Sir Peter MacCallum Department of Oncology - Research Publications
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ItemMolecular comparison of interval and screen-detected breast cancers(WILEY, 2019-06)
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ItemAn analysis of a multiple biomarker panel to better predict prostate cancer metastasis after radical prostatectomy(WILEY, 2019-03-01)A plethora of individual candidate biomarkers for predicting biochemical relapse in localized prostate cancer (PCa) have been proposed. Combined biomarkers may improve prognostication, and ensuring validation against more clinically relevant endpoints are required. The Australian PCa Research Centre NSW has contributed to numerous studies of molecular biomarkers associated with biochemical relapse. In the current study, these biomarkers were re-analyzed for biochemical relapse, metastatic relapse and PCa death with extended follow-up. Biomarkers of significance were then used to develop a combined prognostic model for clinical outcomes and validated in a large independent cohort. The discovery cohort (n = 324) was based on 12 biomarkers with a median follow-up of 16 years. Seven biomarkers were significantly associated with biochemical relapse. Three biomarkers were associated with metastases: AZGP1, Ki67 and PML. Only AZGP1 was associated with PCa death. In their individual and combinational forms, AZGP1 and Ki67 as a dual BM signature was the most robust predictor of metastatic relapse (AUC 0.762). The AZPG1 and Ki67 signature was validated in an independent cohort of 347 PCa patients. The dual BM signature of AZGP1 and Ki67 predicted metastasis in the univariable (HR 7.2, 95% CI, 1.6-32; p = 0.01) and multivariable analysis (HR 5.4, 95% CI, 1.2-25; p = 0.03). The dual biomarker signature marginally improved risk prediction compared to AZGP1 alone (AUC 0.758 versus 0.738, p < 0.001). Our findings indicate that biochemical relapse is not an adequate surrogate for metastasis or PCa death. The dual biomarker signature of AZGP1 and Ki67 offers a small benefit in predicting metastasis over AZGP1 alone.
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ItemDevelopment and validation of a targeted gene sequencing panel for application to disparate cancers(Nature Publishing Group, 2019-11-19)Next generation sequencing has revolutionised genomic studies of cancer, having facilitated the development of precision oncology treatments based on a tumour's molecular profile. We aimed to develop a targeted gene sequencing panel for application to disparate cancer types with particular focus on tumours of the head and neck, plus test for utility in liquid biopsy. The final panel designed through Roche/Nimblegen combined 451 cancer-associated genes (2.01 Mb target region). 136 patient DNA samples were collected for performance and application testing. Panel sensitivity and precision were measured using well-characterised DNA controls (n = 47), and specificity by Sanger sequencing of the Aryl Hydrocarbon Receptor Interacting Protein (AIP) gene in 89 patients. Assessment of liquid biopsy application employed a pool of synthetic circulating tumour DNA (ctDNA). Library preparation and sequencing were conducted on Illumina-based platforms prior to analysis with our accredited (ISO15189) bioinformatics pipeline. We achieved a mean coverage of 395x, with sensitivity and specificity of >99% and precision of >97%. Liquid biopsy revealed detection to 1.25% variant allele frequency. Application to head and neck tumours/cancers resulted in detection of mutations aligned to published databases. In conclusion, we have developed an analytically-validated panel for application to cancers of disparate types with utility in liquid biopsy.
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ItemE6AP Promotes a Metastatic Phenotype in Prostate Cancer(CELL PRESS, 2019-12-20)Although primary prostate cancer is largely curable, progression to metastatic disease is associated with very poor prognosis. E6AP is an E3 ubiquitin ligase and a transcriptional co-factor involved in normal prostate development. E6AP drives prostate cancer when overexpressed. Our study exposed a role for E6AP in the promotion of metastatic phenotype in prostate cells. We revealed that elevated levels of E6AP in primary prostate cancer correlate with regional metastasis and demonstrated that E6AP promotes acquisition of mesenchymal features, migration potential, and ability for anchorage-independent growth. We identified the metastasis suppressor NDRG1 as a target of E6AP and showed it is key in E6AP induction of mesenchymal phenotype. We showed that treatment of prostate cancer cells with pharmacological agents upregulated NDRG1 expression suppressed E6AP-induced cell migration. We propose that the E6AP-NDRG1 axis is an attractive therapeutic target for the treatment of E6AP-driven metastatic prostate cancer.
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ItemThe FANCM:p.Arg658* truncating variant is associated with risk of triple-negative breast cancer(Springer Nature, 2019-11-01)Breast cancer is a common disease partially caused by genetic risk factors. Germline pathogenic variants in DNA repair genes BRCA1, BRCA2, PALB2, ATM, and CHEK2 are associated with breast cancer risk. FANCM, which encodes for a DNA translocase, has been proposed as a breast cancer predisposition gene, with greater effects for the ER-negative and triple-negative breast cancer (TNBC) subtypes. We tested the three recurrent protein-truncating variants FANCM:p.Arg658*, p.Gln1701*, and p.Arg1931* for association with breast cancer risk in 67,112 cases, 53,766 controls, and 26,662 carriers of pathogenic variants of BRCA1 or BRCA2. These three variants were also studied functionally by measuring survival and chromosome fragility in FANCM−/− patient-derived immortalized fibroblasts treated with diepoxybutane or olaparib. We observed that FANCM:p.Arg658* was associated with increased risk of ER-negative disease and TNBC (OR = 2.44, P = 0.034 and OR = 3.79; P = 0.009, respectively). In a country-restricted analysis, we confirmed the associations detected for FANCM:p.Arg658* and found that also FANCM:p.Arg1931* was associated with ER-negative breast cancer risk (OR = 1.96; P = 0.006). The functional results indicated that all three variants were deleterious affecting cell survival and chromosome stability with FANCM:p.Arg658* causing more severe phenotypes. In conclusion, we confirmed that the two rare FANCM deleterious variants p.Arg658* and p.Arg1931* are risk factors for ER-negative and TNBC subtypes. Overall our data suggest that the effect of truncating variants on breast cancer risk may depend on their position in the gene. Cell sensitivity to olaparib exposure, identifies a possible therapeutic option to treat FANCM-associated tumors.
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ItemCNspector: a web-based tool for visualisation and clinical diagnosis of copy number variation from next generation sequencing(Nature Publishing Group, 2019-04-23)Next Generation Sequencing is now routinely used in the practice of diagnostic pathology to detect clinically relevant somatic and germline sequence variations in patient samples. However, clinical assessment of copy number variations (CNVs) and large-scale structural variations (SVs) is still challenging. While tools exist to estimate both, their results are typically presented separately in tables or static plots which can be difficult to read and are unable to show the context needed for clinical interpretation and reporting. We have addressed this problem with CNspector, a multi-scale interactive browser that shows CNVs in the context of other relevant genomic features to enable fast and effective clinical reporting. We illustrate the utility of CNspector at different genomic scales across a variety of sample types in a range of case studies. We show how CNspector can be used for diagnosis and reporting of exon-level deletions, focal gene-level amplifications, chromosome and chromosome arm level amplifications/deletions and in complex genomic rearrangements. CNspector is a web-based clinical variant browser tailored to the clinical application of next generation sequencing for CNV assessment. We have demonstrated the utility of this interactive software in typical applications across a range of tissue types and disease contexts encountered in the context of diagnostic pathology. CNspector is written in R and the source code is available for download under the GPL3 Licence from https://github.com/PapenfussLab/CNspector. A server running CNspector loaded with the figures from this paper can be accessed at https://shiny.wehi.edu.au/jmarkham/CNspector/index.html.