非対称的な前額面上の骨盤傾斜と骨盤痛との関係

博士（保健学）神戸大

Identification and Validation Model for Informative Liquid Biopsy-Based microRNA Biomarkers:Insights from Germ Cell Tumor In Vitro, In Vivo and Patient-Derived Data

Liquid biopsy-based biomarkers, such as microRNAs, represent valuable tools for patient management, but often do not make it to integration in the clinic. We aim to explore issues impeding this transition, in the setting of germ cell tumors, for which novel biomarkers are needed. We describe a model for identifying and validating clinically relevant microRNAs for germ cell tumor patients, using both in vitro, in vivo (mouse model) and patient-derived data. Initial wide screening of candidate microRNAs is performed, followed by targeted profiling of potentially relevant biomarkers. We demonstrate the relevance of appropriate (negative) controls, experimental conditions (proliferation), and issues related to sample origin (serum, plasma, cerebral spinal fluid) and pre-analytical variables (hemolysis, contaminants, temperature), all of which could interfere with liquid biopsy-based studies and their conclusions. Finally, we show the value of our identification model in a specific scenario, contradicting the presumed role of miR-375 as marker of teratoma histology in liquid biopsy setting. Our findings indicate other putative microRNAs (miR-885-5p, miR-448 and miR-197-3p) fulfilling this clinical need. The identification model is informative to identify the best candidate microRNAs to pursue in a clinical setting

Serum microRNA profiles in athyroid patients on and off levothyroxine therapy

BackgroundLevothyroxine replacement treatment in hypothyroidism is unable to restore physiological thyroxine and triiodothyronine concentrations in serum and tissues completely. Normal serum thyroid stimulating hormone (TSH) concentrations reflect only pituitary euthyroidism and, therefore, novel biomarkers representing tissue-specific thyroid state are needed. MicroRNAs (miRNAs), small non-coding regulatory RNAs, exhibit tissue-specific expression patterns and can be detectable in serum. Previous studies have demonstrated differential expression of (precursors of) miRNAs in tissues under the influence of thyroid hormone.ObjectiveTo study if serum miRNA profiles are changed in different thyroid states.Design and methodsWe studied 13 athyroid patients (6 males) during TSH suppressive therapy and after 4 weeks of thyroid hormone withdrawal. A magnetic bead capture system was used to isolate 384 defined miRNAs from serum. Subsequently, the TaqMan Array Card 3.0 platform was used for profiling after individual target amplification.ResultsMean age of the subjects was 44.0 years (range 20-61 years). Median TSH levels were 88.9 mU/I during levothyroxine withdrawal and 0.006 mU/I during LT4 treatment with a median dosage of 2.1 fag/kg. After normalization to allow inter-sample analysis, a paired analysis did not demonstrate a significant difference in expression of any of the 384 miRNAs analyzed on and off LT4 treatment.ConclusionAlthough we previously showed an up-regulation of pri-miRNAs 133b and 206 in hypothyroid state in skeletal muscle, the present study does not supply evidence that thyroid state also affects serum miRNAs in humans

Breast cancer oestrogen independence mediated by BCAR1 or BCAR3 genes is transmitted through mechanisms distinct from the oestrogen receptor signalling pathway or the epidermal growth factor receptor signalling pathway

INTRODUCTION: Tamoxifen is effective for endocrine treatment of oestrogen receptor-positive breast cancers but ultimately fails due to the development of resistance. A functional screen in human breast cancer cells identified two BCAR genes causing oestrogen-independent proliferation. The BCAR1 and BCAR3 genes both encode components of intracellular signal transduction, but their direct effect on breast cancer cell proliferation is not known. The aim of this study was to investigate the growth control mediated by these BCAR genes by gene expression profiling. METHODS: We have measured the expression changes induced by overexpression of the BCAR1 or BCAR3 gene in ZR-75-1 cells and have made direct comparisons with the expression changes after cell stimulation with oestrogen or epidermal growth factor (EGF). A comparison with published gene expression data of cell models and breast tumours is made. RESULTS: Relatively few changes in gene expression were detected in the BCAR-transfected cells, in comparison with the extensive and distinct differences in gene expression induced by oestrogen or EGF. Both BCAR1 and BCAR3 regulate discrete sets of genes in these ZR-75-1-derived cells, indicating that the proliferation signalling proceeds along distinct pathways. Oestrogen-regulated genes in our cell model showed general concordance with reported data of cell models and gene expression association with oestrogen receptor status of breast tumours. CONCLUSIONS: The direct comparison of the expression profiles of BCAR transfectants and oestrogen or EGF-stimulated cells strongly suggests that anti-oestrogen-resistant cell proliferation is not caused by alternative activation of the oestrogen receptor or by the epidermal growth factor receptor signalling pathway

Text-derived concept profiles support assessment of DNA microarray data for acute myeloid leukemia and for androgen receptor stimulation

BACKGROUND: High-throughput experiments, such as with DNA microarrays, typically result in hundreds of genes potentially relevant to the process under study, rendering the interpretation of these experiments problematic. Here, we propose and evaluate an approach to find functional associations between large numbers of genes and other biomedical concepts from free-text literature. For each gene, a profile of related concepts is constructed that summarizes the context in which the gene is mentioned in literature. We assign a weight to each concept in the profile based on a likelihood ratio measure. Gene concept profiles can then be clustered to find related genes and other concepts. RESULTS: The experimental validation was done in two steps. We first applied our method on a controlled test set. After this proved to be successful the datasets from two DNA microarray experiments were analyzed in the same way and the results were evaluated by domain experts. The first dataset was a gene-expression profile that characterizes the cancer cells of a group of acute myeloid leukemia patients. For this group of patients the biological background of the cancer cells is largely unknown. Using our methodology we found an association of these cells to monocytes, which agreed with other experimental evidence. The second data set consisted of differentially expressed genes following androgen receptor stimulation in a prostate cancer cell line. Based on the analysis we put forward a hypothesis about the biological processes induced in these studied cells: secretory lysosomes are involved in the production of prostatic fluid and their development and/or secretion are androgen-regulated processes. CONCLUSION: Our method can be used to analyze DNA microarray datasets based on information explicitly and implicitly available in the literature. We provide a publicly available tool, dubbed Anni, for this purpose