David Quigley, PhD

Publications

Peer-reviewed publications

Google Scholar link

2017
Age, estrogen, and immune response in breast adenocarcinoma and adjacent normal tissue.
Quigley DA, Tahiri A, Lüders T, Riis M, Balmain A, Børresen-Dale A, Bukholm I, & Kristensen V.
OncoImmunology, 2017, Accepted, in press
Analysis of circulating cell-free DNA identifies multi-clonal heterogeneity of BRCA2 reversion mutations associated with resistance to PARP inhibitors
Quigley DA*, Alumkal JJ*, Wyatt A, Kothari V, Foye A, Lloyd P, Aggarwal R, Kim W, Lu E, Schwartzman J, Beja K, Annala M, Das R, Diolaiti M, Pritchard C, Thomas G, Tomlins S, Knudsen K, Lord C, Ryan C, Youngren K, Beer T, Ashworth A, Small E, Feng FY. (* co-first authors)
Cancer Discovery, DOI: 10.1158/2159-8290.CD-17-0146. January 2017, In press and online. [Pubmed]
2016
Panx3 links body mass index and tumorigenesis in a genetically heterogeneous mouse model of carcinogen-induced cancer
Halliwill K, Quigley DA, Kang HC, Rosario R, Ginzinger D, Balmain A.
Genome Medicine, 2016 Aug 9;8(1):83. [Pubmed]
Gene expression architecture of mouse dorsal and tail skin reveals functional differences in inflammation and cancer.
Quigley DA, Kandyba E, Huang P, Halliwill K, Sjölund J, Pelorosso F, Wong C, Hirst G, Wu D, Delrosario R, Kumar A, & Balmain A
Cell Reports, 2016 Jul 26;16(4):1153-65. [Pubmed].
Large Scale Profiling of Kinase Dependencies in Cancer Cell Lines
Campbell J, Ryan C, Brough R, Bajrami I, Pemberton H, Chong I, Costa-Cabral S, Frankum J, Gulati A, Holme H, Miller R, Postel-Vinay S, Rafiq R, Wei W, Williamson C, Quigley DA, Tym J, Al-Lazikani B, Fenton T, Natrajan R, Strauss S, Ashworth A and Lord C
Cell Reports, 2016 Mar 15;14(10):2490-501 [Pubmed] (open access)
2015
Predicting prognosis and therapeutic response from interactions between lymphocytes and tumor cells
Quigley DA., Kristensen V.
Molecular Oncology, 2015 Dec;9(10):2054-62. [Pubmed]
equalizer reduces SNP bias in Affymetrix microarrays.
Quigley DA.
BMC Bioinformatics, 2015, 16:238 (30 July 2015) [Pubmed] (open access)
The software package equalizer allows you to remove probes from Affymetrix microarrays using VCF files that describe the location of germline SNPs.
See the equalizer project page for more information.
2014
Expression Quantitative Trait Loci and Receptor Pharmacology Implicate Arg1 and the GABA-A Receptor as Therapeutic Targets in Neuroblastoma
Hackett C, Quigley DA, Wong R, Chen J, Cheng C, Song Y, Wei J, Pawlikowska L, Bao Y, Goldenberg D, Nguyen K, Gustafson W, Rallapalli S, Cho Y, Cook J, Kozlov S, Mao J, Van Dyke T, Kwok P, Kahn J, Balmain A, Fan Q, Weiss W
Cell Reports 2014 Nov 6;9(3):1034-46. [Pubmed]
The mutational landscapes of genetic and chemical models of Kras-driven non-small cell lung cancer
Westcott PM, Halliwill KD, To M, Mamunar R, Rust A, Keane T, Delrosario R, Jen K, Fredlund E, Quigley DA, Gurley K, Kemp C, Adams D, Balmain A
Nature 2014 Nov 2. doi: 10.1038/nature13898 [Pubmed]
Lymphocyte invasion in IC10/Basal-like breast tumors is associated with wild-type TP53.
Quigley DA, Silwal-Pandit L, Dannenfelser R, Langerød A, Vollan HK, Vaske C, Siegel J, Troyanskaya O, Chin S, Caldas C, Balmain A, Børresen-Dale A, Kristensen V.
Molecular Cancer Research, 2014 Oct 28. pii: molcanres.0387.2014 [Pubmed]
Although TP53 status is not prognostic in Basal-like breast tumors, here we show a novel association between TP53 status in Basal-like and IC10 tumors and protective lymphocyte infiltration.
The 5p12 breast cancer susceptibility locus affects MRPS30 expression in estrogen-receptor positive tumors.
Quigley DA, Fiorito E, Nord S, Van Loo P, Alnaes G, Fleischer T, Tost J, Vollan HK, Tramm T, Overgaard J, Bukholm IR, Hurtado A, Balmain A, Børresen-Dale A, & Kristensen V.
Molecular Oncology, 2014 Mar;8(2):273-84 [Pubmed]
Here we use eQTL mapping and functional analysis in normal breast tissue and breast tumors to propose a mechanism for the breast cancer susceptibility locus on 5p12, previously identified by GWAS.
