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Genomic profile predicts the efficacy of neoadjuvant chemotherapy for cervical cancer patients

Overview of attention for article published in BMC Cancer, October 2015
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Title
Genomic profile predicts the efficacy of neoadjuvant chemotherapy for cervical cancer patients
Published in
BMC Cancer, October 2015
DOI 10.1186/s12885-015-1703-1
Pubmed ID
Authors

Naoki Horikawa, Tsukasa Baba, Noriomi Matsumura, Ryusuke Murakami, Kaoru Abiko, Junzo Hamanishi, Ken Yamaguchi, Masafumi Koshiyama, Yumiko Yoshioka, Ikuo Konishi

Abstract

Neoadjuvant chemotherapy (NAC) using platinum and irinotecan (CPT-11) followed by radical excision has been shown to be a valid treatment for locally advanced squamous cervical cancer (SCC) patients. However, in NAC-resistant or NAC-toxic cases, surgical treatment or radiotherapy might be delayed and the prognosis may be adversely affected. Therefore, it is important to establish a method to predict the efficacy of NAC. Gene expression microarrays of SCC tissue samples (n = 12) and UGT1A1 genotyping of blood samples (n = 23) were investigated in terms of their association with NAC sensitivity. Gene expression and drug sensitivity of SCC cell lines were analyzed for validation. Microarray analysis revealed that the glutathione metabolic pathway (GMP) was significantly up-regulated in NAC-resistant patients (p < 0.01), and there was a positive correlation between 50 % growth inhibitory concentrations of CPT-11 and predictive scores of GMP activation in SCC cells (r = 0.32, p < 0.05). The intracellular glutathione (GSH) concentration showed a highly positive correlation with GMP scores among 4 SCC cell lines (r = 0.72). UGT1A1 genotyping revealed that patients with UGT1A1 polymorphisms exhibited significantly higher response rates to NAC than those with the wild-type (79.5 vs. 49.5 %, respectively, p < 0.05). These results indicate that GMP scores of cancerous tissue combined with UGT1A1 genotyping of blood samples may serve as highly potent markers for predicting the efficacy of NAC for individual SCC patients.

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Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Other 5 19%
Student > Ph. D. Student 5 19%
Student > Bachelor 4 15%
Student > Doctoral Student 2 7%
Professor 2 7%
Other 5 19%
Unknown 4 15%
Readers by discipline Count As %
Medicine and Dentistry 10 37%
Pharmacology, Toxicology and Pharmaceutical Science 3 11%
Biochemistry, Genetics and Molecular Biology 2 7%
Immunology and Microbiology 2 7%
Arts and Humanities 1 4%
Other 3 11%
Unknown 6 22%