Sir Peter MacCallum Department of Oncology - Research Publications

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    Identification of six new susceptibility loci for invasive epithelial ovarian cancer
    Kuchenbaecker, KB ; Ramus, SJ ; Tyrer, J ; Lee, A ; Shen, HC ; Beesley, J ; Lawrenson, K ; McGuffog, L ; Healey, S ; Lee, JM ; Spindler, TJ ; Lin, YG ; Pejovic, T ; Bean, Y ; Li, Q ; Coetzee, S ; Hazelett, D ; Miron, A ; Southey, M ; Terry, MB ; Goldgar, DE ; Buys, SS ; Janavicius, R ; Dorfling, CM ; van Rensburg, EJ ; Neuhausen, SL ; Ding, YC ; Hansen, TVO ; Jonson, L ; Gerdes, A-M ; Ejlertsen, B ; Barrowdale, D ; Dennis, J ; Benitez, J ; Osorio, A ; Garcia, MJ ; Komenaka, I ; Weitzel, JN ; Ganschow, P ; Peterlongo, P ; Bernard, L ; Viel, A ; Bonanni, B ; Peissel, B ; Manoukian, S ; Radice, P ; Papi, L ; Ottini, L ; Fostira, F ; Konstantopoulou, I ; Garber, J ; Frost, D ; Perkins, J ; Platte, R ; Ellis, S ; Godwin, AK ; Schmutzler, RK ; Meindl, A ; Engel, C ; Sutter, C ; Sinilnikova, OM ; Damiola, F ; Mazoyer, S ; Stoppa-Lyonnet, D ; Claes, K ; De Leeneer, K ; Kirk, J ; Rodriguez, GC ; Piedmonte, M ; O'Malley, DM ; de la Hoya, M ; Caldes, T ; Aittomaeki, K ; Nevanlinna, H ; Collee, JM ; Rookus, MA ; Oosterwijk, JC ; Tihomirova, L ; Tung, N ; Hamann, U ; Isaccs, C ; Tischkowitz, M ; Imyanitov, EN ; Caligo, MA ; Campbell, IG ; Hogervorst, FBL ; Olah, E ; Diez, O ; Blanco, I ; Brunet, J ; Lazaroso, C ; Angel Pujana, M ; Jakubowska, A ; Gronwald, J ; Lubinski, J ; Sukiennicki, G ; Barkardottir, RB ; Plante, M ; Simard, J ; Soucy, P ; Montagna, M ; Tognazzo, S ; Teixeira, MR ; Pankratz, VS ; Wang, X ; Lindor, N ; Szabo, CI ; Kauff, N ; Vijai, J ; Aghajanian, CA ; Pfeiler, G ; Berger, A ; Singer, CF ; Tea, M-K ; Phelan, CM ; Greene, MH ; Mai, PL ; Rennert, G ; Mulligan, AM ; Tchatchou, S ; Andrulis, IL ; Glendon, G ; Toland, AE ; Jensen, UB ; Kruse, TA ; Thomassen, M ; Bojesen, A ; Zidan, J ; Friedman, E ; Laitman, Y ; Soller, M ; Liljegren, A ; Arver, B ; Einbeigi, Z ; Stenmark-Askmalm, M ; Olopade, OI ; Nussbaum, RL ; Rebbeck, TR ; Nathanson, KL ; Domchek, SM ; Lu, KH ; Karlan, BY ; Walsh, C ; Lester, J ; Hein, A ; Ekici, AB ; Beckmann, MW ; Fasching, PA ; Lambrechts, D ; Van Nieuwenhuysen, E ; Vergote, I ; Lambrechts, S ; Dicks, E ; Doherty, JA ; Wicklund, KG ; Rossing, MA ; Rudolph, A ; Chang-Claude, J ; Wang-Gohrke, S ; Eilber, U ; Moysich, KB ; Odunsi, K ; Sucheston, L ; Lele, S ; Wilkens, LR ; Goodman, MT ; Thompson, PJ ; Shvetsov, YB ; Runnebaum, IB ; Duerst, M ; Hillemanns, P ; Doerk, T ; Antonenkova, N ; Bogdanova, N ; Leminen, A ; Pelttari, LM ; Butzow, R ; Modugno, F ; Kelley, JL ; Edwards, RP ; Ness, RB ; du Bois, A ; Heitz, F ; Schwaab, I ; Harter, P ; Matsuo, K ; Hosono, S ; Orsulic, S ; Jensen, A ; Kjaer, SK ; Hogdall, E ; Hasmad, HN ; Azmi, MAN ; Teo, S-H ; Woo, Y-L ; Fridley, BL ; Goode, EL ; Cunningham, JM ; Vierkant, RA ; Bruinsma, F ; Giles, GG ; Liang, D ; Hildebrandt, MAT ; Wu, X ; Levine, DA ; Bisogna, M ; Berchuck, A ; Iversen, ES ; Schildkraut, JM ; Concannon, P ; Weber, RP ; Cramer, DW ; Terry, KL ; Poole, EM ; Tworoger, SS ; Bandera, EV ; Orlow, I ; Olson, SH ; Krakstad, C ; Salvesen, HB ; Tangen, IL ; Bjorge, L ; van Altena, AM ; Aben, KKH ; Kiemeney, LA ; Massuger, LFAG ; Kellar, M ; Brooks-Wilson, A ; Kelemen, LE ; Cook, LS ; Le, ND ; Cybulski, C ; Yang, H ; Lissowska, J ; Brinton, LA ; Wentzensen, N ; Hogdall, C ; Lundvall, L ; Nedergaard, L ; Baker, H ; Song, H ; Eccles, D ; McNeish, I ; Paul, J ; Carty, K ; Siddiqui, N ; Glasspool, R ; Whittemore, AS ; Rothstein, JH ; McGuire, V ; Sieh, W ; Ji, B-T ; Zheng, W ; Shu, X-O ; Gao, Y-T ; Rosen, B ; Risch, HA ; McLaughlin, JR ; Narod, SA ; Monteiro, AN ; Chen, A ; Lin, H-Y ; Permuth-Wey, J ; Sellers, TA ; Tsai, Y-Y ; Chen, Z ; Ziogas, A ; Anton-Culver, H ; Gentry-Maharaj, A ; Menon, U ; Harrington, P ; Lee, AW ; Wu, AH ; Pearce, CL ; Coetzee, G ; Pike, MC ; Dansonka-Mieszkowska, A ; Timorek, A ; Rzepecka, IK ; Kupryjanczyk, J ; Freedman, M ; Noushmehr, H ; Easton, DF ; Offit, K ; Couch, FJ ; Gayther, S ; Pharoah, PP ; Antoniou, AC ; Chenevix-Trench, G (NATURE PORTFOLIO, 2015-02)
    Genome-wide association studies (GWAS) have identified 12 epithelial ovarian cancer (EOC) susceptibility alleles. The pattern of association at these loci is consistent in BRCA1 and BRCA2 mutation carriers who are at high risk of EOC. After imputation to 1000 Genomes Project data, we assessed associations of 11 million genetic variants with EOC risk from 15,437 cases unselected for family history and 30,845 controls and from 15,252 BRCA1 mutation carriers and 8,211 BRCA2 mutation carriers (3,096 with ovarian cancer), and we combined the results in a meta-analysis. This new study design yielded increased statistical power, leading to the discovery of six new EOC susceptibility loci. Variants at 1p36 (nearest gene, WNT4), 4q26 (SYNPO2), 9q34.2 (ABO) and 17q11.2 (ATAD5) were associated with EOC risk, and at 1p34.3 (RSPO1) and 6p22.1 (GPX6) variants were specifically associated with the serous EOC subtype, all with P < 5 × 10(-8). Incorporating these variants into risk assessment tools will improve clinical risk predictions for BRCA1 and BRCA2 mutation carriers.
