Literature DB >> 12234024

Predictive factors for response to chemotherapy in advanced breast cancer.

Johanna Sjöström1.   

Abstract

Most breast cancer patients receive chemotherapy at some phase of their illness but only about half of them benefit from it. Identifying the factors predicting response to chemotherapy would also assist the clinician in selection of appropriate patients for chemotherapy, thus saving others from unnecessary exposure to toxic agents. At the present time, there is no tumour biological factor available for clinical use in the prediction of chemotherapy response in advanced breast cancer apart from oestrogen receptor status, which predicts response to hormonal therapy, or the HER2 receptor, which predicts response to trastuzumab. Interestingly, they both are also targets for those therapies. Several groups have tried to find such predictive factors for chemotherapy in advanced breast cancer but the results are so far disappointing. This review collects the rapidly expanding data published so far on the predictive value of tumour biological factors for chemotherapy response in advanced breast cancer. In conclusion, none of them is yet good enough for clinical use in advanced breast cancer.

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Year:  2002        PMID: 12234024     DOI: 10.1080/028418602760169370

Source DB:  PubMed          Journal:  Acta Oncol        ISSN: 0284-186X            Impact factor:   4.089


  5 in total

1.  Prognostic value of proliferation markers expression in breast cancer.

Authors:  Natalija Dedić Plavetić; Jasminka Jakić-Razumović; Ana Kulić; Damir Vrbanec
Journal:  Med Oncol       Date:  2013-03-07       Impact factor: 3.064

2.  A population-based gene signature is predictive of breast cancer survival and chemoresponse.

Authors:  Shruti Rathnagiriswaran; Ying-Wooi Wan; Jame Abraham; Vincent Castranova; Yong Qian; Nancy L Guo
Journal:  Int J Oncol       Date:  2010-03       Impact factor: 5.650

3.  Cyclin A as a marker for prognosis and chemotherapy response in advanced breast cancer.

Authors:  P Poikonen; J Sjöström; R-M Amini; K Villman; J Ahlgren; C Blomqvist
Journal:  Br J Cancer       Date:  2005-09-05       Impact factor: 7.640

4.  A method for predicting target drug efficiency in cancer based on the analysis of signaling pathway activation.

Authors:  Artem Artemov; Alexander Aliper; Michael Korzinkin; Ksenia Lezhnina; Leslie Jellen; Nikolay Zhukov; Sergey Roumiantsev; Nurshat Gaifullin; Alex Zhavoronkov; Nicolas Borisov; Anton Buzdin
Journal:  Oncotarget       Date:  2015-10-06

5.  Gene signature-based prediction of triple-negative breast cancer patient response to Neoadjuvant chemotherapy.

Authors:  Yanding Zhao; Evelien Schaafsma; Chao Cheng
Journal:  Cancer Med       Date:  2020-07-21       Impact factor: 4.452

  5 in total

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