Evolution of Cancer Genomics and Its Clinical Implications
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DNA Repair and Synthetic Lethality
Int J Oral Sci (2011) 3:176-179. www.ijos.org.cn REVIEW DNA repair and synthetic lethality Gong-she Guo1, Feng-mei Zhang1, Rui-jie Gao2, Robert Delsite4, Zhi-hui Feng1,3*, Simon N. Powell4* 1School of Public Health, Shandong University, Jinan 250012, China; 2Second People’s Hospital of Weifang, Weifang 261041, China; 3Department of Radiation Oncology, Washington University in St Louis, St Louis MO 63108, USA; 4Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York NY 10065, USA Tumors often have DNA repair defects, suggesting additional inhibition of other DNA repair pathways in tumors may lead to synthetic lethality. Accumulating data demonstrate that DNA repair-defective tumors, in particular homologous recombination (HR), are highly sensitive to DNA-damaging agents. Thus, HR-defective tumors exhibit potential vulnerability to the synthetic lethality approach, which may lead to new therapeutic strategies. It is well known that poly (adenosine diphosphate (ADP)-ribose) polymerase (PARP) inhibitors show the synthetically lethal effect in tumors defective in BRCA1 or BRCA2 genes encoded proteins that are required for efficient HR. In this review, we summarize the strategies of targeting DNA repair pathways and other DNA metabolic functions to cause synthetic lethality in HR-defective tumor cells. Keywords: DNA repair; homologous recombination; synthetic lethality; BRCA; Rad52 International Journal of Oral Science (2011) 3: 176-179. doi: 10.4248/IJOS11064 Introduction polymerase (PARP) inhibitors are specifically toxic to homologous recombination (HR)-defective cells [3-4]. Synthetic lethality is defined as a genetic combination Playing a key role in maintaining genetic stability, HR is of mutations in two or more genes that leads to cell a major repair pathway for double-strand breaks (DSBs) death, whereas a mutation in any one of the genes does utilizing undamaged homologous DNA sequence [5-6]. -
Comparative Oncogenomics Identifies Tyrosine Kinase FES As a Tumor Suppressor in Melanoma
RESEARCH ARTICLE The Journal of Clinical Investigation Comparative oncogenomics identifies tyrosine kinase FES as a tumor suppressor in melanoma Michael Olvedy,1,2 Julie C. Tisserand,3 Flavie Luciani,1,2 Bram Boeckx,4,5 Jasper Wouters,6,7 Sophie Lopez,3 Florian Rambow,1,2 Sara Aibar,6,7 Bernard Thienpont,4,5 Jasmine Barra,1,2 Corinna Köhler,1,2 Enrico Radaelli,8 Sophie Tartare-Deckert,9 Stein Aerts,6,7 Patrice Dubreuil,3 Joost J. van den Oord,10 Diether Lambrechts,4,5 Paulo De Sepulveda,3 and Jean-Christophe Marine1,2 1Laboratory for Molecular Cancer Biology, Center for Cancer Biology, Vlaams Instituut voor Biotechnologie (VIB), Leuven, Belgium. 2Laboratory for Molecular Cancer Biology, Department of Oncology, KU Leuven, Leuven, Belgium. 3INSERM, Aix Marseille University, CNRS, Institut Paoli-Calmettes, CRCM, Equipe Labellisée Ligue Contre le Cancer, Marseille, France. 4Laboratory for Translational Genetics, Center for Cancer Biology, VIB, Leuven, Belgium. 5Laboratory for Translational Genetics, and 6Laboratory of Computational Biology, Department of Human Genetics, KU Leuven, Leuven, Belgium. 7Laboratory of Computational Biology, and 8Mouse Histopathology Core Facility, VIB Center for Brain & Disease Research, Leuven, Belgium. 9Centre Méditerranéen de Médecine Moléculaire (C3M), INSERM, U1065, Université Côte d’Azur, Nice, France. 10Laboratory of Translational Cell and Tissue Research, Department of Pathology, KU Leuven and UZ Leuven, Leuven, Belgium. Identification and functional validation of oncogenic drivers are essential steps toward -
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. -
Advances in Understanding Cancer Genomes Through Second-Generation Sequencing
Advances in understanding cancer genomes through second-generation sequencing Matthew Meyerson, Stacey Gabriel and Gad Getz Second-generation A major near-term medical impact of the genome comprehensive genome-based diagnosis of cancer is sequencing technology revolution will be the elucidation of mecha- becoming increasingly crucial for therapeutic decisions. Used in this Review to refer to nisms of cancer pathogenesis, leading to improvements During the past decades, there have been major sequencing methods that have in the diagnosis of cancer and the selection of cancer advances in experimental and informatic methods emerged since 2005 that second-generation sequencing parallelize the sequencing treatment. Thanks to for genome characterization based on DNA and RNA 1–5 process and produce millions technologies , recently it has become feasible to microarrays and on capillary-based DNA sequenc- of