Comprehensive detection of recurring genomic abnormalities: a targeted sequencing approach for multiple myeloma
Year: 2019
Type: article
Abstract: Recent genomic research efforts in multiple myeloma have revealed clinically relevant molecular subgroups beyond conventional cytogenetic classifications. Implementing these advances in clinical trial design and in routine patient care requires a new generation of molecular diagnostic tools. Here, we present a custom capture next-generation sequencing (NGS) panel designed to identify rearrangements involving the IGH locus, arm level, and focal copy number aberrations, as well as frequently mutated genes in multiple myeloma in a single assay. We sequenced 154 patients with plasma cell disorders and performed a head-to-head comparison with the results from conventional clinical assays, i.e., fluorescent in situ hybridization (FISH) and single-nucleotide polymorphism (SNP) microarray. Our custom capture NGS panel had high sensitivity (>99%) and specificity (>99%) for detection of IGH translocations and relevant chromosomal gains and losses in multiple myeloma. In addition, the assay was able to capture novel genomic markers associated with poor outcome such as bi-allelic events involving TP53. In summary, we show that a multiple myeloma designed custom capture NGS panel can detect IGH translocations and CNAs with very high concordance in relation to FISH and SNP microarrays and importantly captures the most relevant and recurrent somatic mutations in multiple myeloma rendering this approach highly suitable for clinical application in the modern era.
Source: Blood Cancer Journal
Authors: Venkata Yellapantula, Malin Hultcrantz, Even H. Rustad, Ester Wasserman, Dory Londono, Robert Cimera, Amanda Ciardiello, Heather Landau, Theresia Akhlaghi, Sham Mailankody, Minal Patel, Juan Santiago Medina-Martinez, Juan Esteban Arango Ossa, Max Fine Levine, Niccolo Bolli, Francesco Maura, Ahmet Dogan, Elli Papaemmanuil, Yanming Zhang, Ola Landgren
Language: English
Subfield: Hematology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $4,380
OpenAlex ID: W2996700807
