Biology subjects

Belcher, A.

Publications and source records attributed to Belcher, A..

5 recordsLinked to original sources

bioRxiv2024

Reprogramming the genome of M13 bacteriophage for all-in-one personalized cancer vaccine

Peptide-based vaccines face limitations in immunogenicity and stability, and challenges in co-delivering antigens and adjuvants effectively. Virus-based nanoparticles, particularly M13 bacteriophage, present a promising solution due to their genetic modifiability, intrinsic adjuvanticity, and efficient antigen presentation capabilities. Here we developed a programmable M13 phage-based personalized cancer vaccine enabling single-step antigen-adjuvant assembly. Specifically, we designed a reprogrammed (RP) phage platform that precisely regulates Toll-like receptor 9 activation by programming its genome sequence and modulates antigen density through genetic engineering. Vaccination studies with RP phages demonstrated that the immune response could be modulated by fine-tuning the adjuvanticity and antigen density, revealing an optimal antigen dose and adjuvanticity for maximum vaccine efficacy. The RP phage induced a remarkable 24-fold increase in neoantigen-specific CD8+ T cells and eradicated established MC-38 tumors when combined with anti-PD-1 therapy. These findings highlight the RP phages potential as a powerful nanovaccine platform for personalized cancer vaccines.

bioengineering↗

bioRxiv2024

Optimal Prescriptive Treatments for Ovarian Cancer with Genetic Data

Among the cancers affecting the female population, Ovarian Cancer (OC), while being relatively rare, is the leading cause of gynecological cancer-related deaths, with overall 5-year survival rates of approximately 50% for all stages combined. This is because of the challenges associated with the diagnosis, resulting in detection at advanced stages of OC, coupled with the slow progress in effective treatment options since the approval of platinum-based chemotherapy in the late 1970s. There has been a relative lack of sophisticated methods based on Machine Learning (ML) models that use genetic data for better prediction of Ovarian Cancer outcomes and result in more effective treatment recommendations. Therefore, there is an unmet clinical need to create models that allow physicians to make informed decisions based on all available data, including patient demographic, social, health, and genomic data. Hence, we develop new techniques for leveraging genetic information in prescribing optimal treatments for patients with OC, using a publicly available dataset from the Prostate, Lung, Colorectal and Ovarian Cancer (PLCO) trial. Our approach is able to transform genotype sequencing information into a simple tabular form that can then be used as the input to any ML model. Coupled with the recorded treatment regimen and clinical parameters of matched patients from the genetic dataset, we estimate the treatment effect in terms of mortality prediction and use it to prescribe the optimal treatment for any given patient. By including the genetic features engineered through our proposed method, our models have a higher accuracy than the models without genetic information embedded. The increase in predictive accuracy demonstrates the improved efficacy of our method in the predictive setting. Furthermore, in the prescriptive setting, the models including genetic features output different treatment choices for patients, showing the impact of their inclusion. This is further highlighted by the feature importance of the genetic features such as mutations in the FAT3, BRCA1, BRCA2, and NF1 genes, where they rank highly with a tighter aggregation of the top features, relative to the sharp drop-off in feature importance after the top feature in the models without genetic data. Taken together, in summary, our models will allow oncologists to make more informed and accurate decisions, incorporating a patients genetic data with all other available clinical information, which has the potential for improved prognosis and better long-term survival outcomes for Ovarian Cancer patients.

cancer biology↗

bioRxiv2023

Valuing carbon sequestration by Antarctic krill faecal pellets

Marine life contribute to carbon stores helping lock carbon away from the atmosphere. Open-ocean pelagic ecosystems are vastly under-reported in terms of carbon sequestration conservation potential, compared to coastal vegetation blue carbon systems. Here we show that a harvested organism, Antarctic krill, has similar carbon sequestration potential through its sinking faecal pellets as coastal blue carbon stores, namely seagrasses, mangroves and marshes. Building upon recent advances in krill abundance and faecal pellet carbon flux data, and combining these with an ocean circulation model, we show that from Austral spring to early autumn Antarctic krill sequester 20 Mt C into the deep ocean for at least 100 years. This equates to USD$ 4 - 46 billion per spring/summer season depending on the price of carbon. The footprint of remineralised krill pellet carbon has a global extent, with some reaching as far as the North Pacific. The vast area of ocean krill inhabit and their high abundance make their total carbon sequestered each year similar to that from coastal vegetated blue carbon stores. As Antarctic krill are being impacted by rapid polar climate change and they are harvested, both krill populations and their habitat warrant protection to preserve this valuable carbon sink.

