Search

MicroRNAs (miRNAs) are an emerging class of gene expression modulators with relevant roles in several biological processes, including cell differentiation, development, apoptosis, and regulation of the cell cycle. Deregulation of those tiny RNA molecules has been described frequently as a major determinant for the initiation and progression of diseases, including cancer. Not only miRNAs but also the enzymes responsible for miRNA processing could be deregulated in cancer. In this review, we address the role of miRNAs in the pathogenesis of breast cancer, since there are oncogenic, tumor-suppressive, and metastatic-influencing miRNAs. Additionally, the different detection platforms and normalization strategies for miRNAs will be discussed. The major part of this review, however, will focus on the capability of miRNAs to act as diagnostic, predictive, or prognostic biomarkers. We will give an overview of their potential to correlate with response to or benefit from a given treatment and we will consider their ability to give information on prognosis in breast cancer. We will focus on miRNAs validated by more than one study or verified in independent cohorts or where results rely on preclinical as well as clinical evidence. As such, we will discuss their potential use in the personalized management of breast cancer. Electronic supplementary material The online version of this article (doi:10.1186/s13058-015-0526-y) contains supplementary material, which is available to authorized users.

Introduction: MicroRNAs (miRNAs) are a group of small noncoding RNAs involved in the regulation of gene expression. As such, they regulate a large number of cellular pathways, and deregulation or altered expression of miRNAs is associated with tumorigenesis. In the current study, we evaluated the feasibility and clinical utility of circulating miRNAs as biomarkers for the detection and staging of breast cancer. Methods: miRNAs were extracted from a set of 84 tissue samples from patients with breast cancer and eight normal tissue samples obtained after breast-reductive surgery. After reverse transcription and preamplification, 768 miRNAs were profiled by using the TaqMan low-density arrays. After data normalization, unsupervised hierarchical cluster analysis (UHCA) was used to investigate global differences in miRNA expression between cancerous and normal samples. With fold-change analysis, the most discriminating miRNAs between both tissue types were selected, and their expression was analyzed on serum samples from 20 healthy volunteers and 75 patients with breast cancer, including 16 patients with untreated metastatic breast cancer. miRNAs were extracted from 200 mu l of serum, reverse transcribed, and analyzed in duplicate by using polymerase chain reaction (qRT-PCR). Results: UHCA showed major differences in miRNA expression between tissue samples from patients with breast cancer and tissue samples from breast-reductive surgery (P < 0.0001). Generally, miRNA expression in cancerous samples tends to be repressed when compared with miRNA expression in healthy controls (P = 0.0685). The four most discriminating miRNAs by fold-change (miR-215, miR-299-5p, miR-411, and miR-452) were selected for further analysis on serum samples. All miRNAs at least tended to be differentially expressed between serum samples from patients with cancer and serum samples from healthy controls (miR-215, P = 0.094; miR-299-5P, P = 0.019; miR-411, P = 0.002; and miR-452, P = 0.092). For all these miRNAs, except for miR-452, the greatest difference in expression was observed between serum samples from healthy volunteers and serum samples from untreated patients with metastatic breast cancer. Conclusions: Our study provides a basis for the establishment of miRNAs as biomarkers for the detection and eventually staging of breast cancer through blood-borne testing. We identified and tested a set of putative biomarkers of breast cancer and demonstrated that altered levels of these miRNAs in serum from patients with breast cancer are particularly associated with the presence of metastatic disease.

