Estrogen Receptor and HER2/Neu Status Affect Epigenetic Differences of Tumor-Related Genes in Primary Breast Tumors
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Screening and Identification of Key Biomarkers in Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Screening and identification of key biomarkers in clear cell renal cell carcinoma based on bioinformatics analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignancy of the urinary system. The pathogenesis and effective diagnosis of ccRCC have become popular topics for research in the previous decade. In the current study, an integrated bioinformatics analysis was performed to identify core genes associated in ccRCC. An expression dataset (GSE105261) was downloaded from the Gene Expression Omnibus database, and included 26 ccRCC and 9 normal kideny samples. Assessment of the microarray dataset led to the recognition of differentially expressed genes (DEGs), which was subsequently used for pathway and gene ontology (GO) enrichment analysis. -
Comprehensive Molecular Characterization of Gastric Adenocarcinoma
Comprehensive molecular characterization of gastric adenocarcinoma The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Bass, A. J., V. Thorsson, I. Shmulevich, S. M. Reynolds, M. Miller, B. Bernard, T. Hinoue, et al. 2014. “Comprehensive molecular characterization of gastric adenocarcinoma.” Nature 513 (7517): 202-209. doi:10.1038/nature13480. http://dx.doi.org/10.1038/ nature13480. Published Version doi:10.1038/nature13480 Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:12987344 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA NIH Public Access Author Manuscript Nature. Author manuscript; available in PMC 2014 September 22. NIH-PA Author ManuscriptPublished NIH-PA Author Manuscript in final edited NIH-PA Author Manuscript form as: Nature. 2014 September 11; 513(7517): 202–209. doi:10.1038/nature13480. Comprehensive molecular characterization of gastric adenocarcinoma A full list of authors and affiliations appears at the end of the article. Abstract Gastric cancer is a leading cause of cancer deaths, but analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity. Here we describe a comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer -
HER2 Positive and HER2 Negative Classical Type Invasive Lobular Carcinomas: Comparison of Clinicopathologic Features
Article HER2 Positive and HER2 Negative Classical Type Invasive Lobular Carcinomas: Comparison of Clinicopathologic Features Lin He 1, Ellen Araj 1 and Yan Peng 1,2,* 1 Department of Pathology, University of Texas Southwestern Medical Center, 6201 Harry Hines Blvd, Dallas, TX 75235, USA; [email protected] (L.H.); [email protected] (E.A.) 2 Harold C. Simmons Cancer Center, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75235, USA * Correspondence: [email protected] Abstract: Human epidermal growth factor receptor 2 (HER2) positive (+) classical type invasive lobular carcinoma (cILC) of the breast is extremely rare and its clinicopathologic features have not been well characterized. We compared features of HER2(+) and HER2 negative (−) cILCs. A total of 29 cases were identified from the clinical database at our institution from 2011-2019; 9 were HER2(+) cILC tumors and 20 were HER2(−) cILC tumors. The results reveal that HER2(+) cILC group had significantly increased Ki-67 expression and reduced estrogen receptor (ER) expression compared to HER2(−) cILC group (both p < 0.05). In addition, HER2(+) cILCs tended to be diagnosed at a younger age and more common in the left breast, and appeared to have a higher frequency of nodal or distant metastases. These clinicopathologic features suggest HER2(+) cILC tumors may have more aggressive behavior than their HER2(−) counterpart although both groups of tumors showed similar morphologic features. Future directions of the study: (1) To conduct a multi-institutional study with a larger case series of HER2(+) cILC to further characterize its clinicopathologic features; (2) to compare molecular profiles by next generation sequencing (NGS) assay between HER2(+) cILC and HER2(−) cILC cases to better understand tumor biology of this rare subset of HER2(+) breast cancer; Citation: He, L.; Araj, E.; Peng, Y. -
