Generative artificial intelligence performs rudimentary structural biology modeling.

Natural language-based generative artificial intelligence (AI) has become increasingly prevalent in scientific research. Intriguingly, capabilities of generative pre-trained transformer (GPT) language models beyond the scope of natural language tasks have recently been identified. Here we explored how GPT-4 might be able to perform rudimentary structural biology modeling. We prompted GPT-4 to model 3D structures for the 20 standard amino acids and an α-helical polypeptide chain, with the latter incorporating Wolfram mathematical computation. We also used GPT-4 to perform structural interaction analysis between nirmatrelvir and its target, the SARS-CoV-2 main protease. Geometric parameters of the generated structures typically approximated close to experimental references. However, modeling was sporadically error-prone and molecular complexity was not well tolerated. Interaction analysis further revealed the ability of GPT-4 to identify specific amino acid residues involved in ligand binding along with corresponding bond distances. Despite current limitations, we show the capacity of natural language generative AI to perform basic structural biology modeling and interaction analysis with atomic-scale accuracy.

Integrated metabolic and genetic analysis reveals distinct features of human differentiated thyroid cancer.

BACKGROUND: Differentiated thyroid cancer (DTC) affects thousands of lives worldwide each year. Typically, DTC is a treatable disease with a good prognosis. Yet, some patients are subjected to partial or total thyroidectomy and radioiodine therapy to prevent local disease recurrence and metastasis. Unfortunately, thyroidectomy and/or radioiodine therapy often worsen(s) quality of life and might be unnecessary in indolent DTC cases. On the other hand, the lack of biomarkers indicating a potential metastatic thyroid cancer imposes an additional challenge to managing and treating patients with this disease. AIM: The presented clinical setting highlights the unmet need for a precise molecular diagnosis of DTC and potential metastatic disease, which should dictate appropriate therapy. MATERIALS AND METHODS: In this article, we present a differential multi-omics model approach, including metabolomics, genomics, and bioinformatic models, to distinguish normal glands from thyroid tumours. Additionally, we are proposing biomarkers that could indicate potential metastatic diseases in papillary thyroid cancer (PTC), a sub-class of DTC. RESULTS: Normal and tumour thyroid tissue from DTC patients had a distinct yet well-defined metabolic profile with high levels of anabolic metabolites and/or other metabolites associated with the energy maintenance of tumour cells. The consistency of the DTC metabolic profile allowed us to build a bioinformatic classification model capable of clearly distinguishing normal from tumor thyroid tissues, which might help diagnose thyroid cancer. Moreover, based on PTC patient samples, our data suggest that elevated nuclear and mitochondrial DNA mutational burden, intra-tumour heterogeneity, shortened telomere length, and altered metabolic profile reflect the potential for metastatic disease. DISCUSSION: Altogether, this work indicates that a differential and integrated multi-omics approach might improve DTC management, perhaps preventing unnecessary thyroid gland removal and/or radioiodine therapy. CONCLUSIONS: Well-designed, prospective translational clinical trials will ultimately show the value of this integrated multi-omics approach and early diagnosis of DTC and potential metastatic PTC.

Preclinical optimization of a diode laser-based clamp-free partial nephrectomy in a large animal model.

Kidney cancer is a common urologic malignancy with either laparoscopic (LPN) or robotic partial nephrectomy as therapeutic options of choice for localized tumors. However, renal resection and suturing are challenging steps of the procedure that can lead to complications such as prolonged warm ischemia, bleeding, and urinary fistulas. LPN with a diode laser is an efficient technique due to its cutting and/or coagulation attributes. Surprisingly, key laser features such as wavelength and power remain undefined. Using a large porcine model, we evaluated the laser range of wavelength and power in a clamp-free LPN and compared it to the established gold-standard LPN technique (i.e., cold-cutting and suturing). By analyzing surgery duration, bleeding, presence of urine leak, tissue damage related to the resected renal fragment and the remaining organ, hemoglobin levels, and renal function, we show that an optimized experimental diode laser clamp-free LPN (wavelength, 980 nm; power, 15 W) had shorter surgery time with less bleeding, and better postoperative renal function recovery when compared to the well-established technique. Together, our data indicate that partial nephrectomy with a diode laser clamp-free LPN technique is an improved alternative to the gold-standard technique. Therefore, translational clinical trials towards human patient applications are readily feasible.

