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T. Franklin Williams Scholars Program
Developing a New Generation of Medical Subspecialists with Expertise in Aging and Care of the Elderly T. Franklin Williams Scholars Program Report to T. Franklin Williams Scholars Program Evaluation Team ASP Geriatrics Steering Committee Integrating Geriatrics Project Evaluation Team May 2011 Submitted by: Erika D. Tarver Project Administrator Association of Specialty Professors 330 John Carlyle Road Suite 610 Alexandria, VA 22314 T: (703) 341-4540 F: (703) 519-1890 [email protected] Kevin P. High, MD Principal Investigator William R. Hazzard, MD Co-Principal Investigator Table of Contents Narrative Progress Report Application and Award Progress Summary of Success of T. Williams Scholars Program Appendices A. 2008 Scholars 24-Month Progress Reports Neena S. Abraham, MD (Note: This is Dr. Abraham’s final report) Steven G. Coca, DO Jeffrey G. Horowitz, MD Danelle F. James, MD Heidi Klepin, MD George C. Wang, MD 2009 Williams Scholars Progress Reports and Summary of 18-Month Questionnaire B. Peter Abadir, MD 12-month Progress Report C. Kathleen M. Akgun, MD 12-Month Progress Report Publication D. Alison Huang, MD 12-Month Progress Report Publication E. Eswar Krishnan, MD 12-Month Progress Report Publication F. Rohit Loomba, MD Publication G. Sharmilee Nyenhuis, MD 12-Month Progress Report Publication H. Peter P. Reese, MD 12-Month Progress Report Publication I. Erik B. Schelbert, MD 12-Month Progress Report Publication J. Helen Keipp Talbot, MD 12-Month Progress Report Publication K. Summary of 18-Month Questionnaire 2010 Williams Scholars Mentor Interviews and Summary of Six-Month Questionnaire L. Kellie Hunter-Campbell, MD Six-Month Mentor Interview M. -
Insights Into the Genetic Basis of the Renal Cell Carcinomas from the Cancer Genome Atlas Scott M
Published OnlineFirst June 21, 2016; DOI: 10.1158/1541-7786.MCR-16-0115 Review Molecular Cancer Research Insights into the Genetic Basis of the Renal Cell Carcinomas from The Cancer Genome Atlas Scott M. Haake, Jamie D. Weyandt, and W. Kimryn Rathmell Abstract The renal cell carcinomas (RCC), clear cell, papillary, and mutations in chromatin modifier genes. Importantly, the pap- chromophobe, have recently undergone an unmatched geno- illary RCC classification encompasses a heterogeneous group mic characterization by The Cancer Genome Atlas. This anal- of diseases, each with highly distinct genetic and molecular ysis has revealed new insights into each of these malignancies features. In conclusion, this review summarizes RCCs that and underscores the unique biology of clear cell, papillary, and represent a diverse set of malignancies, each with novel bio- chromophobe RCC. Themes that have emerged include dis- logic programs that define new paradigms for cancer biology. tinct mechanisms of metabolic dysregulation and common Mol Cancer Res; 14(7); 589–98. Ó2016 AACR. Introduction ullary carcinoma and translocation carcinoma. It is anticipated that a revised World Health Organization (WHO) pathologic Cancers of the kidney have long fascinated physicians with classification recognizing even more rare and largely low-risk their highly divergent phenotypes and patterns of behavior (1). entities, such as clear cell tubulopapillary RCC and multi- Kidney tumors are conventionally grouped based upon their locular cystic RCC, will be published in 2016 -
Deep Learning-Based Gene Selection in Comprehensive Gene Analysis In
www.nature.com/scientificreports OPEN Deep learning‑based gene selection in comprehensive gene analysis in pancreatic cancer Yasukuni Mori1*, Hajime Yokota2, Isamu Hoshino3, Yosuke Iwatate4, Kohei Wakamatsu5, Takashi Uno2 & Hiroki Suyari1 The selection of genes that are important for obtaining gene expression data is challenging. Here, we developed a deep learning‑based feature selection method suitable for gene selection. Our novel deep learning model includes an additional feature‑selection layer. After model training, the units in this layer with high weights correspond to the genes that worked efectively in the processing of the networks. Cancer tissue samples and adjacent normal pancreatic tissue samples were collected from 13 patients with pancreatic ductal adenocarcinoma during surgery and subsequently frozen. After processing, gene expression data were extracted from the specimens using RNA