TNFRSF11B computational development network construction and analysis between frontal cortex of HIV encephalitis (HIVE) and HIVE-control patients

Low BIK outside-inside-out interactive inflammation immune-induced transcription-dependent apoptosis through FUT3-PMM2-SQSTM1-SFN-ZNF384

Eighteen different Pearson mutual-positive-correlation BIK-activatory molecular feedback upstream and downstream networks were constructed from 79 overlapping of 376 GRNInfer and 98 Pearson under BIK CC ≥ 0.25 in low normal adjacent tissues of Taiwan compared with high lung adenocarcinoma. Our identified BIK interactive total feedback molecular network showed FUT3 [fucosyltransferase 3 (galactoside 3(4)-L-fucosyltransferase Lewis blood group)], PMM2 (phosphomannomutase 2), SQSTM1 (sequestosome 1), SFN_2 [REX2 RNA exonuclease 2 homolog (S. cerevisiae)] and ZNF384 (zinc finger protein 384) in low normal adjacent tissues of lung adenocarcinoma. BIK interactive total feedback terms included mitochondrial envelope, endomembrane system, integral to membrane, Golgi apparatus, cytoplasm, nucleus, cytosol, intracellular signaling cascade, mitochondrion, extracellular space, inflammation, immune response, apoptosis, cell differentiation, cell cycle, regulation of cell cycle, cell proliferation, estrogen-responsive protein Efp controls cell cycle and breast tumors growth, induction or regulation of apoptosis based on integrative GO, KEGG, GenMAPP, BioCarta and disease databases in low normal adjacent tissues of lung adenocarcinoma. Therefore, we propose low BIK outside-inside-out interactive inflammation immune-induced transcription-dependent apoptosis through FUT3-PMM2-SQSTM1-SFN-ZNF384 in normal adjacent tissues of lung adenocarcinoma.

Adenosylmethionine decarboxylase 1 (AMD1)-mediated mRNA processing and cell adhesion activated & inhibited transition mechanisms by different comparisons between chimpanzee and human left hemisphere

To understand adenosylmethionine decarboxylase 1 (AMD1)-mediated mRNA processing and cell adhesion activated & inhibited transition mechanisms between chimpanzee and human left hemisphere, AMD1-activated different complete (all no positive correlation, Pearson correlation coefficient < 0.25) and uncomplete (partly no positive correlation except AMD1, Pearson < 0.25) networks were identified in higher human compared with lower chimpanzee left hemisphere from the corresponding AMD1-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 AMD1-stimulated different complete network was involved in AMD1 activation with cytoplasm ubiquitin specific peptidase (tRNA-guanine transglycosylase) to nucleus paired box-induced mRNA processing, whereas the corresponding inhibited network participated in AMD1 repression with cytoplasm protocadherin gamma and adaptor-related protein complex 3-induced cell adhesion in lower chimpanzee left hemisphere. However, AMD1-stimulated network contained AMD1 activation with plakophilin and phosphodiesterase to SH3 binding glutamic acid-rich protein to dynein and zinc finger-induced cell adhesion, whereas the corresponding inhibited different complete network included AMD1 repression with mitochondrial denine nucleotide translocator, brain protein, and ADH dehydrogenase to ribonucleoprotein-induced mRNA processing in higher human left hemisphere. Our AMD1 different networks were verified by AMD1-activated or -inhibited complete and uncomplete networks within and between chimpanzee left hemisphere or (and) human left hemisphere.

CAMK1 phosphoinositide signal-mediated protein sorting and transport network in human hepatocellular carcinoma (HCC) by biocomputation