MARKER PANEL Figure 1
Epithelial to Mesenchymal Transition MARKER PANEL Figure 1. E-cadherin (A-F) and N-cadherin (G-L) expression profiles in normal human tissues shown by IHC with the Anti-CDH1 antibody AMAb90863 and the Anti-CDH2 antibody AMAb91220. Note the differential expression of two cadherins in colon (A, J), duodenum (B, K), cervix (C, L), cerebellum (D, G), heart (E, H) and testis (F, I). Inset on J shows CDH2- immunoreactivity in the peripheral ganglion neurons in rectum. A A B B Figure 2. Western blot using Anti-CDH1 antibody AMAb90863 (A) and Anti-CDH2 antibody AMAb91220 (B). Blot A: Lane 1: Marker [kDa], Lane 2: Human cell line MCF-7 (posi- tive), Lane 3: Human cell line SK-BR-3 (negative), Lane 4: Human cell line HeLa (nega- Figure 3. E-cadherin – beta-catenin protein-protein interactions tive). Blot B: Lane 1: Marker [kDa], Lane 2 Human U-251 MG (positive). shown by in situ proximity ligation assay (PLA) in the epi- thelium of normal fallopian tube (A). The Anti-CDH1 mouse Cover image: monoclonal antibody AMAb90865 and the Anti-CTNNB1 rabbit polyclonal antibody HPA029159 were used for the Multiplexed IHC-IF staining of human colorectal cancer section showing membranous PLA reaction. Tonsil was used as negative control ( ). E-cadherin immunoreactivity in tumor cells (AMAb90865, magenta) and laminin gamma 1 B positivity in basement membranes (AMAb91138, green). Page 2 (4) The Epithelial to Mesenchymal The antibodies targeting selected EMT On the contrary, N-cadherin (CDH2) ex- Transition Marker Panel marker proteins are: pression is high in e.g. the nervous sys- tem (G and inset on J), heart muscle (H) Epithelial and mesenchymal cells are fun- • IHC-validated in relevant normal and and testis (I), while glandular epithelium of damentally different and represent the two cancer human tissues gastrointestinal tract (J, K) and squamous main cell types in the body. -
The N-Cadherin Interactome in Primary Cardiomyocytes As Defined Using Quantitative Proximity Proteomics Yang Li1,*, Chelsea D
© 2019. Published by The Company of Biologists Ltd | Journal of Cell Science (2019) 132, jcs221606. doi:10.1242/jcs.221606 TOOLS AND RESOURCES The N-cadherin interactome in primary cardiomyocytes as defined using quantitative proximity proteomics Yang Li1,*, Chelsea D. Merkel1,*, Xuemei Zeng2, Jonathon A. Heier1, Pamela S. Cantrell2, Mai Sun2, Donna B. Stolz1, Simon C. Watkins1, Nathan A. Yates1,2,3 and Adam V. Kwiatkowski1,‡ ABSTRACT requires multiple adhesion, cytoskeletal and signaling proteins, The junctional complexes that couple cardiomyocytes must transmit and mutations in these proteins can cause cardiomyopathies (Ehler, the mechanical forces of contraction while maintaining adhesive 2018). However, the molecular composition of ICD junctional homeostasis. The adherens junction (AJ) connects the actomyosin complexes remains poorly defined. – networks of neighboring cardiomyocytes and is required for proper The core of the AJ is the cadherin catenin complex (Halbleib and heart function. Yet little is known about the molecular composition of the Nelson, 2006; Ratheesh and Yap, 2012). Classical cadherins are cardiomyocyte AJ or how it is organized to function under mechanical single-pass transmembrane proteins with an extracellular domain that load. Here, we define the architecture, dynamics and proteome of mediates calcium-dependent homotypic interactions. The adhesive the cardiomyocyte AJ. Mouse neonatal cardiomyocytes assemble properties of classical cadherins are driven by the recruitment of stable AJs along intercellular contacts with organizational and cytosolic catenin proteins to the cadherin tail, with p120-catenin β structural hallmarks similar to mature contacts. We combine (CTNND1) binding to the juxta-membrane domain and -catenin β quantitative mass spectrometry with proximity labeling to identify the (CTNNB1) binding to the distal part of the tail. -
