Inv(16)(p13q22) and t(16;16)(p13;q22) are cytogenetic hallmarks of acute myelomonoblastic leukaemia, most of them associated with abnormal bone marrow eosinophils [acute myeloid leukaemia French-American-British classification M4 with eosinophilia (FAB AML-M4Eo)] and a relatively favourable clinical course. They generate a 5'CBFB-3'MYH11 fusion gene. However, in a few cases, although RT-PCR identified a CBFB-MYH11 transcript, normal karyotype and/or fluorescent in situ hybridization (FISH) analyses using commercially available probes are found. We identified a 32-year-old woman with AML-M4Eo and normal karyotype and FISH results. Using two libraries of Bacterial Artificial Chromosome clones on 16p13 and 16q22, FISH analyses identified an insertion of 16q22 material in band 16p13, generating a CBFB-MYH11 type A transcript. Although very rare, insertions should be searched for in patients with discordant cytological and cytogenetic features because of the therapeutic consequences. Copyright © 2015 John Wiley & Sons, Ltd.

Objectives: The present study aims to investigate the interest of young adults in predictive oncological genetic testing and their willingness to pay for such a test. Furthermore, major determinants of the 2 variables of interest were identified. Methods: 348 students of economics from the Leibniz University of Hanover were queried in July 2013 using an extensive questionnaire. Among other things, the participants were asked if they are interested in information about the probability to develop cancer in the future and their willingness to pay for such information. Data were analysed using descriptive statistics and ordinal probit regressions. Additionally marginal effects were calculated. Results: About 50% of the students were interested in predictive oncological genetic testing and were willing to pay for the test. Moreover, the participants who were willing to pay for the test partly attach high monetary values to the information that could so be obtained. The study shows that the interest of the students and their willingness to pay were primarily influenced by individual attitudes and perceptions. Conclusions: The study proves that young adults were interested in predictive genetic testing and appreciate information about their probability of develop cancer someday.

With the growth of high-throughput proteomic data, in particular time series gene expression data from various perturbations, a general question that has arisen is how to organize inherently heterogenous data into meaningful structures. Since biological systems such as breast cancer tumors respond differently to various treatments, little is known about exactly how these gene regulatory networks (GRNs) operate under different stimuli. Challenges due to the lack of knowledge not only occur in modeling the dynamics of a GRN but also cause bias or uncertainties in identifying parameters or inferring the GRN structure. This paper describes a new algorithm which enables us to estimate bias error due to the effect of perturbations and correctly identify the common graph structure among biased inferred graph structures. To do this, we retrieve common dynamics of the GRN subject to various perturbations. We refer to the task as "repairing" inspired by "image repairing" in computer vision. The method can automatically correctly repair the common graph structure across perturbed GRNs, even without precise information about the effect of the perturbations. We evaluate the method on synthetic data sets and demonstrate an application to the DREAM data sets and discuss its implications to experiment design.

The high mortality of solid tumors can be attributed to their invasive and metastatic potential that is based on their migration and proliferation. Importantly, growth factor receptor (GF) signaling pathways regulating proliferation and migration are often affected by oncogenic mutations and are important targets for antitumor therapy. We found positive correlation between migration and proliferation in melanoma and lung cancer cells using videomicroscopy, not supporting the "go or grow" hypothesis. Furthermore, the invasion into collagen I matrices from brain tumor spheroids was not impaired upon the inhibition of proliferation. Sensitivity of human melanoma cells towards EGF and FGF2 treatment but not against GF receptor tyrosine kinase inhibitors was oncogenic BRAF or NRAS mutation status dependent. Prenylation inhibition failed to decrease clonogenic growth in BRAF mutant but PTEN wild-type melanoma lines but increased migration in BRAF-mutant cells. In certain mesothelioma cells, activin signaling showed a pro-tumorigenic effect suggesting activin as a valuable candidate for therapeutic interference. In summary, our findings demonstrate that proliferation is neither an obstacle nor a prerequisite for tumor cell invasion. Furthermore, the specific oncogenic mutations may differentially regulate migration and proliferation of tumor cells. Therefore, they are not only therapeutic targets but can also profoundly influence the efficacy of various therapies.

