30 research outputs found
Recommended from our members
Characterisation of microRNA expression in post-natal mouse mammary gland development.
BACKGROUND: The differential expression pattern of microRNAs (miRNAs) during mammary gland development might provide insights into their role in regulating the homeostasis of the mammary epithelium. Our aim was to analyse these regulatory functions by deriving a comprehensive tissue-specific combined miRNA and mRNA expression profile of post-natal mouse mammary gland development.We measured the expression of 318 individual murine miRNAs by bead-based flow-cytometric profiling of whole mouse mammary glands throughout a 16-point developmental time course, including juvenile, puberty, mature virgin, gestation, lactation, and involution stages. In parallel whole-genome mRNA expression data were obtained. RESULTS: One third (n = 102) of all murine miRNAs analysed were detected during mammary gland development. MicroRNAs were represented in seven temporally co-expressed clusters, which were enriched for both miRNAs belonging to the same family and breast cancer-associated miRNAs. Global miRNA and mRNA expression was significantly reduced during lactation and the early stages of involution after weaning. For most detected miRNA families we did not observe systematic changes in the expression of predicted targets. For miRNA families whose targets did show changes, we observed inverse patterns of miRNA and target expression. The data sets are made publicly available and the combined expression profiles represent an important community resource for mammary gland biology research. CONCLUSION: MicroRNAs were expressed in likely co-regulated clusters during mammary gland development. Breast cancer-associated miRNAs were significantly enriched in these clusters. The mechanism and functional consequences of this miRNA co-regulation provide new avenues for research into mammary gland biology and generate candidates for functional validation.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are
Antibody recognition of Plasmodium falciparum infected red blood cells by symptomatic and asymptomatic individuals in the Brazilian Amazon
Pathological chemotherapy response score is prognostic in tubo-ovarian high-grade serous carcinoma: A systematic review and meta-analysis of individual patient data
There is a need to develop and validate biomarkers for treatment response and survival in tubo-ovarian high-grade serous carcinoma (HGSC). The chemotherapy response score (CRS) stratifies patients into complete/near-complete (CRS3), partial (CRS2), and no/minimal (CRS1) response after neoadjuvant chemotherapy (NACT). Our aim was to review current evidence to determine whether the CRS is prognostic in women with tubo-ovarian HGSC treated with NACT.This article is freely available via Open Access. Click on the Publisher URL to access the full-text via the publisher's site
Ovarian borderline tumors in the 2014 WHO classification: evolving concepts and diagnostic criteria
Borderline ovarian tumors (BOT) are uncommon but not rare epithelial ovarian neoplasms, intermediate between benign and malignant categories. Since BOT were first identified >40 years ago, they have inspired controversies disproportionate to their incidence. This review discusses diagnostic criteria for the histologic subtypes of BOT, highlighting areas of diagnostic challenges, ongoing controversies, and changes in terminology implemented by the recent 2014 WHO Classification of Tumours of the Female Genital Organs. Emerging knowledge supports the notion that subtypes of borderline ovarian tumors comprise distinct biologic, pathogenetic, and molecular entities, precluding a single unifying concept for BOT. Serous borderline tumors (SBT) share molecular and genetic alterations with low-grade serous carcinomas and can present at higher stages with peritoneal implants and/or lymph node involvement, which validates their borderline malignant potential. All other (non-serous) subtypes of BOT commonly present at stage I confined to the ovary(ies) and are associated with overall survival approaching that of the general population. An important change in the WHO 2014 classification is the new terminology of non-invasive implants associated with SBT, as any invasive foci (previously called “invasive implants”) are now in line with their biological behavior considered peritoneal low-grade serous carcinoma (LGSC). The controversy regarding the terminology of non-serous borderline tumors, called by some pathologists “atypical proliferative tumor” in view of their largely benign behavior, has not been resolved. The concepts of intraepithelial carcinoma and microinvasion may evolve in further studies, as their presence appears to have no prognostic impact and is subject to considerable inter-observer variability
Variation in cell signaling protein expression may introduce sampling bias in primary epithelial ovarian cancer.