Variations in Microrna-25 Expression Influence the Severity of Diabetic
BASIC RESEARCH www.jasn.org Variations in MicroRNA-25 Expression Influence the Severity of Diabetic Kidney Disease † † † Yunshuang Liu,* Hongzhi Li,* Jieting Liu,* Pengfei Han, Xuefeng Li, He Bai,* Chunlei Zhang,* Xuelian Sun,* Yanjie Teng,* Yufei Zhang,* Xiaohuan Yuan,* Yanhui Chu,* and Binghai Zhao* *Heilongjiang Key Laboratory of Anti-Fibrosis Biotherapy, Medical Research Center, Heilongjiang, People’s Republic of China; and †Clinical Laboratory of Hong Qi Hospital, Mudanjiang Medical University, Heilongjiang, People’s Republic of China ABSTRACT Diabetic nephropathy is characterized by persistent albuminuria, progressive decline in GFR, and second- ary hypertension. MicroRNAs are dysregulated in diabetic nephropathy, but identification of the specific microRNAs involved remains incomplete. Here, we show that the peripheral blood from patients with diabetes and the kidneys of animals with type 1 or 2 diabetes have low levels of microRNA-25 (miR-25) compared with those of their nondiabetic counterparts. Furthermore, treatment with high glucose decreased the expression of miR-25 in cultured kidney cells. In db/db mice, systemic administration of an miR-25 agomir repressed glomerular fibrosis and reduced high BP. Notably, knockdown of miR-25 in normal mice by systemic administration of an miR-25 antagomir resulted in increased proteinuria, extracellular matrix accumulation, podocyte foot process effacement, and hypertension with renin-angiotensin system activation. However, excessive miR-25 did not cause kidney dysfunction in wild-type mice. RNA sequencing showed the alteration of miR-25 target genes in antagomir-treated mice, including the Ras-related gene CDC42. In vitro,cotrans- fection with the miR-25 antagomir repressed luciferase activity from a reporter construct containing the CDC42 39 untranslated region. -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
Flow Reagents Single Color Antibodies CD Chart
CD CHART CD N° Alternative Name CD N° Alternative Name CD N° Alternative Name Beckman Coulter Clone Beckman Coulter Clone Beckman Coulter Clone T Cells B Cells Granulocytes NK Cells Macrophages/Monocytes Platelets Erythrocytes Stem Cells Dendritic Cells Endothelial Cells Epithelial Cells T Cells B Cells Granulocytes NK Cells Macrophages/Monocytes Platelets Erythrocytes Stem Cells Dendritic Cells Endothelial Cells Epithelial Cells T Cells B Cells Granulocytes NK Cells Macrophages/Monocytes Platelets Erythrocytes Stem Cells Dendritic Cells Endothelial Cells Epithelial Cells CD1a T6, R4, HTA1 Act p n n p n n S l CD99 MIC2 gene product, E2 p p p CD223 LAG-3 (Lymphocyte activation gene 3) Act n Act p n CD1b R1 Act p n n p n n S CD99R restricted CD99 p p CD224 GGT (γ-glutamyl transferase) p p p p p p CD1c R7, M241 Act S n n p n n S l CD100 SEMA4D (semaphorin 4D) p Low p p p n n CD225 Leu13, interferon induced transmembrane protein 1 (IFITM1). p p p p p CD1d R3 Act S n n Low n n S Intest CD101 V7, P126 Act n p n p n n p CD226 DNAM-1, PTA-1 Act n Act Act Act n p n CD1e R2 n n n n S CD102 ICAM-2 (intercellular adhesion molecule-2) p p n p Folli p CD227 MUC1, mucin 1, episialin, PUM, PEM, EMA, DF3, H23 Act p CD2 T11; Tp50; sheep red blood cell (SRBC) receptor; LFA-2 p S n p n n l CD103 HML-1 (human mucosal lymphocytes antigen 1), integrin aE chain S n n n n n n n l CD228 Melanotransferrin (MT), p97 p p CD3 T3, CD3 complex p n n n n n n n n n l CD104 integrin b4 chain; TSP-1180 n n n n n n n p p CD229 Ly9, T-lymphocyte surface antigen p p n p n -
