DMRforPairs: Identifying Differentially Methylated Regions between unique samples using array based methylation profiles

Background: Array based methylation profiling is a cost-effective solution to study the association between genome methylation and human disease & development. Available tools to analyze the Illumina Infinium HumanMethylation450 BeadChip focus on comparing methylation levels per locus. Other tools combine multiple probes into a range, identifying differential methylated regions (DMRs). These tools all require groups of samples to compare. However, comparison of unique, individual samples is essential in situations where larger sample sizes are not possible.Results: DMRforPairs was designed to compare regional methylation status between unique samples. It identifies probe dense genomic regions and quantifies/tests their (difference in) methylation level between the samples. As a proof of concept, DMRforPairs is applied to public data from four human cell lines: two lymphoblastoid cell lines from healthy individuals and the cancer cell lines A431 and MCF7 (including 2 technical replicates each). DMRforPairs identified an increasing number of DMRs related to the sample phenotype when biological similarity of the samples decreased. DMRs identified by DMRforPairs were related to the biological origin of the cell lines.Conclusion: To our knowledge, DMRforPairs is the first tool to identify and visualize relevant and significant differentially methylated regions between unique samples

BCAR1, a human homologue of the adapter protein p130Cas, and antiestrogen resistance in breast cancer cells

BACKGROUND: Treatment of breast cancer with the antiestrogen tamoxifen is effective in approximately one half of the patients with estrogen receptor-positive disease, but tumors recur frequently because of the development of metastases that are resistant to tamoxifen. We have previously shown that mutagenesis of human estrogen-dependent ZR-75-1 breast cancer cells by insertion of a defective retrovirus genome caused the cells to become antiestrogen resistant. In this study, we isolated and characterized the crucial gene at the breast cancer antiestrogen resistance 1 (BCAR1) locus. METHODS/RESULTS: Transfer of the BCAR1 locus from retrovirus-mutated, antiestrogen-resistant cells to estrogen-dependent ZR-75-1 cells by cell fusion conferred an antiestrogen-resistant phenotype on the recipient cells. The complete coding sequence of BCAR1 was isolated by use of exon-trapping and complementary DNA (cDNA) library screening. Sequence analysis of human BCAR1 cDNA predicted a protein of 870 amino acids that was strongly homologous to rat p130Cas-adapter protein. Genomic analysis revealed that BCAR1 consists of seven exons and is located at chromosome 16q23.1. BCAR1 transcripts were detected in multiple human tissues and were similar in size to transcripts produced by retrovirus-mutated ZR-75-1 cells. Transfection of BCAR1 cDNA into ZR-75-1 cells again resulted in sustained cell proliferation in the presence of antiestrogens, confirming that BCAR1 was the responsible gene in the locus. CONCLUSIONS: Overexpression of the BCAR1 gene confers antiestrogen resistance on human ZR-75-1 breast cancer cells. Overexpression of BCAR1 in retrovirus-mutated cells appears to result from activation of the gene's promoter. The isolation and characterization of this gene open new avenues to elucidating mechanisms by which the growth of human breast cancer becomes independent of estrogen

Pleiotropic actions of suramin on the proliferation of human breast-cancer cells in vitro

Suramin, a non‐specific growth factor antagonist, is currently under investigation for treatment of cancer patients. We studied its action on 6 different human breast‐cancer cell lines in vitro. In complete growth medium, pleiotropic effects were observed with respect to cell proliferation, i.e. suramin is stimulatory at low concentrations and inhibitory at higher concentrations, for 4 of the 6 cell lines studied. The various cell lines showed marked differences with respect to the antiproliferative action of suramin, the Evsa‐T cells being by far the most sensitive ones. A suramin concentration of 100 μg/ml brought about a 100% stimulation of the proliferation of ZR/HERc cells, ZR 75.1 cells ectopically expressing a human epidermal growth factor receptor (EGF‐R) cDNA. Although less pronounced (10 to 60% stimulation), a similar response was observed for the parent ZR 75.1 cells, as well as for T‐47D and MDA‐MB‐231 cells. The non‐specificity of the action of suramin was established by the observation that suramin‐induced inhibition of cell proliferation could be abolished by insulin‐like growth factor‐1 (IGF‐I) or basic fibroblast growth factor (bFGF), and even by estradiol, both in complete growth medium and under defined serum‐free conditions. Our data indicate that suramin exerts pleiotropic effects on the proliferation of human breast cancer cells in vitro, and confirm the non‐specific nature of its action. The stimulatory effect of low concentrations of suramin on the proliferation of breast cancer cells may have important consequences for breast cancer patients treated with suramin. Copyrigh

