Literature DB >> 27282497

Molecular evaluation of PIK3CA gene mutation in breast cancer: determination of frequency, distribution pattern and its association with clinicopathological findings in Indian patients.

Firoz Ahmad1, Anuya Badwe1, Geeta Verma2, Simi Bhatia2, Bibhu Ranjan Das3.   

Abstract

Somatic mutations in the PIK3CA gene are common in breast cancer and represent a clinically useful marker for prognosis and therapeutic target. Activating mutations in the PI3K p110 catalytic subunit (PIK3CA) have been identified in 18-40 % of breast carcinomas. In this study, we evaluated PIK3CA mutation in 185 Indian breast cancer patients by direct DNA sequencing. PIK3CA mutations were observed in 23.2 % (43/185) of breast tumor samples. PIK3CA mutations were more frequent exon 30 (76.8 %) than in exon 9 (23.2 %). Mutations were mostly clustered within two hotspot region between nucleotides 1624 and 1636 or between 3129 and 3140. Sequencing analysis revealed four different missense mutations at codon 542 and 545 (E542K, E545K, E545A and E545G) in the helical domain and two different amino acid substitutions at codon 1047 (H1047R and H1047L) in the kinase domain. None of the cases harbored concomitant mutations at multiple codons. PIK3CA mutations were more frequent in older patients, smaller size tumors, ductal carcinomas, grade II tumors, lymph node-positive tumors and non-DCIS tumors; however, none of the differences were significant. In addition, PIK3CA mutations were common in ER+, PR+ and HER2+ cases (30 %), and a comparatively low frequency were noted in triple-negative tumors (13.6 %). In conclusion, to our knowledge, this is the largest study to evaluate the PIK3CA mutation in Indian breast cancer patients. The frequency and distribution pattern of PIK3CA mutations is similar to global reports. Furthermore, identification of molecular markers has unique strengths and can provide insights into the pathogenic process of breast carcinomas.

Entities:  

Keywords:  Breast cancer; India; PIK3CA mutation; Sequencing analysis

Mesh:

Substances:

Year:  2016        PMID: 27282497     DOI: 10.1007/s12032-016-0788-y

Source DB:  PubMed          Journal:  Med Oncol        ISSN: 1357-0560            Impact factor:   3.064


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