Association of Gene Ontology Categories with Decay Rate for Hepg2 Experiments These Tables Show Details for All Gene Ontology Categories
Supplementary Table 1: Association of Gene Ontology Categories with Decay Rate for HepG2 Experiments These tables show details for all Gene Ontology categories. Inferences for manual classification scheme shown at the bottom. Those categories used in Figure 1A are highlighted in bold. Standard Deviations are shown in parentheses. P-values less than 1E-20 are indicated with a "0". Rate r (hour^-1) Half-life < 2hr. Decay % GO Number Category Name Probe Sets Group Non-Group Distribution p-value In-Group Non-Group Representation p-value GO:0006350 transcription 1523 0.221 (0.009) 0.127 (0.002) FASTER 0 13.1 (0.4) 4.5 (0.1) OVER 0 GO:0006351 transcription, DNA-dependent 1498 0.220 (0.009) 0.127 (0.002) FASTER 0 13.0 (0.4) 4.5 (0.1) OVER 0 GO:0006355 regulation of transcription, DNA-dependent 1163 0.230 (0.011) 0.128 (0.002) FASTER 5.00E-21 14.2 (0.5) 4.6 (0.1) OVER 0 GO:0006366 transcription from Pol II promoter 845 0.225 (0.012) 0.130 (0.002) FASTER 1.88E-14 13.0 (0.5) 4.8 (0.1) OVER 0 GO:0006139 nucleobase, nucleoside, nucleotide and nucleic acid metabolism3004 0.173 (0.006) 0.127 (0.002) FASTER 1.28E-12 8.4 (0.2) 4.5 (0.1) OVER 0 GO:0006357 regulation of transcription from Pol II promoter 487 0.231 (0.016) 0.132 (0.002) FASTER 6.05E-10 13.5 (0.6) 4.9 (0.1) OVER 0 GO:0008283 cell proliferation 625 0.189 (0.014) 0.132 (0.002) FASTER 1.95E-05 10.1 (0.6) 5.0 (0.1) OVER 1.50E-20 GO:0006513 monoubiquitination 36 0.305 (0.049) 0.134 (0.002) FASTER 2.69E-04 25.4 (4.4) 5.1 (0.1) OVER 2.04E-06 GO:0007050 cell cycle arrest 57 0.311 (0.054) 0.133 (0.002) -
CD Markers Are Routinely Used for the Immunophenotyping of Cells
ptglab.com 1 CD MARKER ANTIBODIES www.ptglab.com Introduction The cluster of differentiation (abbreviated as CD) is a protocol used for the identification and investigation of cell surface molecules. So-called CD markers are routinely used for the immunophenotyping of cells. Despite this use, they are not limited to roles in the immune system and perform a variety of roles in cell differentiation, adhesion, migration, blood clotting, gamete fertilization, amino acid transport and apoptosis, among many others. As such, Proteintech’s mini catalog featuring its antibodies targeting CD markers is applicable to a wide range of research disciplines. PRODUCT FOCUS PECAM1 Platelet endothelial cell adhesion of blood vessels – making up a large portion molecule-1 (PECAM1), also known as cluster of its intracellular junctions. PECAM-1 is also CD Number of differentiation 31 (CD31), is a member of present on the surface of hematopoietic the immunoglobulin gene superfamily of cell cells and immune cells including platelets, CD31 adhesion molecules. It is highly expressed monocytes, neutrophils, natural killer cells, on the surface of the endothelium – the thin megakaryocytes and some types of T-cell. Catalog Number layer of endothelial cells lining the interior 11256-1-AP Type Rabbit Polyclonal Applications ELISA, FC, IF, IHC, IP, WB 16 Publications Immunohistochemical of paraffin-embedded Figure 1: Immunofluorescence staining human hepatocirrhosis using PECAM1, CD31 of PECAM1 (11256-1-AP), Alexa 488 goat antibody (11265-1-AP) at a dilution of 1:50 anti-rabbit (green), and smooth muscle KD/KO Validated (40x objective). alpha-actin (red), courtesy of Nicola Smart. PECAM1: Customer Testimonial Nicola Smart, a cardiovascular researcher “As you can see [the immunostaining] is and a group leader at the University of extremely clean and specific [and] displays Oxford, has said of the PECAM1 antibody strong intercellular junction expression, (11265-1-AP) that it “worked beautifully as expected for a cell adhesion molecule.” on every occasion I’ve tried it.” Proteintech thanks Dr. -
