The APCB is a named author on a number of manuscripts as listed below.


Publications in 2021

APCB_Shape-05 Polygenic hazard score is associated with prostate cancer in multi-ethnic populations

Huynh-Le  et al., Nat Commun; [Impact factor 12.121]

 APCB_Shape-05 Additional SNPs improve risk stratification of a polygenic hazard score for prostate cancer

Karunamuni  et al., Prostate Cancer Prostatic Dis; [Impact factor 4.311]


Publications in 2020

APCB_Shape-05 The effect of sample size on polygenic hazard models for prostate cancer

Karunamuni et al., Eur J Hum Genet; [Impact factor 3.657]

APCB_Shape-05 A Genetic Risk Score to Personalize Prostate Cancer Screening, Applied to Population Data

Huynh-Le et al., Cancer Epidemiol Biomarkers Prev; [Impact factor 5.057]


Publications in 2019

APCB_Shape-05 ETS1 induces transforming growth factor β signaling and promotes epithelial-to-mesenchymal transition in prostate cancer cells

Rodger  et al., J Cell Biochem; [Impact factor 4.237]

APCB_Shape-05 MicroRNA-3162-5p-Mediated Crosstalk between Kallikrein Family Members Including Prostate-Specific Antigen in Prostate Cancer

Matin et al., Clin Chem; [Impact factor 8.008]

 APCB_Shape-05 Establishing a cryopreservation protocol for patient-derived xenografts of prostate cancer

Porter et al., Prostate; [Impact factor 8.008]


Publications in 2018

APCB_Shape-05 Association analysis of a microsattelite repeat in the TRIB1 gene with prostate cancer risk, aggressiveness and survival.

Moya et al., Front Genetic 2018; [Impact factor 3.789]

APCB_Shape-05 ETS1 induces transforming growth factor b signalling and promotes epithelial-to-mesenchymal transition in prostate cancer cells.

Rodgers et al., J Cell Biochem 2018; [Impact factor 3.446]

APCB_Shape-05 Patient-derived models of abiraterone-and Enzalutamide-resistant prostate cancer reveal sensitivity to ribosome-directed therapy.

Lawrence et al., Eur Urol 2018; [Impact factor 17.581]

APCB_Shape-05 Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci.

Schumacher et al., Nat Genet 2018; [Impact factor 27.125]

APCB_Shape-05 A plasma biomarker panel of four microRNAs for the diagnosis of prostate cancer.

Martin et al., Sci Rep 2018; [Impact factor 4.122]

APCB_Shape-05 Polygenic hazard score to guide screening for aggressive prostate cancer: development and validation in large scale cohorts.

Seibert et al., BMJ 2018; [Impact factor 23.295]

APCB_Shape-05 Intraductal carcinoma of the prostate can evade androgen deprivation, with emergence of castrate-tolerant cells.

Porter et al., BJU 2018; [Impact factor 4.387]


Publications in 2017

APCB_Shape-05 A micro satellite repeat in PCA3 long non-coding RNA is associated with prostate cancer risk and aggressiveness.

Lai et al., Sci Rep 2017; [Impact factor 4.122]

APCB_Shape-05 Extracellular vesicles for personalised therapy decision support in advanced metastatic cancers and its potential impact for prostate cancer.

Soekmadji et al., Prostate 2017; [Impact factor 3.565]

APCB_Shape-05 Height, selected genetic markers and prostate cancer risk: results from practical consortium.

Lophatananon et al., Br J Cancer 2017; [Impact factor 5.569]

APCB_Shape-05 Kallikrein-related peptidase 4 induces cancer-associated fibroblast features in prostate-derived stromal cells.

Kryza et al., Mol Oncol 2017; [Impact factor 5.314]

APCB_Shape-05 Characterisation of microbial communities within aggressive prostate tissues.

