Literature DB >> 30393007

Assessing genome-wide copy number aberrations and copy-neutral loss-of-heterozygosity as best practice: An evidence-based review from the Cancer Genomics Consortium working group for plasma cell disorders.

Trevor J Pugh1, James M Fink2, Xinyan Lu3, Susan Mathew4, Joyce Murata-Collins5, Pascale Willem6, Min Fang7.   

Abstract

BACKGROUND: Plasma cell neoplasms (PCNs) encompass a spectrum of disorders including monoclonal gammopathy of undetermined significance, smoldering myeloma, plasma cell myeloma, and plasma cell leukemia. Molecular subtypes have been defined by recurrent cytogenetic abnormalities and somatic mutations that are prognostic and predictive. Karyotype and fluorescence in situ hybridization (FISH) have historically been used to guide management; however, new technologies and markers raise the need to reassess current testing algorithms.
METHODS: We convened a panel of representatives from international clinical laboratories to capture current state-of-the-art testing from published reports and to put forward recommendations for cytogenomic testing of plasma cell neoplasms. We reviewed 65 papers applying FISH, chromosomal microarray (CMA), next-generation sequencing, and gene expression profiling for plasma cell neoplasm diagnosis and prognosis. We also performed a survey of our peers to capture current laboratory practice employed outside our working group.
RESULTS: Plasma cell enrichment is widely used prior to FISH testing, most commonly by magnetic bead selection. A variety of strategies for direct, short- and long-term cell culture are employed to ensure clonal representation for karyotyping. Testing of clinically-informative 1p/1q, del(13q) and del(17p) are common using karyotype, FISH and, increasingly, CMA testing. FISH for a variety of clinically-informative balanced IGH rearrangements is prevalent. Literature review found that CMA analysis can detect abnormalities in 85-100% of patients with PCNs; more specifically, in 5-53% (median 14%) of cases otherwise normal by FISH and cytogenetics. CMA results in plasma cell neoplasms are usually complex, with alteration counts ranging from 1 to 74 (median 10-20), primarily affecting loci not covered by FISH testing. Emerging biomarkers include structural alterations of MYC as well as somatic mutations of KRAS, NRAS, BRAF, and TP53. Together, these may be measured in a comprehensive manner by a combination of newer technologies including CMA and next-generation sequencing (NGS). Our survey suggests most laboratories have, or are soon to have, clinical CMA platforms, with a desire to move to NGS assays in the future.
CONCLUSION: We present an overview of current practices in plasma cell neoplasm testing as well as an algorithm for integrated FISH and CMA testing to guide treatment of this disease.
Copyright © 2018. Published by Elsevier Inc.

Entities:  

Keywords:  Chromosomal microarray testing; Cytogenetics; Guidelines; Multiple myeloma; Next-generation sequencing; Plasma cell disorders; Plasma cell myeloma; Recommendations

Mesh:

Substances:

Year:  2018        PMID: 30393007     DOI: 10.1016/j.cancergen.2018.07.002

Source DB:  PubMed          Journal:  Cancer Genet


  5 in total

Review 1.  The complex karyotype in hematological malignancies: a comprehensive overview by the Francophone Group of Hematological Cytogenetics (GFCH).

Authors:  F Nguyen-Khac; A Bidet; A Daudignon; M Lafage-Pochitaloff; G Ameye; C Bilhou-Nabéra; E Chapiro; M A Collonge-Rame; W Cuccuini; N Douet-Guilbert; V Eclache; I Luquet; L Michaux; N Nadal; D Penther; B Quilichini; C Terre; C Lefebvre; M-B Troadec; L Véronèse
Journal:  Leukemia       Date:  2022-04-16       Impact factor: 12.883

2.  Mate pair sequencing outperforms fluorescence in situ hybridization in the genomic characterization of multiple myeloma.

Authors:  James Smadbeck; Jess F Peterson; Kathryn E Pearce; Beth A Pitel; Andrea Lebron Figueroa; Michael Timm; Dragan Jevremovic; Min Shi; A Keith Stewart; Esteban Braggio; Daniel L Riggs; P Leif Bergsagel; George Vasmatzis; Hutton M Kearney; Nicole L Hoppman; Rhett P Ketterling; Shaji Kumar; S Vincent Rajkumar; Patricia T Greipp; Linda B Baughn
Journal:  Blood Cancer J       Date:  2019-12-16       Impact factor: 11.037

3.  Prognostic value of integrated cytogenetic, somatic variation, and copy number variation analyses in Korean patients with newly diagnosed multiple myeloma.

Authors:  Nuri Lee; Sung-Min Kim; Youngeun Lee; Dajeong Jeong; Jiwon Yun; Sohee Ryu; Sung-Soo Yoon; Yong-Oon Ahn; Sang Mee Hwang; Dong Soon Lee
Journal:  PLoS One       Date:  2021-02-05       Impact factor: 3.240

4.  Artificial Intelligence in Plasma Cell Myeloma: Neural Networks and Support Vector Machines in the Classification of Plasma Cell Myeloma Data at Diagnosis.

Authors:  Ashwini K Yenamandra; Caitlin Hughes; Alexander S Maris
Journal:  J Pathol Inform       Date:  2021-09-16

5.  Genomic arrays identify high-risk chronic lymphocytic leukemia with genomic complexity: a multi-center study.

Authors:  Alexander C Leeksma; Panagiotis Baliakas; Theodoros Moysiadis; Anna Puiggros; Karla Plevova; Anne-Marie Van der Kevie-Kersemaekers; Hidde Posthuma; Ana E Rodriguez-Vicente; Anh Nhi Tran; Gisela Barbany; Larry Mansouri; Rebeqa Gunnarsson; Helen Parker; Eva Van den Berg; Mar Bellido; Zadie Davis; Meaghan Wall; Ilaria Scarpelli; Anders Österborg; Lotta Hansson; Marie Jarosova; Paolo Ghia; Pino Poddighe; Blanca Espinet; Sarka Pospisilova; Constantine Tam; Loïc Ysebaert; Florence Nguyen-Khac; David Oscier; Claudia Haferlach; Jacqueline Schoumans; Marian Stevens-Kroef; Eric Eldering; Kostas Stamatopoulos; Richard Rosenquist; Jonathan C Strefford; Clemens Mellink; Arnon P Kater
Journal:  Haematologica       Date:  2021-01-01       Impact factor: 9.941

  5 in total

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