Analysis of Urinary Iodine Concentration in Differentiated Thyroid Cancer and Breast Cancer Cases.

Iodine intake can affect thyroid and breast cells, and urinary iodine concentration (UIC) is an effective biomarker for iodine intake. OBJECTIVES: This study aimed to analyze the correlation between urinary iodine concentration in differentiated thyroid cancer (DTC) and breast cancer (BC) subjects. METHODS: The study consisted of 80 subjects divided into case (20 DTC and 20 BC subjects) and control (40 subjects). Morning urine or spot urine was used for UIC measurement. RESULTS: In thyroid cancer, UIC median patients and controls were 195.45 ± 133.61 µg/L and 145 ± 39.64 µg/L, respectively, with p =0.33. The UIC median of PTC subjects was significantly higher compared to FTC subjects, 227.12±130.98 µg/L versus 68.75±22.95 µg/L, p=0.00, and papillary thyroid cancer is closely related to a high iodine excretion in urine with contingency coefficient  (c)=0.722. In BC patients, regardless of subtypes, breast cancer subjects showed a significantly lower iodine excretion level. The median of UIC patients and controls were 80.05 ± 38.24 µg/L and 144.25 ± 36.79 µg/L, respectively, p=0.000. CONCLUSIONS: Iodine urine concentrations strongly correlate with the type of DTC histopathology, and in BC subjects, IUC was significantly lower compared to the control.

Deep learning-assisted monitoring of trastuzumab efficacy in HER2-Overexpressing breast cancer via SERS immunoassays of tumor-derived urinary exosomal biomarkers.

Monitoring drug efficacy is significant in the current concept of companion diagnostics in metastatic breast cancer. Trastuzumab, a drug targeting human epidermal growth factor receptor 2 (HER2), is an effective treatment for metastatic breast cancer. However, some patients develop resistance to this therapy; therefore, monitoring its efficacy is essential. Here, we describe a deep learning-assisted monitoring of trastuzumab efficacy based on a surface-enhanced Raman spectroscopy (SERS) immunoassay against HER2-overexpressing mouse urinary exosomes. Individual Raman reporters bearing the desired SERS tag and exosome capture substrate were prepared for the SERS immunoassay; SERS tag signals were collected to prepare deep learning training data. Using this deep learning algorithm, various complicated mixtures of SERS tags were successfully quantified and classified. Exosomal antigen levels of five types of cell-derived exosomes were determined using SERS-deep learning analysis and compared with those obtained via quantitative reverse transcription polymerase chain reaction and western blot analysis. Finally, drug efficacy was monitored via SERS-deep learning analysis using urinary exosomes from trastuzumab-treated mice. Use of this monitoring system should allow proactive responses to any treatment-resistant issues.

Enhancing breast cancer screening with urinary biomarkers and Random Forest supervised classification: A comprehensive investigation.

OBJECTIVES: Urinary sex hormones are investigated as potential biomarkers for the early detection of breast cancer, aiming to evaluate their relevance and applicability, in combination with supervised machine-learning data analysis, toward the ultimate goal of extensive screening. METHODS: Sex hormones were determined on urine samples collected from 250 post-menopausal women (65 healthy - 185 with breast cancer, recruited among the clinical patients of Candiolo Cancer Institute FPO-IRCCS (Torino, Italy). Two analytical procedures based on UHPLC-MS/HRMS were developed and comprehensively validated to quantify 20 free and conjugated sex hormones from urine samples. The quantitative data were processed by seven machine learning algorithms. The efficiency of the resulting models was compared. RESULTS: Among the tested models aimed to relate urinary estrogen and androgen levels and the occurrence of breast cancer, Random Forest (RF) proved to underscore all the other supervised classification approaches, including Partial Least Squares - Discriminant Analysis (PLS-DA), in terms of effectiveness and robustness. The final optimized model built on only five biomarkers (testosterone-sulphate, alpha-estradiol, 4-methoxyestradiol, DHEA-sulphate, and epitestosterone-sulphate) achieved an approximate 98% diagnostic accuracy on replicated validation sets. To balance the less-represented population of healthy women, a Synthetic Minority Oversampling TEchnique (SMOTE) data oversampling approach was applied. CONCLUSIONS: By means of tunable hyperparameters optimization, the RF algorithm showed great potential for early breast cancer detection, as it provides clear biomarkers ranking and their relative efficiency, allowing to ground the final diagnostic model on a restricted selection five steroid biomarkers only, as desirable for noninvasive tests with wide screening purposes.

