Clinical Pathology - Research Publications

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    Modifiable lifestyle risk factors and survival after diagnosis with multiple myeloma
    Cheah, S ; Bassett, JK ; Bruinsma, FJ ; Hopper, J ; Jayasekara, H ; Joshua, D ; Macinnis, RJ ; Prince, HM ; Southey, MC ; Vajdic, CM ; van Leeuwen, MT ; Doo, NW ; Harrison, SJ ; English, DR ; Giles, GG ; Milne, RL (TAYLOR & FRANCIS LTD, 2023-10-03)
    BACKGROUND: While remaining incurable, median overall survival for MM now exceeds 5 years. Yet few studies have investigated how modifiable lifestyle factors influence survival. We investigate whether adiposity, diet, alcohol, or smoking are associated with MM-related fatality. RESEARCH DESIGN AND METHODS: We recruited 760 incident cases of MM via cancer registries in two Australian states during 2010-2016. Participants returned questionnaires on health and lifestyle. Follow-up ended in 2020. Flexible parametric survival models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for lifestyle exposures and risk of all-cause and MM-specific fatality. RESULTS: Higher pre-diagnosis Alternative Healthy Eating Index (AHEI) scores were associated with reduced MM-specific fatality (per 10-unit score, HR = 0.84, 95%CI = 0.70-0.99). Pre-diagnosis alcohol consumption was inversely associated with MM-specific fatality, compared with nondrinkers (0.1-20 g per day, HR = 0.59, 95%CI = 0.39-0.90; >20 g per day, HR = 0.67, 95%CI = 0.40-1.13). Tobacco smoking was associated with increased all-cause fatality compared with never smoking (former smokers: HR = 1.44, 95%CI = 1.10-1.88; current smokers: HR = 1.30, 95%CI = 0.80-2.10). There was no association between pre-enrollment body mass index (BMI) and MM-specific or all-cause fatality. CONCLUSIONS: Our findings support established recommendations for healthy diets and against smoking. Higher quality diet, as measured by the AHEI, may improve survival post diagnosis with MM.
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    Heritable methylation marks associated with prostate cancer risk.
    Dowty, JG ; Yu, C ; Hosseinpour, M ; Joo, JE ; Wong, EM ; Nguyen-Dumont, T ; Rosenbluh, J ; Giles, GG ; Milne, RL ; MacInnis, RJ ; Dugué, P-A ; Southey, MC (Springer Science and Business Media LLC, 2023-07)
    DNA methylation marks that are inherited from parents to offspring are known to play a role in cancer risk and could explain part of the familial risk for cancer. We therefore conducted a genome-wide search for heritable methylation marks associated with prostate cancer risk. Peripheral blood DNA methylation was measured for 133 of the 469 members of 25 multiple-case prostate cancer families, using the EPIC array. We used these families to systematically search the genome for methylation marks with Mendelian patterns of inheritance, then we tested the 1,000 most heritable marks for association with prostate cancer risk. After correcting for multiple testing, 41 heritable methylation marks were associated with prostate cancer risk. Separate analyses, based on 869 incident cases and 869 controls from a prospective cohort study, showed that 9 of these marks near the metastable epiallele VTRNA2-1 were also nominally associated with aggressive prostate cancer risk in the population.
