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Dive into the research topics where Ella R. Thompson is active.

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Featured researches published by Ella R. Thompson.


Nature Genetics | 2008

No evidence of clonal somatic genetic alterations in cancer-associated fibroblasts from human breast and ovarian carcinomas.

Wen Qiu; Min Hu; Anita Sridhar; Ken Opeskin; Stephen B. Fox; Michail Shipitsin; Melanie Trivett; Ella R. Thompson; Manasa Ramakrishna; Kylie L. Gorringe; Kornelia Polyak; Izhak Haviv; Ian G. Campbell

There is increasing evidence showing that the stromal cells surrounding cancer epithelial cells, rather than being passive bystanders, might have a role in modifying tumor outgrowth. The molecular basis of this aspect of carcinoma etiology is controversial. Some studies have reported a high frequency of genetic aberrations in carcinoma-associated fibroblasts (CAFs), whereas other studies have reported very low or zero mutation rates. Resolution of this contentious area is of critical importance in terms of understanding both the basic biology of cancer as well as the potential clinical implications of CAF somatic alterations. We undertook genome-wide copy number and loss of heterozygosity (LOH) analysis of CAFs derived from breast and ovarian carcinomas using a 500K SNP array platform. Our data show conclusively that LOH and copy number alterations are extremely rare in CAFs and cannot be the basis of the carcinoma-promoting phenotypes of breast and ovarian CAFs.


Bioinformatics | 2012

CONTRA: copy number analysis for targeted resequencing.

Jason Li; Richard Lupat; Kaushalya C. Amarasinghe; Ella R. Thompson; Maria A. Doyle; Georgina L. Ryland; Richard W. Tothill; Saman K. Halgamuge; Ian G. Campbell; Kylie L. Gorringe

Motivation: In light of the increasing adoption of targeted resequencing (TR) as a cost-effective strategy to identify disease-causing variants, a robust method for copy number variation (CNV) analysis is needed to maximize the value of this promising technology. Results: We present a method for CNV detection for TR data, including whole-exome capture data. Our method calls copy number gains and losses for each target region based on normalized depth of coverage. Our key strategies include the use of base-level log-ratios to remove GC-content bias, correction for an imbalanced library size effect on log-ratios, and the estimation of log-ratio variations via binning and interpolation. Our methods are made available via CONTRA (COpy Number Targeted Resequencing Analysis), a software package that takes standard alignment formats (BAM/SAM) and outputs in variant call format (VCF4.0), for easy integration with other next-generation sequencing analysis packages. We assessed our methods using samples from seven different target enrichment assays, and evaluated our results using simulated data and real germline data with known CNV genotypes. Availability and implementation: Source code and sample data are freely available under GNU license (GPLv3) at http://contra-cnv.sourceforge.net/ Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.


Clinical Cancer Research | 2007

High-Resolution Single Nucleotide Polymorphism Array Analysis of Epithelial Ovarian Cancer Reveals Numerous Microdeletions and Amplifications

Kylie L. Gorringe; Sharoni Jacobs; Ella R. Thompson; Anita Sridhar; Wen Qiu; David Y. H. Choong; Ian G. Campbell

Purpose: Genetic changes in sporadic ovarian cancer are relatively poorly characterized compared with other tumor types. We have evaluated the use of high-resolution whole genome arrays for the genetic profiling of epithelial ovarian cancer. Experimental Design: We have evaluated 31 primary ovarian cancers and matched normal DNA for loss of heterozygosity and copy number alterations using 500K single nucleotide polymorphism arrays. Results: In addition to identifying the expected large-scale genomic copy number changes, >380 small regions of copy number gain or loss (<500 kb) were identified among the 31 tumors, including 33 regions of high-level gain (>5 copies) and 27 homozygous deletions. The existence of such a high frequency of small regions exhibiting copy number alterations had not been previously suspected because earlier genomic array platforms lacked comparable resolution. Interestingly, many of these regions harbor known cancer genes. For example, one tumor harbored a 350-kb high-level amplification centered on FGFR1 and three tumors showed regions of homozygous loss 109 to 216 kb in size involving the RB1 tumor suppressor gene only. Conclusions: These data suggest that novel cancer genes may be located within the other identified small regions of copy number alteration. Analysis of the number of copy number breakpoints and the distribution of the small regions of copy number change indicate high levels of structural chromosomal genetic instability in ovarian cancer.