We data-analyzed and constructed the high-expression CAMK1 phosphoinositide signal-mediated protein sorting and transport network in human hepatocellular carcinoma (HCC) compared with low-expression (fold change ≥ 2) no-tumor hepatitis/cirrhotic tissues (HBV or HCV infection) in GEO data set, using integration of gene regulatory network inference method with gene ontology (GO). Our result showed that CAMK1 transport subnetwork upstream KCNQ3, LCN2, NKX2_5, NUP62, SORT1, STX1A activated CAMK1, and downstream CAMK1-activated AFP, ENAH, KPNA2, SLC4A3; CAMK1 signal subnetwork upstream BRCA1, DKK1, GPSM2, LEF1, NR5A1, NUP62, SORT1, SSTR5, TBL3 activated CAMK1, and downstream CAMK1-activated MAP2K6, SFRP4, SSTR5, TSHB, UBE2C in HCC. We proposed that CAMK1 activated network enhanced endosome to lysosome transport, endosome transport via multivesicular body sorting pathway, Golgi to endosome transport, intracellular protein transmembrane transport, intracellular protein transport, ion transport, mRNA transport, plasma membrane to endosome transport, potassium ion transport, protein transport, vesicle-mediated transport, anion transport, intracellular transport, androgen receptor signaling pathway, cell surface receptor-linked signal transduction, hormone-mediated signaling, induction of apoptosis by extracellular signals, signal transduction by p53 class mediator resulting in transcription of p21 class mediator, signal transduction resulting in induction of apoptosis, phosphoinositide-mediated signaling, Wnt receptor signaling pathway, as a result of inducing phosphoinositide signal-mediated protein sorting, and transport in HCC. Our hypothesis was verified by CAMK1 functional regulation subnetwork containing positive regulation of calcium ion transport via voltage gated calcium channel, cell proliferation, DNA repair, exocytosis, I-kappaB kinase/NF-kappaB cascade, immunoglobulin-mediated immune response, mast cell activation, natural killer cell-mediated cytotoxicity directed against tumor cell target, protein ubiquitination, sodium ion transport, survival gene product activity, T cell-mediated cytotoxicity, transcription, transcription from RNA polymerase II promoter, transcription initiation from RNA polymerase II promoter, transcription via serum response element binding, exit from mitosis, ubiquitin ligase activity during mitotic cell cycle, regulation of angiogenesis, apoptosis, cell growth, cell proliferation, cyclin-dependent protein kinase activity, gene expression, insulin secretion, steroid biosynthesis, transcription from RNA polymerase II promoter, transcription from RNA polymerase III promoter, cell cycle, cell migration, DNA recombination, and protein metabolism; also by CAMK1 negative functional regulation subnetwork including negative regulation of apoptosis, cell proliferation, centriole replication, fatty acid biosynthesis, lipoprotein lipase activity, MAPK activity, progression through cell cycle, transcription, transcription from RNA polymerase II promoter, cell growth, phosphorylation, and ubiquitin ligase activity during mitotic cell cycle in HCC.

High EGFR_1 Inside-Out Activated Inflammation-Induced Motility through SLC2A1-CCNB2-HMMR-KIF11-NUSAP1-PRC1-UBE2C

48 different Pearson mutual-positive-correlation epidermal growth factor receptor (EGFR_1)-activatory molecular feedback, up- and down-stream network was constructed from 171 overlapping of 366 GRNInfer and 223 Pearson under EGFR_1 CC ≥0.25 in high lung adenocarcinoma compared with low human normal adjacent tissues. Our identified EGFR_1 inside-out upstream activated molecular network showed SLC2A1 (solute carrier family 2 (facilitated glucose transporter) member 1), CCNB2 (cyclin B2), HMMR (hyaluronan-mediated motility receptor (RHAMM)), KIF11 (kinesin family member 11), NUSAP1 (nucleolar and spindle associated protein 1), PRC1 (protein regulator of cytokinesis 1), UBE2C (ubiquitin-conjugating enzyme E2C) in high lung adenocarcinoma. EGFR_1 inside-out upstream activated terms network includes intracellular, membrane fraction, cytoplasm, plasma membrane, integral to membrane, basolateral plasma membrane, transmembrane transport, nucleus, cytosol, cell surface; T cell homeostasis, inflammation; microtubule cytoskeleton, embryonic development (sensu Mammalia), cell cycle, mitosis, thymus development, cell division, regulation of cell cycle, Contributed--cellular process--Hs cell cycle KEGG, cytokinesis, M phase, M phase of mitotic cell cycle, estrogen-responsive protein Efp controls cell cycle and breast tumors growth, cell motility, locomotion, locomotory behavior, neoplasm metastasis, spindle pole, spindle microtubule, microtubule motor activity, microtubule-based movement, mitotic spindle organization and biogenesis, mitotic centrosome separation, spindle pole body organization and biogenesis, microtubule-based process, microtubule, cytokinesis after mitosis, mitotic chromosome condensation, establishment of mitotic spindle localization, positive regulation of mitosis, mitotic spindle elongation, spindle organization and biogenesis, positive regulation of exit from mitosis, regulation of cell proliferation, positive regulation of cell proliferation based on integrative GO, KEGG, GenMAPP, BioCarta and disease databases in high lung adenocarcinoma. Therefore, we propose high EGFR_1 inside-out activated inflammation-induced motility through SLC2A1-CCNB2-HMMR-KIF11-NUSAP1-PRC1-UBE2C in lung adenocarcinoma.