sequencing. Task 1 for the model training was to discriminate between cancerous and normal pancreatic tissue in six patients. Task 2 was to discriminate between patients with pancreatic cancer (n = 13) who survived for more than one year after surgery. The most frequently selected genes were ACACB, ADAMTS6, NCAM1, and CADPS in Task 1, and CD1D, PLA2G16, DACH1, and SOWAHA in Task 2. According to The Cancer Genome Atlas dataset, these genes are all prognostic factors for pancreatic cancer. Thus, the feasibility of using our deep learning‑based method for the selection of genes associated with pancreatic cancer development and prognosis was confrmed. Deep learning techniques have produced impressive results in many felds, including image classifcation, image generation, automated driving, and even board gameplay 1–6. A great deal of research is now being conducted to apply the superior inference performance of deep learning to the feld of medicine 7,8. -
Association of RYR2 Mutation with Tumor Mutation Burden, Prognosis
ORIGINAL RESEARCH published: 17 May 2021 doi: 10.3389/fgene.2021.669694 Association of RYR2 Mutation With Tumor Mutation Burden, Prognosis, and Antitumor Immunity in Patients With Esophageal Adenocarcinoma Zaoqu Liu 1,2,3†, Long Liu 4†, Dechao Jiao 1, Chunguang Guo 5, Libo Wang 4, Zhaonan Li 1, Zhenqiang Sun 6, Yanan Zhao 1,2,3* and Xinwei Han 1,2,3* 1 Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China, 2 Interventional Institute of Zhengzhou University, Zhengzhou, China, 3 Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, China, 4 Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Edited by: 5 Valerio Costa, Zhengzhou University, Zhengzhou, China, Department of Endovascular Surgery, The First Affiliated Hospital of Zhengzhou 6 Consiglio Nazionale delle Ricerche University, Zhengzhou, China, Department of Colorectal Surgery, The First Affiliated Hospital of Zhengzhou University, (CNR), Italy Zhengzhou, China Reviewed by: Umberto Malapelle, Background: Esophageal adenocarcinoma (EAC) remains a leading cause of cancer- University of Naples Federico II, Italy related deaths worldwide and demonstrates a predominant rising incidence in Western Valentina Silvestri, Sapienza University of Rome, Italy countries. Recently, immunotherapy has dramatically changed the landscape of treatment *Correspondence: for many advanced cancers, with the benefit in EAC thus far been limited to a small fraction Yanan Zhao of patients. [email protected] Xinwei Han Methods: Using somatic mutation data of The Cancer Genome Atlas (TCGA) and the [email protected] International Cancer Genome Consortium, we delineated the somatic mutation landscape † These authors have contributed of EAC patients from US and England. -
Journal Pre-Proof
Journal Pre-proof Neutralizing monoclonal antibodies for COVID-19 treatment and prevention Juan P. Jaworski PII: S2319-4170(20)30209-2 DOI: https://doi.org/10.1016/j.bj.2020.11.011 Reference: BJ 374 To appear in: Biomedical Journal Received Date: 2 September 2020 Revised Date: 6 November 2020 Accepted Date: 22 November 2020 Please cite this article as: Jaworski JP, Neutralizing monoclonal antibodies for COVID-19 treatment and prevention, Biomedical Journal, https://doi.org/10.1016/j.bj.2020.11.011. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Chang Gung University. Publishing services by Elsevier B.V. TITLE: Neutralizing monoclonal antibodies for COVID-19 treatment and prevention Juan P. JAWORSKI Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires, Argentina Instituto Nacional de Tecnología Agropecuaria, Buenos Aires, Argentina KEYWORDS: SARS-CoV-2, Coronavirus, Monoclonal Antibody, mAb, Prophylaxis, Treatment CORRESPONDING AUTHOR: Dr. Juan Pablo Jaworski, DVM, MSc, PhD. Consejo Nacional de Investigaciones Científicas y Técnicas Instituto de Virología, Instituto Nacional de Tecnología Agropecuaria Las Cabañas y de los Reseros (S/N), Hurlingham (1686), Buenos Aires, Argentina Tel / Fax: 054-11-4621-1447 (int:3400) [email protected] ABSTRACT The SARS-CoV-2 pandemic has caused unprecedented global health and economic crises. -
Oncogenomic Portals for the Visualization and Analysis of Genome-Wide Cancer Data
