Literature DB >> 16199162

Predicting response to systemic treatments: learning from the past to plan for the future.

Meredith M Regan1, Richard D Gelber.   

Abstract

Therapeutic effects of adjuvant therapies for breast cancer have been assessed "across the board" and implemented using the principle that if a treatment is effective "on average" then it is effective "for all patients." Exploration and improved understanding of the biological basis for predicting response to available adjuvant therapies is essential to enhance patient care. As illustration, we consider the effects of chemotherapy and tamoxifen in two International Breast Cancer Study Group (IBCSG) trials for postmenopausal women. The level of estrogen receptor (ER) expression in the primary tumor is a powerful predictor of response to adjuvant therapy. Absence of ER identifies a chemosensitive cohort for which concurrent tamoxifen significantly blunts the large chemotherapy effect. High levels of ER expression are associated with good results using tamoxifen alone; adding chemotherapy provides little additional benefit. By contrast, adding chemotherapy to tamoxifen provides additional benefit for patients with node-positive disease and tumors expressing intermediate levels of ER. Identification of chemosensitive targets, e.g., absence of PgR, in tumors with intermediate ER expression is required to further tailor, adding chemotherapy within this otherwise endocrine-responsive cohort. Age is not a therapeutic target. Thus, the biological bases for treatment responsiveness must be defined. All findings from clinical trials and meta-analyses should be presented primarily according to steroid hormone receptor status and future studies should be designed as tailored treatment investigations.

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Year:  2005        PMID: 16199162     DOI: 10.1016/j.breast.2005.08.021

Source DB:  PubMed          Journal:  Breast        ISSN: 0960-9776            Impact factor:   4.380


  6 in total

1.  Using clinical trial data to tailor adjuvant treatments for individual patients.

Authors:  Meredith M Regan; Richard D Gelber
Journal:  Breast       Date:  2007-08-23       Impact factor: 4.380

2.  Evaluation of treatment-effect heterogeneity using biomarkers measured on a continuous scale: subpopulation treatment effect pattern plot.

Authors:  Ann A Lazar; Bernard F Cole; Marco Bonetti; Richard D Gelber
Journal:  J Clin Oncol       Date:  2010-09-13       Impact factor: 44.544

3.  Is adjuvant chemotherapy of benefit for postmenopausal women who receive endocrine treatment for highly endocrine-responsive, node-positive breast cancer? International Breast Cancer Study Group Trials VII and 12-93.

Authors:  Olivia Pagani; Shari Gelber; Edda Simoncini; Monica Castiglione-Gertsch; Karen N Price; Richard D Gelber; Stig B Holmberg; Diana Crivellari; John Collins; Jurij Lindtner; Beat Thürlimann; Martin F Fey; Elizabeth Murray; John F Forbes; Alan S Coates; Aron Goldhirsch
Journal:  Breast Cancer Res Treat       Date:  2008-10-25       Impact factor: 4.872

4.  ERα propelled aberrant global DNA hypermethylation by activating the DNMT1 gene to enhance anticancer drug resistance in human breast cancer cells.

Authors:  Xinxin Si; Yue Liu; Jinghuan Lv; Haijian Ding; Xin A Zhang; Lipei Shao; Nan Yang; He Cheng; Luan Sun; Dongliang Zhu; Yin Yang; Andi Li; Xiao Han; Yujie Sun
Journal:  Oncotarget       Date:  2016-04-12

5.  Adjuvant breast cancer chemotherapy during late-trimester pregnancy: not quite a standard of care.

Authors:  Richard J Epstein
Journal:  BMC Cancer       Date:  2007-05-30       Impact factor: 4.430

6.  Interaction of WBP2 with ERα increases doxorubicin resistance of breast cancer cells by modulating MDR1 transcription.

Authors:  Shuai Chen; Han Wang; Zhi Li; Jun You; Qiu-Wan Wu; Can Zhao; Chi-Meng Tzeng; Zhi-Ming Zhang
Journal:  Br J Cancer       Date:  2018-05-01       Impact factor: 7.640

  6 in total

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