KAT6A Syndrome: Genotype-Phenotype Correlation in 76 Patients with Pathogenic KAT6A Variants
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ONCOPANEL (Popv3)
ONCOPANEL (POPv3) TEST INFORMATION BACKGROUND: Somatic genetic alterations in oncogenes and tumor-suppressor genes contribute to the pathogenesis and evolution of human cancers. These alterations can provide prognostic and predictive information and stratify cancers for targeted therapeutic information. We classify these alterations into five tiers using the following guidelines: Tier 1: The alteration has well-established published evidence confirming clinical utility in this tumor type, in at least one of the following contexts: predicting response to treatment with an FDA-approved therapy; assessing prognosis; establishing a definitive diagnosis; or conferring an inherited increased risk of cancer to this patient and family. Tier 2: The alteration may have clinical utility in at least one of the following contexts: selection of an investigational therapy in clinical trials for this cancer type; limited evidence of prognostic association; supportive of a specific diagnosis; proven association of response to treatment with an FDA-approved therapy in a different type of cancer; or similar to a different mutation with a proven association with response to treatment with an FDA-approved therapyin this type of cancer. Tier 3: The alteration is of uncertain clinical utility, but may have a role as suggested by at least one of the following: demonstration of association with response to treatment in this cancer type in preclinical studies (e.g., in vitro studies or animal models); alteration in a biochemical pathway that has other known, therapeutically-targetable alterations; alteration in a highly conserved region of the protein predicted, in silico, to alter protein function; or selection of an investigational therapy for a different cancer type. -
Benefits of Cancerplex
CancerPlexSM is a comprehensive genetic assessment of a patient’s tumor that guides oncologists towards effective treatment options. What is CancerPlex? CancerPlex is a next generation DNA sequencing test for solid SM tumors. The specific coding regions of over 400 known cancer Potential outcomes from CancerPlex genes are simultaneously determined using a small amount of Identification of variants associated with response or resis- DNA extracted from tumor samples, including formalin-fixed, tance to an FDA-approved therapy for the patient’s disease. paraffin-embedded (FFPE) tissue and cell blocks from fine-needle aspirates or effusions. This analysis is performed in a single assay, Identification of variants associated with response or resis- simplifying and streamlining the test ordering process, and eliminat- tance to a therapy associated with another clinical indication. ing time consuming serial testing. Clinically actionable information unique to each patient’s tumor is consolidated into a simple report. Identification of variants associated with a therapy(s) in CancerPlex reveals missense changes, insertions and deletions, clinical development. and previously described rearrangements of ALK, RET, and ROS. Benefits of CancerPlex: CancerPlex genes were selected because of their importance in tumor The average turn-around-time for CancerPlex is under 10 biology. Analyzing more genes increases the chance of discovering business days, dramatically shortening the waiting period for actionable findings that lead to more choices for treatment. Our initial the start of treatment. results indicate that CancerPlex analysis identifies actionable findings up to 20% more frequently than previously published studies. CancerPlex ordering is simple: KEW provides all necessary shipping materials, can facilitate tissue retrieval and return with Since knowledge of tumor biology changes rapidly, CancerPlex pathologists, and manages 3rd party payment for the test. -
Further Delineation of the Clinical Spectrum of KAT6B Disorders and Allelic Series of Pathogenic Variants
