Targeting AKR1B10 by drug repurposing with epalrestat overcomes chemoresistance in non-small cell lung cancer patient-derived tumor organoids.

PURPOSE: Systemic treatments given to non-small cell lung cancer (NSCLC) patients are often ineffective due to drug resistance. In the present study, we investigated patient-derived tumor organoids (PDTOs) and matched tumor tissues from surgically treated NSCLC patients to identify drug repurposing targets to overcome resistance towards standard-of-care platinum-based doublet chemotherapy. EXPERIMENTAL DESIGN: PDTOs were established from ten prospectively enrolled non-metastatic NSCLC patients from resected tumors. PDTOs were compared with matched tumor tissues by histopathology/immunohistochemistry, whole exome and transcriptome sequencing. PDTO growths and drug responses were determined by measuring 3D tumoroid volumes, cell viability, and proliferation/apoptosis. Differential gene expression analysis identified drug-repurposing targets. Validations were performed with internal/external NSCLC patient data sets. NSCLC cell lines were used for aldo-keto reductase 1B10 (AKR1B10) knockdown studies and xenograft models to determine the intratumoral bioavailability of epalrestat. RESULTS: PDTOs retained histomorphology and pathological biomarker expression, mutational/transcriptomic signatures, and cellular heterogeneity of the matched tumor tissues. Five (50%) PDTOs were chemoresistant towards carboplatin/paclitaxel. Chemoresistant PDTOs and matched tumor tissues demonstrated overexpression of AKR1B10. Epalrestat, an orally available AKR1B10 inhibitor in clinical use for diabetic polyneuropathy, was repurposed to overcome chemoresistance of PDTOs. In vivo efficacy of epalrestat to overcome drug resistance corresponded to intratumoral epalrestat levels. CONCLUSIONS: PDTOs are efficient preclinical models recapitulating the tumor characteristics and are suitable for drug testing. AKR1B10 can be targeted by repurposing epalrestat to overcome chemoresistance in NSCLC. Epalrestat has the potential to advance to clinical trials in drug-resistant NSCLC patients due to favorable toxicity, pharmacological profile, and bioavailability.

PathFinder: a novel graph transformer model to infer multi-cell intra- and inter-cellular signaling pathways and communications.

Recently, large-scale scRNA-seq datasets have been generated to understand the complex signaling mechanisms within the microenvironment of Alzheimer's Disease (AD), which are critical for identifying novel therapeutic targets and precision medicine. However, the background signaling networks are highly complex and interactive. It remains challenging to infer the core intra- and inter-multi-cell signaling communication networks using scRNA-seq data. In this study, we introduced a novel graph transformer model, PathFinder, to infer multi-cell intra- and inter-cellular signaling pathways and communications among multi-cell types. Compared with existing models, the novel and unique design of PathFinder is based on the divide-and-conquer strategy. This model divides complex signaling networks into signaling paths, which are then scored and ranked using a novel graph transformer architecture to infer intra- and inter-cell signaling communications. We evaluated the performance of PathFinder using two scRNA-seq data cohorts. The first cohort is an APOE4 genotype-specific AD, and the second is a human cirrhosis cohort. The evaluation confirms the promising potential of using PathFinder as a general signaling network inference model.

Numerical modeling of ultrasound-triggered microneedle-mediated delivery of drug particles into bacterial biofilms.

Ultrasonic microneedle patches, a class of ultrasound-driven transdermal drug delivery systems, are promising in addressing bacterial biofilms. This device has been proven to be more effective in treating Staphylococcus aureus biofilms than drug in free solution. However, there exists a notable gap in understanding how various excitation conditions and material parameters affect drug delivery efficiency. This study aims to fill this void by conducting an comprehensive multi-physics numerical analysis of ultrasonic microneedle patches, with the ultimate goal of enhancing drug delivery. First, we investigate the impact of various ultrasound frequencies on drug penetration depths. The findings reveal that local resonance can accelerate drug release within a shorter time window (first 1.5 h), whereas non-resonant frequencies enable more profound and prolonged diffusion. This information is crucial for medical professionals in selecting the most effective frequency for optimal drug administration. Furthermore, our investigation extends to the effects of applied voltage on temperature distribution, a critical aspect for ensuring medical safety during the application of these patches. Additionally, we examine how particles of different sizes respond to acoustic pressure and streaming fields, providing valuable insights for tailoring drug delivery strategies to specific therapeutic needs. Overall, our findings offer comprehensive guidelines for the effective use of ultrasonic microneedle patches, potentially shifting the paradigm in patient care and enhancing the overall quality of life.