www.impactjournals.com/oncotarget/ Oncotarget, Vol. 7, No. 1 Oncogenomic portals for the visualization and analysis of genome-wide cancer data Katarzyna Klonowska1, Karol Czubak1, Marzena Wojciechowska1, Luiza Handschuh1,2, Agnieszka Zmienko1,3, Marek Figlerowicz1,3, Hanna Dams- Kozlowska4,5 and Piotr Kozlowski1 1 European Centre for Bioinformatics and Genomics, Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland 2 Department of Hematology and Bone Marrow Transplantation, Poznan University of Medical Sciences, Poznan, Poland 3 Institute of Computing Sciences, Poznan University of Technology, Poznan, Poland 4 Department of Diagnostics and Cancer Immunology, Greater Poland Cancer Centre, Poznan, Poland 5 Chair of Medical Biotechnology, Poznan University of Medical Sciences, Poznan, Poland Correspondence to: Piotr Kozlowski, email: [email protected] Keywords: cBioPortal, COSMIC, IntOGen, PPISURV/MIRUMIR, Tumorscape Received: June 18, 2015 Accepted: September 28, 2015 Published: October 15, 2015 This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT Somatically acquired genomic alterations that drive oncogenic cellular processes are of great scientific and clinical interest. Since the initiation of large-scale cancer genomic projects (e.g., the Cancer Genome Project, The Cancer Genome Atlas, and the International Cancer Genome Consortium cancer genome projects), a number of web-based portals have been created to facilitate access to multidimensional oncogenomic data and assist with the interpretation of the data. The portals provide the visualization of small-size mutations, copy number variations, methylation, and gene/protein expression data that can be correlated with the available clinical, epidemiological, and molecular features. -
Metastatic Adrenocortical Carcinoma Displays Higher Mutation Rate and Tumor Heterogeneity Than Primary Tumors
ARTICLE DOI: 10.1038/s41467-018-06366-z OPEN Metastatic adrenocortical carcinoma displays higher mutation rate and tumor heterogeneity than primary tumors Sudheer Kumar Gara1, Justin Lack2, Lisa Zhang1, Emerson Harris1, Margaret Cam2 & Electron Kebebew1,3 Adrenocortical cancer (ACC) is a rare cancer with poor prognosis and high mortality due to metastatic disease. All reported genetic alterations have been in primary ACC, and it is 1234567890():,; unknown if there is molecular heterogeneity in ACC. Here, we report the genetic changes associated with metastatic ACC compared to primary ACCs and tumor heterogeneity. We performed whole-exome sequencing of 33 metastatic tumors. The overall mutation rate (per megabase) in metastatic tumors was 2.8-fold higher than primary ACC tumor samples. We found tumor heterogeneity among different metastatic sites in ACC and discovered recurrent mutations in several novel genes. We observed 37–57% overlap in genes that are mutated among different metastatic sites within the same patient. We also identified new therapeutic targets in recurrent and metastatic ACC not previously described in primary ACCs. 1 Endocrine Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. 2 Center for Cancer Research, Collaborative Bioinformatics Resource, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. 3 Department of Surgery and Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA. Correspondence and requests for materials should be addressed to E.K. (email: [email protected]) NATURE COMMUNICATIONS | (2018) 9:4172 | DOI: 10.1038/s41467-018-06366-z | www.nature.com/naturecommunications 1 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-06366-z drenocortical carcinoma (ACC) is a rare malignancy with types including primary ACC from the TCGA to understand our A0.7–2 cases per million per year1,2. -
The Challenge of Developing Cancer Biomarkers
Downloaded from genome.cshlp.org on September 26, 2021 - Published by Cold Spring Harbor Laboratory Press Perspective Translational genomics: The challenge of developing cancer biomarkers James D. Brooks1 Department of Urology, Stanford University, Stanford, California 94305, USA Early detection and definitive treatment of cancer have been shown to decrease death and suffering in epidemiologic and intervention studies. Application of genomic approaches to many malignancies has produced thousands of candidate biomarkers for detection and prognostication, yet very few have become established in clinical practice. Fundamental issues related to tumor heterogeneity, cancer progression, natural history, and biomarker performance have provided challenges to biomarker development. Technical issues in biomarker assay detection limits, specificity, clinical