Evidence map›Paper›PMID 20011461›Full record

ArticleCancer informatics2009

Discrimination of carcinogens by hepatic transcript profiling in rats following 28-day administration.

Hiroshi Matsumoto, Yoshikuni Yakabe, Koichi Saito, Kayo Sumida, Masaru Sekijima, Koji Nakayama, Hideki Miyaura, Fumiyo Saito, Masanori Otsuka, Tomoyuki Shirai

Open access · goldAbstract read
In one paragraph

Article in Cancer informatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 23% 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

4 citing papers in PubMed, 31 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. 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

10 authors at 3 institutions in 1 country.

Hiroshi MatsumotoChemical Assessment Center, Chemicals Evaluation and Research Institute, Japan (CERI), 1600, Shimo-Takano, Sugito-machi, Kitakatsushika-gun, Saitama 345-0043, Japan. matsumoto-hiroshi@ceri.jp
Yoshikuni Yakabe
Koichi Saito
Kayo Sumida
Masaru Sekijima
Koji Nakayama
Hideki Miyaura
Fumiyo Saito
Masanori Otsuka
Tomoyuki Shirai
Mitsubishi Chemical (Japan) · JPSumitomo Chemical (Japan) · JPMitsubishi Group (Japan) · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed at discriminating carcinogens on the basis of hepatic transcript profiling in the rats administrated with a variety of carcinogens and non-carcinogens. We conducted 28-day toxicity tests in male F344 rats with 47 carcinogens and 26 non-carcinogens, and then investigated periodically the hepatic gene expression profiles using custom microarrays. By hierarchical cluster analysis based on significantly altered genes, carcinogens were clustered into three major groups (Group 1 to 3). The formation of these groups was not affected by the gene sets used as well as the administration period, indicating that the grouping of carcinogens was universal independent of the conditions of both statistical analysis and toxicity testing. Seventeen carcinogens belonging to Group 1 were composed of mainly rat hepatocarcinogens, most of them being mutagenic ones. Group 2 was formed by three subgroups, which were composed of 23 carcinogens exhibiting distinct properties in terms of genotoxicity and target tissues, namely nonmutagenic hepatocarcinogens, and mutagenic and nonmutagenic carcinogens both of which are targeted to other tissues. Group 3 contained 6 carcinogens including 4 estrogenic substances, implying the group of estrogenic carcinogens. Gene network analyses revealed that the significantly altered genes in Group 1 included Bax, Tnfrsf6, Btg2, Mgmt and Abcb1b, suggesting that p53-mediated signaling pathway involved in early pathologic alterations associated with preceding mutagenic carcinogenesis. Thus, the common transcriptional signatures for each group might reflect the early molecular events of carcinogenesis and hence would enable us to identify the biomarker genes, and then to develop a new assay for carcinogenesis prediction.

Indexed as

carcinogenicitycluster analysishepatocarcinogenmicroarraymutagenicitytoxicogenomics

Identifiers

PMID20011461
PMCPMC2791490
OpenAlexW161841361

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.