Low glucose transporter SLC2A5-inhibited human normal adjacent lung adenocarcinoma cytoplasmic pro-B cell development mechanism network

Solute carrier family 2 (facilitated glucose/fructose transporter) member 5 (SLC2A5)-inhibited seven different molecular Pearson mutual-positive-correlation networks constructed by 24 overlapping molecules from 368 GRNInfer and 34 Pearson under SLC2A5 CC ≤-0.25 in low human normal adjacent tissues were compared with high lung adenocarcinoma. Based on GO, KEGG, GenMAPP, BioCarta, and disease databases, our result showed that low SLC2A5-inhibited network included Golgi apparatus of AP1M2_1; cell cycle of CUL7, SAC3D1; protein amino acid dephosphorylation of STYXL1; pro-B cell-cell differentiation of SOX4_3; and FAD biosynthesis of FLAD1. Thus, we propose low glucose transporter SLC2A5-inhibited human normal adjacent lung adenocarcinoma cytoplasmic pro-B cell development mechanism network through repression of protein amino acid dephosphorylation to FAD biosynthesis.

BRCA1-mediated inflammation and growth activated & inhibited transition mechanisms between no-tumor hepatitis/cirrhotic tissues and HCC

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.

AGR2-mediated lung adenocarcinoma metastasis novel mechanism network through repression with interferon coupling cytoskeleton to steroid metabolism-dependent humoral immune response

7 anterior gradient homolog 2 (AGR2)-inhibited different molecular mutual positive correlation network was constructed in lung adenocarcinoma compared with human normal adjacent tissues by 17 overlapping molecules of 358 GRNInfer and 19 Pearson (AGR2 CC⩽-0.25). Based on GO, KEGG, GenMAPP, BioCarta and disease databases, we determined AGR2-mediated lung adenocarcinoma metastasis through repression with cytoskeleton of MAST1; steroid metabolism of SOAT2; humoral immune response of POU2AF1; interferon alpha-inducible of IFI6; immunoglobulin of IGKC_3, CTA_246H3.1. Thus we proposed AGR2-mediated lung adenocarcinoma metastasis novel mechanism network through repression with interferon coupling cytoskeleton to steroid metabolism-dependent humoral immune response.

Inhibited PTHLH downstream leukocyte adhesion-mediated protein amino acid N-linked glycosylation coupling Notch and JAK-STAT cascade to iron-sulfur cluster assembly-induced aging network in no-tumor hepatitis/cirrhotic tissues (HBV or HCV infection) by systems-theoretical analysis

