Medicine (RMH) - Research Publications

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    Identifying colorectal cancer caused by biallelic MUTYH pathogenic variants using tumor mutational signatures
    Georgeson, P ; Harrison, TA ; Pope, BJ ; Zaidi, SH ; Qu, C ; Steinfelder, RS ; Lin, Y ; Joo, JE ; Mahmood, K ; Clendenning, M ; Walker, R ; Amitay, EL ; Berndt, S ; Brenner, H ; Campbell, PT ; Cao, Y ; Chan, AT ; Chang-Claude, J ; Doheny, KF ; Drew, DA ; Figueiredo, JC ; French, AJ ; Gallinger, S ; Giannakis, M ; Giles, GG ; Gsur, A ; Gunter, MJ ; Hoffmeister, M ; Hsu, L ; Huang, W-Y ; Limburg, P ; Manson, JE ; Moreno, V ; Nassir, R ; Nowak, JA ; Obon-Santacana, M ; Ogino, S ; Phipps, A ; Potter, JD ; Schoen, RE ; Sun, W ; Toland, AE ; Trinh, QM ; Ugai, T ; Macrae, FA ; Rosty, C ; Hudson, TJ ; Jenkins, MA ; Thibodeau, SN ; Winship, IM ; Peters, U ; Buchanan, DD (NATURE PORTFOLIO, 2022-06-06)
    Carriers of germline biallelic pathogenic variants in the MUTYH gene have a high risk of colorectal cancer. We test 5649 colorectal cancers to evaluate the discriminatory potential of a tumor mutational signature specific to MUTYH for identifying biallelic carriers and classifying variants of uncertain clinical significance (VUS). Using a tumor and matched germline targeted multi-gene panel approach, our classifier identifies all biallelic MUTYH carriers and all known non-carriers in an independent test set of 3019 colorectal cancers (accuracy = 100% (95% confidence interval 99.87-100%)). All monoallelic MUTYH carriers are classified with the non-MUTYH carriers. The classifier provides evidence for a pathogenic classification for two VUS and a benign classification for five VUS. Somatic hotspot mutations KRAS p.G12C and PIK3CA p.Q546K are associated with colorectal cancers from biallelic MUTYH carriers compared with non-carriers (p = 2 × 10-23 and p = 6 × 10-11, respectively). Here, we demonstrate the potential application of mutational signatures to tumor sequencing workflows to improve the identification of biallelic MUTYH carriers.
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    Population-based estimates of breast cancer risk for carriers of pathogenic variants identified by gene-panel testing
    Southey, MC ; Dowty, JG ; Riaz, M ; Steen, JA ; Renault, A-L ; Tucker, K ; Kirk, J ; James, P ; Winship, I ; Pachter, N ; Poplawski, N ; Grist, S ; Park, DJ ; Pope, BJ ; Mahmood, K ; Hammet, F ; Mahmoodi, M ; Tsimiklis, H ; Theys, D ; Rewse, A ; Willis, A ; Morrow, A ; Speechly, C ; Harris, R ; Sebra, R ; Schadt, E ; Lacaze, P ; McNeil, JJ ; Giles, GG ; Milne, RL ; Hopper, JL ; Nguyen-Dumont, T (NATURE PORTFOLIO, 2021-12-09)
    Population-based estimates of breast cancer risk for carriers of pathogenic variants identified by gene-panel testing are urgently required. Most prior research has been based on women selected for high-risk features and more data is needed to make inference about breast cancer risk for women unselected for family history, an important consideration of population screening. We tested 1464 women diagnosed with breast cancer and 862 age-matched controls participating in the Australian Breast Cancer Family Study (ABCFS), and 6549 healthy, older Australian women enroled in the ASPirin in Reducing Events in the Elderly (ASPREE) study for rare germline variants using a 24-gene-panel. Odds ratios (ORs) were estimated using unconditional logistic regression adjusted for age and other potential confounders. We identified pathogenic variants in 11.1% of the ABCFS cases, 3.7% of the ABCFS controls and 2.2% of the ASPREE (control) participants. The estimated breast cancer OR [95% confidence interval] was 5.3 [2.1-16.2] for BRCA1, 4.0 [1.9-9.1] for BRCA2, 3.4 [1.4-8.4] for ATM and 4.3 [1.0-17.0] for PALB2. Our findings provide a population-based perspective to gene-panel testing for breast cancer predisposition and opportunities to improve predictors for identifying women who carry pathogenic variants in breast cancer predisposition genes.
