Application of Structure Equation Modeling for Inferring a Serial Transcriptional Regulation in Yeast

Revealing the gene regulatory systems among DNA and proteins in living cells is one of the central aims of systems biology. In this study, I used Structural Equation Modeling (SEM) in combination with stepwise factor analysis to infer the protein-DNA interactions for gene expression control from only gene expression profiles, in the absence of protein information. I applied my approach to infer the causalities within the well-studied serial transcriptional regulation composed of GAL-related genes in yeast. This allowed me to reveal the hierarchy of serial transcriptional regulation, including previously unclear protein-DNA interactions. The validity of the constructed model was demonstrated by comparing the results with previous reports describing the regulation of the transcription factors. Furthermore, the model revealed combinatory regulation by Gal4p and Gal80p. In this study, the target genes were divided into three types: those regulated by one factor and those controlled by a combination of two factors

Development of a novel small antibody that retains specificity for tumor targeting

<p>Abstract</p> <p>Background</p> <p>For the targeted therapy of solid tumor mediated by monoclonal antibody (mAb), there have different models of rebuilding small antibodies originated from native ones. Almost all natural antibody molecules have the similar structure and conformation, but those rebuilt small antibodies cannot completely keep the original traits of parental antibodies, especially the reduced specificity, which gravely influences the efficacy of small antibodies.</p> <p>Methods</p> <p>In this study, authors developed a novel mimetic in the form of V_HFR1_C-10-V_HCDR1-V_HFR2-V_LCDR3-V_LFR4_N-10for a parental mAb induced with human breast cancer, and the mimetic moiety was conjugated to the C-terminal of toxicin colicin Ia. The novel fusion peptide, named protomimecin (PMN), was administered to MCF-7 breast cancer cells to demonstrate its killing competency <it>in vitro </it>and <it>in vivo</it>.</p> <p>Results</p> <p>Compared with original antibody-colicin Ia (Fab-Ia) and single-chain antibody-colicin Ia (Sc-Ia) fusion proteins, PMN retained the targeting specificity of parental antibody and could specifically kill MCF-7 cells <it>in vitro</it>. By injecting intraperitoneally into BALB/c athymic mice bearing MCF-7 tumors, with reduced affinity, PMN significantly suppressed the growth of tumors compared with control mice treated by toxicin protein, Fab-Ia protein, Sc-Ia protein or by PBS (<it>p </it>< 0.05).</p> <p>Conclusion</p> <p>This novel mimetic antibody retained original specificity of parental antibody, and could effectively guide killer moiety to suppress the growth of breast cancer by targeted cell death.</p

Increased mRNA expression levels of ERCC1, OGG1 and RAI in colorectal adenomas and carcinomas

BACKGROUND: The majority of colorectal cancer (CRC) cases develop through the adenoma-carcinoma pathway. If an increase in DNA repair expression is detected in both early adenomas and carcinomas it may indicate that low repair capacity in the normal mucosa is a risk factor for adenoma formation. METHODS: We have examined mRNA expression of two DNA repair genes, ERCC1 and OGG1 as well as the putative apoptosis controlling gene RAI, in normal tissues and lesions from 36 cases with adenomas (mild/moderat n = 21 and severe n = 15, dysplasia) and 9 with carcinomas. RESULTS: Comparing expression levels of ERCC1, OGG1 and RAI between normal tissue and all lesions combined yielded higher expression levels in lesions, 3.3-fold higher (P = 0.005), 5.6-fold higher(P < 3·10(-5)) and 7.7-fold higher (P = 0.0005), respectively. The levels of ERCC1, OGG1 and RAI expressions when comparing lesions, did not differ between adenomas and CRC cases, P = 0.836, P = 0.341 and P = 0.909, respectively. When comparing expression levels in normal tissue, the levels for OGG1 and RAI from CRC cases were significantly lower compared to the cases with adenomas, P = 0.012 and P = 0.011, respectively. CONCLUSION: Our results suggest that increased expression of defense genes is an early event in the progression of colorectal adenomas to carcinomas

Targeting of mutant hogg1 in mammalian mitochondria and nucleus: effect on cellular survival upon oxidative stress

BACKGROUND: Oxidative damage to mitochondrial DNA has been implicated as a causative factor in a wide variety of degenerative diseases, aging and cancer. The modified guanine, 7,8-dihydro-8-oxoguanine (also known as 8-hydroxyguanine) is one of the major oxidized bases generated in DNA by reactive oxygen species and has gained most of the attention in recent years as a marker of oxidative DNA injury and its suspected role in the initiation of carcinogenesis. 8-hydroxyguanine is removed by hOgg1, a DNA glycosylase/AP lyase involved in the base excision repair pathway. METHODS: We over-expressed wild type and R229Q mutant hOGG1 in the nucleus and mitochondria of cells lacking mitochondrial hOGG1 expression through an expression vector containing nuclear and mitochondrial targeting sequence respectively. We used quantitative real time PCR to analyze mtDNA integrity after exposure to oxidative damaging agents, in cells transfected with or without mitochondrially-targeted mutant hogg1. RESULT: Over-expression of wild type hOgg1 in both nucleus and mitochondria resulted in increased cellular survival when compared to vector or mutant over-expression of hOGG1. Interestingly, mitochondrially-targeted mutant hogg1 resulted in more cell death than nuclear targeted mutant hogg1 upon exposure of cells to oxidative damage. Additional we examined mitochondrial DNA integrity after oxidative damage exposure using real-time quantitative PCR. The presence of mutant hogg1 in the mitochondria resulted in reduced mitochondrial DNA integrity when compared to the wild type. Our work indicates that the R229Q hOGG1 mutation failed to protect cells from oxidative damage and that such mutations in cancer may be more detrimental to cellular survival when present in the mitochondria than in the nucleus. CONCLUSION: These findings suggest that deficiencies in hOGG1, especially in the mitochondria may lead to reduced mitochondrial DNA integrity, consequently resulting in decreased cell viability

Gene set-based module discovery in the breast cancer transcriptome

<p>Abstract</p> <p>Background</p> <p>Although microarray-based studies have revealed global view of gene expression in cancer cells, we still have little knowledge about regulatory mechanisms underlying the transcriptome. Several computational methods applied to yeast data have recently succeeded in identifying expression modules, which is defined as co-expressed gene sets under common regulatory mechanisms. However, such module discovery methods are not applied cancer transcriptome data.</p> <p>Results</p> <p>In order to decode oncogenic regulatory programs in cancer cells, we developed a novel module discovery method termed EEM by extending a previously reported module discovery method, and applied it to breast cancer expression data. Starting from seed gene sets prepared based on <it>cis</it>-regulatory elements, ChIP-chip data, and gene locus information, EEM identified 10 principal expression modules in breast cancer based on their expression coherence. Moreover, EEM depicted their activity profiles, which predict regulatory programs in each subtypes of breast tumors. For example, our analysis revealed that the expression module regulated by the Polycomb repressive complex 2 (PRC2) is downregulated in triple negative breast cancers, suggesting similarity of transcriptional programs between stem cells and aggressive breast cancer cells. We also found that the activity of the PRC2 expression module is negatively correlated to the expression of EZH2, a component of PRC2 which belongs to the E2F expression module. E2F-driven EZH2 overexpression may be responsible for the repression of the PRC2 expression modules in triple negative tumors. Furthermore, our network analysis predicts regulatory circuits in breast cancer cells.</p> <p>Conclusion</p> <p>These results demonstrate that the gene set-based module discovery approach is a powerful tool to decode regulatory programs in cancer cells.</p