Evidence map›Paper›PMID 39001512›Full record

ArticleCancers2024

Utility of Targeted Sequencing Compared to FISH for Detection of Chronic Lymphocytic Leukemia Copy Number Alterations.

J Erin Wiedmeier-Nutor, Chantal E McCabe, Daniel R O'Brien, Erik Jessen, Cecilia Bonolo de Campos, Nicholas J Boddicker, Rosalie Griffin, Cristine Allmer, Kari G Rabe, James R Cerhan and 6 more

Abstract read
In one paragraph

Article in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. 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

16 authors.

J Erin Wiedmeier-NutorDivision of Hematology and Oncology, Department of Medicine, Mayo Clinic, Phoenix, AZ 85054, USA.ORCID 0000-0001-9434-5269
Chantal E McCabeDivision of Computational Biology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA.ORCID 0000-0003-2786-5496
Daniel R O'BrienDivision of Computational Biology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA.
Erik JessenDivision of Computational Biology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA.ORCID 0000-0001-9851-6897
Cecilia Bonolo de CamposDivision of Hematology and Oncology, Department of Medicine, Mayo Clinic, Phoenix, AZ 85054, USA.
Nicholas J BoddickerDivision of Computational Biology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA.
Rosalie GriffinDivision of Computational Biology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA.
Cristine AllmerDivision of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA.
Kari G RabeDivision of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA.ORCID 0000-0002-7313-1875
James R CerhanDivision of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA.ORCID 0000-0002-7482-178X
Sameer A ParikhDivision of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA.
Neil E KayDivision of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA.ORCID 0000-0002-5951-5055
Huihuang YanDivision of Computational Biology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA.
Daniel L Van DykeDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA.
Susan L SlagerDivision of Computational Biology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA.
Esteban BraggioDivision of Hematology and Oncology, Department of Medicine, Mayo Clinic, Phoenix, AZ 85054, USA.

Funding

Genetics of Common Cancers: Discovery to ImplementationK00CA234943 · NCI · MAYO CLINIC ROCHESTER · PI GRIFFIN, ROSALIE · 2020 to 2023
$391k
NCI NIH HHS K00 CA234943
6 · The paper itself

Abstract

Chronic lymphocytic leukemia (CLL) is characterized by multiple copy number alterations (CNAs) and somatic mutations that are central to disease prognosis, risk stratification, and mechanisms of therapy resistance. Fluorescence in situ hybridization (FISH) panels are widely used in clinical applications as the gold standard for screening prognostic chromosomal abnormalities in CLL. DNA sequencing is an alternative approach to identifying CNAs but is not an established method for clinical CNA screening. We sequenced DNA from 509 individuals with CLL or monoclonal B-cell lymphocytosis (MBL), the precursor to CLL, using a targeted sequencing panel of 59 recurrently mutated genes in CLL and additional amplicons across regions affected by clinically relevant CNAs [i.e., del(17p), del(11q), del(13q), and trisomy 12]. We used the PatternCNV algorithm to call CNA and compared the concordance of calling clinically relevant CNAs by targeted sequencing to that of FISH. We found a high accuracy of calling CNAs via sequencing compared to FISH. With FISH as the gold standard, the specificity of targeted sequencing was >95%, sensitivity was >86%, positive predictive value was >90%, and negative predictive value was >84% across the clinically relevant CNAs. Using targeted sequencing, we were also able to identify other common CLL-associated CNAs, including del(6q), del(14q), and gain 8q, as well as complex karyotype, defined as the presence of 3 or more chromosomal abnormalities, in 26 patients. In a single and cost-effective assay that can be performed on stored DNA samples, targeted sequencing can simultaneously detect CNAs, somatic mutations, and complex karyotypes, which are all important prognostic features in CLL.

Indexed as

CLLFISHNGS

Identifiers

PMID39001512
PMCPMC11240685

What OpenQuestion holds

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Registered trials

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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.