Evidence map›Paper›PMID 17854999›Full record

ReviewCancer treatment reviews2007

Use of comparative proteomics to identify potential resistance mechanisms in cancer treatment.

Jian-Ting Zhang, Yang Liu

Abstract readReview
In one paragraph

Review in Cancer treatment reviews, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
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

17 citing papers in PubMed.

  1. Review
  2. Article
  3. 14-3-3σ and Its Modulators in Cancer.Pharmaceuticals (Basel, Switzerland) · 2020
    Review
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  5. Article
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  7. Article
  8. Review
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  13. Article
  14. Article
  15. Article
  16. Review
  17. 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

2 authors.

Jian-Ting ZhangDepartment of Pharmacology and Toxicology, Walther Oncology Center/Walther Cancer Institute and IU Cancer Center, Indiana University School of Medicine, 1044 W. Walnut Street, R4-166, IN 46202, United States. jianzhan@iupui.edu
Yang Liu

Funding

Role of p170 in lung tumorigenesisR01CA094961 · NCI · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI ZHANG, JIAN-TING · 2003 to 2007
$1.5M
Targeting the oligomerization of human ABCG2R01CA120221 · NCI · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI ZHANG, JIAN-TING · 2006 to 2009
$842k
NCI NIH HHS R01 CA094961NCI NIH HHS R01 CA120221NCI NIH HHS R01 CA94961
6 · The paper itself

Abstract

Drug resistance is a major problem in successful cancer chemotherapy. Many molecular mechanisms that are responsible for drug resistance are known whereas others have yet to be discovered. Determining the exact mechanism activated in a particular case (clinical or laboratory) is a difficult task. Recently, proteomics has been applied to investigate drug resistance mechanisms in model cancer cell lines. As a result, novel mechanisms of resistance have been discovered and known mechanisms of resistance confirmed. In this paper, we wish to review recent developments and progresses in the application of proteomic tools to identify known and novel drug resistance mechanisms in drug-selected model cancer cell lines. Our combined analyses of multiple proteomic studies of various drug resistant cancer cell lines revealed that many mechanisms of resistance likely exist in any given drug-selected cancer cell line and that common mechanisms of resistance may be selected in a spectrum of cancer cell lines. These observations suggest that combination therapies targeting multiple mechanisms to sensitize drug resistant cancers may be necessary to eradicate cancers in the future.

Indexed as

AnimalsDrug Resistance, NeoplasmHumansNeoplasmsProteomics

Identifiers

PMID17854999
PMCPMC2203306

What OpenQuestion holds

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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.