Pamela Rabbitts

University of Leeds, Leeds, England, United Kingdom

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Publications (111)673.6 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: The study of the relationships between pre-cancer and cancer and identification of early driver mutations is becoming increasingly important as the value of molecular markers of early disease and personalised drug targets is recognised, especially now the extent of clonal heterogeneity in fully invasive disease is being realised. It has been assumed that pre-cancerous lesions exhibit a fairly passive progression to invasive disease; the degree to which they too are heterogeneous is unknown. We performed ultra-deep sequencing of thousands of selected mutations together with copy number analysis from multiple, matched pre-invasive lesions, primary tumours and metastases from five patients with oral cancer, some with multiple primary tumours presenting either synchronously or metachronously, totalling 75 samples. This allowed the clonal relationships between the samples to be observed for each patient. We expose for the first time the unexpected variety and complexity of the relationships between this group of oral dysplasias and their associated carcinomas, and ultimately, the diversity of processes by which tumours are initiated, spread and metastasise. Instead of a series of genomic precursors of their adjacent invasive disease, we have shown dysplasia to be a distinct dynamic entity, refuting the belief that pre-cancer and invasive tumours with a close spatial relationship always have linearly-related genomes. We show that oral pre-cancer exhibits considerable sub-clonal heterogeneity in its own right, that mutational changes in pre-cancer do not predict the onset of invasion, and that the genomic pathway to invasion is neither unified nor predictable. This article is protected by copyright. All rights reserved.
    The Journal of Pathology 06/2015; DOI:10.1002/path.4576 · 7.33 Impact Factor
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    ABSTRACT: Verrucous carcinoma of the oral cavity (OVC) is considered a subtype of classical oral squamous cell carcinoma (OSCC). Diagnosis is problematic, and additional biomarkers are needed to better stratify patients. To investigate their molecular signature, we performed low coverage copy number sequencing on 57 OVC and exome and RNA sequencing on a subset of these and compared the data to the same OSCC parameters. Copy number results showed that OVC lacked any of the classical OSCC patterns such as gain of 3q and loss of 3p and demonstrated considerably fewer genomic rearrangements compared to the OSCC cohort. OVC and OSCC samples could be clearly differentiated. Exome sequencing showed that OVC samples lacked mutations in genes commonly associated with OSCC (TP53, NOTCH1, NOTCH2, CDKN2A and FAT1). RNA sequencing identified genes that were differentially expressed between the groups. In silico functional analysis showed that the mutated and differentially expressed genes in OVC samples were involved in cell adhesion and keratinocyte proliferation, while those in the OSCC cohort were enriched for cell death and apoptosis pathways. This is the largest and most detailed genomic and transcriptomic analysis yet performed on this tumour type, which, as an example of non-metastatic cancer, may shed light on the nature of metastases. These three independent investigations consistently show substantial differences between the cohorts. Taken together they lead to the conclusion that OVC is not a subtype of OSCC, but should be classified as a distinct entity. This article is protected by copyright. All rights reserved. © 2014 Wiley Periodicals, Inc. © 2015 UICC.
