A prospective case-cohort analysis of plasma metabolites and breast cancer risk.

BACKGROUND: Breast cancer incidence rates have not declined despite an improvement in risk prediction and the identification of modifiable risk factors, suggesting the need to identify novel risk factors and etiological pathways involved in this cancer. Metabolomics has emerged as a promising tool to find circulating metabolites associated with breast cancer risk. METHODS: Untargeted metabolomic analysis was done on prediagnostic plasma samples from a case-cohort study of 1695 incident breast cancer cases and a 1983 women subcohort drawn from Cancer Prevention Study 3. The associations of 868 named metabolites (per one standard deviation increase) with breast cancer were determined using Prentice-weighted Cox proportional hazards regression modeling. RESULTS: A total of 11 metabolites were associated with breast cancer at false discovery rate (FDR) < 0.05 with the majority having inverse association [ranging from RR = 0.85 (95% CI 0.80-0.92) to RR = 0.88 (95% CI 0.82-0.94)] and one having a positive association [RR = 1.14 (95% CI 1.06-1.23)]. An additional 50 metabolites were associated at FDR < 0.20 with inverse associations ranging from RR = 0.88 (95% CI 0.81-0.94) to RR = 0.91 (95% CI 0.85-0.98) and positive associations ranging from RR = 1.13 (95% CI 1.05-1.22) to RR = 1.11 (95% CI 1.02-1.20). Several of these associations validated the findings of previous metabolomic studies. These included findings that several progestogen and androgen steroids were associated with increased risk of breast cancer in postmenopausal women and four phospholipids, and the amino acids glutamine and asparagine were associated with decreased risk of this cancer in pre- and postmenopausal women. Several novel associations were also identified, including a positive association for syringol sulfate, a biomarker for smoked meat, and 3-methylcatechol sulfate and 3-hydroxypyridine glucuronide, which are metabolites of xenobiotics used for the production of pesticides and other products. CONCLUSIONS: Our study validated previous metabolite findings and identified novel metabolites associated with breast cancer risk, demonstrating the utility of large metabolomic studies to provide new leads for understanding breast cancer etiology. Our novel findings suggest that consumption of smoked meats and exposure to catechol and pyridine should be investigated as potential risk factors for breast cancer.

Identification of Genetic Risk Factors for Familial Urinary Bladder Cancer: An Exome Sequencing Study.

PURPOSE: Previous studies have shown an approximately two-fold elevation in the relative risk of urinary bladder cancer (UBC) among people with a family history that could not be entirely explained by shared environmental exposures, thus suggesting a genetic component in its predisposition. Multiple genome-wide association studies and recent gene panel sequencing studies identified several genetic loci that are associated with UBC risk; however, the list of UBC-associated variants and genes is incomplete. MATERIALS AND METHODS: We exome sequenced eight patients from three multiplex UBC pedigrees and a group of 77 unrelated familial UBC cases matched to 241 cancer-free controls. In addition, we examined pathogenic germline variation in 444 candidate genes in 392 The Cancer Genome Atlas UBC cases. RESULTS: In the pedigrees, segregating variants were family-specific although the identified genes clustered in common pathways, most notably DNA repair (MLH1 and MSH2) and cellular metabolism (IDH1 and ME1). In the familial UBC group, the proportion of pathogenic and likely pathogenic variants was significantly higher in cases compared with controls (P = .003). Pathogenic and likely pathogenic variant load was also significantly increased in genes involved in cilia biogenesis (P = .001). In addition, a pathogenic variant in CHEK2 (NM_007194.4:c.1100del; p.T367Mfs*15) was over-represented in cases (variant frequency = 2.6%; 95% CI, 0.71 to 6.52) compared with controls (variant frequency = 0.21%; 95% CI, 0.01 to 1.15), but was not statistically significant. CONCLUSION: These results point to a complex polygenic predisposition to UBC. Despite heterogeneity, the genes cluster in several biologically relevant pathways and processes, for example, DNA repair, cilia biogenesis, and cellular metabolism. Larger studies are required to determine the importance of CHEK2 in UBC etiology.

Association between Smoking Cannabis and Quitting Cigarettes in a Large American Cancer Society Cohort.