PLOS Genetics | 2012

Exome sequencing identifies rare deleterious mutations in DNA repair genes FANCC and BLM as potential breast cancer susceptibility alleles.

Ella R. Thompson; Maria A. Doyle; Georgina L. Ryland; Simone M. Rowley; David Y. H. Choong; Richard W. Tothill; Heather Thorne; kConFab; Daniel R. Barnes; Jason Li; Jason Ellul; Gayle Philip; Yoland C. Antill; Paul A. James; Alison H. Trainer; Gillian Mitchell; Ian G. Campbell

Despite intensive efforts using linkage and candidate gene approaches, the genetic etiology for the majority of families with a multi-generational breast cancer predisposition is unknown. In this study, we used whole-exome sequencing of thirty-three individuals from 15 breast cancer families to identify potential predisposing genes. Our analysis identified families with heterozygous, deleterious mutations in the DNA repair genes FANCC and BLM, which are responsible for the autosomal recessive disorders Fanconi Anemia and Bloom syndrome. In total, screening of all exons in these genes in 438 breast cancer families identified three with truncating mutations in FANCC and two with truncating mutations in BLM. Additional screening of FANCC mutation hotspot exons identified one pathogenic mutation among an additional 957 breast cancer families. Importantly, none of the deleterious mutations were identified among 464 healthy controls and are not reported in the 1,000 Genomes data. Given the rarity of Fanconi Anemia and Bloom syndrome disorders among Caucasian populations, the finding of multiple deleterious mutations in these critical DNA repair genes among high-risk breast cancer families is intriguing and suggestive of a predisposing role. Our data demonstrate the utility of intra-family exome-sequencing approaches to uncover cancer predisposition genes, but highlight the major challenge of definitively validating candidates where the incidence of sporadic disease is high, germline mutations are not fully penetrant, and individual predisposition genes may only account for a tiny proportion of breast cancer families.


Cancer Research | 2007

Genome-Wide, High-Resolution Detection of Copy Number, Loss of Heterozygosity, and Genotypes from Formalin-Fixed, Paraffin-Embedded Tumor Tissue Using Microarrays

Sharoni Jacobs; Ella R. Thompson; Yasuhito Nannya; Go Yamamoto; Raji Pillai; Seishi Ogawa; Dione K. Bailey; Ian G. Campbell

Formalin-fixed, paraffin-embedded (FFPE) material tends to yield degraded DNA and is thus suboptimal for use in many downstream applications. We describe an integrated analysis of genotype, loss of heterozygosity (LOH), and copy number for DNA derived from FFPE tissues using oligonucleotide microarrays containing over 500K single nucleotide polymorphisms. A prequalifying PCR test predicted the performance of FFPE DNA on the microarrays better than age of FFPE sample. Although genotyping efficiency and reliability were reduced for FFPE DNA when compared with fresh samples, closer examination revealed methods to improve performance at the expense of variable reduction in resolution. Important steps were also identified that enable equivalent copy number and LOH profiles from paired FFPE and fresh frozen tumor samples. In conclusion, we have shown that the Mapping 500K arrays can be used with FFPE-derived samples to produce genotype, copy number, and LOH predictions, and we provide guidelines and suggestions for application of these samples to this integrated system.


Journal of Clinical Oncology | 2016

Panel Testing for Familial Breast Cancer: Calibrating the Tension Between Research and Clinical Care

Ella R. Thompson; Simone M. Rowley; Na Li; Simone McInerny; Lisa Devereux; Michelle W. Wong-Brown; Alison H. Trainer; Gillian Mitchell; Rodney J. Scott; Paul A. James; Ian G. Campbell