mosGraphGen: a novel tool to generate multi-omic signaling graphs to facilitate integrative and interpretable graph AI model development.

Multi-omic data, i.e., genomics, epigenomics, transcriptomics, proteomics, characterize cellular complex signaling systems from multi-level and multi-view and provide a holistic view of complex cellular signaling pathways. However, it remains challenging to integrate and interpret multi-omics data. Graph neural network (GNN) AI models have been widely used to analyze graph-structure datasets and are ideal for integrative multi-omics data analysis because they can naturally integrate and represent multi-omics data as a biologically meaningful multi-level signaling graph and interpret multi-omics data by node and edge ranking analysis for signaling flow/cascade inference. However, it is non-trivial for graph-AI model developers to pre-analyze multi-omics data and convert them into graph-structure data for individual samples, which can be directly fed into graph-AI models. To resolve this challenge, we developed mosGraphGen (multi-omics signaling graph generator), a novel computational tool that generates multi-omics signaling graphs of individual samples by mapping the multi-omics data onto a biologically meaningful multi-level background signaling network. With mosGraphGen, AI model developers can directly apply and evaluate their models using these mos-graphs. We evaluated the mosGraphGen using both multi-omics datasets of cancer and Alzheimer's disease (AD) samples. The code of mosGraphGen is open-source and publicly available via GitHub: https://github.com/Multi-OmicGraphBuilder/mosGraphGen.

Driver Mutations in Pancreatic Cancer and Opportunities for Targeted Therapy.

Pancreatic cancer is the sixth leading cause of cancer-related mortality globally. As the most common form of pancreatic cancer, pancreatic ductal adenocarcinoma (PDAC) represents up to 95% of all pancreatic cancer cases, accounting for more than 300,000 deaths annually. Due to the lack of early diagnoses and the high refractory response to the currently available treatments, PDAC has a very poor prognosis, with a 5-year overall survival rate of less than 10%. Targeted therapy and immunotherapy are highly effective and have been used for the treatment of many types of cancer; however, they offer limited benefits in pancreatic cancer patients due to tumor-intrinsic and extrinsic factors that culminate in drug resistance. The identification of key factors responsible for PDAC growth and resistance to different treatments is highly valuable in developing new effective therapeutic strategies. In this review, we discuss some molecules which promote PDAC initiation and progression, and their potential as targets for PDAC treatment. We also evaluate the challenges associated with patient outcomes in clinical trials and implications for future research.

Targeted Therapy for Highly Desmoplastic and Immunosuppressive Tumor Microenvironment of Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with a very poor prognosis. Despite advancements in treatment strategies, PDAC remains recalcitrant to therapies because patients are often diagnosed at an advanced stage. The advanced stage of PDAC is characterized by metastasis, which typically renders it unresectable by surgery or untreatable by chemotherapy. The tumor microenvironment (TME) of PDAC comprises highly proliferative myofibroblast-like cells and hosts the intense deposition of a extracellular matrix component that forms dense fibrous connective tissue, a process called the desmoplastic reaction. In desmoplastic TMEs, the incessant aberration of signaling pathways contributes to immunosuppression by suppressing antitumor immunity. This feature offers a protective barrier that impedes the targeted delivery of drugs. In addition, the efficacy of immunotherapy is compromised because of the immune cold TME of PDAC. Targeted therapy approaches towards stromal and immunosuppressive TMEs are challenging. In this review, we discuss cellular and non-cellular TME components that contain actionable targets for drug development. We also highlight findings from preclinical studies and provide updates about the efficacies of new investigational drugs in clinical trials.

