Biology subjects

Anderson, A. R.

Publications and source records attributed to Anderson, A. R..

12 recordsLinked to original sources

bioRxiv2024

Evolutionary double-bind treatment using radiotherapy and NK cell-based immunotherapy in prostate cancer

Evolution-informed therapies exploit ecological and evolutionary consequences of drug resistance to inhibit the expansion of treatment-resistant populations and prolong time to progression. One strategy, termed an evolutionary double-bind, uses an initial therapy to elicit a specific adaptive response by the cancer cells, which is then selectively targeted by a follow-on therapy. Here we examine the combination of radiation therapy and immunotherapy as a quantifiable double-bind strategy. Radiotherapy (RT) induces lethal double-strand DNA breaks, but cancer cells can adapt by upregulating DNA damage response pathways. While this evolutionary strategy increases resistance to DNA damaging agents, it also results in enhanced expression of natural killer (NK) cell ligands potentially increasing vulnerability to an immune response. Using a radiation-resistant human prostate carcinoma cell line (22Rv1), we demonstrate that RT-resistant cells upregulate NK cell ligands, including major histocompatibility complex class I chain-related protein A/B (MICA/B), and poliovirus receptors (PVR1, PVRL2) with a 2-fold increase in sensitivity to NK cell mediated killing. We investigated this potential evolutionary double bind through in vitro studies and evolution-based mathematical models. Radiotherapy alone slowed overall growth but strongly selected for RT-resistant cells. NK cell therapy alone suppressed the RT-resistant population but with a surviving population of radiation-sensitive cells. These dynamics were framed mathematically, and model simulation predicted optimal tumour control would be achieved through initial RT rapidly followed by NK-based immunotherapy. Subsequent experiments confirmed the model prediction. We conclude that radiotherapy and NK cell-based immunotherapy produces an evolutionary double bind that can be exploited in heterogenous tumours to limit RT resistance.

cancer biology↗

bioRxiv2023

Engineering the microstructure and spatial bioactivity of MAP scaffolds in vitro instructs neovascularization in vivo

In tissues where the vasculature is either lacking or abnormal, biomaterials can be designed to promote vessel formation and enhance tissue repair. In this work, we independently tune the microstructure and bioactivity of microporous annealed particle (MAP) scaffolds to guide cell patterning in 3D and promote de novo assembly of endothelial progenitor-like cells into vessels. We implement both in silico characterization and in vitro experimentation to elucidate an optimal scaffold formulation for vessel formation. We determine that MAP scaffolds with pore volumes on the same order of magnitude as cells facilitate cell growth and vacuole formation. We achieve spatial control over cell spreading by incorporating adhesive microgels in well-mixed, heterogeneous MAP scaffolds. While we demonstrate that integrin engagement is the primary driver of network formation in these materials, introducing adhesive microgels loaded with heparin nanoparticles leads to the formation of vascular tubes after 3 days in culture. We then show in vivo that this unique scaffold formulation enhances vessel maturation in a wound healing model and instructs differential vascular patterning in the tumor microenvironment. Taken together, this work determines the optimal microstructure and ligand presentation within MAP scaffolds that lead to vascular constructs in vitro and facilitate neovascularization in vivo.

bioengineering↗

bioRxiv2021

Gattaca: Base pair resolution mutation tracking for somatic evolution studies using agent-based models

Gattaca provides the first base-pair resolution artificial genomes for tracking somatic mutations within agent based modeling. Through the incorporation of human reference genomes, mutational context, sequence coverage/error information Gattaca is able to realistically provide comparable sequence data for in-silico comparative evolution studies with human somatic evolution studies. This user-friendly method, incorporated into each in-silico cell, allows us to fully capture somatic mutation spectra and evolution.

evolutionary biology↗

bioRxiv2021

Reconstruction of Contemporary Human Stem Cell Dynamics with Oscillatory Molecular Clocks

Molecular clocks record cellular ancestry. However, currently used clocks tick too slowly to measure the short-timescale dynamics of cellular renewal in adult tissues. Here we develop rapidly oscillating DNA methylation clocks where ongoing (de)methylation causes the clock to tick-tock back-and-forth between methylated and unmethylated states like a pendulum. We identify oscillators using standard methylation arrays and develop a mathematical modelling framework to quantitatively measure human adult stem cell dynamics from these data. Small intestinal crypts were inferred to contain slightly more stem cells than colon (6.5 {+/-} 1.0 vs 5.8 {+/-} 1.7 stem cells/crypt) with slower stem cell replacement in small intestine (0.79 {+/-} 0.5 vs 1.1 {+/-} 0.8 replacements/stem cell/year). Germline APC mutation increased the number of replacements per crypt (13.0 {+/-} 2.4 replacements/crypt/year vs 6.9 {+/-} 4.6 for healthy colon). In blood, we measure rapid expansion of acute leukaemia and slower growth of chronic disease. Rapidly oscillating molecular clocks are a new methodology to quantitatively measure human somatic cell dynamics.

