Evidence map›Paper›PMID 23734685›Full record

ReviewFuture medicinal chemistry2013

Development of new estrogen receptor-targeting therapeutic agents for tamoxifen-resistant breast cancer.

Quan Jiang, Shilong Zheng, Guangdi Wang

Open access · greenAbstract readReview
In one paragraph

Review in Future medicinal chemistry, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
4.2field-weighted citation impact, top 6% 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

14 citing papers in PubMed, 47 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

3 authors at 1 institution in 1 country.

Quan JiangDepartment of Chemistry, Xavier University of Louisiana, New Orleans, LA 70125, USA.
Shilong Zheng
Guangdi Wang
Xavier University of Louisiana · US

Funding

Xavier's RCMI Cancer Research ProgramG12MD007595 · NIMHD · XAVIER UNIVERSITY OF LOUISIANA · PI D'AMOUR, GENE, WANG, GUANGDI · 2012 to 2018
$15.7M
XAVIER'S RCMI CANCER RESEARCH PROGRAMG12RR026260 · NCRR · XAVIER UNIVERSITY OF LOUISIANA · PI WIESE, THOMAS E · 2009 to 2011
$7.0M
NCRR NIH HHS G12 RR026260NIMHD NIH HHS 8G12MD007595NIMHD NIH HHS G12 MD007595
6 · The paper itself

Abstract

Despite our deepening understanding of the mechanisms of resistance and intensive efforts to develop therapeutic solutions to combat resistance, de novo and acquired tamoxifen resistance remains a clinical challenge, and few effective regimens exist to treat tamoxifen-resistant breast cancer. The complexity of tamoxifen resistance calls for diverse therapeutic approaches. This review presents several therapeutic strategies and lead compounds targeting the estrogen receptor signaling pathways for treatment of tamoxifen-resistant breast cancer, with a critical assessment of challenges and potentials regarding clinical outcome. Medicinal chemistry holds the key to effective, personalized combination therapy for tamoxifen-resistant breast cancer by making available a diverse arsenal of small-molecule drugs that specifically target signaling pathways modulating hormone resistance. These combination therapy candidates should have the desired specificity, selectivity and low toxicity to resensitize tumor response to tamoxifen and/or inhibit the growth and proliferation of resistant breast cancer cells.

Indexed as

Antineoplastic Agents, HormonalApoptosisAromataseAromatase InhibitorsBreast NeoplasmsDrug Resistance, NeoplasmEstrogen AntagonistsFemaleHumansReceptors, EstrogenTamoxifenAntineoplastic Agents, HormonalAromataseAromatase InhibitorsEstrogen AntagonistsReceptors, EstrogenTamoxifen

Identifiers

PMID23734685
PMCPMC3855007
OpenAlexW2061365526

What OpenQuestion holds

Textmetadata
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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.