Although the expression of cell signaling proteins is used as prognostic and predictive biomarker, variability of protein levels within tumors is not well studied. We assessed intratumoral heterogeneity of protein expression within primary ovarian cancer. Full-length proteins were extracted from 88 formalin-fixed and paraffin-embedded tissue samples of 13 primary high-grade serous ovarian carcinomas with 5-9 samples each. In addition, 14 samples of normal fallopian tube epithelium served as reference. Quantitative reverse phase protein arrays were used to analyze the expression of 36 cell signaling proteins including HER2, EGFR, PI3K/Akt, and angiogenic pathways as well as 15 activated (phosphorylated) proteins. We found considerable intratumoral heterogeneity in the expression of proteins with a mean coefficient of variation of 25% (range 17-53%). The extent of intratumoral heterogeneity differed between proteins (p<0.005). Interestingly, there were no significant differences in the extent of heterogeneity between phosphorylated and non-phosphorylated proteins. In comparison, we assessed the variation of protein levels amongst tumors from different patients, which revealed a similar mean coefficient of variation of 21% (range 12-48%). Based on hierarchical clustering, samples from the same patient clustered more closely together compared to samples from different patients. However, a clear separation of tumor versus normal tissue by clustering was only achieved when mean expression values of all individual samples per tumor were analyzed. While differential expression of some proteins was detected independently of the sampling method used, the majority of proteins only demonstrated differential expression when mean expression values of multiple samples per tumor were analyzed. Our data indicate that assessment of established and novel cell signaling proteins as diagnostic or prognostic markers may require sampling of serous ovarian cancers at several distinct locations to avoid sampling bias
Detection of Tumor-Specific PTPmu in Gynecological Cancer and Patient Derived Xenografts
Background: We developed a fluorophore-conjugated peptide agent, SBK4, that detects a tumor-specific proteolyzed form of the cell adhesion molecule, PTPmu, found in the tumor microenvironment. We previously demonstrated its tissue specific distribution in high-grade brain tumors. To extend those studies to other aggressive solid tumor types, we assessed the tissue distribution of PTPmu/SBK4 in a set of matched gynecologic cancer patient derived xenografts (PDXs) and primary patient tumors, as well as a limited cohort of tumors from gynecological cancer patients. PDXs isolated from the tissues of cancer patients have been shown to yield experimentally manipulatable models that replicate the clinical characteristics of individual patients’ tumors. In this study, gynecological cancer PDXs and patient biopsies were examined to determine if tumor-specific proteolyzed PTPmu was present. Methods: We used the peptide agent SBK4 conjugated to the fluorophore Texas Red (TR) to label tumor tissue microarrays (TMAs) containing patient and/or PDX samples from several high-grade gynecologic cancer types, and quantified the level of staining with Image J. In one TMA, we were able to directly compare the patient and the matched PDX tissue on the same slide. Results: While normal tissue had very little SBK4-TR staining, both primary tumor tissue and PDXs have higher labeling with SBK4-TR. Matched PDXs and patient samples from high-grade endometrial and ovarian cancers demonstrated higher levels of PTPmu by staining with SBK4 than normal tissue. Conclusion: In this sample set, all PDXs and high-grade ovarian cancer samples had increased labeling by SBK4-TR compared with the normal controls. Our results indicate that proteolyzed PTPmu and its novel peptide detection agent, SBK4, allow for the visualization of tumor-specific changes in cell adhesion molecules by tissue-based staining, providing a rationale for further development as an imaging agent in aggressive solid tumors, including gynecological cancers
miR-181a initiates and perpetuates oncogenic transformation through the regulation of innate immune signaling
The majority of high grade serous ovarian cancers originate from fallopian tube secretory epithelial cells (FTSECs). Here the authors show that miR-181a drives oncogenic transformation in FTSECs through the cooperative inhibition of the tumor suppressor RB1 and of STING, resulting in genomic instability and suppression of intrinsic interferon signaling
Prediction of Response to Neoadjuvant Chemotherapy by Sequential F-18-Fluorodeoxyglucose Positron Emission Tomography in Patients With Advanced-Stage Ovarian Cancer
Impact of sampling method on identification of proteins differentially expressed in tumors vs. normal tissues.
*<p>randomly selected single tumor samples per case; this analysis was repeated 3 times (tumor samples 1–3).</p><p>+ and − symbols after p-values indicate significant upregulation (+) or downregulation (−) of the respective protein in tumor vs. normal tissues.</p><p>n.s., not significant (>0.05).</p><p><i>Italics</i> indicate the group of proteins identified as differentially expressed by all four approaches.</p