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    Independent evaluation of melanoma polygenic risk scores in UK and Australian prospective cohorts
    Steinberg, J ; Lee, JY ; Wang, H ; Law, M ; Smit, A ; Nguyen-Dumont, T ; Giles, G ; Southey, M ; Milne, R ; Mann, G ; MacInnis, R ; Cust, A (OXFORD UNIV PRESS, 2021-09)
    BACKGROUND: Previous studies suggest that polygenic risk scores (PRSs) may improve melanoma risk stratification. However, there has been limited independent validation of PRS-based risk prediction, particularly assessment of calibration (comparing predicted to observed risks). OBJECTIVES: To evaluate PRS-based melanoma risk prediction in prospective UK and Australian cohorts with European ancestry. METHODS: We analysed invasive melanoma incidence in the UK Biobank (UKB; n = 395 647, 1651 cases) and a case-cohort nested within the Melbourne Collaborative Cohort Study (MCCS, Australia; n = 4765, 303 cases). Three PRSs were evaluated: 68 single-nucleotide polymorphisms (SNPs) at 54 loci from a 2020 meta-analysis (PRS68), 50 SNPs significant in the 2020 meta-analysis excluding UKB (PRS50) and 45 SNPs at 21 loci known in 2018 (PRS45). Ten-year melanoma risks were calculated from population-level cancer registry data by age group and sex, with and without PRS adjustment. RESULTS: Predicted absolute melanoma risks based on age and sex alone underestimated melanoma incidence in the UKB [ratio of expected/observed cases: E/O = 0·65, 95% confidence interval (CI) 0·62-0·68] and MCCS (E/O = 0·63, 95% CI 0·56-0·72). For UKB, calibration was improved by PRS adjustment, with PRS50-adjusted risks E/O = 0·91, 95% CI 0·87-0·95. The discriminative ability for PRS68- and PRS50-adjusted absolute risks was higher than for risks based on age and sex alone (Δ area under the curve 0·07-0·10, P < 0·0001), and higher than for PRS45-adjusted risks (Δ area under the curve 0·02-0·04, P < 0·001). CONCLUSIONS: A PRS derived from a larger, more diverse meta-analysis improves risk prediction compared with an earlier PRS, and might help tailor melanoma prevention and early detection strategies to different risk levels. Recalibration of absolute risks may be necessary for application to specific populations.
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    Weight is More Informative than Body Mass Index for Predicting Postmenopausal Breast Cancer Risk: Prospective Family Study Cohort (ProF-SC)
    Ye, Z ; Li, S ; Dite, GS ; Nguyen, TL ; MacInnis, RJ ; Andrulis, IL ; Buys, SS ; Daly, MB ; John, EM ; Kurian, AW ; Genkinger, JM ; Chung, WK ; Phillips, K-A ; Thorne, H ; Winship, IM ; Milne, RL ; Dugue, P-A ; Southey, MC ; Giles, GG ; Terry, MB ; Hopper, JL (AMER ASSOC CANCER RESEARCH, 2022-03)
    UNLABELLED: We considered whether weight is more informative than body mass index (BMI) = weight/height2 when predicting breast cancer risk for postmenopausal women, and if the weight association differs by underlying familial risk. We studied 6,761 women postmenopausal at baseline with a wide range of familial risk from 2,364 families in the Prospective Family Study Cohort. Participants were followed for on average 11.45 years and there were 416 incident breast cancers. We used Cox regression to estimate risk associations with log-transformed weight and BMI after adjusting for underlying familial risk. We compared model fits using the Akaike information criterion (AIC) and nested models using the likelihood ratio test. The AIC for the weight-only model was 6.22 units lower than for the BMI-only model, and the log risk gradient was 23% greater. Adding BMI or height to weight did not improve fit (ΔAIC = 0.90 and 0.83, respectively; both P = 0.3). Conversely, adding weight to BMI or height gave better fits (ΔAIC = 5.32 and 11.64; P = 0.007 and 0.0002, respectively). Adding height improved only the BMI model (ΔAIC = 5.47; P = 0.006). There was no evidence that the BMI or weight associations differed by underlying familial risk (P > 0.2). Weight is more informative than BMI for predicting breast cancer risk, consistent with nonadipose as well as adipose tissue being etiologically relevant. The independent but multiplicative associations of weight and familial risk suggest that, in terms of absolute breast cancer risk, the association with weight is more important the greater a woman's underlying familial risk. PREVENTION RELEVANCE: Our results suggest that the relationship between BMI and breast cancer could be due to a relationship between weight and breast cancer, downgraded by inappropriately adjusting for height; potential importance of anthropometric measures other than total body fat; breast cancer risk associations with BMI and weight are across a continuum.