ecology↗

bioRxiv2023

A Machine Learning-optimized system for on demand, pulsatile, photo- and chemo-therapeutic treatment using near-infrared responsive MoS2-based microparticles in a breast cancer model

Cancer therapy research is of high interest because of the persistence and mortality of the disease and the side effects of traditional therapeutic methods, while often multimodal treatments are necessary based on the patients needs. The development of less invasive modalities for recurring treatment cycles is thus of critical significance. Herein, a light-activatable microparticle system was developed for localized, pulsatile delivery of anticancer drugs with simultaneous thermal ablation, by applying controlled ON-OFF thermal cycles using near-infrared laser irradiation. The system is composed of poly(caprolactone) microparticles of 200 m size with incorporated molybdenum disulfide (MoS2) nanosheets as the photothermal agent and hydrophilic doxorubicin or hydrophobic violacein, as model drugs. Upon irradiation the nanosheets heat up to [≥]50 {degrees}C leading to polymer matrix melting and release of the drug. MoS2 nanosheets exhibit high photothermal conversion efficiency and allow for application of low power laser irradiation for the system activation. A Machine Learning algorithm was applied to acquire optimal laser operation conditions; 0.4 W/cm2 laser power at 808 nm, 3-cycle irradiation, for 3 cumulative minutes. In a mouse subcutaneous model of 4T1 triple-negative breast cancer, 25 microparticles were intratumorally administered and after 3-cycle laser treatment the system conferred synergistic phototherapeutic and chemotherapeutic effect. Our on-demand, pulsatile synergistic treatment resulted in increased median survival up to 40 days post start of treatment compared to untreated mice, with complete eradication of the tumors at the primary site. Such a system could have potential for patients in need of recurring cycles of treatment on subcutaneous tumors. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=56 SRC="FIGDIR/small/536750v1_ufig1.gif" ALT="Figure 1"> View larger version (11K): org.highwire.dtl.DTLVardef@14ab0f3org.highwire.dtl.DTLVardef@a72649org.highwire.dtl.DTLVardef@1c28608org.highwire.dtl.DTLVardef@1ed9c06_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2020

Targeting Thymidine Phosphorylase with Tipiracil Hydrochloride is a Safe and Effective Antithrombotic Therapy

RationaleMost of the current anti-platelet drugs inhibit platelet function permanently and have systemic side effects, including thrombocytopenia and hemorrhage. We previously found that thymidine phosphorylase (TYMP), a platelet cytoplasmic protein, facilitates multiple agonist induced platelet activation and enhances thrombosis. A specific TYMP inhibitor, namely, tipiracil hydrochloride (TPI), has been approved by the U.S. Food and Drug Administration for clinical use as an auxiliary drug making it possible to be repositioned as an anti-platelet medicine. ObjectiveWe aimed to test the hypothesis that TPI is a novel and safe anti-platelet drug by examining its role in platelet activation and thrombosis using both in vitro and in vivo studies. Methods and ResultsBy co-expression of TYMP and Lyn or Lyn-SH3 domain tagged with glutathione S-transferase, we showed the direct evidence that TYMP binds to the SH3 domain in its partners. TYMP haplodeficiency is sufficient to inhibit thrombosis in vivo regardless of gender. TPI treatment rapidly inhibited collagen- and ADP-induced platelet aggregation, which copied the phenotype of TYMP deficient platelets. Under both normal and hyperlipidemic conditions, treating wild type (WT) mice with TPI via intraperitoneal injection, intravenous injection, or gavage feeding dramatically inhibited thrombosis without inducing significant bleeding. Even administered above the effective dose, TPI has a lower bleeding side effect compared to aspirin and clopidogrel. Most importantly, intravenously delivery of TPI alone or combined with tissue plasminogen activator dramatically inhibited the growth of developing thrombi. Dual administration of very low dose of aspirin and TPI also dramatically inhibited thrombosis without disturbing hemostasis. ConclusionThis pharmacological study demonstrated that TYMP participates in multiple signaling pathways in platelet and plays a mechanistic role in regulating platelet activation and thrombosis. TPI, a specific TYMP inhibitor, would be a novel safe anti-platelet and anti-thrombosis medicine.

cell biology↗