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This file contains all supplementary figures, which show further details on the model setup and behavior. This includes separated time to recurrence plots and results from additional migration speeds and metastatic compositions.

Comparing CT, AT1, and AT2 treatment schedules for a heterogeneous sensitive tumor initialized by a normal distribution with a mean sensitivity s=100% and standard deviation σs=25%.

Comparing CT, AT1, and AT2 treatment schedules for a heterogeneous sensitive tumor when cells can migrate. Tumors were initialized by a normal distribution with a mean sensitivity s=100% and standard deviation σs=25%.

Comparing CT, AT1, and AT2 treatment schedules for a homogeneous sensitive tumor initialized by a normal distribution with a mean sensitivity s=100% and standard deviation σs=5%.

Ongoing intratumoral evolution is apparent in molecular variations among cancer cells from different regions of the same tumor, but genetic data alone provide little insight into environmental selection forces and cellular phenotypic adaptations that govern the underlying Darwinian dynamics. In three spontaneous murine cancers (prostate cancers in TRAMP and PTEN mice, pancreatic cancer in KPC mice), we identified two subpopulations with distinct niche construction adaptive strategies that remained stable in culture: (i) invasive cells that produce an acidic environment via upregulated aerobic glycolysis; and (ii) noninvasive cells that were angiogenic and metabolically near-normal. Darwinian interactions of these subpopulations were investigated in TRAMP prostate cancers. Computer simulations demonstrated invasive, acid-producing (C2) cells maintain a fitness advantage over noninvasive, angiogenic (C3) cells by promoting invasion and reducing efficacy of immune response. Immunohistochemical analysis of untreated tumors confirmed that C2 cells were invariably more abundant than C3 cells. However, the C2 adaptive strategy phenotype incurred a significant cost due to inefficient energy production (i.e., aerobic glycolysis) and depletion of resources for adaptations to an acidic environment. Mathematical model simulations predicted that small perturbations of the microenvironmental extracellular pH (pHe) could invert the cost/benefit ratio of the C2 strategy and select for C3 cells. In vivo, 200 mmol/L NaHCO3 added to the drinking water of 4-week-old TRAMP mice increased the intraprostatic pHe by 0.2 units and promoted proliferation of noninvasive C3 cells, which remained confined within the ducts so that primary cancer did not develop. A 0.2 pHe increase in established tumors increased the fraction of C3 cells and signficantly diminished growth of primary and metastatic tumors. In an experimental tumor construct, MCF7 and MDA-MB-231 breast cancer cells were coinjected into the mammary fat pad of SCID mice. C2-like MDA-MB-231 cells dominated in untreated animals, but C3-like MCF7 cells were selected and tumor growth slowed when intratumoral pHe was increased. Overall, our data support the use of mathematical modeling of intratumoral Darwinian interactions of environmental selection forces and cancer cell adaptive strategies. These models allow the tumor to be steered into a less invasive pathway through the application of small but selective biological force. Cancer Res; 77(9); 2242–54. ©2017 AACR.

Comparing CT, AT1, and AT2 treatment schedules for a heterogeneous sensitive tumor when phenotypes can drift. Tumors were initialized by a normal distribution with a mean sensitivity s=80% and standard deviation σs=25%.

Treatment of advanced cancers has benefited from new agents that supplement or bypass conventional therapies. However, even effective therapies fail as cancer cells deploy a wide range of resistance strategies. We propose that evolutionary dynamics ultimately determine survival and proliferation of resistant cells. Therefore, evolutionary strategies should be used with conventional therapies to delay or prevent resistance. Using an agent-based framework to model spatial competition among sensitive and resistant populations, we applied antiproliferative drug treatments to varying ratios of sensitive and resistant cells. We compared a continuous maximum-tolerated dose schedule with an adaptive schedule aimed at tumor control via competition between sensitive and resistant cells. Continuous treatment cured mostly sensitive tumors, but with any resistant cells, recurrence was inevitable. We identified two adaptive strategies that control heterogeneous tumors: dose modulation controls most tumors with less drug, while a more vacation-oriented schedule can control more invasive tumors. These findings offer potential modifications to treatment regimens that may improve outcomes and reduce resistance and recurrence.Significance: By using drug dose modulation or treatment vacations, adaptive therapy strategies control the emergence of tumor drug resistance by spatially suppressing less fit resistant populations in favor of treatment sensitive ones. Cancer Res; 78(8); 2127–39. ©2018 AACR.

