CXCR7 contributes to the aggressive phenotype of cholangiocarcinoma cells

Development of cholangiocarcinoma (CCA) is dependent on a cross-talk with stromal cells, which release different chemokines including CXCL12, that interacts with two different receptors, CXCR4 and CXCR7. The aim of the present study was to investigate the role of CXCR7 in CCA cells. CXCR7 is overexpressed by different CCA cell lines and in human CCA specimens. Knock-down of CXCR7 in HuCCT-1 cells reduced migration, invasion, and CXCL12-induced adhesion to collagen I. Survival of CCA was also reduced in CXCR7-silenced cells. The ability of CXCL12 to induce cell migration and survival was also blocked by CCX733, a CXCR7 antagonist. Similar effects of CXCR7 activation were observed in CCLP-1 cells and in primary iCCA cells. Enrichment of tumor stem-like cells by a 3D culture system resulted in increased CXCR7 expression compared to cells grown in monolayers, and genetic knockdown of CXCR7 robustly reduced sphere formation both in HuCCT-1 and in CCLP-1 cells. In HuCCT-1 cells CXCR7 was found to interact with β-arrestin 2, which was necessary to mediate CXCL12-induced migration, but not survival. In conclusion, CXCR7 is widely expressed in CCA, and contributes to the aggressive phenotype of CCA cells, inducing cell migration, invasion, adhesion, survival, growth and stem cell-like features. Cell migration induced by CXCR7 requires interaction with β-arrestin 2.     

A Novel Five Gene Signature Derived from Stem-Like Side Population Cells Predicts Overall and Recurrence-Free Survival in NSCLC

Gene expression profiling has been used to characterize prognosis in various cancers. Earlier studies had shown that side population cells isolated from Non-Small Cell Lung Cancer (NSCLC) cell lines exhibit cancer stem cell properties. In this study we apply a systems biology approach to gene expression profiling data from cancer stem like cells isolated from lung cancer cell lines to identify novel gene signatures that could predict prognosis. Microarray data from side population (SP) and main population (MP) cells isolated from 4 NSCLC lines (A549, H1650, H460, H1975) were used to examine gene expression profiles associated with stem like properties. Differentially expressed genes that were over or under-expressed at least two fold commonly in all 4 cell lines were identified. We found 354 were upregulated and 126 were downregulated in SP cells compared to MP cells; of these, 89 up and 62 downregulated genes (average 2 fold changes) were used for Principle Component Analysis (PCA) and MetaCore™ pathway analysis. The pathway analysis demonstrated representation of 4 up regulated genes (TOP2A, AURKB, BRRN1, CDK1) in chromosome condensation pathway and 1 down regulated gene FUS in chromosomal translocation. Microarray data was validated using qRT-PCR on the 5 selected genes and all showed robust correlation between microarray and qRT-PCR. Further, we analyzed two independent gene expression datasets that included 360 lung adenocarcinoma patients from NCI Director''s Challenge Set for overall survival and 63 samples from Sungkyunkwan University (SKKU) for recurrence free survival. Kaplan-Meier and log-rank test analysis predicted poor survival of patients in both data sets. Our results suggest that genes involved in chromosome condensation are likely related with stem-like properties and might predict survival in lung adenocarcinoma. Our findings highlight a gene signature for effective identification of lung adenocarcinoma patients with poor prognosis and designing more aggressive therapies for such patients.     

Stem Cell-Like Gene Expression in Ovarian Cancer Predicts Type II Subtype and Prognosis

Although ovarian cancer is often initially chemotherapy-sensitive, the vast majority of tumors eventually relapse and patients die of increasingly aggressive disease. Cancer stem cells are believed to have properties that allow them to survive therapy and may drive recurrent tumor growth. Cancer stem cells or cancer-initiating cells are a rare cell population and difficult to isolate experimentally. Genes that are expressed by stem cells may characterize a subset of less differentiated tumors and aid in prognostic classification of ovarian cancer. The purpose of this study was the genomic identification and characterization of a subtype of ovarian cancer that has stem cell-like gene expression. Using human and mouse gene signatures of embryonic, adult, or cancer stem cells, we performed an unsupervised bipartition class discovery on expression profiles from 145 serous ovarian tumors to identify a stem-like and more differentiated subgroup. Subtypes were reproducible and were further characterized in four independent, heterogeneous ovarian cancer datasets. We identified a stem-like subtype characterized by a 51-gene signature, which is significantly enriched in tumors with properties of Type II ovarian cancer; high grade, serous tumors, and poor survival. Conversely, the differentiated tumors share properties with Type I, including lower grade and mixed histological subtypes. The stem cell-like signature was prognostic within high-stage serous ovarian cancer, classifying a small subset of high-stage tumors with better prognosis, in the differentiated subtype. In multivariate models that adjusted for common clinical factors (including grade, stage, age), the subtype classification was still a significant predictor of relapse. The prognostic stem-like gene signature yields new insights into prognostic differences in ovarian cancer, provides a genomic context for defining Type I/II subtypes, and potential gene targets which following further validation may be valuable in the clinical management or treatment of ovarian cancer.     

