TMAinspiration: Decode Interdependencies in Multifactorial Tissue Microarray Data
There are no satisfying tools in tissue microarray (TMA) data analysis up to now to analyze the cooperative behavior of all measured markers in a multifactorial TMA approach. The developed tool TMAinspiration is not only offering an analysis option to close this gap but also offering an ecosystem consisting of quality control concepts and supporting scripts to make this approach a platform for informed practice and further research. The TMAinspiration method is specifically focusing on the demands of the TMA analysis by controlling errors and noise by a generalized regression scheme while at the same time avoiding to intro...
Source: Cancer Informatics - June 28, 2016 Category: Cancer & Oncology Authors: Florian BoeckerHorst BuergerNikhil V. MallelaEberhard Korsching Source Type: research
An Integrated Approach for RNA-seq Data Normalization
Conclusions: Using information from DNA copy number, integrated approach is successful in reducing noises due to both biological and nonbiological causes in RNA-seq data, thus increasing the accuracy of gene profiling. (Source: Cancer Informatics)
Source: Cancer Informatics - June 26, 2016 Category: Cancer & Oncology Authors: Shengping YangDonald E. MercanteKun ZhangZhide Fang Source Type: research
The Melanoma MAICare Framework: A Microsimulation Model for the Assessment of Individualized Cancer Care
We describe the framework as the required input and the model output. Furthermore, we illustrate model calibration using registry data and data from the literature. (Source: Cancer Informatics)
Source: Cancer Informatics - June 14, 2016 Category: Cancer & Oncology Authors: Elisabeth van der MeijdeAlfons J. M. van den EertweghSabine C. LinnGerrit A. MeijerRemond J. A. Fijnemanand Veerle M. H. Coupé Source Type: research
multiClust: An R-package for Identifying Biologically Relevant Clusters in Cancer Transcriptome Profiles
Clustering is carried out to identify patterns in transcriptomics profiles to determine clinically relevant subgroups of patients. Feature (gene) selection is a critical and an integral part of the process. Currently, there are many feature selection and clustering methods to identify the relevant genes and perform clustering of samples. However, choosing an appropriate methodology is difficult. In addition, extensive feature selection methods have not been supported by the available packages. Hence, we developed an integrative R-package called multiClust that allows researchers to experiment with the choice of combination...
Source: Cancer Informatics - June 11, 2016 Category: Cancer & Oncology Authors: Nathan LawlorAlec FabbriPeiyong GuanJoshy GeorgeR. Krishna Murthy Karuturi Source Type: research
A Novel Approach to Predict Core Residues on Cancer-Related DNA-Binding Domains
In this study, we propose a computational method to predict and locate core residues on DNA-binding domains. In particular, we have selected the cancer-related DNA-binding domains for in-depth studies, namely, winged Helix Turn Helix family, homeodomain family, and basic Helix-Loop-Helix family. The results demonstrate that the proposed method can predict the core residues involved in protein–DNA interactions, as verified by the existing structural data. Given its good performance, various aspects of the method are discussed and explored: for instance, different uses of prediction algorithm, different protein domains, an...
Source: Cancer Informatics - June 1, 2016 Category: Cancer & Oncology Authors: Ka-Chun Wong Source Type: research
Rational Design of Peptide Vaccines Against Multiple Types of Human Papillomavirus
Human papillomavirus (HPV) occurs in many types, some of which cause cervical, genital, and other cancers. While vaccination is available against the major cancer-causing HPV types, many others are not covered by these preventive measures. Herein, we present a bioinformatics study for the designing of multivalent peptide vaccines against multiple HPV types as an alternative strategy to the virus-like particle vaccines being used now. Our technique of rational design of peptide vaccines is expected to ensure stability of the vaccine against many cycles of mutational changes, elicit immune response, and negate autoimmune pos...