ARTICLE © American College of Medical Genetics and Genomics Further delineation of the clinical spectrum of KAT6B disorders and allelic series of pathogenic variants Li Xin Zhang1, Gabrielle Lemire, MD2, Claudia Gonzaga-Jauregui, PhD3, Sirinart Molidperee, Gr. Cert1, Carolina Galaz-Montoya, MD3, David S. Liu, MD3, Alain Verloes, MD PhD4, Amelle G. Shillington, DO5, Kosuke Izumi, MD PhD6, Alyssa L. Ritter, MS LCGC7, Beth Keena, MS LCGC6, Elaine Zackai, MD7,8, Dong Li, PhD9, Elizabeth Bhoj, MD PhD7, Jennifer M. Tarpinian, MS CGC10, Emma Bedoukian, MS LCGC10, Mary K. Kukolich, MD11, A. Micheil Innes, MD12, Grace U. Ediae, BSc13, Sarah L. Sawyer, MD PhD14, Karippoth Mohandas Nair, MD15, Para Chottil Soumya, MD15, Kinattinkara R. Subbaraman, MD15, Frank J. Probst, MD PhD3,16, Jennifer A. Bassetti, MD3,16, Reid V. Sutton, MD3,16, Richard A. Gibbs, PhD3, Chester Brown, MD PhD17, Philip M. Boone, MD PhD18, Ingrid A. Holm, MD MPH18, Marco Tartaglia, PhD19, Giovanni Battista Ferrero, MD PhD20, Marcello Niceta, MD PhD19, Maria Lisa Dentici, MD19, Francesca Clementina Radio, MD PhD19, Boris Keren, MD21, Constance F. Wells, MD22, Christine Coubes, MD22, Annie Laquerrière, MD PhD23, Jacqueline Aziza, MD24, Charlotte Dubucs, MD24, Sheela Nampoothiri, MD25, David Mowat, MD26, Millan S. Patel, MD27, Ana Bracho, MD28, Francisco Cammarata-Scalisi, MD29, Alper Gezdirici, MD30, Alberto Fernandez-Jaen, MD31, Natalie Hauser, MD32, Yuri A. Zarate, MD33, Katherine A. Bosanko, MS CGC33, Klaus Dieterich, MD PhD34, John C. Carey, MD MPH35, Jessica X. Chong, PhD36,37, Deborah A. Nickerson, PhD37,38, Michael J. Bamshad, MD36,37, Brendan H. Lee, MD PhD3, Xiang-Jiao Yang, PhD39, James R. -
Abstracts Books 2014
TWENTY-FIFTH EUROPEAN MEETING ON DYSMORPHOLOGY 10 – 12 SEPTEMBER 2014 25th EUROPEAN MEETING ON DYSMORPHOLOGY LE BISCHENBERG WEDNESDAY 10th SEPTEMBER 5 p.m. to 7.30 p.m. Registration 7.30 p.m. to 8.30 p.m. Welcome reception 8.30 p.m. Dinner 9.30 p.m. Unknown THURSDAY 11th SEPTEMBER 8.15 a.m. Opening address 8.30 a.m. to 1.00 p.m. First session 1.00 p.m. Lunch 2.30 p.m. to 7.00 p.m. Second and third sessions 8.00 p.m. Dinner 9.00 p.m. to 11.00 p.m. Unknown FRIDAY 12th SEPTEMBER 8.30 a.m. to 1.00 p.m. Fourth and fifth sessions 1.00 p.m. Lunch 2.30 p.m. to 6.00 p.m. Sixth and seventh sessions 7.30 p.m. Dinner SATURDAY 13th SEPTEMBER Breakfast – Departure Note: This program is tentative and may be modified. WEDNESDAY 10th SEPTEMBER 9.30 UNKNOWN SESSION Chair: FRYNS J.P. H. VAN ESCH Case 1 H. VAN ESCH Case 2 H. JILANI, S. HIZEM, I. REJEB, F. DZIRI AND L. BEN JEMAA Developmental delay, dysmorphic features and hirsutism in a Tunisian girl. Cornelia de Lange syndrome? L. VAN MALDERGEM, C. CABROL, B. LOEYS, M. SALEH, Y. BERNARD, L. CHAMARD AND J. PIARD Megalophthalmos and thoracic great vessels aneurisms E. SCHAEFER AND Y. HERENGER An unknown diagnosis associating facial dysmorphism, developmental delay, posterior urethral valves and severe constipation P. RUMP AND T. VAN ESSEN What’s in the name G. MUBUNGU, A. LUMAKA, K. -
Microrna Regulation of Epigenetic Modifiers in Breast Cancer
cancers Review MicroRNA Regulation of Epigenetic Modifiers in Breast Cancer Brock Humphries 1,* , Zhishan Wang 2 and Chengfeng Yang 2,3,* 1 Center for Molecular Imaging, Department of Radiology, University of Michigan, Ann Arbor, MI 48109; USA 2 Department of Toxicology and Cancer Biology, College of Medicine, University of Kentucky, Lexington, KY 40536, USA 3 Center for Research on Environment Disease, College of Medicine, University of Kentucky, Lexington, KY 40536; USA * Correspondence: [email protected] (B.H.); [email protected] (C.Y.) Received: 24 May 2019; Accepted: 24 June 2019; Published: 27 June 2019 Abstract: Epigenetics refers to the heritable changes in gene expression without a change in the DNA sequence itself. Two of these major changes include aberrant DNA methylation as well as changes to histone modification patterns. Alterations to the epigenome can drive expression of oncogenes and suppression of tumor suppressors, resulting in tumorigenesis and cancer progression. In addition to modifications of the epigenome, microRNA (miRNA) dysregulation is also a hallmark for cancer initiation and metastasis. Advances in our understanding of cancer biology demonstrate that alterations in the epigenome are not only a major cause of miRNA dysregulation in cancer, but that miRNAs themselves also indirectly drive these DNA and histone modifications. More explicitly, recent work has shown that miRNAs can regulate chromatin structure and gene expression by directly targeting key enzymes involved in these processes. This review aims to summarize these research findings specifically in the context of breast cancer. This review also discusses miRNAs as epigenetic biomarkers and as therapeutics, and presents a comprehensive summary of currently validated epigenetic targets in breast cancer. -