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    Segregation analysis of 17,425 population-based breast cancer families: Evidence for genetic susceptibility and risk prediction
    Li, S ; MacInnis, RJ ; Lee, A ; Nguyen-Dumont, T ; Dorling, L ; Carvalho, S ; Dite, GS ; Shah, M ; Luccarini, C ; Wang, Q ; Milne, RL ; Jenkins, MA ; Giles, GG ; Dunning, AM ; Pharoah, PDP ; Southey, MC ; Easton, DF ; Hopper, JL ; Antoniou, AC (CELL PRESS, 2022-10-06)
    Rare pathogenic variants in known breast cancer-susceptibility genes and known common susceptibility variants do not fully explain the familial aggregation of breast cancer. To investigate plausible genetic models for the residual familial aggregation, we studied 17,425 families ascertained through population-based probands, 86% of whom were screened for pathogenic variants in BRCA1, BRCA2, PALB2, CHEK2, ATM, and TP53 via gene-panel sequencing. We conducted complex segregation analyses and fitted genetic models in which breast cancer incidence depended on the effects of known susceptibility genes and other unidentified major genes and a normally distributed polygenic component. The proportion of familial variance explained by the six genes was 46% at age 20-29 years and decreased steadily with age thereafter. After allowing for these genes, the best fitting model for the residual familial variance included a recessive risk component with a combined genotype frequency of 1.7% (95% CI: 0.3%-5.4%) and a penetrance to age 80 years of 69% (95% CI: 38%-95%) for homozygotes, which may reflect the combined effects of multiple variants acting in a recessive manner, and a polygenic variance of 1.27 (95% CI: 0.94%-1.65), which did not vary with age. The proportion of the residual familial variance explained by the recessive risk component was 40% at age 20-29 years and decreased with age thereafter. The model predicted age-specific familial relative risks consistent with those observed by large epidemiological studies. The findings have implications for strategies to identify new breast cancer-susceptibility genes and improve disease-risk prediction, especially at a young age.
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    Genome-wide interaction analysis of menopausal hormone therapy use and breast cancer risk among 62,370 women
    Wang, X ; Kapoor, PM ; Auer, PL ; Dennis, J ; Dunning, AM ; Wang, Q ; Lush, M ; Michailidou, K ; Bolla, MK ; Aronson, KJ ; Murphy, RA ; Brooks-Wilson, A ; Lee, DG ; Guenel, P ; Truong, T ; Mulot, C ; Teras, LR ; Patel, A ; Dossus, L ; Kaaks, R ; Hoppe, R ; Bruening, T ; Hamann, U ; Czene, K ; Gabrielson, M ; Hall, P ; Eriksson, M ; Jung, A ; Becher, H ; Couch, FJ ; Larson, NL ; Olson, JE ; Ruddy, KJ ; Giles, GG ; MacInnis, RJ ; Southey, MC ; Le Marchand, L ; Wilkens, LR ; Haiman, CA ; Olsson, H ; Augustinsson, A ; Krueger, U ; Wagner, P ; Scott, C ; Winham, SJ ; Vachon, CM ; Perou, CM ; Olshan, AF ; Troester, MA ; Hunter, DJ ; Eliassen, HA ; Tamimi, RM ; Brantley, K ; Andrulis, IL ; Figueroa, J ; Chanock, SJ ; Ahearn, TU ; Evans, GD ; Newman, WG ; VanVeen, EM ; Howell, A ; Wolk, A ; Hakansson, N ; Ziogas, A ; Jones, ME ; Orr, N ; Schoemaker, MJ ; Swerdlow, AJ ; Kitahara, CM ; Linet, M ; Prentice, RL ; Easton, DF ; Milne, RL ; Kraft, P ; Chang-Claude, J ; Lindstrom, S (NATURE PORTFOLIO, 2022-04-13)
    Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values < 5 × 10-8 as genome-wide significant, and p-values < 1 × 10-5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants. None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values < 1 × 105. The strongest evidence was found for rs4674019 (p-value = 2.27 × 10-7), which showed genome-wide significant interaction (p-value = 3.8 × 10-8) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen-progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT-breast cancer risk association.
