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https://www.readbyqxmd.com/read/29331675/module-analysis-captures-pancancer-genetically-and-epigenetically-deregulated-cancer-driver-genes-for-smoking-and-antiviral-response
#1
Magali Champion, Kevin Brennan, Tom Croonenborghs, Andrew J Gentles, Nathalie Pochet, Olivier Gevaert
The availability of increasing volumes of multi-omics profiles across many cancers promises to improve our understanding of the regulatory mechanisms underlying cancer. The main challenge is to integrate these multiple levels of omics profiles and especially to analyze them across many cancers. Here we present AMARETTO, an algorithm that addresses both challenges in three steps. First, AMARETTO identifies potential cancer driver genes through integration of copy number, DNA methylation and gene expression data...
December 1, 2017: EBioMedicine
https://www.readbyqxmd.com/read/29330507/uncovering-the-anticancer-mechanism-of-compound-kushen-injection-against-hcc-by-integrating-quantitative-analysis-network-analysis-and-experimental-validation
#2
Li Gao, Ke-Xin Wang, Yu-Zhi Zhou, Jian-Song Fang, Xue-Mei Qin, Guan-Hua Du
Compound Kushen Injection (CKI) is a Traditional Chinese Medicine (TCM) preparation that has been clinically used in China to treat various types of solid tumours. Although several studies have revealed that CKI can inhibit the proliferation of hepatocellular carcinoma (HCC) cell lines, the active compounds, potential targets and pathways involved in these effects have not been systematically investigated. Here, we proposed a novel idea of "main active compound-based network pharmacology" to explore the anti-cancer mechanism of CKI...
January 12, 2018: Scientific Reports
https://www.readbyqxmd.com/read/29329368/discovering-personalized-driver-mutation-profiles-of-single-samples-in-cancer-by-network-control-strategy
#3
Wei-Feng Guo, Shao-Wu Zhang, Li-Li Liu, Fei Liu, Qian-Qian Shi, Lei Zhang, Ying Tang, Tao Zeng, Luonan Chen
Motivation: It is a challenging task to discover personalized driver genes that provide crucial information on disease risk and drug sensitivity for individual patients. However, few methods have been proposed to identify the personalized-sample driver genes from the cancer omics data due to the lack of samples for each individual. To circumvent this problem, here we present a novel single-sample controller strategy (SCS) to identify personalized driver mutation profiles from network controllability perspective...
January 10, 2018: Bioinformatics
https://www.readbyqxmd.com/read/29328992/transcriptome-wide-identification-and-competitive-disruption-of-sacum-binding-partners-in-human-colorectal-cancer
#4
Yinguang Zhang, Yongwang Zhang, Yuxiang Zhang
Human sacum is regulatory adaptor protein involved in cellular signaling network of colorectal cancer. Molecular evidences suggest that the protein is integrated into oncogenic signaling network by binding to SH3-containing proteins through its proline-rich motifs. In this study, we have performed a transcriptome-wide analysis and identification of sacum-binding partners in the genome profile of human colorectal cancer. The sacum-binding potency of SH3-containing proteins found in colorectal cancer was investigated by using bioinformatics modeling and intermolecular binding analysis...
December 30, 2017: Journal of Molecular Graphics & Modelling
https://www.readbyqxmd.com/read/29328363/support-vector-machine-classifier-for-prediction-of-the-metastasis-of-colorectal-cancer
#5
Jiajun Zhi, Jiwei Sun, Zhongchuan Wang, Wenjun Ding
Colorectal cancer (CRC) is one of the most common cancers and a major cause of mortality. The present study aimed to identify potential biomarkers for CRC metastasis and uncover the mechanisms underlying the etiology of the disease. The five datasets GSE68468, GSE62321, GSE22834, GSE14297 and GSE6988 were utilized in the study, all of which contained metastatic and non-metastatic CRC samples. Among them, three datasets were integrated via meta-analysis to identify the differentially expressed genes (DEGs) between the two types of samples...