de- ployment, and regulation have also slowed progress. The recent emergence of biomarkers and molecular imaging strategies for treatment selection and monitoring demonstrates the promise of cancer biomarkers. Organized efforts by interdisciplinary teams will spur progress in cancer diagnostics. Since the war on cancer was declared in 1972, cancer death rates, and many have been tested on clinical samples and show some after rising for several decades, have begun to slowly decline (Siegel utility. There the story usually stops (Ludwig and Weinstein 2005; et al. 2011). This drop can be attributed to preventive efforts (e.g., Ioannidis and Panagiotou 2011). In fact, the number of biomarkers smoking cessation), improved treatments for advanced disease, approved by the FDA each year for clinical use is in the single digits. and early detection and treatment of localized cancers. Future This drop-off rate shows that the development of biomarkers is progress in prevention and treatment of advanced disease requires every bit as difficult as the development and approval of a new drug. -
HIV?AIDS Researchers at the NIH Clinical Center
The NIH Clinical Center treats a diverse group of patients from all over the world. It also draws researchers from different cultures and backgrounds. Learn more about some of the many researchers who conduct their work on the human immunodeficiency virus (HIV) and acquired immunodeficiency syndrome (AIDS) at the Clinical Center. Thomas C. Quinn, M.D., M.Sc., conducts research for the National Institute of Allergy and Infectious Diseases at the NIH Clinical Center. He is a senior investigator and chief of the International HIV/STD Section of the Laboratory of Immunoregulation. Dr. Quinn obtained his M.D. from Northwestern University. He was a research associate in infectious diseases in the NIAID Laboratory of Parasitic Diseases and completed a fellowship in infectious diseases at the University of Washington. Since 1981, he has been assigned to the division of infectious diseases at Johns Hopkins University, where he became a professor of medicine in 1991. Dr. Quinn is a member of the Institute of Medicine and the National Academy of Sciences and is a fellow of the American Association for the Advancement of Science. His major areas of research are: Definition of epidemiologic features of HIV-1 and HIV-2 infections in developing countries and the United States Assessment of biomedical interventions to control HIV, including circumcision, prevention of mother-to-child transmission, pre-exposure prophylaxis, and vaccine development Assessment of the frequency of Chlamydia trachomatis infections in selected populations using noninvasive sensitive nucleic-acid amplification assays for diagnosis Evaluations of interventions to control blinding trachoma due to Chlamydia trachomatis in sub-Saharan Africa See the full program description. -
That Record-Breaking Sprint to Create a COVID-19 Vaccine The
NATIONAL INSTITUTES OF HEALTH • OFFICE OF THE DIRECTOR | VOLUME 29 ISSUE 5 • SEPTEMBER-OCTOBER 2021 That Record-breaking The Intersection of Man and Machine Sprint to Create a Bionics Gives New Hope to Those Living With Physical Disabilities COVID-19 Vaccine BY MICHAEL TABASKO, OD BY MELISSA GLIM At the end of 2019, most people were looking forward to an exciting 2020, a new decade starting with those magic numbers, 20-20, that denote a sharpness of vision. There would be the Summer Olympics in Japan and the U.S. presidential election. Meanwhile, intramural scientists at the National Institute of Allergy and Infectious Diseases’ Vaccine Research Center (VRC) were designing vaccines for several coronaviruses using a promising, new platform based on messenger RNA (mRNA). Everything changed on a Saturday morning in early January. Chinese scientists CREDIT: TH0MAS BULEA (LEFT); NIH CLINCAL CENTER (RICHT) had isolated a new coronavirus that was (Left) The NIH pediatric exoskeleton for children with cerebral palsy and other movement disorders uses custom actuators causing a serious epidemic in China’s Wuhan from Agilik developed as part of a cooperative research and development agreement with NIH, along with embedded sensors and microcontrollers, to provide overground gait training while worn. (Right) Alexander Theodorakos, a participant province and released its genetic sequence to in a research protocol at the NIH Clinical Center that is evaluating the new pediatric exoskeleton, and Thomas Bulea, the the scientific community around the world. study’s principal investigator, discuss how the device changes the way the legs move when walking. Barney Graham, director of the VRC’s Viral Pathogenesis Laboratory (VPL), and If popular culture is any indication, the notion that bionic technology will VRC research fellow Kizzmekia Corbett someday redefine the boundaries of human function has long held our collective dropped everything and began using this fascination. -