BACKGROUND: Cannabis use is increasing, including among smokers, an at-risk population for cancer. Research is equivocal on whether using cannabis inhibits quitting cigarettes. The current longitudinal study investigated associations between smoking cannabis and subsequently quitting cigarettes. METHODS: Participants were 4,535 adult cigarette smokers from a cohort enrolled in the American Cancer Society's Cancer Prevention Study-3 in 2009-2013. Cigarette quitting was assessed on a follow-up survey in 2015-2017, an average of 3.1 years later. Rates of quitting cigarettes at follow-up were examined by retrospectively assessed baseline cannabis smoking status (never, former, recent), and by frequency of cannabis smoking among recent cannabis smokers (low: ≤3 days/month; medium: 4-19 days/month; high: ≥20 days/month). Logistic regression models adjusted for sociodemographic factors, smoking- and health-related behaviors, and time between baseline and follow-up. RESULTS: Adjusted cigarette quitting rates at follow-up did not differ significantly by baseline cannabis smoking status [never 36.2%, 95% confidence interval (CI), 34.5-37.8; former 34.1%, CI, 31.4-37.0; recent 33.6%, CI, 30.1-37.3], nor by frequency of cannabis smoking (low 31.4%, CI, 25.6-37.3; moderate 36.7%, CI, 30.7-42.3; high 34.4%, CI, 28.3-40.2) among recent baseline cannabis smokers. In cross-sectional analyses conducted at follow-up, the proportion of cigarette smokers intending to quit smoking cigarettes in the next 30 days did not differ by cannabis smoking status (P = 0.83). CONCLUSIONS: Results do not support the hypothesis that cannabis smoking inhibits quitting cigarette smoking among adults. IMPACT: Future longitudinal research should include follow-ups of >1 year, and assess effects of intensity/frequency of cannabis use and motivation to quit on smoking cessation.

Risk of Late-Onset Breast Cancer in Genetically Predisposed Women.

PURPOSE: The prevalence of germline pathogenic variants (PVs) in established breast cancer predisposition genes in women in the general population over age 65 years is not well-defined. However, testing guidelines suggest that women diagnosed with breast cancer over age 65 years might have < 2.5% likelihood of a PV in a high-penetrance gene. This study aimed to establish the frequency of PVs and remaining risks of breast cancer for each gene in women over age 65 years. METHODS: A total of 26,707 women over age 65 years from population-based studies (51.5% with breast cancer and 48.5% unaffected) were tested for PVs in germline predisposition gene. Frequencies of PVs and associations between PVs in each gene and breast cancer were assessed, and remaining lifetime breast cancer risks were estimated for non-Hispanic White women with PVs. RESULTS: The frequency of PVs in predisposition genes was 3.18% for women with breast cancer and 1.48% for unaffected women over age 65 years. PVs in BRCA1, BRCA2, and PALB2 were found in 3.42% of women diagnosed with estrogen receptor (ER)-negative, 1.0% with ER-positive, and 3.01% with triple-negative breast cancer. Frequencies of PVs were lower among women with no first-degree relatives with breast cancer. PVs in CHEK2, PALB2, BRCA2, and BRCA1 were associated with increased risks (odds ratio = 2.9-4.0) of breast cancer. Remaining lifetime risks of breast cancer were ≥ 15% for those with PVs in BRCA1, BRCA2, and PALB2. CONCLUSION: This study suggests that all women diagnosed with triple-negative breast cancer or ER-negative breast cancer should receive genetic testing and that women over age 65 years with BRCA1 and BRCA2 PVs and perhaps with PALB2 and CHEK2 PVs should be considered for magnetic resonance imaging screening.

Author Correction: A case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-23162-4.

A case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers.

Breast cancer (BC) risk for BRCA1 and BRCA2 mutation carriers varies by genetic and familial factors. About 50 common variants have been shown to modify BC risk for mutation carriers. All but three, were identified in general population studies. Other mutation carrier-specific susceptibility variants may exist but studies of mutation carriers have so far been underpowered. We conduct a novel case-only genome-wide association study comparing genotype frequencies between 60,212 general population BC cases and 13,007 cases with BRCA1 or BRCA2 mutations. We identify robust novel associations for 2 variants with BC for BRCA1 and 3 for BRCA2 mutation carriers, P < 10-8, at 5 loci, which are not associated with risk in the general population. They include rs60882887 at 11p11.2 where MADD, SP11 and EIF1, genes previously implicated in BC biology, are predicted as potential targets. These findings will contribute towards customising BC polygenic risk scores for BRCA1 and BRCA2 mutation carriers.

A Metabolomics Analysis of Postmenopausal Breast Cancer Risk in the Cancer Prevention Study II.