January 2, 2018: International Journal of Molecular Medicine
https://www.readbyqxmd.com/read/29328361/logistic-regression-analysis-for-the-identification-of-the-metastasis-associated-signaling-pathways-of-osteosarcoma
#6
Yang Liu, Wei Sun, Xiaojun Ma, Yuedong Hao, Gang Liu, Xiaohui Hu, Houlai Shang, Pengfei Wu, Zexue Zhao, Weidong Liu
Osteosarcoma (OS) is the most common histological type of primary bone cancer. The present study was designed to identify the key genes and signaling pathways involved in the metastasis of OS. Microarray data of GSE39055 were downloaded from the Gene Expression Omnibus database, which included 19 OS biopsy specimens before metastasis (control group) and 18 OS biopsy specimens after metastasis (case group). After the differentially expressed genes (DEGs) were identified using the Linear Models for Microarray Analysis package, hierarchical clustering analysis and unsupervised clustering analysis were performed separately, using orange software and the self-organization map method...
January 2, 2018: International Journal of Molecular Medicine
https://www.readbyqxmd.com/read/29327492/a-five-gene-signature-may-predict-sunitinib-sensitivity-and-serve-as-prognostic-biomarkers-for-renal-cell-carcinoma
#7
Yuan-Lei Chen, Guang-Ju Ge, Chao Qi, Huan Wang, Huai-Lan Wang, Li-Yang Li, Gong-Hui Li, Li-Qun Xia
Sunitinib resistance is, nowadays, the major challenge for advanced renal cell carcinoma patients. Illuminating the potential mechanisms and exploring effective strategies to overcome sunitinib resistance are highly desired. We constructed a reliable gene signature which may function as biomarkers for prediction of sunitinib sensitivity and clinical prognosis. The gene expression profiles were obtained from The Cancer Genome Atlas database. By performing GEO2R analysis, numerous differentially expressed genes (DEGs) were found to be associated with sunitinib resistance...
January 12, 2018: Journal of Cellular Physiology
https://www.readbyqxmd.com/read/29325141/lncmap-pan-cancer-atlas-of-long-noncoding-rna-mediated-transcriptional-network-perturbations
#8
Yongsheng Li, Lili Li, Zishan Wang, Tao Pan, Nidhi Sahni, Xiyun Jin, Guangjuan Wang, Junyi Li, Xiangyi Zheng, Yunpeng Zhang, Juan Xu, Song Yi, Xia Li
Gene regulatory network perturbations contribute to the development and progression of cancer, however, molecular determinants that mediate transcriptional perturbations remain a fundamental challenge for cancer biology. We show that transcriptional perturbations are widely mediated by long noncoding RNAs (lncRNAs) via integration of genome-wide transcriptional regulation with paired lncRNA and gene expression profiles. Systematic construction of an LncRNA Modulator Atlas in Pan-cancer (LncMAP) reveals distinct types of lncRNA regulatory molecules, which are expressed in multiple tissues, exhibit higher conservation...
January 9, 2018: Nucleic Acids Research
https://www.readbyqxmd.com/read/29322930/ontological-representation-integration-and-analysis-of-lincs-cell-line-cells-and-their-cellular-responses
#9
Edison Ong, Jiangan Xie, Zhaohui Ni, Qingping Liu, Sirarat Sarntivijai, Yu Lin, Daniel Cooper, Raymond Terryn, Vasileios Stathias, Caty Chung, Stephan Schürer, Yongqun He
BACKGROUND: Aiming to understand cellular responses to different perturbations, the NIH Common Fund Library of Integrated Network-based Cellular Signatures (LINCS) program involves many institutes and laboratories working on over a thousand cell lines. The community-based Cell Line Ontology (CLO) is selected as the default ontology for LINCS cell line representation and integration. RESULTS: CLO has consistently represented all 1097 LINCS cell lines and included information extracted from the LINCS Data Portal and ChEMBL...
December 21, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/29322918/a-linear-programming-computational-framework-integrates-phosphor-proteomics-and-prior-knowledge-to-predict-drug-efficacy
#10
Zhiwei Ji, Bing Wang, Ke Yan, Ligang Dong, Guanmin Meng, Lei Shi
BACKGROUND: In recent years, the integration of 'omics' technologies, high performance computation, and mathematical modeling of biological processes marks that the systems biology has started to fundamentally impact the way of approaching drug discovery. The LINCS public data warehouse provides detailed information about cell responses with various genetic and environmental stressors. It can be greatly helpful in developing new drugs and therapeutics, as well as improving the situations of lacking effective drugs, drug resistance and relapse in cancer therapies, etc...
