Evidence map›Paper›PMID 29513759›Full record

ArticlePloS one2018

Subtype assignment of CLL based on B-cell subset associated gene signatures from normal bone marrow - A proof of concept study.

Caroline Holm Nørgaard, Lasse Hjort Jakobsen, Andrew J Gentles, Karen Dybkær, Tarec Christoffer El-Galaly, Julie Støve Bødker, Alexander Schmitz, Preben Johansen, Tobias Herold, Karsten Spiekermann and 4 more

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.3field-weighted citation impact, top 20% 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

9 citing papers in PubMed, 14 citations in OpenAlex.

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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

14 authors at 4 institutions in 3 countries.

Caroline Holm NørgaardDepartment of Haematology, Aalborg University Hospital, Aalborg, Denmark.ORCID 0000-0003-3279-4872
Lasse Hjort JakobsenDepartment of Haematology, Aalborg University Hospital, Aalborg, Denmark.
Andrew J GentlesDepartments of Medicine and Biomedical Data Science, Stanford, California, United States of America.
Karen DybkærDepartment of Haematology, Aalborg University Hospital, Aalborg, Denmark.
Tarec Christoffer El-GalalyDepartment of Haematology, Aalborg University Hospital, Aalborg, Denmark.
Julie Støve BødkerDepartment of Haematology, Aalborg University Hospital, Aalborg, Denmark.
Alexander SchmitzDepartment of Haematology, Aalborg University Hospital, Aalborg, Denmark.
Preben JohansenDepartment of Pathology, Aalborg University Hospital, Aalborg, Denmark.
Tobias HeroldDepartment of Internal Medicine 3, University of Munich, Munich, Germany.
Karsten SpiekermannDepartment of Internal Medicine 3, University of Munich, Munich, Germany.
Jennifer R BrownDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States of America.
Josephine L KlitgaardDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States of America.
Hans Erik JohnsenDepartment of Haematology, Aalborg University Hospital, Aalborg, Denmark.
Martin BøgstedDepartment of Haematology, Aalborg University Hospital, Aalborg, Denmark.
Aalborg University Hospital · DKBrigham and Women's Hospital · USLudwig-Maximilians-Universität München · DEStanford Medicine · US

Funding

Translational Oncology Research Program (Project-005)P30CA124435 · NCI · STANFORD UNIVERSITY · PI Melinda L. Telli · 2007 to 2026
$71.4M
ProteomicsP01CA206978 · NCI · DANA-FARBER CANCER INST · PI CARR, STEVEN A · 2016 to 2025
$17.0M
Unlocking the Potential of PI3K Inhibition in CLLR01CA213442 · NCI · DANA-FARBER CANCER INST · PI BROWN, JENNIFER R · 2017 to 2021
$2.9M
NCI NIH HHS P01 CA206978NCI NIH HHS R01 CA213442
6 · The paper itself

Abstract

Diagnostic and prognostic evaluation of chronic lymphocytic leukemia (CLL) involves blood cell counts, immunophenotyping, IgVH mutation status, and cytogenetic analyses. We generated B-cell associated gene-signatures (BAGS) based on six naturally occurring B-cell subsets within normal bone marrow. Our hypothesis is that by segregating CLL according to BAGS, we can identify subtypes with prognostic implications in support of pathogenetic value of BAGS. Microarray-based gene-expression samples from eight independent CLL cohorts (1,024 untreated patients) were BAGS-stratified into pre-BI, pre-BII, immature, naïve, memory, or plasma cell subtypes; the majority falling within the memory (24.5-45.8%) or naïve (14.5-32.3%) categories. For a subset of CLL patients (n = 296), time to treatment (TTT) was shorter amongst early differentiation subtypes (pre-BI/pre-BII/immature) compared to late subtypes (memory/plasma cell, HR: 0.53 [0.35-0.78]). Particularly, pre-BII subtype patients had the shortest TTT among all subtypes. Correlates derived for BAGS subtype and IgVH mutation (n = 405) revealed an elevated mutation frequency in late vs. early subtypes (71% vs. 45%, P < .001). Predictions for BAGS subtype resistance towards rituximab and cyclophosphamide varied for rituximab, whereas all subtypes were sensitive to cyclophosphamide. This study supports our hypothesis that BAGS-subtyping may be of tangible prognostic and pathogenetic value for CLL patients.

Indexed as

AdultAgedAged, 80 and overAntineoplastic Agents, AlkylatingAntineoplastic Agents, ImmunologicalB-Lymphocyte SubsetsBone MarrowCyclophosphamideDrug Resistance, NeoplasmFemaleGene Expression Regulation, NeoplasticHumansLeukemia, Lymphocytic, Chronic, B-CellMaleMicroarray AnalysisMiddle AgedAntineoplastic Agents, AlkylatingAntineoplastic Agents, ImmunologicalCyclophosphamideRituximab

Identifiers

PMID29513759
PMCPMC5841735
OpenAlexW2794203670

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.