Evidence map›Paper›PMID 32456143›Full record

ArticleCancers2020

Application of Next-Generation Sequencing for the Genomic Characterization of Patients with Smoldering Myeloma.

Martina Manzoni, Valentina Marchica, Paola Storti, Bachisio Ziccheddu, Gabriella Sammarelli, Giannalisa Todaro, Francesca Pelizzoni, Simone Salerio, Laura Notarfranchi, Alessandra Pompa and 5 more

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.9field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Review
  7. Review
  8. Review
  9. Review
  10. Article
  11. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 5 institutions in 1 country.

Martina ManzoniDepartment of Oncology and Hemato-oncology, University of Milan, 20122 Milan, Italy.ORCID 0000-0003-0861-9951
Valentina MarchicaDepartment of Medicine and Surgery, University of Parma, 43126 Parma, Italy.
Paola StortiDepartment of Medicine and Surgery, University of Parma, 43126 Parma, Italy.ORCID 0000-0001-8014-8205
Bachisio ZicchedduDepartment of Clinical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy.
Gabriella SammarelliHematology, "Azienda Ospedaliero-Universitaria di Parma", 43126 Parma, Italy.
Giannalisa TodaroHematology, "Azienda Ospedaliero-Universitaria di Parma", 43126 Parma, Italy.
Francesca PelizzoniHematology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy.
Simone SalerioHematology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy.
Laura NotarfranchiDepartment of Medicine and Surgery, University of Parma, 43126 Parma, Italy.
Alessandra PompaHematology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy.
Luca BaldiniDepartment of Oncology and Hemato-oncology, University of Milan, 20122 Milan, Italy.
Niccolò BolliDepartment of Oncology and Hemato-oncology, University of Milan, 20122 Milan, Italy.ORCID 0000-0002-1018-5139
Antonino NeriDepartment of Oncology and Hemato-oncology, University of Milan, 20122 Milan, Italy.
Nicola GiulianiDepartment of Medicine and Surgery, University of Parma, 43126 Parma, Italy.ORCID 0000-0003-3457-3774
Marta LionettiDepartment of Oncology and Hemato-oncology, University of Milan, 20122 Milan, Italy.ORCID 0000-0002-3342-9095
University of Milan · ITUniversity of Parma · ITFondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico · ITOspedale di Parma · ITFondazione IRCCS Istituto Nazionale dei Tumori · IT

Funding

Associazione Italiana per la Ricerca sul Cancro 16722 to A.N.; 20299 to N.G.Fondazione Italiana per la Ricerca sul Cancro 22389 to M.M.H2020 European Research Council 817997 to N.B.Ministero della Salute Ricerca Corrente Funds 2019 to A.N.; grant PE-2016-02361261 to N.G.Ministero dell'Istruzione, dell'Università e della Ricerca to A.N.
6 · The paper itself

Abstract

Genomic analysis could contribute to a better understanding of the biological determinants of the evolution of multiple myeloma (MM) precursor disease and an improved definition of high-risk patients. To assess the feasibility and value of next-generation sequencing approaches in an asymptomatic setting, we performed a targeted gene mutation analysis and a genome-wide assessment of copy number alterations (CNAs) by ultra-low-pass whole genome sequencing (ULP-WGS) in six patients with monoclonal gammopathy of undetermined significance and 25 patients with smoldering MM (SMM). Our comprehensive genomic characterization highlighted heterogeneous but substantial values of the tumor fraction, especially in SMM; a rather high degree of genomic complexity, in terms of both mutations and CNAs, and inter-patient variability; a higher incidence of gene mutations and CNAs in SMM, confirming ongoing evolution; intraclonal heterogeneity; and instances of convergent evolution. ULP-WGS of these patients proved effective in revealing the marked genome-wide level of their CNAs, most of which are not routinely investigated. Finally, the analysis of our small SMM cohort suggested that chr(8p) deletions, the DNA tumor fraction, and the number of alterations may have clinical relevance in the progression to overt MM. Although validation in larger series is mandatory, these findings highlight the promising impact of genomic approaches in the clinical management of SMM.

Indexed as

multiple myelomanext-generation sequencingpremalignant stages

Identifiers

PMID32456143
PMCPMC7281620
OpenAlexW3026978650

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.