Evidence map›Paper›PMID 20396564›Full record

ArticleCancer research and treatment2004

The differential gene expression profiles between sensitive and resistant breast cancer cells to adriamycin by cDNA microarray.

Myung-Ju Ahn, Ki-Hwan Lee, Joon-Ik Ahn, Dong-Hyun Yu, Hye-Sook Lee, Jung-Hye Choi, Joung Soon Jang, Jong Min Bae, Yong-Sung Lee

Open access · bronzeAbstract read
In one paragraph

Article in Cancer research and treatment, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.3field-weighted citation impact, top 39% 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

6 citing papers in PubMed, 14 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Myung-Ju AhnDepartment of Internal Medicine, College of Medicine, Hanyang University, Seoul, Korea. ahnmj@hanyang.ac.kr
Ki-Hwan Lee
Joon-Ik Ahn
Dong-Hyun Yu
Hye-Sook Lee
Jung-Hye Choi
Joung Soon Jang
Jong Min Bae
Yong-Sung Lee
Hanyang University · KRGyeongsang National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAdriamycin is one of the most commonly used drugs in the treatment of breast cancer. This study was performed to understand the molecular mechanisms of drug resistance in breast cancer cells. MATERIALS AND

methodsWe have analyzed the MCF-7 breast cell line and its adriamycin-resistant variants, MCF-7/ADR using human 10 K element cDNA microarrays.

resultsWe defined 68 genes that were up-regulated (14 genes) or down-regulated (54 genes) in adriamycin resistant breast cancer cells. Several genes, such as G protein-coupled receptor kinase 5, phospholipase A2, guanylate cyclase 1, vimentin, matrix metalloproteinase 1 are up-regulated in drug resistant cells. Several genes, such as interferon, alpha-inducible protein 27, forkhead box M1, mitogen-activated protein kinase 6, regulator of mitotic spindle assembly 1 and tumor necrosis factor superfamily are down-regulated in adriamycin resistant cells. The altered expression of genes observed in microarray was verified by RT-PCR.

conclusionThese findings show that cDNA microarray analysis can be used to obtain gene expression profiles reflecting the effect of anticancer drugs on breast cancer cells. Such data may lead to the assigning of signature expression profiles of drug-resistant tumors which may help predict responses to drugs and assist in the design of tailored therapeutic regimens to overcome drug resistance.

Indexed as

AdriamycinBreast cancer cellscDNA microarrayDrug resistance

Identifiers

PMID20396564
PMCPMC2855115
OpenAlexW2024930772

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.