Yow et al., Infect Agent Cancer 2017; [Impact factor 1.718]


Publications in 2016

APCB_Shape-05 Commentary on “A large0scale analysis of genetic variants within putative miRNA binding sites in prostate cancer.”

Lin D., Urol Oncol 2016; [Impact factor 3.767]

APCB_Shape-05 A novel class of Hsp90 C-terminal modulators have pre-clinical efficacy in prostate tumour cells without induction of a heat shock response.

Armstrong et al., Prostate 2016; [Impact factor 3.565]

APCB_Shape-05 Assays for qualification and quality stratification of clinical biospecimens used in research: A technical report from the ISBER biospecimen science working group.

Betsou et al., Biopreserv Biobank 2016; [Impact factor 1.698]

APCB_Shape-05 Genome-wide meta-analyses of breast, ovarian and prostate cancer association studies identify multiple new susceptibility loci shared by at least two cancer types.

Kar et al., Cancer Discov 2016; [Impact factor 19.453]

APCB_Shape-05 High expression of TRO2P2 characterizes different cell subpopulations in androgen-sensitive and androgen-independent prostate cancer cells.

Xie et al., Oncotarget 2016; [Impact factor 5.008]


Publications in 2015

APCB_Shape-05 Fusion transcript loci share many genomic features with non-fusion loci.

Lai et al., BMC Genomics 2015; [Impact factor 3.729]

APCB_Shape-05 Genome-wide association study of prostate cancer-specific survival.

Szulkin et al., Cancer Epidemiol Biomarkers 2015; [Impact factor 4.125]

APCB_Shape-05 Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans.

Amin Al Olama et al., Hum Mol Genet 2015; [Impact factor 5.985]

APCB_Shape-05 Prediction of individual genetic risk to prostate cancer using a polygenic score.

Szulkin et al., Prostate 2015; [Impact factor 3.565]

APCB_Shape-05 A large-scale analysis of genetic variants with putative miRNA binding sites in prostate cancer.

Stegeman et al., Cancer Discov 2015; [Impact factor 19.453]


Publications in 2014

APCB_Shape-05 Commentary on “Identification of 23 new prostate cancer susceptibility loci using the iCOGS custom genotyping array”.

Olumi., Urol Oncol 2014; [Impact factor 3.767]

APCB_Shape-05 PTRF/cavin-1 neutralizes non-caveolar caveolin-1 microdomains in prostate cancer.

Moon et al., Oncogene 2014; [Impact factor 8.459]


Publications in 2013

APCB_Shape-05 A preclinical xenograft model identifies castration-tolerant cancer-repopulating cells in localized prostate tumors.

Toivanen et al., Sci Trans Med 2013; [Impact factor 16.796]

APCB_Shape-05 Circulating microRNAs predict biochemical recurrence in prostate cancer patients.

Selth et al., British Journal of Cancer 2013; [Impact factor 5.082]

APCB_Shape-05 A bioengineered microenvironment to quantitatively measure the tumorigenic properties of cancer-associated fibroblasts in human prostate cancer.

Clark et al., Biomaterials 2013; [Impact factor 7.404]

APCB_Shape-05 A preclinical xenograft model of prostate cancer using human tumors.

Lawrence et al.,Nat Protoc 2013; [Impact factor 9.924]

APCB_Shape-05 A meta-analysis of genome-wide association studies to identify prostate cancer susceptibility loci associated with aggressive and non-aggressive disease.

Amin Al Olama et al., Hum Mol Genet 2013; [Impact factor 7.636]

APCB_Shape-05 Identification of 23 new prostate cancer susceptibility loci using iCOGS custom genotyping array.

Eeles et al., Nat Genet 2013; [Impact factor 32.209]

APCB_Shape-05 Characterization of the prostate cancer susceptibility gene KLF6 in human and mouse prostate cancers.

Chiam et al., The Prostate 2013; [Impact factor 3.565]

APCB_Shape-05 Common variation in kallikrein genes KLK5, KLK6, KLK12, and KLK13 and risk of prostate cancer and tumor aggressiveness.