Fragmentation patterns of cell-free DNA and somatic mutations in the urine of metastatic breast cancer patients.

BACKGROUND: Urinary cell-free deoxyribonucleic acid (DNA) (ucfDNA) holds promise as a biomarker; however, its potential remains largely unexplored. We examined the fragmentation pattern of ucfDNA and identified somatic mutations within urine samples from metastatic breast cancer (MBC) patients. METHODS: Urine and blood specimens were collected before treatment from 45 MBC patients and posttreatment urine samples from 16 of the 45 patients at the China National Cancer Center. Somatic mutations and tumor mutational burden (TMB) in the urine and plasma of 10 patients were analyzed by next-generation sequencing (NGS). Fragmentation patterns of cfDNA were displayed using electropherograms. Differences in the extracted amount of cfDNA, length of cfDNA fragments, and TMB between urine and plasma were compared using a Wilcoxon test. RESULTS: The fragmentation patterns of ucfDNA were categorized as follows: (1) profile A (n = 26) containing a short peak (100-200 bp) and a long peak (>1500 bp); (2) profile B (n = 8) containing only a long peak; and (3) profile C (n = 11) containing flat pattern. For profile A patients, the short-peaked ucfDNA circulating in the bloodstream was much shorter compared with plasma cfDNA (149 vs. 171 bp, Wilcoxon test, P = 0.023). The fragmentation patterns in lung metastasis patients exhibited a higher propensity toward profile C ( P = 0.002). After treatment, 87.5% of the patients exhibited consistent fragmentation patterns. The concordance rate for somatic mutations in the plasma and urine was 30%, and the median TMB of urine and plasma was not significantly different. CONCLUSIONS: This study established a fragmentation pattern for ucfDNA and detected somatic mutations in the urine of MBC patients. These results suggest the potential application of ucfDNA as a biomarker for MBC.

Associations of Circulating Estrogens and Estrogen Metabolites with Fecal and Oral Microbiome in Postmenopausal Women in the Ghana Breast Health Study.

The human fecal and oral microbiome may play a role in the etiology of breast cancer through modulation of endogenous estrogen metabolism. This study aimed to investigate associations of circulating estrogens and estrogen metabolites with the fecal and oral microbiome in postmenopausal African women. A total of 117 women with fecal (N = 110) and oral (N = 114) microbiome data measured by 16S rRNA gene sequencing, and estrogens and estrogen metabolites data measured by liquid chromatography tandem mass spectrometry were included. The outcomes were measures of the microbiome and the independent variables were the estrogens and estrogen metabolites. Estrogens and estrogen metabolites were associated with the fecal microbial Shannon index (global P < 0.01). In particular, higher levels of estrone (ß = 0.36, P = 0.03), 2-hydroxyestradiol (ß = 0.30, P = 0.02), 4-methoxyestrone (ß = 0.51, P = 0.01), and estriol (ß = 0.36, P = 0.04) were associated with higher levels of the Shannon index, while 16alpha-hydroxyestrone (ß = -0.57, P < 0.01) was inversely associated with the Shannon index as indicated by linear regression. Conjugated 2-methoxyestrone was associated with oral microbial unweighted UniFrac as indicated by MiRKAT (P < 0.01) and PERMANOVA, where conjugated 2-methoxyestrone explained 2.67% of the oral microbial variability, but no other estrogens or estrogen metabolites were associated with any other beta diversity measures. The presence and abundance of multiple fecal and oral genera, such as fecal genera from families Lachnospiraceae and Ruminococcaceae, were associated with several estrogens and estrogen metabolites as indicated by zero-inflated negative binomial regression. Overall, we found several associations of specific estrogens and estrogen metabolites and the fecal and oral microbiome. IMPORTANCE Several epidemiologic studies have found associations of urinary estrogens and estrogen metabolites with the fecal microbiome. However, urinary estrogen concentrations are not strongly correlated with serum estrogens, a known risk factor for breast cancer. To better understand whether the human fecal and oral microbiome were associated with breast cancer risk via the regulation of estrogen metabolism, we conducted this study to investigate the associations of circulating estrogens and estrogen metabolites with the fecal and oral microbiome in postmenopausal African women. We found several associations of parent estrogens and several estrogen metabolites with the microbial communities, and multiple individual associations of estrogens and estrogen metabolites with the presence and abundance of multiple fecal and oral genera, such as fecal genera from families Lachnospiraceae and Ruminococcaceae, which have estrogen metabolizing properties. Future large, longitudinal studies to investigate the dynamic changes of the fecal and oral microbiome and estrogen relationship are needed.

