A pyruvate decarboxylase-mediated therapeutic strategy for mimicking yeast metabolism in cancer cells.

Cancer cells have high rates of glycolysis and lactic acid fermentation in order to fuel accelerated rates of cell division (Warburg effect). Here, we present a strategy for merging cancer and yeast metabolism to remove pyruvate, a key intermediate of cancer cell metabolism, and produce the toxic compound acetaldehyde. This approach was achieved by administering the yeast enzyme pyruvate decarboxylase to triple negative breast cancer cells. To overcome the challenges of protein delivery, a nanoparticle-based system consisting of cationic lipids and porous silicon were employed to obtain efficient intracellular uptake. The results demonstrate that the enzyme therapy decreases cancer cell viability through production of acetaldehyde and reduction of lactic acid fermentation.

Single-particle absorption spectroscopy by photothermal contrast.

Removing effects of sample heterogeneity through single-molecule and single-particle techniques has advanced many fields. While background free luminescence and scattering spectroscopy is widely used, recording the absorption spectrum only is rather difficult. Here we present an approach capable of recording pure absorption spectra of individual nanostructures. We demonstrate the implementation of single-particle absorption spectroscopy on strongly scattering plasmonic nanoparticles by combining photothermal microscopy with a supercontinuum laser and an innovative calibration procedure that accounts for chromatic aberrations and wavelength-dependent excitation powers. Comparison of the absorption spectra to the scattering spectra of the same individual gold nanoparticles reveals the blueshift of the absorption spectra, as predicted by Mie theory but previously not detectable in extinction measurements that measure the sum of absorption and scattering. By covering a wavelength range of 300 nm, we are furthermore able to record absorption spectra of single gold nanorods with different aspect ratios. We find that the spectral shift between absorption and scattering for the longitudinal plasmon resonance decreases as a function of nanorod aspect ratio, which is in agreement with simulations.

Dedifferentiation-mediated stem cell niche maintenance in early-stage ductal carcinoma in situ progression: insights from a multiscale modeling study.

We present a multiscale agent-based model of ductal carcinoma in situ (DCIS) to study how key phenotypic and signaling pathways are involved in the early stages of disease progression. The model includes a phenotypic hierarchy, and key endocrine and paracrine signaling pathways, and simulates cancer ductal growth in a 3D lattice-free domain. In particular, by considering stochastic cell dedifferentiation plasticity, the model allows for study of how dedifferentiation to a more stem-like phenotype plays key roles in the maintenance of cancer stem cell populations and disease progression. Through extensive parameter perturbation studies, we have quantified and ranked how DCIS is sensitive to perturbations in several key mechanisms that are instrumental to early disease development. Our studies reveal that long-term maintenance of multipotent stem-like cell niches within the tumor are dependent on cell dedifferentiation plasticity, and that disease progression will become arrested due to dilution of the multipotent stem-like population in the absence of dedifferentiation. We have identified dedifferentiation rates necessary to maintain biologically relevant multipotent cell populations, and also explored quantitative relationships between dedifferentiation rates and disease progression rates, which may potentially help to optimize the efficacy of emerging anti-cancer stem cell therapeutics.

Mass Transport Model of Radiation Response: Calibration and Application to Chemoradiation for Pancreatic Cancer.

PURPOSE: The benefit of radiation therapy for pancreatic ductal adenocarcinoma (PDAC) remains unclear. We hypothesized that a new mechanistic mathematical model of chemotherapy and radiation response could predict clinical outcomes a priori, using a previously described baseline measurement of perfusion from computed tomography scans, normalized area under the enhancement curve (nAUC). METHODS AND MATERIALS: We simplified an existing mass transport model that predicted cancer cell death by replacing previously unknown variables with averaged direct measurements from randomly selected pathologic sections of untreated PDAC. This allowed using nAUC as the sole model input to approximate tumor perfusion. We then compared the predicted cancer cell death to the actual cell death measured from corresponding resected tumors treated with neoadjuvant chemoradiation in a calibration cohort (n = 80) and prospective cohort (n = 25). After calibration, we applied the model to 2 separate cohorts for pathologic and clinical associations: targeted therapy cohort (n = 101), cetuximab/bevacizumab + radiosensitizing chemotherapy, and standard chemoradiation cohort (n = 81), radiosensitizing chemotherapy to 50.4 Gy in 28 fractions. RESULTS: We established the relationship between pretreatment computed v nAUC to pathologically verified blood volume fraction of the tumor (r = 0.65; P = .009) and fractional tumor cell death (r = 0.97-0.99; P < .0001) in the calibration and prospective cohorts. On multivariate analyses, accounting for traditional covariates, nAUC independently associated with overall survival in all cohorts (mean hazard ratios, 0.14-0.31). Receiver operator characteristic analyses revealed discrimination of good and bad prognostic groups in the cohorts with area under the curve values of 0.64 to 0.71. CONCLUSIONS: This work presents a new mathematical modeling approach to predict clinical response from chemotherapy and radiation for PDAC. Our findings indicate that oxygen/drug diffusion strongly influences clinical responses and that nAUC is a potential tool to select patients with PDAC for radiation therapy.