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    DNA methylation in ductal carcinoma in situ of the breast
    Pang, J-MB ; Dobrovic, A ; Fox, SB (BMC, 2013)
    Ductal carcinoma in situ (DCIS) is a non-obligate precursor lesion of invasive carcinoma of the breast. Current prognostic markers based on histopathological examination are unable to accurately predict which DCIS cases will progress to invasive carcinoma or recur after surgical excision. Epigenetic changes have been shown to be a significant driver of tumorigenesis, and DNA methylation of specific gene promoters provides predictive and prognostic markers in many types of cancer, including invasive breast cancer. In general, the spectrum of genes that are methylated in DCIS strongly resembles that seen in invasive ductal carcinoma. The identification of specific prognostic markers in DCIS remains elusive and awaits additional work investigating a large panel of methylatable genes by using sensitive and reproducible technologies. This review critically appraises the role of methylation in DCIS and its use as a biomarker.
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    A multisite blinded study for the detection of BRAF mutations in formalin-fixed, paraffin-embedded malignant melanoma
    Richter, A ; Grieu, F ; Carrello, A ; Amanuel, B ; Namdarian, K ; Rynska, A ; Lucas, A ; Michael, V ; Bell, A ; Fox, SB ; Hewitt, CA ; Do, H ; McArthur, GA ; Wong, SQ ; Dobrovic, A ; Iacopetta, B (NATURE PORTFOLIO, 2013-04-15)
    Melanoma patients with BRAF mutations respond to treatment with vemurafenib, thus creating a need for accurate testing of BRAF mutation status. We carried out a blinded study to evaluate various BRAF mutation testing methodologies in the clinical setting. Formalin-fixed, paraffin-embedded melanoma samples were macrodissected before screening for mutations using Sanger sequencing, single-strand conformation analysis (SSCA), high resolution melting analysis (HRM) and competitive allele-specific TaqMan® PCR (CAST-PCR). Concordance of 100% was observed between the Sanger sequencing, SSCA and HRM techniques. CAST-PCR gave rapid and accurate results for the common V600E and V600K mutations, however additional assays are required to detect rarer BRAF mutation types found in 3-4% of melanomas. HRM and SSCA followed by Sanger sequencing are effective two-step strategies for the detection of BRAF mutations in the clinical setting. CAST-PCR was useful for samples with low tumour purity and may also be a cost-effective and robust method for routine diagnostics.
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    Quantitative threefold allele-specific PCR (QuanTAS-PCR) for highly sensitive JAK2 V617F mutant allele detection
    Zapparoli, GV ; Jorissen, RN ; Hewitt, CA ; McBean, M ; Westerman, DA ; Dobrovic, A (BMC, 2013-04-24)
    BACKGROUND: The JAK2 V617F mutation is the most frequent somatic change in myeloproliferative neoplasms, making it an important tumour-specific marker for diagnostic purposes and for the detection of minimal residual disease. Sensitive quantitative assays are required for both applications, particularly for the monitoring of minimal residual disease, which requires not only high sensitivity but also very high specificity. METHODS: We developed a highly sensitive probe-free quantitative mutant-allele detection method, Quantitative Threefold Allele-Specific PCR (QuanTAS-PCR), that is performed in a closed-tube system, thus eliminating the manipulation of PCR products. QuantTAS-PCR uses a threefold approach to ensure allele-specific amplification of the mutant sequence: (i) a mutant allele-specific primer, (ii) a 3'dideoxy blocker to suppress false-positive amplification from the wild-type template and (iii) a PCR specificity enhancer, also to suppress false-positive amplification from the wild-type template. Mutant alleles were quantified relative to exon 9 of JAK2. RESULTS: We showed that the addition of the 3'dideoxy blocker suppressed but did not eliminate false-positive amplification from the wild-type template. However, the addition of the PCR specificity enhancer near eliminated false-positive amplification from the wild-type allele. Further discrimination between true and false positives was enabled by using the quantification cycle (Cq) value of a single mutant template as a cut-off point, thus enabling robust distinction between true and false positives. As 10,000 JAK2 templates were used per replicate, the assay had a sensitivity of 1/10(-4) per replicate. Greater sensitivity could be reached by increasing the number of replicates analysed. Variation in replicates when low mutant-allele templates were present necessitated the use of a statistics-based approach to estimate the load of mutant JAK2 copies. QuanTAS-PCR showed comparable quantitative results when validated against a commercial assay. CONCLUSIONS: QuanTAS-PCR is a simple, cost-efficient, closed-tube method for JAK2 V617F mutation quantification that can detect very low levels of the mutant allele, thus enabling analysis of minimal residual disease. The approach can be extended to the detection of other recurrent single nucleotide somatic changes in cancer.