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    Common variants in breast cancer risk loci predispose to distinct tumor subtypes
    Ahearn, TU ; Zhang, H ; Michailidou, K ; Milne, RL ; Bolla, MK ; Dennis, J ; Dunning, AM ; Lush, M ; Wang, Q ; Andrulis, IL ; Anton-Culver, H ; Arndt, V ; Aronson, KJ ; Auer, PL ; Augustinsson, A ; Baten, A ; Becher, H ; Behrens, S ; Benitez, J ; Bermisheva, M ; Blomqvist, C ; Bojesen, SE ; Bonanni, B ; Borresen-Dale, A-L ; Brauch, H ; Brenner, H ; Brooks-Wilson, A ; Bruening, T ; Burwinkel, B ; Buys, SS ; Canzian, F ; Castelao, JE ; Chang-Claude, J ; Chanock, SJ ; Chenevix-Trench, G ; Clarke, CL ; Collee, JM ; Cox, A ; Cross, SS ; Czene, K ; Daly, MB ; Devilee, P ; Dork, T ; Dwek, M ; Eccles, DM ; Evans, DG ; Fasching, PA ; Figueroa, J ; Floris, G ; Gago-Dominguez, M ; Gapstur, SM ; Garcia-Saenz, JA ; Gaudet, MM ; Giles, GG ; Goldberg, MS ; Gonzalez-Neira, A ; Alnaes, GIG ; Grip, M ; Guenel, P ; Haiman, CA ; Hall, P ; Hamann, U ; Harkness, EF ; Heemskerk-Gerritsen, BAM ; Holleczek, B ; Hollestelle, A ; Hooning, MJ ; Hoover, RN ; Hopper, JL ; Howell, A ; Jakimovska, M ; Jakubowska, A ; John, EM ; Jones, ME ; Jung, A ; Kaaks, R ; Kauppila, S ; Keeman, R ; Khusnutdinova, E ; Kitahara, CM ; Ko, Y-D ; Koutros, S ; Kristensen, VN ; Kruger, U ; Kubelka-Sabit, K ; Kurian, AW ; Kyriacou, K ; Lambrechts, D ; Lee, DG ; Lindblom, A ; Linet, M ; Lissowska, J ; Llaneza, A ; Lo, W-Y ; MacInnis, RJ ; Mannermaa, A ; Manoochehri, M ; Margolin, S ; Martinez, ME ; McLean, C ; Meindl, A ; Menon, U ; Nevanlinna, H ; Newman, WG ; Nodora, J ; Offit, K ; Olsson, H ; Orr, N ; Park-Simon, T-W ; Patel, A ; Peto, J ; Pita, G ; Plaseska-Karanfilska, D ; Prentice, R ; Punie, K ; Pylkas, K ; Radice, P ; Rennert, G ; Romero, A ; Ruediger, T ; Saloustros, E ; Sampson, S ; Sandler, DP ; Sawyer, EJ ; Schmutzler, RK ; Schoemaker, MJ ; Schottker, B ; Sherman, ME ; Shu, X-O ; Smichkoska, S ; Southey, MC ; Spinelli, JJ ; Swerdlow, AJ ; Tamimi, RM ; Tapper, WJ ; Taylor, JA ; Teras, LR ; Terry, MB ; Torres, D ; Troester, MA ; Vachon, CM ; van Deurzen, CHM ; van Veen, EM ; Wagner, P ; Weinberg, CR ; Wendt, C ; Wesseling, J ; Winqvist, R ; Wolk, A ; Yang, XR ; Zheng, W ; Couch, FJ ; Simard, J ; Kraft, P ; Easton, DF ; Pharoah, PDP ; Schmidt, MK ; Garcia-Closas, M ; Chatterjee, N (BMC, 2022-01-04)
    BACKGROUND: Genome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear. METHODS: Among 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes. RESULTS: Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate < 5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at p < 0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions. CONCLUSION: This report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.
