hSAGEing: An Improved SAGE-Based Software for Identification of Human Tissue-Specific or Common Tumor Markers and Suppressors

SAGE (serial analysis of gene expression) is a powerful method of analyzing gene expression for the entire transcriptome. There are currently many well-developed SAGE tools. However, the cross-comparison of different tissues is seldom addressed, thus limiting the identification of common- and tissue-specific tumor markers.To improve the SAGE mining methods, we propose a novel function for cross-tissue comparison of SAGE data by combining the mathematical set theory and logic with a unique “multi-pool method” that analyzes multiple pools of pair-wise case controls individually. When all the settings are in “inclusion”, the common SAGE tag sequences are mined. When one tissue type is in “inclusion” and the other types of tissues are not in “inclusion”, the selected tissue-specific SAGE tag sequences are generated. They are displayed in tags-per-million (TPM) and fold values, as well as visually displayed in four kinds of scales in a color gradient pattern. In the fold visualization display, the top scores of the SAGE tag sequences are provided, along with cluster plots. A user-defined matrix file is designed for cross-tissue comparison by selecting libraries from publically available databases or user-defined libraries

Integrative DNA methylation and gene expression analysis in high-grade soft tissue sarcomas

BACKGROUND: High-grade soft tissue sarcomas are a heterogeneous, complex group of aggressive malignant tumors showing mesenchymal differentiation. Recently, soft tissue sarcomas have increasingly been classified on the basis of underlying genetic alterations; however, the role of aberrant DNA methylation in these tumors is not well understood and, consequently, the usefulness of methylation-based classification is unclear. RESULTS: We used the Infinium HumanMethylation27 platform to profile DNA methylation in 80 primary, untreated high-grade soft tissue sarcomas, representing eight relevant subtypes, two non-neoplastic fat samples and 14 representative sarcoma cell lines. The primary samples were partitioned into seven stable clusters. A classification algorithm identified 216 CpG sites, mapping to 246 genes, showing different degrees of DNA methylation between these seven groups. The differences between the clusters were best represented by a set of eight CpG sites located in the genes SPEG, NNAT, FBLN2, PYROXD2, ZNF217, COL14A1, DMRT2 and CDKN2A. By integrating DNA methylation and mRNA expression data, we identified 27 genes showing negative and three genes showing positive correlation. Compared with non-neoplastic fat, NNAT showed DNA hypomethylation and inverse gene expression in myxoid liposarcomas, and DNA hypermethylation and inverse gene expression in dedifferentiated and pleomorphic liposarcomas. Recovery of NNAT in a hypermethylated myxoid liposarcoma cell line decreased cell migration and viability. CONCLUSIONS: Our analysis represents the first comprehensive integration of DNA methylation and transcriptional data in primary high-grade soft tissue sarcomas. We propose novel biomarkers and genes relevant for pathogenesis, including NNAT as a potential tumor suppressor in myxoid liposarcomas

An expression module of WIPF1-coexpressed genes identifies patients with favorable prognosis in three tumor types

Wiskott–Aldrich syndrome (WAS) predisposes patients to leukemia and lymphoma. WAS is caused by mutations in the protein WASP which impair its interaction with the WIPF1 protein. Here, we aim to identify a module of WIPF1-coexpressed genes and to assess its use as a prognostic signature for colorectal cancer, glioma, and breast cancer patients. Two public colorectal cancer microarray data sets were used for discovery and validation of the WIPF1 co-expression module. Based on expression of the WIPF1 signature, we classified more than 400 additional tumors with microarray data from our own experiments or from publicly available data sets according to their WIPF1 signature expression. This allowed us to separate patient populations for colorectal cancers, breast cancers, and gliomas for which clinical characteristics like survival times and times to relapse were analyzed. Groups of colorectal cancer, breast cancer, and glioma patients with low expression of the WIPF1 co-expression module generally had a favorable prognosis. In addition, the majority of WIPF1 signature genes are individually correlated with disease outcome in different studies. Literature gene network analysis revealed that among WIPF1 co-expressed genes known direct transcriptional targets of c-myc, ESR1 and p53 are enriched. The mean expression profile of WIPF1 signature genes is correlated with the profile of a proliferation signature. The WIPF1 signature is the first microarray-based prognostic expression signature primarily developed for colorectal cancer that is instrumental in other tumor types: low expression of the WIPF1 module is associated with better prognosis

Thymosin β10 Expression Driven by the Human TERT Promoter Induces Ovarian Cancer-Specific Apoptosis through ROS Production

Thymosin β10 (Tβ10) regulates actin dynamics as a cytoplasm G-actin sequestering protein. Previously, we have shown that Tβ10 diminishes tumor growth, angiogenesis, and proliferation by disrupting actin and by inhibiting Ras. However, little is known about its mechanism of action and biological function. In the present study, we establish a new gene therapy model using a genetically modified adenovirus, referred to as Ad.TERT.Tβ10, that can overexpress the Tβ10 gene in cancer cells. This was accomplished by replacing the native Tβ10 gene promoter with the human TERT promoter in Ad.TERT.Tβ10. We investigated the cancer suppression activity of Tβ10 and found that Ad.TERT.Tβ10 strikingly induced cancer-specific expression of Tβ10 as well as apoptosis in a co-culture model of human primary ovarian cancer cells and normal fibroblasts. Additionally, Ad.TERT.Tβ10 decreased mitochondrial membrane potential and increased reactive oxygen species (ROS) production. These effects were amplified by co-treatment with anticancer drugs, such as paclitaxel and cisplatin. These findings indicate that the rise in ROS production due to actin disruption by Tβ10 overexpression increases apoptosis of human ovarian cancer cells. Indeed, the cancer-specific overexpression of Tβ10 by Ad.TERT.Tβ10 could be a valuable anti-cancer therapeutic for the treatment of ovarian cancer without toxicity to normal cells

ADAM9 is highly expressed in renal cell cancer and is associated with tumour progression

<p>Abstract</p> <p>Background</p> <p><b>A D</b>isintegrin <b>A</b>nd <b>M</b>etalloprotease (ADAM) 9 has been implicated in tumour progression of various solid tumours, however, little is known about its role in renal cell carcinoma. We evaluated the expression of ADAM9 on protein and transcript level in a clinico-pathologically characterized renal cell cancer cohort.</p> <p>Methods</p> <p>108 renal cancer cases were immunostained for ADAM9 on a tissue-micro-array. For 30 additional cases, ADAM9 mRNA of microdissected tumour and normal tissue was analyzed via quantitative RT-PCR. SPSS 14.0 was used to apply crosstables (Fisher's exact test and χ²-test), correlations and univariate as well as multivariate survival analyses.</p> <p>Results</p> <p>ADAM9 was significantly up-regulated in renal cancer in comparison to the adjacent normal tissue on mRNA level. On protein level, ADAM9 was significantly associated with higher tumour grade, positive nodal status and distant metastasis. Furthermore, ADAM9 protein expression was significantly associated with shortened patient survival in the univariate analysis.</p> <p>Conclusion</p> <p>ADAM9 is strongly expressed in a large proportion of renal cell cancers, concordant with findings in other tumour entities. Additionally, ADAM9 expression is significantly associated with markers of unfavourable prognosis. Whether the demonstrated prognostic value of ADAM9 is independent from other tumour parameters will have to be verified in larger study cohorts.</p