Sir Peter MacCallum Department of Oncology - Research Publications
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ItemDistress and unmet needs during treatment and quality of life in early cancer survivorship: A longitudinal study of haematological cancer patients(WILEY, 2017-11)OBJECTIVE: To examine the influence of anxiety, depression and unmet supportive care needs on future quality of life (QoL) in multiple myeloma (MM) and diffuse large B-cell lymphoma (DLBCL) patients. METHODS: Multiple myeloma and DLBCL patients recruited through the population-based Victorian Cancer Registry. Data were collected through two telephone interviews: (T1) on average 7 months postdiagnosis, (T2) average 8 months later. QoL was examined at T2 using the Functional Assessment of Cancer Therapy (FACT-G) scale. The Hospital Anxiety and Depression Scale measured anxiety and depression, and the Supportive Care Needs Survey measured unmet needs at T1. Multivariate linear regression examined associations between QoL subscales (physical, emotional, social and functional well-being and overall QoL) and T1 anxiety, depression and unmet needs. RESULTS: Except physical well-being, all other QoL subscales and overall QoL were significantly associated with T1 anxiety. All QoL subscales and overall QoL were significantly associated with T1 depression. Only patient care needs were associated with physical and social well-being and overall QoL. CONCLUSION: Anxiety, depression and patient care unmet needs during treatment are associated with diminished physical and emotional well-being in the following months. Psychological distress and unmet supportive care needs experienced during treatment should be addressed to maximise future QoL.
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ItemTrends in the surgical management of stage 1 renal cell carcinoma: findings from a population-based study(WILEY, 2017-11)OBJECTIVES: To determine whether the use of nephron-sparing surgery (NSS) for treatment of stage 1 renal cell carcinoma (RCC) changed between 2009 and the end of 2013 in Australia. PATIENTS AND METHODS: All adult cases of RCC diagnosed in 2009, 2012 and 2013 were identified through the population-based Victorian Cancer Registry. For each identified patient, trained data-abstractors attended treating hospitals or clinician rooms to extract tumour and treatment data through medical record review. Multivariable logistic regression analyses were carried out to examine the significance of change in use of NSS over time, after adjusting for potential confounders. RESULTS: A total of 1 836 patients with RCC were identified. Of these, the proportion of cases with stage 1 tumours was 64% in 2009, 66% in 2012 and 69% in 2013. For T1a tumours, the proportion of patients residing in metropolitan areas receiving NSS increased from 43% in 2009 to 58% in 2012 (P < 0.05), and 69% in 2013 (P < 0.05). For patients residing in non-metropolitan areas, the proportion receiving NSS increased from 27% in 2009 to 49% in 2012, and 61% in 2013 (P < 0.01). Univariable logistic regression showed patients with moderate (odds ratio [OR] 0.57, 95% confidence interval [CI] 0.35-0.94) or severe comorbidities (OR 0.58, 95% CI 0.33-0.99), residing in non-metropolitan areas (OR 0.65, 95% CI 0.47-0.90), were less likely to be treated by NSS, while those attending high-volume hospitals (≥30 cases/year: OR 1.79, 95% CI 1.21-2.65) and those with higher socio-economic status (OR 1.45, 95% CI 1.02-2.07) were more likely to be treated by NSS. In multivariable analyses, patients with T1a tumours in 2012 (OR 2.00, 95% CI 1.34-2.97) and 2013 (OR 3.15, 95% CI 2.13-4.68) were more likely to be treated by NSS than those in 2009. For T1b tumours, use of NSS increased from 8% in 2009 to 20% in 2013 (P < 0.05). CONCLUSION: This population-based study of the management of T1 renal tumours in Australia found that the use of NSS increased over the period 2009 to 2013. Between 2009 and 2013 clinical practice for the treatment of small renal tumours in Australia has increasingly conformed to international guidelines.
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ItemBenign breast disease increases breast cancer risk independent of underlying familial risk profile: Findings from a Prospective Family Study Cohort(WILEY, 2019-07-15)Benign breast disease (BBD) is an established breast cancer (BC) risk factor, but it is unclear whether the magnitude of the association applies to women at familial or genetic risk. This information is needed to improve BC risk assessment in clinical settings. Using the Prospective Family Study Cohort, we used Cox proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of BBD with BC risk. We also examined whether the association with BBD differed by underlying familial risk profile (FRP), calculated using absolute risk estimates from the Breast Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) model. During 176,756 person-years of follow-up (median: 10.9 years, maximum: 23.7) of 17,154 women unaffected with BC at baseline, we observed 968 incident cases of BC. A total of 4,704 (27%) women reported a history of BBD diagnosis at baseline. A history of BBD was associated with a greater risk of BC: HR = 1.31 (95% CI: 1.14-1.50), and did not differ by underlying FRP, with HRs of 1.35 (95% CI: 1.11-1.65), 1.26 (95% CI: 1.00-1.60), and 1.40 (95% CI: 1.01-1.93), for categories of full-lifetime BOADICEA score <20%, 20 to <35%, ≥35%, respectively. There was no difference in the association for women with BRCA1 mutations (HR: 1.64; 95% CI: 1.04-2.58), women with BRCA2 mutations (HR: 1.34; 95% CI: 0.78-2.3) or for women without a known BRCA1 or BRCA2 mutation (HR: 1.31; 95% CI: 1.13-1.53) (pinteraction = 0.95). Women with a history of BBD have an increased risk of BC that is independent of, and multiplies, their underlying familial and genetic risk.