Integrated metabolic and genetic analysis reveals distinct features of primary differentiated thyroid cancer and its metastatic potential in humans.

Differentiated thyroid cancer (DTC) affects thousands of lives worldwide every year. Typically, DTC is a treatable disease with a good prognosis. Yet, some patients are subjected to partial or total thyroidectomy and radioiodine therapy to prevent local disease recurrence and metastasis. Unfortunately, thyroidectomy and/or radioiodine therapy often worsen(s) the quality of life and might be unnecessary in indolent DTC cases. This clinical setting highlights the unmet need for a precise molecular diagnosis of DTC, which should dictate appropriate therapy. Here we propose a differential multi-omics model approach to distinguish normal gland from thyroid tumor and to indicate potential metastatic diseases in papillary thyroid cancer (PTC), a sub-class of DTC. Based on PTC patient samples, our data suggest that elevated nuclear and mitochondrial DNA mutational burden, intratumor heterogeneity, shortened telomere length, and altered metabolic profile reflect the potential for metastatic disease. Specifically, normal and tumor thyroid tissues from these patients had a distinct yet well-defined metabolic profile with high levels of anabolic metabolites and/or other metabolites associated with the energy maintenance of tumor cells. Altogether, this work indicates that a differential and integrated multi-omics approach might improve DTC management, perhaps preventing unnecessary thyroid gland removal and/or radioiodine therapy. Well-designed, prospective translational clinical trials will ultimately show the value of this targeted molecular approach. TRANSLATIONAL RELEVANCE: In this article, we propose a new integrated metabolic, genomic, and cytopathologic methods to diagnose Differentiated Thyroid Cancer when the conventional methods failed. Moreover, we suggest metabolic and genomic markers to help predict high-risk Papillary Thyroid Cancer. Both might be important tools to avoid unnecessary surgery and/or radioiodine therapy that can worsen the quality of life of the patients more than living with an indolent Thyroid nodule.

Dysregulation of the PRUNE2/PCA3 genetic axis in human prostate cancer: from experimental discovery to validation in two independent patient cohorts.

Background: We have previously shown that the long non-coding (lnc)RNA prostate cancer associated 3 (PCA3; formerly prostate cancer antigen 3) functions as a trans-dominant negative oncogene by targeting the previously unrecognized prostate cancer suppressor gene PRUNE2 (a homolog of the Drosophila prune gene), thereby forming a functional unit within a unique allelic locus in human cells. Here, we investigated the PCA3/PRUNE2 regulatory axis from early (tumorigenic) to late (biochemical recurrence) genetic events during human prostate cancer progression. Methods: The reciprocal PCA3 and PRUNE2 gene expression relationship in paired prostate cancer and adjacent normal prostate was analyzed in two independent retrospective cohorts of clinically annotated cases post-radical prostatectomy: a single-institutional discovery cohort (n=107) and a multi-institutional validation cohort (n=497). We compared the tumor gene expression of PCA3 and PRUNE2 to their corresponding expression in the normal prostate. We also serially examined clinical/pathological variables including time to disease recurrence. Results: We consistently observed increased expression of PCA3 and decreased expression of PRUNE2 in prostate cancer compared with the adjacent normal prostate across all tumor grades and stages. However, there was no association between the relative gene expression levels of PCA3 or PRUNE2 and time to disease recurrence, independent of tumor grades and stages. Conclusions: We concluded that upregulation of the lncRNA PCA3 and targeted downregulation of the protein-coding PRUNE2 gene in prostate cancer could be early (rather than late) molecular events in the progression of human prostate tumorigenesis but are not associated with biochemical recurrence. Further studies of PCA3/PRUNE2 dysregulation are warranted. Funding: We received support from the Human Tissue Repository and Tissue Analysis Shared Resource from the Department of Pathology of the University of New Mexico School of Medicine and a pilot award from the University of New Mexico Comprehensive Cancer Center. RP and WA were supported by awards from the Levy-Longenbaugh Donor-Advised Fund and the Prostate Cancer Foundation. EDN reports research fellowship support from the Brazilian National Council for Scientific and Technological Development (CNPq), Brazil, and the Associação Beneficente Alzira Denise Hertzog Silva (ABADHS), Brazil. This work has been funded in part by the NCI Cancer Center Support Grants (CCSG; P30) to the University of New Mexico Comprehensive Cancer Center (CA118100) and the Rutgers Cancer Institute of New Jersey (CA072720).