Simultaneous video of four simulations of tumor growth with accompanying phenotypic "flow" diagram, Top left: untreated; top right: low dose, early; bottom left: high dose, late; bottom right: low dose, late. The appearance of the white box in each of the treated windows indicates when the buffer treatment was applied (all vessels secrete buffer). In the phenotype flow plot, the cyan dot shows the median phenotype of all tumor cells, black points indicate distribution of phenotypes present in the tumor at each time point. The simulations show that the buffer therapy reverses the evolution towards the glycolytic, acid-resistant phenotype, with early or high dose having the stronger effect. A late, low dose does have an effect on the progression, but the invasive phenotype persists despite the therapy and will eventually dominate.

Supplemental material contains additional details of tumor imaging and mathematical models. Supplemental figures demonstrating results from experimental and computational studies referenced in the manuscript are included

Comparing CT, AT1, and AT2 treatment schedules for a homogeneous resistant tumor initialized by a normal distribution with a mean sensitivity s=60% and standard deviation σs=5%.

Background Cancer progression is governed by evolutionary dynamics in both the tumour population and its host. Since cancers die with the host, each new population of cancer cells must reinvent strategies to overcome the host’s heritable defences. In contrast, host species evolve defence strategies over generations if tumour development limits procreation. Methods We investigate this “evolutionary arms race” through intentional breeding of immunodeficient SCID and immunocompetent Black/6 mice to evolve increased tumour suppression. Over 10 generations, we injected Lewis lung mouse carcinoma cells [LL/2-Luc-M38] and selectively bred the two individuals with the slowest tumour growth at day 11. Their male progeny were hosts in the subsequent round. Results The evolved SCID mice suppressed tumour growth through biomechanical restriction from increased mesenchymal proliferation, and the evolved Black/6 mice suppressed tumour growth by increasing immune-mediated killing of cancer cells. However, transcriptomic changes of multicellular tissue organisation and function genes allowed LL/2-Luc-M38 cells to adapt through increased matrix remodelling in SCID mice, and reduced angiogenesis, increased energy utilisation and accelerated proliferation in Black/6 mice. Conclusion Host species can rapidly evolve both immunologic and non-immunologic tumour defences. However, cancer cell plasticity allows effective phenotypic and population-based counter strategies.

The acidic pH of tumors profoundly inhibits effector functions of activated CD8 + T-cells. We hypothesize that this is a physiological process in immune regulation, and that it occurs within lymph nodes (LNs), which are likely acidic because of low convective flow and high glucose metabolism. Here we show by in vivo fluorescence and MR imaging, that LN paracortical zones are profoundly acidic. These acidic niches are absent in athymic Nu/Nu and lymphodepleted mice, implicating T-cells in the acidifying process. T-cell glycolysis is inhibited at the low pH observed in LNs. We show that this is due to acid inhibition of monocarboxylate transporters (MCTs), resulting in a negative feedback on glycolytic rate. Importantly, we demonstrate that this acid pH does not hinder initial activation of naïve T-cells by dendritic cells. Thus, we describe an acidic niche within the immune system, and demonstrate its physiological role in regulating T-cell activation., T-cell activation primarily occurs in the lymph nodes, highly organized and specialized secondary lymphoid organs. Here the authors show that the acidic extracellular pH in lymph node paracortical zones limits cytokine production by effector T-cells, but does not alter their activation by antigen-presenting cells.