typically short sequence sequence the expressed genes (‘transcriptomes’)6,7, ing (‘first-generation sequencing’, also known as Sanger reads (50–400 bases) from known exons (‘exomes’)8,9, and complete genomes10–15 sequencing). These technologies provided the ability amplified DNA clones. of cancer samples. to analyse exonic mutations and copy number altera- It is also often known as next-generation sequencing. These technological advances are important for tions and have led to the discovery of many important advancing our understanding of malignant neoplasms alterations in the cancer genome20. because cancer is fundamentally a disease of the genome. However, there are particular challenges for the A wide range of genomic alterations — including point detection and diagnosis of cancer genome alterations. mutations, copy number changes and rearrangements For example, some genomic alterations in cancer are — can lead to the development of cancer. -
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. -
The Tumor Therapy Landscape of Synthetic Lethality
ARTICLE https://doi.org/10.1038/s41467-021-21544-2 OPEN The tumor therapy landscape of synthetic lethality Biyu Zhang1,4, Chen Tang1,4, Yanli Yao2,4, Xiaohan Chen1, Chi Zhou 1, Zhiting Wei1, Feiyang Xing1, Lan Chen2, ✉ ✉ Xiang Cai3, Zhiyuan Zhang2, Shuyang Sun 2 & Qi Liu 1 Synthetic lethality is emerging as an important cancer therapeutic paradigm, while the comprehensive selective treatment opportunities for various tumors have not yet been explored. We develop the Synthetic Lethality Knowledge Graph (SLKG), presenting the tumor therapy landscape of synthetic lethality (SL) and synthetic dosage lethality (SDL). SLKG 1234567890():,; integrates the large-scale entity of different tumors, drugs and drug targets by exploring a comprehensive set of SL and SDL pairs. The overall therapy landscape is prioritized to identify the best repurposable drug candidates and drug combinations with literature supports, in vitro pharmacologic evidence or clinical trial records. Finally, cladribine, an FDA-approved multiple sclerosis treatment drug, is selected and identified as a repurposable drug for treating melanoma with CDKN2A mutation by in vitro validation, serving as a demonstrating SLKG utility example for novel tumor therapy discovery. Collectively, SLKG forms the com- putational basis to uncover cancer-specific susceptibilities and therapy strategies based on the principle of synthetic lethality. 1 Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, China. 2 Department of Oral and Maxillofacial-Head Neck Oncology, Shanghai Ninth People’s Hospital, College of Stomatology, Shanghai Jiao Tong University School of Medicine, Shanghai, China. -
Rare Variants in the DNA Repair Pathway and the Risk of Colorectal Cancer Marco Matejcic1, Hiba A
Author Manuscript Published OnlineFirst on February 24, 2021; DOI: 10.1158/1055-9965.EPI-20-1457 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Rare variants in the DNA repair pathway and the risk of colorectal cancer Marco Matejcic1, Hiba A. Shaban1, Melanie W. Quintana2, Fredrick R. Schumacher3,4, Christopher K. Edlund5, Leah Naghi6, Rish K. Pai7, Robert W. Haile8, A. Joan Levine8, Daniel D. Buchanan9,10,11, Mark A. Jenkins12, Jane C. Figueiredo13, Gad Rennert14, Stephen B. Gruber15, Li Li16, Graham Casey17, David V. Conti18†, Stephanie L. Schmit1,19† † These authors contributed equally to this work. Affiliations 1 Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL 33612, USA 2 Berry Consultants, Austin, TX, 78746, USA 3 Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH 44106, USA 4 Seidman Cancer Center, University Hospitals, Cleveland, OH 44106, USA 5 Department of Preventive Medicine, USC Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA 6 Department of Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, NY 10467, USA 7 Department of Laboratory Medicine and Pathology, Mayo Clinic Arizona, Scottsdale, AZ 85259, USA 8 Department of Medicine, Research Center for Health Equity, Cedars-Sinai Samuel Oschin Comprehensive Cancer Center, Los Angeles, CA 90048, USA 9 Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria 3010, Australia 10 Victorian Comprehensive Cancer Centre, University of Melbourne, Centre for Cancer Research, Parkville, Victoria 3010, Australia 1 Downloaded from cebp.aacrjournals.org on September 29, 2021. -
A Sleeping Beauty Mutagenesis Screen Reveals a Tumor Suppressor
