Evidence map›Paper›PMID 20070305›Full record

ReviewCancer science2010

Diversity of genome profiles in malignant lymphoma.

Masao Seto, Keiichiro Honma, Masao Nakagawa

Open access · bronzeAbstract readReview
In one paragraph

Review in Cancer science, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

11 citing papers in PubMed, 56 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Review
  5. Review
  6. Multi-Omics Model Applied to Cancer Genetics.International journal of molecular sciences · 2021
    Review
  7. A sulfated polyphenols-rich extract fromSaudi journal of biological sciences · 2021
    Article
  8. Article
  9. Environmental factors inducing human cancers.Iranian journal of public health · 2012
    Article
  10. Article
  11. Genomic profiles in B cell lymphoma.International journal of hematology · 2010
    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

3 authors at 1 institution in 1 country.

Masao SetoDivision of Molecular Medicine, Aichi Cancer Center Research Institute, Nagoya, Japan. mseto@aichi-cc.jp
Keiichiro Honma
Masao Nakagawa
Aichi Cancer Center · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Characteristic chromosome translocations are associated with specific disease entities, and are known to play a pivotal role in lymphoma development. Chromosome translocation alone, however, is not sufficient to produce tumors. Factors including the microenvironment and epigenetic and genetic alterations other than chromosome translocations have been shown to play a role in lymphoma development. Follicular lymphoma cells proliferate in close contact with follicular dendritic cells. Mucosa-associated lymphoid tissue (MALT) lymphoma cells proliferate at the marginal zone area of reactive follicles which are formed by preceding chronic inflammation. The importance of genetic alterations other than chromosome translocation has been recognized since the introduction of array comparative genomic hybridization (array CGH). Variations in the genomic profile among patients with the same disease entity have been found by array CGH analyses. These variations indicate that multiple genetic pathways leading to the development of lymphomas may exist and hence result in the variable clinicopathological features observed.

Indexed as

AnimalsGenes, bcl-2Genetic VariationHumansImmunoglobulin Heavy ChainsLymphomaTranslocation, GeneticImmunoglobulin Heavy Chains

Identifiers

PMID20070305
PMCPMC11159680
OpenAlexW2091840799

What OpenQuestion holds

Textmetadata
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.