The complexity of modern in vivo magnetic resonance imaging (MRI) methods in oncology has dramatically changed in the last 10 years. The field has long since moved passed its (unparalleled) ability to form images with exquisite soft-tissue contrast and morphology, allowing for the enhanced identification of primary tumors and metastatic disease. Currently, it is not uncommon to acquire images related to blood flow, cellularity, and macromolecular content in the clinical setting. The acquisition of images related to metabolism, hypoxia, pH, and tissue stiffness are also becoming common. All of these techniques have had some component of their invention, development, refinement, validation, and initial applications in the preclinical setting using in vivo animal models of cancer. In this review, we discuss the genesis of quantitative MRI methods that have been successfully translated from preclinical research and developed into clinical applications. These include methods that interrogate perfusion, diffusion, pH, hypoxia, macromolecular content, and tissue mechanical properties for improving detection, staging, and response monitoring of cancer. For each of these techniques, we summarize the 1) underlying biological mechanism(s); 2) preclinical applications; 3) available repeatability and reproducibility data; 4) clinical applications; and 5) limitations of the technique. We conclude with a discussion of lessons learned from translating MRI methods from the preclinical to clinical setting, and a presentation of four fundamental problems in cancer imaging that, if solved, would result in a profound improvement in the lives of oncology patients. Level of Evidence: 5 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;50:1377-1392.

Ongoing intratumoral evolution is apparent in molecular variations among cancer cells from different regions of the same tumor, but genetic data alone provide little insight into environmental selection forces and cellular phenotypic adaptations that govern the underlying Darwinian dynamics. In three spontaneous murine cancers (prostate cancers in TRAMP and PTEN mice, pancreatic cancer in KPC mice), we identified two subpopulations with distinct niche construction adaptive strategies that remained stable in culture: (i) invasive cells that produce an acidic environment via upregulated aerobic glycolysis; and (ii) noninvasive cells that were angiogenic and metabolically near-normal. Darwinian interactions of these subpopulations were investigated in TRAMP prostate cancers. Computer simulations demonstrated invasive, acid-producing (C2) cells maintain a fitness advantage over noninvasive, angiogenic (C3) cells by promoting invasion and reducing efficacy of immune response. Immunohistochemical analysis of untreated tumors confirmed that C2 cells were invariably more abundant than C3 cells. However, the C2 adaptive strategy phenotype incurred a significant cost due to inefficient energy production (i.e., aerobic glycolysis) and depletion of resources for adaptations to an acidic environment. Mathematical model simulations predicted that small perturbations of the microenvironmental extracellular pH (pHe) could invert the cost/benefit ratio of the C2 strategy and select for C3 cells. In vivo, 200 mmol/L NaHCO3 added to the drinking water of 4-week-old TRAMP mice increased the intraprostatic pHe by 0.2 units and promoted proliferation of noninvasive C3 cells, which remained confined within the ducts so that primary cancer did not develop. A 0.2 pHe increase in established tumors increased the fraction of C3 cells and signficantly diminished growth of primary and metastatic tumors. In an experimental tumor construct, MCF7 and MDA-MB-231 breast cancer cells were coinjected into the mammary fat pad of SCID mice. C2-like MDA-MB-231 cells dominated in untreated animals, but C3-like MCF7 cells were selected and tumor growth slowed when intratumoral pHe was increased. Overall, our data support the use of mathematical modeling of intratumoral Darwinian interactions of environmental selection forces and cancer cell adaptive strategies. These models allow the tumor to be steered into a less invasive pathway through the application of small but selective biological force. Cancer Res; 77(9); 2242–54. ©2017 AACR.