PURPOSE Gene panel sequencing is revolutionizing germline risk assessment for hereditary breast cancer. Despite scant evidence supporting the role of many of these genes in breast cancer predisposition, results are often reported to families as the definitive explanation for their family history. We assessed the frequency of mutations in 18 genes included in hereditary breast cancer panels among index cases from families with breast cancer and matched population controls. PATIENTS AND METHODS Cases (n = 2,000) were predominantly breast cancer-affected women referred to specialized Familial Cancer Centers on the basis of a strong family history of breast cancer and BRCA1 and BRCA2 wild type. Controls (n = 1,997) were cancer-free women from the LifePool study. Sequencing data were filtered for known pathogenic or novel loss-of-function mutations. RESULTS Excluding 19 mutations identified in BRCA1 and BRCA2 among the cases and controls, a total of 78 cases (3.9%) and 33 controls (1.6%) were found to carry potentially actionable mutations. A significant excess of mutations was only observed for PALB2 (26 cases, four controls) and TP53 (five cases, zero controls), whereas no mutations were identified in STK11. Among the remaining genes, loss-of-function mutations were rare, with similar frequency between cases and controls. CONCLUSION The frequency of mutations in most breast cancer panel genes among individuals selected for possible hereditary breast cancer is low and, in many cases, similar or even lower than that observed among cancer-free population controls. Although multigene panels can significantly aid in cancer risk management and expedite clinical translation of new genes, they equally have the potential to provide clinical misinformation and harm at the individual level if the data are not interpreted cautiously.


Human Mutation | 2012

Analysis of RAD51C germline mutations in high‐risk breast and ovarian cancer families and ovarian cancer patients

Ella R. Thompson; Samantha E. Boyle; Julie Johnson; Georgina L. Ryland; Sarah Sawyer; David Y. H. Choong; kConFab; Georgia Chenevix-Trench; Alison H. Trainer; Geoffrey J. Lindeman; Gillian Mitchell; Paul A. James; Ian G. Campbell

There is strong evidence that overtly inactivating mutations in RAD51C predispose to hereditary breast and ovarian cancer but the prevalence of such mutations, and whether they are associated with a particular clinical phenotype, remains unclear. Resolving these questions has important implications for the implementation of RAD51C into routine clinical genetic testing. Consequently, we have performed a large RAD51C mutation screen of hereditary breast and ovarian cancer families, and the first study of unselected patients diagnosed with ovarian cancer. Our data confirm a consistent but low frequency (2/335 families) of inactivating RAD51C mutations among families with a history of both breast and ovarian cancer and an absence of mutations among breast cancer only families (0/1,053 families). Our data also provide support for the designation of the missense variant p.Gly264Ser as a moderate penetrance allele. Hum Mutat 33:95–99, 2012.


Journal of Medical Genetics | 2012

Rare variants in XRCC2 as breast cancer susceptibility alleles

Florentine S. Hilbers; Juul T. Wijnen; Nicoline Hoogerbrugge; Jan C. Oosterwijk; Margriet J. Collee; Paolo Peterlongo; Paolo Radice; Siranoush Manoukian; Irene Feroce; Fabio Capra; Fergus J. Couch; Xianshu Wang; Lucia Guidugli; Kenneth Offit; Sohela Shah; Ian G. Campbell; Ella R. Thompson; Paul A. James; Alison H. Trainer; Javier de Gracia; Javier Benitez; Christi J. van Asperen; Peter Devilee

Background Recently, rare germline variants in XRCC2 were detected in non-BRCA1/2 familial breast cancer cases, and a significant association with breast cancer was reported. However, the breast cancer risk associated with these variants needs further evaluation. Methods The coding regions and exon–intron boundaries of XRCC2 were scanned for mutations in an international cohort of 3548 non-BRCA1/2 familial breast cancer cases and 1435 healthy controls using various mutation scanning methods. Predictions on functional relevance of detected missense variants were obtained from three different prediction algorithms. Results The only protein-truncating variant detected was found in a control. Rare non-protein-truncating variants were detected in 20 familial cases (0.6%) and nine healthy controls (0.6%). Although the number of variants predicted to be damaging or neutral differed between prediction algorithms, in all instances these categories were evenly represented among cases and controls. Conclusions Our data do not confirm an association between XRCC2 variants and breast cancer risk, although a relative risk smaller than two could not be excluded. Variants in XRCC2 are unlikely to explain a substantial proportion of familial breast cancer.


