Association of microRNA-7 and its binding partner CDR1-AS with the prognosis and prediction of 1st-line tamoxifen therapy in breast cancer

The large number of non-coding RNAs (ncRNAs) and their breadth of functionalities has fuelled many studies on their roles in cancer. We previously linked four microRNAs to breast cancer prognosis. One of these microRNAs, hsa-miR-7, was found to be regulated by another type of ncRNA, the circular non-coding RNA (circRNA) CDR1-AS, which contains multiple hsa-miR-7 binding sites. Based on this finding, we studied the potential clinical value of this circRNA on breast cancer prognosis in a cohort based on a cohort that was previously analysed for hsa-miR-7 and in an adjuvant hormone-naïve cohort for 1st-line tamoxifen treatment outcomes, in which we also analysed hsa-miR-7. A negative correlation was observed between hsa-miR-7 and CDR1-AS in both cohorts. Despite associations with various clinical metrics (e.g., tumour grade, tumour size, and relapse location), CDR1-AS was neither prognostic nor predictive of relevant outcomes in our cohorts. However, we did observe stromal CDR1-AS expression, suggesting a possible cell-type specific interaction. Next to the known association of hsa-miR-7 expression with poor prognosis in primary breast cancer, we found that high hsa-miR-7 expression was predictive of an adverse response to tamoxifen therapy and poor progression-free and post-relapse overall survival in patients with recurrent disease

MRNA expression profiles of colorectal liver metastases as a novel biomarker for early recurrence after partial hepatectomy

Background: Identification of specific risk groups for recurrence after surgery for isolated colorectal liver metastases (CRLM) remains challenging due to the heterogeneity of the disease. Classical clinicopathologic parameters have limited prognostic value. The aim of this study was to identify a gene expression signature measured in CRLM discriminating early from late recurrence after partial hepatectomy. Methods: CRLM from two patient groups were collected: I) with recurrent disease ≤12 months after surgery (N = 33), and II) without recurrences and disease free for ≥36 months (N = 30). The patients were clinically homogeneous; all had a low clinical risk score (0-2) and did not receive (neo-) adjuvant chemotherapy. Total RNA was hybridised to Illumina arrays, and processed for analysis. A leave-one-out cross validation (LOOCV) analysis was performed to identify a prognostic gene expression signature. Results: LOOCV yielded an 11-gene profile with prognostic value in relation to recurrent disease ≤12 months after partial hepatectomy. This signature had a sensitivity of 81.8%, with a specificity of 66.7% for predicting recurrences (≤12 months) versus no recurrences for at least 36 months after surgery (X2 P < 0.0001). Conclusion: The current study yielded an 11-gene signature at mRNA level in CRLM discriminating early from late or no relapse after partial hepatectomy

A method to correlate mRNA expression datasets obtained from fresh frozen and formalin-fixed, paraffin-embedded tissue samples: A matter of thresholds

Background: Gene expression profiling of tumors is a successful tool for the discovery of new cancer biomarkers and potential targets for the development of new therapeutic strategies. Reliable profiling is preferably performed on fresh frozen (FF) tissues in which the quality of nucleic acids is better preserved than in formalin-fixed paraffin-embedded (FFPE) material. However, since snap-freezing of biopsy materials is often not part of daily routine in pathology laboratories, one may have to rely on archival FFPE material. Procedures to retrieve the RNAs from FFPE materials have been developed and therefore, datasets obtained from FFPE and FF materials need to be made compatible to ensure reliable comparisons are possible. Aim: To develop an efficient method to compare gene expression profiles obtained from FFPE and FF samples using the same platform. Methods: Twenty-six FFPE-FF sample pairs of the same tumors representing various cancer types, and two FFPE-FF sample pairs of breast cancer cell lines, were included. Total RNA was extracted and gene expression profiling was carried out using Illumina's Whole-Genome cDNA-mediated Annealing, Selection, extension and Ligation (WG-DASL) V3 arrays, enabling the simultaneous detection of 24,526 mRNA transcripts. A sample exclusion criterion was created based on the expression of 11 stably expressed reference genes. Pearson correlation at the probe level was calculated for paired FFPE-FF, and three cut-off values were chosen. Spearman correlation coefficients between the matched FFPE and FF samples were calculated for three probe lists with varying levels of significance and compared to the correlation based on all measured probes. Unsupervised hierarchical cluster analysis was performed to verify performance of the included probe lists to compare matched FPPE-FF samples. Results: Twenty-seven FFPE-FF pairs passed the sample exclusion criterion. From the profiles of 27 FFPE and FF matched samp

High TWIST1 mRNA expression is associated with poor prognosis in lymph node-negative and estrogen receptor-positive human breast cancer and is co-expressed with stromal as well as ECM related genes