    International Journal of Cancer 05/2015; DOI:10.1002/ijc.29615 · 5.01 Impact Factor
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    ABSTRACT: The role of personalised medicine and target treatment in the clinical management of cancer patients has become increasingly important in recent years. This has made the task of precise histological substratification of cancers crucial. Increasingly genomic data are being seen as a valuable classifier. Specifically, copy number alteration (CNA) profiles generated by next-generation sequencing (NGS) can become a determinant for tumours subtyping. The principle purpose of this study is to devise a model with good prediction capability for the tumours histological subtypes as a function of both the patients covariates and their genome-wide CNA profiles from NGS data. We investigate a logistic regression for modelling tumour histological subtypes as a function of the patients' covariates and their CNA profiles, in a mixed model framework. The covariates, such as age and gender, are considered as fixed predictors and the genome- wide CNA profiles are considered as random predictors. We illustrate the application of this model in lung and oral cancer datasets, and the results indicate that the tumour histological subtypes can be modelled with a good fit. Our cross-validation indicates that the logistic regression exhibits the best prediction relative to other classification methods we considered in this study. The model also exhibits the best agreement in the prediction between smooth-segmented and circular binary-segmented CNA profiles. An R package to run a logistic regression is available in http://www1.maths.leeds.ac.uk/~arief/R/CNALR/ CONTACT: a.gusnanto@leeds.ac.uk. © The Author (2015). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
    Bioinformatics 04/2015; DOI:10.1093/bioinformatics/btv191 · 4.62 Impact Factor
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    ABSTRACT: Progress in sequencing technology is intrinsically linked to progress in understand cancer genomics. This review aims to discuss the development from Sanger sequencing to next generation sequencing (NGS) technology. We highlight the technical considerations for understanding reports using NGS. We discuss the findings of studies in head and neck cancer using NGS as well as the Cancer Genome Atlas. Finally we discuss future routes for research utilising this methodology and the potential impact of this. This article is protected by copyright. All rights reserved. © 2015 Wiley Periodicals, Inc.
    Head & Neck 04/2015; DOI:10.1002/hed.24085 · 3.01 Impact Factor
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    ABSTRACT: The catalogue of tumour-specific somatic mutations (SMs) is growing rapidly owing to the advent of next-generation sequencing. Identifying those mutations responsible for the development and progression of the disease, so-called driver mutations, will increase our understanding of carcinogenesis and provide candidates for targeted therapeutics. The phenotypic consequence(s) of driver mutations cause them to be selected for within the tumour environment, such that many approaches aimed at distinguishing drivers are based on finding significantly somatically mutated genes. Currently, these methods are designed to analyse, or be specifically applied to, nonsynonymous mutations: those that alter an encoded protein. However, growing evidence suggests the involvement of noncoding transcripts in carcinogenesis, mutations in which may also be disease-driving. We wished to test the hypothesis that common DNA variation rates within humans can be used as a baseline from which to score the rate of SMs, irrespective of coding capacity. We preliminarily tested this by applying it to a dataset of 159,498 SMs and using the results to rank genes. This resulted in significant enrichment of known cancer genes, indicating that the approach has merit. As additional data from cancer sequencing studies are made publicly available, this approach can be refined and applied to specific cancer subtypes. We named this preliminary version of our approach PRISMAD (polymorphism rates indicate somatic mutations as drivers) and have made it publicly accessible, with scripts, via a link at www.precancer.leeds.ac.uk/software-and-datasets. What's New? Somatic mutations are important drivers of the cancerous process but identifying the key “driver” mutations remains a challenging question. The authors hypothesize that the variation level in healthy tissue represents a transcript's tolerance to mutation and that if the number of mutations in tumors exceeds this level, positive selection might have occurred that point to this transcript as a major driver in carcinogenesis. They tested their program with a large dataset of somatic mutations and obtained a ranked list of genes significantly enriched in known cancer-associated genes. Their program called PRISMAD is publicly available and could help identify new driver mutations in various tumors.
    International Journal of Cancer 01/2015; 136(1). DOI:10.1002/ijc.28951 · 5.01 Impact Factor
  • Neeraj Sethi, Henry Wood, Pamela Rabbitts
    Oral Oncology 11/2014; 50(11). DOI:10.1016/j.oraloncology.2014.07.014 · 3.03 Impact Factor
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    ABSTRACT: MicroRNAs are a class of non-coding RNA which regulate gene expression. Their discovery in humans in 2000 has led to an explosion in research in this area in terms of their role as a biomarker, therapeutic target as well as trying to elucidate their function. This review aims to summarise the function of microRNAs as well as to examine how dysregulation at any step in their biogenesis or functional pathway can play a role in the development of cancer. We review which microRNAs are implicated as oncogenic or tumour suppressor in head and neck cancer as well as the data available on the use of microRNAs as diagnostic and prognostic marker. We also discuss routes for future research.
