Relationship Among Dietary Taurine Intake, Dietary Attitudes, Dietary Behaviors, and Life Stress by Depression in Korean Female College Students.

This study was conducted to investigate the correlation between dietary taurine intake, nutrients intake, dietary attitudes, dietary behaviors, and life stress by depression in Korean female college students. Depression was measured by self-reported symptoms of depression on the CES-D (Center for Epidemiologic Studies Depression) scale. The subjects of this cross-sectional study included 56 female college students with depression (depression group, DG) and 122 female students without depression (control group, CG). Self-reported life stress score was determined using the life stress scale developed for Korean college students. Intakes of dietary taurine and nutrients were assessed using 3-day food records (2 weekdays and 1 weekend day) and evaluated using the computer aided nutrition program 4.0 version. Statistical analysis was performed using SPSS 24.0. We observed no significant difference in the average dietary taurine intake between DG (87.6 mg/day) and CG (92.3 mg/day). The average dietary intakes of vitamin A and calcium in DG were significantly lower as compared to CG (p < 0.05). The average total scores of dietary attitudes (p < 0.01) and dietary behaviors (p < 0.05) in DG were significantly lower as compared to CG. The average total life stress score (p < 0.001) and all stress categories were significantly higher in DG as compared to CG. No significant correlation was observed between the CES-D scale score and dietary taurine intake. However, there were significant negative correlations between the CES-D scale score and vitamin A, folic acid, vitamin C, and calcium intakes (p < 0.05), dietary attitudes, and dietary behaviors (p < 0.01). Scores of the CES-D scale and life stress showed a significantly positive correlation (p < 0.01). Therefore, continuous nutrition education and counseling for good dietary attitudes and behaviors are required. Future studies need to be undertaken to confirm the correlation between dietary taurine intake and depression by intervention with taurine.

Crowdsourcing scoring of immunohistochemistry images: Evaluating Performance of the Crowd and an Automated Computational Method.

The assessment of protein expression in immunohistochemistry (IHC) images provides important diagnostic, prognostic and predictive information for guiding cancer diagnosis and therapy. Manual scoring of IHC images represents a logistical challenge, as the process is labor intensive and time consuming. Since the last decade, computational methods have been developed to enable the application of quantitative methods for the analysis and interpretation of protein expression in IHC images. These methods have not yet replaced manual scoring for the assessment of IHC in the majority of diagnostic laboratories and in many large-scale research studies. An alternative approach is crowdsourcing the quantification of IHC images to an undefined crowd. The aim of this study is to quantify IHC images for labeling of ER status with two different crowdsourcing approaches, image-labeling and nuclei-labeling, and compare their performance with automated methods. Crowdsourcing- derived scores obtained greater concordance with the pathologist interpretations for both image-labeling and nuclei-labeling tasks (83% and 87%), as compared to the pathologist concordance achieved by the automated method (81%) on 5,338 TMA images from 1,853 breast cancer patients. This analysis shows that crowdsourcing the scoring of protein expression in IHC images is a promising new approach for large scale cancer molecular pathology studies.

Image-guided Coring for Large-scale Studies in Molecular Pathology.

Sampling of formalin-fixed paraffin-embedded (FFPE) tissue blocks is a critical initial step in molecular pathology. Image-guided coring (IGC) is a new method for using digital pathology images to guide tissue block coring for molecular analyses. The goal of our study is to evaluate the use of IGC for both tissue-based and nucleic acid-based projects in molecular pathology. First, we used IGC to construct a tissue microarray (TMA); second, we used IGC for FFPE block sampling followed by RNA extraction; and third, we assessed the correlation between nuclear counts quantitated from the IGC images and RNA yields. We used IGC to construct a TMA containing 198 normal and breast cancer cores. Histopathologic analysis showed high accuracy for obtaining tumor and normal breast tissue. Next, we used IGC to obtain normal and tumor breast samples before RNA extraction. We selected a random subset of tumor and normal samples to perform computational image analysis to quantify nuclear density, and we built regression models to estimate RNA yields from nuclear count, age of the block, and core diameter. Number of nuclei and core diameter were the strongest predictors of RNA yields in both normal and tumor tissue. IGC is an effective method for sampling FFPE tissue blocks for TMA construction and nucleic acid extraction. We identify significant associations between quantitative nuclear counts obtained from IGC images and RNA yields, suggesting that the integration of computational image analysis with IGC may be an effective approach for tumor sampling in large-scale molecular studies.

