Evidence map›Paper›PMID 29391886›Full record

ArticleOncology letters2018

Silencing of

Seiji Asai, Noriyoshi Miura, Yuichiro Sawada, Terutaka Noda, Tadahiko Kikugawa, Nozomu Tanji, Takashi Saika

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.2field-weighted citation impact, top 48% 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

5 citing papers in PubMed, 7 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

7 authors at 2 institutions in 1 country.

Seiji AsaiDepartment of Urology, Ehime University Graduate School of Medicine, Toon, Ehime 791-0295, Japan.
Noriyoshi MiuraDepartment of Urology, Ehime University Graduate School of Medicine, Toon, Ehime 791-0295, Japan.
Yuichiro SawadaDepartment of Urology, Ehime University Graduate School of Medicine, Toon, Ehime 791-0295, Japan.
Terutaka NodaDepartment of Urology, Ehime University Graduate School of Medicine, Toon, Ehime 791-0295, Japan.
Tadahiko KikugawaDepartment of Urology, Ehime University Graduate School of Medicine, Toon, Ehime 791-0295, Japan.
Nozomu TanjiDepartment of Urology, Houshasen-Daiichi Hospital, Imabari, Ehime 794-0054, Japan.
Takashi SaikaDepartment of Urology, Ehime University Graduate School of Medicine, Toon, Ehime 791-0295, Japan.
Ehime University · JPDaiyūkaidaiichi Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Combined gemcitabine and cisplatin (GC) treatment is a first line chemotherapy for bladder cancer. However, acquired resistance to GC has been a major problem. To address the mechanism of gemcitabine resistance, and to identify potential biomarkers or target proteins for its therapy, we aimed to identify candidate proteins associated with gemcitabine resistance using proteomic analysis. We established gemcitabine-resistant human bladder cancer cell lines (UMUC3GR and HT1376GR) from gemcitabine-sensitive human bladder cancer cell lines (UMUC3 and HT1376). We compared the protein expression of parental and gemcitabine-resistant cell lines using isobaric tags for relative and absolute quantification (iTRAQ) and liquid chromatography tandem mass spectrometry. Among the identified proteins, ethylmalonyl-CoA decarboxylase (ECHDC1) expression was significantly increased in both of the gemcitabine-resistant cell lines compared to the respective parental cell lines. Silencing of

Indexed as

bladder cancerECHDC1ethylmalonyl-CoA decarboxylasegemcitabine resistancemetabolite proofreading enzymeproteomic analysis

Identifiers

PMID29391886
PMCPMC5769416
OpenAlexW2766685431

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.