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    Targeted-capture massively-parallel sequencing enables robust detection of clinically informative mutations from formalin-fixed tumours
    Wong, SQ ; Li, J ; Salemi, R ; Sheppard, KE ; Do, H ; Tothill, RW ; McArthur, GA ; Dobrovic, A (NATURE PORTFOLIO, 2013-12-13)
    Massively parallel sequencing offers the ability to interrogate a tumour biopsy for multiple mutational changes. For clinical samples, methodologies must enable maximal extraction of available sequence information from formalin-fixed and paraffin-embedded (FFPE) material. We assessed the use of targeted capture for mutation detection in FFPE DNA. The capture probes targeted the coding region of all known kinase genes and selected oncogenes and tumour suppressor genes. Seven melanoma cell lines and matching FFPE xenograft DNAs were sequenced. An informatics pipeline was developed to identify variants and contaminating mouse reads. Concordance of 100% was observed between unfixed and formalin-fixed for reported COSMIC variants including BRAF V600E. mutations in genes not conventionally screened including ERBB4, ATM, STK11 and CDKN2A were readily detected. All regions were adequately covered with independent reads regardless of GC content. This study indicates that hybridisation capture is a robust approach for massively parallel sequencing of FFPE samples.
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    Mutational profiling of familial male breast cancers reveals similarities with luminal A female breast cancer with rare TP53 mutations
    Deb, S ; Wong, SQ ; Li, J ; Do, H ; Weiss, J ; Byrne, D ; Chakrabarti, A ; Bosma, T ; Fellowes, A ; Dobrovic, A ; Fox, SB (NATURE PUBLISHING GROUP, 2014-12-09)
    BACKGROUND: Male breast cancer (MBC) is still poorly understood with a large proportion arising in families with a history of breast cancer. Genomic studies have focused on germline determinants of MBC risk, with minimal knowledge of somatic changes in these cancers. METHODS: Using a TruSeq amplicon cancer panel, this study evaluated 48 familial MBCs (3 BRCA1 germline mutant, 17 BRCA2 germline mutant and 28 BRCAX) for hotspot somatic mutations and copy number changes in 48 common cancer genes. RESULTS: Twelve missense mutations included nine PIK3CA mutations (seven in BRCAX patients), two TP53 mutations (both in BRCA2 patients) and one PTEN mutation. Common gains were seen in GNAS (34.1%) and losses were seen in GNAQ (36.4%), ABL1 (47.7%) and ATM (34.1%). Gains of HRAS (37.5% vs 3%, P=0.006), STK11 (25.0% vs 0%, P=0.01) and SMARCB1 (18.8% vs 0%, P=0.04) and the loss of RB1 (43.8% vs 13%, P=0.03) were specific to BRCA2 tumours. CONCLUSIONS: This study is the first to perform high-throughput somatic sequencing on familial MBCs. Overall, PIK3CA mutations are most commonly seen, with fewer TP53 and PTEN mutations, similar to the profile seen in luminal A female breast cancers. Differences in mutation profiles and patterns of gene gains/losses are seen between BRCA2 (associated with TP53/PTEN mutations, loss of RB1 and gain of HRAS, STK11 and SMARCB1) and BRCAX (associated with PIK3CA mutations) tumours, suggesting that BRCA2 and BRCAX MBCs may be distinct and arise from different tumour pathways. This has implications on potential therapies, depending on the BRCA status of MBC patients.