Source: Cancer Informatics - May 31, 2016 Category: Cancer & Oncology Authors: Sumanta DeyAntara DeAshesh Nandy Source Type: research
Bioinformatic Studies to Predict MicroRNAs with the Potential of Uncoupling RECK Expression from Epithelial–Mesenchymal Transition in Cancer Cells
RECK is downregulated in many tumors, and forced RECK expression in tumor cells often results in suppression of malignant phenotypes. Recent findings suggest that RECK is upregulated after epithelial-mesenchymal transition (EMT) in normal epithelium-derived cells but not in cancer cells. Since several microRNAs (miRs) are known to target RECK mRNA, we hypothesized that certain miR(s) may be involved in this suppression of RECK upregulation after EMT in cancer cells. To test this hypothesis, we used three approaches: (1) text mining to find miRs relevant to EMT in cancer cells, (2) predicting miR targets using four algorith...
Source: Cancer Informatics - May 18, 2016 Category: Cancer & Oncology Authors: Zhipeng WangRyusuke MurakamiKanako YukiYoko YoshidaMakoto Noda Source Type: research
Selecting Reliable mRNA Expression Measurements Across Platforms Improves Downstream Analysis
In this study, we propose a statistical framework for selecting reliable measurements between platforms by modeling the correlations of mRNA expression levels using a beta-mixture model. The model-based selection provides an effective and objective way to separate good probes from probes with low quality, thereby improving the efficiency and accuracy of the analysis. The proposed method can be used to compare two microarray technologies or microarray and RNA sequencing measurements. We tested the approach in two matched profiling data sets, using microarray gene expression measurements from the same samples profiled on bot...
Source: Cancer Informatics - May 9, 2016 Category: Cancer & Oncology Authors: Pan TongLixia DiaoLi ShenLerong LiJohn Victor HeymachLuc GirardJohn D. MinnaKevin R. CoombesLauren Averett ByersJing Wang Source Type: research
Thyroid Cancer and Tumor Collaborative Registry (TCCR)
A multicenter, web-based Thyroid Cancer and Tumor Collaborative Registry (TCCR, http://tccr.unmc.edu) allows for the collection and management of various data on thyroid cancer (TC) and thyroid nodule (TN) patients. The TCCR is coupled with OpenSpecimen, an open-source biobank management system, to annotate biospecimens obtained from the TCCR subjects. The demographic, lifestyle, physical activity, dietary habits, family history, medical history, and quality of life data are provided and may be entered into the registry by subjects. Information on diagnosis, treatment, and outcome is entered by the clinical personnel. The ...
Source: Cancer Informatics - May 2, 2016 Category: Cancer & Oncology Authors: Oleg ShatsWhitney GoldnerJianmin FengAlexander ShermanRussell B. SmithSimon Sherman Source Type: research
Immunomediated Pan-cancer Regulation Networks are Dominant Fingerprints After Treatment of Cell Lines with Demethylation
Pan-cancer studies are particularly relevant not only for addressing the complexity of the inherently observed heterogeneity but also for identifying clinically relevant features that may be common to the cancer types. Immune system regulations usually reveal synergistic modulation with other cancer mechanisms and in combination provide insights on possible advances in cancer immunotherapies. Network inference is a powerful approach to decipher pan-cancer systems dynamics. The methodology proposed in this study elucidates the impacts of epigenetic treatment on the drivers of complex pan-cancer regulation circuits involving...
Source: Cancer Informatics - April 26, 2016 Category: Cancer & Oncology Authors: Mariama El BaroudiCaterina CintiEnrico Capobianco Source Type: research
RefCNV: Identification of Gene-Based Copy Number Variants Using Whole Exome Sequencing
With rapid advances in DNA sequencing technologies, whole exome sequencing (WES) has become a popular approach for detecting somatic mutations in oncology studies. The initial intent of WES was to characterize single nucleotide variants, but it was observed that the number of sequencing reads that mapped to a genomic region correlated with the DNA copy number variants (CNVs). We propose a method RefCNV that uses a reference set to estimate the distribution of the coverage for each exon. The construction of the reference set includes an evaluation of the sources of variability in the coverage distribution. We observed that ...
