UZH-Logo

Maintenance Infos

Functional viability profiles of breast cancer


Abstract

The design of targeted therapeutic strategies for cancer has been driven by the identification of tumor specific genetic changes. However, the large number of genetic alterations present in tumor cells means that it is difficult to discriminate between genes that are critical for maintenance of the disease state from those that are merely coincidental. Even when critical genes can be identified, directly targeting these is often challenging, meaning that alternative strategies such as exploiting synthetic lethality may be beneficial. To address these issues, we have carried out a functional genetic screen in over 30 commonly used models of breast cancer to identify genes that are critical for the growth of specific breast cancer subtypes. In particular, we describe potential new therapeutic targets for PTEN mutated cancers and for ER+ve breast cancers. We also show that large-scale functional profiling allows the classification of breast cancers into subgroups distinct from established subtypes.

Abstract

The design of targeted therapeutic strategies for cancer has been driven by the identification of tumor specific genetic changes. However, the large number of genetic alterations present in tumor cells means that it is difficult to discriminate between genes that are critical for maintenance of the disease state from those that are merely coincidental. Even when critical genes can be identified, directly targeting these is often challenging, meaning that alternative strategies such as exploiting synthetic lethality may be beneficial. To address these issues, we have carried out a functional genetic screen in over 30 commonly used models of breast cancer to identify genes that are critical for the growth of specific breast cancer subtypes. In particular, we describe potential new therapeutic targets for PTEN mutated cancers and for ER+ve breast cancers. We also show that large-scale functional profiling allows the classification of breast cancers into subgroups distinct from established subtypes.

Citations

78 citations in Web of Science®
81 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

3 downloads since deposited on 16 Feb 2012
0 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Gynecology
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:2011
Deposited On:16 Feb 2012 15:50
Last Modified:05 Apr 2016 15:37
Publisher:American Association for Cancer Research
ISSN:2159-8274 (P) 2159-8290 (E)
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1158/2159-8290.CD-11-0107
PubMed ID:21984977

Download

[img]
Content: Published Version
Filetype: PDF - Registered users only
Size: 4MB
View at publisher

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.

Author Collaborations