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Cancer Informatics

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https://www.readbyqxmd.com/read/28932104/gene-set-reduction-for-analysis-of-major-and-minor-gleason-scores-based-on-differential-gene-set-expressions-and-biological-pathways-in-prostate-cancer
#1
Irina Dinu, Surya Poudel, Saumyadipta Pyne
The Gleason score (GS) plays an important role in prostate cancer detection and treatment. It is calculated based on a sum between its major and minor components, each ranging from 1 to 5, assigned after examination of sample cells taken from each side of the prostate gland during biopsy. A total GS of at least 7 is associated with more aggressive prostate cancer. However, it is still unclear how prostate cancer outcomes differ for various distributions of GS between its major and minor components. This article applies Significance Analysis of Microarray for Gene-Set Reduction to a real microarray study of patients with prostate cancer and identifies 13 core genes differentially expressed between patients with a major GS of 3 and a minor GS of 4, or (3,4), vs patients with a combination of (4,3), starting from a less aggressive GS combination of (3,3), and moving toward a more aggressive one of (4,4) via gray areas of (3,4) and (4,3)...
2017: Cancer Informatics
https://www.readbyqxmd.com/read/28874883/xsyn-a-software-tool-for-identifying-sophisticated-3-way-interactions-from-cancer-expression-data
#2
Baishali Bandyopadhyay, Veda Chanda, Yupeng Wang
BACKGROUND: Constructing gene co-expression networks from cancer expression data is important for investigating the genetic mechanisms underlying cancer. However, correlation coefficients or linear regression models are not able to model sophisticated relationships among gene expression profiles. Here, we address the 3-way interaction that 2 genes' expression levels are clustered in different space locations under the control of a third gene's expression levels. RESULTS: We present xSyn, a software tool for identifying such 3-way interactions from cancer gene expression data based on an optimization procedure involving the usage of UPGMA (Unweighted Pair Group Method with Arithmetic Mean) and synergy...
2017: Cancer Informatics
https://www.readbyqxmd.com/read/28835735/adaptive-multiview-nonnegative-matrix-factorization-algorithm-for-integration-of-multimodal-biomedical-data
#3
Bisakha Ray, Wenke Liu, David Fenyö
The amounts and types of available multimodal tumor data are rapidly increasing, and their integration is critical for fully understanding the underlying cancer biology and personalizing treatment. However, the development of methods for effectively integrating multimodal data in a principled manner is lagging behind our ability to generate the data. In this article, we introduce an extension to a multiview nonnegative matrix factorization algorithm (NNMF) for dimensionality reduction and integration of heterogeneous data types and compare the predictive modeling performance of the method on unimodal and multimodal data...
2017: Cancer Informatics
https://www.readbyqxmd.com/read/28804242/immuno-oncology-integrative-networks-elucidating-the-influences-of-osteosarcoma-phenotypes
#4
REVIEW
Ankush Sharma, Enrico Capobianco
In vivo and in vitro functional phenotyping characterization was recently obtained with reference to an experimental pan-cancer study of 22 osteosarcoma (OS) cell lines. Here, differentially expressed gene (DEG) profiles were recomputed from the publicly available data to conduct network inference on the immune system regulatory activity across the characterized OS phenotypes. Based on such DEG profiles, and for each phenotype that was analyzed, we obtained coexpression networks and bio-annotations for them...
2017: Cancer Informatics
https://www.readbyqxmd.com/read/28747816/prediction-with-dimension-reduction-of-multiple-molecular-data-sources-for-patient-survival
#5
Adam Kaplan, Eric F Lock
Predictive modeling from high-dimensional genomic data is often preceded by a dimension reduction step, such as principal component analysis (PCA). However, the application of PCA is not straightforward for multisource data, wherein multiple sources of 'omics data measure different but related biological components. In this article, we use recent advances in the dimension reduction of multisource data for predictive modeling. In particular, we apply exploratory results from Joint and Individual Variation Explained (JIVE), an extension of PCA for multisource data, for prediction of differing response types...