    European Journal of Cancer 10/2014; 50(15). DOI:10.1016/j.ejca.2014.07.012 · 4.82 Impact Factor
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    ABSTRACT: Objective. The etiology of oral verrucous carcinoma is unknown, and human papillomavirus 'involvement' remains contentious. The uncertainty can be attributed to varied detection procedures and difficulties in defining 'gold-standard' histologic criteria for diagnosing 'verrucous' lesions. Their paucity also hampers investigation. We aimed to analyze oral verrucous lesions for human papillomavirus (HPV) subtype genomes. Study Design. We used next-generation sequencing for the detection of papillomavirus sequences, identifying subtypes and computing viral loads. We identified a total of 78 oral verrucous cases (62 carcinomas and 16 hyperplasias). DNA was extracted from all and sequenced at a coverage between 2.5% and 13%. Results. An HPV-16 sequence was detected in 1 carcinoma and 1 hyperplasia, and an HPV-2 sequence was detected in 1 carcinoma out of the 78 cases, with viral loads of 2.24, 8.16, and 0.33 viral genomes per cell, respectively. Conclusions. Our results indicate no conclusive human papillomavirus involvement in oral verrucous carcinoma or hyperplasia.
    Oral Surgery, Oral Medicine, Oral Pathology, Oral Radiology, and Endodontology 07/2014; 118(1):117-125.e1. DOI:10.1016/j.oooo.2014.03.018 · 1.46 Impact Factor
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    ABSTRACT: Purpose The aetiology of oral verrucous carcinoma is unknown whilst human papillomavirus ‘involvement’ remains contentious. Dubiety can be attributed to varied detection procedures and difficulties in defining ‘gold-standard’ histological criteria for diagnosing ‘verrucous’ lesions. Their paucity also hampers investigation. Design We aimed to analyse oral verrucous lesions for HPV subtype genomes using ‘next generation sequencing’ for the detection of papilloma virus sequences, identifying subtypes and computing viral loads. We identified a total of 78 oral verrucous cases [62 carcinomas and 16 hyperplasias]. DNA was extracted from all and sequenced at a coverage between 2.5 and 13%. Findings An HPV-16 sequence was detected in one carcinoma and one hyperplasia, and an HPV-2 sequence was detected in one carcinoma out of the 78 cases, with viral loads of 2.24, 8.16 and 0.33 viral genomes per cell respectively. Practical implications Our results indicate no conclusive human papilloma virus involvement in oral verrucous carcinoma or hyperplasia.
    Oral Surgery, Oral Medicine, Oral Pathology, Oral Radiology, and Endodontology 04/2014; · 1.46 Impact Factor
  • Cancer Research 03/2014; 73(24 Supplement):PD3-3-PD3-3. DOI:10.1158/0008-5472.SABCS13-PD3-3 · 9.28 Impact Factor
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    ABSTRACT: Current high throughput sequencing has greatly transformed genome sequence analysis. In the context of very low- coverage sequencing (<0.1X), performing 'binning' or 'windowing' on mapped short sequences ('reads') is critical to extract genomic information of interest for further evaluation, such as copy number alterations analysis. If the window size is too small, many windows will exhibit zero counts and almost no pattern can be observed. In contrast, if the window size is too wide, the patterns or genomic features will be 'smoothed out'. Our objective is to identify an optimal window size in between the two extremes. We assume the reads density to be a step function. Given this model, we propose a data-based estimation of optimal window size based on Akaike's information criterion (AIC) and cross-validation (CV) log-likelihood. By plotting the AIC and CV log likelihood curve as a function of window size, we are able to estimate the optimal window size that minimises AIC or maximise CV log-likelihood. The proposed methods are of general purpose and we illustrate their application using low-coverage next-generation sequence datasets from real tumour samples and simulated datasets. An R package to estimate optimal window size is available in http://www1.maths.leeds.ac.uk/~arief/R/win/ CONTACT: a.gusnanto@leeds.ac.uk.
