Early ctDNA kinetics as a dynamic biomarker of cancer treatment response.

Circulating tumor DNA assays are promising tools for the prediction of cancer treatment response. Here, we build a framework for the design of ctDNA biomarkers of therapy response that incorporate variations in ctDNA dynamics driven by specific treatment mechanisms. We develop mathematical models of ctDNA kinetics driven by tumor response to several therapy classes, and utilize them to simulate randomized virtual patient cohorts to test candidate biomarkers. Using this approach, we propose specific biomarkers, based on ctDNA longitudinal features, for targeted therapy, chemotherapy and radiation therapy. We evaluate and demonstrate the efficacy of these biomarkers in predicting treatment response within a randomized virtual patient cohort dataset. These biomarkers are based on novel proposals for ctDNA sampling protocols, consisting of frequent sampling within a compact time window surrounding therapy initiation - which we hypothesize to hold valuable prognostic information on longer-term treatment response. This study highlights a need for tailoring ctDNA sampling protocols and interpretation methodology to specific biological mechanisms of therapy response, and it provides a novel modeling and simulation framework for doing so. In addition, it highlights the potential of ctDNA assays for making early, rapid predictions of treatment response within the first days or weeks of treatment, and generates hypotheses for further clinical testing.

Biomacromolecular Characterizations Using State-of-the-Art Quartz Crystal Microbalance with Dissipation.

Biomolecular characterization is essential in fields such as drug discovery, glycomics, and cell biology. This feature article focuses on the experimental use of quartz crystal microbalance with dissipation (QCM-D) as a powerful analytical technique to probe biological events ranging from biomacromolecular interactions and conformational changes of biomacromolecules to surface immobilization of biomacromolecules and cell morphological changes.

A comparison of mutation and amplification-driven resistance mechanisms and their impacts on tumor recurrence.

Tumor recurrence, driven by the evolution of drug resistance is a major barrier to therapeutic success in cancer. Tumor drug resistance is often caused by genetic alterations such as point mutation, which refers to the modification of a single genomic base pair, or gene amplification, which refers to the duplication of a region of DNA that contains a gene. These mechanisms typically confer varying degrees of resistance, and they tend to occur at vastly different frequencies. Here we investigate the dependence of tumor recurrence dynamics on these mechanisms of resistance, using stochastic multi-type branching process models. We derive tumor extinction probabilities and deterministic estimates for the tumor recurrence time, defined as the time when an initially drug sensitive tumor surpasses its original size after developing resistance. For models of amplification-driven and mutation-driven resistance, we prove law of large numbers results regarding the convergence of the stochastic recurrence times to their mean. Additionally, we prove sufficient and necessary conditions for a tumor to escape extinction under the gene amplification model, discuss behavior under biologically relevant parameters, and compare the recurrence time and tumor composition in the mutation and amplification models both analytically and using simulations. In comparing these mechanisms, we find that the ratio between recurrence times driven by amplification versus mutation depends linearly on the number of amplification events required to acquire the same degree of resistance as a mutation event, and we find that the relative frequency of amplification and mutation events plays a key role in determining the mechanism under which recurrence is more rapid for any specific system. In the amplification-driven resistance model, we also observe that increasing drug concentration leads to a stronger initial reduction in tumor burden, but that the eventual recurrent tumor population is less heterogeneous, more aggressive and harbors higher levels of drug-resistance.

A Comparison of Mutation and Amplification-Driven Resistance Mechanisms and Their Impacts on Tumor Recurrence.

Tumor recurrence, driven by the evolution of drug resistance is a major barrier to therapeutic success in cancer. Resistance is often caused by genetic alterations such as point mutation, which refers to the modification of a single genomic base pair, or gene amplification, which refers to the duplication of a region of DNA that contains a gene. Here we investigate the dependence of tumor recurrence dynamics on these mechanisms of resistance, using stochastic multi-type branching process models. We derive tumor extinction probabilities and deterministic estimates for the tumor recurrence time, defined as the time when an initially drug sensitive tumor surpasses its original size after developing resistance. For models of amplification-driven and mutation-driven resistance, we prove law of large numbers results regarding the convergence of the stochastic recurrence times to their mean. Additionally, we prove sufficient and necessary conditions for a tumor to escape extinction under the gene amplification model, discuss behavior under biologically relevant parameters, and compare the recurrence time and tumor composition in the mutation and amplification models both analytically and using simulations. In comparing these mechanisms, we find that the ratio between recurrence times driven by amplification vs. mutation depends linearly on the number of amplification events required to acquire the same degree of resistance as a mutation event, and we find that the relative frequency of amplification and mutation events plays a key role in determining the mechanism under which recurrence is more rapid. In the amplification-driven resistance model, we also observe that increasing drug concentration leads to a stronger initial reduction in tumor burden, but that the eventual recurrent tumor population is less heterogeneous, more aggressive, and harbors higher levels of drug-resistance.

A Factor XIa Inhibitor Engineered from Banded Krait Venom Toxin: Efficacy and Safety in Rodent Models of Arterial and Venous Thrombosis.