Urinary concentration of endocrine-disrupting phthalates and breast cancer risk in Indian women: A case-control study with a focus on mutations in phthalate-responsive genes.

BACKGROUND: Phthalates are known endocrine-disrupting chemicals used indiscriminately as constituents in consumer products including food processing, and packaging, cosmetics, personal care and household items. Although, few studies have assessed the risk of breast cancer on exposure to phthalates, their association with breast cancer risk in Indian women have not yet been evaluated. METHODS: We conducted a case-control study involving 171 participants. Urinary concentrations of six phthalate dieters; DMP (Dimethyl phthalate), DEP (Diethyl phthalate), DBP (Dibutyl phthalate), BBP (benzyl butyl phthalate), DEHP (Di-2-ethyl-hexyl phthalate), DINOP (Di-n-octyl phthalate) were estimated by GC-MS and geometric means were calculated. Univariate and multivariable logistic regression was performed to assess breast cancer risk on exposure to phthalates. Genes responsive to phthalates were identified through literature search and matched with NGS data, and gene-enrichment analysis was performed. RESULTS: Significant associations were observed between urinary phthalate concentrations and increased risk of breast cancer for di-butyl phthalate (OR=1.5, 95% CI; 1.06, 2.11, p = 0.002) and di-2-ethyl-hexyl phthalate (>median vs ≤ median; OR=2.97, 95% CI; 1.18, 7.47, p = 0.005) in multivariable analyses. We also found several phthalate-responsive gene mutations in paired breast tumor tissues, which include PTPRD (76.19%), AR (42.86%), CYP1A1 (42.86%), CYP19A1 (23.81%), AHRR (19.05%), PIK3CA (19.05%), CYP1B1 (9.52%), RB1 (9.52%) and MMP9 (9.52%). Gene-enrichment analysis revealed that these genes form a major part of ER/PR, PPAR and HIF-1α-TGF-ß signaling cascades involved in breast cancer CONCLUSION: Although the sample size is small, in this first case-control study from India, DBP and DEHP were found to be associated with increased risk of invasive breast cancer and tumor tissues revealed mutations in several phthalate-responsive genes. It is, therefore suggested that human biomonitoring in India and larger studies evaluating the early life genetic and epigenetic alterations on phthalates exposure are required to establish their role in breast carcinogenesis.

Establishing pteridine metabolism in a progressive isogenic breast cancer cell model - part II.

INTRODUCTION: Determining the biological significance of pteridines in cancer development and progression remains an important step in understanding the altered levels of urinary pteridines seen in certain cancers. Our companion study revealed that several folate-derived pteridines and lumazines correlated with tumorigenicity in an isogenic, progressive breast cancer cell model, providing direct evidence for the tumorigenic origin of pteridines. OBJECTIVES: This study sought to elucidate the pteridine biosynthetic pathway in a progressive breast cancer model via direct pteridine dosing to determine how pteridine metabolism changes with tumorigenicity. METHODS: First, MCF10AT breast cancer cells were dosed individually with 15 pteridines to determine which pteridines were being metabolized and what metabolic products were being produced. Second, pteridines that were significantly metabolized were dosed individually across the progressive breast cancer cell model (MCF10A, MCF10AT, and MCF10ACA1a) to determine the relationship between each metabolic reaction and breast cancer tumorigenicity. RESULTS: Several pteridines were found to have altered metabolism in breast cancer cell lines, including pterin, isoxanthopterin, xanthopterin, sepiapterin, 6-biopterin, lumazine, and 7-hydroxylumazine (p < 0.05). In particular, isoxanthopterin and 6-biopterin concentrations were differentially expressed (p < 0.05) with respect to tumorigenicity following dosing with pterin and sepiapterin, respectively. Finally, the pteridine biosynthetic pathway in breast cancer cells was proposed based on these findings. CONCLUSIONS: This study, along with its companion study, demonstrates that pteridine metabolism becomes disrupted in breast cancer tumor cells. This work highlights several key metabolic reactions within the pteridine biosynthetic pathway that may be targeted for further investigation and clinical applications.