Identifying the Risky SNP of Osteoporosis with ID3-PEP Decision Tree Algorithm
Hindawi Complexity Volume 2017, Article ID 9194801, 8 pages https://doi.org/10.1155/2017/9194801 Research Article Identifying the Risky SNP of Osteoporosis with ID3-PEP Decision Tree Algorithm Jincai Yang,1 Huichao Gu,1 Xingpeng Jiang,1 Qingyang Huang,2 Xiaohua Hu,1 and Xianjun Shen1 1 School of Computer Science, Central China Normal University, Wuhan 430079, China 2School of Life Science, Central China Normal University, Wuhan 430079, China Correspondence should be addressed to Jincai Yang; [email protected] Received 31 March 2017; Revised 26 May 2017; Accepted 8 June 2017; Published 7 August 2017 Academic Editor: Fang-Xiang Wu Copyright © 2017 Jincai Yang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In the past 20 years, much progress has been made on the genetic analysis of osteoporosis. A number of genes and SNPs associated with osteoporosis have been found through GWAS method. In this paper, we intend to identify the suspected risky SNPs of osteoporosis with computational methods based on the known osteoporosis GWAS-associated SNPs. The process includes two steps. Firstly, we decided whether the genes associated with the suspected risky SNPs are associated with osteoporosis by using random walk algorithm on the PPI network of osteoporosis GWAS-associated genes and the genes associated with the suspected risky SNPs. In order to solve the overfitting problem in ID3 decision tree algorithm, we then classified the SNPs with positive results based on their features of position and function through a simplified classification decision tree which was constructed by ID3 decision tree algorithm with PEP (Pessimistic-Error Pruning). -
Epigenetic Mechanisms Are Involved in the Oncogenic Properties of ZNF518B in Colorectal Cancer
Epigenetic mechanisms are involved in the oncogenic properties of ZNF518B in colorectal cancer Francisco Gimeno-Valiente, Ángela L. Riffo-Campos, Luis Torres, Noelia Tarazona, Valentina Gambardella, Andrés Cervantes, Gerardo López-Rodas, Luis Franco and Josefa Castillo SUPPLEMENTARY METHODS 1. Selection of genomic sequences for ChIP analysis To select the sequences for ChIP analysis in the five putative target genes, namely, PADI3, ZDHHC2, RGS4, EFNA5 and KAT2B, the genomic region corresponding to the gene was downloaded from Ensembl. Then, zoom was applied to see in detail the promoter, enhancers and regulatory sequences. The details for HCT116 cells were then recovered and the target sequences for factor binding examined. Obviously, there are not data for ZNF518B, but special attention was paid to the target sequences of other zinc-finger containing factors. Finally, the regions that may putatively bind ZNF518B were selected and primers defining amplicons spanning such sequences were searched out. Supplementary Figure S3 gives the location of the amplicons used in each gene. 2. Obtaining the raw data and generating the BAM files for in silico analysis of the effects of EHMT2 and EZH2 silencing The data of siEZH2 (SRR6384524), siG9a (SRR6384526) and siNon-target (SRR6384521) in HCT116 cell line, were downloaded from SRA (Bioproject PRJNA422822, https://www.ncbi. nlm.nih.gov/bioproject/), using SRA-tolkit (https://ncbi.github.io/sra-tools/). All data correspond to RNAseq single end. doBasics = TRUE doAll = FALSE $ fastq-dump -I --split-files SRR6384524 Data quality was checked using the software fastqc (https://www.bioinformatics.babraham. ac.uk /projects/fastqc/). The first low quality removing nucleotides were removed using FASTX- Toolkit (http://hannonlab.cshl.edu/fastxtoolkit/). -
Kat2a and Kat2b Acetyltransferase Activity Regulates Craniofacial Cartilage and Bone Differentiation in Zebrafish and Mice