Evolution of resistance remains a barrier to successful therapy in most metastatic cancers despite the increasing number of treatment options. A major driver of the evolutionary capacity of cancer populations is the dynamic interactions of spatial and temporal variations in environmental conditions with malignant cells that can access a vast number of phenotypic properties encoded in the human genome. As a result, cells with phenotypic or ecological resistance are often present prior to administration of a drug. Furthermore, it is likely that many other cancer cells, particularly those that must adapt to rapid temporal changes in the environment due to chaotic tumor blood flow, have the ability to rapidly change their phenotypes to adapt to many cytotoxic therapies. Current standard of care principles typically treat metastatic cancers by application of one or more drugs at maximum tolerated dose (MTD) until unambiguous evidence of tumor progression. However, because of the phenotypic diversity found in most large metastatic cancers, this approach is usually evolutionarily unwise. That is, if prior clinical experience and published data indicated there is no possible curative outcome for treatment, it will likely accelerate proliferation of resistant populations through a well-known evolutionary dynamic termed “competitive release.” This is because continuous MTD therapy will eventually kill the population of drug-sensitive cells and leave behind a population of resistant cancer cells that can proliferate unopposed by competition with other populations. Here we present cancer treatment strategies that integrate evolutionary dynamics to maximize the effectiveness of currently available drugs even within very heterogeneous tumor populations. We have demonstrated the feasibility of these therapies in preclinical models and, currently, are being used in clinical trials showing promising preliminary results.

Clinical breast cancers in which at least 10% of cells express the estrogen receptor are labeled as “ER positive.” First line therapy for these patients is typically continuous administration of anti-estrogen drugs at maximum tolerated dose (MTD) until progression. In the vast majority of patients, resistance to hormone therapy evolves in the breast cancer cells within 2 years leading to treatment failure and tumor progression. In prior studies, we have demonstrated continuous application of MTD chemotherapy results in evolutionary dynamics (termed “competitive release”) that accelerates proliferation of treatment-resistance populations. In contrast, evolution-informed application of treatment reduces drug administration to maintain substantial populations of therapy-sensitive cells to reduce proliferation of resistant phenotypes. Prior pre-clinical and clinical studies have shown this strategy can delay or prevent proliferation of resistant cells and prolong time to progression (TTP). We hypothesize that similar dynamics may be observed in hormonal therapy of ER+ breast cancers. Here we address two important dynamics. First, we consider a clinical scenario in which symptoms are sufficiently severe or life-threatening to require rapid and substantial tumor reduction. Can this be achieved while retaining evolutionary dynamics to subsequently delay proliferation of resistance? A second, related question is defining the cost of resistance to anti-estrogen therapy. Here, we investigated the evolutionary dynamics of resistance to anti-estrogen therapy using ER+ MCF-7 orthotropic xenografts treated with both continuous Tamoxifen as well as cycles in which estrogen stimulation is combined with estrogen suppression. As expected, continuous administration of anti-estrogen drugs successfully suppressed tumor growth. However we found that brief interruptions in drug administration permitted equal tumor control while administering up to 50% less drug and maintaining cell phenotypes that retained high levels of ER expression and lower levels of MDR1 expression. In follow-on experiments combining hormonal and chemo-therapies; we obtained similar tumor control to hormonal therapy alone but with more necrosis and significantly lower ER expression in the surviving population.

Due to imbalances between vascularity and cellular growth patterns, the tumour microenvironment harbours multiple metabolic stressors including hypoxia and acidosis, which have significant influences on remodelling both tumour and peritumoral tissues. These stressors are also immunosuppressive and can contribute to escape from immune surveillance. Understanding these effects and characterizing the pathways involved can identify new targets for therapy and may redefine our understanding of traditional anti-tumour therapies. In this review, the effects of hypoxia and acidosis on tumour immunity will be summarized, and how modulating these parameters and their sequelae can be a useful tool for future therapeutic interventions is discussed.

