Literature DB >> 19836373

The effect of genetic variability on drug response in conventional breast cancer treatment.

Emilia Wiechec1, Lise Lotte Hansen.   

Abstract

The conventional breast cancer diagnosis based mainly upon histopathology, hormone and HER-2 receptor status, will in the future be combined with information on genomic and epigenetic profiles of the individual patient. This will lead to an optimal personalized therapy, directed towards specific genomic aberrations, avoiding unnecessary toxicity, side effects and chemotherapeutic drugs for which the patient evolves resistance. Breast cancer is a very heterogeneous malignancy, expressing a considerable variation in genomic aberrations from deletions and amplifications comprising entire chromosomes to minor regions. A wide spectrum of differently expressed genes and mutations has been identified, adding information to the highly complex picture of the tumor genome. The vast majority of breast cancer incidents is of somatic origin and may be caused by a combination of the individual genetic profile and environmental exposure. A major contributor to the variation in genetic profile is the single nucleotide polymorphisms (SNPs), which are highly abundant throughout the genome, and both current and future methodologies have the potential to screen millions of SNP genotypes in one analysis. Identification of specific SNP genotypes affecting transcriptional activity and thereby the outcome for the patient, of genes involved in DNA repair, metabolizing of chemotherapeutic drugs and drug target genes will determine the outcome for the patient. This will be an essential part of the development of personalized treatment of cancer. In this review the focus is on clinically relevant SNPs in genes implicated in drug metabolism and disposition as well as their influence on breast cancer therapy toxicity and/or efficacy.

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Year:  2009        PMID: 19836373     DOI: 10.1016/j.ejphar.2009.08.045

Source DB:  PubMed          Journal:  Eur J Pharmacol        ISSN: 0014-2999            Impact factor:   4.432


  10 in total

1.  Interferon gamma +874 T/A polymorphism increases the risk of cervical cancer: evidence from a meta-analysis.

Authors:  Yifan Sun; Yu Lu; Qiliu Pen; Taijie Li; Li Xie; Yan Deng; Aiping Qin
Journal:  Tumour Biol       Date:  2015-02-04

2.  The diplotype Fas -1377A/-670G as a genetic marker to predict a lower risk of breast cancer in Chinese women.

Authors:  Yeqiong Xu; Qiwen Deng; Bangshun He; Yuqin Pan; Rui Li; Tianyi Gao; Huiling Sun; Guoqi Song; Shukui Wang; William C Cho
Journal:  Tumour Biol       Date:  2014-06-12

3.  Interferon Gamma +874T/A Polymorphism Increases the Risk of Hepatitis Virus-Related Diseases: Evidence from a Meta-Analysis.

Authors:  Yifan Sun; Yu Lu; Taijie Li; Li Xie; Yan Deng; Shan Li; Xue Qin
Journal:  PLoS One       Date:  2015-05-04       Impact factor: 3.240

4.  One-step colorimetric genotyping of single nucleotide polymorphism using probe-enhanced loop-mediated isothermal amplification (PE-LAMP).

Authors:  Sheng Ding; Rong Chen; Gangyi Chen; Mei Li; Jiayu Wang; Jiawei Zou; Feng Du; Juan Dong; Xin Cui; Xin Huang; Yun Deng; Zhuo Tang
Journal:  Theranostics       Date:  2019-05-31       Impact factor: 11.556

5.  Functional polymorphisms of FAS and FASL gene and risk of breast cancer - pilot study of 134 cases.

Authors:  Mohammad Hashemi; Aliakbar Fazaeli; Saeid Ghavami; Ebrahim Eskandari-Nasab; Farshid Arbabi; Mohammad Ali Mashhadi; Mohsen Taheri; Wiem Chaabane; Mayur V Jain; Marek J Łos
Journal:  PLoS One       Date:  2013-01-11       Impact factor: 3.240

6.  A novel multiplex tetra-primer ARMS-PCR for the simultaneous genotyping of six single nucleotide polymorphisms associated with female cancers.

Authors:  Chen Zhang; Ying Liu; Brian Z Ring; Kai Nie; Mengjie Yang; Miao Wang; Hongwei Shen; Xiyang Wu; Xuejun Ma
Journal:  PLoS One       Date:  2013-04-17       Impact factor: 3.240

7.  Common variants in genes coding for chemotherapy metabolizing enzymes, transporters, and targets: a case-control study of contralateral breast cancer risk in the WECARE Study.

Authors:  Jennifer D Brooks; Sharon N Teraoka; Leslie Bernstein; Lene Mellemkjær; Kathleen E Malone; Charles F Lynch; Robert W Haile; Patrick Concannon; Anne S Reiner; David J Duggan; Katherine Schiermeyer; Jonine L Bernstein; Jane C Figueiredo
Journal:  Cancer Causes Control       Date:  2013-06-18       Impact factor: 2.506

8.  Predicting chemotherapeutic drug combinations through gene network profiling.

Authors:  Thi Thuy Trang Nguyen; Jacqueline Kia Kee Chua; Kwi Shan Seah; Seok Hwee Koo; Jie Yin Yee; Eugene Guorong Yang; Kim Kiat Lim; Shermaine Yu Wen Pang; Audrey Yuen; Louxin Zhang; Wee Han Ang; Brian Dymock; Edmund Jon Deoon Lee; Ee Sin Chen
Journal:  Sci Rep       Date:  2016-01-21       Impact factor: 4.379

9.  Genetic polymorphisms and response to 5-fluorouracil, doxorubicin and cyclophosphamide chemotherapy in breast cancer patients.

Authors:  Karolina Tecza; Jolanta Pamula-Pilat; Joanna Lanuszewska; Ewa Grzybowska
Journal:  Oncotarget       Date:  2016-10-11

10.  Effects of FGFR gene polymorphisms on response and toxicity of cyclophosphamide-epirubicin-docetaxel-based chemotherapy in breast cancer patients.

Authors:  Lu Chen; Huijie Qi; Liudi Zhang; Haixia Li; Jie Shao; Haifei Chen; Mingkang Zhong; Xiaojin Shi; Ting Ye; Qunyi Li
Journal:  BMC Cancer       Date:  2018-10-25       Impact factor: 4.430

  10 in total

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