Evidence map›Paper›PMID 30871527›Full record

ArticleBMC medical genomics2019

Clinical aspects of TP53 gene inactivation in diffuse large B-cell lymphoma.

Elena N Voropaeva, Tatyana I Pospelova, Mikhail I Voevoda, Vladimir N Maksimov, Yuriy L Orlov, Olga B Seregina

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2019. 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
3.1field-weighted citation impact, top 8% 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

26 citing papers in PubMed, 40 citations in OpenAlex.

  1. Article
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  5. Frontiers in oncology · 2025
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  11. BGRS: bioinformatics of genome regulation and data integration.Journal of integrative bioinformatics · 2023
    Article
  12. Review
  13. Article
  14. Article
  15. Role of RNA Splicing Mutations in Diffuse Large B Cell Lymphoma.International journal of general medicine · 2023
    Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

6 authors at 2 institutions in 1 country.

Elena N VoropaevaInstitute of Internal and Preventive Medicine, Branch of Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia. vena.81@mail.ru.
Tatyana I PospelovaNovosibirsk State Medical University, Novosibirsk, Russia.
Mikhail I VoevodaInstitute of Internal and Preventive Medicine, Branch of Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia.
Vladimir N MaksimovInstitute of Internal and Preventive Medicine, Branch of Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia.
Yuriy L OrlovInstitute of Internal and Preventive Medicine, Branch of Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia.
Olga B SereginaNovosibirsk State Medical University, Novosibirsk, Russia.
Institute of Cytology and Genetics · RUNovosibirsk State Medical University · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe knowledge about specific mechanisms generating TP53 dysfunction in diffuse large B-cell lymphoma is limited. The aim of the current study was to comprehensively explore TP53 gene variability resulting from somatic mutations, promoter methylation, and allelic imbalance in tumorous tissue of diffuse large B-cell lymphoma (DLBCL).

methodsDNA samples from 74 patients with DLBCL were used. Genomic DNA was isolated from paraffin blocks of lymph nodes or from extranodal biopsies of tumors by the phenol-chloroform extraction method with guanidine. Analysis of coding sequences of the TP53 gene was based on Sanger's direct sequencing method. The methylation status of the TP53 promoter was analyzed using by methylation-specific PCR on bisulfite-converted DNA. Assessment of the detected mutations was carried out in the IARC TP53 Database and the TP53 UMD mutation database of human cancer.

resultsThe mutations in regions coding for the DNA-binding domain were prevalent (95%). In the analyzed sample of patients, codons 275, 155, 272, and 212 were hotspots of mutations in the TP53 gene. In addition, functionally significant intron mutations (IVS6-36G > C and IVS5 + 43G > T) were detected. Instances of TP53 promoter methylation were observed only in a few samples of diffuse large B-cell lymphoma tissue. Furthermore, loss of heterozygosity was revealed only in the subgroup of patients with altered status of the gene (mutations were detected in five patients and promoter methylation in one case).

conclusionsThus, the results suggest that there are two sequential events in the formation of diffuse large B-cell lymphoma in at least some cases. The first event is mutation or methylation of the TP53 promoter, leading to appearance of a cell with increased risk of malignant transformation. The second event is the loss of an intact allele of the gene; this change is necessary for tumorigenesis. We identified TP53 mutation patterns in a Russian cohort of patients with de novo DLBCL who were treated with R-CHOP and R-CHOP-like regimens and confirmed that TP53 mutation status is a valuable prognostic biomarker.

Indexed as

AdultAgedAllelesAntineoplastic Combined Chemotherapy ProtocolsCyclophosphamideDNA MethylationDoxorubicinFemaleGene FrequencyHumansIntronsLoss of HeterozygosityLymphoma, Large B-Cell, DiffuseMaleMicrosatellite RepeatsMiddle AgedCyclophosphamideDoxorubicinPrednisoneR-CHOP protocolRituximabTumor Suppressor Protein p53VincristineAllelic imbalanceDiffuse large B-cell lymphomaIntron mutationsMethylationSequencingTP53 gene

Identifiers

PMID30871527
PMCPMC6416833
OpenAlexW2921755290

What OpenQuestion holds

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LicenceCC BY
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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.