Interferon α-Inducible Protein 27 Computational Network Construction and Comparison between the Frontal Cortex of HIV Encephalitis (HIVE) and HIVE-Control Patients~!2010-04-06~!2010-08-05~!2010-09-06~!

Huang, Jianing; Wang, Lin; Jiang, Minghu; Zheng, Xiguang

doi:10.2174/1875693x01003010001

Cited by 20 publications

(4 citation statements)

References 62 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our aim is to construct, interpret and verify novel different lowand high-expression CDH13 downstream network from no-tumor hepatitis/cirrhosis (HBV or HCV infection) to HCC malignant transformation. We have already constructed some novel molecular networks from different databases and analyzed significance of our work presented in our articles [26][27][28][29][30][31][32][33]. Such as, we inferred BIRC5 cell cycle module more mitosis but less complex-dependent proteasomal ubiquitin-dependent protein catabolism, as a result of increasing cell division and cell numbers in no-tumor hepatitis/cirrhosis; more protein amino acid autophosphorylation but less negative regulation of ubiquitin ligase activity during mitotic cell cycle, as a result of increasing growth and cell volume in HCC [34].…”

Section: Discussionmentioning

confidence: 99%

Differential Differentiation- and Survival and Invasion-related T-/Hcadherin (CDH13) Computational Downstream Network from No-Tumor Hepatitis/Cirrhosis (HBV or HCV infection) to Human Hepatocellular Carcinoma (HCC) Malignant Transformation

Wang

Wu²,

Jiang³

et al. 2012

J Mol Biomark Diagn

View full text Add to dashboard Cite

We constructed and analyzed the low-and high-expression (fold change ≥2) different-activated and -inhibited T-/H-cadherin (CDH13) downstream network from no-tumor hepatitis/cirrhosis (HBV or HCV infection) to HCC malignant transformation in GEO data set by integration of gene regulatory network inference method based on linear programming and decomposition procedure with GO database. Our results show that the low-expression CDH13 downstream network has the multi-activated and -inhibited molecular pattern in no-tumor hepatitis/cirrhosis, whereas high-expression CDH13 downstream mainly somewhat inhibited molecular connections but significant reduced network (fold ≥2) in HCC. We suppose that the low-expression CDH13 downstream network mainly activates cell differentiation cell adhesion, but inhibits nuclear chromosome, mitosis in no-tumor hepatitis/cirrhosis, whereas the high-expression CDH13 downstream network activates Rab-protein geranylgeranyltransferase activity, protein modification, but inhibits modification-dependent protein catabolism and nucleotide binding in HCC. We put forward hypothesis that low-expression CDH13 activates cadherin binding, homophilic cell adhesion, negative regulation of cell adhesion, positive regulation of calcium-mediated signaling, calcium-dependent cell-cell adhesion, positive regulation of cell-matrix adhesion, low density lipoprotein mediated signaling and inhibits regulation of endothelial cell proliferation, positive regulation of smooth muscle cell proliferation, keratinocyte proliferation, as a result of inducing differentiation in no-tumor hepatitis/cirrhosis, whereas high-expression CDH13 activates positive regulation of survival gene product activity, protein homodimerization activity, Rho protein signal transduction, Rac protein signal transduction, positive regulation of cell migration, sprouting angiogenesis, positive regulation of positive chemotaxis, epidermal growth factor receptor signaling pathway, endothelial cell migration, lamellipodium biogenesis, and inhibits regulation of endocytosis, caveola, as a result of inducing survival and invasion in HCC. Our inferences are consistent with different-activated and -inhibited CDH13 downstream network, GO database and literatures, respectively.

show abstract

Section: Discussionmentioning

confidence: 99%

Differential Differentiation- and Survival and Invasion-related T-/Hcadherin (CDH13) Computational Downstream Network from No-Tumor Hepatitis/Cirrhosis (HBV or HCV infection) to Human Hepatocellular Carcinoma (HCC) Malignant Transformation

Wang

Wu²,

Jiang³

et al. 2012

J Mol Biomark Diagn

View full text Add to dashboard Cite

show abstract

“…Novel BRCA1 ‐activated (Pearson ≥0.25) and ‐inhibited (Pearson ≤−0.25) different complete (all no positive correlation, Pearson <0.25) and uncomplete (partly no positive correlation except BRCA1 , Pearson <0.25) networks were constructed between lower no‐tumor hepatitis/cirrhotic tissues (HBV or HCV infection) and higher HCC by GRNInfer [Wang et al, ], our articles [Wang et al, ,, ,,,,,, ,,,; Huang et al, 2010, 2011, ; Sun et al, ; Sun et al, ; Lin et al, ] and GVedit tool and our programming, respectively.…”