A new generation of internet-based diagnostic and research tools have arrived in the last decade. The most extensive group of these includes programs predicting the expected survival mainly by utilizing clinical data of the patient. This includes Adjuvant! Online, the MSKCC and MD Anderson nomograms and the UK-based PREDICT algorithm. A common feature of all these is the comparison of the given patient to previously treated breast cancer samples, and evaluating the clinical outcome of these previous patients. New diagnostic biomarkers can be gene expression or mutation based. Of these, large transcriptomic databases lay the basis for the KMplot.com analysis platform which is capable to assess the prognostic value of a selected gene or gene set. The link between a given mutation and survival is the focus of the cBioportal and the G-2-O software. Diagnosis is based on a transcriptome-level data derived using gene chips in the RecurrenceOnline algorithm. A risk of breast cancer development is assessed by a polygenic model in BOADICEA. In our review we target oncologists, pathologists and breast cancer researchers and provide a comprehensive summary of these and other analysis platforms.

Breast cancer (BC) is leading type of cancer among group of women, which determines almost 23% of invasive cancers. It has been reported repeatedly that the level of oxidative stress is higher for BC in comparison to cancer-free woman. The goal of the present study was to evaluate the role of base excision repair (BER) pathway in the development of BC. One-hundred seventy-one women with confirmed BC and 222 healthy controls were enrolled in presented study. The level of oxidative DNA damage and the kinetic of their repair were analyzed by the modified alkaline comet assay. The efficiency of BER pathway was evaluated by BER assay. The presence of the 326Cys/Cys genotype and 326Cys allele of OGG1 gene and the 324His/His of MUTYH gene are associated with increased risk of BC development. Moreover, correlation between clinical parameter with selected genes has shown increased risk of BC progression. The survival analysis has shown a significant lower DFS for individuals with the 762Ala/Ala genotype compared to 762Val/Vla carriers and the 762Val/Ala genotype in relation to concomitant chemotherapy and radiotherapy. In subgroup of patients with alone chemotherapy and alone radiotherapy, the 762Val/Val genotype was significantly associated with lower overall survival. Furthermore, we also elevated the level of basal and oxidative DNA damage in a group of patients with BC in relation to healthy controls. We also observed the difference in effectiveness of DNA damage repair. The results of present studies suggested the important role of BER pathway in BC development. © 2015 Wiley Periodicals, Inc.

Phospholipase C beta 1 (PLCβ1) expresses in gliomas and cultured glial cells, but its expression is barely detectable in normal glial cells. We analyzed data from Gene Expression Omnibus (GEO-GDSxxx), The Cancer Genome Atlas (TCGA), and the Repository for Molecular Brain Neoplasia Data (REMBRANDT) to explore the potential role of PLCβ1 as a biomarker in high-grade glioma (HGG). PLCβ1 expression is significantly higher in grade III gliomas than that in grade IV gliomas from GDS1815 (n = 24 vs. 76), GDS1962 (n = 19 vs. 81), and GDS1975 (n = 26 vs. 59). In GDS1815, PLCβ1 expression correlates with several known proneural (PN) signature genes; its expression from PN subtype (n = 15) is significantly higher than that from mesenchymal (Mes) subtype (n = 33) HGG. In GDS1962, PLCβ1 expression is the highest in nontumor brain tissue (n = 23) and is significantly higher than its expression in grade II gliomas [astrocytomas (n = 7) and oligodendrogliomas (n = 37)]. A Kaplan-Meier survival curve from a REMBRANDT cohort demonstrates that glioma patients with intermediate PLCβ1 expression (n = 103) survived significantly longer than PLCβ1 downregulated (2X) groups (n = 226). From TCGA data, PLCβ1 RNA-Seq signal inversely correlates with the pathological grades, and PLCβ1 expression in PN (n = 8) is of significantly higher levels than that in Mes (n = 8) subtypes of glioblastoma. The top 50 % of PLCβ1 expression subgroup (n = 294) of gliomas (grades II to IV merged) survived significantly longer than the low 50 percentile of the PLCβ1 expression subgroup (n = 293). p values are less than 0.05 for all these analyses. We conclude that PLCβ1 is a candidate signature gene for PN subtype HGG, and its expression inversely correlates with glioma pathological grade and is a potential prognostic factor.