    Bioinformatics 03/2014; 30(13). DOI:10.1093/bioinformatics/btu123 · 4.62 Impact Factor
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    Journal of Investigative Dermatology 01/2014; 134(7). DOI:10.1038/jid.2014.52 · 6.37 Impact Factor
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    ABSTRACT: Human papilloma virus is a risk factor for oropharyngeal cancer. Evidence for a similar aetiological role in the development of oral dysplasia or its transformation to oral cancer is not as clear. Meta-analyses estimate the prevalence of high-risk human papilloma virus (HPV) serotypes to be three times higher in pre-malignant lesions and cancer than in normal oral mucosa. However, this does not imply a causal relationship. Conflicting results are reported from the few studies examining the prognostic significance of HPV positivity in the development of oral cancer. We aimed to examine the ability of p16(INK) (4a) protein expression, a surrogate marker of HPV infection, to predict malignant progression in a large cohort of oral dysplasia patients. One hundred forty eight oral dysplasia cases underwent immunohistochemical analysis using a monoclonal antibody against p16(INK) (4a) . Clinical factors were also collated on each case. Slides were double scored independently by two trained observers. Univariate analyses using both logistic and Cox regression models were performed. Thirty nine of 148 cases progressed to cancer. Ten of 148 cases (7%) were p16(INK) (4a) positive. High grade of dysplasia (P = 0.0002) and lesion morphology (P = 0.03) were found to be prognostic of malignant progression. p16(INK) (4a) score was not prognostic in this cohort (P = 0.29). This did not change with a time to event analysis (P = 0.24). Few studies have assessed the aetiological role of HPV in cancer development from dysplastic lesions. Our study, using one of the largest cohorts of oral dysplasia, demonstrated a low rate of p16(INK) (4a) positivity and was unable to confirm a prognostic ability for this biomarker.
    Journal of Oral Pathology and Medicine 12/2013; DOI:10.1111/jop.12128 · 1.87 Impact Factor
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    ABSTRACT: Squamous cell carcinoma (SCC) of the lung kills over 350,000 people annually worldwide, and is the main lung cancer histotype with no targeted treatments. High-coverage whole-genome sequencing of the other main subtypes, small-cell and adenocarcinoma, gave insights into carcinogenic mechanisms and disease etiology. The genomic complexity within the lung SCC subtype, as revealed by The Cancer Genome Atlas, means this subtype is likely to benefit from a more integrated approach in which the transcriptional consequences of somatic mutations are simultaneously inspected. Here we present such an approach: the integrated analysis of deep sequencing data from both the whole genome and whole transcriptome (coding and non-coding) of LUDLU-1, a SCC lung cell line. Our results show that LUDLU-1 lacks the mutational signature that has been previously associated with tobacco exposure in other lung cancer subtypes, and suggests that DNA-repair efficiency is adversely affected; LUDLU-1 contains somatic mutations in TP53 and BRCA2, allelic imbalance in the expression of two cancer-associated BRCA1 germline polymorphisms and reduced transcription of a potentially endogenous PARP2 inhibitor. Functional assays were performed and compared with a control lung cancer cell line. LUDLU-1 did not exhibit radiosensitisation or an increase in sensitivity to PARP inhibitors. However, LUDLU-1 did exhibit small but significant differences with respect to cisplatin sensitivity. Our research shows how integrated analyses of high-throughput data can generate hypotheses to be tested in the lab.
