Profiling Age-Related Epigenetic Markers of Stomach Adenocarcinoma in Young and Old Subjects
The purpose of our study is to identify epigenetic markers that are differently expressed in the stomach adenocarcinoma (STAD) condition. Based on data from The Cancer Genome Atlas (TCGA), we were able to detect an age-related difference in methylation patterns and changes in gene and miRNA expression levels in young (n = 14) and old (n = 70) STAD subjects. Our analysis identified 323 upregulated and 653 downregulated genes in old STAD subjects. We also found 76 miRNAs with age-related expression patterns and 113 differentially methylated genes (DMGs), respectively. Our further analysis revealed that significant upregulate...
Source: Cancer Informatics - April 20, 2015 Category: Cancer & Oncology Authors: Byoung-Chul KimHyoung Oh JeongDaeui ParkChul-Hong KimEun Kyeong LeeDae Hyun KimEunok ImNam Deuk KimSunghoon LeeByung Pal YuJong BhakHae Young Chung Source Type: research
BioMiner: Paving the Way for Personalized Medicine
Personalized medicine is promising a revolution for medicine and human biology in the 21st century. The scientific foundation for this revolution is accomplished by analyzing biological high-throughput data sets from genomics, transcriptomics, proteomics, and metabolomics. Currently, access to these data has been limited to either rather simple Web-based tools, which do not grant much insight or analysis by trained specialists, without firsthand involvement of the physician. Here, we present the novel Web-based tool “BioMiner,” which was developed within the scope of an international and interdisciplinary project (SYST...
Source: Cancer Informatics - April 20, 2015 Category: Cancer & Oncology Authors: Chris BauerKarol StecAlexander GlintschertKristina GrudenChristian SchichorMichal Or-GuilJoachim SelbigJohannes Schuchhardt Source Type: research
Catchment Area Analysis Using Bayesian Regression Modeling
A catchment area (CA) is the geographic area and population from which a cancer center draws patients. Defining a CA allows a cancer center to describe its primary patient population and assess how well it meets the needs of cancer patients within the CA. A CA definition is required for cancer centers applying for National Cancer Institute (NCI)-designated cancer center status. In this research, we constructed both diagnosis and diagnosis/ treatment CAs for the Massey Cancer Center (MCC) at Virginia Commonwealth University. We constructed diagnosis CAs for all cancers based on Virginia state cancer registry data and Bayesi...
Source: Cancer Informatics - April 19, 2015 Category: Cancer & Oncology Authors: Aobo WangDavid C. Wheeler Source Type: research
Computing Molecular Signatures as Optima of a Bi-Objective Function: Method and Application to Prediction in Oncogenomics
Conclusions: Defining molecular signatures as the optima of a bi-objective function that combined the signature size and the interclass distance was well founded and efficient for prediction in oncogenomics. The complexity of the computation was very low because the optimal signatures were the sets of genes in the ranking of their valuation. Software can be freely downloaded from http://gardeux-vincent.eu/DeltaRanking.php (Source: Cancer Informatics)
Source: Cancer Informatics - April 19, 2015 Category: Cancer & Oncology Authors: Vincent GardeuxRachid ChelouahMaria F. Barbosa WanderleyPatrick SiarryAntônio P. BragaFabien ReyalRoman RouzierLajos PusztaiRené Natowicz Source Type: research
Prioritization of Cancer-Related Genomic Variants by SNP Association Network
We have developed a general framework to construct an association network of single nucleotide polymorphisms (SNPs) (SNP association network, SAN) based on the functional interactions of genes located in the flanking regions of SNPs. SAN, which was constructed based on protein– protein interactions in the Human Protein Reference Database (HPRD), showed significantly enriched signals in both linkage disequilibrium (LD) and long-range chromatin interaction (Hi-C). We used this network to further develop two methods for predicting and prioritizing disease-associated genes from genome-wide association studies (GWASs). We fou...
Source: Cancer Informatics - April 1, 2015 Category: Cancer & Oncology Authors: Changning LiuZhenyu Xuan Source Type: research
Expression of Polarity Genes in Human Cancer
Polarity protein complexes are crucial for epithelial apical–basal polarity and directed cell migration. Since alterations of these processes are common in cancer, polarity proteins have been proposed to function as tumor suppressors or oncogenic promoters. Here, we review the current understanding of polarity protein functions in epithelial homeostasis, as well as tumor formation and progression. As most previous studies focused on the function of single polarity proteins in simplified model systems, we used a genomics approach to systematically examine and identify the expression profiles of polarity genes in human can...
Source: Cancer Informatics - March 30, 2015 Category: Cancer & Oncology Authors: Wan-Hsin LinYan W. AsmannPanos Z. Anastasiadis Source Type: research
HCsnip: An R Package for Semi-supervised Snipping of the Hierarchical Clustering Tree
Hierarchical clustering (HC) is one of the most frequently used methods in computational biology in the analysis of high-dimensional genomics data. Given a data set, HC outputs a binary tree leaves of which are the data points and internal nodes represent clusters of various sizes. Normally, a fixed-height cut on the HC tree is chosen, and each contiguous branch of data points below that height is considered as a separate cluster. However, the fixed-height branch cut may not be ideal in situations where one expects a complicated tree structure with nested clusters. Furthermore, due to lack of utilization of related backgro...