2017: Cancer Informatics
https://www.readbyqxmd.com/read/28690395/an-assessment-of-database-validated-microrna-target-genes-in-normal-colonic-mucosa-implications-for-pathway-analysis
#6
Martha L Slattery, Jennifer S Herrick, John R Stevens, Roger K Wolff, Lila E Mullany
BACKGROUND: Determination of functional pathways regulated by microRNAs (miRNAs), while an essential step in developing therapeutics, is challenging. Some miRNAs have been studied extensively; others have limited information. In this study, we focus on 254 miRNAs previously identified as being associated with colorectal cancer and their database-identified validated target genes. METHODS: We use RNA-Seq data to evaluate messenger RNA (mRNA) expression for 157 subjects who also had miRNA expression data...
2017: Cancer Informatics
https://www.readbyqxmd.com/read/28690394/a-software-application-for-mining-and-presenting-relevant-cancer-clinical-trials-per-cancer-mutation
#7
Lisa M Gandy, Jordan Gumm, Amanda L Blackford, Elana J Fertig, Luis A Diaz
ClinicalTrials.org is a popular portal which physicians use to find clinical trials for their patients. However, the current setup of ClinicalTrials.org makes it difficult for oncologists to locate clinical trials for patients based on mutational status. We present CTMine, a system that mines ClinicalTrials.org for clinical trials per cancer mutation and displays the trials in a user-friendly Web application. The system currently lists clinical trials for 6 common genes (ALK, BRAF, ERBB2, EGFR, KIT, and KRAS)...
2017: Cancer Informatics
https://www.readbyqxmd.com/read/28659712/the-model-based-study-of-the-effectiveness-of-reporting-lists-of-small-feature-sets-using-rna-seq-data
#8
Eunji Kim, Ivan Ivanov, Jianping Hua, Johanna W Lampe, Meredith Aj Hullar, Robert S Chapkin, Edward R Dougherty
Ranking feature sets for phenotype classification based on gene expression is a challenging issue in cancer bioinformatics. When the number of samples is small, all feature selection algorithms are known to be unreliable, producing significant error, and error estimators suffer from different degrees of imprecision. The problem is compounded by the fact that the accuracy of classification depends on the manner in which the phenomena are transformed into data by the measurement technology. Because next-generation sequencing technologies amount to a nonlinear transformation of the actual gene or RNA concentrations, they can potentially produce less discriminative data relative to the actual gene expression levels...
2017: Cancer Informatics
https://www.readbyqxmd.com/read/28634423/tumor-ras-gene-expression-levels-are-influenced-by-the-mutational-status-of-ras-genes-and-both-upstream-and-downstream-ras-pathway-genes
#9
Robert M Stephens, Ming Yi, Bailey Kessing, Dwight V Nissley, Frank McCormick
The 3 human RAS genes play pivotal roles regulating proliferation, differentiation, and survival in normal cells and become mutated in 15% to 20% of all human tumors and amplified in many others. In this report, we examined data from The Cancer Genome Atlas to investigate the relationship between RAS gene mutational status and messenger RNA expression. We show that all 3 RAS genes exhibit increased expression when they are mutated in a context-dependent manner. In the case of KRAS, this increase is manifested by a larger proportional increase in KRAS4A than KRAS4B, although both increase significantly...
2017: Cancer Informatics
https://www.readbyqxmd.com/read/28615920/immune-checkpoint-inhibition-and-the-prevalence-of-autoimmune-disorders-among-patients-with-lung-and-renal-cancer
#10
Sherif M El-Refai, Joshua D Brown, Esther P Black, Jeffery C Talbert
PURPOSE: Immune checkpoint inhibition reactivates the immune response against cancer cells in multiple tissue types and has been shown to induce durable responses. However, for patients with autoimmune disorders, their conditions can worsen with this reactivation. We sought to identify, among patients with lung and renal cancer, how many harbor a comorbid autoimmune condition and may be at risk of worsening their condition while on immune checkpoint inhibitors such as nivolumab and pembrolizumab...