A modeling-based approach to optimize COVID-19 vaccine dosing schedules for improved protection.

While the development of different vaccines has slowed the dissemination of SARS-CoV-2, the occurrence of breakthrough infections continues to fuel the pandemic. As a strategy to secure at least partial protection, with a single dose of a given COVID-19 vaccine to maximum possible fraction of the population, delayed administration of subsequent doses (or boosters) has been implemented in many countries. However, waning immunity and emergence of new variants of SARS-CoV-2 suggest that such measures may jeopardize the attainment of herd immunity due to intermittent lapses in protection. Optimizing vaccine dosing schedules could thus make the difference between periodic occurrence of breakthrough infections or effective control of the pandemic. To this end, we have developed a mechanistic mathematical model of adaptive immune response to vaccines and demonstrated its applicability to COVID-19 mRNA vaccines as a proof-of-concept for future outbreaks. The model was thoroughly calibrated against multiple clinical datasets involving immune response to SARS-CoV-2 infection and mRNA vaccines in healthy and immunocompromised subjects (cancer patients undergoing therapy); the model showed robust clinical validation by accurately predicting neutralizing antibody kinetics, a correlate of vaccine-induced protection, in response to multiple doses of mRNA vaccines. Importantly, we estimated population vulnerability to breakthrough infections and predicted tailored vaccination dosing schedules to maximize protection and thus minimize breakthrough infections, based on the immune status of a sub-population. We have identified a critical waiting window for cancer patients (or, immunocompromised subjects) to allow recovery of the immune system (particularly CD4+ T-cells) for effective differentiation of B-cells to produce neutralizing antibodies and thus achieve optimal vaccine efficacy against variants of concern, especially between the first and second doses. Also, we have obtained optimized dosing schedules for subsequent doses in healthy and immunocompromised subjects, which vary from the CDC-recommended schedules, to minimize breakthrough infections. The developed modeling tool is based on generalized adaptive immune response to antigens and can thus be leveraged to guide vaccine dosing schedules during future outbreaks.

Leveraging the scientific findings to develop therapeutic strategies for dormant breast cancer cells.

Breast cancer (BC) metastasis can occur decades before clinical diagnosis. During this time, the cancer cells (BCCs) can remain dormant for decades. This type of dormancy also occurs during remission where the dormant BCCs adapt cycling quiescence within the tissue microenvironment. BC shows preference for the bone marrow (BM), resulting in poor prognosis. The BM provides a challenge due to the complex niche between the peripheral interface and endosteum. The process of dormancy begins upon entry into the marrow with the changes facilitated through crosstalk between the cancer cells and tissue niche. More importantly, dormancy can occur at any time during the disease process, including the time during treatment. This perspective discusses the challenges posed by the marrow microenvironment to develop treatment. The article discusses the complex mechanisms at each compartment within the marrow niche and the added negative issue of toxicity to the endogenous stem cells.

Genomic landscape of lymphatic malformations: a case series and response to the PI3Kα inhibitor alpelisib in an N-of-1 clinical trial.