Source: Cancer Informatics - March 22, 2015 Category: Cancer & Oncology Authors: Askar ObulkasimMark A. van de Wiel Source Type: research
GeneMed: An Informatics Hub for the Coordination of Next-Generation Sequencing Studies that Support Precision Oncology Clinical Trials
We have developed an informatics system, GeneMed, for the National Cancer Institute (NCI) molecular profiling-based assignment of cancer therapy (MPACT) clinical trial (NCT01827384) being conducted in the National Institutes of Health (NIH) Clinical Center. This trial is one of the first to use a randomized design to examine whether assigning treatment based on genomic tumor screening can improve the rate and duration of response in patients with advanced solid tumors. An analytically validated next-generation sequencing (NGS) assay is applied to DNA from patients' tumors to identify mutations in a panel of genes that are ...
Source: Cancer Informatics - March 19, 2015 Category: Cancer & Oncology Authors: Yingdong ZhaoEric C. PolleyMing-Chung LiChih-Jian LihAlida PalmisanoDavid J. SimsLawrence V. RubinsteinBarbara A. ConleyAlice P. ChenP. Mickey WilliamsShivaani KummarJames H. DoroshowRichard M. Simon Source Type: research
Case-Based Retrieval Framework for Gene Expression Data
Conclusion: The designed case-based retrieval framework is an appropriate choice for retrieving previous patients who are similar to a new patient, on the basis of their gene expression data, for better diagnosis and treatment of childhood leukemia. Moreover, this framework can be applied to other gene expression data sets using some or all of its steps. (Source: Cancer Informatics)
Source: Cancer Informatics - March 19, 2015 Category: Cancer & Oncology Authors: Ali AnaissiMadhu GoyalDaniel R. CatchpooleAli BrayteePaul J. Kennedy Source Type: research
Modeling Discrete Survival Time Using Genomic Feature Data
In this study, we further extended the GMIFS method for ordinal response modeling using a complementary log-log link, which allows one to model discrete survival data. We applied our extension to a publicly available microarray gene expression dataset (GSE53733) with a discrete survival outcome. The dataset included 70 primary glioblastoma samples from patients of the German Glioma Network with long-, intermediate-, and short-term overall survival. We tested the performance of our method by examining the prediction accuracy of the fitted model. The method has been implemented as an addition to the ordinalgmifs package in t...
Source: Cancer Informatics - March 2, 2015 Category: Cancer & Oncology Authors: Kyle FerberKellie J. Archer Source Type: research
Introductory Editorial: Sequencing Platform Modeling and Analysis
No abstract supplied. (Source: Cancer Informatics)
Source: Cancer Informatics - March 2, 2015 Category: Cancer & Oncology Authors: Li-Xuan QinYen-Tsung Huang Source Type: research
What Tumor Dynamics Modeling Can Teach us About Exploiting the Stem-Cell View for Better Cancer Treatment
The cancer stem cell hypothesis is that in human solid cancers, only a small proportion of the cells, the cancer stem cells (CSCs), are self-renewing; the vast majority of the cancer cells are unable to sustain tumor growth indefinitely on their own. In recent years, discoveries have led to the concentration, if not isolation, of putative CSCs. The evidence has mounted that CSCs do exist and are important. This knowledge may promote better understanding of treatment resistance, create opportunities to test agents against CSCs, and open up promise for a fresh approach to cancer treatment. The first clinical trials of new an...
Source: Cancer Informatics - February 24, 2015 Category: Cancer & Oncology Authors: Roger S. Day Source Type: research
Mapping Splicing Quantitative Trait Loci in RNA-Seq
Conclusions: We have evaluated three statistical methods for the analysis of sQTLs in RNA-Seq. Results from our study will be instructive for researchers in selecting the appropriate statistical methods for sQTL analysis. (Source: Cancer Informatics)
Source: Cancer Informatics - February 16, 2015 Category: Cancer & Oncology Authors: Cheng JiaYu HuYichuan LiuMingyao Li Source Type: research
Toolbox for Mobile-Element Insertion Detection on Cancer Genomes
In this study, we report a new feature that enables TANGRAM to be used on alignments generated by any mainstream short-read mapper, making it accessible for many genomic users. To demonstrate its utility for cancer genome analysis, we have applied TANGRAM to the TCGA (The Cancer Genome Atlas) mutation calling benchmark 4 dataset. TANGRAM is fast, accurate, easy to use, and open source on https://github.com/jiantao/Tangram. (Source: Cancer Informatics)
Source: Cancer Informatics - February 12, 2015 Category: Cancer & Oncology Authors: Wan-Ping LeeJiantao Wuand Gabor T. Marth Source Type: research
Evaluating Methods for Modeling Epistasis Networks with Application to Head and Neck Cancer
Epistasis helps to explain how multiple single-nucleotide polymorphisms (SNPs) interact to cause disease. A variety of tools have been developed to detect epistasis. In this article, we explore the strengths and weaknesses of an information theory approach for detecting epistasis and compare it to the logistic regression approach through simulations. We consider several scenarios to simulate the involvement of SNPs in an epistasis network with respect to linkage disequilibrium patterns among them and the presence or absence of main and interaction effects. We conclude that the information theory approach more efficiently d...
Source: Cancer Informatics - February 10, 2015 Category: Cancer & Oncology Authors: Rajesh TalluriSanjay Shete Source Type: research