Simultaneously improving the pore structure and electron conductive network of the anode catalyst layer via SnO2 doping for proton exchange membrane water electrolysis.

Proton exchange membrane water electrolysis (PEMWE) is a promising technology for green hydrogen production. However, its large-scale commercial application is limited by its high precious metal loading, because low catalyst loading leads to reduced electron transport channels and decreased water transportation, etc. Herein, we study the electrode level strategy for reducing Ir loading by the optimization of the micro-structure of the anode catalyst layer via SnO2 doping. The pore structure and electron conductive network of the anode catalyst layer can be simultaneously improved by SnO2 doping, under appropriate conditions. Therefore, mass transfer polarization and ohmic polarization of the single cell are reduced. Moreover, the enhanced pore structure and improved electron conduction network collectively contribute to a decreased occurrence of charge transfer polarization. By this strategy, the performance of the single cell with the Ir loading of 1.5 mg cm-2 approaches the single cell with the higher Ir loading of 2.0 mg cm-2, which means that SnO2 doping saves about 25% loading of Ir. This paper provides a perspective at the electrode level to reduce the precious metal loading of the anode in PEMWE.

A randomized, blind, parallel controlled phase I clinical trial to evaluate the safety and preliminary immunogenicity of 23-valent pneumococcal polysaccharide vaccine in healthy people aged 2 years and older.

BACKGROUND: Despite some progress in pneumococcal immunization, the global burden of pneumococcal infection remains high, and pneumococcal disease remains a public health concern. Studies in China and abroad have found that 23-valent pneumococcal polysaccharide vaccine (PPV23) vaccination can effectively prevent invasive pneumococcal disease. This phase Ⅰ clinical study assessed the safety and immunogenicity of a PPV23 vaccine candidate. METHODS: All subjects were randomly assigned to receive one dose intramuscular injection of experimental vaccine or control vaccine at a ratio of 1:1. The incidence of any adverse events was observed within 30 min, 0-7 days and 8-28 days post vaccination and the incidence of abnormal blood biochemical and blood routine indicators were tested on the 4th day post vaccination, the incidence of serious adverse events (SAEs) at 6 months post vaccination was recorded. Blood samples were collected prior to vaccination and on the 28th day post vaccination, and serum antibodies were detected by enzyme linked immunosorbent assay (ELISA). RESULTS: The most common adverse reaction was pain at the injection site, followed by erythema. There was no significant difference of the incidence of systemic adverse reactions between the two vaccine groups. The adverse reactions observed in the trial were all common vaccination-related reactions, and no serious adverse reactions were observed. Compared to pre-vaccination, the (geometric mean concentrations) GMCs of IgG (immunoglobulin G) specific antibody against each serotype were all increased in the experimental group and the control group, there were statistical differences in seroconversion rates of serotypes 4 and 20 between the two vaccine groups. CONCLUSION: This clinical study showed good safety of the PPV23 vaccine candidate produced by Ab&b Biotechnology Co., Ltd.JS had good safety after vaccination in people aged 2 years and older. At the same time, good immunogenicity was also demonstrated.

PathFinder: a novel graph transformer model to infer multi-cell intra- and inter-cellular signaling pathways and communications.

Recently, large-scale scRNA-seq datasets have been generated to understand the complex and poorly understood signaling mechanisms within microenvironment of Alzheimer's Disease (AD), which are critical for identifying novel therapeutic targets and precision medicine. Though a set of targets have been identified, however, it remains a challenging to infer the core intra- and inter-multi-cell signaling communication networks using the scRNA-seq data, considering the complex and highly interactive background signaling network. Herein, we introduced a novel graph transformer model, PathFinder, to infer multi-cell intra- and inter-cellular signaling pathways and signaling communications among multi-cell types. Compared with existing models, the novel and unique design of PathFinder is based on the divide-and-conquer strategy, which divides the complex signaling networks into signaling paths, and then score and rank them using a novel graph transformer architecture to infer the intra- and inter-cell signaling communications. We evaluated PathFinder using scRNA-seq data of APOE4-genotype specific AD mice models and identified novel APOE4 altered intra- and inter-cell interaction networks among neurons, astrocytes, and microglia. PathFinder is a general signaling network inference model and can be applied to other omics data-driven signaling network inference.