Background: Lymphatic malformations (LMs) often pose treatment challenges due to a large size or a critical location that could lead to disfigurement, and there are no standardized treatment approaches for either refractory or unresectable cases. Methods: We examined the genomic landscape of a patient cohort of LMs (n = 30 cases) that underwent comprehensive genomic profiling using a large-panel next-generation sequencing assay. Immunohistochemical analyses were completed in parallel. Results: These LMs had low mutational burden with hotspot PIK3CA mutations (n = 20) and NRAS (n = 5) mutations being most frequent, and mutually exclusive. All LM cases with Kaposi sarcoma-like (kaposiform) histology had NRAS mutations. One index patient presented with subacute abdominal pain and was diagnosed with a large retroperitoneal LM harboring a somatic PIK3CA gain-of-function mutation (H1047R). The patient achieved a rapid and durable radiologic complete response, as defined in RECIST1.1, to the PI3Kα inhibitor alpelisib within the context of a personalized N-of-1 clinical trial (NCT03941782). In translational correlative studies, canonical PI3Kα pathway activation was confirmed by immunohistochemistry and human LM-derived lymphatic endothelial cells carrying an allele with an activating mutation at the same locus were sensitive to alpelisib treatment in vitro, which was demonstrated by a concentration-dependent drop in measurable impedance, an assessment of cell status. Conclusions: Our findings establish that LM patients with conventional or kaposiform histology have distinct, yet targetable, driver mutations. Funding: R.P. and W.A. are supported by awards from the Levy-Longenbaugh Fund. S.G. is supported by awards from the Hugs for Brady Foundation. This work has been funded in part by the NCI Cancer Center Support Grants (CCSG; P30) to the University of Arizona Cancer Center (CA023074), the University of New Mexico Comprehensive Cancer Center (CA118100), and the Rutgers Cancer Institute of New Jersey (CA072720). B.K.M. was supported by National Science Foundation via Graduate Research Fellowship DGE-1143953. Clinical trial number: NCT03941782.

Translational Modeling Identifies Synergy between Nanoparticle-Delivered miRNA-22 and Standard-of-Care Drugs in Triple-Negative Breast Cancer.

PURPOSE: Downregulation of miRNA-22 in triple-negative breast cancer (TNBC) is associated with upregulation of eukaryotic elongation 2 factor kinase (eEF2K) protein, which regulates tumor growth, chemoresistance, and tumor immunosurveillance. Moreover, exogenous administration of miRNA-22, loaded in nanoparticles to prevent degradation and improve tumor delivery (termed miRNA-22 nanotherapy), to suppress eEF2K production has shown potential as an investigational therapeutic agent in vivo. METHODS: To evaluate the translational potential of miRNA-22 nanotherapy, we developed a multiscale mechanistic model, calibrated to published in vivo data and extrapolated to the human scale, to describe and quantify the pharmacokinetics and pharmacodynamics of miRNA-22 in virtual patient populations. RESULTS: Our analysis revealed the dose-response relationship, suggested optimal treatment frequency for miRNA-22 nanotherapy, and highlighted key determinants of therapy response, from which combination with immune checkpoint inhibitors was identified as a candidate strategy for improving treatment outcomes. More importantly, drug synergy was identified between miRNA-22 and standard-of-care drugs against TNBC, providing a basis for rational therapeutic combinations for improved response CONCLUSIONS: The present study highlights the translational potential of miRNA-22 nanotherapy for TNBC in combination with standard-of-care drugs.

Mathematical modeling of cancer immunotherapy for personalized clinical translation.

Encouraging advances are being made in cancer immunotherapy modeling, especially in the key areas of developing personalized treatment strategies based on individual patient parameters, predicting treatment outcomes and optimizing immunotherapy synergy when used in combination with other treatment approaches. Here we present a focused review of the most recent mathematical modeling work on cancer immunotherapy with a focus on clinical translatability. It can be seen that this field is transitioning from pure basic science to applications that can make impactful differences in patients' lives. We discuss how researchers are integrating experimental and clinical data to fully inform models so that they can be applied for clinical predictions, and present the challenges that remain to be overcome if widespread clinical adaptation is to be realized. Lastly, we discuss the most promising future applications and areas that are expected to be the focus of extensive upcoming modeling studies.

Early prediction of clinical response to checkpoint inhibitor therapy in human solid tumors through mathematical modeling.