Background: The epidermal growth factor receptor belongs to the ErbB family of cell-surface receptors. Hotspot mutations within this gene occur in 27% of lung cancers and patients carrying mutation(s) likely receive more benefit from EGFR targeted therapy. We have evaluated the feasibility of multiplex PCR targeting known mutational hotspots in EGFR exon 18 till 21, followed by 454 pyrosequencing to determine the EGFR mutational status in patients with lung cancer. Methods: FFPE samples from 10 lung cancer patients were collected. Four samples were mutant and six carried the wild-type (WT) genotype. A multiplex PCR was performed in which primers had a gene specific sequence, a patient specific ‘bar code’ (MID) and Roche sequencing tags. The unique multiplex identifiers (MIDs) allow appropriate mixing of patient samples and differentiation in the sequence data. Amplicon generation was verified by fragment analysis (GeneScan). Amplicons were purified using AMPure XP beads, quantified by Quant-iT PicoGreen, pooled in equimolar ratios and diluted before emulsion PCR. Sequencing was carried out in 2 runs using Titanium Amplicon chemistry (Lib-A) on a 454 GS Junior. Two samples were analyzed in duplicate to assess reproducibility. Data were analyzed using the amplicon variant analyzer software. Results: A throughput of 52.159 and 28.769 high quality reads was achieved for the library in the performed runs. Considering the EGFR amplicons, a mean coverage of 837 reads (range 589 - 1350) was obtained. Four variants were detected by sequencing and were 100% concordant with results obtained using a StripAssay in an ISO-certified setting. The variants and frequencies detected were G719X (21,7%), p.L747-S752del (21,46%), p.H773_V774insNPH (11,14%) and p.L861Q (24,11%). In the WT samples no EGFR mutations were detected, suggesting a 100% specificity on the obtained 454 data. Additionally, variant analysis showed 2 different SNPs in exon 20 and 21 (rs1050171 and rs17290559, respectively). These are classified as the synonymous mutations Q787Q and R836R and do not have any clinical significance. The SNPs in exon 20 and 21 were detected in 67% and 17% of the WT samples, respectively. Inter-run reproducibility was established from comparison of 2 WT samples in different sequence runs. Intra-assay reproducibility was demonstrated via analysis of EGFR mutant samples in duplicate. Conclusions: Our study provides a basis for the implementation of next generation sequencing for the detection of somatic mutations in EGFR in a routine clinical setting. The used multiplex PCR and subsequent 454 sequencing allowed the detection of significant activating or resistance associated EGFR mutations in FFPE material from patients with lung cancer. We obtained 100% concordance with previously obtained results from an accredited laboratory. Citation Format: Eleni van Schooneveld, Bram De Laere, Roberto Salgado, Peter Vermeulen, Hans Wildiers, Ignace Vergote, Luc Dirix, Steven Van Laere. Determination of the EGFR mutational status on FFPE material from patients with lung cancer using Multiplex PCR followed by sequencing on a compatible 454 sequencing platform. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4145. doi:10.1158/1538-7445.AM2013-4145

Proceedings: AACR 103rd Annual Meeting 2012‐‐ Mar 31‐Apr 4, 2012; Chicago, IL Background: Patients with estrogen receptor (ER)-positive breast cancers are generally treated with endocrine therapy, but in a considerable fraction of patients resistance occurs. Previous research showed that nuclear factor kappa B (NFkB) may play a role in the development of resistance to hormonal therapy. In this study, we investigated the role of NFkB, and its interaction with ER in the development of endocrine resistance by studying breast cancer cell lines with variable ER and NFkB activity. Material and methods: Three gene expression data sets of breast cancer cell lines ([GSE12777][1]: Hoeflich et al, 2009; [GSE16795][2]: Hollestelle et al, 2009; E-TAM-157: Neve et al, 2005) were retrieved from Gene Expression Omnibus or ArrayExpress. The expression profiles were screened for ER and NFkB target genes to identify cell lines with strong and weak activation of ER and NFkB. Based on these activation profiles, 8 cell lines (MCF7, BT20, CAMA1, MDA-MB-361, MDA-MB-231, MDA-MB-134, MDA-MB-468 and MDA-MB-436) with high and low ER and NFkB activation profiles were selected. Using qRT-PCR on RNA from these cell lines, the expression of 6 biomarkers for endocrine resistance (ADAMDEC1, ITK, ABAT, CLEC7A, ETS1 and STC2) were profiled. 18S and beta-Actin were used as housekeeping genes. Relative expression levels were analyzed in function of ER and NFkB activation. Results: There is a significant lower expression of ADAMDEC1 (P=0.011), ITK (P=0.012) and ETS1 (P