Literature DB >> 16002001

Genomics-based prognosis and therapeutic prediction in breast cancer.

Stefanie S Jeffrey1, Per Eystein Lønning, Bruce E Hillner.   

Abstract

Breast cancer is a heterogeneous disease. DNA microarray technology is being applied to breast cancer to identify new prognostic biomarkers, to predict response to therapy, and to discover targets for the development of novel therapies. New diagnostic assays based on global gene expression are being introduced into clinical practice or tested in large-scale clinical trials. This review focuses on translational studies using microarray analyses and discusses best practice features and pitfalls. We note that factors that predict metastatic disease are not necessarily the same factors that predict therapeutic response. We believe that the characterization and discernment of different systems among breast cancers is crucial for understanding drug sensitivity and resistance mechanisms and for guiding therapy.

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Year:  2005        PMID: 16002001     DOI: 10.6004/jnccn.2005.0016

Source DB:  PubMed          Journal:  J Natl Compr Canc Netw        ISSN: 1540-1405            Impact factor:   11.908


  19 in total

1.  A hybrid BPSO-CGA approach for gene selection and classification of microarray data.

Authors:  Li-Yeh Chuang; Cheng-Huei Yang; Jung-Chike Li; Cheng-Hong Yang
Journal:  J Comput Biol       Date:  2011-01-06       Impact factor: 1.479

2.  Transcriptional profiling and genotyping of degraded nucleic acids from autopsy tissue samples after prolonged formalin fixation times.

Authors:  Antonio Ferruelo; Mariam El-Assar; José A Lorente; Nicolás Nin; Oscar Peñuelas; Pilar Fernández-Segoviano; Constancio Gonzalez; Andrés Esteban
Journal:  Int J Clin Exp Pathol       Date:  2011-01-06

3.  Berberine reverses lapatinib resistance of HER2-positive breast cancer cells by increasing the level of ROS.

Authors:  Ruohan Zhang; Hongyu Qiao; Suning Chen; Xu Chen; Kefeng Dou; Li Wei; Jian Zhang
Journal:  Cancer Biol Ther       Date:  2016-07-14       Impact factor: 4.742

Review 4.  Molecular screening for breast cancer prevention, early detection, and treatment planning: combining biomarkers from DNA, RNA, and protein.

Authors:  Katherine Stemke-Hale; Bryan Hennessy; Gordon B Mills; Rahul Mitra
Journal:  Curr Oncol Rep       Date:  2006-11       Impact factor: 5.075

Review 5.  pH-sensitive membrane peptides (pHLIPs) as a novel class of delivery agents.

Authors:  Oleg A Andreev; Donald M Engelman; Yana K Reshetnyak
Journal:  Mol Membr Biol       Date:  2010-10-13       Impact factor: 2.857

6.  Tuning a polar molecule for selective cytoplasmic delivery by a pH (Low) insertion peptide.

Authors:  Dayanjali Wijesinghe; Donald M Engelman; Oleg A Andreev; Yana K Reshetnyak
Journal:  Biochemistry       Date:  2011-11-04       Impact factor: 3.162

7.  A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes.

Authors:  Richard M Neve; Koei Chin; Jane Fridlyand; Jennifer Yeh; Frederick L Baehner; Tea Fevr; Laura Clark; Nora Bayani; Jean-Philippe Coppe; Frances Tong; Terry Speed; Paul T Spellman; Sandy DeVries; Anna Lapuk; Nick J Wang; Wen-Lin Kuo; Jackie L Stilwell; Daniel Pinkel; Donna G Albertson; Frederic M Waldman; Frank McCormick; Robert B Dickson; Michael D Johnson; Marc Lippman; Stephen Ethier; Adi Gazdar; Joe W Gray
Journal:  Cancer Cell       Date:  2006-12       Impact factor: 31.743

Review 8.  Pathways to tamoxifen resistance.

Authors:  Rebecca B Riggins; Randy S Schrecengost; Michael S Guerrero; Amy H Bouton
Journal:  Cancer Lett       Date:  2007-05-01       Impact factor: 8.679

9.  Accurate analysis of tumor margins using a fluorescent pH Low Insertion Peptide (pHLIP).

Authors:  James Segala; Donald M Engelman; Yana K Reshetnyak; Oleg A Andreev
Journal:  Int J Mol Sci       Date:  2009-08-04       Impact factor: 5.923

10.  Genomic analysis of head and neck squamous cell carcinoma cell lines and human tumors: a rational approach to preclinical model selection.

Authors:  Hua Li; John S Wawrose; William E Gooding; Levi A Garraway; Vivian Wai Yan Lui; Noah D Peyser; Jennifer R Grandis
Journal:  Mol Cancer Res       Date:  2014-01-14       Impact factor: 5.852

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