Background: Checkpoint inhibitor therapy of cancer has led to markedly improved survival of a subset of patients in multiple solid malignant tumor types, yet the factors driving these clinical responses or lack thereof are not known. We have developed a mechanistic mathematical model for better understanding these factors and their relations in order to predict treatment outcome and optimize personal treatment strategies. Methods: Here, we present a translational mathematical model dependent on three key parameters for describing efficacy of checkpoint inhibitors in human cancer: tumor growth rate (α), tumor-immune infiltration (Λ), and immunotherapy-mediated amplification of anti-tumor response (µ). The model was calibrated by fitting it to a compiled clinical tumor response dataset (n = 189 patients) obtained from published anti-PD-1 and anti-PD-L1 clinical trials, and then validated on an additional validation cohort (n = 64 patients) obtained from our in-house clinical trials. Results: The derived parameters Λ and µ were both significantly different between responding versus nonresponding patients. Of note, our model appropriately classified response in 81.4% of patients by using only tumor volume measurements and within 2 months of treatment initiation in a retrospective analysis. The model reliably predicted clinical response to the PD-1/PD-L1 class of checkpoint inhibitors across multiple solid malignant tumor types. Comparison of model parameters to immunohistochemical measurement of PD-L1 and CD8+ T cells confirmed robust relationships between model parameters and their underlying biology. Conclusions: These results have demonstrated reliable methods to inform model parameters directly from biopsy samples, which are conveniently obtainable as early as the start of treatment. Together, these suggest that the model parameters may serve as early and robust biomarkers of the efficacy of checkpoint inhibitor therapy on an individualized per-patient basis. Funding: We gratefully acknowledge support from the Andrew Sabin Family Fellowship, Center for Radiation Oncology Research, Sheikh Ahmed Center for Pancreatic Cancer Research, GE Healthcare, Philips Healthcare, and institutional funds from the University of Texas M.D. Anderson Cancer Center. We have also received Cancer Center Support Grants from the National Cancer Institute (P30CA016672 to the University of Texas M.D. Anderson Cancer Center and P30CA072720 the Rutgers Cancer Institute of New Jersey). This research has also been supported in part by grants from the National Science Foundation Grant DMS-1930583 (ZW, VC), the National Institutes of Health (NIH) 1R01CA253865 (ZW, VC), 1U01CA196403 (ZW, VC), 1U01CA213759 (ZW, VC), 1R01CA226537 (ZW, RP, WA, VC), 1R01CA222007 (ZW, VC), U54CA210181 (ZW, VC), and the University of Texas System STARS Award (VC). BC acknowledges support through the SER Cymru II Programme, funded by the European Commission through the Horizon 2020 Marie Sklodowska-Curie Actions (MSCA) COFUND scheme and the Welsh European Funding Office (WEFO) under the European Regional Development Fund (ERDF). EK has also received support from the Project Purple, NIH (U54CA210181, U01CA200468, and U01CA196403), and the Pancreatic Cancer Action Network (16-65-SING). MF was supported through NIH/NCI center grant U54CA210181, R01CA222959, DoD Breast Cancer Research Breakthrough Level IV Award W81XWH-17-1-0389, and the Ernest Cockrell Jr. Presidential Distinguished Chair at Houston Methodist Research Institute. RP and WA received serial research awards from AngelWorks, the Gillson-Longenbaugh Foundation, and the Marcus Foundation. This work was also supported in part by grants from the National Cancer Institute to SHC (R01CA109322, R01CA127483, R01CA208703, and U54CA210181 CITO pilot grant) and to PYP (R01CA140243, R01CA188610, and U54CA210181 CITO pilot grant). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Repurposing Ferumoxytol as a Breast Cancer-Associated Macrophage Tracer with Five-Dimensional Quantitative [Fe]MRI of SPION Dynamics.