CXCR4 expression in prostate cancer progenitor cells

Tumor progenitor cells represent a population of drug-resistant cells that can survive conventional chemotherapy and lead to tumor relapse. However, little is known of the role of tumor progenitors in prostate cancer metastasis. The studies reported herein show that the CXCR4/CXCL12 axis, a key regulator of tumor dissemination, plays a role in the maintenance of prostate cancer stem-like cells. The CXCL4/CXCR12 pathway is activated in the CD44(+)/CD133(+) prostate progenitor population and affects differentiation potential, cell adhesion, clonal growth and tumorigenicity. Furthermore, prostate tumor xenograft studies in mice showed that a combination of the CXCR4 receptor antagonist AMD3100, which targets prostate cancer stem-like cells, and the conventional chemotherapeutic drug Taxotere, which targets the bulk tumor, is significantly more effective in eradicating tumors as compared to monotherapy.     

溶瘤腺病毒ZD55对类肝癌干细胞的抑制效应

溶瘤腺病毒能够靶向和杀死癌症干细胞,被认为是一种很有前景的抗癌药物.已有研究表明,溶瘤腺病毒ZD55能够靶向肝癌,并且表现出明显的细胞毒性效应.然而,其对肝癌干细胞是否具有同样地杀伤效力仍需进一步探讨.利用悬浮培养富集类肝癌干细胞,并验证其肝癌干细胞的特征.进一步通过MTT、结晶紫染色、Hoechst染色、Western blot和流式细胞术等检测ZD55对类肝癌干细胞的细胞存活率、凋亡诱导和病理效应等.结果发现,悬浮培养的类肝癌干细胞具有自我更新和分化能力、高表达干细胞相关转录因子(如NANOG和OCT4)、处于静息状态和具有耐药性等特性,溶瘤腺病毒处理后表现出明显的细胞毒性效应和杀伤特性,类肝癌干细胞的最低生存率仅为26.7%.ZD55能够非常明显地诱导类肝癌干细胞凋亡,其凋亡率最高达到60%.因此,ZD55可能会成为靶向肝癌干细胞的一种很有前景的治疗药物,对肝癌的临床治疗具有一定的应用价值.     

Discovering tightly regulated and differentially expressed gene sets in whole genome expression data

MOTIVATION: Recently, a new type of expression data is being collected which aims to measure the effect of genetic variation on gene expression in pathways. In these datasets, expression profiles are constructed for multiple strains of the same model organism under the same condition. The goal of analyses of these data is to find differences in regulatory patterns due to genetic variation between strains, often without a phenotype of interest in mind. We present a new method based on notions of tight regulation and differential expression to look for sets of genes which appear to be significantly affected by genetic variation. RESULTS: When we use categorical phenotype information, as in the Alzheimer's and diabetes datasets, our method finds many of the same gene sets as gene set enrichment analysis. In addition, our notion of correlated gene sets allows us to focus our efforts on biological processes subjected to tight regulation. In murine hematopoietic stem cells, we are able to discover significant gene sets independent of a phenotype of interest. Some of these gene sets are associated with several blood-related phenotypes. AVAILABILITY: The programs are available by request from the authors.     

Methylome analysis reveals Jak-STAT pathway deregulation in putative breast cancer stem cells

Growing evidence supports the existence of a subpopulation of cancer cells with stem cell characteristics within breast tumors. In spite of its potential clinical implications, an understanding of the mechanisms responsible for retaining the stem cell characteristics in these cells is still lacking. Here, we used the mammosphere model combined with DNA methylation bead arrays and quantitative gene expression to characterize the epigenetic mechanisms involved in the regulation of developmental pathways in putative breast cancer stem cells. Our results revealed that MCF7-derived mammospheres exhibit distinct CpG promoter methylation profiles in a specific set of genes, including those involved in Jak-STAT signaling pathway. Hypomethylation of several gene components of the Jak-STAT pathway was correlated with an increased expression in mammospheres relative to parental cells. Remarkably, cell sorting of the cells with a putative cancer stem cell phenotype (CD44⁺/CD24 low) suggests a constitutive activation of Jak-STAT pathway in these cells. These results show that Jak-STAT activation may represent a characteristic of putative breast cancer stem cells. In addition, they favor the concept that the expression of cancer stem-like pathways and the establishment and maintenance of defining properties of cancer stem cells are orchestrated by epigenetic mechanisms.     

