Genetically determined body mass index is associated with diffuse large B-cell lymphoma in polygenic and Mendelian randomization analyses.

Obesity has been associated with non-Hodgkin lymphoma (NHL), but the evidence is inconclusive. We examined the association between genetically determined adiposity and four common NHL subtypes: diffuse large B-cell lymphoma (DLBCL), follicular lymphoma, chronic lymphocytic leukemia, and marginal zone lymphoma, using eight genome-wide association studies of European ancestry (N = 10,629 cases, 9505 controls) and constructing polygenic scores for body mass index (BMI), waist-to-hip ratio (WHR), and waist-to-hip ratio adjusted for BMI (WHRadjBMI). Higher genetically determined BMI was associated with an increased risk of DLBCL [odds ratio (OR) per standard deviation (SD) = 1.

Quality control checkpoints for high throughput DNA methylation measurement using the human MethylationEPICv1 array: application to formalin-fixed paraffin embedded prostate tissue.

Objective: The performance of FFPE tissue-derived DNA on the MethylationEpicV1.0 array can be unpredictable as the protocol only has two quality checks; checkpoint 1 for DNA quantity and checkpoint 2 for DNA quality assessment. We sought to incorporate a third, previously developed bisulfite conversion quality check prior to processing 255 FFPE tissue derived DNA samples.

GWAS meta-analysis identifies five susceptibility loci for endometrial cancer.

Background: Endometrial cancer is the most common gynaecological cancer in high-income countries. In addition to environmental risk factors, genetic predisposition contributes towards endometrial cancer development but is still incompletely defined.

Methods: Building on genome-wide association studies (GWASs) by the Endometrial Cancer Association Consortium, we conducted a GWAS meta-analysis of 17,278 endometrial cancer cases and 289,180 controls, incorporating biobank samples from the UK, Finland, Estonia and Japan.

Exogenous Hormones, Tumor Intrinsic Subtypes, and Breast Cancer.

Importance: Etiologic heterogeneity in breast carcinogenesis needs to be well characterized for targeted prevention. Associations between menopausal hormonal therapy (MHT) and oral contraceptive (OC) use and breast cancer intrinsic-like subtypes are not well understood.

Objective: To examine whether exogenous hormone use is differentially associated with breast cancer subtypes and to evaluate heterogeneity by intrinsic-like subtypes.

A review of the use of tumour DNA methylation for breast cancer subtyping and prediction of outcomes.

DNA methylation in breast tumours has been extensively studied and has provided valuable insights into the clinical heterogeneity of breast cancer. In this review, we summarise the current literature that has used DNA methylation markers to subtype breast cancer and predict progression and survival. Widespread methylation differences have been observed across breast cancer subtypes at both the candidate genes and in genome-wide analyses, most notably between oestrogen receptor (ER) positive and ER-negative subtypes and for triple-negative tumours.

Analysis of more than 400,000 women provides case-control evidence for BRCA1 and BRCA2 variant classification.

Clinical genetic testing identifies variants causal for hereditary cancer, information that is used for risk assessment and clinical management. Unfortunately, some variants identified are of uncertain clinical significance (VUS), complicating patient management. Case-control data is one evidence type used to classify VUS.

Smart Nonuniformity for Calibrating Sequencing Depth of a Targeted Gene Panel to Simultaneously Detect Somatic and Germline Variants.

Targeted gene panel sequencing that measures genomic variation at different depths has potential diagnostic application. A targeted gene panel, smart nonuniformity sequencing, was developed to detect somatic variants associated with clonal hematopoiesis of indeterminate potential (CHIP), which requires an optimal sequencing depth of >500×; and germline variants requiring a lower ≥50× depth (panel 1). This was achieved by adjusting probe ratios for genomic regions relevant to identifying CHIP in comparison to those relevant to germline variation analysis.

Association of Epigenetic Markers of Aging With Prevalent and Incident Type 2 Diabetes.

Background: Type 2 diabetes (T2D) is characterized by elevated levels of metabolic and inflammatory markers but less is known about other molecular alterations that occur with aging. We aimed to assess the associations of DNA methylation-based measures of aging (epigenetic aging) with prevalent and incident T2D in a large sample of middle-aged and older Australians.

Methods: We used data from 5 403 participants in the Melbourne Collaborative Cohort Study (mean age = 59 years).

Intratumoural pksEscherichia coli is associated with risk of metachronous colorectal cancer and adenoma development in people with Lynch syndrome.

Background: The adverse gut microbiome may underlie the variability in risks of colorectal cancer (CRC) and metachronous CRC in people with Lynch syndrome (LS). The role of pksEscherichia coli (pksE. coli), Enterotoxigenic Bacteroides fragilis (ETBF), and Fusobacterium nucleatum (Fn) in CRCs and adenomas in people with LS is unknown.

Overlap of high-risk individuals across family history, genetic & non-genetic breast cancer risk models: Analysis of 180,398 women from European & Asian ancestries.

Background: Breast cancer is multifactorial. Focusing on limited risk factors may miss high-risk individuals.

Methods: We assessed the performance and overlap of various risk factors in identifying high-risk individuals for invasive breast cancer (BrCa) and ductal carcinoma in situ (DCIS) in 161,849 European-ancestry and 18,549 Asian-ancestry women.

Breast tumors from ATM pathogenic variant carriers display a specific genome-wide DNA methylation profile.

