Molecular and computational approaches to understanding Keloid scarring

Ph.DDOCTOR OF PHILOSOPH

The genetic interplay between body mass index, breast size and breast cancer risk: a Mendelian randomization analysis.

BACKGROUND: Evidence linking breast size to breast cancer risk has been inconsistent, and its interpretation is often hampered by confounding factors such as body mass index (BMI). Here, we used linkage disequilibrium score regression and two-sample Mendelian randomization (MR) to examine the genetic associations between BMI, breast size and breast cancer risk. METHODS: Summary-level genotype data from 23andMe, Inc (breast size, n = 33 790), the Breast Cancer Association Consortium (breast cancer risk, n = 228 951) and the Genetic Investigation of ANthropometric Traits (BMI, n = 183 507) were used for our analyses. In assessing causal relationships, four complementary MR techniques [inverse variance weighted (IVW), weighted median, weighted mode and MR-Egger regression] were used to test the robustness of the results. RESULTS: The genetic correlation (rg) estimated between BMI and breast size was high (rg = 0.50, P = 3.89x10-43). All MR methods provided consistent evidence that higher genetically predicted BMI was associated with larger breast size [odds ratio (ORIVW): 2.06 (1.80-2.35), P = 1.38x10-26] and lower overall breast cancer risk [ORIVW: 0.81 (0.74-0.89), P = 9.44x10-6]. No evidence of a relationship between genetically predicted breast size and breast cancer risk was found except when using the weighted median and weighted mode methods, and only with oestrogen receptor (ER)-negative risk. There was no evidence of reverse causality in any of the analyses conducted (P > 0.050). CONCLUSION: Our findings indicate a potential positive causal association between BMI and breast size and a potential negative causal association between BMI and breast cancer risk. We found no clear evidence for a direct relationship between breast size and breast cancer risk

Towards precision medicine: interrogating the human genome to identify drug pathways associated with potentially functional, population-differentiated polymorphisms

10.1038/s41397-019-0096-yPHARMACOGENOMICS JOURNAL196516-52

Machine learning using genetic and clinical data identifies a signature that robustly predicts methotrexate response in rheumatoid arthritis

10.1093/rheumatology/keac032RHEUMATOLOG

The genetic interplay between body mass index, breast size and breast cancer risk: a Mendelian randomization analysis

10.1093/ije/dyz124INTERNATIONAL JOURNAL OF EPIDEMIOLOGY483781-79

Histological and pathological analyses of a mucoepidermoid tumor.

<p>Haematoxylin and Eosin staining provides visualization of the excised tracheal mucoepidermoid tumor biopsy (a), periodic acid-Schiff stain identifies mucins and glycoproteins in magenta (b), Mucin 1, Muc-1 identifies mucin-producing cells (c), Cytokeratin marker, Ck-MNF116 shows epithelial staining (d), carcino-embryonic antigen, CEA is an oncofetal antigen expressed by some tumors but not in normal adult tissues (e), androgen receptor, AR is a predictive marker for choice of therapy (f), muscle specific actin, MSA identifies the stromal component (g), and Ki-67 is a cell proliferation marker used for quantifying the proliferative index of the tumor (h). Scale bar: 100 µm.</p

Spheroid cultures and flow cytometry analyses of spheroid outgrowths.

<p>Day 10 spheroids in low adhesion culture plates (a), day 10 trachea spheroids plated onto culture plates after 24 hours (b), outgrowths from spheroid cultures (c). Flow cytometry analyses of spheroid outgrowths after 25 days <i>in vitro</i>. Scale bar: 100 µm. Cell morphology before (d) and after (f) trypsinization. Scale bar: 200 µm. Flow cytometry analyses for a panel of mesenchymal stromal cell markers before (e) and after (g) trypsinization.</p

KEGG pathways significantly enriched by genes differentially expressed between MEi cells and BM-MSCs.

<p>Pathways were identified by DAVID Functional Annotation and ranked by P-value with a cutoff of 0.01. Counts and percentages refer to the number and percentage of genes from the input list that fit into a given KEGG pathway. Fold enrichment is the magnitude of enrichment for each KEGG pathway compared with the entire gene list in the Affymetrix Human Gene 1.1 ST Array that serves as the reference.</p><p>KEGG pathways significantly enriched by genes differentially expressed between MEi cells and BM-MSCs.</p

Gene expression profiles and karyotyping of MEi cells.

<p>Two-dimensional cluster plots for the classification of samples based on the first two principal components. Tumor 1, 2, 3, 4 are MEi cells and MSC 1, 2 are BM-MSCs (a), Each row represents a gene and each column represents a sample. The expression level of each gene in a single sample is relative to its median abundance across all samples and is depicted according to a color scale shown on the right. Red and green indicate expression levels respectively above and below the median. (b), a representative image of tetraploidy and normal karyotype (c) at passage 12+3.</p

<i>In vitro</i> differentiation of MEi (MSC-like mucoepidermoid tumor) cells to endoderm and ectoderm lineages.

<p>A representative image of endoderm differentiation of MEi cells (a–c) and BM-MSCs (d–f) were stained positive for GATA 6, and ectoderm differentiation of MEi cells (g–i) and BM-MSCs (j–l) were positive for β-III tubulin. Scale bar: 50 µm.</p