Reinvestigating the Synthesis and Characterization of Ethyl 3‑[5-(2-Ethoxycarbonyl-1-methylvinyloxy)-1-methyl‑1<i>H</i>‑indol-3-yl]-but-2-enoate

We reinvestigated the reported method for the synthesis of ethyl 3-[5-(2-ethoxycarbonyl-1-methylvinyloxy)-1-methyl-1H-indol-3-yl]-but-2-enoate (MIBE), which was obtained by the reaction of 5-hydroxy-1-methyl-1H-indole with excess ethyl acetoacetate catalyzed by indium­(III) chloride. Based on the NMR and MS data, we assigned the structure of the isolated product as (3E)-3-(2-ethoxy-2-oxoethylidene)-1,2,3,4-tetrahydro-7-hydroxy-1,4-dimethylcyclopent­[b]­indole-1-acetate (2a) rather than the reported MIBE

Demonstration of the DEABM to reproduce expected patterns of luminal cell growth in response to estrogen and progesterone within a menstrual cycle.

<p>Panel A depicts the output of the DEABM in terms of differentiated luminal cell population during the course of a single menstrual cycle period. The individual runs (n = 5) are depicted in light grey dashed plots and demonstrate the inter-run variance expected from the stochastic nature of the DEABM. The average of these runs is seen in the solid black line, and reproduces the expected increase in luminal cell mass seen during the luteal phase. The general trajectory of the DEABM seen in Panel A is noted to be similar to reference data sets present in the literature, as seen in Panel B (reproduced with under the Creative Commons License from Ref <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0064091#pone.0064091-Navarrete1" target="_blank">[42]</a>) and Panel C (reproduced with permission from Ref <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0064091#pone.0064091-Going1" target="_blank">[43]</a>); both of which depict the degree of luminal cell proliferation during various phases of the menstrual cycle. Note in particular the wide variance in the sample points present in the reference data sets, which represent multiple samples obtained from multiple individuals.</p

Examining the Pathogenesis of Breast Cancer Using a Novel Agent-Based Model of Mammary Ductal Epithelium Dynamics

<div><p>The study of the pathogenesis of breast cancer is challenged by the long time-course of the disease process and the multi-factorial nature of generating oncogenic insults. The characterization of the longitudinal pathogenesis of malignant transformation from baseline normal breast duct epithelial dynamics may provide vital insight into the cascading systems failure that leads to breast cancer. To this end, extensive information on the baseline behavior of normal mammary epithelium and breast cancer oncogenesis was integrated into a computational model termed the <u>D</u>uctal <u>E</u>pithelium <u>A</u>gent-<u>B</u>ased <u>M</u>odel (DEABM). The DEABM is composed of computational agents that behave according to rules established from published cellular and molecular mechanisms concerning breast duct epithelial dynamics and oncogenesis. The DEABM implements DNA damage and repair, cell division, genetic inheritance and simulates the local tissue environment with hormone excretion and receptor signaling. Unrepaired DNA damage impacts the integrity of the genome within individual cells, including a set of eight representative oncogenes and tumor suppressors previously implicated in breast cancer, with subsequent consequences on successive generations of cells. The DEABM reproduced cellular population dynamics seen during the menstrual cycle and pregnancy, and demonstrated the oncogenic effect of known genetic factors associated with breast cancer, namely <i>TP53</i> and <i>Myc</i>, in simulations spanning ∼40 years of simulated time. Simulations comparing normal to <i>BRCA1</i>-mutant breast tissue demonstrated rates of invasive cancer development similar to published epidemiologic data with respect to both cumulative incidence over time and estrogen-receptor status. Investigation of the modeling of ERα-positive (ER+) tumorigenesis led to a novel hypothesis implicating the transcription factor and tumor suppressor <i>RUNX3</i>. These data suggest that the DEABM can serve as a potentially valuable framework to augment the traditional investigatory workflow for future hypothesis generation and testing of the mechanisms of breast cancer oncogenesis.</p></div

Set of included representative “genes” and their relationship to cellular behaviors and general functions within the DEABM.