Tumor-associated macrophages (TAMs) in breast cancer regulate inflammation, immunosuppression, angiogenesis, and metastasis. However, TAM imaging remains a clinical challenge. Ferumoxytol has long been an FDA-approved superparamagnetic iron oxide nanoparticle (SPION) preparation used as an intravenous (IV) treatment for iron-deficiency anemia. Given its high transverse relaxivity, ferumoxytol produces a negative image contrast upon cellular uptake in T2-weighted magnetic resonance imaging (MRI) studies. Here we evaluated ferumoxytol as a contrast agent to image/quantify TAMs in an aggressive mouse model of breast cancer: We developed [Fe]MRI to measure the 5-dimensional function c(x,y,z,t), where c is the concentration of nanoparticle iron and {x,y,z,t} is the 4-dimensional set of tumor space-time coordinates. Ferumoxytol SPIONs are readily phagocytosed (~104/cell) by the F4/80+CD11b+ TAMs within breast tumors. Quantitative [Fe]MRIs served to determine both the spatial and the temporal distribution of the SPION iron, and hence to measure [Fe] = c(x,y,z,t), a surrogate for TAM density. In single-dose pharmacokinetic studies, after an IV dose of 5 mg/Kg iron, [Fe]MRI measurements showed that c(x,y,z,t) within breast tumors peaked around [Fe] = 70 µM at 42 h post-administration, and decayed below the [Fe]MRI detection limit (~2 µM) by day 7. There was no SPION uptake in control organs (muscle and adipose tissue). Optical microscopy of tissue sections confirmed that F4/80+CD11b+ TAMs infiltrated the tumors and accumulated SPION iron. Our methodology and findings have translational applications for breast cancer patients.

Design and proof of concept for targeted phage-based COVID-19 vaccination strategies with a streamlined cold-free supply chain.

Development of effective vaccines against coronavirus disease 2019 (COVID-19) is a global imperative. Rapid immunization of the entire human population against a widespread, continually evolving, and highly pathogenic virus is an unprecedented challenge, and different vaccine approaches are being pursued. Engineered filamentous bacteriophage (phage) particles have unique potential in vaccine development due to their inherent immunogenicity, genetic plasticity, stability, cost-effectiveness for large-scale production, and proven safety profile in humans. Herein we report the development and initial evaluation of two targeted phage-based vaccination approaches against SARS-CoV-2: dual ligand peptide-targeted phage and adeno-associated virus/phage (AAVP) particles. For peptide-targeted phage, we performed structure-guided antigen design to select six solvent-exposed epitopes of the SARS-CoV-2 spike (S) protein. One of these epitopes displayed on the major capsid protein pVIII of phage induced a specific and sustained humoral response when injected in mice. These phage were further engineered to simultaneously display the peptide CAKSMGDIVC on the minor capsid protein pIII to enable their transport from the lung epithelium into the systemic circulation. Aerosolization of these "dual-display" phage into the lungs of mice generated a systemic and specific antibody response. In the second approach, targeted AAVP particles were engineered to deliver the entire S protein gene under the control of a constitutive CMV promoter. This induced tissue-specific transgene expression, stimulating a systemic S protein-specific antibody response in mice. With these proof-of-concept preclinical experiments, we show that both targeted phage- and AAVP-based particles serve as robust yet versatile platforms that can promptly yield COVID-19 vaccine prototypes for translational development.

Fatty acid mobilization from adipose tissue is mediated by CD36 posttranslational modifications and intracellular trafficking.

The mechanism controlling long-chain fatty acid (LCFA) mobilization from adipose tissue is not well understood. Here, we investigated how the LCFA transporter CD36 regulates this process. By using tissue-specific KO mouse models, we showed that CD36 in adipocytes and endothelial cells mediated both LCFA deposition into and release from adipose tissue. We demonstrated the role of adipocytic and endothelial CD36 in promoting tumor growth and chemoresistance conferred by adipose tissue-derived LCFAs. We showed that dynamic cysteine S-acylation of CD36 in adipocytes, endothelial cells, and cancer cells mediated intercellular LCFA transport. We demonstrated that lipolysis induction in adipocytes triggered CD36 deacylation and deglycosylation, as well as its dissociation from interacting proteins, prohibitin-1 (PHB) and annexin 2 (ANX2). Our data indicate that lipolysis triggers caveolar endocytosis and translocation of CD36 from the cell membrane to lipid droplets. This study suggests a mechanism for both outside-in and inside-out cellular LCFA transport regulated by CD36 S-acylation and its interactions with PHB and ANX2.

