canEvolve: A Web Portal for Integrative Oncogenomics

Abstract

Background & ObjectiveGenome-wide profiles of tumors obtained using functional genomics platforms are being deposited to the public repositories at an astronomical scale, as a result of focused efforts by individual laboratories and large projects such as the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium. Consequently, there is an urgent need for reliable tools that integrate and interpret these data in light of current knowledge and disseminate results to biomedical researchers in a user-friendly manner. We have built the canEvolve web portal to meet this need.ResultscanEvolve query functionalities are designed to fulfill most frequent analysis needs of cancer researchers with a view to generate novel hypotheses. canEvolve stores gene, microRNA (miRNA) and protein expression profiles, copy number alterations for multiple cancer types, and protein-protein interaction information. canEvolve allows querying of results of primary analysis, integrative analysis and network analysis of oncogenomics data. The querying for primary analysis includes differential gene and miRNA expression as well as changes in gene copy number measured with SNP microarrays. canEvolve provides results of integrative analysis of gene expression profiles with copy number alterations and with miRNA profiles as well as generalized integrative analysis using gene set enrichment analysis. The network analysis capability includes storage and visualization of gene co-expression, inferred gene regulatory networks and protein-protein interaction information. Finally, canEvolve provides correlations between gene expression and clinical outcomes in terms of univariate survival analysis.ConclusionAt present canEvolve provides different types of information extracted from 90 cancer genomics studies comprising of more than 10,000 patients. The presence of multiple data types, novel integrative analysis for identifying regulators of oncogenesis, network analysis and ability to query gene lists/pathways are distinctive features of canEvolve. canEvolve will facilitate integrative and meta-analysis of oncogenomics datasets.AvailabilityThe canEvolve web portal is available at http://www.canevolve.org/.

Heteroclitic XBP1 peptides evoke tumor-specific memory cytotoxic T lymphocytes against breast cancer, colon cancer, and pancreatic cancer cells

“…XBP1-CTL (n D 3) induced CD107a degranulation and IFNg production in response to each heteroclitic XBP1 peptide. These functional immune responses were higher than those against K562-A*0201 cells alone or the cells presenting irrelevant IMP [58][59][60][61][62][63][64][65][66] peptide. Importantly, XBP1-CTL recognized and responded to both native and heteroclictic XBP1 unspliced and native XBP1 spliced peptides as seen by comparable levels of CD107a degranulation (6-8%; Fig.…”

“…HLA-A2-specific native XBP1 [184][185][186][187][188][189][190][191][192] (NISPWILAV), native XBP1 SP 367-375 (ELFPQLISV), heteroclitic XBP1 [184][185][186][187][188][189][190][191][192] (YISPWILAV), heteroclitic XBP1 SP 367-375 (YLFPQ-LISV), and influenza virus matrix protein [58][59][60][61][62][63][64][65][66] (IMP [58][59][60][61][62][63][64][65][66] : GILGFVFTL) peptides were synthesized by standard fmoc (9-fluorenylmethyl-oxycarbonyl) chemistry, purified to > 95% using reverse-phase chromatography, and validated by mass-spectrometry for molecular weight (Biosynthesis). Lyophilized peptides were dissolved in DMSO (Sigma), diluted in AIM-V medium (Gibco-Life Technologies), and stored at ¡140 C.…”

“…Expression analysis of the XBP1 gene was performed using canEvolve (www.canevolve.org) 65 and Oncomine (www.onco mine.org) 66 databases. The Oncomine database covers two subtypes for colon adenocarcinoma and six subtypes of breast cancer, as well as the appropriate control sample data.…”

“…A differential analysis in Oncomine was used to compare expression in cancer versus healthy donors, with the student's t-test to calculate p values. 65 The canEvolve database uses linear models to calculate differential gene expression between groups and calculates the p values for given dataset. Phenotypic analysis of XBP1-CTL and evaluation of critical T cell markers XBP1-CTL were evaluated for the frequency of CD3 C CD8 C T cells and expression levels (% positive cells, mean fluorescence intensity (MFI)) of critical T cell surface markers including CD45RO, CCR7, CD38, CD40L, CD69, 41BB, ICOS, and TCRab.…”

Scan_Tcga Tools for Integrated Epigenomic and Transcriptomic Analysis of Tumor Subgroups

“…However, tools for analyzing epigenomic and transcriptomic level information are very limited. Currently, a small number of web-based tools (such as cBio [11,12], Wanderer [13], canEvolve [14] Web-TCGA [15] and TCGA compass [16] are available to access TCGA data for further analysis. However, these tools have several limitations with regard to flexible and systematic analysis of epigenomic data.…”