We analyzed the different biological processes and occurrence numbers between low expression inhibited PTHLH downstream-mediated aging gene ontology (GO) network of no-tumor hepatitis/cirrhotic tissues (HBV or HCV infection) and the corresponding high expression (fold change ≥2) inhibited GO network of human hepatocellular carcinoma (HCC). Inhibited PTHLH downstream-mediated aging network consisted of aging, branched chain family amino acid biosynthesis, cellular metabolism, cholesterol biosynthesis, coupled to cyclic nucleotide second messenger, cytolysis, 'de novo' GDP-l-fucose biosynthesis, detection of mechanical stimulus, glucose homeostasis, G-protein signaling, leukocyte adhesion, iron-sulfur cluster assembly, JAK-STAT cascade, Notch signaling pathway, nucleotide-sugar metabolism, peptidyl-tyrosine sulfation, protein amino acid N-linked glycosylation, protein amino acid phosphorylation, response to drug, rRNA processing, translational initiation, ubiquitin-dependent protein catabolism, homophilic cell adhesion in no-tumor hepatitis/cirrhotic tissues. We proposed inhibited PTHLH downstream leukocyte adhesion-mediated protein amino acid N-linked glycosylation coupling Notch and JAK-STAT cascade to iron-sulfur cluster assembly-induced aging network. Our hypothesis was verified by the same inhibited PTHLH downstream-mediated aging GO network in no-tumor hepatitis/cirrhotic tissues with the corresponding activated GO network of HCC, or the different with the corresponding activated GO network of no-tumor hepatitis/cirrhotic tissues. Inhibited PTHLH downstream leukocyte adhesion-mediated protein amino acid N-linked glycosylation coupling Notch and JAK-STAT cascade to iron-sulfur cluster assembly-induced aging network included TSTA3, ALK, CIAO1, NOTCH3 in no-tumor hepatitis/cirrhotic tissues from the GEO data set using gene regulatory network inference method and our programming.

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

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.

Activated PTHLH coupling feedback phosphoinositide to G-protein receptor signal-induced cell adhesion network in human hepatocellular carcinoma by systems-theoretic analysis

Studies were done on analysis of biological processes in the same high expression (fold change ≥2) activated PTHLH feedback-mediated cell adhesion gene ontology (GO) network of human hepatocellular carcinoma (HCC) compared with the corresponding low expression activated GO network of no-tumor hepatitis/cirrhotic tissues (HBV or HCV infection). Activated PTHLH feedback-mediated cell adhesion network consisted of anaphase-promoting complex-dependent proteasomal ubiquitin-dependent protein catabolism, cell adhesion, cell differentiation, cell-cell signaling, G-protein-coupled receptor protein signaling pathway, intracellular transport, metabolism, phosphoinositide-mediated signaling, positive regulation of transcription, regulation of cyclin-dependent protein kinase activity, regulation of transcription, signal transduction, transcription, and transport in HCC. We proposed activated PTHLH coupling feedback phosphoinositide to G-protein receptor signal-induced cell adhesion network. Our hypothesis was verified by the different activated PTHLH feedback-mediated cell adhesion GO network of HCC compared with the corresponding inhibited GO network of no-tumor hepatitis/cirrhotic tissues, or the same compared with the corresponding inhibited GO network of HCC. Activated PTHLH coupling feedback phosphoinositide to G-protein receptor signal-induced cell adhesion network included BUB1B, GNG10, PTHR2, GNAZ, RFC4, UBE2C, NRXN3, BAP1, PVRL2, TROAP, and VCAN in HCC from GEO dataset using gene regulatory network inference method and our programming.

Tissue-specific transplantation antigen P35B (TSTA3) immune response-mediated metabolism coupling cell cycle to postreplication repair network in no-tumor hepatitis/cirrhotic tissues (HBV or HCV infection) by biocomputation

We constructed the low-expression tissue-specific transplantation antigen P35B (TSTA3) immune response-mediated metabolism coupling cell cycle to postreplication repair network in no-tumor hepatitis/cirrhotic tissues (HBV or HCV infection) compared with high-expression (fold change ≥ 2) human hepatocellular carcinoma in GEO data set, by using integration of gene regulatory network inference method with gene ontology analysis of TSTA3-activated up- and downstream networks. Our results showed TSTA3 upstream-activated CCNB2, CKS1B, ELAVL3, GAS7, NQO1, NTN1, OCRL, PLA2G1B, REG3A, SSTR5, etc. and TSTA3 downstream-activated BAP1, BRCA1, CCL20, MCM2, MS4A2, NTN1, REG1A, TP53I11, VCAN, SLC16A3, etc. in no-tumor hepatitis/cirrhotic tissues. TSTA3-activated network enhanced the regulation of apoptosis, cyclin-dependent protein kinase activity, cell migration, insulin secretion, transcription, cell division, cell proliferation, DNA replication, postreplication repair, cell differentiation, T-cell homeostasis, neutrophil-mediated immunity, neutrophil chemotaxis, interleukin-8 production, inflammatory response, immune response, B-cell activation, humoral immune response, actin filament organization, xenobiotic metabolism, lipid metabolism, phospholipid metabolism, leukotriene biosynthesis, organismal lipid catabolism, phosphatidylcholine metabolism, arachidonic acid secretion, activation of phospholipase A2, deoxyribonucleotide biosynthesis, heterophilic cell adhesion, activation of MAPK activity, signal transduction by p53 class mediator resulting in transcription of p21 class mediator, G-protein-coupled receptor protein signaling pathway, response to toxin, acute-phase response, DNA damage response, intercellular junction assembly, cell communication, and cell recognition, as a result of inducing immune response-mediated metabolism coupling cell cycle to postreplication repair in no-tumor hepatitis/cirrhotic tissues.