    PLoS ONE 11/2013; 8(11):e78823. DOI:10.1371/journal.pone.0078823 · 3.53 Impact Factor
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    ABSTRACT: Background:Prognostic biomarkers aim to improve on the current inadequate method of histological assessment to identify patients with oral epithelial dysplasia at greatest risk of malignant transformation. We aimed to assess the prognostic ability of six protein biomarkers linked to the epidermal growth factor receptor (EGFR) pathway, including three tetraspanins, in a large multicentre oral dysplasia cohort.Methods:One hundred and forty-eight cases with varying degrees of epithelial dysplasia underwent immunohistochemical assessment for CD9, CD151, CD82, EGFR, Her-2, and COX-2. Scoring was performed independently by two observers. Univariate analyses using both logistic and Cox regression models and a multivariate regression were performed.Results:Malignant progression was significantly greater in those cases with decreased expression of CD9 (P=0.02), and increased expression of CD151 (P=0.02), EGFR (P=0.04), and COX-2 (P=0.003). Histological grade (P=0.0002) and morphology (P=0.03) were also prognostic, whereas smoking and alcohol were not. The optimal combination by backward-variable selection was of histological grade (hazard ratio (HR) 1.64; 95% CI 1.12, 2.40), COX-2 overexpression (HR 1.12; 1.02, 1.24) and CD9 underexpression (HR 0.88; 0.80, 0.97). CD82 and Her-2 demonstrated no prognostic ability.Conclusion:This is the first study of the expression and prognostic potential of the tetraspanins in oral dysplasia. A combination of certain biomarkers with clinical factors appeared to improve the accuracy of determining the risk of malignancy in individuals with oral dysplasia. These findings may also offer potential new therapeutic approaches for this condition.British Journal of Cancer advance online publication, 7 November 2013; doi:10.1038/bjc.2013.600 www.bjcancer.com.
    British Journal of Cancer 11/2013; 109(11). DOI:10.1038/bjc.2013.600 · 4.82 Impact Factor
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    ABSTRACT: Current methods for resolving genetically distinct subclones in tumour samples require somatic mutations to be clustered by allelic frequencies, which are determined by applying a variant calling program to next-generation sequencing data. Such programs were developed to accurately distinguish true polymorphisms and somatic mutations from the artifactual non-reference alleles introduced during library preparation and sequencing. However, numerous variant callers exist with no clear indication of the best-performer for subclonal analysis, in which the accuracy of the assigned variant frequency is as important as correctly indicating whether the variant is present or not. Furthermore, sequencing depth (the number of times that a genomic position is sequenced) affects the ability to detect low-allelic fraction variants and accurately assign their allele frequencies. We created two synthetic sequencing datasets, and sequenced real KRAS amplicons, with variants spiked in at specific ratios, in order to assess which caller performs best in terms of both variant detection and assignment of allelic frequencies. We also assessed the sequencing depths required to detect low-allelic fraction variants. We found that VarScan2 performed best overall with sequencing depths of 100x, 250x, 500x and 1000x required to accurately identify variants present at 10%, 5%, 2.5% and 1% respectively. This article is protected by copyright. All rights reserved.
    Human Mutation 10/2013; 34(10). DOI:10.1002/humu.22365 · 5.05 Impact Factor
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    ABSTRACT: Metagenomics, the study of microbial genomes within diverse environments, is a rapidly developing field. The identification of microbial sequences within a host organism enables the study of human intestinal, respiratory, and skin microbiota, and has allowed the identification of novel viruses in diseases such as Merkel cell carcinoma. There are few publicly available tools for metagenomic high throughput sequence analysis. We present Integrated Metagenomic Sequence Analysis (IMSA), a flexible, fast, and robust computational analysis pipeline that is available for public use. IMSA takes input sequence from high throughput datasets and uses a user-defined host database to filter out host sequence. IMSA then aligns the filtered reads to a user-defined universal database to characterize exogenous reads within the host background. IMSA assigns a score to each node of the taxonomy based on read frequency, and can output this as a taxonomy report suitable for cluster analysis or as a taxonomy map (TaxMap). IMSA also outputs the specific sequence reads assigned to a taxon of interest for downstream analysis. We demonstrate the use of IMSA to detect pathogens and normal flora within sequence data from a primary human cervical cancer carrying HPV16, a primary human cutaneous squamous cell carcinoma carrying HPV 16, the CaSki cell line carrying HPV16, and the HeLa cell line carrying HPV18.