Activated factor XI (FXIa) is an important antithrombotic drug target. Clinical and pre-clinical data have demonstrated that its inhibition attenuates thrombosis with minimal risk of excessive bleeding. We isolated Fasxiator from the venom of banded krait Bungarus fasciatus and subsequently engineered FasxiatorN17R,L19E, with improved affinity (Ki = 0.9 nM) and selectivity towards FXIa. Here, we assess the in vivo efficacy and bleeding risk of rFasxiatorN17R, L19E in pre-clinical animal models. Rats injected intravenously (i.v.) with bolus rFasxiatorN17R, L19E showed the specific in vivo attenuation of the intrinsic coagulation pathway, lasting for at least 60 min. We performed the in vivo dose-ranging experiments for rFasxiatorN17R, L19E as follows: FeCl3-induced carotid artery occlusion in rats (arterial thrombosis); inferior vena cava ligation in mice (venous thrombosis); tail bleeding time in both rats and mice (bleeding risk). Head-to-head comparisons were made using therapeutic dosages of unfractionated heparin (UFH) and low-molecular-weight heparin (LMWH) for arterial and venous thrombosis, respectively. In the arterial thrombosis model, 2 mg/kg i.v. rFasxiatorN17R,L19E achieved a similar antithrombotic efficacy to that of UFH, with >3-fold lower bleeding time. In the venous thrombosis model, the 10 mg/kg subcutaneous (s.c.) injection of rFasxiatorN17R,L19E achieved similar efficacy and bleeding levels to those of LMWH enoxaparin. Overall, rFasxiatorN17R,L19E represents a promising molecule for the development of FXIa-targeting anticoagulants.

Efficacy and safety of next-generation tick transcriptome-derived direct thrombin inhibitors.

Despite their limitations, unfractionated heparin (UFH) and bivalirudin remain standard-of-care parenteral anticoagulants for percutaneous coronary intervention (PCI). We discovered novel direct thrombin inhibitors (DTIs) from tick salivary transcriptomes and optimised their pharmacologic activity. The most potent, ultravariegin, inhibits thrombin with a Ki of 4.0 pM, 445-fold better than bivalirudin. Unexpectedly, despite their greater antithrombotic effect, variegin/ultravariegin demonstrated less bleeding, achieving a 3-to-7-fold wider therapeutic index in rodent thrombosis and bleeding models. When used in combination with aspirin and ticagrelor in a porcine model, variegin/ultravariegin reduced stent thrombosis compared with antiplatelet therapy alone but achieved a 5-to-7-fold lower bleeding time than UFH/bivalirudin. Moreover, two antibodies screened from a naïve human antibody library effectively reversed the anticoagulant activity of ultravariegin, demonstrating proof-of-principle for antidote reversal. Variegin and ultravariegin are promising translational candidates for next-generation DTIs that may reduce peri-PCI bleeding in the presence of antiplatelet therapy.

Deletion of Mfsd2b impairs thrombotic functions of platelets.

We recently discovered that Mfsd2b, which is the S1P exporter found in blood cells. Here, we report that Mfsd2b is critical for the release of all S1P species in both resting and activated platelets. We show that resting platelets store S1P in the cytoplasm. After activation, this S1P pool is delivered to the plasma membrane, where Mfsd2b is predominantly localized for export. Employing knockout mice of Mfsd2b, we reveal that platelets contribute a minor amount of plasma S1P. Nevertheless, Mfsd2b deletion in whole body or platelets impairs platelet morphology and functions. In particular, Mfsd2b knockout mice show significantly reduced thrombus formation. We show that loss of Mfsd2b affects intrinsic platelet functions as part of remarkable sphingolipid accumulation. These findings indicate that accumulation of sphingolipids including S1P by deletion of Mfsd2b strongly impairs platelet functions, which suggests that the transporter may be a target for the prevention of thrombotic disorders.

Importance of the heart vector origin point definition for an ECG analysis: The Atherosclerosis Risk in Communities (ARIC) study.

AIM: Our goal was to investigate the effect of a global XYZ median beat construction and the heart vector origin point definition on predictive accuracy of ECG biomarkers of sudden cardiac death (SCD). METHODS: Atherosclerosis Risk In Community study participants with analyzable digital ECGs were included (n = 15,768; 55% female, 73% white, mean age 54.2 ±â€¯5.8 y). We developed an algorithm to automatically detect the heart vector origin point on a median beat. Three different approaches to construct a global XYZ beat and two methods to locate origin point were compared. Global electrical heterogeneity was measured by sum absolute QRST integral (SAI QRST), spatial QRS-T angle, and spatial ventricular gradient (SVG) magnitude, azimuth, and elevation. Adjudicated SCD served as the primary outcome. RESULTS: There was high intra-observer (kappa 0.972) and inter-observer (kappa 0.984) agreement in a heart vector origin definition between an automated algorithm and a human. QRS was wider in a median beat that was constructed using R-peak alignment than in time-coherent beat (88.1 ±â€¯16.7 vs. 83.7 ±â€¯15.9 ms; P < 0.0001), and on a median beat constructed using QRS-onset as a zeroed baseline, vs. isoelectric origin point (86.7 ±â€¯15.9 vs. 83.7 ±â€¯15.9 ms; P < 0.0001). ROC AUC was significantly larger for QRS, QT, peak QRS-T angle, SVG elevation, and SAI QRST if measured on a time-coherent median beat, and for SAI QRST and SVG magnitude if measured on a median beat using isoelectric origin point. CONCLUSION: Time-coherent global XYZ median beat with physiologically meaningful definition of the heart vector's origin point improved predictive accuracy of SCD biomarkers.