Journal of Developmental Biology Article Kat2a and Kat2b Acetyltransferase Activity Regulates Craniofacial Cartilage and Bone Differentiation in Zebrafish and Mice Rwik Sen 1,†, Sofia A. Pezoa 2,3,4,†, Lomeli Carpio Shull 1, Laura Hernandez-Lagunas 1, Lee A. Niswander 3,4 and Kristin Bruk Artinger 1,* 1 Department of Craniofacial Biology, School of Dental Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; [email protected] (R.S.); [email protected] (L.C.S.); [email protected] (L.H.-L.) 2 Cell Biology, Stem Cells, and Development Graduate Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Sofi[email protected] 3 Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; [email protected] 4 Molecular Cellular and Developmental Biology, University of Colorado Boulder, Boulder, CO 80309, USA * Correspondence: [email protected]; Tel.: +303-724-4562; Fex: +303-724-4580 † These authors contributed equally to this work. Received: 2 October 2018; Accepted: 7 November 2018; Published: 12 November 2018 Abstract: Cranial neural crest cells undergo cellular growth, patterning, and differentiation within the branchial arches to form cartilage and bone, resulting in a precise pattern of skeletal elements forming the craniofacial skeleton. However, it is unclear how cranial neural crest cells are regulated to give rise to the different shapes and sizes of the bone and cartilage. Epigenetic regulators are good candidates to be involved in this regulation, since they can exert both broad as well as precise control on pattern formation. Here, we investigated the role of the histone acetyltransferases Kat2a and Kat2b in craniofacial development using TALEN/CRISPR/Cas9 mutagenesis in zebrafish and the Kat2ahat/hat (also called Gcn5) allele in mice. -
Identification of Shared and Unique Gene Families Associated with Oral
International Journal of Oral Science (2017) 9, 104–109 OPEN www.nature.com/ijos ORIGINAL ARTICLE Identification of shared and unique gene families associated with oral clefts Noriko Funato and Masataka Nakamura Oral clefts, the most frequent congenital birth defects in humans, are multifactorial disorders caused by genetic and environmental factors. Epidemiological studies point to different etiologies underlying the oral cleft phenotypes, cleft lip (CL), CL and/or palate (CL/P) and cleft palate (CP). More than 350 genes have syndromic and/or nonsyndromic oral cleft associations in humans. Although genes related to genetic disorders associated with oral cleft phenotypes are known, a gap between detecting these associations and interpretation of their biological importance has remained. Here, using a gene ontology analysis approach, we grouped these candidate genes on the basis of different functional categories to gain insight into the genetic etiology of oral clefts. We identified different genetic profiles and found correlations between the functions of gene products and oral cleft phenotypes. Our results indicate inherent differences in the genetic etiologies that underlie oral cleft phenotypes and support epidemiological evidence that genes associated with CL/P are both developmentally and genetically different from CP only, incomplete CP, and submucous CP. The epidemiological differences among cleft phenotypes may reflect differences in the underlying genetic causes. Understanding the different causative etiologies of oral clefts is -
Mir-22/KAT6B Axis Is a Chemotherapeutic Determiner Via
Gu et al. Journal of Experimental & Clinical Cancer Research (2018) 37:164 https://doi.org/10.1186/s13046-018-0834-z RESEARCH Open Access miR-22/KAT6B axis is a chemotherapeutic determiner via regulation of PI3k-Akt-NF-kB pathway in tongue squamous cell carcinoma Yixue Gu1,2†, Hao Liu1,2†, Fangren Kong1, Jiahui Ye1, Xiaoting Jia1,2, Zhijie Zhang1,2, Nan Li1, Jiang Yin1,2, Guopei Zheng1,2* and Zhimin He1,2* Abstract Background: Tongue squamous cell carcinoma (TSCC) is the most common oral cancer. Neoadjuvant systemic treatment before or after surgery for advanced TSCC is considered one of the most crucial factors in reducing mortality. However, the therapeutic benefits of chemotherapy are usually attenuated due to intrinsic and/or acquired drug resistance, and a large proportion of TSCC are resistant to chemotherapy, which may result in more aggressive tumor