Literature DB >> 31377433

Clinical use of SNP-microarrays for the detection of genome-wide changes in haematological malignancies.

Nadine K Berry1, Rodney J Scott2, Philip Rowlings3, Anoop K Enjeti3.   

Abstract

Single nucleotide polymorphism (SNP) microarrays are commonly used for the clinical investigation of constitutional genomic disorders; however, their adoption for investigating somatic changes is being recognised. With increasing importance being placed on defining the cancer genome, a shift in technology is imperative at a clinical level. Microarray platforms have the potential to become frontline testing, replacing or complementing standard investigations such as FISH or karyotype. This 'molecular karyotype approach' exemplified by SNP-microarrays has distinct advantages in the investigation of several haematological malignancies. A growing body of literature, including guidelines, has shown support for the use of SNP-microarrays in the clinical laboratory to aid in a more accurate definition of the cancer genome. Understanding the benefits of this technology along with discussing the barriers to its implementation is necessary for the development and incorporation of SNP-microarrays in a clinical laboratory for the investigation of haematological malignancies.
Copyright © 2019 The Author(s). Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Haematological malignancies; Haematology; Microarray; SNP-microarray

Mesh:

Year:  2019        PMID: 31377433     DOI: 10.1016/j.critrevonc.2019.07.016

Source DB:  PubMed          Journal:  Crit Rev Oncol Hematol        ISSN: 1040-8428            Impact factor:   6.312


  4 in total

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Review 2.  A Tangle of Genomic Aberrations Drives Multiple Myeloma and Correlates with Clinical Aggressiveness of the Disease: A Comprehensive Review from a Biological Perspective to Clinical Trial Results.

Authors:  Mariarosaria Sessa; Francesco Cavazzini; Maurizio Cavallari; Gian Matteo Rigolin; Antonio Cuneo
Journal:  Genes (Basel)       Date:  2020-12-03       Impact factor: 4.096

3.  Genetic variations analysis for complex brain disease diagnosis using machine learning techniques: opportunities and hurdles.

Authors:  Hala Ahmed; Louai Alarabi; Shaker El-Sappagh; Hassan Soliman; Mohammed Elmogy
Journal:  PeerJ Comput Sci       Date:  2021-09-20

4.  Prognostic impact of pre-transplant chromosomal aberrations in peripheral blood of patients undergoing unrelated donor hematopoietic cell transplant for acute myeloid leukemia.

Authors:  Youjin Wang; Weiyin Zhou; Lisa J McReynolds; Hormuzd A Katki; Elizabeth A Griffiths; Swapna Thota; Mitchell J Machiela; Meredith Yeager; Philip McCarthy; Marcelo Pasquini; Junke Wang; Ezgi Karaesmen; Abbas Rizvi; Leah Preus; Hancong Tang; Yiwen Wang; Loreall Pooler; Xin Sheng; Christopher A Haiman; David Van Den Berg; Stephen R Spellman; Tao Wang; Michelle Kuxhausen; Stephen J Chanock; Stephanie J Lee; Theresa E Hahn; Lara E Sucheston-Campbell; Shahinaz M Gadalla
Journal:  Sci Rep       Date:  2021-07-22       Impact factor: 4.996

  4 in total

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