Key pathways involved in prostate cancer based on gene set enrichment analysis and meta analysis

Prostate cancer is one of the most common male malignant neoplasms; however, its causes are not completely understood. A few recent studies have used gene expression profiling of prostate cancer to identify differentially expressed genes and possible relevant pathways. However, few studies have examined the genetic mechanics of prostate cancer at the pathway level to search for such pathways. We used gene set enrichment analysis and a meta-analysis of six independent studies after standardized microarray preprocessing, which increased concordance between these gene datasets. Based on gene set enrichment analysis, there were 12 down- and 25 up-regulated mixing pathways in more than two tissue datasets, while there were two down- and two up-regulated mixing pathways in three cell datasets. Based on the meta-analysis, there were 46 and nine common pathways in the tissue and cell datasets, respectively. Three up- and 10 down-regulated crossing pathways were detected with combined gene set enrichment analysis and meta-analysis. We found that genes with small changes are difficult to detect by classic univariate statistics; they can more easily be identified by pathway analysis. After standardized microarray preprocessing, we applied gene set enrichment analysis and a meta-analysis to increase the concordance in identifying biological mechanisms involved in prostate cancer. The gene pathways that we identified could provide insight concerning the development of prostate cancer.     

When Is Hub Gene Selection Better than Standard Meta-Analysis?

Since hub nodes have been found to play important roles in many networks, highly connected hub genes are expected to play an important role in biology as well. However, the empirical evidence remains ambiguous. An open question is whether (or when) hub gene selection leads to more meaningful gene lists than a standard statistical analysis based on significance testing when analyzing genomic data sets (e.g., gene expression or DNA methylation data). Here we address this question for the special case when multiple genomic data sets are available. This is of great practical importance since for many research questions multiple data sets are publicly available. In this case, the data analyst can decide between a standard statistical approach (e.g., based on meta-analysis) and a co-expression network analysis approach that selects intramodular hubs in consensus modules. We assess the performance of these two types of approaches according to two criteria. The first criterion evaluates the biological insights gained and is relevant in basic research. The second criterion evaluates the validation success (reproducibility) in independent data sets and often applies in clinical diagnostic or prognostic applications. We compare meta-analysis with consensus network analysis based on weighted correlation network analysis (WGCNA) in three comprehensive and unbiased empirical studies: (1) Finding genes predictive of lung cancer survival, (2) finding methylation markers related to age, and (3) finding mouse genes related to total cholesterol. The results demonstrate that intramodular hub gene status with respect to consensus modules is more useful than a meta-analysis p-value when identifying biologically meaningful gene lists (reflecting criterion 1). However, standard meta-analysis methods perform as good as (if not better than) a consensus network approach in terms of validation success (criterion 2). The article also reports a comparison of meta-analysis techniques applied to gene expression data and presents novel R functions for carrying out consensus network analysis, network based screening, and meta analysis.     

CXCL14 is no direct modulator of CXCR4

C-X-C motif chemokine 12/C-X-C chemokine receptor type 4 (CXCL12/CXCR4) signaling is involved in ontogenesis, hematopoiesis, immune function and cancer. Recently, the orphan chemokine CXCL14 was reported to inhibit CXCL12-induced chemotaxis – probably by allosteric modulation of CXCR4. We thus examined the effects of CXCL14 on CXCR4 regulation and function using CXCR4-transfected human embryonic kidney (HEK293) cells and Jurkat T cells. CXCL14 did not affect dose–response profiles of CXCL12-induced CXCR4 phosphorylation, G protein-mediated calcium mobilization, dynamic mass redistribution, kinetics of extracellular signal-regulated kinase 1 (ERK1) and ERK2 phosphorylation or CXCR4 internalization. Hence, essential CXCL12-operated functions of CXCR4 are insensitive to CXCL14, suggesting that interactions of CXCL12 and CXCL14 pathways depend on a yet to be identified CXCL14 receptor.     