Breast cancer is the most common cancer in women, but its incidence can only be partially explained through established risk factors. Our aim was to use metabolomics to identify novel risk factors for breast cancer and to validate recently reported metabolite-breast cancer findings. We measured levels of 1275 metabolites in prediagnostic serum in a nested case-control study of 782 postmenopausal breast cancer cases and 782 matched controls. Metabolomics analysis was performed by Metabolon Inc using ultra-performance liquid chromatography and a Q-Exactive high resolution/accurate mass spectrometer. Controls were matched by birth date, date of blood draw, and race/ethnicity. Odds ratios (ORs) and 95% confidence intervals (CIs) of breast cancer at the 90th versus 10th percentile (modeled on a continuous basis) of metabolite levels were estimated using conditional logistic regression, with adjustment for age. Twenty-four metabolites were significantly associated with breast cancer risk at a false discovery rate <0.20. For the nine metabolites positively associated with risk, the ORs ranged from 1.75 (95% CI: 1.29-2.36) to 1.45 (95% CI: 1.13-1.85), and for the 15 metabolites inversely associated with risk, ORs ranged from 0.59 (95% CI: 0.43-0.79) to 0.69 (95% CI: 0.55-0.87). These metabolites largely comprised carnitines, glycerolipids, and sex steroid metabolites. Associations for three sex steroid metabolites validated findings from recent studies and the remainder were novel. These findings contribute to growing data on metabolite-breast cancer associations by confirming prior findings and identifying novel leads for future validation efforts.

Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction.

Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction.

A Population-Based Study of Genes Previously Implicated in Breast Cancer.

BACKGROUND: Population-based estimates of the risk of breast cancer associated with germline pathogenic variants in cancer-predisposition genes are critically needed for risk assessment and management in women with inherited pathogenic variants. METHODS: In a population-based case-control study, we performed sequencing using a custom multigene amplicon-based panel to identify germline pathogenic variants in 28 cancer-predisposition genes among 32,247 women with breast cancer (case patients) and 32,544 unaffected women (controls) from population-based studies in the Cancer Risk Estimates Related to Susceptibility (CARRIERS) consortium. Associations between pathogenic variants in each gene and the risk of breast cancer were assessed. RESULTS: Pathogenic variants in 12 established breast cancer-predisposition genes were detected in 5.03% of case patients and in 1.63% of controls. Pathogenic variants in BRCA1 and BRCA2 were associated with a high risk of breast cancer, with odds ratios of 7.62 (95% confidence interval [CI], 5.33 to 11.27) and 5.23 (95% CI, 4.09 to 6.77), respectively. Pathogenic variants in PALB2 were associated with a moderate risk (odds ratio, 3.83; 95% CI, 2.68 to 5.63). Pathogenic variants in BARD1, RAD51C, and RAD51D were associated with increased risks of estrogen receptor-negative breast cancer and triple-negative breast cancer, whereas pathogenic variants in ATM, CDH1, and CHEK2 were associated with an increased risk of estrogen receptor-positive breast cancer. Pathogenic variants in 16 candidate breast cancer-predisposition genes, including the c.657_661del5 founder pathogenic variant in NBN, were not associated with an increased risk of breast cancer. CONCLUSIONS: This study provides estimates of the prevalence and risk of breast cancer associated with pathogenic variants in known breast cancer-predisposition genes in the U.S. population. These estimates can inform cancer testing and screening and improve clinical management strategies for women in the general population with inherited pathogenic variants in these genes. (Funded by the National Institutes of Health and the Breast Cancer Research Foundation.).

Plasma Metabolomic Profiles and Risk of Advanced and Fatal Prostate Cancer.

