BACKGROUND Ovarian cancer is the leading cause of death among malignancies in women. Despite advances in treatment, >50% of patients relapse. For disease monitoring, the identification of a blood-based biomarker would be of prime interest. In this regard, noncoding RNAs, such as microRNA (miRNA) or small nuclear RNA (snRNA), have been suggested as biomarkers for noninvasive cancer diagnosis. In the present study, we sought to identify differentially expressed miRNA/snRNA in sera of ovarian cancer patients and investigate their potential to aid in therapy monitoring. METHODS miRNA/snRNA abundance was investigated in serum (n = 10) by microarray analysis and validated in an extended serum set (n = 119) by reverse-transcription quantitative PCR. RESULTS Abundance of U2-1 snRNA fragment (RNU2-1f) was significantly increased in sera of ovarian cancer patients (P < 0.0001) and paralleled International Federation of Gynecology and Obstetrics stage as well as residual tumor burden after surgery (P < 0.0001 and P = 0.011, respectively). Moreover, for patients with suboptimal debulking, preoperative RNU2-1f concentration was associated with radiographic response after chemotherapy and with platinum resistance (P = 0.0088 and P = 0.0015, respectively). Interestingly, according to the RNU2-1f abundance dynamics, persistent RNU2-1f positivity before surgery and after chemotherapy identified a subgroup of patients with high risk of recurrence and poor prognosis. CONCLUSIONS This is the first report to suggest that a circulating snRNA can serve as an auxiliary diagnostic tool for monitoring tumor dynamics in ovarian cancer. Our results provide a rationale to further investigate whether this high-risk patient group may benefit from additional therapies that are directly applied after chemotherapy.

BackgroundCirculating tumor cells (CTC) are discussed to be an ideal surrogate marker for individualized treatment in metastatic breast cancer (MBC) since metastatic tissue is often difficult to obtain for repeated analysis. We established a nine gene qPCR panel to characterize the heterogeneous CTC population in MBC patients including epithelial CTC, their receptors (EPCAM, ERBB2, ERBB3, EGFR) CTC in Epithelial-Mesenchymal-Transition [(EMT); PIK3CA, AKT2), stem cell-like CTC (ALDH1) as well as resistant CTC (ERCC1, AURKA] to identify individual therapeutic targets.ResultsAt TP0, at least one marker was detected in 84%, at TP1 in 74% and at TP2 in 79% of the patients, respectively. The expression of ERBB2, ERBB3 and ERCC1 alone or in combination with AURKA was significantly associated with therapy failure. ERBB2 + CTC were only detected in patients not receiving ERBB2 targeted therapies which correlated with no response. Furthermore, patients responding at TP2 had a significantly prolonged overall-survival than patients never responding (p = 0.0090).Patients and Methods2 × 5 ml blood of 62 MBC patients was collected at the time of disease progression (TP0) and at two clinical staging time points (TP1 and TP2) after 8–12 weeks of chemo-, hormone or antibody therapy for the detection of CTC (AdnaTest EMT-2/StemCell Select™, QIAGEN Hannover GmbH, Germany). After pre-amplification, multiplex qPCR was performed. Establishment was performed using various cancer cell lines. PTPRC (Protein tyrosine phosphatase receptor type C) and GAPDH served as controls.ConclusionsMonitoring MBC patients using a multimarker qPCR panel for the characterization of CTC might help to treat patients accordingly in the future.

could be a key marker in distinguishing R from NR, and was powerful in identifying CTCs.