A miR-206 regulated gene landscape enhances mammary epithelial differentiation

miR-206 is known to suppress breast cancer. However, while it is expressed in mammary stem cells, its function in such nontumor cells is not well understood. Here, we explore the role of miR-206 in undifferentiated, stem-like mammary cells using the murine mammary differentiation model HC11, genome-wide gene expression analysis, and functional assays. We describe the miR-206-regulated gene landscape and propose a network whereby miR-206 suppresses tumor development. We functionally demonstrate that miR-206 in nontumor stem-like cells induces a G1–S cell cycle arrest, and reduces colony formation and epithelial-to-mesenchymal transition markers. Finally, we show that addition of miR-206 accelerates the mammary differentiation process along with related accumulation of lipids. We conclude that miR-206 impacts a network of signaling pathways, and acts as a regulator of proliferation, stemness, and mammary cell differentiation in nontumor stem-like mammary cells. Our study provides a broad insight into the breast cancer suppressive functions of miR-206.     

Systematic identification of cancer driving signaling pathways based on mutual exclusivity of genomic alterations

We present a novel method for the identification of sets of mutually exclusive gene alterations in a given set of genomic profiles. We scan the groups of genes with a common downstream effect on the signaling network, using a mutual exclusivity criterion that ensures that each gene in the group significantly contributes to the mutual exclusivity pattern. We test the method on all available TCGA cancer genomics datasets, and detect multiple previously unreported alterations that show significant mutual exclusivity and are likely to be driver events.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0612-6) contains supplementary material, which is available to authorized users.     

Alteration in genes expression patterns during in vitro differentiation of mouse spermatogonial cells into neuroepithelial-like cells

Pluripotent stem cells derived from testis is a new, natural, and unlimited source for cell therapy in regenerative medicine and represent a possible alternative to replacing of all cells in the body. Here, we designed a simple co-culture system of spermatogonia cells with Sertoli cells for the generation of embryonic stem-like cells from mouse testis. The importance of our simple method will be clear when we compared it with other complex and time-consuming methods. Embryonic stem-like colonies with sharp border confirmed by real-time PCR, immunocytochemistry and flow cytometry assessments. Embryonic stem-like colonies were immunopositive for pluripotency markers. Transition of spermatogonia cells to embryonic stem-like cells was accompanied by extensive changes in gene expression. These changes included significant increase in pluripotency genes expression and significant decrease in germ cell-specific genes expression. Also, we proved the differentiation capacity of embryonic stem-like cells to neuroepithelial-like cells which were immunoreactive to Nestin and Neurofilament 68. Evaluation of genes expression during in vitro differentiation into neuroepithelial-like cells showed high-level expression of Nestin whether this gene approximately has no expression in undifferentiated embryonic stem-like cells. Also, expression of pluripotency genes has significantly decreased in neuroepithelial-like cells compared with embryonic stem-like cells. This study shows that embryonic stem-like cells derived from testis are capable to differentiate into neuroepithelial-like cells that may provide a cellular reservoir usable for neurodegenerative disorders.     

Comparative analyses identify molecular signature of MRI-classified SVZ-associated glioblastoma

Glioblastoma (GBM) is a highly aggressive brain cancer with limited therapeutic options. While efforts to identify genes responsible for GBM have revealed mutations and aberrant gene expression associated with distinct types of GBM, patients with GBM are often diagnosed and classified based on MRI features. Therefore, we seek to identify molecular representatives in parallel with MRI classification for group I and group II primary GBM associated with the subventricular zone (SVZ). As group I and II GBM contain stem-like signature, we compared gene expression profiles between these 2 groups of primary GBM and endogenous neural stem progenitor cells to reveal dysregulation of cell cycle, chromatin status, cellular morphogenesis, and signaling pathways in these 2 types of MRI-classified GBM. In the absence of IDH mutation, several genes associated with metabolism are differentially expressed in these subtypes of primary GBM, implicating metabolic reprogramming occurs in tumor microenvironment. Furthermore, histone lysine methyltransferase EZH2 was upregulated while histone lysine demethylases KDM2 and KDM4 were downregulated in both group I and II primary GBM. Lastly, we identified 9 common genes across large data sets of gene expression profiles among MRI-classified group I/II GBM, a large cohort of GBM subtypes from TCGA, and glioma stem cells by unsupervised clustering comparison. These commonly upregulated genes have known functions in cell cycle, centromere assembly, chromosome segregation, and mitotic progression. Our findings highlight altered expression of genes important in chromosome integrity across all GBM, suggesting a common mechanism of disrupted fidelity of chromosome structure in GBM.