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Itemrs495139 in the TYMS-ENOSF1 Region and Risk of Ovarian Carcinoma of Mucinous Histology(MDPI, 2018-09)Thymidylate synthase (TYMS) is a crucial enzyme for DNA synthesis. TYMS expression is regulated by its antisense mRNA, ENOSF1. Disrupted regulation may promote uncontrolled DNA synthesis and tumor growth. We sought to replicate our previously reported association between rs495139 in the TYMS-ENOSF1 3' gene region and increased risk of mucinous ovarian carcinoma (MOC) in an independent sample. Genotypes from 24,351 controls to 15,000 women with invasive OC, including 665 MOC, were available. We estimated per-allele odds ratios (OR) and 95% confidence intervals (CI) using unconditional logistic regression, and meta-analysis when combining these data with our previous report. The association between rs495139 and MOC was not significant in the independent sample (OR = 1.09; 95% CI = 0.97⁻1.22; p = 0.15; N = 665 cases). Meta-analysis suggested a weak association (OR = 1.13; 95% CI = 1.03⁻1.24; p = 0.01; N = 1019 cases). No significant association with risk of other OC histologic types was observed (p = 0.05 for tumor heterogeneity). In expression quantitative trait locus (eQTL) analysis, the rs495139 allele was positively associated with ENOSF1 mRNA expression in normal tissues of the gastrointestinal system, particularly esophageal mucosa (r = 0.51, p = 1.7 × 10-28), and nonsignificantly in five MOC tumors. The association results, along with inconclusive tumor eQTL findings, suggest that a true effect of rs495139 might be small.
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ItemBody mass index and breast cancer survival: a Mendelian randomization analysis(OXFORD UNIV PRESS, 2017-12)BACKGROUND: There is increasing evidence that elevated body mass index (BMI) is associated with reduced survival for women with breast cancer. However, the underlying reasons remain unclear. We conducted a Mendelian randomization analysis to investigate a possible causal role of BMI in survival from breast cancer. METHODS: We used individual-level data from six large breast cancer case-cohorts including a total of 36 210 individuals (2475 events) of European ancestry. We created a BMI genetic risk score (GRS) based on genotypes at 94 known BMI-associated genetic variants. Association between the BMI genetic score and breast cancer survival was analysed by Cox regression for each study separately. Study-specific hazard ratios were pooled using fixed-effect meta-analysis. RESULTS: BMI genetic score was found to be associated with reduced breast cancer-specific survival for estrogen receptor (ER)-positive cases [hazard ratio (HR) = 1.11, per one-unit increment of GRS, 95% confidence interval (CI) 1.01-1.22, P = 0.03). We observed no association for ER-negative cases (HR = 1.00, per one-unit increment of GRS, 95% CI 0.89-1.13, P = 0.95). CONCLUSIONS: Our findings suggest a causal effect of increased BMI on reduced breast cancer survival for ER-positive breast cancer. There is no evidence of a causal effect of higher BMI on survival for ER-negative breast cancer cases.
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ItemAdult height is associated with increased risk of ovarian cancer: a Mendelian randomisation study(NATURE PUBLISHING GROUP, 2018-04)BACKGROUND: Observational studies suggest greater height is associated with increased ovarian cancer risk, but cannot exclude bias and/or confounding as explanations for this. Mendelian randomisation (MR) can provide evidence which may be less prone to bias. METHODS: We pooled data from 39 Ovarian Cancer Association Consortium studies (16,395 cases; 23,003 controls). We applied two-stage predictor-substitution MR, using a weighted genetic risk score combining 609 single-nucleotide polymorphisms. Study-specific odds ratios (OR) and 95% confidence intervals (CI) for the association between genetically predicted height and risk were pooled using random-effects meta-analysis. RESULTS: Greater genetically predicted height was associated with increased ovarian cancer risk overall (pooled-OR (pOR) = 1.06; 95% CI: 1.01-1.11 per 5 cm increase in height), and separately for invasive (pOR = 1.06; 95% CI: 1.01-1.11) and borderline (pOR = 1.15; 95% CI: 1.02-1.29) tumours. CONCLUSIONS: Women with a genetic propensity to being taller have increased risk of ovarian cancer. This suggests genes influencing height are involved in pathways promoting ovarian carcinogenesis.
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ItemFine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants(NATURE PORTFOLIO, 2018-06-11)Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.
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ItemGermline variation at 8q24 and prostate cancer risk in men of European ancestry(NATURE PORTFOLIO, 2018-11-05)Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10-15), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62-4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification.
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ItemAge-specific breast cancer risk by body mass index and familial risk: prospective family study cohort (ProF-SC)(BMC, 2018-11-03)BACKGROUND: The association between body mass index (BMI) and risk of breast cancer depends on time of life, but it is unknown whether this association depends on a woman's familial risk. METHODS: We conducted a prospective study of a cohort enriched for familial risk consisting of 16,035 women from 6701 families in the Breast Cancer Family Registry and the Kathleen Cunningham Foundation Consortium for Research into Familial Breast Cancer followed for up to 20 years (mean 10.5 years). There were 896 incident breast cancers (mean age at diagnosis 55.7 years). We used Cox regression to model BMI risk associations as a function of menopausal status, age, and underlying familial risk based on pedigree data using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), all measured at baseline. RESULTS: The strength and direction of the BMI risk association depended on baseline menopausal status (P < 0.001); after adjusting for menopausal status, the association did not depend on age at baseline (P = 0.6). In terms of absolute risk, the negative association with BMI for premenopausal women has a much smaller influence than the positive association with BMI for postmenopausal women. Women at higher familial risk have a much larger difference in absolute risk depending on their BMI than women at lower familial risk. CONCLUSIONS: The greater a woman's familial risk, the greater the influence of BMI on her absolute postmenopausal breast cancer risk. Given that age-adjusted BMI is correlated across adulthood, maintaining a healthy weight throughout adult life is particularly important for women with a family history of breast cancer.
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ItemPolygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes(CELL PRESS, 2019-01-03)Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.