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Biology subjects

Ishitsuka, M.

Publications and source records attributed to Ishitsuka, M..

2 recordsLinked to original sources

Sodium butyrate inhibits the proliferation of temozolomide-resistant glioblastoma (A172) and lung adenocarcinoma (A549) cells and biphasically regulates EGFR expression

Glioblastoma carries one of the poorest prognoses of any solid tumour, and once resistance to temozolomide (TMZ) emerges there is little left to offer. Because the TMZ response is governed largely by epigenetic silencing of MGMT, histone deacetylase (HDAC) inhibitors are a rational partner for TMZ. We asked whether sodium butyrate (NaB), a short-chain fatty acid produced by the gut microbiota and a class I/IIa HDAC inhibitor, retains activity against TMZ-resistant cells. In A172 glioblastoma and A549 lung adenocarcinoma cells, NaB changed EGFR expression biphasically: EGFR exon 2-5 mRNA was induced at 0.15 mM in A172 and at 0.30 mM in A549, and was suppressed at higher concentrations, with EGFR protein following the same pattern in A172. NaB reduced proliferation of both lines from 0.31 mM in a concentration-dependent manner, more markedly in A172 than in A549. At concentrations that were inactive alone (NaB 0.30 mM, TMZ 3 {micro}M), the combination inhibited proliferation of A172 on day 3 and of A549 on days 2 and 3. TMZ-resistant sublines (A172 rTMZ, A549 rTMZ) established by stepwise exposure showed no response to TMZ 10 {micro}M alone, but NaB at 0.5 and 2.5 mM inhibited their proliferation concentration-dependently. The ratio of combination to TMZ alone was not lower in the resistant sublines than in the parental lines (A172 0.70 vs 0.86; A549 0.49 vs 0.58), indicating that the effect in resistant cells is attributable to NaB itself rather than to restored TMZ sensitivity. Millimolar exposure is the main barrier to translation.

molecular biology↗

Network controllability: viruses are driver agents in dynamic molecular systems

In recent years control theory has been applied to biological systems with the aim of identifying the minimum set of molecular interactions that can drive the network to a required state. However in an intra-cellular network it is unclear what control means. To address this limitation we use viral infection, specifically HIV-1 and HCV, as a paradigm to model control of an infected cell. Using a large human signalling network comprised of over 6000 human proteins and more than 34000 directed interactions, we compared two dynamic states: normal/uninfected and infected. Our network controllability analysis demonstrates how a virus efficiently brings the dynamic host system into its control by mostly targeting existing critical control nodes, requiring fewer nodes than in the uninfected network. The driver nodes used by the virus are distributed throughout the pathways in specific locations enabling effective control of the cell via the high control centrality of the viral and targeted host nodes. Furthermore, this viral infection of the human system permits discrimination between available network-control models, and demonstrates the minimum-dominating set (MDS) method better accounts for how biological information and signals are transferred than the maximum matching (MM) method as it identified most of the HIV-1 proteins as critical driver nodes and goes beyond identifying receptors as the only critical driver nodes. This is because MDS, unlike MM, accounts for the inherent non-linearity of signalling pathways. Our results demonstrate control-theory gives a more complete and dynamic understanding of the viral hijack mechanism when compared with previous analyses limited to static single-state networks.

systems biology↗