Introduction: The TWIST homolog 1 (TWIST1) is a transcription factor that induces epithelial to mesenchymal transition (EMT), a key process in metastasis. The purpose of this study was to investigate whether TWIST1 expression predicts disease progression in a large breast cancer cohort with long-term clinical follow-up, and to reveal the biology related to TWIST1 mediated disease progression.Methods: TWIST1 mRNA expression level was analyzed by quantitative real-time reverse polymerase chain reaction (RT-PCR) in 1,427 primary breast cancers. In uni- and multivariate analysis using Cox regression, TWIST1 mRNA expression level was associated with metastasis-free survival (MFS), disease-free survival (DFS) and overall survival (OS). Separate analyses in lymph node-negative patients (LNN, n = 778) who did not receive adjuvant systemic therapy, before and after stratification into estrogen receptor (ER)-positive (n = 552) and ER-negative (n = 226) disease, were also performed. The association of TWIST1 mRNA with survival endpoints was assessed using Kaplan-Meier analysis. Using gene expression arrays, genes showing a significant Spearman rank correlation with TWIST1 were used to identify overrepresented Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG)-annotated biological pathways.Results: Increased mRNA expression level of TWIST1 analyzed as a continuous variable in both uni- and multivariate analysis was associated with shorter MFS in all patients (hazard ratio (HR): 1.17, 95% confidence interval, (95% CI):1.09 to 1.26; and HR: 1.17, 95% CI: 1.08 to 1.26; respectively), in LNN patients (HR: 1.22, 95% CI: 1.09 to 1.36; and HR: 1.21, 95% CI: 1.07 to 1.36; respectively) and in the ER-positive subgroup of LNN patients (HR: 1.34, 95% CI: 1.17 to 1.53; and HR: 1.32, 95% CI: 1.14 to 1.53; respectively). Similarly, high TWIST1 expression was associated with shorter DFS and OS in all patients and in the LNN/ER-positive subgroup. In contrast, no association of TWIST1 mRNA expression with MFS, DFS or OS was observed in ER-negative patients. Genes h

Phosphoserine aminotransferase 1 is associated to poor outcome on tamoxifen therapy in recurrent breast cancer

In a previous study, we detected a significant association between phosphoserine aminotransferase 1 (PSAT1) hyper-methylation and mRNA levels to outcome to tamoxifen treatment in recurrent disease. We here aimed to study the association of PSAT1 protein levels to outcome upon tamoxifen treatment and to obtain more insight in its role in tamoxifen resistance. A cohort of ER positive, hormonal therapy naïve primary breast carcinomas was immunohistochemically (IHC) stained for PSAT1. Staining was analyzed for association with patient's time to progression (TTP) and overall response on first-line tamoxifen for recurrent disease. PSAT1 mRNA levels were also assessed by reverse transcriptase quantitative polymerase chain reaction (RT-qPCR; n = 161) and Affymetrix GeneChip (n = 155). Association of PSAT1 to biological pathways on tamoxifen outcome were assessed by global test. PSAT1 protein and mRNA levels were significantly associated to poor outcome to tamoxifen treatment. When comparing PSAT1

DC-SCRIPT is a novel regulator of the tumor suppressor gene CDKN2B and induces cell cycle arrest in ERα-positive breast cancer cells

Breast cancer is one of the most common causes of cancer-related deaths in women. The estrogen receptor (ERα) is well known for having growth promoting effects in breast cancer. Recently, we have identified DC-SCRIPT (ZNF366) as a co-suppressor of ERα and as a strong and independent prognostic marker in ESR1 (ERα gene)-positive breast cancer patients. In this study, we further investigated the molecular mechanism on how DC-SCRIPT inhibits breast cancer cell growth. DC-SCRIPT mRNA levels from 190 primary ESR1-positive breast tumors were related to global gene expression, followed by gene ontology and pathway analysis. The effect of DC-SCRIPT on breast cancer cell growth and cell cycle arrest was investigated using novel DC-SCRIPT-inducible MCF7 breast cancer cell lines. Genome-wide expression profiling of DC-SCRIPT-expressing MCF7 cells was performed to investigate the effect of DC-SCRIPT on cell cycle-related gene expression. Findings were validated by real-time PCR in a cohort of 1,132 ESR1-positive breast cancer patients. In the primary ESR1-positive breast tumors, DC-SCRIPT expression negatively correlated with several cell cycle gene ontologies and pathways. DC-SCRIPT expression strongly reduced breast cancer cell growth in vitro, breast tumor growth in vivo, and induced cell cycle arrest. In addition, in the presence of DC-SCRIPT, multiple cell cycles related genes were differentially expressed including the tumor suppressor gene CDKN2B. Moreover, in 1,132 primary ESR1-positive breast tumors, DC-SCRIPT expression also correlated with CDKN2B expression. Collectively, these data show that DC-SCRIPT acts as a novel regulator of CDKN2B and induces cell cycle arrest in ESR1-positive breast cancer cells