Data mining in networks of differentially expressed genes during sow pregnancy

Small to moderate gains in Pig fertility can mean large returns in overall efficiency, and developing methods to improve it is highly desirable. High fertility rates depend on completion of successful pregnancies. To understand the molecular signals associated with pregnancy in sows, expression profiling experiments were conducted to identify differentially expressed genes in ovary and myometrium at different pregnancy periods using the Affymetrix Porcine GeneChip^TM. A total of 974, 1800, 335 and 710 differentially expressed transcripts were identified in the myometrium during early pregnancy (EP) and late pregnancy (LP), and in the ovary during EP and LP, respectively. Self-Organizing Map (SOM) clusters indicated the differentially expressed genes belonged to 7 different functional groups. Based on BLASTX searches and Gene Ontology (GO) classifications, 129 unique genes closely related to pregnancy showed differential expression patterns. GO analysis also indicated that there were 21 different molecular function categories, 20 different biological process categories, and 8 different cellular component categories of genes differentially expressed during sow pregnancy. Gene regulatory network reconstruction provided us with an interaction model of known genes such as insulin-like growth factor 2 (IGF2) gene, estrogen receptor (ESR) gene, retinol-binding protein-4 (RBP4) gene, and several unknown candidate genes related to reproduction. Several pitch point genes were selected for association study with reproduction traits. For instance, DPPA5 g.363 T>C was found to associate with litter born weight at later parities in Beijing Black pigs significantly (p < 0.05). Overall, this study contributes to elucidating the mechanism underlying pregnancy processes, which maybe provide valuable information for pig reproduction improvement.

Glycogen debranching enzyme 6 (AGL), enolase 1 (ENOSF1), ectonucleotide pyrophosphatase 2 (ENPP2_1), glutathione S-transferase 3 (GSTM3_3) and mannosidase (MAN2B2) metabolism computational network analysis between chimpanzee and human left cerebrum

We identified significantly higher expression of the genes glycogen debranching enzyme 6 (AGL), enolase 1 (ENOSF1), ectonucleotide pyrophosphatase 2 (ENPP2_1), glutathione S-transferase 3 (GSTM3_3) and mannosidase (MAN2B2) from human left cerebrums versus chimpanzees. Yet the distinct low- and high-expression AGL, ENOSF1, ENPP2_1, GSTM3_3 and MAN2B2 metabolism networks between chimpanzee and human left cerebrum remain to be elucidated. Here, we constructed low- and high-expression activated and inhibited upstream and downstream AGL, ENOSF1, ENPP2_1, GSTM3_3 and MAN2B2 metabolism network between chimpanzee and human left cerebrum in GEO data set by gene regulatory network inference method based on linear programming and decomposition procedure, under covering AGL, ENOSF1, ENPP2_1, GSTM3_3 and MAN2B2 pathway and matching metabolism enrichment analysis by CapitalBio MAS 3.0 integration of public databases, including Gene Ontology, KEGG, BioCarta, GenMapp, Intact, UniGene, OMIM, etc. Our results show that the AGL, ENOSF1, ENPP2_1, GSTM3_3 and MAN2B2 metabolism network has more activated and less inhibited molecules in chimpanzee, but less activated and more inhibited in the human left cerebrum. We inferred stronger carbohydrate, glutathione and proteoglycan metabolism, ATPase activity, but weaker base excision repair, arachidonic acid and drug metabolism as a result of inducing cell growth in low-expression AGL, ENOSF1, ENPP2_1, GSTM3_3 and MAN2B2 metabolism network of chimpanzee left cerebrum; whereas stronger lipid metabolism, amino acid catabolism, DNA repair but weaker inflammatory response, cell proliferation, glutathione and carbohydrate metabolism as a result of inducing cell differentiation in high-expression AGL, ENOSF1, ENPP2_1, GSTM3_3 and MAN2B2 metabolism network of human left cerebrum. Our inferences are consistent with recent reports and computational activation and inhibition gene number patterns, respectively.