December 21, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/29322790/integrated-network-analysis-to-identify-the-key-genes-transcription-factors-and-micrornas-involved-in-hepatocellular-carcinoma
#11
S Q Shi, J-J Ke, Q S Xu, W Q Wu, Y Y Wan
HCC (hepatocellular carcinoma), which can be induced by cirrhosis and viral hepatitis infection, is the most frequent form of liver cancer. This study is performed to investigate the mechanisms of HCC. GSE57957 was obtained from Gene Expression Omnibus database, including 39 HCC samples and 39 adjacent non-tumorous samples. The DEGs (differentially expressed genes) were screened using the limma package in R, and then were conducted with enrichment analysis using "BioCloud" platform. Using STRING database, WebGestalt tool, as well as ITFP and TRANSFAC databases, PPI (protein-protein interaction) pairs, miRNA (microRNA)-target pairs, and TF (transcription factor)-target pairs separately were predicted...
2018: Neoplasma
https://www.readbyqxmd.com/read/29319503/synthesizing-artificial-devices-that-redirect-cellular-information-at-will
#12
Yuchen Liu, Jianfa Li, Zhicong Chen, Weiren Huang, Zhiming Cai
Natural signaling circuits could be rewired to reprogram cells with pre-determined procedures. However, it is difficult to link cellular signals at will. Here, we describe signal-connectors-a series of RNA devices-that connect one signal to another signal at the translational level. We use them to either repress or enhance the translation of target genes in response to signals. Application of these devices allows us to construct various logic gates and to incorporate feedback loops into gene networks. They have also been used to rewire a native signaling pathway and even to create novel pathways...
January 10, 2018: ELife
https://www.readbyqxmd.com/read/29317304/lncrna-and-mrna-integration-network-reconstruction-reveals-novel-key-regulators-in-esophageal-squamous-cell-carcinoma
#13
Shervin Alaei, Balal Sadeghi, Ali Najafi, Ali Masoudi-Nejad
Many experimental and computational studies have identified key protein coding genes in initiation and progression of esophageal squamous cell carcinoma (ESCC). However, the number of researches that tried to reveal the role of long non-coding RNAs (lncRNAs) in ESCC has been limited. LncRNAs are one of the important regulators of cancers which are transcribed dominantly in the genome and in various conditions. The main goal of this study was to use a systems biology approach to predict novel lncRNAs as well as protein coding genes associated with ESCC and assess their prognostic values...
January 6, 2018: Genomics
https://www.readbyqxmd.com/read/29311159/pd2-paf1-at-the-crossroads-of-the-cancer-network
#14
REVIEW
Saswati Karmakar, Parama Dey, Arokia P Vaz, Sukesh R Bhaumik, Moorthy P Ponnusamy, Surinder K Batra
Pancreatic differentiation 2 (PD2)/RNA polymerase II-associated factor 1 (PAF1) is the core subunit of the human PAF1 complex (PAF1C) that regulates the promoter-proximal pausing of RNA polymerase II as well as transcription elongation and mRNA processing and coordinates events in mRNA stability and quality control. As an integral part of its transcription-regulatory function, PD2/PAF1 plays a role in posttranslational histone covalent modifications as well as regulates expression of critical genes of the cell-cycle machinery...
January 8, 2018: Cancer Research
https://www.readbyqxmd.com/read/29304754/integration-of-multiple-networks-and-pathways-identifies-cancer-driver-genes-in-pan-cancer-analysis
#15
Claudia Cava, Gloria Bertoli, Antonio Colaprico, Catharina Olsen, Gianluca Bontempi, Isabella Castiglioni
BACKGROUND: Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network...