Human Molecular Genetics | 2015

FANCM c.5791C>T nonsense mutation (rs144567652) induces exon skipping, affects DNA repair activity and is a familial breast cancer risk factor

Paolo Peterlongo; Irene Catucci; Mara Colombo; Laura Caleca; Eliseos J. Mucaki; Massimo Bogliolo; Maria Marín; Francesca Damiola; Loris Bernard; Valeria Pensotti; Sara Volorio; Valentina Dall'Olio; Alfons Meindl; Claus R. Bartram; Christian Sutter; Harald Surowy; Valérie Sornin; Marie Gabrielle Dondon; Séverine Eon-Marchais; Dominique Stoppa-Lyonnet; Nadine Andrieu; Olga M. Sinilnikova; Gillian Mitchell; Paul A. James; Ella R. Thompson; Marina Marchetti; Cristina Verzeroli; Carmen Tartari; Gabriele Lorenzo Capone; Anna Laura Putignano

Numerous genetic factors that influence breast cancer risk are known. However, approximately two-thirds of the overall familial risk remain unexplained. To determine whether some of the missing heritability is due to rare variants conferring high to moderate risk, we tested for an association between the c.5791C>T nonsense mutation (p.Arg1931*; rs144567652) in exon 22 of FANCM gene and breast cancer. An analysis of genotyping data from 8635 familial breast cancer cases and 6625 controls from different countries yielded an association between the c.5791C>T mutation and breast cancer risk [odds ratio (OR) = 3.93 (95% confidence interval (CI) = 1.28-12.11; P = 0.017)]. Moreover, we performed two meta-analyses of studies from countries with carriers in both cases and controls and of all available data. These analyses showed breast cancer associations with OR = 3.67 (95% CI = 1.04-12.87; P = 0.043) and OR = 3.33 (95% CI = 1.09-13.62; P = 0.032), respectively. Based on information theory-based prediction, we established that the mutation caused an out-of-frame deletion of exon 22, due to the creation of a binding site for the pre-mRNA processing protein hnRNP A1. Furthermore, genetic complementation analyses showed that the mutation influenced the DNA repair activity of the FANCM protein. In summary, we provide evidence for the first time showing that the common p.Arg1931* loss-of-function variant in FANCM is a risk factor for familial breast cancer.


Breast Cancer Research | 2013

COMPLEXO: identifying the missing heritability of breast cancer via next generation collaboration

Melissa C. Southey; Daniel J. Park; Tú Nguyen-Dumont; Ian G. Campbell; Ella R. Thompson; Alison H. Trainer; Georgia Chenevix-Trench; Jacques Simard; Martine Dumont; Penny Soucy; Mads Thomassen; Lars Jønson; Inge Søkilde Pedersen; Thomas V O Hansen; Heli Nevanlinna; Sofia Khan; Olga M. Sinilnikova; Sylvie Mazoyer; Fabienne Lesueur; Francesca Damiola; Rita K. Schmutzler; Alfons Meindl; Eric Hahnen; Michael R. Dufault; T. L. Chris Chan; Ava Kwong; Rosa B. Barkardottir; Paolo Radice; Paolo Peterlongo; Peter Devilee

Linkage analysis, positional cloning, candidate gene mutation scanning and genome-wide association study approaches have all contributed significantly to our understanding of the underlying genetic architecture of breast cancer. Taken together, these approaches have identified genetic variation that explains approximately 30% of the overall familial risk of breast cancer, implying that more, and likely rarer, genetic susceptibility alleles remain to be discovered.

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Ian G. Campbell

Peter MacCallum Cancer Centre

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Paul A. James

Peter MacCallum Cancer Centre

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Gillian Mitchell

Peter MacCallum Cancer Centre

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Jason Li

Peter MacCallum Cancer Centre

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Kylie L. Gorringe

Peter MacCallum Cancer Centre

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Georgina L. Ryland

Peter MacCallum Cancer Centre

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Simone M. Rowley

Peter MacCallum Cancer Centre

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David Y. H. Choong

Peter MacCallum Cancer Centre

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Lisa Devereux

Peter MacCallum Cancer Centre

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