Keratin Expression Patterns in Stromal Cells of Benign Sclerosing Lesions of the Breast: A Potential Diagnostic Pitfall.

CONTEXT: Metaplastic carcinomas arising in association with benign sclerosing lesions (BSLs) are rare malignancies in which a neoplastic spindle cell proliferation can be recognized extending beyond the boundaries of the complex sclerosing lesion or papilloma. However, in cases in which the metaplastic carcinoma is of the low-grade fibromatosis-like type or is a low-grade adenosquamous carcinoma, distinction from the background BSL can be a significant challenge. Cytokeratin (CK) and/or p63 immunostains are helpful in confirming the diagnosis of metaplastic carcinoma, but the expression patterns of these markers in the stromal cells of BSLs have not been well characterized. OBJECTIVE: To characterize the expression patterns of CKs and p63 in BSLs. DESIGN: We evaluated the spindle cell component of 55 BSLs using CK 5/6, CK 903, CK MNF116, and p63. RESULTS: A total of 45 cases (81%) showed no staining for CKs or p63 in benign stromal cells. CK 5/6, CK 903, and p63 were positive in one case each. CK MNF116 stained spindle cells within 10 BSLs. No cases showed spindle cell reactivity for all 4 markers. Positive cases demonstrated very focal, weak staining of spindle cells; only 1 case showed focal, moderate CK staining. Spindle cell positivity was not associated with lesion type, growth pattern, spindle cell atypia, or mitoses. CONCLUSIONS: These findings suggest that although the presence or absence of expression of CK 5/6, CK 903, and p63 may be useful to distinguish BSL from metaplastic carcinomas arising in this setting, CK MNF116 positivity may be a diagnostic pitfall.

NFAT1 promotes intratumoral neutrophil infiltration by regulating IL8 expression in breast cancer.

NFAT transcription factors are key regulators of gene expression in immune cells. In addition, NFAT1-induced genes play diverse roles in mediating the progression of various solid tumors. Here we show that NFAT1 induces the expression of the IL8 gene by binding to its promoter and leading to IL8 secretion. Thapsigargin stimulation of breast cancer cells induces IL8 expression in an NFAT-dependent manner. Moreover, we show that NFAT1-mediated IL8 production promotes the migration of primary human neutrophils in vitro and also promotes neutrophil infiltration in tumor xenografts. Furthermore, expression of active NFAT1 effectively suppresses the growth of nascent and established tumors by a non cell-autonomous mechanism. Evaluation of breast tumor tissue reveals that while the levels of NFAT1 are similar in tumor cells and normal breast epithelium, cells in the tumor stroma express higher levels of NFAT1 compared to normal stroma. Elevated levels of NFAT1 also correlate with increased neutrophil infiltrate in breast tumors. These data point to a mechanism by which NFAT1 orchestrates the communication between breast cancer cells and host neutrophils during breast cancer progression.

Extensive rewiring of epithelial-stromal co-expression networks in breast cancer.

BACKGROUND: Epithelial-stromal crosstalk plays a critical role in invasive breast cancer pathogenesis; however, little is known on a systems level about how epithelial-stromal interactions evolve during carcinogenesis. RESULTS: We develop a framework for building genome-wide epithelial-stromal co-expression networks composed of pairwise co-expression relationships between mRNA levels of genes expressed in the epithelium and stroma across a population of patients. We apply this method to laser capture micro-dissection expression profiling datasets in the setting of breast carcinogenesis. Our analysis shows that epithelial-stromal co-expression networks undergo extensive rewiring during carcinogenesis, with the emergence of distinct network hubs in normal breast, and estrogen receptor-positive and estrogen receptor-negative invasive breast cancer, and the emergence of distinct patterns of functional network enrichment. In contrast to normal breast, the strongest epithelial-stromal co-expression relationships in invasive breast cancer mostly represent self-loops, in which the same gene is co-expressed in epithelial and stromal regions. We validate this observation using an independent laser capture micro-dissection dataset and confirm that self-loop interactions are significantly increased in cancer by performing computational image analysis of epithelial and stromal protein expression using images from the Human Protein Atlas. CONCLUSIONS: Epithelial-stromal co-expression network analysis represents a new approach for systems-level analyses of spatially localized transcriptomic data. The analysis provides new biological insights into the rewiring of epithelial-stromal co-expression networks and the emergence of epithelial-stromal co-expression self-loops in breast cancer. The approach may facilitate the development of new diagnostics and therapeutics targeting epithelial-stromal interactions in cancer.

