Evidence map›Paper›PMID 21253797›Full record

ReviewRecent results in cancer research. Fortschritte der Krebsforschung. Progres dans les recherches sur le cancer2011

Chemoprevention of hormone receptor-negative breast cancer: new approaches needed.

Iván P Uray, Powel H Brown

Open access · greenAbstract readReview
In one paragraph

Review in Recent results in cancer research. Fortschritte der Krebsforschung. Progres dans les recherches sur le cancer, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
24.3field-weighted citation impact, top 1% 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

28 citing papers in PubMed, 68 citations in OpenAlex.

  1. Article
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  9. Vitamin D and Breast Cancer: Latest Evidence and Future Steps.Breast cancer : basic and clinical research · 2017
    Review
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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

2 authors at 1 institution in 1 country.

Iván P UrayDepartment of Clinical Cancer Prevention, The University of Texas M. D. Anderson Cancer Center, Houston, TX 77230, USA.
Powel H Brown
The University of Texas MD Anderson Cancer Center · US

Funding

PREVENTION OF BREAST CANCER USING SELECTIVE RETINOIDSR01CA078480 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI BROWN, POWEL H · 1999 to 2008
$3.1M
Prevention of Estrogen Receptor-negative Breast CancerR01CA101211 · NCI · BAYLOR COLLEGE OF MEDICINE · PI BROWN, POWEL H · 2003 to 2007
$2.4M
NCI NIH HHS R01 CA078480NCI NIH HHS R01 CA101211
6 · The paper itself

Abstract

Results from clinical trials have demonstrated that it is possible to prevent estrogen-responsive breast cancers by targeting the estrogen receptor with selective estrogen receptor modulators (SERMs) (tamoxifen, raloxifene, or lasofoxifene) or with aromatase inhibitors (AIs) (anastrozole, letrozole, or exemestene). Results from breast cancer treatment trials suggest that aromatase inhibitors may be even more effective in preventing breast cancer than SERMs. However, while SERMs and aromatase inhibitors do prevent the development of many ER-positive breast cancers, these drugs do not prevent ER-negative breast cancer. These results show that new approaches are needed for the prevention of this aggressive form of breast cancer. Our laboratory and clinical efforts have been focused on identifying critical molecular pathways in breast cells that can be targeted for the prevention of ER-negative breast cancer. Our preclinical studies have demonstrated that other nuclear receptors, such as RXR receptors, vitamin D receptors, as well as others are critical for the growth of ER-negative breast cells and for the transformation of these cells into ER-negative cancers. Other studies show that growth factor pathways including those activated by EGFR, Her2, and IGFR, which are activated in many ER-negative breast cancers, can be targeted for the prevention of ER-negative breast cancer in mice. Clinical studies have also shown that PARP inhibitors are effective for the treatment of breast cancers arising in BRCA-1 or -2 mutation carriers, suggesting that targeting PARP may also be useful for the prevention of breast cancers arising in these high-risk individuals. Most recently, we have demonstrated that ER-negative breast cancers can be subdivided into four distinct groups based on the kinases that they express. These groups include ER-negative/Her-2-positive groups (the MAPK and immunomodulatory groups) and ER-negative/Her2-negative groups (the S6K and the cell cycle checkpoint groups). These groups of ER-negative breast cancers can be targeted with kinase inhibitors specific for each subgroup. These preclinical studies have supported the development of several clinical trials testing targeted agents for the prevention of breast cancer. The results of a completed Phase II cancer prevention trial using the RXR ligand bexarotene in women at high risk of breast cancer will be reviewed, and the current status of an ongoing Phase II trial using the EGFR and Her2 kinase inhibitor lapatinib for the treatment of women with DCIS breast cancer will be presented. It is anticipated that in the future these molecularly targeted drugs will be combined with hormonal agents such as SERMs or aromatase inhibitors to prevent all forms of breast cancer.

Indexed as

Aromatase InhibitorsBreast NeoplasmsFemaleHumansHydroxymethylglutaryl-CoA Reductase InhibitorsMetforminPoly(ADP-ribose) Polymerase InhibitorsReceptors, EstrogenRetinoidsSelective Estrogen Receptor ModulatorsAromatase InhibitorsHydroxymethylglutaryl-CoA Reductase InhibitorsMetforminPoly(ADP-ribose) Polymerase InhibitorsReceptors, EstrogenRetinoidsSelective Estrogen Receptor Modulators

Identifiers

PMID21253797
PMCPMC3415693
OpenAlexW1521078998

What OpenQuestion holds

Textmetadata
LicenceTDM
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.