a powerful tool for identifying putative cancer genes in mice. To uncover the regulatory mechanisms by which common insertion loci affect downstream processes, we supplemented genotyping data with genome-wide mRNA expression profiling data for 97 tumors induced by retroviral insertional mutagenesis. We developed locus expression signature analysis, an algorithm to construct and interpret the differential gene expression signature associated with each common insertion locus. Comparing locus expression signatures to promoter affinity profiles allowed us to build a detailed map of transcription factors whose protein-level regulatory activity is modulated by a particular locus. We also predicted a large set of drugs that might mitigate the effect of the insertion on tumorigenesis. Taken together, our results demonstrate the potential of a locus-specific signature approach for identifying mammalian regulatory mechanisms in a cancer context.
    Proceedings of the National Academy of Sciences 04/2014; DOI:10.1073/pnas.1309293111 · 9.81 Impact Factor
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    ABSTRACT: The ability of retroviruses and transposons to insert their genetic material into host DNA makes them widely used tools in molecular biology, cancer research and gene therapy. However, these systems have biases that may strongly affect research outcomes. To address this issue, we generated very large datasets consisting of [Formula: see text] to [Formula: see text] unselected integrations in the mouse genome for the Sleeping Beauty (SB) and piggyBac (PB) transposons, and the Mouse Mammary Tumor Virus (MMTV). We analyzed [Formula: see text] (epi)genomic features to generate bias maps at both local and genome-wide scales. MMTV showed a remarkably uniform distribution of integrations across the genome. More distinct preferences were observed for the two transposons, with PB showing remarkable resemblance to bias profiles of the Murine Leukemia Virus. Furthermore, we present a model where target site selection is directed at multiple scales. At a large scale, target site selection is similar across systems, and defined by domain-oriented features, namely expression of proximal genes, proximity to CpG islands and to genic features, chromatin compaction and replication timing. Notable differences between the systems are mainly observed at smaller scales, and are directed by a diverse range of features. To study the effect of these biases on integration sites occupied under selective pressure, we turned to insertional mutagenesis (IM) screens. In IM screens, putative cancer genes are identified by finding frequently targeted genomic regions, or Common Integration Sites (CISs). Within three recently completed IM screens, we identified 7%-33% putative false positive CISs, which are likely not the result of the oncogenic selection process. Moreover, results indicate that PB, compared to SB, is more suited to tag oncogenes.
    PLoS Genetics 04/2014; 10(4):e1004250. DOI:10.1371/journal.pgen.1004250 · 8.17 Impact Factor

Publication Stats

7k Citations
1,416.11 Total Impact Points

Institutions

  • 2004–2014
    • Netherlands Cancer Institute
      • • Division of Molecular Biology
      • • Division of Experimental Therapy
      • • Division of Diagnostic Oncology
      Amsterdamo, North Holland, Netherlands
  • 1999–2014
    • Delft University of Technology
      • • Faculty of Electrical Engineering, Mathematics and Computer Sciences (EEMCS)
      • • Department of Biotechnology
      Delft, South Holland, Netherlands
  • 2010
    • Netherlands Bioinformatics Centre
      Nymegen, Gelderland, Netherlands
  • 2008
    • Centro de Investigación del Cáncer
      Helmantica, Castille and León, Spain