A prediction model using 2-propanol and 2-butanone in urine distinguishes breast cancer.

Safe and noninvasive methods for breast cancer screening with improved accuracy are urgently needed. Volatile organic compounds (VOCs) in biological samples such as breath and blood have been investigated as noninvasive novel markers of cancer. We investigated volatile organic compounds in urine to assess their potential for the detection of breast cancer. One hundred and ten women with biopsy-proven breast cancer and 177 healthy volunteers were enrolled. The subjects were divided into two groups: a training set and an external validation set. Urine samples were collected and analyzed by gas chromatography and mass spectrometry. A predictive model was constructed by multivariate analysis, and the sensitivity and specificity of the model were confirmed using both a training set and an external set with reproducibility tests. The training set included 60 breast cancer patients (age 34-88 years, mean 60.3) and 60 healthy controls (age 34-81 years, mean 58.7). The external validation set included 50 breast cancer patients (age 35-85 years, mean 58.8) and 117 healthy controls (age 18-84 years, mean 51.2). One hundred and ninety-one compounds detected in at least 80% of the samples from the training set were used for further analysis. The predictive model that best-detected breast cancer at various clinical stages was constructed using a combination of two of the compounds, 2-propanol and 2-butanone. The sensitivity and specificity in the training set were 93.3% and 83.3%, respectively. Triplicated reproducibility tests were performed by randomly choosing ten samples from each group, and the results showed a matching rate of 100% for the breast cancer patient group and 90% for the healthy control group. Our prediction model using two VOCs is a useful complement to the current diagnostic tools. Further studies inclusive of benign tumors and non-breast malignancies are warranted.

Bisphenol-A in biological samples of breast cancer mastectomy and mammoplasty patients and correlation with levels measured in urine and tissue.

Endocrine disrupting chemicals (EDCs) are organic compounds that have estrogenic activity and can interfere with the endocrine system. Bisphenol-A (BPA) is one of these compounds which possess a potential risk for breast cancer. The aim of this research was to evaluate BPA concentration in both the urine and breast adipose tissue samples of breast cancer mastectomy and mammoplasty patients and study correlations of BPA levels in breast adipose tissue with urine samples in the both groups. Urine and breast adipose tissue samples from 41 breast cancer mastectomy and 11 mammoplasty patients were taken. BPA concentrations were detected using an ELISA assay. Urinary BPA concentrations were significantly higher in cancerous patients (2.12 ± 1.48 ng/ml; P < 0.01) compared to non-cancerous (0.91 ± 0.42 ng/ml). Likewise, tissue BPA concentrations in cancerous patients (4.20 ± 2.40 ng/g tissue; P < 0.01) were significantly higher than non- cancerous (1.80 ± 1.05 ng/g tissue). Urinary BPA concentrations were positively correlated with breast adipose tissue BPA in the case group (P < 0.001, R = 0.896). We showed that BPA was present in urine and breast adipose tissue samples of the studied populations. With regard to higher BPA mean concentration in cancerous patients than non-cancerous individuals in this study, BPA might increase the risk of breast cancer incidence.

An integrative approach based on GC-qMS and NMR metabolomics data as a comprehensive strategy to search potential breast cancer biomarkers.