Source: Cancer Informatics - April 26, 2016 Category: Cancer & Oncology Authors: Lun-Ching ChangBiswajit DasChih-Jian LihHan SiCorinne E. CamalierPaul M. McGregor IIIEric Polley Source Type: research
Unraveling the Deleterious Effects of Cancer-Driven STK11 Mutants Through Conformational Sampling Approach
In this study, we focused on identifying those driver mutations through analyzing structural variations of mutants, viz., D194N, E199K, L160P, and Y49D. Native and the mutants were analyzed to determine their geometrical deviations such as root-mean-square deviation, root-mean-square fluctuation, radius of gyration, potential energy, and solvent-accessible surface area using conformational sampling technique. Additionally, the global minimized structure of native and mutants was further analyzed to compute their intramolecular interactions and distribution of secondary structure. Subsequently, simulated thermal denaturatio...
Source: Cancer Informatics - April 3, 2016 Category: Cancer & Oncology Authors: Merlin LopusD. Meshach PaulR. Rajasekaran Source Type: research
Integrative Analysis of mRNA, microRNA, and Protein Correlates of Relative Cerebral Blood Volume Values in GBM Reveals the Role for Modulators of Angiogenesis and Tumor Proliferation
This study aims to provide a comprehensive radiogenomic and radioproteomic characterization of the hemodynamic phenotype of GBM using publicly available imaging and genomic data from the Cancer Genome Atlas GBM cohort. Based on this analysis, we identified pathways associated with angiogenesis and tumor proliferation underlying this hemodynamic parameter in GBM. (Source: Cancer Informatics)
Source: Cancer Informatics - March 28, 2016 Category: Cancer & Oncology Authors: Arvind RaoGaniraju ManyamGanesh RaoRajan Jain Source Type: research
Detection of Productively Rearranged TcR-α V–J Sequences in TCGA Exome Files: Implications for Tumor Immunoscoring and Recovery of Antitumor T-cells
Tumor immunoscoring is rapidly becoming a universal parameter of prognosis, and T-cells isolated from tumor masses are used for ex vivo amplification and readministration to patients to facilitate an antitumor immune response. We recently exploited the cancer genome atlas (TCGA) RNASeq data to assess T-cell receptor (TcR) expression and, in particular, discovered strong correlations between major histocompatibility class II (MHCII) and TcR-α constant region expression levels. In this article, we describe the results of searching TCGA exome files for TcR-α V-regions, followed by searching the V-region datasets for TcR-α-...
Source: Cancer Informatics - February 25, 2016 Category: Cancer & Oncology Authors: Thomas R. GillMohammad D. SamyShanitra N. ButlerJames A. MauroWade J. SextonGeorge Blanck Source Type: research
Detection of Productively Rearranged TcR- & alpha; V & ndash;J Sequences in TCGA Exome Files: Implications for Tumor Immunoscoring and Recovery of Antitumor T-cells
Tumor immunoscoring is rapidly becoming a universal parameter of prognosis, and T-cells isolated from tumor masses are used for ex vivo amplification and readministration to patients to facilitate an antitumor immune response. We recently exploited the cancer genome atlas (TCGA) RNASeq data to assess T-cell receptor (TcR) expression and, in particular, discovered strong correlations between major histocompatibility class II (MHCII) and TcR-α constant region expression levels. In this article, we describe the results of searching TCGA exome files for TcR-α V-regions, followed by searching the V-region datasets for TcR-α-...
Source: Cancer Informatics - February 24, 2016 Category: Cancer & Oncology Authors: Thomas R. Gill Mohammad D. Samy Shanitra N. Butler James A. Mauro Wade J. Sexton George Blanck Source Type: research
