Yitong (Pepper) Huang, Northwestern University

• Title: Theoretical considerations for circadian medicine
• Abstract: What effect sizes should we expect from circadian medicine? With limited data on dosing around the clock, coupled with minimal controls for interindividual variability in the real world, solid insights into how much timing actually matters for medicine can be hard to come by. Yet with computational techniques and mathematical modeling, we can begin to build an intuition for the conditions under which timing should and should not play an important role, as well as how factors such as pharmacokinetics, target availability, and therapeutic window may interact with endogenous rhythms in the body. In this presentation, I will show a theoretical framework for circadian medicine and map simulations derived from this framework to real world drug timing data.

Rupleen Kaur, Case Western Reserve University

• Title: Astrocyte reprogramming enhances tumor growth and recapitulates chemoresistance in agent-based models of breast cancer brain metastases
• Abstract: Breast cancer brain metastases (BCBM) affect nearly 90,000 patients with breast cancer in the United States annually and carry a significant risk of mortality. As metastatic lesions develop, the unique milieu of the brain microenvironment shapes disease progression and therapeutic response, but the contribution of astrocytes to metastasis formation and treatment response is not well understood.

  Using a computational model for tumor growth, we simulated BCBM formation and astrocyte behavior on a 2D lattice. In our model, tumor cells convert astrocytes from anti- to pro-metastatic, which in turn increases the division rate of tumor cells. We simulated chemotherapy and radiotherapy treatment to examine tumor growth dynamics across different astrocyte distributions, conversion rates, and dosing schedules.

  Our results showed that the reprogramming of astrocytes led to an increased tumor growth rate and recapitulates chemoresistance. As a result, our model predicts greater anti-tumor effects from radiotherapy due to its deleterious effects on both tumor cells and astrocytes, with the gain in efficacy varying based on underlying astrocyte density. This suggests a potential differential effect of radiotherapy in regions of brain with varying astrocyte densities. Our model suggests that inhibiting conversion of astrocytes from anti- to pro-metastatic, when combined with radiotherapy and chemotherapy, enhances tumor control, especially in regions of high astrocyte density.

  In sum, our findings highlight that astrocyte reprogramming promotes tumor growth and recapitulates chemoresistance, suggesting that tailoring radiotherapy to underlying astrocyte density and targeting astrocyte conversion with specific inhibitors could enhance treatment outcomes in breast cancer brain metastases.

Eli Newby, Cleveland Clinic

• Title: Comparative analysis of miRNA-target networks to identify key oncologic drivers and therapeutic targets
• Abstract: MicroRNAs (miRNAs) are key post-transcriptional regulators of gene expression, primarily targeting mRNA for degradation, which makes them strong genetic regulators. Unfortunately, their effects on a cell’s function are context-dependent, and these exact mechanisms are not well understood. Specifically, in some cases, the dysregulation of miRNA pathways has been linked to the emergence of cancers, but how this dysregulation affects the complex system of miRNA-mRNA interactions is unknown. We study these complex functions and their emergent properties by constructing an array of bipartite miRNA-mRNA target networks. These networks are constructed from TCGA data of various cancerous cell types and their adjacent normal cells and are filtered using a known, validated database of miRNA targets (miRTarBase). Analysis and comparisons of these networks revealed sub-networks of miRNAs that are uniquely important in each cancer type while also having a low importance in surrounding normal tissue. The identified miRNA sub-networks are predicted to be important drivers of their respective cancer type and, thus, are excellent candidates for novel therapeutic targets.

Hannah Scanlon, Duke University

• Title: Multiscale modeling of microtubule polarity mechanisms following neuronal axotomy
• Abstract: Microtubules are dynamic intracellular filaments which provide structure to cells and facilitate cargo transport. In a healthy neuron, various mechanisms maintain a strict polarity distribution of microtubules throughout the lifetime of the cell. In the case of axon severing in neurons in the peripheral nervous system, microtubules can rearrange dramatically to localize cellular cargo and facilitate axonal regeneration. While several mechanisms have been hypothesized to regulate microtubule organization, they are difficult to verify experimentally. Motivated by experiments in model organisms such as fruit flies and sea slugs, we use multi-scale mathematical modeling to investigate microtubule dynamics and cargo localization behavior. The goal of this work is to identify what cellular mechanisms are necessary and sufficient to facilitate the observed microtubule reorganization and protein accumulations in neuronal regeneration.

Ayalur Raghu Subbalakshmi, City of Hope National Medical Center

• Title: The ELF3 transcription factor is associated with an epithelial phenotype and repressesepithelial-mesenchymal transition
• Abstract: Epithelial-mesenchymal plasticity (EMP) involves reversible transitions between epithelial, mesenchymal, and various intermediate hybrid epithelial/mesenchymal states. Although the process of epithelial-mesenchymal transition (EMT) and its associated transcription factors are well-characterized, the transcription factors that drive mesenchymal-epithelial transition (MET) and stabilize hybrid E/M phenotypes remain less understood. In our study, we analyzed several publicly available transcriptomic datasets at both bulk and single-cell levels, identifying ELF3 as a factor closely linked to the epithelial phenotype and was found to be downregulated during EMT. Through mechanism-based mathematical modeling, we demonstrate that ELF3 inhibits the progression of EMT, suggesting that ELF3 can counteract EMT even in the presence of EMT-inducing factors such as WT1. Our model predicts that ELF3’s capacity to induce MET is stronger than that of KLF4 but weaker than GRHL2. Finally, we show that ELF3 levels are associated with poorer patient survival in certain solid tumor types, indicating a cell-of-origin or lineage-specific role in ELF3's prognostic significance.