    PLoS ONE 05/2013; 8(5):e64546. DOI:10.1371/journal.pone.0064546 · 3.53 Impact Factor
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    ABSTRACT: Array Comparative Genomic Hybridisation (aCGH) profiling is currently the gold standard for genetic diagnosis of copy number. Next Generation Sequencing technologies provide an alternative and adaptable method of detecting copy number by comparing the number of sequence reads in non-overlapping windows between patient and control samples. Detection of copy number using the BlueGnome 8x60K oligonucleotide aCGH platform was compared with low resolution Next Generation Sequencing using the Illumina GAIIx on 39 patients referred to the Leeds Clinical Cytogenetics Laboratory with developmental delay and/or learning difficulties. Sensitivity and workflow of the two platforms were compared. Customised copy number algorithms assessed sequence counts and detected changes in copy number. Imbalances detected on both platforms were compared. Of the thirty-nine patients analysed, all eleven imbalances detected by array CGH and confirmed by FISH or Q-PCR were also detected by CNV-seq. In addition, CNV-seq reported one purported pathogenic copy number variant that was not detected by array CGH. Non-pathogenic, unconfirmed copy number calls were detected by both platforms; however few were concordant between the two. CNV-seq offers an alternative to array CGH for copy number analysis with resolution and future costs comparable to conventional array CGH platforms and with less stringent sample requirements.
    Genomics 04/2013; 102(3). DOI:10.1016/j.ygeno.2013.04.006 · 2.79 Impact Factor
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    ABSTRACT: Chromosomal translocations and other abnormalities are central to the initiation of cancer in all cell types. Understanding the mechanism is therefore important to evaluate the evolution of cancer from the cancer initiating events to overt disease. Recent work has concentrated on model systems to develop an understanding of the molecular mechanisms of translocations but naturally occurring events are more ideal case studies since biological selection is absent from model systems. In solid tumours, nonreciprocal translocations are most commonly found, and accordingly we have investigated the recurrent nonreciprocal t(3;5) chromosomal translocations in renal carcinoma to better understand the mechanism of these naturally occurring translocations in cancer. Unexpectedly, the junctions of these translocations can be associated with site-specific, intrachromosomal inversion involving at least two double strand breaks (DSB) in cis and rejoining by nonhomologous end joining or micro-homology end joining. However, these translocations are not necessarily associated with transcribed regions questioning accessibility per se in controlling these events. In addition, intrachromosomal deletions also occur. We conclude these naturally occurring, nonreciprocal t(3;5) chromosomal translocations occur after complex and multiple unresolved intrachromosomal DSBs leading to aberrant joining with concurrent interstitial inversion and that clonal selection of cells is the critical element in cancer development emerging from a plethora of DSBs that may not always be pathogenic. © 2013 Wiley Periodicals, Inc.
    Genes Chromosomes and Cancer 04/2013; 52(4). DOI:10.1002/gcc.22038 · 3.84 Impact Factor
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Publication Stats

3k Citations
673.60 Total Impact Points

Institutions

  • 2007–2015
    • University of Leeds
      • Leeds Institute of Molecular Medicine (LIMM)
      Leeds, England, United Kingdom
  • 2008–2014
    • St. James University
      Сент-Джеймс, New York, United States
    • Saint James School Of Medicine
      Park Ridge, Illinois, United States
  • 2010–2012
    • Institute of Genetics and Molecular Medicine
      Edinburgh, Scotland, United Kingdom
  • 1994–2007
    • University of Cambridge
      • Department of Oncology
      Cambridge, England, United Kingdom
    • Cambridge Eco
      Cambridge, England, United Kingdom
  • 1989–1998
    • Medical Research Council (UK)
      Londinium, England, United Kingdom
  • 1989–1994
    • Mrc Harwell
      Oxford, England, United Kingdom
  • 1993
    • University of Texas at San Antonio
      San Antonio, Texas, United States
  • 1989–1991
    • Uppsala University
      Uppsala, Uppsala, Sweden
  • 1990
    • MRC Clinical Sciences Centre
      London Borough of Harrow, England, United Kingdom
  • 1988
    • Ludwig Institute for Cancer Research
      La Jolla, California, United States
  • 1987–1988
    • Cancer Research UK Cambridge Institute
      Cambridge, England, United Kingdom