Targeting a cell surface vitamin D receptor on tumor-associated macrophages in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive tumor with limited treatment options and poor prognosis. We applied the in vivo phage display technology to isolate peptides homing to the immunosuppressive cellular microenvironment of TNBC as a strategy for non-malignant target discovery. We identified a cyclic peptide (CSSTRESAC) that specifically binds to a vitamin D receptor, protein disulfide-isomerase A3 (PDIA3) expressed on the cell surface of tumor-associated macrophages (TAM), and targets breast cancer in syngeneic TNBC, non-TNBC xenograft, and transgenic mouse models. Systemic administration of CSSTRESAC to TNBC-bearing mice shifted the cytokine profile toward an antitumor immune response and delayed tumor growth. Moreover, CSSTRESAC enabled ligand-directed theranostic delivery to tumors and a mathematical model confirmed our experimental findings. Finally, in silico analysis showed PDIA3-expressing TAM in TNBC patients. This work uncovers a functional interplay between a cell surface vitamin D receptor in TAM and antitumor immune response that could be therapeutically exploited.

Targeted Phage Display-based Pulmonary Vaccination in Mice and Non-human Primates.

BACKGROUND: The extensive alveolar capillary network of the lungs is an attractive route for administration of several agents. One key functional attribute is the rapid onset of systemic action due to the absence of first-pass metabolism. METHODS: Here we applied a combinatorial approach for ligand-directed pulmonary delivery as a unique route for systemic targeting in vaccination. FINDINGS: We screened a phage display random peptide library in vivo to select, identify, and validate a ligand (CAKSMGDIVC) that specifically targets and is internalized through its receptor, α3ß1 integrin, on the surface of cells lining the lung airways and alveoli and mediates CAKSMGDIVC-displaying phage binding and systemic delivery without compromising lung homeostasis. As a proof-of-concept, we show that the pulmonary delivery of targeted CAKSMGDIVC-displaying phage particles in mice and non-human primates elicit a systemic and specific humoral response. CONCLUSIONS: This broad methodology blueprint represents a robust and versatile platform tool enabling new ligand-receptor discovery with many potential translational applications. FUNDING: Cancer Center Support Grants to the University of Texas M.D. Anderson Cancer Center (CA016672), University of New Mexico Comprehensive Cancer Center (CA118100), Rutgers Cancer Institute of New Jersey (CA072720), research awards from the Gillson Longenbaugh Foundation, and National Institutes of Health (NIH) grant no. 1R01CA226537.

Amphibian regeneration and mammalian cancer: Similarities and contrasts from an evolutionary biology perspective: Comparing the regenerative potential of mammalian embryos and urodeles to develop effective strategies against human cancer.

Here we review and discuss the link between regeneration capacity and tumor suppression comparing mammals (embryos versus adults) with highly regenerative vertebrates. Similar to mammal embryo morphogenesis, in amphibians (essentially newts and salamanders) the reparative process relies on a precise molecular and cellular machinery capable of sensing abnormal signals and actively reprograming or eliminating them. As the embryo's evil twin, tumor also retains common functional attributes. The immune system plays a pivotal role in maintaining a physiological balance to provide surveillance against tumor initiation or to support its initiation and progression. We speculate that susceptibility to cancer development in adult mammals may be determined by the loss of an advanced regenerative capability during evolution and believe that gaining mechanistic insights into how regenerative capacity linked to tumor suppression is postnatally lost in mammals might illuminate an as yet unrecognized route to cancer treatment.

Design and proof-of-concept for targeted phage-based COVID-19 vaccination strategies with a streamlined cold-free supply chain.