INTRODUCTION: Globally, breast cancer (BC) is leading at the top of women's diseases and, as a multifactorial disease, there is the need for the development of new approaches to aid clinicians on monitoring BC treatments. In this sense, metabolomic studies have become an essential tool allowing the establishment of interdependency among metabolites in biological samples. OBJECTIVE: The combination of nuclear magnetic resonance (NMR) and gas chromatography-quadrupole mass spectrometry (GC-qMS) based metabolomic analyses of urine and breast tissue samples from BC patients and cancer-free individuals was used. METHODS: Multivariate statistical tools were used in order to obtain a panel of metabolites that could discriminate malignant from healthy status assisting in the diagnostic field. Urine samples (n = 30), cancer tissues (n = 30) were collected from BC patients, cancer-free tissues were resected outside the tumor margin from the same donors (n = 30) while cancer-free urine samples (n = 40) where obtained from healthy subjects and analysed by NMR and GC-qMS methodologies. RESULTS: The orthogonal partial least square discriminant analysis model showed a clear separation between BC patients and cancer-free subjects for both classes of samples. Specifically, for urine samples, the goodness of fit (R2Y) and predictive ability (Q2) was 0.946 and 0.910, respectively, whereas for tissue was 0.888 and 0.813, revealing a good predictable accuracy. The discrimination efficiency and accuracy of tissue and urine metabolites was ascertained by receiver operating characteristic curve analysis that allowed the identification of metabolites with high sensitivity and specificity. The metabolomic pathway analysis identified several dysregulated pathways in BC, including those related with lactate, valine, aspartate and glutamine metabolism. Additionally, correlations between urine and tissue metabolites were investigated and five metabolites (e.g. acetone, 3-hexanone, 4-heptanone, 2-methyl-5-(methylthio)-furan and acetate) were found to be significant using a dual platform approach. CONCLUSION: Overall, this study suggests that an improved metabolic profile combining NMR and GC-qMS may be useful to achieve more insights regarding the mechanisms underlying cancer.

C. elegans-based chemosensation strategy for the early detection of cancer metabolites in urine samples.

Chemosensory receptors play a crucial role in distinguishing the wide range of volatile/soluble molecules by binding them with high accuracy. Chemosensation is the main sensory modality in organisms lacking long-range sensory mechanisms like vision/hearing. Despite its low number of sensory neurons, the nematode Caenorhabditis elegans possesses several chemosensory receptors, allowing it to detect about as many odorants as mammals. Here, we show that C. elegans displays attraction towards urine samples of women with breast cancer, avoiding control ones. Behavioral assays on animals lacking AWC sensory neurons demonstrate the relevance of these neurons in sensing cancer odorants: calcium imaging on AWC increases the accuracy of the discrimination (97.22%). Also, chemotaxis assays on animals lacking GPCRs expressed in AWC allow to identify receptors involved in binding cancer metabolites, suggesting that an alteration of a few metabolites is sufficient for the cancer discriminating behavior of C. elegans, which may help identify a fundamental fingerprint of breast cancer.

Risk of breast cancer and prediagnostic urinary excretion of bisphenol A, triclosan and parabens: The Multiethnic Cohort Study.

Exposure to bisphenol A (BPA), triclosan and parabens is widespread but their impact on breast cancer risk remains unclear. This nested case-control study investigated endocrine-disrupting chemicals (EDCs) and breast cancer risk within the Multiethnic Cohort (MEC). We measured prediagnostic urinary BPA, triclosan and parabens in 1032 postmenopausal women with breast cancer (48 African American, 77 Latino, 155 Native Hawaiian, 478 Japanese American and 274 White) and 1030 individually matched controls, using a sensitive and validated liquid chromatography mass spectrometry assay. Conditional logistic regression was used to examine risk with these EDCs with adjustment for creatinine and potential confounders. In all women, breast cancer risk was not associated with BPA (Ptrend  = 0.53) and was inversely associated with triclosan (ORT3 vs T1  = 0.83, 95% CI: 0.66-1.04, Ptrend  = 0.045) and total parabens (ORT3 vs T1  = 0.77, 95% CI: 0.62-0.97, Ptrend  = 0.03). While risk of hormone receptor positive (HR+) cancer was 20% to 23% lower among women in the upper two tertiles of paraben exposure (Ptrend  = 0.02), risk of HR negative (HR-) was reduced 27% but only among those in the upper tertile of exposure. Although risk associations did not differ significantly by ethnicity or by body mass index (BMI), the inverse association with triclosan was observed mainly among overweight/obese women (ORT3 vs T1  = 0.76, 95% CI: 0.56-1.02, Ptrend  = 0.02). In summary, breast cancer risk in a multiethnic population was unrelated to BPA and was weakly inversely associated with triclosan and paraben exposures. Studies with multiple urine samples collected before breast cancer diagnosis are needed to further investigate these EDCs and breast cancer risk.

Exposure of bisphenol A in breast cancer patients-quantitatively assessed by sensitivity-enhanced high-performance liquid chromatography coupled with fluorescence detection: A case-control study.