Cancer treatment has greatly benefited from the introduction of both new agents (i.e. targeted therapy and check point inhibitors) and new strategies for conventional therapies such as chemotherapy and hormonal therapy. Most cancer types now have at least one effective treatment agent, and many tumors, such as breast and prostate cancer, have multiple available treatment options. However, even the most effective therapy is usually defeated as cancer cells deploy a wide range of molecular strategies to overcome therapy leading to disease progression. Here we propose that, while molecular dynamics govern response and resistance to therapy, evolutionary dynamics determine survival and proliferation of treatment-resistant cells. We hypothesize that understanding these evolutionary interactions may identify strategies to delay or prevent proliferation of resistant population thus prolong time to recurrence. To simulate these interactions, we use an off-lattice, agent-based, framework to model competition between sensitive and resistant populations during therapy in a spatially competitive environment. Our model applies a classic evolutionary trade-off between fecundity (cellular proliferation) and survivorship (drug sensitivity) to the tumor populations. Thus, in the resource-limited tumor microenvironment, the cost of increased resource investment in a resistant phenotype necessarily results in slower proliferation while a phenotype invested in fast proliferation is less likely to survive in drug. Model simulations demonstrate that, in the absence of therapy, cells with slower growth but higher survivorship may become confined in the interior of the tumor during growth phases, which provides a spatial sanctuary during initial drug administration. Over time, therapy eliminates the treatment-sensitive population allowing the resistant cells to proliferate unopposed. We simulate the application of an anti-proliferative drug on varying ratios of mixed sensitive and resistant cells using two general treatment strategies: a continuous schedule of maximum tolerated dose or an evolution-informed schedule that incorporates dose-modulation and treatment vacations to sustain control of the tumor through competition between sensitive and resistant cell populations. We find tumors consisting only of sensitive cells can cured with continuous treatment, but the presence of any significant population of resistant cells will lead to eventual recurrence. We identify two treatment strategies that control heterogeneous tumors: one emphasizes continuous dose modulation, and the other relies on treatment vacations. Both strategies control tumors over a wide range of resistant/sensitive population ratios but the average dose given is significantly lower with dose modulation. Cell migration and phenotypic drift limit the time to recurrence advantage of these strategies but some efficacy can be retained through a more vacation-oriented schedule.

Tumors are multicellular ecosystems that characteristically exhibit extensive spatial and temporal heterogeneity due to complex ecoevolutionary forces driven by interactions between tumor cells and their environment. Although this variability is recognized by both researchers and physicians, current systemic therapies are not influenced by spatial variations in tumors and are typically fixed over time by protocol so that treatment changes only in the event of excessive toxicity or unambiguous evidence of tumor progression. Here we propose that optimal cancer therapy must be as dynamic as the tumor itself. Thus, as the tumor populations and ecology change with time in response to treatment, therapies must do the same to suppress proliferation of resistant phenotypes and prolonging control. Here, we discuss different therapies, based on evolutionary principles that allow continuous changes in therapy to respond to and even anticipate the ecoevolutionary dynamics of tumor response and, most importantly, resistance to therapy.

Neutralizing tumor external acidity with oral buffers has proven effective for the prevention and inhibition of metastasis in several cancer mouse models. Solid tumors are highly acidic as a result of high glycolysis combined with an inadequate blood supply. Our prior work has shown that sodium bicarbonate, imidazole, and free‐base (but not protonated) lysine are effective in reducing tumor progression and metastasis. However, a concern in translating these results to clinic has been the presence of counter ions and their potential undesirable side effects (e.g., hypernatremia). In this work, we investigate tris(hydroxymethyl)aminomethane, (THAM or Tris), a primary amine with no counter ion, for its effects on metastasis and progression in prostate and pancreatic cancer in vivo models using MRI and bioluminescence imaging. At an ad lib concentration of 200 mmol/L, Tris effectively inhibited metastasis in both models and furthermore led to a decrease in the expression of the major glucose transporter, GLUT‐1. Our results also showed that Tris–base buffer (pH 8.4) had no overt toxicity to C3H mice even at higher doses (400 mmol/L). In conclusion, we have developed a novel therapeutic approach to manipulate tumor extracellular pH (pHe) that could be readily adapted to a clinical trial.