Lose et al., Urol Oncol 2013; [Impact factor 3.216]


Publications in 2012

 APCB_Shape-05 Genetic Association of the KLK4 Locus with Risk of Prostate Cancer.

Lose et al.,PLOS one 2012; [Impact factor 4.092]

APCB_Shape-05 Evidence for Efficacy of New Hsp90 Inhibitors Revealed by Ex Vivo Culture of Human Prostate Tumors.

Centenera et al.,Clin Cancer Res 2012; [Impact factor 7.742]

APCB_Shape-05 Breaking through a roadblock in prostate cancer research: An update on human model systems.

Toivanen et al., J Steroid Biochem Mol Biol 2012; [Impact factor 3.053]

APCB_Shape-05 A gene signature identified using a mouse model of androgen receptor-dependent prostate cancer predicts biochemical relapse in human disease.

Thompson et al., Int J Cancer 2012; [Impact factor 5.444]

APCB_Shape-05 Human Epithelial Basal Cells Are Cells of Origin of Prostate Cancer, Independent of CD133 Status.

Taylor et al., Stem Cells 2012; [Impact factor 7.781]

APCB_Shape-05 The kallikrein 14 gene is down-regulated by androgen receptor signalling and harbours genetic variation that is associated with prostate tumour aggressiveness.

Lose et al., Biol Chem 2012; [Impact factor 2.965]

APCB_Shape-05 Interleukin-6 promoter variants, prostate cancer risk, and survival.

Tindall et al., The Prostate 2012; [Impact factor 3.565]


Publications in 2011

APCB_Shape-05 Seven novel prostate cancer susceptibility loci identified by a multi-stage genome-wide association study.

Kote-Jarai et al., Nature Genetics 2011; [Impact factor 35.532]

APCB_Shape-05 Seven prostate cancer susceptibility loci identified by a multi-stage genome-wide association study.

Eeles et al., Nat Genet Letters 2011; [Impact factor 32.209]

APCB_Shape-05 A Replication Study Examining Novel Common Single Nucleotide Polymorphisms Identified Through a Prostate Cancer Genome-wide Association Study in a Japanese Population.

Batra et al., Am J Epidemiol 2011; [Impact factor 5.216]

APCB_Shape-05 Reactivation of Embryonic Nodal Signaling Is Associated With Tumor Progression and Promotes the Growth of Prostate Cancer Cells.

Lawrence et al., Prostate 2011; [Impact factor 3.485]


Publications in 2010

APCB_Shape-05 Kallikreins on Steroids: Structure, Function, and Hormonal Regulation of Prostate-Specific Antigen and the Extended Kallikrein Locus.

Lawrence et al., Endo Reviews 2010; [Impact factor 19.929]

APCB_Shape-05 Global Levels of Specific Histone Modifications and an Epigenetic Gene Signature Predict Prostate Cancer Progression and Development.

Bianco-Miotto et al., CEBP 2010; [Impact factor 4.123]

APCB_Shape-05 Comparative Biomarker Expression and RNA Integrity in Biospecimens Derived from Radical Retropubic and Robot-Assisted Laparoscopic Prostatectomies.

Ricciardelli et al., CEBP 2010; [Impact factor 4.123]

APCB_Shape-05 Comprehensive analysis of the cytokine-rich chromosome 5q31.1 region suggests a role for IL-4 gene variants in prostate cancer risk.

Tindall et al., Carcinogenesis 2010; [Impact factor 5.702]

APCB_Shape-05 Standard Preanalytical Coding for Biospecimens: Defining the Sample Pre-analytical Code.

Betsou et al., CEBP 2010; [Impact factor 4.123]


Publications in 2009

APCB_Shape-05 Human Biospecimen Research: Experimental Protocol and Quality Control Tools.

Betsou et al., CEBP 2009;[Impact factor 4.123]