Computational pathology to discriminate benign from malignant intraductal proliferations of the breast.

The categorization of intraductal proliferative lesions of the breast based on routine light microscopic examination of histopathologic sections is in many cases challenging, even for experienced pathologists. The development of computational tools to aid pathologists in the characterization of these lesions would have great diagnostic and clinical value. As a first step to address this issue, we evaluated the ability of computational image analysis to accurately classify DCIS and UDH and to stratify nuclear grade within DCIS. Using 116 breast biopsies diagnosed as DCIS or UDH from the Massachusetts General Hospital (MGH), we developed a computational method to extract 392 features corresponding to the mean and standard deviation in nuclear size and shape, intensity, and texture across 8 color channels. We used L1-regularized logistic regression to build classification models to discriminate DCIS from UDH. The top-performing model contained 22 active features and achieved an AUC of 0.95 in cross-validation on the MGH data-set. We applied this model to an external validation set of 51 breast biopsies diagnosed as DCIS or UDH from the Beth Israel Deaconess Medical Center, and the model achieved an AUC of 0.86. The top-performing model contained active features from all color-spaces and from the three classes of features (morphology, intensity, and texture), suggesting the value of each for prediction. We built models to stratify grade within DCIS and obtained strong performance for stratifying low nuclear grade vs. high nuclear grade DCIS (AUC = 0.98 in cross-validation) with only moderate performance for discriminating low nuclear grade vs. intermediate nuclear grade and intermediate nuclear grade vs. high nuclear grade DCIS (AUC = 0.83 and 0.69, respectively). These data show that computational pathology models can robustly discriminate benign from malignant intraductal proliferative lesions of the breast and may aid pathologists in the diagnosis and classification of these lesions.

The circadian clock gene Per1 suppresses cancer cell proliferation and tumor growth at specific times of day.

Cell cycle progression is tightly regulated. The expressions of cell cycle regulators, the products of which either promote or inhibit cell proliferation, oscillate during each cell cycle. Cellular proliferation and the expression of cell cycle regulators are also controlled by the circadian clock. Disruption of the circadian clock may thereby lead to deregulated cell proliferation. Mammalian Per2 is a core clock gene, the product of which suppresses cancer cell proliferation and tumor growth in vivo and in vitro. Because Per1, another key clock gene, is mutated in human breast cancers, and because its clock functions are similar and complementary to those of Per2, we have studied its role in modulating breast cancer cell proliferation and tumor growth. We find that breast cancer growth rate is gated by the circadian clock with two daily peaks and troughs, and that they are coupled to the daily expression patterns of clock-controlled genes that regulate cell proliferation. Down-regulation of the expression of tumor Per1 increases cancer cell growth in vitro and tumor growth in vivo by enhancing the circadian amplitude of the two daily tumor growth peaks. The data of the study suggest Per1 has tumor-suppressor function that diminishes cancer proliferation and tumor growth, but only at specific times of day.

Beta-catenin induces beta-TrCP-mediated PER2 degradation altering circadian clock gene expression in intestinal mucosa of ApcMin/+ mice.

Proliferation of intestinal epithelial cells is rhythmic throughout the day. This temporal organization occurs through the interaction between the endogenous peripheral circadian clock and pathways controlling cell cycle progression. Per2, a core clock gene with tumour suppresser function, is critical to clock function and to the regulation of cellular proliferation. Circadian disruption, which increases colon cancer incidence, may do so by deregulating clock controlled epithelial cell proliferation. Increased expression of beta-catenin is a contributing cause of most familial and spontaneous human colon cancer and the cause of multiple intestinal neoplasia of the Apc(Min/+) mouse. Here we report that increased beta-catenin destabilizes PER2 clock protein by inducing beta-TrCP, an F-box protein of SCF ubiquitin E3 ligase. In the intestinal mucosa of the Apc(Min/)(+) mouse, the decrease in PER2 protein levels is associated with altered circadian rhythms of clock genes, Per1 and Per2, and clock controlled genes, Dbp and Wee1. These findings suggest that disruption of the peripheral intestinal circadian clock may be intimately involved in beta-catenin induced intestinal epithelial neoplastic transformation in both mouse and man.