Evidence map›Paper›PMID 18416826›Full record

ArticleBMC cancer2008

Explorative data analysis of MCL reveals gene expression networks implicated in survival and prognosis supported by explorative CGH analysis.

Steffen Blenk, Julia C Engelmann, Stefan Pinkert, Markus Weniger, Jörg Schultz, Andreas Rosenwald, Hans K Müller-Hermelink, Tobias Müller, Thomas Dandekar

Abstract read
In one paragraph

Article in BMC cancer, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

26 citing papers in PubMed.

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  11. Veterinary sciences · 2022
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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

9 authors.

Steffen BlenkDepartment of Bioinformatics, University of Würzburg, Biozentrum, Am Hubland, D-97074 Würzburg, Germany. steffen.blenk@biozentrum.uni-wuerzburg.de
Julia C Engelmann
Stefan Pinkert
Markus Weniger
Jörg Schultz
Andreas Rosenwald
Hans K Müller-Hermelink
Tobias Müller
Thomas Dandekar

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMantle cell lymphoma (MCL) is an incurable B cell lymphoma and accounts for 6% of all non-Hodgkin's lymphomas. On the genetic level, MCL is characterized by the hallmark translocation t(11;14) that is present in most cases with few exceptions. Both gene expression and comparative genomic hybridization (CGH) data vary considerably between patients with implications for their prognosis.

methodsWe compare patients over and below the median of survival. Exploratory principal component analysis of gene expression data showed that the second principal component correlates well with patient survival. Explorative analysis of CGH data shows the same correlation.

resultsOn chromosome 7 and 9 specific genes and bands are delineated which improve prognosis prediction independent of the previously described proliferation signature. We identify a compact survival predictor of seven genes for MCL patients. After extensive re-annotation using GEPAT, we established protein networks correlating with prognosis. Well known genes (CDC2, CCND1) and further proliferation markers (WEE1, CDC25, aurora kinases, BUB1, PCNA, E2F1) form a tight interaction network, but also non-proliferative genes (SOCS1, TUBA1B CEBPB) are shown to be associated with prognosis. Furthermore we show that aggressive MCL implicates a gene network shift to higher expressed genes in late cell cycle states and refine the set of non-proliferative genes implicated with bad prognosis in MCL.

conclusionThe results from explorative data analysis of gene expression and CGH data are complementary to each other. Including further tests such as Wilcoxon rank test we point both to proliferative and non-proliferative gene networks implicated in inferior prognosis of MCL and identify suitable markers both in gene expression and CGH data.

Indexed as

CDC2 Protein KinaseChromosomes, Human, Pair 7Chromosomes, Human, Pair 9Cyclin BCyclin DCyclin-Dependent KinasesCyclinsGene ExpressionHumansLymphoma, B-CellLymphoma, Mantle-CellNucleic Acid HybridizationPrognosisCDC2 Protein KinaseCDK1 protein, humanCyclin BCyclin DCyclin-Dependent KinasesCyclins

Identifiers

PMID18416826
PMCPMC2442114

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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.