behavior and an even worse clinical outcome. Recently, the potential application of using miRNAs to predict therapeutic response to cancer treatment holds high promise, but miRNAs with predictive value remain to be identified and underlying mechanisms remain to be understood in TSCC. Methods: The expression of miR-22 in tissues from patients diagnosed with TSCC was analyzed using real-time PCR. The effects of miR-22 on cell proliferation and tumorigenesis in TSCC cells were analyzed by MTS assay, and flow cytometry. The tumor growth in vivo was observed in xenograft model. Luciferase reporter assay, real-time PCR and western blot were performed to validate a potential target of miR-22 in TC. The correlation between miR-22 expression and KAT6B expression, as well as the mechanisms by which miR-22 regulates PI3k-Akt-NF-kB pathway in TSCC were also addressed. -
Next-Generation Sequencing Expanded NGS Gene List
Next-Generation Sequencing Expanded NGS Gene List Mutations (DNA) ABI1 BRD4 CRLF2 FOXO4 HOXC11 KLF4 MUC1 PAK3 RHOH TAL2 ABL1 BTG1 DDB2 FSTL3 HOXC13 KLK2 MUTYH PATZ1 RNF213 TBL1XR1 ACKR3 BTK DDIT3 GATA1 HOXD11 LASP1 MYCL (MYCL1) PAX8 RPL10 TCEA1 AKT1 C15orf65 DNM2 GATA2 HOXD13 LMO1 NBN PDE4DIP SEPT5 TCL1A ® AMER1 (FAM123B) CBLC DNMT3A GNA11 HRAS LMO2 NDRG1 PHF6 SEPT6 TERT Tumor Profiling Services from Caris Molecular Intelligence AR CD79B EIF4A2 GPC3 IKBKE MAFB NKX2-1 PHOX2B SFPQ TFE3 ARAF CDH1 ELF4 HEY1 INHBA MAX NONO PIK3CG SLC45A3 TFPT ATP2B3 CDK12 ELN HIST1H3B IRS2 MECOM NOTCH1 PLAG1 SMARCA4 THRAP3 ATRX CDKN2B ERCC1 HIST1H4I JUN MED12 NRAS PMS1 SOCS1 TLX3 BCL11B CDKN2C ETV4 HLF KAT6A (MYST3) MKL1 NUMA1 POU5F1 SOX2 TMPRSS2 BCL2 CEBPA FAM46C HMGN2P46 KAT6B MLLT11 NUTM2B PPP2R1A SPOP UBR5 Next-Generation BCL2L2 CHCHD7 FANCF HNF1A KCNJ5 MN1 OLIG2 PRF1 SRC VHL Sequencing BCOR CNOT3 FEV HOXA11 KDM5C MPL OMD PRKDC SSX1 WAS Multi-platform, solid tumor BCORL1 COL1A1 FOXL2 HOXA13 KDM6A MSN P2RY8 RAD21 STAG2 ZBTB16 Next-Generation Sequencing for BRD3 COX6C FOXO3 HOXA9 KDSR MTCP1 PAFAH1B2 RECQL4 TAL1 ZRSR2 biomarker analysis for therapeutic decision support additional biomarker analysis Mutations and Copy Number Variations (DNA) ABL2 BRCA21 COPB1 ESR1 FUS KIT MYB PER1 RUNX1 TFG ACSL3 BRIP1 CREB1 ETV1 GAS7 KLHL6 MYC PICALM RUNX1T1 TFRC Chemotherapy 4 – ACSL6 BUB1B CREB3L1 ETV5 GATA3 KMT2A (MLL) MYCN PIK3CA SBDS TGFBR2 AFF1 C11orf30 (EMSY) CREB3L2 ETV6 GID4 (C17orf39) KMT2C (MLL3) MYD88 PIK3R1 SDC4 TLX1 Immunotherapy 4 – AFF3 C2orf44 CREBBP EWSR1 -
Genetic Basis of Human Congenital Heart Disease
This is a free sample of content from Heart Development and Disease. Click here for more information on how to buy the book. Genetic Basis of Human Congenital Heart Disease Shannon N. Nees1 and Wendy K. Chung1,2 1Department of Pediatrics,2Department of Medicine, Columbia University Irving Medical Center, New York, New York 10032, USA Correspondence: [email protected] Congenital heart disease (CHD) is the most common major congenital anomaly with an incidence of ∼1% of live births and is a significant cause of birth defect–related mortality. The genetic mechanisms underlying the development of CHD are complex and remain incompletely understood. Known genetic causes include all classes of genetic variation in- cluding chromosomal aneuploidies, copy number variants, and rare and common single- nucleotide variants, which can be either de novo or inherited. Among patients with CHD, ∼8%–12% have a chromosomal abnormality or aneuploidy, between 3% and 25% have a copy number variation, and 3%–5% have a single-gene defect in an established CHD gene with higher likelihood of identifying a genetic cause in patients with nonisolated CHD. These genetic variants disrupt or alter genes that play an important role in normal cardiac develop- ment and in some cases have pleiotropic effects on other organs. This work reviews some of the most common genetic causes of CHD as well as what is currently known about the underlying mechanisms. ongenital heart disease (CHD) is the most are underdeveloped left-sided cardiac structures Ccommon major congenital anomaly with an and only a single functioning ventricle. The high incidence of ∼1% of live births (Hoffman and concordance in monozygotic twins, the in- Kaplan 2002; Calzolari et al.