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    Population-based estimates of age-specific cumulative risk of breast cancer for pathogenic variants in ATM
    Renault, A-L ; Dowty, JG ; Steen, JA ; Li, S ; Winship, IM ; Giles, GG ; Hopper, JL ; Southey, MC ; Nguyen-Dumont, T (BMC, 2022-04-01)
    BACKGROUND: Multigene panel tests for breast cancer predisposition routinely include ATM as it is now a well-established breast cancer predisposition gene. METHODS: We included ATM in a multigene panel test applied to the Australian Breast Cancer Family Registry (ABCFR), a population-based case-control-family study of breast cancer, with the purpose of estimating the prevalence and penetrance of heterozygous ATM pathogenic variants from the family data, using segregation analysis. RESULTS: The estimated breast cancer hazard ratio for carriers of pathogenic ATM variants in the ABCFR was 1.32 (95% confidence interval 0.45-3.87; P = 0.6). The estimated cumulative risk of breast cancer to age 80 years for heterozygous ATM pathogenic variant carriers was estimated to be 13% (95% CI 4.6-30). CONCLUSIONS: Although ATM has been definitively identified as a breast cancer predisposition gene, further evidence, such as variant-specific penetrance estimates, are needed to inform risk management strategies for carriers of pathogenic variants to increase the clinical utility of population testing of this gene.
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    Prospective Evaluation over 15 Years of Six Breast Cancer Risk Models
    Li, SX ; Milne, RL ; Nguyen-Dumont, T ; English, DR ; Giles, GG ; Southey, MC ; Antoniou, AC ; Lee, A ; Winship, I ; Hopper, JL ; Terry, MB ; MacInnis, RJ (MDPI, 2021-10-01)
    Prospective validation of risk models is needed to assess their clinical utility, particularly over the longer term. We evaluated the performance of six commonly used breast cancer risk models (IBIS, BOADICEA, BRCAPRO, BRCAPRO-BCRAT, BCRAT, and iCARE-lit). 15-year risk scores were estimated using lifestyle factors and family history measures from 7608 women in the Melbourne Collaborative Cohort Study who were aged 50-65 years and unaffected at commencement of follow-up two (conducted in 2003-2007), of whom 351 subsequently developed breast cancer. Risk discrimination was assessed using the C-statistic and calibration using the expected/observed number of incident cases across the spectrum of risk by age group (50-54, 55-59, 60-65 years) and family history of breast cancer. C-statistics were higher for BOADICEA (0.59, 95% confidence interval (CI) 0.56-0.62) and IBIS (0.57, 95% CI 0.54-0.61) than the other models (p-difference ≤ 0.04). No model except BOADICEA calibrated well across the spectrum of 15-year risk (p-value < 0.03). The performance of BOADICEA and IBIS was similar across age groups and for women with or without a family history. For middle-aged Australian women, BOADICEA and IBIS had the highest discriminatory accuracy of the six risk models, but apart from BOADICEA, no model was well-calibrated across the risk spectrum.