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    A critical re-assessment of DNA repair gene promoter methylation in non-small cell lung carcinoma
    Do, H ; Wong, NC ; Murone, C ; John, T ; Solomon, B ; Mitchell, PL ; Dobrovic, A (NATURE PORTFOLIO, 2014-02-26)
    DNA repair genes that have been inactivated by promoter methylation offer potential therapeutic targets either by targeting the specific repair deficiency, or by synthetic lethal approaches. This study evaluated promoter methylation status for eight selected DNA repair genes (ATM, BRCA1, ERCC1, MGMT, MLH1, NEIL1, RAD23B and XPC) in 56 non-small cell lung cancer (NSCLC) tumours and 11 lung cell lines using the methylation-sensitive high resolution melting (MS-HRM) methodology. Frequent methylation in NEIL1 (42%) and infrequent methylation in ERCC1 (2%) and RAD23B (2%) are reported for the first time in NSCLC. MGMT methylation was detected in 13% of the NSCLCs. Contrary to previous studies, methylation was not detected in ATM, BRCA1, MLH1 and XPC. Data from The Cancer Genome Atlas (TCGA) was consistent with these findings. The study emphasises the importance of using appropriate methodology for accurate assessment of promoter methylation.
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    Methylation profiling of ductal carcinoma in situ and its relationship to histopathological features
    Pang, J-MB ; Deb, S ; Takano, EA ; Byrne, DJ ; Jene, N ; Boulghourjian, A ; Holliday, A ; Millar, E ; Lee, CS ; O'Toole, SA ; Dobrovic, A ; Fox, SB (BMC, 2014)
    INTRODUCTION: DNA methylation is a well-studied biomarker in invasive breast cancer, but its role in ductal carcinoma in situ (DCIS) is less well characterized. The aims of this study are to assess the methylation profile in DCIS for a panel of well-characterized genes that are frequently methylated in breast cancer, to investigate the relationship of methylation with pathological features, and to perform a proof-of-principle study to evaluate the practicality of methylation as a biomarker in diagnostic DCIS material. METHODS: Promoter CpG island methylation for a panel of 11 breast cancer-related genes was performed by methylation-sensitive high resolution melting (MS-HRM). Formalin-fixed, paraffin-embedded (FFPE) biopsies from 72 samples of pure DCIS (DCIS occurring in the absence of synchronous invasive carcinoma), 10 samples of mixed DCIS (DCIS adjacent to invasive carcinoma), and 18 samples of normal breast epithelium adjacent to a DCIS lesion were micro-dissected prior to DNA extraction. RESULTS: Methylation was seen for all the tested genes except BRCA1. RASSF1A was the most frequently methylated gene (90% of DCIS samples) and its methylation was associated with comedo necrosis (p = 0.018). Cluster analysis based on the methylation profile revealed four groups, the highly methylated cluster being significantly associated with high nuclear grade, HER2 amplification, negative estrogen receptor (ER) α status, and negative progesterone receptor (PgR) status, (p = 0.038, p = 0.018, p <0.001, p = 0.001, respectively). Methylation of APC (p = 0.017), CDH13 (p = 0.017), and RARβ (p <0.001) was associated with negative ERα status. Methylation of CDH13 (p <0.001), and RARβ (p = 0.001) was associated with negative PgR status. Methylation of APC (p = 0.013) and CDH13 (p = 0.026) was associated with high nuclear grade. Methylation of CDH13 (p = 0.009), and RARβ (p = 0.042) was associated with HER2-amplification. CONCLUSIONS: DNA methylation can be assessed in FFPE-derived samples using suitable methodologies. Methylation of a panel of genes that are known to be methylated in invasive breast cancer was able to classify DCIS into distinct groups and was differentially associated with phenotypic features in DCIS.
