Acidic pH activates the UPR pathway and enhances EGF-SubA cytotoxicity.

<p>U251 cells grown in RPMI media whose pH was adjusted to 6.7 and 7.0 with 1N HCl for 3 passages prior to performing experiments demonstrated UPR activation, as determined by PERK phosphorylation (A; pPERK), Xbp1 splicing and increased GRP78 transcription (B). (C) To determine if cells grown in acidic conditions influenced EGF-SubA cytotoxicity, a clonogenic assay was performed with U251 cells grown in normal (pH 7.4) or acidic (pH 6.7) conditions at the stated concentrations. Cell survival was significantly different between cells grown in normal and acidic pH at higher doses of EGF SubA (p<0.0001 at 2.5 pM). Each figure is a representative of three independent experiments.</p

GRP78 expression in glioma.

<p>Immunohistochemical staining was performed on a glioma tissue microarray using an anti-GRP78 antibody and expression levels (0, 1+, 2+, and 3+) were quantified based on the intensity of staining. Representative staining patterns (A) and tumor grade-specific distributions of identified staining intensities (B) are provided.</p

SubA and EGF-SubA cleaves GRP78 and activates the UPR.

<p>Exponentially growing glioblastoma cell lines and normal human astrocytes (NHA) were (A) treated with SubA or EGF-SubA at the specified picomolar concentrations for 24 h or (B) exposed EGF-SubA (1 pM) for the specified time periods. Total cellular protein was isolated and immunoblotting was performed with anti-GRP78 antibody. SubA and EGF-SubA cleaved the endogenous GRP78 (78 kDa) resulting in an additional smaller fragment of 28 kDa (cGRP78). (C-E) Total cellular protein and RNA were isolated from U251 cells exposed to EGF-SubA at the stated concentrations for 24 h. EGF-SubA induced GRP78 cleavage resulted in nuclear localization of ATF6 (C; nATF6), a dose-dependent phosphorylation of PERK (D; pPERK), and Ire1 activation, determined by Xbp1 mRNA splicing (E). Each figure is a representative of three independent experiments.</p

EGF-SubA enhances anti-tumor activity of temozolomide and ionizing radiation.

<p>A clonogenic assay was performed to evaluate the potential of EGF-SubA to enhance temozolomide (A) (statistically significant p<0.0001) and radiation-induced (B) cytotoxicity (statistically significant p<0.0024). U251 cells were seeded in six well culture plates and exposed to 1 pM of EGF-SubA 16 h prior to the addition of temozolomide or radiation exposure. Fresh media was then replaced in the culture plates after 8 h, and surviving fractions were calculated 10 to 14 d following treatment, normalizing for the individual cytotoxicity of EGF-SubA. Each figure is a representative of three independent experiments.</p

EGF-SubA delays tumor growth in mice.

<p>U251 cells were injected s.c in a mouse flank model (A). When tumors reached ∼150 mm³ in size, mice were randomized into two groups: vehicle control (PBS) or EGF-SubA (125 µg/kg) delivered s.c. on the stated days (arrow). To obtain a tumor growth curve, perpendicular diameter measurements of each tumor were measured with digital calipers, and volumes were calculated using the formula (<i>L</i> × <i>W</i> × <i>W</i>)/2. Tumor volumes (A) and weight of mice (B) were measured every other day. Tumor volumes were normalized to their volume at randomization. Each group contained six mice. *<i>p</i> = 0.0009. (C) U251 cells were injected s.c. in a mouse flank model. When tumors reached ∼500 mm³ in size, mice were exposed to either PBS alone or EGF-SubA (125 µg/kg). Mice were then sacrificed 24 h after treatment and stated tissue was dissected, flash frozen, and tissue lysates were generated to evaluate for GRP78 cleavage by immunoblot.</p

Microenvironmental Variables Must Influence Intrinsic Phenotypic Parameters of Cancer Stem Cells to Affect Tumourigenicity

<div><p>Since the discovery of tumour initiating cells (TICs) in solid tumours, studies focussing on their role in cancer initiation and progression have abounded. The biological interrogation of these cells continues to yield volumes of information on their pro-tumourigenic behaviour, but actionable generalised conclusions have been scarce. Further, new information suggesting a dependence of tumour composition and growth on the microenvironment has yet to be studied theoretically. To address this point, we created a hybrid, discrete/continuous computational cellular automaton model of a generalised stem-cell driven tissue with a simple microenvironment. Using the model we explored the phenotypic traits inherent to the tumour initiating cells and the effect of the microenvironment on tissue growth. We identify the regions in phenotype parameter space where TICs are able to cause a disruption in homeostasis, leading to tissue overgrowth and tumour maintenance. As our parameters and model are non-specific, they could apply to any tissue TIC and do not assume specific genetic mutations. Targeting these phenotypic traits could represent a generalizable therapeutic strategy across cancer types. Further, we find that the microenvironmental variable does not strongly affect the outcomes, suggesting a need for direct feedback from the microenvironment onto stem-cell behaviour in future modelling endeavours.</p></div

Cartoon representing the hierarchical model of stem-cell driven tissues.

<p>In this formulation, each stem can undergo two types of division, either symmetric (with probability ) or asymmetric (with probability ). Each subsequently generated transient amplifying cell (TAC) can then undergo a certain number () of round of amplification before differentiating into a terminally differentiated cell (TD) which will live for a certain amount of time before dying ( timesteps). It is these three parameters, which we assume are intrinsic to a given stem cell, which we explore in this paper.</p

The three qualitatively different tissue scale phenotypes plotted as cell numbers over time for the example simulations in figure 4.

<p>The black trace, representing the unsustainable simulation, grows quickly though never expands its stem population and then outstrips the available oxygen and collapses. The blue trace, representing the homeostatic simulation, reaches a critical size and then maintains a steady birth-death balance. The red trace, representing the tumorigenic simulation, settles into an effectively linear trace on this log-log plot, suggesting power law growth.</p

Size of tissues vs. progenitor proliferative potential achieved by simulations using different levels of vascularisation and rates of symmetric vs. asymmetric divisions.

<p>Lines represent averages for each of the three realisations in each scenario. (Left). Low vascularisation density of 0.01 (Centre) Normal vascularisation density of 0.05 (Right) High vascularisation density of 0.1. In each of these cases, the maximum tissue size will depend on the right combination of and .</p

Model parameters.

<p>Model parameters.</p