A simple, reproducible and sensitive liquid chromatography (HPLC) method has been developed and validated for estimation of bisphenol A (BPA) in human urine. A simple liquid-liquid extraction technique was used in BPA sample preparation. The analyte was chromatographed on a Shimadzu Prominence HPLC system using isocratic mobile phase conditions at a flow rate of 0.500 ml/min and a Hypersil Gold C18 column maintained at 40°C. Quantification was performed on a fluorescence detector set at excitation 275 nm, emission 313 nm and bisphenol B was used as internal standard. The total run time was 8 min. The method was found to have acceptable sensitivity, selectivity, accuracy (98.82-103.64%), precision (1.17-5.36) and stability in the validation experiment carried out as per the USFDA guidelines. The method sensitivity was as low as 0.50 ng/ml. The applicability of the validated analytical method was established in human patient urine samples. The mean human urine BPA concentrations were 1.18 ± 2.11 ng/ml in the control group and 5.76 ± 6.00 ng/ml in the patient group (P < 0.001). Therefore, this method could be considered as an alternative for routine bio-monitoring of BPA which is less expensive and feasible in resource-poor settings.

Zinc stable isotopes in urine as diagnostic for cancer of secretory organs.

Breast, prostate, and pancreatic cancers alter the zinc (Zn) metabolism. Combined analyses of urinary Zn concentrations [Zn] and Zn stable isotope compositions (δ66Zn) may provide a non-invasive approach for tracing malignancy-induced Zn dyshomeostasis. In this study, we measured [Zn] and δ66Zn in urine from prostate (n = 22), breast (n = 16), and from women with benign breast disease (n = 14) and compared those with age-matched healthy controls (22-49 years or 50+ years) and published data for pancreatic cancer (n = 17). Our results show that cancer-induced changes are reflected in higher urinary [Zn] and lower urinary δ66Zn for pancreatic and prostate cancer and benign breast disease when compared with healthy controls. For prostate cancer, the progression of low [Zn] and high δ66Zn for patients of low-risk disease toward high [Zn] and low δ66Zn for the higher risk patients demonstrates that [Zn] and δ66Zn in urine could serve as a reliable prognostic tool. Urinary excretion of isotopically light Zn by patients with prostatic and pancreatic cancer is probably the result of increased reactive oxygen species in cancerous cells, which limits the scavenging of hydroxyl radicals and thus facilitates the oxidation of metalloproteins with sulfur-rich ligands. Urine from breast cancer patients shows undistinguishable δ66Zn to healthy controls, implying that the expression of metalloproteins with sulfur-rich ligands is stronger in breast cancer tissues. In conclusion, urinary δ66Zn may provide a non-invasive diagnostic tool for pancreatic cancer and support disease prognosis for prostate cancer. These findings should translate to comprehensive transverse and longitudinal cohort studies in future.

CYP3A7*1C allele: linking premenopausal oestrone and progesterone levels with risk of hormone receptor-positive breast cancers.

BACKGROUND: Epidemiological studies provide strong evidence for a role of endogenous sex hormones in the aetiology of breast cancer. The aim of this analysis was to identify genetic variants that are associated with urinary sex-hormone levels and breast cancer risk. METHODS: We carried out a genome-wide association study of urinary oestrone-3-glucuronide and pregnanediol-3-glucuronide levels in 560 premenopausal women, with additional analysis of progesterone levels in 298 premenopausal women. To test for the association with breast cancer risk, we carried out follow-up genotyping in 90,916 cases and 89,893 controls from the Breast Cancer Association Consortium. All women were of European ancestry. RESULTS: For pregnanediol-3-glucuronide, there were no genome-wide significant associations; for oestrone-3-glucuronide, we identified a single peak mapping to the CYP3A locus, annotated by rs45446698. The minor rs45446698-C allele was associated with lower oestrone-3-glucuronide (-49.2%, 95% CI -56.1% to -41.1%, P = 3.1 × 10-18); in follow-up analyses, rs45446698-C was also associated with lower progesterone (-26.7%, 95% CI -39.4% to -11.6%, P = 0.001) and reduced risk of oestrogen and progesterone receptor-positive breast cancer (OR = 0.86, 95% CI 0.82-0.91, P = 6.9 × 10-8). CONCLUSIONS: The CYP3A7*1C allele is associated with reduced risk of hormone receptor-positive breast cancer possibly mediated via an effect on the metabolism of endogenous sex hormones in premenopausal women.