Section: Methodsmentioning

confidence: 99%

BRCA1-Mediated Inflammation and Growth Activated & Inhibited Transition Mechanisms Between No-Tumor Hepatitis/Cirrhotic Tissues and HCC

et al. 2014

Self Cite

View full text Add to dashboard Cite

To understand breast cancer 1 early onset (BRCA1)-mediated inflammation and growth activated and inhibited transition mechanisms between no-tumor hepatitis/cirrhotic tissues (HBV or HCV infection) and human hepatocellular carcinoma (HCC), BRCA1-activated different complete (all no positive correlation, Pearson correlation coefficient <0.25) and uncomplete (partly no positive correlation except BRCA1, Pearson <0.25) networks were identified in higher HCC compared with lower no-tumor hepatitis/cirrhotic tissues (HBV or HCV infection) from the corresponding BRCA1-stimulated (Pearson ≥0.25) or inhibited (Pearson ≤-0.25) overlapping molecules of Pearson and GRNInfer, respectively. This result was verified by the corresponding scatter matrix. As visualized by GO, KEGG, GenMAPP, BioCarta, and disease database integration, we proposed mainly that BRCA1-stimulated different complete network was involved in BRCA1 activation with integral to membrane killer cell lectin-like receptor C to nucleus interferon regulatory factor 5-induced inflammation, whereas the corresponding inhibited network participated in BRCA1 repression with matrix roundabout axon guidance receptor homolog 1 to plasma membrane versican-induced growth in lower no-tumor hepatitis/cirrhotic tissues (HBV or HCV infection). However, BRCA1-stimulated network contained BRCA1 activation with endothelium-specific to lysosomal transmembrane and carbamoyl synthetase to tastin, histone cluster and cyclin-induced growth, whereas the corresponding inhibited different complete network included BRCA1 repression with ovalbumin, thyroid stimulating hormone beta and Hu antigen C to cytochrome P450 to transducin-induced inflammation in higher HCC. Our BRCA1 different networks were verified by BRCA1-activated or -inhibited complete and uncomplete networks within and between no-tumor hepatitis/cirrhotic tissues (HBV or HCV infection) or (and) HCC.

show abstract

“…AMELY -activated upstream regulation molecular networks in non-tumor hepatitis/cirrhotic tissues and HCC were constructed by GRNInfer (21) and published studies (22–36), and illustrated by GVedit tool, respectively.…”

Section: Methodsmentioning

confidence: 99%

Activated amelogenin Y-linked (AMELY) regulation and angiogenesis in human hepatocellular carcinoma by biocomputation

Wang

Huang

et al. 2013

Oncology Letters

Self Cite

View full text Add to dashboard Cite

In the present study, a comparison of the biological processes and gene ontology (GO) in human hepatocellular carcinoma (HCC) with high expression (fold change ≥2) of amelogenin Y-linked (AMELY)-activated upstream regulation networks with non-tumor hepatitis/cirrhotic tissues (HBV or HCV infection) with low expression of activated networks was performed. The principle biological processes involved in non-tumor hepatitis/cirrhotic tissues include positive regulation of mismatch repair, regulation of transcription from RNA polymerase II promoters, negative regulation of cell-cell adhesion, protein ubiquitinatin and protein catabolism. The main biological processes involved in the development of HCC include positive regulation of calcium ion transport into the cytosol, cell proliferation, DNA replication, fibroblast proliferation, immune response, microtubule polymerization and protein secretion. Specific transcription from RNA polymerase II promoters, regulation of angiogenesis, cell growth, protein metabolism, Wnt receptor signaling pathways, negative regulation of endothelial cell differentiation, microtubule depolymerization, peptidase activity and progression through the cell cycle are also involved. Positive regulation of transcription is involved in both processes. An activated AMELY-coupled upstream positive regulation of immune response-mediated protein secretion to Wnt signaling and calcium into cytosol-induced regulation of cell growth and angiogenesis in HCC is proposed. The AMELY upstream regulation molecular network model was constructed with BUB1B, CST6, ESM1, HOXA5, LEF1, MAPT, MYBL2, NOTCH3, PLA2G1B, PROK1, ROBO1, SCML2 and UBE2C in HCC from a Gene Expression Omnibus (GEO) dataset by gene regulation network inference methods and our programming methods.

show abstract

Interferon α-Inducible Protein 27 Computational Network Construction and Comparison between the Frontal Cortex of HIV Encephalitis (HIVE) and HIVE-Control Patients~!2010-04-06~!2010-08-05~!2010-09-06~!

Cited by 20 publications

References 62 publications

Differential Differentiation- and Survival and Invasion-related T-/Hcadherin (CDH13) Computational Downstream Network from No-Tumor Hepatitis/Cirrhosis (HBV or HCV infection) to Human Hepatocellular Carcinoma (HCC) Malignant Transformation

Differential Differentiation- and Survival and Invasion-related T-/Hcadherin (CDH13) Computational Downstream Network from No-Tumor Hepatitis/Cirrhosis (HBV or HCV infection) to Human Hepatocellular Carcinoma (HCC) Malignant Transformation

BRCA1-Mediated Inflammation and Growth Activated & Inhibited Transition Mechanisms Between No-Tumor Hepatitis/Cirrhotic Tissues and HCC

Activated amelogenin Y-linked (AMELY) regulation and angiogenesis in human hepatocellular carcinoma by biocomputation

Contact Info

Product

Resources

About