<p>As the representational focus of the DEABM is on characterizing the functional dynamics associated with oncogenesis, potentially detrimental “genes” have been included on their known influences on those functions that are plausibly involved and altered in the process of tumorigenesis. Additionally, the arrows are intended to represent known direct regulatory effects; it is expected that there are many second and third order effects that might lead a named gene to affect other downstream behaviors. *Note that the labeling of these “genes” is not intended to be a comprehensive description of all the known effects of the named genes, but rather to label certain putative cellular behaviors possibly involved in malignant transformation.</p

Reproduction of ER tumor status in both wild-type/sporadic and BRCA1 mutated populations of breast cancer.

<p>These data demonstrate the similarity between DEABM simulation runs and data extracted from the literature concerning the percentage of ER+ tumors generated in both wild-type/sporadic and BRCA1-mutated populations <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0064091#pone.0064091-Easton1" target="_blank">[46]</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0064091#pone.0064091-Tung1" target="_blank">[57]</a>. Panel A depicts the ER+ percentage among wild-type/sporadic populations from both the literature, ∼68% (range 60–77%) of premenopausal breast tumors <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0064091#pone.0064091-Atchley1" target="_blank">[51]</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0064091#pone.0064091-Haffty1" target="_blank">[54]</a>, and in simulated populations (n-individuals = 500, N-groups = 3) of ∼65% (range 59–71%) of the simulated breast cancers. Panel B demonstrates the same comparison of ER+ tumors in the <i>BRCA1</i> mutant population, where the DEABM shows that only ∼38% (range 29–44%) of tumors generated were ER+ as compared to published incidences of ER+ <i>BRCA1</i> mutant tumors of ∼36% (range 19–52%) <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0064091#pone.0064091-Atchley1" target="_blank">[51]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0064091#pone.0064091-Lee1" target="_blank">[55]</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0064091#pone.0064091-Tung1" target="_blank">[57]</a>. For both Panel A and B published cancer population data is denoted by the name of the study’s first author, whereas the DEABM runs are labeled with their N-group number. These findings indicate that the DEABM incorporates plausible mechanisms for ER+ tumorigenesis, suggesting a role of <i>RUNX3</i> expression (or other genes performing a similar function) in the selectivity of ER+ breast cancer previously unknown.</p

Post-calibration behavior of the DEABM reproducing baseline, normal breast epithelial dynamics.

<p>These graphs demonstrate the ability of the DEABM to generate recognizable fluctuations in luminal cell mass during normal menses (Letter A), demonstrating the first stage of the face validity of the DEABM in being able to reproduce self-sustaining cellular population without evidence of unconstrained growth. Furthermore, the DEABM was also able to reproduce expected alterations in luminal cell population dynamics associated with pregnancy, initiation depicted by red arrow (Letter B). These data.</p

ERβ negatively regulates cell proliferation in an E2 dependent-manner.

<p>C4–12/Flag.ERβ cells were treated with 10 nM E2 for 3 days. Cell confluency, detected by the Incucyte FLR live content imaging system (Essen Bioscience), was used to measure cell proliferation. Bar graph represents fold change relative to day 0. (Error bar = standard deviation).</p

Representative genes and their functions incorporated in the DEABM.

<p>Representative genes and their functions incorporated in the DEABM.</p

Schematic of control logic concerning DNA damage, repair and functional consequences of unrepaired DNA damage within the DEABM.

<p>A baseline premise of the DEABM is that DNA damage can occur during a luminal epithelial cell’s life-time, and that damage that remains unrepaired by the time the cell is to divide can be passed on as a mutation, a certain subset of which may affect a critical cellular function that may influence tumorigenesis. The DEABM incorporates abstract representations of DNA damage, damage repair, senescence, apoptosis and passage of mutations to subsequent cellular generations.</p

Agent classes and their associated variables.

<p>Agent classes and their associated variables.</p