Development of effective vaccines against Coronavirus Disease 2019 (COVID-19) is a global imperative. Rapid immunization of the world human population against a widespread, continually evolving, and highly pathogenic virus is an unprecedented challenge, and many different vaccine approaches are being pursued to meet this task. Engineered filamentous bacteriophage (phage) have unique potential in vaccine development due to their inherent immunogenicity, genetic plasticity, stability, cost-effectiveness for large-scale production, and proven safety profile in humans. Herein we report the design, development, and initial evaluation of targeted phage-based vaccination approaches against Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) by using dual ligand peptide-targeted phage and adeno-associated virus/phage (AAVP) particles. Towards a unique phage- and AAVP-based dual-display candidate approach, we first performed structure-guided antigen design to select six solvent-exposed epitopes of the SARS-CoV-2 spike (S) protein for display on the recombinant major capsid coat protein pVIII. Targeted phage particles carrying one of these epitopes induced a strong and specific humoral response. In an initial experimental approach, when these targeted phage particles were further genetically engineered to simultaneously display a ligand peptide (CAKSMGDIVC) on the minor capsid protein pIII, which enables receptor-mediated transport of phage particles from the lung epithelium into the systemic circulation (termed "dual-display"), they enhanced a systemic and specific spike (S) protein-specific antibody response upon aerosolization into the lungs of mice. In a second line of investigation, we engineered targeted AAVP particles to deliver the entire S protein gene under the control of a constitutive cytomegalovirus (CMV) promoter, which induced tissue-specific transgene expression stimulating a systemic S protein-specific antibody response. As proof-of-concept preclinical experiments, we show that targeted phage- and AAVP-based particles serve as robust yet versatile enabling platforms for ligand-directed immunization and promptly yield COVID-19 vaccine prototypes for further translational development. SIGNIFICANCE: The ongoing COVID-19 global pandemic has accounted for over 2.5 million deaths and an unprecedented impact on the health of mankind worldwide. Over the past several months, while a few COVID-19 vaccines have received Emergency Use Authorization and are currently being administered to the entire human population, the demand for prompt global immunization has created enormous logistical challenges--including but not limited to supply, access, and distribution--that justify and reinforce the research for additional strategic alternatives. Phage are viruses that only infect bacteria and have been safely administered to humans as antibiotics for decades. As experimental proof-of-concept, we demonstrated that aerosol pulmonary vaccination with lung-targeted phage particles that display short epitopes of the S protein on the capsid as well as preclinical vaccination with targeted AAVP particles carrying the S protein gene elicit a systemic and specific immune response against SARS-CoV-2 in immunocompetent mice. Given that targeted phage- and AAVP-based viral particles are sturdy yet simple to genetically engineer, cost-effective for rapid large-scale production in clinical grade, and relatively stable at room temperature, such unique attributes might perhaps become additional tools towards COVID-19 vaccine design and development for immediate and future unmet needs.

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.

The loss-of-function PCSK9Q152H variant increases ER chaperones GRP78 and GRP94 and protects against liver injury.

Individuals harboring the loss-of-function (LOF) proprotein convertase subtilisin/kexin type 9 Gln152His variation (PCSK9Q152H) have low circulating low-density lipoprotein cholesterol levels and are therefore protected against cardiovascular disease (CVD). This uncleavable form of proPCSK9, however, is retained in the endoplasmic reticulum (ER) of liver hepatocytes, where it would be expected to contribute to ER storage disease (ERSD), a heritable condition known to cause systemic ER stress and liver injury. Here, we examined liver function in members of several French-Canadian families known to carry the PCSK9Q152H variation. We report that PCSK9Q152H carriers exhibited marked hypocholesterolemia and normal liver function despite their lifelong state of ER PCSK9 retention. Mechanistically, hepatic overexpression of PCSK9Q152H using adeno-associated viruses in male mice greatly increased the stability of key ER stress-response chaperones in liver hepatocytes and unexpectedly protected against ER stress and liver injury rather than inducing them. Our findings show that ER retention of PCSK9 not only reduced CVD risk in patients but may also protect against ERSD and other ER stress-driven conditions of the liver. In summary, we have uncovered a cochaperone function for PCSK9Q152H that explains its hepatoprotective effects and generated a translational mouse model for further mechanistic insights into this clinically relevant LOF PCSK9 variant.