January 6, 2018: BMC Genomics
https://www.readbyqxmd.com/read/29303984/transcription-factor-and-lncrna-regulatory-networks-identify-key-elements-in-lung-adenocarcinoma
#16
Dan Li, William Yang, Jialing Zhang, Jack Y Yang, Renchu Guan, Mary Qu Yang
Lung cancer is the second most commonly diagnosed carcinoma and is the leading cause of cancer death. Although significant progress has been made towards its understanding and treatment, unraveling the complexities of lung cancer is still hampered by a lack of comprehensive knowledge on the mechanisms underlying the disease. High-throughput and multidimensional genomic data have shed new light on cancer biology. In this study, we developed a network-based approach integrating somatic mutations, the transcriptome, DNA methylation, and protein-DNA interactions to reveal the key regulators in lung adenocarcinoma (LUAD)...
January 5, 2018: Genes
https://www.readbyqxmd.com/read/29301446/real-time-estimation-of-lesion-depth-and-control-of-radiofrequency-ablation-within-ex-vivo-animal-tissues-using-a-neural-network
#17
Yearnchee Curtis Wang, Terence Chee-Hung Chan, Alan Varteres Sahakian
BACKGROUND: Radiofrequency ablation (RFA), a method of inducing thermal ablation (cell death), is often used to destroy tumours or potentially cancerous tissue. Current techniques for RFA estimation (electrical impedance tomography, Nakagami ultrasound, etc.) require long compute times (≥ 2 s) and measurement devices other than the RFA device. This study aims to determine if a neural network (NN) can estimate ablation lesion depth for control of bipolar RFA using complex electrical impedance - since tissue electrical conductivity varies as a function of tissue temperature - in real time using only the RFA therapy device's electrodes...
January 4, 2018: International Journal of Hyperthermia
https://www.readbyqxmd.com/read/29298665/analysis-of-microarrays-of-mir-34a-and-its-identification-of-prospective-target-gene-signature-in-hepatocellular-carcinoma
#18
Fang-Hui Ren, Hong Yang, Rong-Quan He, Jing-Ning Lu, Xing-Gu Lin, Hai-Wei Liang, Yi-Wu Dang, Zhen-Bo Feng, Gang Chen, Dian-Zhong Luo
BACKGROUND: Currently, some studies have demonstrated that miR-34a could serve as a suppressor of several cancers including hepatocellular carcinoma (HCC). Previously, we discovered that miR-34a was downregulated in HCC and involved in the tumorigenesis and progression of HCC; however, the mechanism remains unclear. The purpose of this study was to estimate the expression of miR-34a in HCC by applying the microarray profiles and analyzing the predicted targets of miR-34a and their related biological pathways of HCC...
January 3, 2018: BMC Cancer
https://www.readbyqxmd.com/read/29297304/novel-human-microbe-disease-association-prediction-using-network-consistency-projection
#19
Wenzheng Bao, Zhichao Jiang, De-Shuang Huang
BACKGROUND: Accumulating biological and clinical reports have indicated that imbalance of microbial community is closely associated with occurrence and development of various complex human diseases. Identifying potential microbe-disease associations, which could provide better understanding of disease pathology and further boost disease diagnostic and prognostic, has attracted more and more attention. However, hardly any computational models have been developed for large scale microbe-disease association prediction...
December 28, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/29290766/integrated-analysis-of-long-non-coding-rna-and-mrna-expression-profile-in-pancreatic-cancer-derived-exosomes-treated-dendritic-cells-by-microarray-analysis
#20
Jionghuang Chen, Shaowen Wang, Shengnan Jia, Guoping Ding, Guixing Jiang, Liping Cao
Background: Pancreatic cancer is a devastating disease with a low five-year survival rate. Dendritic cells (DCs), which are the most potent antigen-presenting cells in the human body, play a pivotal role in the immune response. However, few studies have investigated the role of pancreatic cancer-derived exosomes (PEXs) in DC-meditated immune escape. The expression profiles of long noncoding RNAs (lncRNAs) and mRNAs of PEX-treated dendritic cells are unknown. Methods: We used integrated lncRNA and mRNA microarrays to determine the expression profiles of PEX-treated DCs and normal DCs derived from five healthy donors...
2018: Journal of Cancer
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