Survivin (BIRC5) cell cycle computational network in human no-tumor hepatitis/cirrhosis and hepatocellular carcinoma transformation

Survivin (BIRC5) relationship with tumor is presented in several papers. However, how the molecular network and interpretation concerning BIRC5 cell cycle between no-tumor hepatitis/cirrhosis and hepatocellular carcinoma (HCC) remains to be elucidated. Here, we constructed and analyzed significant higher expression gene BIRC5 activated and inhibited cell cycle network from HCC versus no-tumor hepatitis/cirrhosis patients (viral infection HCV or HBV) in GEO Dataset by combination of gene regulatory network inference method based on linear programming and decomposition procedure with the CapitalBio MAS 3.0 software based on the integration of public databases including Gene Ontology, KEGG, BioCarta, GenMapp, Intact, UniGene, OMIM, etc. Compared the same and different activated and inhibited BIRC5 network with GO analysis between no-tumor hepatitis/cirrhosis and HCC, our result showed BIRC5 cell cycle network weaker transcription factor activity in both no-tumor hepatitis/cirrhosis and HCC (1); stronger nucleus protein binding but weaker cytoplasm protein binding in no-tumor hepatitis/cirrhosis (2); stronger cytoplasm protein phosphatase binding but weaker ubiquitin-protein ligase activity in HCC (3). Therefore, we inferred BIRC5 cell cycle module less transcription from RNA polymerase II promoter in both no-tumor hepatitis/cirrhosis and HCC (4). We deduced BIRC5 cell cycle module different from more mitosis but less complex-dependent proteasomal ubiquitin-dependent protein catabolism as a result increasing cell division and cell numbers in no-tumor hepatitis/cirrhosis to more protein amino acid autophosphorylation but less negative regulation of ubiquitin ligase activity during mitotic cell cycle as a result increasing growth and cell volume in HCC (5).

Cyclin-dependent kinase inhibitor 3 (CDKN3) novel cell cycle computational network between human non-malignancy associated hepatitis/cirrhosis and hepatocellular carcinoma (HCC) transformation

The relationship of cyclin-dependent kinase inhibitor 3 (CDKN3) with tumours has previously been presented in a number of publications. However, the molecular network and interpretation of CDKN3 through the cell cycle between non-malignancy associated hepatitis/cirrhosis and hepatocellular carcinoma (HCC) have remained to be elucidated. Here, we have constructed and analysed significant high expression gene CDKN3 activated and inhibited cell cycle networks from 25 HCC versus 25 non-malignancy associated hepatitis/cirrhosis patients (viral infection HCV or HBV) in GEO Dataset GSE10140-10141, by combination of a gene regulatory network inference method based on linear programming, and decomposition procedure using CapitalBio MAS 3.0 software, based on integration of public databases including Gene Ontology, KEGG, BioCarta, GenMapp, Intact, UniGene, OMIM, and others. Comparing the same and differently activated and inhibited CDKN3 networks with GO analysis, between non-malignancy associated hepatitis/cirrhosis and HCC, our results suggest a CDKN3 cell cycle network (i) with stronger DNA replication and with weaker ubiquitin-dependent protein catabolism as common characteristics in both non-malignancy associated hepatitis/cirrhosis and HCC; (ii) with more cell division and weaker mitotic G2 checkpoint in non-malignancy associated hepatitis/cirrhosis; (iii) with stronger cell cycle and weaker cytokinesis, as a result forming multinucleate cells in HCC. Thus, it is useful to identify CDKN3 cell cycle networks for comprehension of molecular mechanism between non-malignancy associated hepatitis/cirrhosis and HCC transformation.