Regulation of Epithelial-Mesenchymal Transition in Breast Cancer Cells by Cell Contact and Adhesion
Epithelial-mesenchymal transition (EMT) is a physiological program that is activated during cancer cell invasion and metastasis. We show here that EMT-related processes are linked to a broad and conserved program of transcriptional alterations that are influenced by cell contact and adhesion. Using cultured human breast cancer and mouse mammary epithelial cells, we find that reduced cell density, conditions under which cell contact is reduced, leads to reduced expression of genes associated with mammary epithelial cell differentiation and increased expression of genes associated with breast cancer. We further find that tre...
Source: Cancer Informatics - February 9, 2015 Category: Cancer & Oncology Authors: Magdalena A. CichonCeleste M. Nelsonand Derek C. Radisky Source Type: research
An Improved Version of Logistic Bayesian LASSO for Detecting Rare Haplotype-Environment Interactions with Application to Lung Cancer
The importance of haplotype association and gene–environment interactions (GxE) in the context of rare variants has been underlined in voluminous literature. Recently, a software based on logistic Bayesian LASSO (LBL) was proposed for detecting GxE, where G is a rare (or common) haplotype variant (rHTV)–it is called LBL-GxE. However, it required relatively long computation time and could handle only one environmental covariate with two levels. Here we propose an improved version of LBL-GxE, which is not only computationally faster but can also handle multiple covariates, each with multiple levels. We also discuss detai...
Source: Cancer Informatics - February 9, 2015 Category: Cancer & Oncology Authors: Yuan ZhangSwati Biswas Source Type: research
sfDM: Open-Source Software for Temporal Analysis and Visualization of Brain Tumor Diffusion MR Using Serial Functional Diffusion Mapping
We present the general workflow of the pipeline, along with a typical use case for the software. sfDM is written in Python and is freely available as an open-source package under the Berkley Software Distribution (BSD) license to promote transparency and reproducibility. (Source: Cancer Informatics)
Source: Cancer Informatics - February 1, 2015 Category: Cancer & Oncology Authors: Rafael CeschinAshok PanigrahyVanathi Gopalakrishnan Source Type: research
Nonparametric Tests for Differential Histone Enrichment with ChIP-Seq Data
Chromatin immunoprecipitation sequencing (ChIP-seq) is a powerful method for analyzing protein interactions with DNA. It can be applied to identify the binding sites of transcription factors (TFs) and genomic landscape of histone modification marks (HMs). Previous research has largely focused on developing peak-calling procedures to detect the binding sites for TFs. However, these procedures may fail when applied to ChIP-seq data of HMs, which have diffuse signals and multiple local peaks. In addition, it is important to identify genes with differential histone enrichment regions between two experimental conditions, such a...
Source: Cancer Informatics - January 27, 2015 Category: Cancer & Oncology Authors: Qian WuKyoung-Jae WonHongzhe Li Source Type: research
Mitochondrial Variations in Non-Small Cell Lung Cancer (NSCLC) Survival
Mutations in the mtDNA genome have long been suspected to play an important role in cancer. Although most cancer cells harbor mtDNA mutations, the question of whether such mutations are associated with clinical prognosis of lung cancer remains unclear. We resequenced the entire mitochondrial genomes of tumor tissue from a population of 250 Korean patients with non-small cell lung cancer (NSCLC). Our analysis revealed that the haplogroup (D/D4) was associated with worse overall survival (OS) of early-stage NSCLC adjusted hazard ratio (AHR), 1.95; 95% CI, 1.14–3.33; Ptrend = 0.03. By comparing the mtDNA variations between ...
Source: Cancer Informatics - January 27, 2015 Category: Cancer & Oncology Authors: Zhaoxi WangSojung ChoiJinseon LeeYen-Tsung HuangFeng ChenYang ZhaoXihong LinDonna NeubergJhingook KimDavid C. Christiani Source Type: research
Prognostic Gene Signature Identification Using Causal Structure Learning: Applications in Kidney Cancer
Identification of molecular-based signatures is one of the critical steps toward finding therapeutic targets in cancer. In this paper, we propose methods to discover prognostic gene signatures under a causal structure learning framework across the whole genome. The causal structures are represented by directed acyclic graphs (DAGs), wherein we construct gene-specific network modules that constitute a gene and its corresponding regulators. The modules are then subsequently used to correlate with survival times, thus, allowing for a network-oriented approach to gene selection to adjust for potential confounders, as opposed t...
Source: Cancer Informatics - January 27, 2015 Category: Cancer & Oncology Authors: Min Jin HaVeerabhadran BaladandayuthapaniKim-Anh Do Source Type: research
Network-Constrained Group Lasso for High-Dimensional Multinomial Classification with Application to Cancer Subtype Prediction
Classic multinomial logit model, commonly used in multiclass regression problem, is restricted to few predictors and does not take into account the relationship among variables. It has limited use for genomic data, where the number of genomic features far exceeds the sample size. Genomic features such as gene expressions are usually related by an underlying biological network. Efficient use of the network information is important to improve classification performance as well as the biological interpretability. We proposed a multinomial logit model that is capable of addressing both the high dimensionality of predictors and...
Source: Cancer Informatics - January 12, 2015 Category: Cancer & Oncology Authors: Xinyu TianXuefeng Wangand Jun Chen Source Type: research
Detection of Pancreatic Cancer Biomarkers Using Mass Spectrometry
Background: Pancreatic cancer is the fourth leading cause of cancer-related deaths. Therefore, in order to improve survival rates, the development of biomarkers for early diagnosis is crucial. Recently, diabetes has been associated with an increased risk of pancreatic cancer. The aims of this study were to search for novel serum biomarkers that could be used for early diagnosis of pancreatic cancer and to identify whether diabetes was a risk factor for this disease.