The Steroid Metabolome and Breast Cancer Risk in Women with a Family History of Breast Cancer: The Novel Role of Adrenal Androgens and Glucocorticoids.

BACKGROUND: No study has comprehensively examined how the steroid metabolome is associated with breast cancer risk in women with familial risk. METHODS: We examined 36 steroid metabolites across the spectrum of familial risk (5-year risk ranged from 0.14% to 23.8%) in pre- and postmenopausal women participating in the New York site of the Breast Cancer Family Registry (BCFR). We conducted a nested case-control study with 62 cases/124 controls individually matched on menopausal status, age, and race. We measured metabolites using GC-MS in urine samples collected at baseline before the onset of prospectively ascertained cases. We used conditional logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) per doubling in hormone levels. RESULTS: The average proportion of total steroid metabolites in the study sample were glucocorticoids (61%), androgens (26%), progestogens (11%), and estrogens (2%). A doubling in glucocorticoids (aOR = 2.7; 95% CI = 1.3-5.3) and androgens (aOR = 1.6; 95% CI = 1.0-2.7) was associated with increased breast cancer risk. Specific glucocorticoids (THE, THF αTHF, 6ß-OH-F, THA, and α-THB) were associated with 49% to 161% increased risk. Two androgen metabolites (AN and 11-OH-AN) were associated with 70% (aOR = 1.7; 95% CI = 1.1-2.7) and 90% (aOR = 1.9; 95% CI = 1.2-3.1) increased risk, respectively. One intermediate metabolite of a cortisol precursor (THS) was associated with 65% (OR = 1.65; 95% CI = 1.0-2.7) increased risk. E1 and E2 estrogens were associated with 20% and 27% decreased risk, respectively. CONCLUSIONS: Results suggest that glucocorticoids and 11-oxygenated androgens are positively associated with breast cancer risk across the familial risk spectrum. IMPACT: If replicated, our findings suggest great potential of including steroids into existing breast cancer risk assessment tools.

Urinary Melatonin in Relation to Breast Cancer Risk: Nested Case-Control Analysis in the DOM Study and Meta-analysis of Prospective Studies.

BACKGROUND: Exposure to higher levels of melatonin may be associated with lower breast cancer risk, but epidemiologic evidence has been limited. We examined the relationship in a case-control study nested within the Diagnostisch Onderzoek Mammacarcinoom (DOM) study and conducted a meta-analysis of prospective studies. METHODS: Concentrations of 6-sulfatoxymelatonin (aMT6s) in prediagnostic first morning urine voids were measured in 274 postmenopausal women diagnosed with breast cancer and 274 matched controls from the DOM study. Conditional logistic regression models were used to estimate multivariable adjusted ORs of breast cancer for thirds of aMT6s. Meta-analysis of this and previous prospective studies of urinary melatonin with breast cancer risk estimated the inverse-variance weighted averages of study-specific log RRs of breast cancer for the highest versus lowest levels of aMT6s. RESULTS: In the DOM study, the ORs of breast cancer for the middle and highest versus lowest thirds of aMT6s were 0.70 [95% confidence interval (CI), 0.45-1.09] and 0.72 (95% CI, 0.44-1.19), respectively. In the meta-analysis of the DOM study with six previous studies (2,296 cases), RR of breast cancer for the highest versus lowest levels of aMT6s was 0.87 (95% CI, 0.76-1.01). CONCLUSIONS: Results from the DOM study, together with the published prospective data, do not support a strong association of melatonin with breast cancer risk. IMPACT: This study adds to the relatively scarce prospective data on melatonin in relation to breast cancer risk. The totality of the prospective evidence does not clearly show an association between melatonin and breast cancer risk, but further data are needed to be able to exclude a modest association.

Probing of breast cancer using a combination of plasma and urinary circulating cell-free DNA.