Code and data to reproduce
Identification of Hipk2 as an essential regulator of white fat development.
Sjölund J, Pelorosso F, Quigley DA, DelRosario R, and Balmain A
Proceedings of the National Academy of Sciences 2014 May 20;111(20):7373-8 [Pubmed]
Two different microarray datasets are referred to by the code, mouse skin data and mouse mammary tissue data. Raw data for both of these datasets are publicly available on GEO, at accessions GSE46077 and GSE12248. Processed data as used by the code in the paper is included in the data folder.
ANALYSIS
Please see the README file for details. Analysis was executed in R using code in the file "reproduce_hipk2.r".
TP53 mutation spectrum in breast cancer is subtype specific and has distinct prognostic relevance.
Silwal-Pandit L, Vollan HK, Chin SF, Rueda OM, McKinney S, Osako T, Quigley DA, Kristensen VN, Aparicio S, Børresen-Dale AL, Caldas C, Langerød A.
Clinical Cancer Research 2014 Jul 1;20(13):3569-80. [Pubmed ]
Lung Tumorigenesis in a Conditional Cul4A Transgenic Mouse Model.
Yang YL, Hung MS, Wang Y, Ni J, Mao JH, Hsieh D, Au A, Kumar A, Quigley D, Fang LT, Yeh CC, Xu Z, Jablons DM, You L.
J Pathol. 2014 Mar 19 [Pubmed]
2013
Rewiring of human lung cell lineage and mitotic networks in lung adenocarcinomas.
Kim IJ, Quigley D, To M, Jen, Pham P, Lin K, Jo B, Jen K, Raz D, Kim J, Mao JH, Jablons D & Balmain A
Nature Communications, 2013 Apr 16 [Nature Website]
Inflammation and Hras Signaling Control Epithelial-mesenchymal Transition during Skin Tumor Progression
Wong C, Yu J, Quigley DA, To M, Jen Kuang-Yu, Huang P, Del Rosario R & Balmain A
Genes and Development, 2013 Mar 15;27(6):670-82 [Pubmed]
Multiple Self-Healing Squamous Epithelioma (MSSE): Rare Variants in an Adjacent Region of Chromosome 9q22.3 to known TGFBR1 Mutations Suggest a Digenic or Multilocus Etiology.
Kang HC, Quigley D, Kim IJ, Wakabayashi Y, Ferguson-Smith MA, D'Alessandro M, Lane EB, Akhurst RJ, Goudie DR, Balmain A.
Journal of Investigative Dermatology, 2013 January 28. [Pubmed]
2012
Mouse and human strategies identify PTPN14 as a modifier of angiogenesis and hereditary haemorrhagic telangiectasia.
Benzinou M, Clermont FF, Letteboer TG, Kim JH, Espejel S, Harradine KA, Arbelaez J, Luu MT, Roy R, Quigley D, Higgins MN, Zaid M, Aouizerat BE, van Amstel JK, Giraud S, Dupuis-Girod S, Lesca G, Plauchu H, Hughes CC, Westermann CJ & Akhurst RJ.
Nature Communications, 2012 January 10. [Pubmed]
2011
Progressive genomic instability in the FVB/KrasLA2 mouse model of lung cancer.
To MD, Quigley D, Mao J, Rosario R, Hsu J, Hodgson G, Jacks T, & Balmain A.
Molecular Cancer Research, 2011 August 1. [Pubmed] [PDF]
The array-CGH data used in this paper can be downloaded from GEO at GSE29230. The data as used in the reproducible analysis can be downloaded directly as a zip archive.
Membrane Array Analysis of Tear Proteins in Ocular Cicatricial Pemphigoid.
Chan MF, Sack R, Quigley DA, Sathe S, Vijmasi T, Li S, Holsclaw D, Strauss EC, McNamara NA.
Optometry & Visual Science, 2011 May 5. [Pubmed]
Amphotericin B and natamycin are not synergistic in vitro against Fusarium and Aspergillus spp. isolated from keratitis.
Lalitha P, Shapiro BL, Loh AR, Fothergill AW, Prajna NV, Srinivasan M, Oldenburg CE, Quigley DA, Chidambaram JD, McLeod SD, Acharya NR, Lietman TM.
British Journal of Ophthalmology, 2011 May;95(5):744-5. [Pubmed]
Outgrowth of drug-resistant carcinomas expressing markers of tumor aggression after long-term TGFBRI/II kinase inhibition with LY2109761.
Connolly EC, Saunier EF, Quigley D, Luu MT, De Sapio A, Hann B, Yingling JM, Akhurst RJ.
Cancer Research, 2011 Mar 15;71(6):2339-49.
[Pubmed]
Network Analysis of Skin Tumor Progression Identifies a Rewired Genetic Architecture Affecting Inflammation and Tumor Susceptibility.
Quigley DA, To MD, Kim IJ, Lin KK, Albertson DG, Sjolund J, Perez-Losada J, Balmain A.
Genome Biology, 2011 Jan 18;12(1):R5. [Pubmed] (open access) [PDF] [supplement]