The aim of the present study was to compare the phosphatidylinositol 3-kinase (PI3KCA)-AKT serine/threonine kinase (AKT) pathway in circulating tumor cells (CTCs) and corresponding cancerous tissues. Stemness-like circulating tumor cells (slCTCs) and CTCs in epithelial-mesenchymal transition (EMT) have been implicated as the active source of metastatic spread in breast cancer (BC). In this regard, the PI3KCA-AKT signaling pathway was demonstrated to be implicated in and to be frequently mutated in BC. The present study compared this pathway in slCTCs/CTCs in EMT and the corresponding tumor tissues of 90 metastatic BC patients (pts). slCTCs and CTCs in EMT were isolated using the AdnaTest EMT-1/StemCell for the detection of aldehyde dehydrogenase 1 family member A1 (ALDH1) (singleplex PCR) and PI3KCA, AKT2 and twist family bHLH transcription factor 1 (multiplex PCR). Tumor tissue was investigated for PI3KCA hotspot mutations using Sanger sequencing of genomic DNA from micro-dissected formalin-fixed paraffin-embedded tissue, and for the expression of ALDH1 and phosphorylated AKT (pAKT), and phosphatase and tensin homolog (PTEN) loss, by immunohistochemistry. slCTCs were identified in 23% of pts (21/90 pts) and CTCs in EMT in 56% (50/90 pts) of pts. pAKT and ALDH1 positivity in tumor tissue was identified in 47 and 9% of cases, respectively, and a PTEN loss was observed in 18% of pts. A significant association was detected between pAKT expression in cancerous tissue and AKT2 expression in CTCs (P=0.037). PI3KCA mutations were detected in 32% of pts, most frequently on exons 21 (55%) and 10 (45%). Pts with PI3KCA mutations in tumor tissue had a significantly longer overall survival than pts with wild-type PI3KCA expression (P=0.007). Similar results were obtained for pts with aberrant PI3KCA signaling in CTCs and/or aberrant signaling in cancerous tissue (P=0.009). Therapy-resistant CTCs, potentially derived from the primary tumor or metastatic tissue, may be eliminated with specific PI3K pathway inhibitors, alone or in combination, to improve the prognosis of metastatic BC pts.

Background: Improved treatment strategies for metastatic breast cancer (MBC) patients are urgently needed. Since metastatic tissue may be difficult to obtain for repeated analysis, circulating tumor cells (CTC) would be an ideal surrogate tissue to identify prognostic and predictive factors that will help to select the optimal therapeutic strategy for each individual patient. Assuming that the population of CTC contains epithelial-like, EMT (Epithelial-Mesenchymal-Transition)-like and stem cell-like cells, we established a multi-marker qPCR for the characterization of these cells.Materials and Methods: Establishment of a 16 gene qPCR panel was performed using various epithelial cancer cell lines for the markers: EpCAM, MUC1 (epithelial); PI3K, PTEN, TWIST, mTOR, KRAS, AKT2 (EMT); ALDH1, CD44, CD24L4 (stem cell); ER, PR, HER2 and EGFR (receptors) and CD45 as a leucocyte control. The prostate cancer cell line LNCAP, expressing most of these genes, was used for spiking experiments. 10 ml blood of eight healthy donors (HDs), five HDs spiked with 10 LNCAP cells and 25 MBC patients were selected for CTC using AdnaTest BreastCancerSelect (AdnaGen AG) resulting in cDNA1. Subsequently, the same sample (with removed target cells) was processed again using the same procedure resulting in cDNA2. cDNA1 and cDNA2 were gene specifically preamplified using TaqMan PreAmp Master Mix according to in house designed assays. qPCR was performed using Bio-Rad SYBR Green Mix. If the CD45 deltaCt was > zero, deltaCt value of a given gene was calculated as the difference between Ct (cDNA2) and Ct(cDNA1). A gene with a deltaCt > zero was considered positive.Results: When HDs were tested for all genes, no false positive findings were observed except for AKT2, CD24L4, CD44 (n=3 cases). All of the genes except for TWIST, ER and PR could be positively detected in samples spiked with 10 LNCAP cells. In patient samples, at least one of all studied markers was detected in 21/25 (84%) of the patients. The distribution of the markers across all patients was highly variable. However, PI3K expression was observed most frequently (n=8/21 patients), followed by the expression of CD44 (n=6/21 patients), HER2 (n=5/21 patients) and TWIST, KRAS, mTOR and EpCAM (4/21 patients), respectively. No expression was observed for MUC1, PR and CD45. In general, EMT- and stem cell-like CTC were predominantly detected. HER2 positive and epithelial-like CTC as well as CTC expressing ER, PR and EGFR were observed less frequently. Interestingly, some patients expressed only one CTC-subtype.Conclusion: Multi-gene expression profiling improves the characterization of CTC of an individual patient. Furthermore, it was possible to classify individual patient samples into CTC subtypes. Despite these promising preliminary findings, the method has to be further optimized and needs to be verified in a larger patient population. Citation Format: Maren Bredemeier, Bahriye Aktas, Rainer Kimmig, Sabine Kasimir-Bauer. Establishment of a multimarker gene panel for the characterization of circulating tumor cells in metastatic breast cancer. [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 1466. doi:10.1158/1538-7445.AM2013-1466