2017: Cancer Informatics
https://www.readbyqxmd.com/read/28615919/sequence-analysis-and-phylogenetic-studies-of-hypoxia-inducible-factor-1%C3%AE
#11
Jagadeesha Poyya, Chandrashekhar G Joshi, D Jagadeesha Kumar, H G Nagendra
Hypoxia-inducible factors (HIF) belong to the basic helix loop helix-PER ARNT SIM (bHLH-PAS) family of transcription factors that induce metabolic reprogramming under hypoxic condition. The phylogenetic studies of hypoxia-inducible factor-1α (HIF-1α) sequences across different organisms/species may leave a clue on the evolutionary relationships and its probable correlation to tumorigenesis and adaptation to low oxygen environments. In this study, we have aimed at the evolutionary investigation of the protein HIF-1α across different species to decipher their sequence variations/mutations and look into the probable causes and abnormal behaviour of this molecule under exotic conditions...
2017: Cancer Informatics
https://www.readbyqxmd.com/read/28615918/lung-cancer-pathological-image-analysis-using-a-hidden-potts-model
#12
Qianyun Li, Faliu Yi, Tao Wang, Guanghua Xiao, Faming Liang
Nowadays, many biological data are acquired via images. In this article, we study the pathological images scanned from 205 patients with lung cancer with the goal to find out the relationship between the survival time and the spatial distribution of different types of cells, including lymphocyte, stroma, and tumor cells. Toward this goal, we model the spatial distribution of different types of cells using a modified Potts model for which the parameters represent interactions between different types of cells and estimate the parameters of the Potts model using the double Metropolis-Hastings algorithm...
2017: Cancer Informatics
https://www.readbyqxmd.com/read/28579741/time-based-switching-control-of-genetic-regulatory-networks-toward-sequential-drug-intake-for-cancer-therapy
#13
Wasiu Opeyemi Oduola, Xiangfang Li, Chang Duan, Lijun Qian, Fen Wu, Edward R Dougherty
As cancer growth and development typically involves multiple genes and pathways, combination therapy has been touted as the standard of care in the treatment of cancer. However, drug toxicity becomes a major concern whenever a patient takes 2 or more drugs simultaneously at the maximum tolerable dosage. A potential solution would be administering the drugs in a sequential or alternating manner rather than concurrently. This study therefore examines the feasibility of such an approach from a switched system control perspective...
2017: Cancer Informatics
https://www.readbyqxmd.com/read/28579740/applying-multivariate-adaptive-splines-to-identify-genes-with-expressions-varying-after-diagnosis-in-microarray-experiments
#14
REVIEW
Fenghai Duan, Ye Xu
PURPOSE: To analyze a microarray experiment to identify the genes with expressions varying after the diagnosis of breast cancer. METHODS: A total of 44 928 probe sets in an Affymetrix microarray data publicly available on Gene Expression Omnibus from 249 patients with breast cancer were analyzed by the nonparametric multivariate adaptive splines. Then, the identified genes with turning points were grouped by K-means clustering, and their network relationship was subsequently analyzed by the Ingenuity Pathway Analysis...
2017: Cancer Informatics
https://www.readbyqxmd.com/read/28579739/quantitative-study-of-thermal-disturbances-due-to-nonuniformly-perfused-tumors-in-peripheral-regions-of-women-s-breast
#15
Akshara Makrariya, Neeru Adlakha
BACKGROUND: Mathematical modeling of biothermal processes is widely used to enhance the quantitative understanding of thermoregulation system of human body organs. This quantitative knowledge of thermal information of various human body organs can be used for developing clinical applications. In the past, investigators have studied thermal distribution in hemisphere-shaped human breast in the presence of sphere-shaped tumor. The shape and size of the breast as well as tumor may also affect thermal distribution which can have serious implications in thermography...
