The mutation pattern of breast cancer molecular subtypes is incompletely understood. The purpose of this study was to identify mutations in genes that may be targeted with currently available investigational drugs in the three major breast cancer subtypes (ER+/HER2-, HER2+, and Triple Negative). We extracted DNA from fine needle aspirations of 267 stage I-III breast cancers. These tumor specimens typically consisted of >80% neoplastic cells. We examined 28 genes for 163 known cancer-related nucleic acid variations by Sequenom technology. We observed at least one mutation in 38 alleles corresponding to 15 genes in 108 (40%) samples, including PIK3CA (16.1% of all samples), FBXW7 (8%), BRAF (3.0%), EGFR (2.6%), AKT1 and CTNNB1 (1.9% each), KIT and KRAS (1.5% each), and PDGFR-α (1.1%). We also checked for the polymorphism in PHLPP2 that is known to activate AKT and it was found at 13.5% of the patient samples. PIK3CA mutations were more frequent in estrogen receptor-positive cancers compared to triple negative breast cancer (TNBC) (19 vs. 8%, p=0.001). High frequency of PIK3CA mutations (28%) were also found in HER2+ breast tumors. In TNBC, FBXW7 mutations were significantly more frequent compared to ER+ tumors (13 vs. 5%, p=0.037). We performed validation for all mutated alleles with allele-specific PCR or direct sequencing; alleles analyzed by two different sequencing techniques showed 95-100% concordance for mutation status. In conclusion, different breast cancer subtypes harbor different type of mutations and approximately 40 % of tumors contained individually rare mutations in signaling pathways that can be potentially targeted with drugs. Simultaneous testing of many different mutations in a single needle biopsy is feasible and allows the design of prospective clinical trials that could test the functional importance of these mutations in the future.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3885980PMC
http://dx.doi.org/10.1007/s10549-012-2035-3DOI Listing

Publication Analysis

Top Keywords

breast cancer
16
breast cancers
8
mutations
8
cancer subtypes
8
triple negative
8
pik3ca mutations
8
mutations frequent
8
breast
7
mutation
5
mutation profiling
4

Similar Publications

Background: The online nature of decision aids (DAs) and related e-tools supporting women's decision-making regarding breast cancer screening (BCS) through mammography may facilitate broader access, making them a valuable addition to BCS programs.

Objective: This systematic review and meta-analysis aims to evaluate the scientific evidence on the impacts of these e-tools and to provide a comprehensive assessment of the factors associated with their increased utility and efficacy.

Methods: We followed the 2020 PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and conducted a search of MEDLINE, PsycINFO, Embase, CINAHL, and Web of Science databases from August 2010 to April 2023.

View Article and Find Full Text PDF

Mammography is one of the main methods available for breast cancer screening in Brazil. However, differences in timely access and performance of the exam can be highlighted based on social determinants of health, considered relevant due to their influence on the health situation of a population. Thus, the present study aimed to identify the social determinants of health associated with access to and performance of mammography in Brazilian women.

View Article and Find Full Text PDF

This article aims to identify the relationship between material deprivation and mortality from breast, cervical, and prostate neoplasms in the Brazilian adult population and the relationship between ethnicity/skin color and material deprivation. This cross-sectional ecological study calculated the mean mortality rate per 100,000 inhabitants, and deaths were standardized by age and gender and redistributed per to ill-defined causes, stratified by age group and ethnicity/skin color. We applied the Negative Binomial model, containing the interaction between ethnicity/skin color and the Brazilian Deprivation Index (IBP).

View Article and Find Full Text PDF

Pathway analysis plays a critical role in bioinformatics, enabling researchers to identify biological pathways associated with various conditions by analyzing gene expression data. However, the rise of large, multi-center datasets has highlighted limitations in traditional methods like Over-Representation Analysis (ORA) and Functional Class Scoring (FCS), which struggle with low signal-to-noise ratios (SNR) and large sample sizes. To tackle these challenges, we use a deep learning-based classification method, Gene PointNet, and a novel $P$-value computation approach leveraging the confusion matrix to address pathway analysis tasks.

View Article and Find Full Text PDF

BRCA1 deficiency is observed in approximately 25% of triple-negative breast cancer (TNBC). BRCA1, a key player of homologous recombination (HR) repair, is also involved in stalled DNA replication fork protection and repair. Here, we investigated the sensitivity of BRCA1-deficient TNBC models to the frequently used replication chain terminator gemcitabine, which does not directly induce DNA breaks.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!