Conventional cancer treatment strategies assume that maximum patient benefit is achieved through maximum killing of tumor cells. However, by eliminating the therapy-sensitive population, this strategy accelerates emergence of resistant clones that proliferate unopposed by competitors-an evolutionary phenomenon termed "competitive release." We present an evolution-guided treatment strategy designed to maintain a stable population of chemosensitive cells that limit proliferation of resistant clones by exploiting the fitness cost of the resistant phenotype. We treated MDA-MB-231/luc triple-negative and MCF7 estrogen receptor-positive (ER(+)) breast cancers growing orthotopically in a mouse mammary fat pad with paclitaxel, using algorithms linked to tumor response monitored by magnetic resonance imaging. We found that initial control required more intensive therapy with regular application of drug to deflect the exponential tumor growth curve onto a plateau. Dose-skipping algorithms during this phase were less successful than variable dosing algorithms. However, once initial tumor control was achieved, it was maintained with progressively smaller drug doses. In 60 to 80% of animals, continued decline in tumor size permitted intervals as long as several weeks in which no treatment was necessary. Magnetic resonance images and histological analysis of tumors controlled by adaptive therapy demonstrated increased vascular density and less necrosis, suggesting that vascular normalization resulting from enforced stabilization of tumor volume may contribute to ongoing tumor control with lower drug doses. Our study demonstrates that an evolution-based therapeutic strategy using an available chemotherapeutic drug and conventional clinical imaging can prolong the progression-free survival in different preclinical models of breast cancer.

The dynamic cancer ecosystem, with its rich temporal and spatial diversity in environmental conditions and heritable cell phenotypes, is remarkably robust to therapeutic perturbations. Even when response to therapy is clinically complete, adaptive tumor strategies almost inevitably emerge and the tumor returns. Although evolution of resistance remains the proximate cause of death in most cancer patients, a recent analysis found that evolutionary terms were included in less than 1% of articles on the cancer treatment outcomes, and this has not changed in 30 years. Here, we review treatment methods that attempt to understand and exploit intratumoral evolution to prolong response to therapy. In general, we find that treating metastatic (i.e., noncurable) cancers using the traditional strategy aimed at killing the maximum number of tumor cells is evolutionarily unsound because, by eliminating all treatment-sensitive cells, it enables rapid proliferation of resistant populations—a well-known evolutionary phenomenon termed “competitive release.” Alternative strategies, such as adaptive therapy, “ersatzdroges,” and double-bind treatments, shift focus from eliminating tumor cells to evolution-based methods that suppress growth of resistant populations to maintain long-term control. Cancer Res; 75(22); 4675–80. ©2015 AACR.

pH homeostasis is a fundamental requirement of life. Energy catabolism via fermentation and respiration results in the conversion of reduced substrates (sugars and fats) to oxidized acids, which must be exported from the cell and eventually eliminated via recycling by other organs (e.g., the Cori cycle) or excretion. Hence, a number of mechanisms have been evolved to export H+ from cells into the extracellular fluid, where they combine with mobile buffers to enter the bloodstream via diffusive flux. As they are regulated by different mechanisms, differences between intracellular (pHi) and extracellular (pHe) pH values can exist. Physiological and pathological processes can alter this dynamic homeostasis, which usually results in acidic stress. Accumulation of acids inside cells generally signals a metabolic shutdown, and pH dysregulation can act as a biomarker of the progression of different pathological diseases including metabolic issues, central nervous diseases, ischemia, wounding, and cancer. Accumulation of acids outside cells can signal tissue remodeling during wound repair and in cancer. Thus, there is a need for robust, reliable, and clinically translatable methods with which to measure intra- and extracellular pH in vivo. A number of biophysical techniques have been developed with which to accurately measure tissue pH in vivo; including inter alia, MRS approaches. In this article, we review the main tools to measure pH by MRS and briefly compare these to alternative approaches. Keywords: pH; MRI; MRS; pHe; pHi