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    Distress and unmet needs during treatment and quality of life in early cancer survivorship: A longitudinal study of haematological cancer patients
    Oberoi, DV ; White, VM ; Seymour, JF ; Prince, HM ; Harrison, S ; Jefford, M ; Winship, I ; Hill, DJ ; Bolton, D ; Millar, J ; Doo, NW ; Kay, A ; Giles, G (WILEY, 2017-11-01)
    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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    Trends in the surgical management of stage 1 renal cell carcinoma: findings from a population-based study
    White, V ; Marco, DJT ; Bolton, D ; Davis, ID ; Jefford, M ; Hill, D ; Prince, HM ; Millar, JL ; Winship, IM ; Coory, M ; Giles, GG (WILEY, 2017-11-01)
    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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    Mendelian randomisation study of smoking exposure in relation to breast cancer risk
    Park, HA ; Neumeyer, S ; Michailidou, K ; Bolla, MK ; Wang, Q ; Dennis, J ; Ahearn, TU ; Andrulis, IL ; Anton-Culver, H ; Antonenkova, NN ; Arndt, V ; Aronson, KJ ; Augustinsson, A ; Baten, A ; Freeman, LEB ; Becher, H ; Beckmann, MW ; Behrens, S ; Benitez, J ; Bermisheva, M ; Bogdanova, N ; Bojesen, SE ; Brauch, H ; Brenner, H ; Brucker, SY ; Burwinkel, B ; Campa, D ; Canzian, F ; Castelao, JE ; Chanock, SJ ; Chenevix-Trench, G ; Clarke, CL ; Conroy, DM ; Couch, FJ ; Cox, A ; Cross, SS ; Czene, K ; Daly, MB ; Devilee, P ; Dork, T ; Dos-Santos-Silva, I ; Dwek, M ; Eccles, DM ; Eliassen, AH ; Engel, C ; Eriksson, M ; Evans, DG ; Fasching, PA ; Flyger, H ; Fritschi, L ; Garcia-Closas, M ; Garcia-Saenz, JA ; Gaudet, MM ; Giles, GG ; Glendon, G ; Goldberg, MS ; Goldgar, DE ; Gonzalez-Neira, A ; Grip, M ; Guenel, P ; Hahnen, E ; Haiman, CA ; Hakansson, N ; Hall, P ; Hamann, U ; Han, S ; Harkness, EF ; Hart, SN ; He, W ; Heemskerk-Gerritsen, BAM ; Hopper, JL ; Hunter, DJ ; Jager, A ; Jakubowska, A ; John, EM ; Jung, A ; Kaaks, R ; Kapoor, PM ; Keeman, R ; Khusnutdinova, E ; Kitahara, CM ; Koppert, LB ; Koutros, S ; Kristensen, VN ; Kurian, AW ; Lacey, J ; Lambrechts, D ; LeMarchand, L ; Lo, W-Y ; Mannermaa, A ; Manoochehri, M ; Margolin, S ; ElenaMartinez, M ; Mavroudis, D ; Meindl, A ; Menon, U ; Milne, RL ; Muranen, TA ; Nevanlinna, H ; Newman, WG ; Nordestgaard, BG ; Offit, K ; Olshan, AF ; Olsson, H ; Park-Simon, T-W ; Peterlongo, P ; Peto, J ; Plaseska-Karanfilska, D ; Presneau, N ; Radice, P ; Rennert, G ; Rennert, HS ; Romero, A ; Saloustros, E ; Sawyer, EJ ; Schmidt, MK ; Schmutzler, RK ; Schoemaker, MJ ; Schwentner, L ; Scott, C ; Shah, M ; Shu, X-O ; Simard, J ; Smeets, A ; Southey, MC ; Spinelli, JJ ; Stevens, V ; Swerdlow, AJ ; Tamimi, RM ; Tapper, WJ ; Taylor, JA ; Terry, MB ; Tomlinson, I ; Troester, MA ; Truong, T ; Vachon, CM ; van Veen, EM ; Vijai, J ; Wang, S ; Wendt, C ; Winqvist, R ; Wolk, A ; Ziogas, A ; Dunning, AM ; Pharoah, PDP ; Easton, DF ; Zheng, W ; Kraft, P ; Chang-Claude, J (SPRINGERNATURE, 2021-08-02)