The prognostic factors associated with the survival of glioma patients have not been well established. Loss of heterozygosity (LOH) of 9p was known to be a typical molecular signature of gliomas, but it was still unclear whether LOH of 9p was associated with poorer survival in patients with gliomas. We searched PubMed and Embase databases from the earliest records to May 2015 to identify studies that met the inclusion criteria. Either a fixed- or a random-effects model was used to calculate the pooled hazard ratio (HR) according to the between-study heterogeneity. Thirteen eligible studies involving 1465 cases of gliomas were included in the meta-analysis. There was little between-study heterogeneity (I 2 = 15 %), and the fixed-effects model was used to calculate the pooled HR. Meta-analysis of total 13 studies showed that LOH of 9p was significantly associated with poorer prognosis of glioma patients (HR = 1.39, 95%CI 1.17-1.64, P = 0.0002). Meta-analysis of eight studies reporting adjusted estimates showed that LOH of 9p was independently associated with poorer prognosis of glioma patients (HR = 1.40, 95%CI 1.14-1.72, P = 0.001). Subgroup analysis by types of gliomas showed that LOH of 9p was significantly associated with poorer prognosis in patients with glioblastoma (HR = 1.34, 95%CI 1.01-1.78, P = 0.04). There was no obvious risk of publication bias shown in the funnel plot. LOH of 9p is significantly associated with poorer prognosis of glioma patients, which is a useful biomarker in predicting patients' survival.

To explore the association of c-erbB-2 protein expression with clinicopathological characteristics and prognosis of gastric cancer (GC) after surgery.

Bone flare reaction as a sign of response to antineoplastic treatment has been redefined, including the onset of new osteoblastic lesions. If misunderstood as skeletal progression, this finding could lead to erroneous therapy discontinuation, changing the disease clinical course. We aim to describe this clinical phenomenon in patients with advanced non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) gene-activating mutations treated with tyrosine kinase inhibitor (TKI).

Osteosarcoma (OS) is the most common primary bone tumor and has low cure rates. Our study aimed to evaluate the roles of mitogen-activated protein kinase 7 (MAPK7) in cell proliferation, migration and invasion using the SOSP-M human OS cell line as an in vitro model.

Human epidermal growth factor receptor 2 (HER2) gene amplification/overexpression is a major therapeutic target in breast cancer, and has been introduced as a predictive biomarker to identify patients who may benefit from therapy with anti-HER2 agents. HER2 somatic mutations have been reported, and these may influence the effect of HER2-targeted drugs.

Breast cancer is the most common cancer in females in Iran and in most of the developed countries. Studies have shown that having chronic stress in individuals predisposes several types of cancer including breast cancer. Research results showed that spiritual factors correlate with indices of physical consequences such as heart disease, cancer, and death, so do psychiatric conditions and changes in receptor gene expression in depression, anxiety, and social dysfunction. Different studies demonstrated the role of neurotransmitters in occurrence and progression of cancers. They affected cells by their various types of receptors. An effective gene in mental and physical conditions is Dopamine receptor. Accordingly, the study was conducted to evaluate effects of psychotherapy (spiritual intervention) on changes in Dopamine receptor gene expressions in breast cancer patients. 90 female volunteers, including 30 healthy individuals and 60 diagnosed with breast cancer, considering exclusion criteria, were selected for the purpose of the study. The breast cancer patients were further categorized into experimental and control groups of 30 each. Blood samples were collected both prior to and following the spiritual intervention to analyze changes in their dopamine gene receptor expressions. We observed that DRD2-DRD4 in the control group (breast cancer patients) PBMC increased compared to healthy individuals. Also, DRD2-DRD4 in intervention group PBMC decreased compared to the control group and to even lower than those of healthy individuals. The findings were of great significance in management and treatment of cancer because they revealed the possibility of using alternative treatments (e.g., spiritual interventions) apart from conventional medical treatments.