A mathematical model for the quantification of a patient's sensitivity to checkpoint inhibitors and long-term tumour burden.

A large proportion of patients with cancer are unresponsive to treatment with immune checkpoint blockade and other immunotherapies. Here, we report a mathematical model of the time course of tumour responses to immune checkpoint inhibitors. The model takes into account intrinsic tumour growth rates, the rates of immune activation and of tumour-immune cell interactions, and the efficacy of immune-mediated tumour killing. For 124 patients, four cancer types and two immunotherapy agents, the model reliably described the immune responses and final tumour burden across all different cancers and drug combinations examined. In validation cohorts from four clinical trials of checkpoint inhibitors (with a total of 177 patients), the model accurately stratified the patients according to reduced or increased long-term tumour burden. We also provide model-derived quantitative measures of treatment sensitivity for specific drug-cancer combinations. The model can be used to predict responses to therapy and to quantify specific drug-cancer sensitivities in individual patients.

A Mathematical Model to Estimate Chemotherapy Concentration at the Tumor-Site and Predict Therapy Response in Colorectal Cancer Patients with Liver Metastases.

Chemotherapy remains a primary treatment for metastatic cancer, with tumor response being the benchmark outcome marker. However, therapeutic response in cancer is unpredictable due to heterogeneity in drug delivery from systemic circulation to solid tumors. In this proof-of-concept study, we evaluated chemotherapy concentration at the tumor-site and its association with therapy response by applying a mathematical model. By using pre-treatment imaging, clinical and biologic variables, and chemotherapy regimen to inform the model, we estimated tumor-site chemotherapy concentration in patients with colorectal cancer liver metastases, who received treatment prior to surgical hepatic resection with curative-intent. The differential response to therapy in resected specimens, measured with the gold-standard Tumor Regression Grade (TRG; from 1, complete response to 5, no response) was examined, relative to the model predicted systemic and tumor-site chemotherapy concentrations. We found that the average calculated plasma concentration of the cytotoxic drug was essentially equivalent across patients exhibiting different TRGs, while the estimated tumor-site chemotherapeutic concentration (eTSCC) showed a quadratic decline from TRG = 1 to TRG = 5 (p < 0.001). The eTSCC was significantly lower than the observed plasma concentration and dropped by a factor of ~5 between patients with complete response (TRG = 1) and those with no response (TRG = 5), while the plasma concentration remained stable across TRG groups. TRG variations were driven and predicted by differences in tumor perfusion and eTSCC. If confirmed in carefully planned prospective studies, these findings will form the basis of a paradigm shift in the care of patients with potentially curable colorectal cancer and liver metastases.

Education and Outreach in Physical Sciences in Oncology.

Physical sciences are often overlooked in the field of cancer research. The Physical Sciences in Oncology Initiative was launched to integrate physics, mathematics, chemistry, and engineering with cancer research and clinical oncology through education, outreach, and collaboration. Here, we provide a framework for education and outreach in emerging transdisciplinary fields.

Immunotherapeutic Transport Oncophysics: Space, Time, and Immune Activation in Cancer.

Immuno-oncology has gained momentum thanks to the success of strategies aimed at enhancing immune-mediated antitumor response. The field of immunotherapeutic transport oncophysics investigates the physical processes that drive cancer immunotherapies. This review discusses three main aspects that determine the outcome of an immunotherapy-based treatment from a physical point of view; (i) space, the distribution of cancer and immune cells within tumor masses, (ii) time, the temporal dynamic of immune response against tumors, and (iii) activity, the ability of immune cell populations to suppress cancer. Upon introducing these topics with examples from the literature, we investigate in detail two cases where the interplay between space, time, and activation variables determines immune response: nanodendritic cell vaccines and immunosuppression in ovarian cancer.

Molecular targeting of FATP4 transporter for oral delivery of therapeutic peptide.