bioinformatics↗

bioRxiv2020

The Harsh Microenvironment in Early Breast Cancer Select for a Warburg Phenotype

The harsh microenvironment of ductal carcinoma in situ (DCIS) exerts strong evolutionary selection pressures on cancer cells. We hypothesize that the poor metabolic conditions near the ductal center foment the emergence of a Warburg Effect (WE) phenotype, wherein cells rapidly ferment glucose to lactic acid, even in normoxia. To test this hypothesis, we subjected pre-malignant breast cancer cells to different microenvironmental selection pressures using combinations of hypoxia, acidosis, low glucose, and starvation for many months, and isolated single clones for metabolic and transcriptomic profiling. The two harshest conditions selected for constitutively expressed WE phenotypes. RNA-seq analysis of WE clones identified the transcription factors NF[kcy]B and KLF4 as potential inducers of the WE phenotype. NF[kcy]B was highly phosphorylated in the glycolytic clones. In stained DCIS samples, KLF4 expression was enriched in the area with the harshest microenvironmental conditions. We simulated in vivo DCIS phenotypic evolution using a mathematical model calibrated from the in vitro results. The WE phenotype emerged in the poor metabolic conditions near the necrotic core. We propose that harsh microenvironments within DCIS select for a Warburg phenotype through constitutive transcriptional reprogramming, thus conferring a survival advantage and facilitating further growth and invasion.

cancer biology↗

bioRxiv2020

High school Internship Program in Integrated Mathematical Oncology (HIP IMO) - five-year experience at Moffitt Cancer Center

Modern cancer research, and the wealth of data across multiple spatial and temporal scales, has created the need for researchers that are well-versed in the life sciences (cancer biology, developmental biology, immunology), medical sciences (oncology) and natural sciences (mathematics, physics, engineering, computer sciences). College undergraduate education is traditionally provided in disciplinary silos, which creates a steep learning curve at the graduate and postdoctoral levels that increasingly bridge multiple disciplines. Numerous colleges have begun to embrace interdisciplinary curricula, but students who double-major in mathematics (or other quantitative sciences) and biology (or medicine) remain scarce. We identified the need to educate junior and senior high school students about integrating mathematical and biological skills, through the lens of mathematical oncology, to better prepare students for future careers at the interdisciplinary interface. The High school Internship Program in Integrated Mathematical Oncology (HIP IMO) at Moffitt Cancer Center has so far trained 59 students between 2015 and 2019. We report here on the program structure, training deliverables, curriculum, and outcomes. We hope to promote such interdisciplinary educational activities early in a students career.

scientific communication and education↗

bioRxiv2019

Click by Click Microporous Annealed Particle (MAP) Scaffolds

Macroporous scaffolds are being increasingly used in regenerative medicine and tissue repair. While our recently developed microporous annealed particle (MAP) scaffolds have overcome issues with injectability and in situ hydrogel formation, limitations with respect to tunability to be able to manipulate hydrogel strength and rigidity for broad applications still exist. To address these key issues, here we synthesized hydrogel microparticles (HMPs) of hyaluronic acid (HA) using the thiol-norbornene click reaction and then subsequently annealed HMPs into a porous scaffold using the tetrazine-norbornene click reaction. This assembly method allowed for straightforward tuning of bulk scaffold rigidity by varying the tetrazine to norbornene ratio, with increasing tetrazine resulting in increasing scaffold storage modulus, Youngs modulus, and maximum stress. These changes were independent of void fraction. Further incorporation of human dermal fibroblasts (HDFs) throughout the porous scaffold revealed the biocompatibility of this annealing strategy as well as differences in proliferation and cell-occupied volume. Finally, injection of porous HA-Tet MAP scaffolds into an ischemic stroke model showed this chemistry is biocompatible in vivo with reduced levels of inflammation and astrogliosis as previously demonstrated for other crosslinking chemistries.

bioengineering↗

bioRxiv2019

Macrophage-mediated immunoediting drives ductal carcinoma evolution: Space is the game changer

Under normal conditions, the immune system is capable of rapidly detecting and eliminating potentially dangerous entities, including tumor cells. Due to intense selection pressure imposed by the immune response, tumor cells often evolve strategies to avoid elimination in a process known as immunoediting. It is less known how the evolutionary response to immune predation is altered by context. We explore the evolution of immune escape strategies in ductal cancers, a natural case in which to study evolution in different contexts: inside and outside of ducts. We highlight the role of macrophages as a source of \"public goods,\" releasing diffusible factors (reactive oxygen species and growth factors). Immunohistochemistry reveals differences between macrophage densities of invasive ductal carcinomas and non-invasive ductal carcinomas in situ. For the first time, immunohistochemistry (IHC) imaging data comparing DCIS to IDC were used to initialize mechanistic agent-based models of evolutionary dynamics. By using IHC to map the initial conditions of a growing tumor, we show that spatial competition and structure influence transient dynamics during invasion. These dynamics are context-dependent, a conclusion that may be missed from interpreting imaging or non-spatial modeling alone. Before invasion, the presence of macrophages correlate with shorter ductal breach times. After invasion, tumors may employ a \"pioneer-engineer\" strategy where pioneering immunoresistant cells on the tumors edge stimulate the release of M1-macrophage-derived reactive oxygen species, degrading surrounding stroma. Behind the invasive edge, the engineering immunosuppressive cells promote the release of M2-macrophage-derived growth factors, providing a long-term immune escape strategy. Together, mathematical modeling and image analysis highlight the crucial role tumor-associated macrophages play in immune escape and invasion, both inside and outside of ducts.

