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Background: Substantial research effort has been directed towards identifying gene amplification events during cancer development, with the view that these represent promising therapeutic targets or otherwise highlight pathways for therapeutic intervention. We considered whether datasets generated by recent large-scale pharmacogenomic studies (1, 2) could be mined to uncover novel associations between amplification status at particular genes of interest and cell line chemo-sensitivity or -resistance. As a case study, we examined the known amplification targets, ERBB2 and MYC, as well as a candidate amplification target, TPD52. Experimental procedures: We accessed and curated datasets from the Cancer Cell Line Encyclopedia (1) and Cancer Therapeutics Response Portal (2). Multivariate linear regression modelling was performed to determine whether cell lines from diverse cancer types displayed differential responses to the same compound according to their gene copy number at ERBB2, MYC and TPD52. Associations between drug response and gene expression of ERBB2, MYC and TPD52 were also modelled to ascertain whether these recapitulated the gene-drug associations predicted by copy number. Both models were adjusted for cell lineage as a potential confounder by performing agglomerative hierarchical clustering of cell lines into 5 groups based on the 500 most highly varying genes. For each drug, chemo-sensitivity measures were discretised into three categories (resistant, intermediate and sensitive) using the waterfall method (1). Results: Predictive modelling was possible for 24 drugs across 487 cell lines (1) and for an additional 323 drugs across 230 cell lines (2). Multivariate linear regression yielded 82 significant associations (p Conclusions: We have applied predictive models to data from large-scale pharmacogenomic studies (1, 2) to detect both known and novel associations between gene amplification status and cell line chemo-sensitivity or -resistance. Such analyses have the potential to link existing anti-cancer drugs with specific gene amplifications, which may then be applied as new biomarkers to predict efficacy. References: (1) Barretina et al 2012 Nature 483, 603 (2) Basu et al 2013 Cell 154, 1151 Citation Format: Sarah Frost, Erdahl Teber, Jennifer A. Byrne. Predictive modeling to identify novel associations between gene amplification status and cancer cell line chemosensitivity. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A2-37.

Gains in the long arm of chromosome 8 (8q) are believed to be associated with poor outcome and the development of hormone-refractory prostate cancer. Based on a meta-analysis of gene expression microarray data from multiple prostate cancer studies (D. R. Rhodes et al., Cancer Res 2002;62:4427–33), a candidate oncogene, Tumor Protein D52 (TPD52), was identified in the 8q21 amplicon. TPD52 is a coiled-coil motif-bearing protein, potentially involved in vesicle trafficking. Both mRNA and protein levels of TPD52 were highly elevated in prostate cancer tissues. Array comparative genomic hybridization and amplification analysis using single nucleotide polymorphism arrays demonstrated increased DNA copy number in the region encompassing TPD52. Fluorescence in situ hybridization on tissue microarrays confirmed TPD52 amplification in prostate cancer epithelia. Furthermore, our studies suggest that TPD52 protein levels may be regulated by androgens, consistent with the presence of androgen response elements in the upstream promoter of TPD52. In summary, these findings suggest that dysregulation of TPD52 by genomic amplification and androgen induction may play a role in prostate cancer progression.

Introduction: Neuroblastoma (NB) is the most common extracranial solid tumor of infants. We constructed a tissue microarray (TMA) including 47 diagnostic NB cases and performed immunohistochemical (IHC) staining for a number of biomarkers. Differential IHC staining was identified between duplicate tissue cores for a proportion of NB cases. Differential IHC staining occurs frequently in cancer specimens, and can be due to technical factors, tissue artefacts, or underlying biological differences between tumor sub-regions. As laser capture microdissection (LCM) allows isolation of cells from formalin-fixed paraffin-embedded (FFPE) tissue slides, we applied LCM to FFPE NB samples, to investigate the basis of differential IHC staining. Material and Methods: NSE, NB84, ALK, TPD52 and MGMT proteins were detected within diagnostic NB TMA cores and whole NB sections using IHC. Cells were isolated from FFPE sections using LCM, and genomic DNA was extracted using the QIAamp DNA FFPE Tissue Kit. Extracted genomic DNA was quantified using a Nanodrop spectrophotometer, and DNA quality was assessed by a Bioanalyzer 2100. All DNA samples were tested using PCR with TPD52 and ALK primers. Results including clinical and sample variables were analysed using SPSS version 19. Results: Of 47 NB cases within the TMA, 35 cases were represented by duplicate tissue cores, whereas the remaining 12 cases were represented by single cores. IHC analysis of 5 biomarkers showed visually different IHC staining in tumour tissue between duplicate tissue cores in 15/35 (43%) cases. Whole tissue sections from 6 of these 15 cases were then examined, which reproduced differential IHC staining. Isolation of NB cells by LCM was successfully performed after substantial optimisation. A total of 14 regions from 8 NB cases were microdissected, producing DNA yields ranging from 0.12 - 4.05 pg/ µm2 tissue. There were no significant associations between total yields of extracted DNA, and microdissected tissue areas, or tissue sample ages. All DNA samples were successfully amplified by TPD52 but not by ALK PCR primers. Conclusions: Genomic DNA can be reliably extracted from microdissected FFPE NB tissues, although only one of 2 genes could be successfully PCR amplified. Downstream assays of DNA extracted from FFPE samples may therefore have particular design requirements. Further application of this approach may help improve our understanding of the level of tumour heterogeneity present in NB samples at diagnosis. Citation Format: Le M. Thwe, Laurence C. Cantrill, Daniel R. Catchpoole, Loretta Lau, Jennifer A. Byrne. Extraction and analysis of genomic DNA from formalin-fixed paraffin-embedded neuroblastoma samples following laser capture microdissection. [abstract]. In: Proceedings of the AACR Special Conference on Pediatric Cancer at the Crossroads: Translating Discovery into Improved Outcomes; Nov 3-6, 2013; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2013;74(20 Suppl):Abstract nr B51.

Background: Tumor protein D52 (D52) overexpression is characteristic of both adult and childhood cancers and has been associated with reduced overall survival in breast cancer patients and an increase in proliferation and metastatic capacity of transfected cell lines. However, little is known about the mechanism(s) by which D52 overexpression contributes to cellular transformation or tumour progression. Aims: We aimed to identify genes which are differentially expressed in response to D52 expression in 3T3 fibroblasts, and to use these gene expression changes to predict cellular phenotypes which are altered by D52 expression. Methods: Gene expression profiling was performed using Affymetrix expression microarray analysis. Up- and down-regulated gene lists were analysed using GOSTAT, Metacore and literature searches. Differential expression of candidate proteins were validated using Western blot analysis of intracellular protein extracts or precipitates from conditioned media. Migration and invasion assays were performed using Boyden chambers. Results: D52 expression was associated with over 300 genes being differentially expressed at least two-fold relative to vector controls. A number of overexpressed genes were found to be normally involved in the inflammatory response. We focused on validating candidates such as COX-2, MMP-2 and Osteopontin as being overexpressed in D52-transfected cells relative to vector controls. We also confirmed an upregulation of phospho-AKT in D52 expressing cells, as reported by others. GOSTAT analysis revealed that gene ontology terms related to the extracellular matrix (ECM) were most over-represented amongst differentially expressed genes. The implied resultant ECM re-modelling was examined through migration and invasion assays, in which D52 expressing cells showed a significantly increased migratory and invasive capacity relative to vector control lines. Conclusions: These results implicate D52 as a pro-inflammatory intermediate, whose expression may act to drive cancer progression via an increase in phospho-AKT, followed by the production of inflammatory molecules such as Osteopontin. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2338.