A Sleeping Beauty mutagenesis screen reveals a tumor PNAS PLUS suppressor role for Ncoa2/Src-2 in liver cancer Kathryn A. O’Donnella,b,1,2, Vincent W. Kengc,d,e, Brian Yorkf, Erin L. Reinekef, Daekwan Seog, Danhua Fanc,h, Kevin A. T. Silversteinc,h, Christina T. Schruma,b, Wei Rose Xiea,b,3, Loris Mularonii,j, Sarah J. Wheelani,j, Michael S. Torbensonk, Bert W. O’Malleyf, David A. Largaespadac,d,e, and Jef D. Boekea,b,i,2 Departments of aMolecular Biology and Genetics, iOncology, jDivision of Biostatistics and Bioinformatics, and kPathology and bThe High Throughput Biology Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21205; cMasonic Cancer Center, dDepartment of Genetics, Cell Biology, and Development, eCenter for Genome Engineering, and hBiostatistics and Bioinformatics Core, University of Minnesota, Minneapolis, MN 55455; fDepartment of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030; and gLaboratory of Experimental Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892 Edited by Harold Varmus, National Cancer Institute, Bethesda, MD, and approved March 23, 2012 (received for review September 21, 2011) The Sleeping Beauty (SB) transposon mutagenesis system is a pow- alterations have been documented in liver cancer, the key genetic erful tool that facilitates the discovery of mutations that accelerate alterations that drive hepatocellular transformation remain tumorigenesis. In this study, we sought to identify mutations that poorly understood. Nevertheless, a unifying feature of human cooperate with MYC, one of the most commonly dysregulated HCC is amplification or overexpression of the MYC oncogene (8, genes in human malignancy. -
Oncogenomics: Clinical Pathogenesis Approach
International Journal of Genetics, ISSN: 0975–2862, Volume 1, Issue 2, 2009, pp-25-43 Oncogenomics: Clinical pathogenesis approach Gupta G. 1, Gupta N. 2, Trivedi S. 3, Patil P. 5, Gupta M. 2, Jhadav A. 4, Vamsi K.K.6, Khairnar Y. 4, Boraste A. 4, Mujapara A.K. 7, Joshi B.8 1S.D.S.M. College Palghar, Mumbai 2Sindhu Mahavidyalaya Panchpaoli Nagpur 3V.V.P. Engineering College, Rajkot, Gujrat 4Padmashree Dr. D.Y. Patil University, Navi Mumbai, 400614, India 5Dr. D. Y. Patil ACS College, Pimpri, Pune 6Rai foundations College CBD Belapur Navi Mumbai 7Sir PP Institute of Science, Bhavnagar 8Rural College of Pharmacy, D.S Road, Bevanahalli, Banglore Abstract - Oncogenomics is new research sub-field of genomics, which applies high throughput technologies to characterize genes associated with cancer and synonymous with cancer genomics. The goal of oncogenomics is to identify new oncogenes or tumor suppressor genes that may provide new insights into cancer diagnosis, predicting clinical outcome of cancers, and new targets for cancer therapies. Oncoproteomics is the term used to describe the application of proteomic technologies in oncology and parallels the related field of oncogenomics. It is now contributing to the development of personalized management of cancer. Genomics has generated a wealth of data that is now being used to identify additional molecular alterations associated with cancer development. Mapping these alterations in the cancer genome is a critical first step in dissecting oncological pathways. Keywords - Biomarkers, Drug development, Drug resistance, Gene therapy, Oncogenomics Introduction Oncogenomics applies high throughput technologies to characterize genes associated transducing cellular signals of cell growth or with cancer and is used to identify new death. -
Strategic Plan 2011-2016
Strategic Plan 2011-2016 Wellcome Trust Sanger Institute Strategic Plan 2011-2016 Mission The Wellcome Trust Sanger Institute uses genome sequences to advance understanding of the biology of humans and pathogens in order to improve human health. -i- Wellcome Trust Sanger Institute Strategic Plan 2011-2016 - ii - Wellcome Trust Sanger Institute Strategic Plan 2011-2016 CONTENTS Foreword ....................................................................................................................................1 Overview .....................................................................................................................................2 1. History and philosophy ............................................................................................................ 5 2. Organisation of the science ..................................................................................................... 5 3. Developments in the scientific portfolio ................................................................................... 7 4. Summary of the Scientific Programmes 2011 – 2016 .............................................................. 8 4.1 Cancer Genetics and Genomics ................................................................................ 8 4.2 Human Genetics ...................................................................................................... 10 4.3 Pathogen Variation .................................................................................................. 13 4.4 Malaria