Methods: Blood samples were collected from 25 patients with diabetes (control) and 93 patients with pancreatic cancer (including 53 patients with diabetes), an...
Source: Cancer Informatics - January 6, 2015 Category: Cancer & Oncology Authors: Kiyoun KimSoohyun AhnJohan LimByong Chul YooJin-Hyeok HwangWoncheol Jang Source Type: research
Web Tool for Estimating the Cancer Hazard Rates in Aging
A computational approach for estimating the overall, population, and individual cancer hazard rates was developed. The population rates characterize a risk of getting cancer of a specific site/type, occurring within an age-specific group of individuals from a specified population during a distinct time period. The individual rates characterize an analogous risk but only for the individuals susceptible to cancer. The approach uses a novel regularization and anchoring technique to solve an identifiability problem that occurs while determining the age, period, and cohort (APC) effects. These effects are used to estimate the o...
Source: Cancer Informatics - December 17, 2014 Category: Cancer & Oncology Authors: Tengiz MdzinarishviliAlexander ShermanOleg Shatsand Simon Sherman Source Type: research
Statistical Issues in the Design and Analysis of nCounter Projects
Numerous statistical methods have been published for designing and analyzing microarray projects. Traditional genome-wide microarray platforms (such as Affymetrix, Illumina, and DASL) measure the expression level of tens of thousands genes. Since the sets of genes included in these array chips are selected by the manufacturers, the number of genes associated with a specific disease outcome is limited and a large portion of the genes are not associated. nCounter is a new technology by NanoString to measure the expression of a selected number (up to 800) of genes. The list of genes for nCounter chips can be selected by custo...
Source: Cancer Informatics - December 14, 2014 Category: Cancer & Oncology Authors: Sin-Ho JungInsuk Sohn Source Type: research
Bayesian Hierarchical Models for Protein Networks in Single-Cell Mass Cytometry
We propose a class of hierarchical models to investigate the protein functional network of cellular markers. We consider a novel data set from single-cell proteomics. The data are generated from single-cell mass cytometry experiments, in which protein expression is measured within an individual cell for multiple markers. Tens of thousands of cells are measured serving as biological replicates. Applying the Bayesian models, we report protein functional networks under different experimental conditions and the differences between the networks, ie, differential networks. We also present the differential network in a novel fash...
Source: Cancer Informatics - December 10, 2014 Category: Cancer & Oncology Authors: Riten MitraPeter MüllerPeng QiuYuan Ji Source Type: research
ordinalgmifs: An R Package for Ordinal Regression in High-dimensional Data Settings
High-throughput genomic assays are performed using tissue samples with the goal of classifying the samples as normal < pre-malignant < malignant or by stage of cancer using a small set of molecular features. In such cases, molecular features monotonically associated with the ordinal response may be important to disease development; that is, an increase in the phenotypic level (stage of cancer) may be mechanistically linked through a monotonic association with gene expression or methylation levels. Though traditional ordinal response modeling methods exist, they assume independence among the predictor variables and require ...
Source: Cancer Informatics - December 10, 2014 Category: Cancer & Oncology Authors: Kellie J. ArcherJiayi HouQing ZhouKyle FerberJohn G. LayneAmanda E. Gentry Source Type: research
CARAT-GxG: CUDA-Accelerated Regression Analysis Toolkit for Large-Scale Gene–Gene Interaction with GPU Computing System
In genome-wide association studies (GWAS), regression analysis has been most commonly used to establish an association between a phenotype and genetic variants, such as single nucleotide polymorphism (SNP). However, most applications of regression analysis have been restricted to the investigation of single marker because of the large computational burden. Thus, there have been limited applications of regression analysis to multiple SNPs, including gene–gene interaction (GGI) in large-scale GWAS data. In order to overcome this limitation, we propose CARAT-GxG, a GPU computing system-oriented toolkit, for performing regre...
Source: Cancer Informatics - December 9, 2014 Category: Cancer & Oncology Authors: Sungyoung LeeMin-Seok KwonTaesung Park Source Type: research
Stratified Pathway Analysis to Identify Gene Sets Associated with Oral Contraceptive Use and Breast Cancer
Cancer biomarker discovery can facilitate drug development, improve staging of patients, and predict patient prognosis. Because cancer is the result of many interacting genes, analysis based on a set of genes with related biological functions or pathways may be more informative than single gene-based analysis for cancer biomarker discovery. The relevant pathways thus identified may help characterize different aspects of molecular phenotypes related to the tumor. Although it is well known that cancer patients may respond to the same treatment differently because of clinical variables and variation of molecular phenotypes, t...
Source: Cancer Informatics - December 9, 2014 Category: Cancer & Oncology Authors: Herbert PangHongyu Zhao Source Type: research
Growth Rate Analysis and Efficient Experimental Design for Tumor Xenograft Studies
Human tumor xenograft studies are the primary means to evaluate the biological activity of anticancer agents in late-stage preclinical drug discovery. The variability in the growth rate of human tumors established in mice and the small sample sizes make rigorous statistical analysis critical. The most commonly used summary of antitumor activity for these studies is the T/C ratio. However, alternative methods based on growth rate modeling can be used. Here, we describe a summary metric called the rate-based T/C, derived by fitting each animal’s tumor growth to a simple exponential model. The rate-based T/C uses all of the...
Source: Cancer Informatics - December 9, 2014 Category: Cancer & Oncology Authors: Gregory HatherRay LiuSyamala BandiJerome MettetalMark ManfrediWen-Chyi ShyuJill DonelanArijit Chakravarty Source Type: research
