An objective noninvasive biomarker for fruit and vegetable (FV) consumption would help to more reliably characterize the relationship between FV intake and health status in observational studies. Because increases in urinary hippuric acid (HA) were observed after consumption of several FV varieties, we aimed to investigate whether 24-h urinary HA may represent a potential biomarker for FV consumption in children and adolescents. The association of FV and juice (FVJ) intake calculated from 3-d weighed dietary records with 24-h urinary HA excretion was analyzed in 240 healthy children and adolescents and compared with associations of the established biomarkers urinary nitrogen (uN) and urinary potassium (uK) with protein and potassium intake, respectively. Spearman correlation coefficients (r) and cross-classifications were calculated for all diet-biomarker associations. Potential confounders for the HA-FVJ association were examined in linear regression models. In children, correlations of HA with FVJ (r = 0.62), uN with protein (r = 0.64), and potassium intake with uK (r = 0.65) were comparable. In adolescents, the HA-FVJ association was weaker (r = 0.41) compared with the biomarkers uN (r = 0.60) and uK (r = 0.58) (all P < 0.0001). Cross-classification into the same/adjacent quartile by dietary and urinary data were >85% for all analyzed comparisons except for a 75% classification agreement between HA and FVJ in adolescents. Unadjusted and adjusted linear regression models indicated significant (P < 0.0001) HA-FVJ associations in both age groups. FVJ explained more of the variability in HA excretion in children (R(2) = 0.38) than in adolescents (R(2) = 0.22). Our findings in children showing HA-FVJ associations comparable to those for well-established biomarkers with their respective dietary intakes suggest that HA may represent a useful biomarker for FVJ.

The clinical course of breast cancer varies from one patient to another. Currently, the choice of therapy relies on clinical parameters and histological and molecular tumor features. Alas, these markers are informative in only a subset of patients. Therefore, additional predictors of disease outcome would be valuable for treatment stratification. Extensive studies showed that the degree of variation of the nuclear DNA content, i.e., aneuploidy, determines prognosis. Our aim was to further elucidate the molecular basis of aneuploidy. We analyzed five diploid and six aneuploid tumors with more than 20 years of follow-up. By performing FISH with a multiplexed panel of 10 probes to enumerate copy numbers in individual cells, and by sequencing 563 cancer-related genes, we analyzed how aneuploidy is linked to intratumor heterogeneity. In our cohort, none of the patients with diploid tumors died of breast cancer during follow-up in contrast to four of six patients with aneuploid tumors (mean survival 86.4 months). The FISH analysis showed markedly increased genomic instability and intratumor heterogeneity in aneuploid tumors. MYC gain was observed in only 20% of the diploid cancers, while all aneuploid cases showed a gain. The mutation burden was similar in diploid and aneuploid tumors, however, TP53 mutations were not observed in diploid tumors, but in all aneuploid tumors in our collective. We conclude that quantitative measurements of intratumor heterogeneity by multiplex FISH, detection of MYC amplification and TP53 mutation could augment prognostication in breast cancer patients.

Breast cancer is the most common cancer type and cause of cancer-related mortality among women worldwide. New biomarker discovery is crucial for diagnostic innovation and personalized medicine in breast cancer. Heat shock proteins (HSPs) have been increasingly reported as biomarkers and potential drug targets for cancers. HLJ1 (DNAJB4) belongs to the DNAJ (HSP40) family of HSPs and is regarded as a tumor suppressor gene in lung, colon, and gastric cancers. However, the role of the HLJ1 gene in breast cancer is currently unknown. We evaluated the role of the HLJ1 gene in breast cancer progression by analyzing its in vitro and in vivo expression and its genetic/epigenetic alterations. HLJ1 expression was found to be reduced or lost in breast cancer cell lines (SK-BR-3, MDA-MB-231, ZR-75-1) compared with the nontumorigenic mammary epithelial cell line (MCF 10A). In a clinical context for breast cancer progression, the HLJ1 expression was significantly less frequent in invasive breast carcinoma samples (n = 230) compared with normal breast tissue (n = 100), benign neoplasia (n = 53), and ductal carcinoma in situ (n = 21). In methylation analyses by the combined bisulfite restriction analysis assay, the CpG island located in the 5¢-flanking region of the HLJ1 gene was found to be methylated in breast cancer cell lines. HLJ1 expression was restored in the ZR-75-1 cell line by DNA demethylating agent 5-Aza-2¢-deoxycytidine (5-AzadC) and histone deacetylase inhibitor trichostatin A. These new observations support the idea that HLJ1 is a tumor suppressor candidate and potential biomarker for breast cancer. Epigenomic mechanisms such as CpG methylation and histone deacetylation might contribute to downregulation of HLJ1 expression. We call for future functional, epigenomic, and clinical studies to ascertain the contribution of HLJ1 to breast cancer pathogenesis and, importantly, evaluate its potential for biomarker development in support of personalized medicine diagnostic innovation in clinical oncology.

Extensive studies using gene expression profiling to characterize breast cancers have revealed four distinct molecular subtypes: i) luminal A, ii) luminal B [with either Supported by the Intramural Research Program of the NIH, National Cancer Institute, and National Library of Medicine; the German Foundation for Young Adults with cancer (Deutsche Stiftung für junge Erwachsene mit Krebs) (A.K.); the Ad Infinitum Foundation (A.L. and N.D.); and a Mildred Scheel postdoctoral fellowship of the German Cancer Aid (Deutsche Krebshilfe) (D.H.).Disclosure: None declared.

◥Purpose: The choice of therapy for patients with breast cancer is often based on clinicopathologic parameters, hormone receptor status, and HER2 amplification. To improve individual prognostication and tailored treatment decisions, we combined clinicopathologic prognostic data with genome instabilty profiles established by quantitative measurements of the DNA content.Experimental Design: We retrospectively assessed clinical data of 4,003 patients with breast cancer with a minimum postoperative follow-up period of 10 years. For the entire cohort, we established genome instability profiles. We applied statistical methods, including correlation matrices, Kaplan-Meier curves, and multivariable Cox proportional hazard models, to ascertain the potential of standard clinicopathologic data and genome instability profiles as independent predictors of disease-specific survival in distinct subgroups, defined clinically or with respect to treatment.Results: In Cox regression analyses, two parameters of the genome instability profiles, the S-phase fraction and the stemline scatter index, emerged as independent predictors in premenopausal women, outperforming all clinicopathologic parameters. In postmenopausal women, age and hormone receptor status were the predominant prognostic factors. However, by including Sphase fraction and 2.5c exceeding rate, we could improve disease outcome prediction in pT1 tumors irrespective of the lymph node status. In pT3-pT4 tumors, a higher S-phase fraction led to poorer prognosis. In patients who received adjuvant endocrine therapy, chemotherapy or radiotherapy, or a combination, the ploidy profiles improved prognostication.Conclusions: Genome instability profiles predict disease outcome in patients with breast cancer independent of clinicopathologic parameters. This applies especially to premenopausal patients. In patients receiving adjuvant therapy, the profiles improve identification of high-risk patients.