BACKGROUND: Little is known about the underlying molecular mechanisms of prostate cancer, especially advanced and fatal prostate cancer. OBJECTIVE: To examine associations of prediagnostic plasma metabolomic profiles with advanced and fatal prostate cancer. DESIGN, SETTING, AND PARTICIPANTS: In a case-cohort study of the Cancer Prevention Study-II Nutrition Cohort, of 14 210 cancer-free men with a blood sample in 1998-2001, 129 were diagnosed with advanced prostate cancer (T3-T4 or N1 or M1) through June 2013 and 112 died from prostate cancer through December 2014. Plasma samples from advanced and fatal cases, and a randomly selected subcohort of 347 men were metabolically profiled using untargeted mass spectroscopy-based platforms. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Prentice-weighted Cox proportional hazards regression models were used to assess associations of 699 known metabolites with advanced and fatal prostate cancer. RESULTS AND LIMITATIONS: Two metabolites derived from fatty acid metabolism (ethylmalonate and butyrylcarnitine), aspartate, sphingomyelin (d18:1/18:0), and two γ-glutamyl amino acids (γ-glutamylmethionine and γ-glutamylglutamine) were statistically significantly associated (false discovery rate <0.2) with fatal prostate cancer. One standard deviation (SD) increase in each γ-glutamyl amino acid was associated with 34-38% decreased risk, whereas one SD increase in each of the other metabolites was associated with 45-53% increased risk. A metabolic risk score based on four of these metabolites (excluding butyrylcarnitine and γ-glutamylglutamine, which were not independent predictors) was strongly associated with fatal prostate cancer (relative risk per SD: 2.72, 95% confidence interval: 2.05-3.60). No metabolites were statistically significantly associated with advanced prostate cancer. These results were observational and may not be causal. CONCLUSIONS: These findings identified metabolic pathways that are altered in the development of fatal prostate cancer. Further research into these pathways may provide insights into the etiology of fatal prostate cancer. PATIENT SUMMARY: In a large follow-up study of cancer-free men, those with a certain metabolomic profile had a higher risk of dying from prostate cancer.

Combined Associations of a Polygenic Risk Score and Classical Risk Factors With Breast Cancer Risk.

We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer.

Low-frequency variation near common germline susceptibility loci are associated with risk of Ewing sarcoma.

BACKGROUND: Ewing sarcoma (EwS) is a rare, aggressive solid tumor of childhood, adolescence and young adulthood associated with pathognomonic EWSR1-ETS fusion oncoproteins altering transcriptional regulation. Genome-wide association studies (GWAS) have identified 6 common germline susceptibility loci but have not investigated low-frequency inherited variants with minor allele frequencies below 5% due to limited genotyped cases of this rare tumor. METHODS: We investigated the contribution of rare and low-frequency variation to EwS susceptibility in the largest EwS genome-wide association study to date (733 EwS cases and 1,346 unaffected controls of European ancestry). RESULTS: We identified two low-frequency variants, rs112837127 and rs2296730, on chromosome 20 that were associated with EwS risk (OR = 0.186 and 2.038, respectively; P-value < 5×10-8) and located near previously reported common susceptibility loci. After adjusting for the most associated common variant at the locus, only rs112837127 remained a statistically significant independent signal (OR = 0.200, P-value = 5.84×10-8). CONCLUSIONS: These findings suggest rare variation residing on common haplotypes are important contributors to EwS risk. IMPACT: Motivate future targeted sequencing studies for a comprehensive evaluation of low-frequency and rare variation around common EwS susceptibility loci.

Transcriptome-wide association study of breast cancer risk by estrogen-receptor status.

Previous transcriptome-wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome-wide association studies (GWAS), but analyses of breast cancer subtype-specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta-analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER-). We further compared associations with ER+ and ER- subtypes, using a case-only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER- breast cancer. We further identified 30 TWAS-significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast-cancer gene in three of six regions harboring multiple TWAS-significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER- breast cancer.

Metabolomic Profiles Associated with BMI, Waist Circumference, and Diabetes and Inflammation Biomarkers in Women.

OBJECTIVE: This study was undertaken to identify metabolites associated with BMI and waist circumference (WC) in women and to determine whether these metabolites are associated with biomarkers of metabolic health. METHODS: Untargeted metabolomic analysis was done on serum from 1,534 women. Metabolites associated with BMI and WC were identified using linear regression with a Bonferroni-corrected P value. Clustered blocks of these metabolites were then defined whose association with the anthropometric measures could be represented by a single metabolite. The association of these representative metabolites with biomarkers for diabetes and inflammation was then determined. RESULTS: About one-third of 781 metabolites included in the analyses were associated with BMI and/or WC. Associations were found for some novel metabolites, including several sphingolipids, nucleotides, and modified fatty acids. Among metabolites most strongly inversely associated with BMI, the choline-containing plasmalogen (O-16:0/18:1) (ß = -0.30, P = 6.62 × 10-32 ) was also inversely associated with c-peptide and positively associated with adiponectin. Adjustment for BMI attenuated the metabolite-biomarker associations more for hemoglobin A1c (> 100%) and c-peptide (58.8% to > 100%) than for C-reactive protein (10.5%-40.0%) and adiponectin (7.0%-30.4%). CONCLUSIONS: These results add to the list of metabolites associated with adiposity and indicate that some may influence processes that contribute to the development of obesity-related diseases.

Metabolomic markers of healthy dietary patterns in US postmenopausal women.