Low oral bioavailability of peptide drugs has limited their application to parenteral administration, which suffers from poor patient compliance. Here, we show that molecular targeting of the FATP4 transporter is an effective approach to specifically transport long-chain fatty acid (LCFA)-conjugated peptides across the enterocytic membrane and, thus, enables oral delivery of drug peptides. We packaged LCFA-conjugated exendin-4 (LCFA-Ex4) into liposomes and coated with chitosan nanoparticles to form an orally deliverable Ex4 (OraEx4). OraEx4 protected LCFA-Ex4 from damage by the gastric fluid and released LCFA-Ex4 in the intestinal cavity, where LCFA-Ex4 was transported across the enterocyte membrane by the FAPT4 transporter. OraEx4 had a high bioavailability of 24.8% with respect to subcutaneous injection and exhibited a substantial hypoglycemic effect in murine models of diabetes mellitus. Thus, molecular targeting of the FATP4 transporter enhances oral absorption of therapeutic peptides and provides a platform for oral peptide drug development.

Retraction of the Research Article: "Molecular targeting of FATP4 transporter for oral delivery of therapeutic peptide" by Z. Hu, S. Nizzero, S. Goel, L. E. Hinkle, X. Wu, C. Li, M. Ferrari and H. Shen.

[This retracts the article DOI: 10.1126/sciadv.aba0145.].

Sequential deconstruction of composite drug transport in metastatic breast cancer.

It is challenging to design effective drug delivery systems (DDS) that target metastatic breast cancers (MBC) because of lack of competent imaging and image analysis protocols that suitably capture the interactions between DDS and metastatic lesions. Here, we integrate high temporal resolution of in vivo whole-body PET-CT, ex vivo whole-organ optical imaging, high spatial resolution of confocal microscopy, and mathematical modeling, to systematically deconstruct the trafficking of injectable nanoparticle generators encapsulated with polymeric doxorubicin (iNPG-pDox) in pulmonary MBC. iNPG-pDox accumulated substantially in metastatic lungs, compared to healthy lungs. Intratumoral distribution and retention of iNPG-pDox varied with lesion size, possibly induced by locally remodeled microenvironment. We further used multiscale imaging and mathematical simulations to provide improved drug delivery strategies for MBC. Our work presents a multidisciplinary translational toolbox to evaluate transport and interactions of DDS within metastases. This knowledge can be recursively applied to rationally design advanced therapies for metastatic cancers.

Image-guided mathematical modeling for pharmacological evaluation of nanomaterials and monoclonal antibodies.

While plasma concentration kinetics has traditionally been the predictor of drug pharmacological effects, it can occasionally fail to represent kinetics at the site of action, particularly for solid tumors. This is especially true in the case of delivery of therapeutic macromolecules (drug-loaded nanomaterials or monoclonal antibodies), which can experience challenges to effective delivery due to particle size-dependent diffusion barriers at the target site. As a result, disparity between therapeutic plasma kinetics and kinetics at the site of action may exist, highlighting the importance of target site concentration kinetics in determining the pharmacodynamic effects of macromolecular therapeutic agents. Assessment of concentration kinetics at the target site has been facilitated by non-invasive in vivo imaging modalities. This allows for visualization and quantification of the whole-body disposition behavior of therapeutics that is essential for a comprehensive understanding of their pharmacokinetics and pharmacodynamics. Quantitative non-invasive imaging can also help guide the development and parameterization of mathematical models for descriptive and predictive purposes. Here, we present a review of the application of state-of-the-art imaging modalities for quantitative pharmacological evaluation of therapeutic nanoparticles and monoclonal antibodies, with a focus on their integration with mathematical models, and identify challenges and opportunities. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease Diagnostic Tools > in vivo Nanodiagnostics and Imaging Nanotechnology Approaches to Biology > Nanoscale Systems in Biology.

Smeared Multiscale Finite Element Models for Mass Transport and Electrophysiology Coupled to Muscle Mechanics.

Mass transport represents the most fundamental process in living organisms. It includes delivery of nutrients, oxygen, drugs, and other substances from the vascular system to tissue and transport of waste and other products from cells back to vascular and lymphatic network and organs. Furthermore, movement is achieved by mechanical forces generated by muscles in coordination with the nervous system. The signals coming from the brain, which have the character of electrical waves, produce activation within muscle cells. Therefore, from a physics perspective, there exist a number of physical fields within the body, such as velocities of transport, pressures, concentrations of substances, and electrical potential, which is directly coupled to biochemical processes of transforming the chemical into mechanical energy and further internal forces for motion. The overall problems of mass transport and electrophysiology coupled to mechanics can be investigated theoretically by developing appropriate computational models. Due to the enormous complexity of the biological system, it would be almost impossible to establish a detailed computational model for the physical fields related to mass transport, electrophysiology, and coupled fields. To make computational models feasible for applications, we here summarize a concept of smeared physical fields, with coupling among them, and muscle mechanics, which includes dependence on the electrical potential. Accuracy of the smeared computational models, also with coupling to muscle mechanics, is illustrated with simple example, while their applicability is demonstrated on a liver model with tumors present. The last example shows that the introduced methodology is applicable to large biological systems.