2019 AACR TET TCGA Poster FINAL
Comprehensive analysis of thymic epithelial tumors using an integrated bioinformatics platform reveals novel biological characteristics Milan Radovich1, Jeffrey P. Solzak1, J Ireland2, Wade Webster2, Jesse Paquette2 1Indiana University Melvin and Bren Simon Cancer Center, Indianapolis, IN, USA; 2Tag.bio, San Francisco, CA, USA Background Methods Results Source data: Thymoma TCGA dataset cBioPortal (http://www.cbioportal.orG/study?id=thym_tcGa) 1. Differential expression identifies high tumoral overexpression of muscle autoantigens in patients with Myasthenia Gravis • Thymic epithelial tumors (TETs) are rare maliGnancies Statistical methods with ~500 cases diaGnosed in the US per year Statistical analyses for results 1A, 1B, 2 and 3A were performed usinG TaG.bio protocol apps. Upstream Predicted https://omics.taG.bio/fc-thym/custom/confiG A B Gene P-value Fold-change C Transcriptional Activation • AmonG TETs, thymoma is the most predominant, Analysis 1 - Differential expression for patients with Myasthenia Gravis The expression distribution for each Gene was compared between two cohorts: patients with Myasthenia PPARGC1A Regulator State Z-score P-value -4 characterized by a unique association with myasthenia Gravis (focus cohort) and patients without Myasthenia Gravis (comparison cohort). PPARGC1A <1x10 5.81 PPARGC1A Activated 3.796 0.00347 Statistical test: Mann-Whitney u-test. Raw p-values and false discovery rate estimates (q-values) were Gravis, followed by thymic carcinoma which is less -4 SOX1 Activated 2.887 0.0322 generated. NEFM NEFM <1x10 27.66 common but more clinically aGGressive. Analysis 2 - Differential expression for patients with metastatic Thymoma SOX2 Activated 2.581 0.0178 -3 The expression distribution for each Gene was compared between two cohorts: patients with Masaoka- NEFL <1x10 35.87 AIRE Activated 2.433 0.24 • The Cancer Genome Atlas (TCGA) recently published a KoGa staGe IVa or IVb (focus cohort), and patients with other staGes of the disease (comparison cohort). -
A Prognostic Model for Predicting Recurrence-Free Survival in Hepatocellular Carcinoma Patients
A prognostic model for predicting recurrence-free survival in hepatocellular carcinoma patients Wenhua Wang Nanchang University Lingchen Wang Nanchang University Xinsheng Xie Nanchang University Yehong Yan First Aliated Hospital of Nanchang University Yue Li Nanchang University Quqin Lu ( [email protected] ) Nanchang University https://orcid.org/0000-0003-2813-197X Research article Keywords: TCGA, hepatocellular carcinoma, recurrence-free survival, risk score, prognostic model Posted Date: May 28th, 2020 DOI: https://doi.org/10.21203/rs.3.rs-30658/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Version of Record: A version of this preprint was published on January 5th, 2021. See the published version at https://doi.org/10.1186/s12885-020-07692-6. Page 1/23 Abstract Hepatocellular carcinoma (HCC) remains the most frequent liver cancer, accounting for approximately 90% of primary liver cancers worldwide. The recurrence-free survival (RFS) of HCC patients is a critical factor in devising a personal treatment plan. Thus, it is necessary to accurately forecast the prognosis of HCC patients in clinical practice. Using the The Cancer Genome Atlas TCGA dataset, we identied genes that are associated with RFS. A robust likelihood-based survival modeling approach was used to select the best genes for the prognostic model. Then, the GSE76427 dataset was used to evaluate the prognostic model’s effectiveness. We identied 1331 differentially expressed genes associated with RFS. Seven of these genes were selected to generate the prognostic model. Validation in both the TCGA cohort and the GEO cohort demonstrated that the 7-gene prognostic model has the capability of predicting the RFS of HCC patients.