Breast cancer shows high intratumoral heterogeneity, which can be visualized as localized sub-populations of tumor cells with different malignancy potential and treatment responsiveness. These regions are like “habitats” that contain different combinations of environmental selection forces, such as hypoxia, acidosis, or nutrient availability. Thus, agents that can perturb these forces may be useful in limiting cancer progression. Studies have shown that melatonin can affect tumor metabolism and we hypothesize that this may be a mechanism by which the disruption of circadian melatonin production by light exposure at night (LAN) promotes breast cancer initiation and progression. The aim of this study was to evaluate the effect of melatonin on intratumoral heterogeneity measured by non-invasive MR imaging in a syngeneic mouse model of breast cancer (4T1). To visualize habitats, clusters were generated from combined MR images generated by different pulse sequences. These were co-registered with histology using tumor specific 3-D printed cradles to classify these tumor habitats. Methods: Mice were exposed to LAN (Control) or LAN plus melatonin. The melatonin metabolite 6-sulfatoxymelatonin (6-SMT) was assessed in urine as a measure of melatonin production. Mice were imaged in a 7T MRI system with: 1) anatomical T2 images, 2) T2*, 3) diffusion-weighted MRI (DWI); and 4) T1 weighted dynamic contrast enhanced (DCE). DCE maps were obtained through semi-quantitative analysis of the pre- and post-contrast agent bolus time-series on a pixel-by-pixel basis. These were combined to the corresponding T2, T2* and Apparent Diffusion Coefficient (ADC) values to generate parameter maps. Parameter maps were used to classify multiple clusters, based on a Gaussian mixture model. Following euthanasia, a 3D printed mold based on the T2 tumor isosurface was created in order to co-register the MRI and histology. Tumors were stained with H&E and for pimonidazole (hypoxia) by immunohistochemistry. Results: Melatonin treatment increased the 6-SMT in urine of mice exposed to LAN and statistically reduced tumor growth by day 15 (p Citation Format: Bruna V. Jardim-Perassi, William Dominguez-Viqueira, Asmaa El-Kenawi, Dominique F. Abrahams, Mikalai Budzevich, Epifanio Ruiz, Suning Huang, Pedro M. Enriquez-Navas, Gary Martinez, Debora Aparecida Pires de Campos Zuccari, Robert J. Gillies. Detection of intratumoral heterogeneity using MR-defined tumor habitats in breast cancer model under melatonin treatment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 884. doi:10.1158/1538-7445.AM2017-884

Magnetic resonance imaging (MRI) is currently one of the most commonly used image modalities for medical diagnosis. The popularity of MRI over other techniques is due to its noninvasive and nonionizing nature along with very good spatial resolution and unlimited tissue penetration. On the negative side, MRI suffers from inherently low sensitivity, requiring the use of contrast agents to increase the detectable signal. Up to now, the most commonly used contrast agents are gadolinium chelates, which, like most conventional diagnostic agents, lack specificity. The use of nanotechnology in the design of inorganic nanoparticles for medical applications has given rise to a new generation of diagnostic agents that hold promise to be more specific and largely increase the sensitivity of current diagnostic techniques. Among them, iron oxide nanoparticles (IONPs) are particularly interesting for MRI-based diagnosis because of their magnetic properties. It is expected that IONPs will make it possible to perform clinical MRI at the molecular level (molecular imaging), which will be one of the key factors for personalized medicine. In this chapter, we discuss some of the applications of inorganic nanoparticles for MRI-based diagnosis, as well as some of the advanced MRI techniques that will allow for the optimal in vivo detection of these new-generation diagnostic agents.