CDH1 Gene Cadherin 1
CDH1 gene cadherin 1 Normal Function The CDH1 gene provides instructions for making a protein called epithelial cadherin or E-cadherin. This protein is found within the membrane that surrounds epithelial cells, which are the cells that line the surfaces and cavities of the body, such as the inside of the eyelids and mouth. E-cadherin belongs to a family of proteins called cadherins whose function is to help neighboring cells stick to one another (cell adhesion) to form organized tissues. Another protein called p120-catenin, produced from the CTNND1 gene, helps keep E-cadherin in its proper place in the cell membrane, preventing it from being taken into the cell through a process called endocytosis and broken down prematurely. E-cadherin is one of the best-understood cadherin proteins. In addition to its role in cell adhesion, E-cadherin is involved in transmitting chemical signals within cells, controlling cell maturation and movement, and regulating the activity of certain genes. Interactions between the E-cadherin and p120-catenin proteins, in particular, are thought to be important for normal development of the head and face (craniofacial development), including the eyelids and teeth. E-cadherin also acts as a tumor suppressor protein, which means it prevents cells from growing and dividing too rapidly or in an uncontrolled way. Health Conditions Related to Genetic Changes Breast cancer Inherited mutations in the CDH1 gene increase a woman's risk of developing a form of breast cancer that begins in the milk-producing glands (lobular breast cancer). In many cases, this increased risk occurs as part of an inherited cancer disorder called hereditary diffuse gastric cancer (HDGC) (described below). -
The Oestrogen Receptor Alpha-Regulated Lncrna NEAT1 Is a Critical Modulator of Prostate Cancer
ARTICLE Received 5 Dec 2013 | Accepted 26 Sep 2014 | Published 21 Nov 2014 DOI: 10.1038/ncomms6383 OPEN The oestrogen receptor alpha-regulated lncRNA NEAT1 is a critical modulator of prostate cancer Dimple Chakravarty1,2, Andrea Sboner1,2,3, Sujit S. Nair4, Eugenia Giannopoulou5,6, Ruohan Li7, Sven Hennig8, Juan Miguel Mosquera1,2, Jonathan Pauwels1, Kyung Park1, Myriam Kossai1,2, Theresa Y. MacDonald1, Jacqueline Fontugne1,2, Nicholas Erho9, Ismael A. Vergara9, Mercedeh Ghadessi9, Elai Davicioni9, Robert B. Jenkins10, Nallasivam Palanisamy11,12, Zhengming Chen13, Shinichi Nakagawa14, Tetsuro Hirose15, Neil H. Bander16, Himisha Beltran1,2, Archa H. Fox7, Olivier Elemento2,3 & Mark A. Rubin1,2 The androgen receptor (AR) plays a central role in establishing an oncogenic cascade that drives prostate cancer progression. Some prostate cancers escape androgen dependence and are often associated with an aggressive phenotype. The oestrogen receptor alpha (ERa)is expressed in prostate cancers, independent of AR status. However, the role of ERa remains elusive. Using a combination of chromatin immunoprecipitation (ChIP) and RNA-sequencing data, we identified an ERa-specific non-coding transcriptome signature. Among putatively ERa-regulated intergenic long non-coding RNAs (lncRNAs), we identified nuclear enriched abundant transcript 1 (NEAT1) as the most significantly overexpressed lncRNA in prostate cancer. Analysis of two large clinical cohorts also revealed that NEAT1 expression is asso- ciated with prostate cancer progression. Prostate cancer cells expressing high levels of NEAT1 were recalcitrant to androgen or AR antagonists. Finally, we provide evidence that NEAT1 drives oncogenic growth by altering the epigenetic landscape of target gene promoters to favour transcription. 1 Department of Pathology and Laboratory Medicine, Weill Medical College of Cornell University, 413 East 69th Street, Room 1402, New York, New York 10021, USA.