BACKGROUND: Healthy diet patterns are associated with lower risk of cancer and other chronic diseases. Metabolomics has the potential to expand dietary biomarker development to include dietary patterns, which may provide a complement or alternative to self-reported diet. OBJECTIVE: This study examined the correlation of serum untargeted metabolomic markers with 4 diet pattern scores-the alternate Mediterranean diet score (aMED), alternate Healthy Eating Index (AHEI)-2010, the Dietary Approaches to Stop Hypertension (DASH) diet, and the Healthy Eating Index (HEI)-2015-and used multivariate methods to identify discriminatory metabolites for each pattern. METHODS: Among 1367 US postmenopausal women with serum metabolomic data in the Cancer Prevention Study-II Nutrition Cohort, we conducted partial correlation analysis, adjusted for demographic and lifestyle variables, to examine cross-sectional correlations between serum metabolomic markers and healthy diet pattern scores. In a randomly selected "training" set (50%), we conducted orthogonal partial least-squares discriminant analysis to identify metabolites that discriminated the top from bottom diet score quintiles. Combinations of metabolites with a variable importance in projection (VIP) score ≥2.5 were tested for predictability in the "testing" set based on the use of receiver operating characteristic curves. RESULTS: Out of 1186 metabolites, 32 unique metabolites were considered discriminatory based on a VIP score ≥2.5 in the training dataset with some overlap across scores (aMED = 16; AHEI = 17; DASH = 13; HEI = 12). Spearman partial correlation analyses, applying a cut-point (|r| ≥ 0.15) and Bonferroni correction (P < 1.05 × 10-5), identified similar key metabolites. The top 5 metabolites for each pattern mostly distinguished high compared with low scores; 4 of the 5 (fish-derived) metabolites were the same for aMED and AHEI, 2 of which were identified for HEI; 4 DASH metabolites were unique. CONCLUSIONS: Metabolomic methods that used a split-sample approach identified potential biomarkers for 4 healthy diet patterns. Similar metabolites across scores reflect fish consumption in healthy dietary patterns. These findings should be replicated in independent populations.

Anthropometric factors and risk of myeloid leukaemias and myelodysplastic syndromes: a prospective study and meta-analysis.

There is insufficient evidence linking excess body weight to risk of myeloid malignancies. We investigated this association using data from the Cancer Prevention Study-II (CPS-II), and a meta-analysis of published cohort studies. Among 152 090 CPS-II participants, 387 acute myeloid leukaemias (AML), 100 chronic myeloid leukaemias (CML) and 170 MDS were identified over 21 years of follow-up. In CPS-II, body mass index (BMI) was weakly associated with risk of CML (hazard ratio [HR] = 1·04, 95% confidence interval [CI]: 0·99-1·09 per 1 unit increase in BMI), AML (HR = 1·01, 95% CI: 0·98-1·03) and MDS (HR = 1·03, 95% CI: 0·99-1·07). After controlling for other anthropometric factors, no clear association was observed for height, BMI at age 18 years or weight change. In the meta-analysis (n = 7117 myeloid leukaemias), BMI 25-29·9 kg/m2 (HRpooled  = 1·36, 95% CI: 1·12-1·59) and BMI ≥30 kg/m2 (HRpooled  = 1·43, 95% CI: 1·18-1·69) were associated with higher risk of myeloid leukaemia overall, compared to a BMI <25 kg/m2 . Likewise, BMI ≥25 kg/m2 was positively associated with both AML and CML risk individually in the meta-analysis. These results underscore the need for large studies to detect associations with rare cancers, and show a modest, but positive association between excess body weight and myeloid malignancy risk.

Genome-wide association and transcriptome studies identify target genes and risk loci for breast cancer.

Genome-wide association studies (GWAS) have identified more than 170 breast cancer susceptibility loci. Here we hypothesize that some risk-associated variants might act in non-breast tissues, specifically adipose tissue and immune cells from blood and spleen. Using expression quantitative trait loci (eQTL) reported in these tissues, we identify 26 previously unreported, likely target genes of overall breast cancer risk variants, and 17 for estrogen receptor (ER)-negative breast cancer, several with a known immune function. We determine the directional effect of gene expression on disease risk measured based on single and multiple eQTL. In addition, using a gene-based test of association that considers eQTL from multiple tissues, we identify seven (and four) regions with variants associated with overall (and ER-negative) breast cancer risk, which were not reported in previous GWAS. Further investigation of the function of the implicated genes in breast and immune cells may provide insights into the etiology of breast cancer.