Elevated APOBEC3B Correlates with Poor Outcomes for Estrogen-Receptor-Positive Breast Cancers

Recent observations connected DNA cytosine deaminase APOBEC3B to the genetic evolution of breast cancer. We addressed whether APOBEC3B is associated with breast cancer clinical outcomes. APOBEC3B messenger RNA (mRNA) levels were related in 1,491 primary breast cancers to disease-free (DFS), metastasis-free (MFS), and overall survival (OS). For independent validation, APOBEC3B mRNA expression was associated with patient outcome data in five additional cohorts (over 3,500 breast cancer cases). In univariate Cox regression analysis, increasing APOBEC3B expression as a continuous variable was associated with worse DFS, MFS, and OS (hazard ratio [HR] = 1.20, 1.21, and 1.24, respectively; all P < .001). Also, in untreated ER-positive (ER+), but not in ER−, lymph-node-negative patients, high APOBEC3B levels were associated with a poor DFS (continuous variable: HR = 1.29, P = .001; dichotomized at the median level, HR = 1.66, P = .0002). This implies that APOBEC3B is a marker of pure prognosis in ER + disease. These findings were confirmed in the analyses of five independent patient sets. In these analyses, APOBEC3B expression dichotomized at the median level was associated with adverse outcomes (METABRIC discovery and validation, 788 and 706 ER + cases, disease-specific survival (DSS), HR = 1.77 and HR = 1.77, respectively, both P < .001; Affymetrix dataset, 754 ER + cases, DFS, HR = 1.57, P = 2.46E-04; NKI295, 181 ER + cases, DFS, HR = 1.72, P = .054; and BIG 1-98, 1,219 ER + cases, breast-cancer-free interval (BCFI), HR = 1.42, P = 0.0079). APOBEC3B is a marker of pure prognosis and poor outcomes for ER + breast cancer, which strongly suggests that genetic aberrations induced by APOBEC3B contribute to breast cancer progression. Electronic supplementary material The online version of this article (doi: 10.1007/s12672-014-0196-8) contains supplementary material, which is available to authorized users

Prognostic Impact of HER2 and ER Status of Circulating Tumor Cells in Metastatic Breast Cancer Patients with a HER2-Negative Primary Tumor

BACKGROUND: Preclinical and clinical studies have reported that human epidermal growth factor receptor 2 (HER2) overexpression yields resistance to endocrine therapies. Here the prevalence and prognostic impact of HER2-positive circulating tumor cells (CTCs) were investigated retrospectively in metastatic breast cancer (MBC) patients with a HER2-negative primary tumor receiving endocrine therapy. Additionally, the prevalence and prognostic significance of HER2-positive CTCs were explored in a chemotherapy cohort, as well as the prognostic impact of the estrogen receptor (ER) CTC status in both cohorts. METHODS: Included were MBC patients with a HER2-negative primary tumor, with ≥1 detectable CTC, starting a new line of treatment. CTCs were enumerated using the CellSearch system, characterized for HER2 with the CellSearch anti-HER2 phenotyping reagent, and characterized for ER mRNA expression. Primary end point was pr

Semiautomated isolation and molecular characterisation of single or highly purified tumour cells from CellSearch enriched blood samples using dielectrophoretic cell sorting

Background: Molecular characterisation of single circulating tumour cells (CTCs) holds considerable promise for predictive biomarker assessment and to explore CTC heterogeneity. We evaluate a new method, the DEPArray system, that allows the dielectrophoretic manipulation and isolation of single and 100% purified groups of CTCs from pre-enriched blood samples and explore the feasibility of their molecular characterisation.Methods:Samples containing known numbers of two cell populations were used to assess cell loss during sample loading. Cultured breast cancer cells were isolated from spiked blood samples using CellSearch CTC and Profile kits. Single tumour cells and groups of up to 10 tumour cells were recovered with the DEPArray system and subjected to transcriptional and mutation analysis.Results:On average, 40% cell loss was observed when loading samples to the DEPArray system. Expected mutations in clinically relevant markers could be obtained for 60% of single recovered tumour cells and all groups of tumour cells. Reliable gene expression profiles were obtained from single cells and groups of up to 10 cells for 2 out of 3 spiked breast cancer cell lines.Conclusion:We describe a semiautomated workflow for the isolation of small groups of 1 to 10 tumour cells from whole blood samples and provide proof of principle for the feasibility of their comprehensive molecular characterisation