Evidence map›Paper›PMID 25632304›Full record

ArticleGenome medicine2015

Higher gene expression variability in the more aggressive subtype of chronic lymphocytic leukemia.

Simone Ecker, Vera Pancaldi, Daniel Rico, Alfonso Valencia

Open access · goldAbstract read
In one paragraph

Article in Genome medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
4.0field-weighted citation impact, top 6% 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

31 citing papers in PubMed, 78 citations in OpenAlex.

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  5. Contributions of transcriptional noise to leukaemia evolution: KAT2A as a case-study.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
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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

4 authors at 2 institutions in 1 country.

Simone EckerStructural Biology and Biocomputing Programme, Spanish National Cancer Research Center (CNIO), 28029 Madrid, Spain.
Vera PancaldiStructural Biology and Biocomputing Programme, Spanish National Cancer Research Center (CNIO), 28029 Madrid, Spain.
Daniel RicoStructural Biology and Biocomputing Programme, Spanish National Cancer Research Center (CNIO), 28029 Madrid, Spain.
Alfonso ValenciaStructural Biology and Biocomputing Programme, Spanish National Cancer Research Center (CNIO), 28029 Madrid, Spain.
Spanish National Cancer Research Centre · ESCentro de Investigación del Cáncer · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChronic lymphocytic leukemia (CLL) presents two subtypes which have drastically different clinical outcomes, IgVH mutated (M-CLL) and IgVH unmutated (U-CLL). So far, these two subtypes are not associated to clear differences in gene expression profiles. Interestingly, recent results have highlighted important roles for heterogeneity, both at the genetic and at the epigenetic level in CLL progression.

methodsWe analyzed gene expression data of two large cohorts of CLL patients and quantified expression variability across individuals to investigate differences between the two subtypes using different measures and statistical tests. Functional significance was explored by pathway enrichment and network analyses. Furthermore, we implemented a random forest approach based on expression variability to classify patients into disease subtypes.

resultsWe found that U-CLL, the more aggressive type of the disease, shows significantly increased variability of gene expression across patients and that, overall, genes that show higher variability in the aggressive subtype are related to cell cycle, development and inter-cellular communication. These functions indicate a potential relation between gene expression variability and the faster progression of this CLL subtype. Finally, a classifier based on gene expression variability was able to correctly predict the disease subtype of CLL patients.

conclusionsThere are strong relations between gene expression variability and disease subtype linking significantly increased expression variability to phenotypes such as aggressiveness and resistance to therapy in CLL.

Identifiers

PMID25632304
PMCPMC4308895
OpenAlexW2074299722

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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.