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    Recreational Physical Activity and Outcomes After Breast Cancer in Women at High Familial Risk
    Kehm, RD ; MacInnis, RJ ; John, EM ; Liao, Y ; Kurian, AW ; Genkinger, JM ; Knight, JA ; Colonna, S ; Chung, WK ; Milne, R ; Zeinomar, N ; Dite, GS ; Southey, MC ; Giles, GG ; Mclachlan, S-A ; Whitaker, KD ; Friedlander, ML ; Weideman, PC ; Glendon, G ; Nesci, S ; Investigators, K ; Phillips, K-A ; Andrulis, IL ; Buys, SS ; Daly, MB ; Hopper, JL ; Terry, MB (OXFORD UNIV PRESS, 2021-12)
    BACKGROUND: Recreational physical activity (RPA) is associated with improved survival after breast cancer (BC) in average-risk women, but evidence is limited for women who are at increased familial risk because of a BC family history or BRCA1 and BRCA2 pathogenic variants (BRCA1/2 PVs). METHODS: We estimated associations of RPA (self-reported average hours per week within 3 years of BC diagnosis) with all-cause mortality and second BC events (recurrence or new primary) after first invasive BC in women in the Prospective Family Study Cohort (n = 4610, diagnosed 1993-2011, aged 22-79 years at diagnosis). We fitted Cox proportional hazards regression models adjusted for age at diagnosis, demographics, and lifestyle factors. We tested for multiplicative interactions (Wald test statistic for cross-product terms) and additive interactions (relative excess risk due to interaction) by age at diagnosis, body mass index, estrogen receptor status, stage at diagnosis, BRCA1/2 PVs, and familial risk score estimated from multigenerational pedigree data. Statistical tests were 2-sided. RESULTS: We observed 1212 deaths and 473 second BC events over a median follow-up from study enrollment of 11.0 and 10.5 years, respectively. After adjusting for covariates, RPA (any vs none) was associated with lower all-cause mortality of 16.1% (95% confidence interval [CI] = 2.4% to 27.9%) overall, 11.8% (95% CI = -3.6% to 24.9%) in women without BRCA1/2 PVs, and 47.5% (95% CI = 17.4% to 66.6%) in women with BRCA1/2 PVs (RPA*BRCA1/2 multiplicative interaction P = .005; relative excess risk due to interaction = 0.87, 95% CI = 0.01 to 1.74). RPA was not associated with risk of second BC events. CONCLUSION: Findings support that RPA is associated with lower all-cause mortality in women with BC, particularly in women with BRCA1/2 PVs.
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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)
    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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    Associations of alcohol intake, smoking, physical activity and obesity with survival following colorectal cancer diagnosis by stage, anatomic site and tumor molecular subtype
    Jayasekara, H ; English, DR ; Haydon, A ; Hodge, AM ; Lynch, BM ; Rosty, C ; Williamson, EJ ; Clendenning, M ; Southey, MC ; Jenkins, MA ; Room, R ; Hopper, JL ; Milne, RL ; Buchanan, DD ; Giles, GG ; MacInnis, RJ (WILEY, 2018-01-15)
    The influence of lifestyle factors on survival following a diagnosis of colorectal cancer (CRC) is not well established. We examined associations between lifestyle factors measured before diagnosis and CRC survival. The Melbourne Collaborative Cohort Study collected data on alcohol intake, cigarette smoking and physical activity, and body measurements at baseline (1990-1994) and wave 2 (2003-2007). We included participants diagnosed to 31 August 2015 with incident stages I-III CRC within 10-years post exposure assessment. Information on tumor characteristics and vital status was obtained. Tumor DNA was tested for microsatellite instability (MSI) and somatic mutations in oncogenes BRAF (V600E) and KRAS. We estimated hazard ratios (HRs) for associations between lifestyle factors and overall and CRC-specific mortality using Cox regression. Of 724 eligible CRC cases, 339 died (170 from CRC) during follow-up (average 9.0 years). Exercise (non-occupational/leisure-time) was associated with higher CRC-specific survival for stage II (HR = 0.25, 95% CI: 0.10-0.60) but not stages I/III disease (p for interaction = 0.01), and possibly for colon and KRAS wild-type tumors. Waist circumference was inversely associated with CRC-specific survival (HR = 1.25 per 10 cm increment, 95% CI: 1.08-1.44), independent of stage, anatomic site and tumor molecular status. Cigarette smoking was associated with lower overall survival, with suggestive evidence of worse survival for BRAF mutated CRC, but not with CRC-specific survival. Alcohol intake was not associated with survival. Survival did not differ by MSI status. We have identified pre-diagnostic predictors of survival following CRC that may have clinical and public health relevance.