Mining microarray datasets aided by knowledge stored in literature

DNA microarray technology produces large amounts of data. For data mining of these datasets, background information on genes can be helpful. Unfortunately most information is stored in free text. Here, we present an approach to use this information for DNA microarray data mining

Targetclone: A multi-sample approach for reconstructing subclonal evolution of tumors

Most tumors are composed of a heterogeneous population of subclones. A more detailed insight into the subclonal evolution of these tumors can be helpful to study progression and treatment response. Problematically, tumor samples are typically very heterogeneous, making deconvolving individual tumor subclones a major challenge. To overcome this limitation, reducing heterogeneity, such as by means of microdissections, coupled with targeted sequencing, is a viable approach. However, computational methods that enable reconstruction of the evolutionary relationships require unbiased read depth measurements, which are commonly challenging to obtain in this setting. We introduce TargetClone, a novel method to reconstruct the subclonal evolution tree of tumors from single-nucleotide polymorphism allele frequency and somatic single-nucleotide variant measurements. Furthermore, our method infers copy numbers, alleles and the fraction of the tumor component in each sample. TargetClone was specifically designed for targeted sequencing data obtained from microdissected samples. We demonstrate that our method obtains low error rates on simulated data. Additionally, we show that our method is able to reconstruct expected trees in a testicular germ cell cancer and ovarian cancer dataset. The TargetClone package including tree visualization is written in Python and is publicly available at https://github.com/UMCUGenetics/targetclone

Co-occurrence based meta-analysis of scientific texts: retrieving biological relationships between genes

MOTIVATION: The advent of high-throughput experiments in molecular biology creates a need for methods to efficiently extract and use information for large numbers of genes. Recently, the associative concept space (ACS) has been developed for the representation of information extracted from biomedical literature. The ACS is a Euclidean space in which thesaurus concepts are positioned and the distances between concepts indicates their relatedness. The ACS uses co-occurrence of concepts as a source of information. In this paper we evaluate how well the system can retrieve functionally related genes and we compare its performance with a simple gene co-occurrence method. RESULTS: To assess the performance of the ACS we composed a test set of five groups of functionally related genes. With the ACS good scores were obtained for four of the five groups. When compared to the gene co-occurrence method, the ACS is capable of revealing more functional biological relations and can achieve results with less literature available per gene. Hierarchical clustering was performed on the ACS output, as a potential aid to users, and was found to provide useful clusters. Our results suggest that the algorithm can be of value for researchers studying large numbers of genes. AVAILABILITY: The ACS program is available upon request from the authors

Bcar1/p130Cas protein and primary breast cancer: prognosis and response to tamoxifen treatment

BACKGROUND: The product of the Bcar1/p130Cas (breast cancer resistance/p130Crk-associated substrate) gene causes resistance to antiestrogen drugs in human breast cancer cells in vitro. To investigate its role in clinical breast cancer, we determined the levels of Bcar1/p130Cas protein in a large series of primary breast carcinomas. METHODS: We measured Bcar1/p130Cas protein in cytosol extracts from 937 primary breast carcinomas by western blot analysis. The levels of Bcar1/p130Cas protein were tested for associations and trends against clinicopathologic and patient characteristics, the lengths of relapse-free survival and overall survival (n = 775), and the efficacy of first-line treatment with tamoxifen for recurrent or metastatic disease (n = 268). RESULTS: Bcar1/p130Cas levels in primary tumors were associated with age/menopausal status and the levels of estrogen receptor and progesterone receptor. In univariate survival analysis, higher Bcar1/p130Cas levels were associated with poor relapse-free survival and overall survival (both two-sided P =.04; log-rank test for trend). In multivariate analysis, a high level of Bcar1/p130Cas was independently associated with poor relapse-free survival and overall survival. The response to tamoxifen therapy in patients with recurrent disease was reduced in patients with primary tumors that expressed high levels of Bcar1/p130Cas. In multivariate analysis for response, Bcar1/p130Cas was independent of classical predictive factors, such as estrogen receptor status, age/menopausal status, disease-free interval, and dominant site of relapse. CONCLUSION: Patients with primary breast tumors expressing a high level of Bcar1/p130Cas protein appear to experience more rapid disease recurrence and have a greater risk of (intrinsic) resistance to tamoxifen therapy. Thus, measurement of Bcar1/p130Cas may provide useful prognostic information for patients with primary or metastatic breast cancer