Background: The ataxia-telangiectasia mutated (ATM) kinase phosphorylates and activates several downstream targets that are essential for DNA damage repair, cell cycle inhibition and apoptosis. Germline biallelic inactivation of the ATM gene causes ataxia-telangiectasia (A-T), and heterozygous pathogenic variant (PV) carriers are at increased risk of cancer, notably breast cancer. This study aimed to investigate whether DNA methylation profiling can be useful as a biomarker to identify tumors arising in ATM PV carriers, which may help for the management and optimal tailoring of therapies of these patients.

Blood-based DNA methylation markers for lung cancer prediction.

Objective: Screening high-risk individuals with low-dose CT reduces mortality from lung cancer, but many lung cancers occur in individuals who are not eligible for screening. Risk biomarkers may be useful to refine risk models and improve screening eligibility criteria. We evaluated if blood-based DNA methylation markers can improve a traditional lung cancer prediction model.

Tumour DNA methylation markers associated with breast cancer survival: a replication study.

Background: Tumour DNA methylation has been investigated as a potential marker for breast cancer survival, but findings often lack replication across studies.

Methods: This study sought to replicate previously reported associations for individual CpG sites and multi-CpG signatures using an Australian sample of 425 women with breast cancer from the Melbourne Collaborative Cohort Study (MCCS). Candidate methylation sites (N = 22) and signatures (N = 3) potentially associated with breast cancer survival were identified from five prior studies that used The Cancer Genome Atlas (TCGA) methylation dataset, which shares key characteristics with the MCCS: comparable sample size, tissue type (formalin-fixed paraffin-embedded; FFPE), technology (Illumina HumanMethylation450 array), and participant characteristics (age, ancestry, and disease subtype and severity).

Polygenic score distribution differences across European ancestry populations: implications for breast cancer risk prediction.

Background: The 313-variant polygenic risk score (PRS) provides a promising tool for clinical breast cancer risk prediction. However, evaluation of the PRS across different European populations which could influence risk estimation has not been performed.

Methods: We explored the distribution of PRS across European populations using genotype data from 94,072 females without breast cancer diagnosis, of European-ancestry from 21 countries participating in the Breast Cancer Association Consortium (BCAC) and 223,316 females without breast cancer diagnosis from the UK Biobank.

Evaluation of agreement between common clustering strategies for DNA methylation-based subtyping of breast tumours.

Aims: Clustering algorithms have been widely applied to tumor DNA methylation datasets to define methylation-based cancer subtypes. This study aimed to evaluate the agreement between subtypes obtained from common clustering strategies.

Materials & Methods: We used tumor DNA methylation data from 409 women with breast cancer from the Melbourne Collaborative Cohort Study (MCCS) and 781 breast tumors from The Cancer Genome Atlas (TCGA).

Menopausal hormone therapy: assessing associations with breast and colorectal cancers by familial risk.

Menopausal users of hormone replacement therapy (HRT) are at increased breast cancer risk and decreased colorectal cancer (CRC) risk compared with individuals who have never used HRT, but these opposing associations may differ by familial risk of breast cancer and CRC. We harmonized data from 3 cohorts and generated separate breast cancer and CRC familial risk scores based on cancer family history. We defined moderate or strong family history as a risk score of 0.

Using a behaviour-change approach to support uptake of population genomic screening and management options for breast or prostate cancer.

As the possibility of implementing population genomic screening programs for the risk of developing hereditary cancers in health systems increases, understanding how to support individuals who wish to have genomic screening is essential. This qualitative study aimed to link public perceived barriers to a) taking up the offer of population genomic screening for breast or prostate cancer risk and b) taking up risk-management options following their result, with possible theory-informed behaviour-change approaches that may support implementation. Ten focus groups were conducted with a total of 25 members of the Australian public to identify and then categorise barriers within the behaviour-change Capability, Opportunity, Motivation - Behaviour (COM-B) model.

Epigenetic Ageing and Breast Cancer Risk: A Systematic Review.

Background: Age is one of the strongest risk factors for breast cancer. Measures of biological age based on DNA methylation have gained popularity for their strong association with risk of many diseases, including cancer, which may help to identify high-risk subgroups for targeted prevention.

Methods: We carried out a systematic review of prospective studies that examined the association of methylation-based markers of ageing with risk of invasive breast cancer in healthy (breast cancer-free) women, published up to May 2023.

Physical activity and DNA methylation-based markers of ageing in 6208 middle-aged and older Australians: cross-sectional and longitudinal analyses.

Epigenetic age quantifies biological age using DNA methylation information and is a potential pathway by which physical activity benefits general health. We aimed to assess the cross-sectional and longitudinal associations between physical activity and epigenetic age in middle-aged and older Australians. Blood DNA methylation data for 6208 participants (40% female) in the Melbourne Collaborative Cohort Study (MCCS) were available at baseline (1990-1994, mean age, 59 years) and, of those, for 1009 at follow-up (2003-2007, mean age, 69 years).

Dietary factors and DNA methylation-based markers of ageing in 5310 middle-aged and older Australian adults.

The role of nutrition in healthy ageing is acknowledged but details of optimal dietary composition are still uncertain. We aimed to investigate the cross-sectional associations between dietary exposures, including macronutrient composition, food groups, specific foods, and overall diet quality, with methylation-based markers of ageing. Blood DNA methylation data from 5310 participants (mean age 59 years) in the Melbourne Collaborative Cohort Study were used to calculate five methylation-based measures of ageing: PCGrimAge, PCPhenoAge, DunedinPACE, ZhangAge, TelomereAge.