Literature DB >> 18698033

Biological processes associated with breast cancer clinical outcome depend on the molecular subtypes.

Christine Desmedt1, Benjamin Haibe-Kains, Pratyaksha Wirapati, Marc Buyse, Denis Larsimont, Gianluca Bontempi, Mauro Delorenzi, Martine Piccart, Christos Sotiriou.   

Abstract

PURPOSE: Recently, several prognostic gene expression signatures have been identified; however, their performance has never been evaluated according to the previously described molecular subtypes based on the estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2), and their biological meaning has remained unclear. Here we aimed to perform a comprehensive meta-analysis integrating both clinicopathologic and gene expression data, focusing on the main molecular subtypes. EXPERIMENTAL
DESIGN: We developed gene expression modules related to key biological processes in breast cancer such as tumor invasion, immune response, angiogenesis, apoptosis, proliferation, and ER and HER2 signaling, and then analyzed these modules together with clinical variables and several prognostic signatures on publicly available microarray studies (>2,100 patients).
RESULTS: Multivariate analysis showed that in the ER+/HER2- subgroup, only the proliferation module and the histologic grade were significantly associated with clinical outcome. In the ER-/HER2- subgroup, only the immune response module was associated with prognosis, whereas in the HER2+ tumors, the tumor invasion and immune response modules displayed significant association with survival. Proliferation was identified as the most important component of several prognostic signatures, and their performance was limited to the ER+/HER2- subgroup.
CONCLUSIONS: Although proliferation is the strongest parameter predicting clinical outcome in the ER+/HER2- subtype and the common denominator of most prognostic gene signatures, immune response and tumor invasion seem to be the main molecular processes associated with prognosis in the ER-/HER2- and HER2+ subgroups, respectively. These findings may help to define new clinicogenomic models and to identify new therapeutic strategies in the specific molecular subgroups.

Entities:  

Mesh:

Substances:

Year:  2008        PMID: 18698033     DOI: 10.1158/1078-0432.CCR-07-4756

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   12.531


  342 in total

Review 1.  Breast cancer assessment tools and optimizing adjuvant therapy.

Authors:  Catherine Oakman; Libero Santarpia; Angelo Di Leo
Journal:  Nat Rev Clin Oncol       Date:  2010-10-26       Impact factor: 66.675

2.  Modeling invasive breast cancer: growth factors propel progression of HER2-positive premalignant lesions.

Authors:  C-R Pradeep; A Zeisel; W J Köstler; M Lauriola; J Jacob-Hirsch; B Haibe-Kains; N Amariglio; N Ben-Chetrit; A Emde; I Solomonov; G Neufeld; M Piccart; I Sagi; C Sotiriou; G Rechavi; E Domany; C Desmedt; Y Yarden
Journal:  Oncogene       Date:  2011-12-05       Impact factor: 9.867

3.  A mammary stem cell population identified and characterized in late embryogenesis reveals similarities to human breast cancer.

Authors:  Benjamin T Spike; Dannielle D Engle; Jennifer C Lin; Samantha K Cheung; Justin La; Geoffrey M Wahl
Journal:  Cell Stem Cell       Date:  2012-02-03       Impact factor: 24.633

4.  PIK3CA mutations associated with gene signature of low mTORC1 signaling and better outcomes in estrogen receptor-positive breast cancer.

Authors:  Sherene Loi; Benjamin Haibe-Kains; Samira Majjaj; Francoise Lallemand; Virginie Durbecq; Denis Larsimont; Ana M Gonzalez-Angulo; Lajos Pusztai; W Fraser Symmans; Alberto Bardelli; Paul Ellis; Andrew N J Tutt; Cheryl E Gillett; Bryan T Hennessy; Gordon B Mills; Wayne A Phillips; Martine J Piccart; Terence P Speed; Grant A McArthur; Christos Sotiriou
Journal:  Proc Natl Acad Sci U S A       Date:  2010-05-17       Impact factor: 11.205

Review 5.  The secret ally: immunostimulation by anticancer drugs.

Authors:  Lorenzo Galluzzi; Laura Senovilla; Laurence Zitvogel; Guido Kroemer
Journal:  Nat Rev Drug Discov       Date:  2012-02-03       Impact factor: 84.694

6.  Cancer progression modeling using static sample data.

Authors:  Yijun Sun; Jin Yao; Norma J Nowak; Steve Goodison
Journal:  Genome Biol       Date:  2014-08-26       Impact factor: 13.583

Review 7.  Tumor metastasis: molecular insights and evolving paradigms.

Authors:  Scott Valastyan; Robert A Weinberg
Journal:  Cell       Date:  2011-10-14       Impact factor: 41.582

8.  Multigene Assays for Classification, Prognosis, and Prediction in Breast Cancer: a Critical Review on the Background and Clinical Utility.

Authors:  P Sinn; S Aulmann; R Wirtz; S Schott; F Marmé; Z Varga; A Lebeau; H Kreipe; A Schneeweiss
Journal:  Geburtshilfe Frauenheilkd       Date:  2013-09       Impact factor: 2.915

Review 9.  Clinical utility of gene-expression signatures in early stage breast cancer.

Authors:  Maryann Kwa; Andreas Makris; Francisco J Esteva
Journal:  Nat Rev Clin Oncol       Date:  2017-05-31       Impact factor: 66.675

10.  Basal/HER2 breast carcinomas: integrating molecular taxonomy with cancer stem cell dynamics to predict primary resistance to trastuzumab (Herceptin).

Authors:  Begoña Martin-Castillo; Cristina Oliveras-Ferraros; Alejandro Vazquez-Martin; Silvia Cufí; José Manuel Moreno; Bruna Corominas-Faja; Ander Urruticoechea; Ángel G Martín; Eugeni López-Bonet; Javier A Menendez
Journal:  Cell Cycle       Date:  2012-01-15       Impact factor: 4.534

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.