    BACKGROUND: Despite a modest association between tobacco smoking and breast cancer risk reported by recent epidemiological studies, it is still equivocal whether smoking is causally related to breast cancer risk. METHODS: We applied Mendelian randomisation (MR) to evaluate a potential causal effect of cigarette smoking on breast cancer risk. Both individual-level data as well as summary statistics for 164 single-nucleotide polymorphisms (SNPs) reported in genome-wide association studies of lifetime smoking index (LSI) or cigarette per day (CPD) were used to obtain MR effect estimates. Data from 108,420 invasive breast cancer cases and 87,681 controls were used for the LSI analysis and for the CPD analysis conducted among ever-smokers from 26,147 cancer cases and 26,072 controls. Sensitivity analyses were conducted to address pleiotropy. RESULTS: Genetically predicted LSI was associated with increased breast cancer risk (OR 1.18 per SD, 95% CI: 1.07-1.30, P = 0.11 × 10-2), but there was no evidence of association for genetically predicted CPD (OR 1.02, 95% CI: 0.78-1.19, P = 0.85). The sensitivity analyses yielded similar results and showed no strong evidence of pleiotropic effect. CONCLUSION: Our MR study provides supportive evidence for a potential causal association with breast cancer risk for lifetime smoking exposure but not cigarettes per day among smokers.
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    DNA Methylation Signatures and the Contribution of Age-Associated Methylomic Drift to Carcinogenesis in Early-Onset Colorectal Cancer
    Joo, JE ; Clendenning, M ; Wong, EM ; Rosty, C ; Mahmood, K ; Georgeson, P ; Winship, IM ; Preston, SG ; Win, AK ; Dugue, P-A ; Jayasekara, H ; English, D ; Macrae, FA ; Hopper, JL ; Jenkins, MA ; Milne, RL ; Giles, GG ; Southey, MC ; Buchanan, DD (MDPI, 2021-06-01)
    We investigated aberrant DNA methylation (DNAm) changes and the contribution of ageing-associated methylomic drift and age acceleration to early-onset colorectal cancer (EOCRC) carcinogenesis. Genome-wide DNAm profiling using the Infinium HM450K on 97 EOCRC tumour and 54 normal colonic mucosa samples was compared with: (1) intermediate-onset CRC (IOCRC; diagnosed between 50-70 years; 343 tumour and 35 normal); and (2) late-onset CRC (LOCRC; >70 years; 318 tumour and 40 normal). CpGs associated with age-related methylation drift were identified using a public dataset of 231 normal mucosa samples from people without CRC. DNAm-age was estimated using epiTOC2. Common to all three age-of-onset groups, 88,385 (20% of all CpGs) CpGs were differentially methylated between tumour and normal mucosa. We identified 234 differentially methylated genes that were unique to the EOCRC group; 13 of these DMRs/genes were replicated in EOCRC compared with LOCRCs from TCGA. In normal mucosa from people without CRC, we identified 28,154 CpGs that undergo ageing-related DNAm drift, and of those, 65% were aberrantly methylated in EOCRC tumours. Based on the mitotic-based DNAm clock epiTOC2, we identified age acceleration in normal mucosa of people with EOCRC compared with normal mucosa from the IOCRC, LOCRC groups (p = 3.7 × 10-16) and young people without CRC (p = 5.8 × 10-6). EOCRC acquires unique DNAm alterations at 234 loci. CpGs associated with ageing-associated drift were widely affected in EOCRC without needing the decades-long accrual of DNAm drift as commonly seen in intermediate- and late-onset CRCs. Accelerated ageing in normal mucosa from people with EOCRC potentially underlies the earlier age of diagnosis in CRC carcinogenesis.