BCAR4 induces antioestrogen resistance but sensitises breast cancer to lapatinib

Background: High BCAR4 and ERBB2 mRNA levels in primary breast cancer associate with tamoxifen resistance and poor patient outcome. We determined whether BCAR4 expression sensitises breast cancer cells to lapatinib, and identifies a subgroup of patients who possibly may benefit from ERBB2-targeted therapies despite having tumours with low ERBB2 expression. Methods :Proliferation assays were applied to determine the effect of BCAR4 expression on lapatinib treatment. Changes in cell signalling were quantified with reverse-phase protein microarrays. Quantitative reverse-transcriptase polymerase chain reaction (RT-PCR) of ERBB2 and BCAR4 was performed in 1418 primary breast cancers. Combined BCAR4 and ERBB2 mRNA levels were evaluated for association with progression-free survival (PFS) in 293 oestrogen receptor-α (ER)-positive patients receiving tamoxifen as first-line monotherapy for recurrent disease.Results:BCAR4 expression strongly sensitised ZR-75-1 and MCF7 breast cancer cells to the combination of lapatinib and antioestrogens. Lapatinib interfered with phosphorylation of ERBB2 and its downstream mediators AKT, FAK, SHC, STAT5, and STAT6. Reverse transcriptase-PCR analysis showed that 27.6% of the breast cancers were positive for BCAR4 and 22% expressed also low levels of ERBB2. The clinical significance of combining BCAR4 and ERBB2 mRNA status was underscored by the finding that the group of patients having BCAR4-positive/ERBB2-low-expressing cancers had a shorter PFS on tamoxifen treatment than the BCAR4-negative group. Conclusion :This study shows that BCAR4 expression identifies a subgroup of ER-positive breast cancer patients without overexpression of ERBB2 who have a poor outcome and might benefit from combined ERBB2-targeted and antioestrogen therapy

Comparing genome-scale DNA methylation and CNV marks between adult human cultured ITGA6+ testicular cells and seminomas to assess in vitro genomic stability

Autologous transplantation of spermatogonial stem cells is a promising new avenue to restore fertility in infertile recipients. Expansion of the initial spermatogonial stem cell pool through cell culturing is a necessary step to obtain enough cells for effective repopulation of the testis after transplantation. Since in vitro propagation can lead to (epi-)genetic mutations and possibly malignant transformation of the starting cell population, we set out to investigate genome-wide DNA methylation status in uncultured and cultured primary testicular ITGA6+ sorted cells and compare them with germ cell tumor samples of the seminoma subtype. Seminomas displayed a severely global hypomethylated profile, including loss of genomic imprinting, which we did not detect in cultured primary testicular ITGA6+ cells. Differential methylation analysis revealed altered regulation of gamete formation and meiotic processes in cultured primary testicular ITGA6+ cells but not in seminomas. The pivotal POU5F1 marker was hypomethylated in seminomas but not in uncultured or cultured primary testicular ITGA6+ cells, which is reflected in the POU5F1 mRNA expression levels. Lastly, seminomas displayed a number of characteristic copy number variations that were not detectable in primary testicular ITGA6+ cells, either before or after culture. Together, the data show a distinct DNA methylation patterns in cultured primary testicular ITGA6+ cells that does not resemble the pattern found in seminomas, but also highlight the need for more sensitive methods to fully exclude the presence of malignant cells after culture and to further study the epigenetic events that take place during in vitro culture

Pattern of p53 protein expression is predictive for survival in chemoradiotherapy-naive esophageal adenocarcinoma

Introduction: TP53 mutations are considered to be the driving factor in the initiation of esophageal adenocarcinoma (EAC). However, the impact of this gene and its encoded protein as a prognostic marker has not been definitely established yet. Methods: In total, 204 chemoradiotherapy (CRT)-naive patients with EAC were included for p53 protein expression evaluation by immunohistochemistry (IHC) on the resection specimens, categorized as overexpression, heterogeneous or loss of expression, and correlated with disease free survival (DFS) and overall survival (OS) using multivariable Cox regression analysis. In a subset representing all three IHC subgroups mutatio