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    Exemplary multiplex bisulfite amplicon data used to demonstrate the utility of Methpat
    Wong, NC ; Pope, BJ ; Candiloro, I ; Korbie, D ; Trau, M ; Wong, SQ ; Mikeska, T ; van Denderen, BJW ; Thompson, EW ; Eggers, S ; Doyle, SR ; Dobrovic, A (OXFORD UNIV PRESS, 2015-11-26)
    BACKGROUND: DNA methylation is a complex epigenetic marker that can be analyzed using a wide variety of methods. Interpretation and visualization of DNA methylation data can mask complexity in terms of methylation status at each CpG site, cellular heterogeneity of samples and allelic DNA methylation patterns within a given DNA strand. Bisulfite sequencing is considered the gold standard, but visualization of massively parallel sequencing results remains a significant challenge. FINDINGS: We created a program called Methpat that facilitates visualization and interpretation of bisulfite sequencing data generated by massively parallel sequencing. To demonstrate this, we performed multiplex PCR that targeted 48 regions of interest across 86 human samples. The regions selected included known gene promoters associated with cancer, repetitive elements, known imprinted regions and mitochondrial genomic sequences. We interrogated a range of samples including human cell lines, primary tumours and primary tissue samples. Methpat generates two forms of output: a tab-delimited text file for each sample that summarizes DNA methylation patterns and their read counts for each amplicon, and a HTML file that summarizes this data visually. Methpat can be used with publicly available whole genome bisulfite sequencing and reduced representation bisulfite sequencing datasets with sufficient read depths. CONCLUSIONS: Using Methpat, complex DNA methylation data derived from massively parallel sequencing can be summarized and visualized for biological interpretation. By accounting for allelic DNA methylation states and their abundance in a sample, Methpat can unmask the complexity of DNA methylation and yield further biological insight in existing datasets.
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    Sequence artefacts in a prospective series of formalin-fixed tumours tested for mutations in hotspot regions by massively parallel sequencing
    Wong, SQ ; Li, J ; Tan, AY-C ; Vedururu, R ; Pang, J-MB ; Do, H ; Ellul, J ; Doig, K ; Bell, A ; McArthur, GA ; Fox, SB ; Thomas, DM ; Fellowes, A ; Parisot, JP ; Dobrovic, A (BMC, 2014-05-13)
    BACKGROUND: Clinical specimens undergoing diagnostic molecular pathology testing are fixed in formalin due to the necessity for detailed morphological assessment. However, formalin fixation can cause major issues with molecular testing, as it causes DNA damage such as fragmentation and non-reproducible sequencing artefacts after PCR amplification. In the context of massively parallel sequencing (MPS), distinguishing true low frequency variants from sequencing artefacts remains challenging. The prevalence of formalin-induced DNA damage and its impact on molecular testing and clinical genomics remains poorly understood. METHODS: The Cancer 2015 study is a population-based cancer cohort used to assess the feasibility of mutational screening using MPS in cancer patients from Victoria, Australia. While blocks were formalin-fixed and paraffin-embedded in different anatomical pathology laboratories, they were centrally extracted for DNA utilising the same protocol, and run through the same MPS platform (Illumina TruSeq Amplicon Cancer Panel). The sequencing artefacts in the 1-10% and the 10-25% allele frequency ranges were assessed in 488 formalin-fixed tumours from the pilot phase of the Cancer 2015 cohort. All blocks were less than 2.5 years of age (mean 93 days). RESULTS: Consistent with the signature of DNA damage due to formalin fixation, many formalin-fixed samples displayed disproportionate levels of C>T/G>A changes in the 1-10% allele frequency range. Artefacts were less apparent in the 10-25% allele frequency range. Significantly, changes were inversely correlated with coverage indicating high levels of sequencing artefacts were associated with samples with low amounts of available amplifiable template due to fragmentation. The degree of fragmentation and sequencing artefacts differed between blocks sourced from different anatomical pathology laboratories. In a limited validation of potentially actionable low frequency mutations, a NRAS G12D mutation in a melanoma was shown to be a false positive. CONCLUSIONS: These findings indicate that DNA damage following formalin fixation remains a major challenge in laboratories working with MPS. Methodologies that assess, minimise or remove formalin-induced DNA damaged templates as part of MPS protocols will aid in the interpretation of genomic results leading to better patient outcomes.