cancer biology↗

bioRxiv2019

Tissue structure accelerates evolution: premalignant sweeps precede neutral expansion

Cancer has been hypothesized to be a caricature of the renewal process of the tissue of origin: arising from (and maintained by) small subpopulations capable of continuous growth1. The strong influence of the tissue structure has been convincingly demonstrated in intestinal cancers where adenomas grow by the fission of stem-cell-maintained glands influenced by early expression of abnormal cell mobility in cancer progenitors2, 3. So-called "born to be bad" tumors arise from progenitors which may already possess the necessary driver mutations for malignancy4, 5 and metastasis6. These tumors subsequently evolve neutrally, thereby maximizing intratumoral heterogeneity and increasing the probability of therapeutic resistance. These findings have been nuanced by the advent of multi-region sequencing, which uses spatial and temporal patterns of genetic variation among competing tumor cell populations to shed light on the mode of tumor evolution (neutral or Darwinian) and also the tempo4, 7-11. Using a classic, well-studied model of tumor evolution (a passenger-driver mutation model12-16) we systematically alter spatial constraints and cell mixing rates to show how tissue structure influences functional (driver) mutations and genetic heterogeneity over time. This model approach explores a key mechanism behind both inter-patient and intratumoral tumor heterogeneity: competition for space. Initial spatial constraints determine the emergent mode of evolution (neutral to Darwinian) without a change in cell-specific mutation rate or fitness effects. Transition from early Darwinian to late neutral evolution is accelerated by the combination of two factors: spatial constraints and well-timed dispersal events.

cancer biology↗

bioRxiv2018

The Goldilocks Window of Personalized Chemotherapy: An Immune Perspective

The immune system is increasingly being recognized for its untapped potential in being recruited to attack tumors in cancer therapy. The main challenge, however, is that most tumors exist in a state of immune tolerance where the patients immune system has become insensitive to the cancer cells. In order to investigate the ability to use chemotherapy to break immune tolerance, we created a mathematical modeling framework for tumor-immune dynamics. Our results suggest that optimal chemotherapy scheduling must balance two opposing objectives: maximal tumor reduction and preserving patient immune function. Successful treatment requires therapy to operate in a Goldilocks Window where patient immune health is not overly compromised. By keeping therapy just right, we show that the synergistic effects of immune activation and chemotherapy can maximize tumor reduction and control.\n\nStatement of SignificanceIn order to maximize the synergy between chemotherapy and anti-tumor immune response, lymphodepleting therapy must be balanced in a Goldilocks Window of optimal dosing.

cancer biology↗

bioRxiv2018

Towards multi-drug adaptive therapy

A new ecologically inspired paradigm in cancer treatment known as \"adaptive therapy\" capitalizes on competitive interactions between drug-sensitive and drug-resistant subclones. The goal of adaptive therapy is to maintain a controllable stable tumor burden by allowing a significant population of treatment sensitive cells to survive. These, in turn, suppress proliferation of the less fit resistant populations. However, there remain several open challenges in designing adaptive therapies, particularly in extending these therapeutic concepts to multiple treatments. We present a cancer treatment case study (metastatic castrate resistant prostate cancer) as a point of departure to illustrate three novel concepts to aid the design of multi-drug adaptive therapies. First, frequency-dependent \"cycles\" of tumor evolution can trap tumor evolution in a periodic, controllable loop. Second, the availability and selection of treatments may limit the evolutionary \"absorbing region\" reachable by the tumor. Third, the velocity of evolution significantly influences the optimal timing of drug sequences.

cancer biology↗

bioRxiv2018

Inferring Tumour Proliferative Organisation from Phylogenetic Tree Measures in a Computational Model

We use a computational modelling approach to explore whether it is possible to infer a tumours cell proliferative hierarchy, under the assumptions of the cancer stem cell hypothesis and neutral evolution. We focus on inferring the symmetric division probability for cancer stem cells in our model, as this is believed to be a key driving parameter of tumour progression and therapeutic response. Given the advent of multi-region sampling, and the opportunities offered by them to understand tumour evolutionary history, we focus on a suite of statistical measures of the phylogenetic trees resulting from the tumours evolution in different regions of parameter space and through time. We find strikingly different patterns in these measures for changing symmetric division probability which hinge on the inclusion of spatial constraints. These results give us a starting point to begin stratifying tumours by this biological parameter and also generate a number of actionable clinical and biological hypotheses including changes during therapy, and through tumour evolution.

cancer biology↗