2017: Cancer Informatics
https://www.readbyqxmd.com/read/28469393/bioinformatics-education-in-pathology-training-current-scope-and-future-direction
#16
REVIEW
Michael R Clay, Kevin E Fisher
Training anatomic and clinical pathology residents in the principles of bioinformatics is a challenging endeavor. Most residents receive little to no formal exposure to bioinformatics during medical education, and most of the pathology training is spent interpreting histopathology slides using light microscopy or focused on laboratory regulation, management, and interpretation of discrete laboratory data. At a minimum, residents should be familiar with data structure, data pipelines, data manipulation, and data regulations within clinical laboratories...
2017: Cancer Informatics
https://www.readbyqxmd.com/read/28469392/mir-10a-and-mir-204-as-a-potential-prognostic-indicator-in-low-grade-gliomas
#17
Ju Cheol Son, Hyoung Oh Jeong, Deaui Park, Sang Gyoon No, Eun Kyeong Lee, Jaewon Lee, Hae Young Chung
This study aimed to identify and characterize microRNAs (miRNAs) that are related to radiosensitivity in low-grade gliomas (LGGs). The miRNA expression levels in radiosensitive and radioresistant LGGs were compared using The Cancer Genome Atlas database, and differentially expressed miRNAs were identified using the EBSeq package. The miRNA target genes were predicted using Web databases. Fifteen miRNAs were differentially expressed between the groups, with miR-10a and miR-204 being related to overall survival (OS) of patients with LGG...
2017: Cancer Informatics
https://www.readbyqxmd.com/read/28469391/a-mixture-copula-bayesian-network-model-for-multimodal-genomic-data
#18
Qingyang Zhang, Xuan Shi
Gaussian Bayesian networks have become a widely used framework to estimate directed associations between joint Gaussian variables, where the network structure encodes the decomposition of multivariate normal density into local terms. However, the resulting estimates can be inaccurate when the normality assumption is moderately or severely violated, making it unsuitable for dealing with recent genomic data such as the Cancer Genome Atlas data. In the present paper, we propose a mixture copula Bayesian network model which provides great flexibility in modeling non-Gaussian and multimodal data for causal inference...
2017: Cancer Informatics
https://www.readbyqxmd.com/read/28469390/therapeutic-interventions-of-cancers-using-intrinsically-disordered-proteins-as-drug-targets-c-myc-as-model-system
#19
REVIEW
Deepak Kumar, Nitin Sharma, Rajanish Giri
The concept of protein intrinsic disorder has taken the driving seat to understand regulatory proteins in general. Reports suggest that in mammals nearly 75% of signalling proteins contain long disordered regions with greater than 30 amino acid residues. Therefore, intrinsically disordered proteins (IDPs) have been implicated in several human diseases and should be considered as potential novel drug targets. Moreover, intrinsic disorder provides a huge multifunctional capability to hub proteins such as c-Myc and p53...
2017: Cancer Informatics
https://www.readbyqxmd.com/read/28469389/roadmap-to-a-comprehensive-clinical-data-warehouse-for-precision-medicine-applications-in-oncology
#20
David J Foran, Wenjin Chen, Huiqi Chu, Evita Sadimin, Doreen Loh, Gregory Riedlinger, Lauri A Goodell, Shridar Ganesan, Kim Hirshfield, Lorna Rodriguez, Robert S DiPaola
Leading institutions throughout the country have established Precision Medicine programs to support personalized treatment of patients. A cornerstone for these programs is the establishment of enterprise-wide Clinical Data Warehouses. Working shoulder-to-shoulder, a team of physicians, systems biologists, engineers, and scientists at Rutgers Cancer Institute of New Jersey have designed, developed, and implemented the Warehouse with information originating from data sources, including Electronic Medical Records, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology and Pathology archives, and Next Generation Sequencing services...
2017: Cancer Informatics
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