Monitoring of early-stage breast cancer is critical in promptly addressing disease relapse. Circulating cell-free DNA provides a minimally invasive and sensitive means to probing the disease. In a longitudinal analysis of 250 patients with early breast cancer, we compared the circulating cell-free DNA recovered from both plasma and urine specimens. For comparison, 50 healthy controls were also recruited. Specific mutations associated with the disease were profiled to determine the clinical sensitivity and specificity. Correlations of recovered concentrations of cell-free DNA with outcomes were examined to address early prognostication. PIK3CA mutation profiling in both plasma and urinary cell-free DNA showed an agreement of 97.2% compared with the results obtained for tumor tissues. The analysis of healthy controls revealed that cell-free DNA measurements were stable and consistent over time. Over the short 6-month period of monitoring, our analyses showed declines in recovered cell-free DNA; these findings may aid physicians in stratifying patients at higher risk for relapse. Similar results were observed in both plasma and urine specimens (hazard ratios: 2.16 and 2.48, respectively). Cell-free DNA presents a novel and sensitive method for the monitoring of early-stage breast cancer. In the present study, serial measurements of both plasma and urine specimens were useful in probing the disease.

Predicting steady-state endoxifen plasma concentrations in breast cancer patients by CYP2D6 genotyping or phenotyping. Which approach is more reliable?

In previous studies, steady-state Z-endoxifen plasma concentrations (ENDOss) correlated with relapse-free survival in women on tamoxifen (TAM) treatment for breast cancer. ENDOss also correlated significantly with CYP2D6 genotype (activity score) and CYP2D6 phenotype (dextromethorphan test). Our aim was to ascertain which method for assessing CYP2D6 activity is more reliable in predicting ENDOss. The study concerned 203 Caucasian women on tamoxifen-adjuvant therapy (20 mg q.d.). Before starting treatment, CYP2D6 was genotyped (and activity scores computed), and the urinary log(dextromethorphan/dextrorphan) ratio [log(DM/DX)] was calculated after 15 mg of oral dextromethorphan. Plasma concentrations of TAM, N-desmethyl-tamoxifen (ND-TAM), Z-4OH-tamoxifen (4OH-TAM) and ENDO were assayed 1, 4, and 8 months after first administering TAM. Multivariable regression analysis was used to identify the clinical and laboratory variables predicting log-transformed ENDOss (log-ENDOss). Genotype-derived CYP2D6 phenotypes (PM, IM, NM, EM) and log(DM/DX) correlated independently with log-ENDOss. Genotype-phenotype concordance was almost complete only for poor metabolizers, whereas it emerged that 34% of intermediate, normal, and ultrarapid metabolizers were classified differently based on log(DM/DX). Multivariable regression analysis selected log(DM/DX) as the best predictor, with patients' age, weak inhibitor use, and CYP2D6 phenotype decreasingly important: log-ENDOss = 0.162 - log(DM/DX) × 0.170 + age × 0.0063 - weak inhibitor use × 0.250 + IM × 0.105 + (NM + UM) × 0.210; (R2  = 0.51). In conclusion, log(DM/DX) seems superior to genotype-derived CYP2D6 phenotype in predicting ENDOss.

Utility of urinary type I collagen cross-linked N-telopeptide as a prognostic indicator in breast cancer patients with bone metastases.

BACKGROUND: Breast cancer patients with bone metastases are usually managed with bone modifying agents, such as zoledronic acid and denosumab, and some bone turnover markers (BTMs) have been recognized as prognostic indicators in such patients. Although several studies have demonstrated the validity of BTMs as prognostic markers in patients treated with zoledronic acid, few studies have reported the utility of BTMs with denosumab treatment. In this study, we evaluated whether urinary N-telopeptide of type I collagen (u-NTX) can be a prognostic indicator in patients treated with denosumab. METHODS: Thirty-six breast cancer patients newly diagnosed with bone metastases were evaluated retrospectively. Patients were treated with denosumab and anti-cancer drugs. u-NTX levels were measured 1 month before and after administration of denosumab, and the ratio of u-NTX levels before and after denosumab (change ratio) was assessed for its association with prognosis. RESULTS: Levels of u-NTX decreased after denosumab administration in all patients except for one. The median value of the u-NTX change ratio was 0.766. Based on the change ratio, patients were divided into either a "high group" (n = 18) or a "low group" (n = 18). The low group showed significantly shorter overall survival (OS) compared with the high group (low group 15.0 months; high group 54.0 months; P = 0.012). Multivariate analysis indicated that the "low group" was an independent prognostic factor for OS (P = 0.028). CONCLUSION: We demonstrated that the u-NTX change ratio in denosumab-treated breast cancer patients with bone metastases can be a prognostic marker.