Introduction: Disseminated cancers are typically treated with the highest possible dose of drug (i.e. maximum tolerated dose) to achieve the goal of killing as many tumor cells as possible. However, these therapies eventually fail due to emergence of resistant clones. We have predicted, using mathematical models of Darwinian dynamics, that treatment regimens that adapt the dosing to the tumor spatial variability and tumor microenvironment, can retard the emergence of chemoresistance. Here we present an evolutionary-guided treatment strategy (Adaptive Therapy, AT) designed to maintain stable chemosensitive populations while limiting the proliferation of chemoresistant clones by exploiting the fitness cost of the resistant phenotype. We also evaluated how this novel treatment strategy modifies tumor vascularity. Methods: Four cohorts (composed by 12, 11, 13, and 10 mice, respectively) of nude mice were injected with 10x106 MDA-MB-231 (triple-negative breast cancer) cells in the mammary fat pad. Control animals didn't receive any treatment. Mice under standard therapy received 20mg/kg of Tamoxifen twice per week for a total of 5 times. We defined two different Tamoxifen AT algorithms (Table 1), under which AT mice were treated. Table 1.Adaptive Therapy treatment algorithmsAT-1Initial Dose = 20 mg/kg (highest dose)> If VT(n)≤ .8*VT(n-1) ->Dose decreased by 50%> If VT(n)≥ 1.2*VT(n-1) ->Dose increased by 50%> If the tumor volume is within 20% range, we will apply same dose as previous dose.Lower Limit: 150mm3 and skip the doseAT-2Starting dose = 15 mg/kg> If VT(n)≥ 1.25*VT(n-2) ->Dose = 15 mg/kg> If VT(n) < 1.25*VT(n-2) ->Skip Dose When the tumors achieve the volume of, approximately 300 mm3, MRI T2 and Diffusion Weighted acquisitions were performed on a horizontal Agilent ASR 310 7T scanner, with 205/120/HDS gradients and 310 mm bore to determine volume and cellularity, respectively. Thereafter, dynamic contrast enhanced (DCE-) MRI was preformed following bolus of 0.1mmol/kg Magnevist to assess distribution of blood flow. Images were processed with different in-house developed MATLAB scripts to obtain reliable information from these images. At the end of the monitoring time, tumors were collected and processed for H&E and CD31 immunohistochemistry staining to study the viable and necrotic tissue, and vessel presence, respectively. The slides were examined using the Aperio ScanScope XT microscope. Using different selected slides, an algorithm was built in order to analyze all tissue samples (software Spectrum Version 10.2.5.2352, Aperio Technologies with a pixel-wise resolution. Results and Discussion: Tumor growth was monitored during the treatment period using the MRI techniques previously described. The AT treatment algorithm has been modified to fine tune the dose and scheduling based on tumor volume. Among these three protocols (2 AT and one ST), AT-1 resulted in the most significant cancer control. AT-1 protocol was able to maintain tumors at a small size for >120 days. Also, AT-1 has demonstrated to decrease the percent tumor necrosis (data not shown), and increase vascular density. New experiments and data analysis are currently undergoing in order to get more information and a deeper insight on how the AT can benefit the in-vivo cancer treatment. Conclusion: In summary, initial results demonstrate that AT, guided by MRI measurement of tumor volume, can maintain a stable small tumor burden with prolonged progression free survival compared to standard high dose therapy. Also, AT is able to maintain the lower necrotic volume and the higher vessel density, which, in addition with the tumor volume, was correlated with tumor stabilization. Citation Format: Pedro M. Enriquez-Navas, Jonathan Wojtkowiak, Epi Ruiz, Sabrina Hassan, Robert J. Gillies, Robert A. Gatenby. Adaptive therapy modifies tumor vascularity. [abstract]. In: Proceedings of the AACR Special Conference: Tumor Angiogenesis and Vascular Normalization: Bench to Bedside to Biomarkers; Mar 5-8, 2015; Orlando, FL. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl):Abstract nr B11.