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    Prospective Evaluation of the Addition of Polygenic Risk Scores to Breast Cancer Risk Models
    Li, SX ; Milne, RL ; Nguyen-Dumont, T ; Wang, X ; English, DR ; Giles, GG ; Southey, MC ; Antoniou, AC ; Lee, A ; Li, S ; Winship, I ; Hopper, JL ; Terry, MB ; MacInnis, RJ (OXFORD UNIV PRESS, 2021-03-02)
    Background: The Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm and the International Breast Cancer Intervention Study breast cancer risk models are used to provide advice on screening intervals and chemoprevention. We evaluated the performance of these models, which now incorporate polygenic risk scores (PRSs), using a prospective cohort study. Methods: We used a case-cohort design, involving women in the Melbourne Collaborative Cohort Study aged 50-75 years when surveyed in 2003-2007, of whom 408 had a first primary breast cancer diagnosed within 10 years (cases), and 2783 were from the subcohort. Ten-year risks were calculated based on lifestyle factors, family history data, and a 313-variant PRS. Discrimination was assessed using a C-statistic compared with 0.50 and calibration using the ratio of expected to observed number of cases (E/O). Results: When the PRS was added to models with lifestyle factors and family history, the C-statistic (95% confidence interval [CI]) increased from 0.57 (0.54 to 0.60) to 0.62 (0.60 to 0.65) using IBIS and from 0.56 (0.53 to 0.59) to 0.62 (0.59 to 0.64) using BOADICEA. IBIS underpredicted risk (E/O = 0.62, 95% CI = 0.48 to 0.80) for women in the lowest risk category (<1.7%) and overpredicted risk (E/O = 1.40, 95% CI = 1.18 to 1.67) in the highest risk category (≥5%), using the Hosmer-Lemeshow test for calibration in quantiles of risk and a 2-sided P value less than  .001. BOADICEA underpredicted risk (E/O = 0.82, 95% CI = 0.67 to 0.99) in the second highest risk category (3.4%-5%); the Hosmer-Lemeshow test and a 2-sided P value was equal to .02. Conclusions: Although the inclusion of a 313 genetic variant PRS doubles discriminatory accuracy (relative to reference 0.50), models with and without this PRS have relatively modest discrimination and might require recalibration before their clinical and wider use are promoted.
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    Population-Based Estimates of the Age-Specific Cumulative Risk of Breast Cancer for Pathogenic Variants in CHEK2: Findings from the Australian Breast Cancer Family Registry
    Nguyen-Dumont, T ; Dowty, JG ; Steen, JA ; Renault, A-L ; Hammet, F ; Mahmoodi, M ; Theys, D ; Rewse, A ; Tsimiklis, H ; Winship, IM ; Giles, GG ; Milne, RL ; Hopper, JL ; Southey, MC (MDPI, 2021-03-01)
    Case-control studies of breast cancer have consistently shown that pathogenic variants in CHEK2 are associated with about a 3-fold increased risk of breast cancer. Information about the recurrent protein-truncating variant CHEK2 c.1100delC dominates this estimate. There have been no formal estimates of age-specific cumulative risk of breast cancer for all CHEK2 pathogenic (including likely pathogenic) variants combined. We conducted a population-based case-control-family study of pathogenic CHEK2 variants (26 families, 1071 relatives) and estimated the age-specific cumulative risk of breast cancer using segregation analysis. The estimated hazard ratio for carriers of pathogenic CHEK2 variants (combined) was 4.9 (95% CI 2.5-9.5) relative to non-carriers. The HR for carriers of the CHEK2 c.1100delC variant was estimated to be 3.5 (95% CI 1.02-11.6) and the HR for carriers of all other CHEK2 variants combined was estimated to be 5.7 (95% CI 2.5-12.9). The age-specific cumulative risk of breast cancer was estimated to be 18% (95% CI 11-30%) and 33% (95% CI 21-48%) to age 60 and 80 years, respectively. These findings provide important information for the clinical management of breast cancer risk for women carrying pathogenic variants in CHEK2.