Systematic comparison of methods for determining the in vivo biodistribution of porous nanostructured injectable inorganic particles.

With a wide variety of biodistribution measurement techniques reported in the literature, it is important to perform side-by-side comparisons of results obtained with different methods on the same particle platform, to determine differences across methods, highlight advantages and disadvantages, and inform methods selection according to specific applications. Inorganic nanostructured particles (INPs) have gained a central role in the development of injectable delivery vectors thanks to their controllable design, biocompatibility, and favorable degradation kinetic. Thus, accurate determination of in vivo biodistribution of INPs is a key aspect of developing and optimizing this class of delivery vectors. In this study, a systematic comparison of spectroscopy (inductively coupled plasma optical emission spectroscopy), fluorescence (in vivo imaging system, confocal microscopy, and plate reader), and radiolabeling (gamma counter)-based techniques is performed to assess the accuracy and sensitivity of biodistribution measurements in mice. Each method is evaluated on porous silicon particles, an established and versatile injectable delivery platform. Biodistribution is evaluated in all major organs and compared in terms of absolute results (%ID/g and %ID/organ when possible) and sensitivity (σ%). Finally, we discuss how these results can be extended to inform method selection for other platforms and specific applications, with an outlook to potential benefit for pre-clinical and clinical studies. Overall, this study presents a new practical guide for selection of in vivo biodistribution methods that yield quantitative results. STATEMENT OF SIGNIFICANCE: The significance of this work lies in the use of a single platform to test performances of different biodistribution methods in vivo, with a strict quantitative metric. These results, united with the qualitative comparison of advantages and disadvantages of each technique, are aimed at supporting the rational choice of each different method according to the specific application, to improve the quantitative description of biodistribution results that will be published by others in the future.

Transport Barriers and Oncophysics in Cancer Treatment.

Transport processes in cancer are the focus of transport oncophysics (TOP). In the TOP approach, the sequential negotiation of transport barriers is critical to both drug delivery and metastasis development. New and creative therapeutic opportunities are currently emerging, stimulated by the study of cancer hallmarks with the TOP approach.

A chloroquine-induced macrophage-preconditioning strategy for improved nanodelivery.

Site-specific localization is critical for improving the therapeutic efficacy and safety of drugs. Nanoparticles have emerged as promising tools for localized drug delivery. However, over 90% of systemically injected nanocarriers typically accumulate in the liver and spleen due to resident macrophages that form the mononuclear phagocyte system. In this study, the clinically approved antimalarial agent chloroquine was shown to reduce nanoparticle uptake in macrophages by suppressing endocytosis. Pretreatment of mice with a clinically relevant dose of chloroquine substantially decreased the accumulation of liposomes and silicon particles in the mononuclear phagocyte system and improved tumoritropic and organotropic delivery. The novel use of chloroquine as a macrophage-preconditioning agent presents a straightforward approach for addressing a major barrier in nanomedicine. Moreover, this priming strategy has broad applicability for improving the biodistribution and performance of particulate delivery systems. Ultimately, this study defines a paradigm for the combined use of macrophage-modulating agents with nanotherapeutics for improved site-specific delivery.

Bone-targeting nanoparticle to co-deliver decitabine and arsenic trioxide for effective therapy of myelodysplastic syndrome with low systemic toxicity.

Myelodysplastic syndromes (MDS) are a diverse group of bone marrow disorders and clonal hematopoietic stem cell disorders characterized by abnormal blood cells, or reduced peripheral blood cell count. Recent clinical studies on combination therapy of decitabine (DAC) and arsenic trioxide (ATO) have demonstrated synergy on MDS treatment, but the treatment can cause significant side effects to patients. In addition, both drugs have to be administered on a daily basis due to their short half-lives. In addressing key issues of reducing toxic side effects and improving pharmacokinetic profiles of the therapeutic agents, we have developed a new formulation by co-packaging DAC and ATO into alendronate-conjugated bone-targeting nanoparticles (BTNPs). Our pharmacokinetic studies revealed that intravenously administered BTNPs increased circulation time up to 3days. Biodistribution analysis showed that the BTNP facilitated DAC and ATO accumulation in the bone, which is 6.7 and 7.9 times more than untargeted NP. Finally, MDS mouse model treated with BTNPs showed better restoration of complete blood count to normal level, and significantly longer median survival as compared to free drugs or untargeted NPs treatment. Our results support bone-targeted co-delivery of DAC and ATO for effective treatment of MDS.