Here we show how the genetic architecture of skin cancer is affected by somatic alterations during progression from normal tissue through benign and malignant tumors.
Raw expression and array-CGH data are available in GEO in SuperSeries GSE21264. Note that this SuperSeries includes the data from the Nature paper.
Genotypes used for this analysis
aCGH data used for this analysis
eQTL Results
eQTL results for Tails, Papillomas, and Carcinomas can be downloaded here. eQTL results were calculated by linear regression using code that can be downloaded from my GitHub repository. Please see this README file for a general overview of the analysis.
2010
Deletion of the PER3 gene on chromosome 1p36 in recurrent ER-positive breast cancer.
Climent J, Perez-Losada J, Quigley DA, Kim IJ, Delrosario R, Jen KY, Bosch A, Lluch A, Mao JH, Balmain A.
Journal of Clinical Oncology, 2010. Aug 10;28(23):3770-8.
[Pubmed] [PDF] [supplement]
2009
Systems genetics analysis of cancer susceptibility: from mouse models to humans.
Quigley DA & Balmain A.
Nature Reviews: Genetics, 2009. Sep;10(9) 651-7. [Pubmed]
This Perspective reviewed the state of systems genetics analysis of cancer.
Genetic architecture of mouse skin inflammation and tumor susceptibility.
Quigley DA, To MD, Perez-Losada J, Pelorosso F, Mao J, Nagase H, Ginzinger D, & Balmain A.
Nature, 2009. Mar 26;458(7237):505-8. [Pubmed]
Here we used eQTL mapping in normal skin of mice who had developed tumors to define the genetic architecture of normal tissue and identify loci associated with hematopoietic traits and tumor development.
Analysis was performed using the 71 microarrays described in the paper; the GEO archive also contains arrays for the parental strains, which should be removed if you want to reproduce as closely as possible the published results.
  • Raw expression data for this paper (Affymetrix CEL files) are available at GEO, GSE12248.
  • Annotation and sample data, including the genotype calls, microarray annotation file derived from Affymetrix na31 probeset annotations, processed data, R code to normalize arrays, and sample attributes, can be obtained here.
  • eQTL results as calculated using the same methods that were described in the methods of the paper are available here..
To reproduce the eQTL analysis from scratch you will need either to perform the linear regressions yourself, or to build the eqtl software that I wrote from C++ source code. The code to call eqtl using four cores and 1000 permutations would be:
            BIN_EQTL=/notebook/code/src/eqtl/build/Release/eqtl
            DIR_REP=/notebook/hiroki/tail_eQTL_paper/reproduce
            $BIN_EQTL \
            -d$DIR_REP/expr_above_mean_4.txt \
            -f$DIR_REP/sample_attributes.txt \
            -g$DIR_REP/gene_attributes_na31_above_mean_4.txt \
            -e$DIR_REP/calls_GSE12248.txt \
            -h$DIR_REP/sample_attributes_calls.txt \
            -s$DIR_REP/gene_attributes_calls_GSE12248.txt \
            -kT -lChr,loc_start,Chr,loc_start -carray_id -n1000 -w4 -o$DIR_REP/eqtl_chr_1000.txt 
            
You can download the Cytoscape CYS file used to create Figure One of Quigley Nature 2009: Q_et_al_figure_one.cys. You will need an up-to-date version of the Java runtime to load the file; I recommend the latest version of Cytoscape as well.


2008
Antibody Protein Array Analysis of the Tear Film Cytokines.
Li S, Sack R, Vijmasi T, Sathe S, Beaton A, Quigley D, Gallup M & McNamara N. Optometry & Vision Science, 2008. Aug;85(8):653-60.
[Pubmed]
2007
Learning regulatory programs that accurately predict differential expression with MEDUSA. Kundaje A, Lianoglou S, Li X, Quigley D, Arias M, Wiggins CH, Zhang L, Leslie C.
Ann N Y Acad Sci. 2007 Dec;1115:178-202.
[Pubmed]
Commentaries
Quigley, DA.
RNA-seq Permits a Closer Look at Normal Skin and Psoriasis Gene Networks.
Journal of Investigative Dermatology, 2014. 134: 1789–1791 doi:10.1038/jid.2014.66 [Pubmed] [JID link]
Comments on Li et al. JID 2014
Talks

Introduction to Quantitative Biology: 2015 Teaching slides


Updated June 2016