Literature DB >> 21278437

Breast cancer management: opportunities and barriers to an individualized approach.

Edith A Perez1.   

Abstract

A personalized approach to breast cancer management is increasingly possible with state of the art diagnostics and treatments. However, many challenges still exist in choosing the right therapeutic strategy and the right dosing for a specific patient population. Biomarkers such as estrogen receptor, progesterone receptor, and HER-2 status are used to tailor therapy, but success rates with targeted therapy suggest that appropriate patient populations still require greater definition. The introduction of the genomic era has likewise advanced the ability to offer a tailored approach to breast cancer management, but much work is still needed in this area as well. Microarray-based gene expression profiles have demonstrated initial promise, but we need a better understanding of more complex tumor signaling pathways. Strategies include annotated tumor specimens, next-generation gene sequencing, proteomics, and metabolomics. An individualized approach to breast cancer management has the potential to offer clear clinical benefits and the ability to bring more tailored, cost-effective strategies to the market. The current issues facing the delivery of individualized breast cancer care will be the focus of this discussion.

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Year:  2011        PMID: 21278437     DOI: 10.1634/theoncologist.2011-S1-20

Source DB:  PubMed          Journal:  Oncologist        ISSN: 1083-7159


  22 in total

Review 1.  Insight into the heterogeneity of breast cancer through next-generation sequencing.

Authors:  Hege G Russnes; Nicholas Navin; James Hicks; Anne-Lise Borresen-Dale
Journal:  J Clin Invest       Date:  2011-10-03       Impact factor: 14.808

2.  Heterogeneity in breast cancer.

Authors:  Kornelia Polyak
Journal:  J Clin Invest       Date:  2011-10-03       Impact factor: 14.808

Review 3.  Epigenetics advancing personalized nanomedicine in cancer therapy.

Authors:  Shujun Liu
Journal:  Adv Drug Deliv Rev       Date:  2012-08-19       Impact factor: 15.470

Review 4.  Oncolytic viruses: emerging options for the treatment of breast cancer.

Authors:  Yogesh R Suryawanshi; Tiantian Zhang; Karim Essani
Journal:  Med Oncol       Date:  2017-02-09       Impact factor: 3.738

5.  NT5E CpG island methylation is a favourable breast cancer biomarker.

Authors:  C Lo Nigro; M Monteverde; S Lee; L Lattanzio; D Vivenza; A Comino; N Syed; A McHugh; H Wang; C Proby; O Garrone; M Merlano; E Hatzimichael; E Briasoulis; O Gojis; C Palmieri; L Jordan; P Quinlan; A Thompson; T Crook
Journal:  Br J Cancer       Date:  2012-05-31       Impact factor: 7.640

6.  Combining functional genomics strategies identifies modular heterogeneity of breast cancer intrinsic subtypes.

Authors:  Nima Pouladi; Richard Cowper-Sallari; Jason H Moore
Journal:  BioData Min       Date:  2014-12-29       Impact factor: 2.522

7.  Circulating tumor cells in HER2-positive metastatic breast cancer patients: a valuable prognostic and predictive biomarker.

Authors:  Yi Liu; Qian Liu; Tao Wang; Li Bian; Shaohua Zhang; Haixu Hu; Sha Li; Zhiyuan Hu; Shikai Wu; Bing Liu; Zefei Jiang
Journal:  BMC Cancer       Date:  2013-04-23       Impact factor: 4.430

8.  Androgen receptor expression and its relationship with clinicopathological parameters in an Iranian population with invasive breast carcinoma.

Authors:  Fereshteh Mohammadizadeh; Sahar Sajadieh; Hamidreza Sajjadieh; Zahra Kasaei
Journal:  Adv Biomed Res       Date:  2014-05-28

9.  Effect of Imaging Parameter Thresholds on MRI Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer Subtypes.

Authors:  Wei-Ching Lo; Wen Li; Ella F Jones; David C Newitt; John Kornak; Lisa J Wilmes; Laura J Esserman; Nola M Hylton
Journal:  PLoS One       Date:  2016-02-17       Impact factor: 3.240

10.  DNA Methylation Patterns Can Estimate Nonequivalent Outcomes of Breast Cancer with the Same Receptor Subtypes.

Authors:  Min Zhang; Shaojun Zhang; Yanhua Wen; Yihan Wang; Yanjun Wei; Hongbo Liu; Dongwei Zhang; Jianzhong Su; Fang Wang; Yan Zhang
Journal:  PLoS One       Date:  2015-11-09       Impact factor: 3.240

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