Gut microbiota and metabolite interface-mediated hepatic inflammation.

Immunologic and metabolic signals regulated by gut microbiota and relevant metabolites mediate bidirectional interaction between the gut and liver. Gut microbiota dysbiosis, due to diet, lifestyle, bile acids, and genetic and environmental factors, can advance the progression of chronic liver disease. Commensal gut bacteria have both pro- and anti-inflammatory effects depending on their species and relative abundance in the intestine. Components and metabolites derived from gut microbiota-diet interaction can regulate hepatic innate and adaptive immune cells, as well as liver parenchymal cells, significantly impacting liver inflammation. In this mini review, recent findings of specific bacterial species and metabolites with functions in regulating liver inflammation are first reviewed. In addition, socioeconomic and environmental factors, hormones, and genetics that shape the profile of gut microbiota and microbial metabolites and components with the function of priming or dampening liver inflammation are discussed. Finally, current clinical trials evaluating the factors that manipulate gut microbiota to treat liver inflammation and chronic liver disease are reviewed. Overall, the discussion of microbial and metabolic mediators contributing to liver inflammation will help direct our future studies on liver disease.

Indispensable Nafion Ionomer for High-Efficiency and Stable Oxygen Evolution Reaction in Alkaline Media.

Addressing the challenge of sluggish kinetics and limited stability in alkaline oxygen evolution reactions, recent exploration of novel electrochemical catalysts offers improved prospects. To expedite the assessment of these catalysts, a half-cell rotating disk electrode is often favored for its simplicity. However, the actual catalyst performance strongly depends on the fabricated catalyst layers, which encounter mass transport overpotentials. We systematically investigate the role and sequence of electrode drop-casting methods onto a glassy carbon electrode regarding the efficiency of the oxygen evolution reaction. The catalyst layer without Nafion experiences nearly 50% activity loss post stability test, while those with Nafion exhibit less than 5% activity loss. Additionally, the sequence of application of the catalyst and Nafion also shows a significant effect on catalyst stability. The catalyst activity increases by roughly 20% after the stability test when the catalyst layer is coated first with an ionomer layer, followed by drop-casting the catalysts. Based on the half-cell results, the Nafion ionomer not only acts as a binder in the catalyst layer but also enhances the interfacial interaction between the catalyst and electrolyte, promoting performance and stability. This study provides new insights into the efficient and accurate evaluation of electrocatalyst performance and stability as well as the role of Nafion ionomer in the catalyst layer.

A novel role of TGFBI in macrophage polarization and macrophage-induced pancreatic cancer growth and therapeutic resistance.

Tumor-associated macrophages (TAMs), as a major and essential component of tumor microenvironment (TME), play a critical role in orchestrating pancreatic cancer (PaC) tumorigenesis from initiation to angiogenesis, growth, and systemic dissemination, as well as immunosuppression and resistance to chemotherapy and immunotherapy; however, the critical intrinsic factors responsible for TAMs reprograming and function remain to be identified. By performing single-cell RNA sequencing, transforming growth factor-beta-induced protein (TGFBI) was identified as TAM-producing factor in murine PaC tumors. TAMs express TGFBI in human PaC and TGFBI expression is positively related with human PaC growth. By inducing TGFBI loss-of-function in macrophage (MΦs) in vitro with siRNA and in vivo with Cre-Lox strategy in our developed TGFBI-floxed mice, we demonstrated disruption of TGFBI not only inhibited MΦ polarization to M2 phenotype and MΦ-mediated stimulation on PaC growth, but also significantly improved anti-tumor immunity, sensitizing PaC to chemotherapy in association with regulation of fibronectin 1, Cxcl10, and Ccl5. Our studies suggest that targeting TGFBI in MΦ can develop an effective therapeutic intervention for highly lethal PaC.

The Important Roles of Natural Killer Cells in Liver Fibrosis.

Liver fibrosis accompanies the development of various chronic liver diseases and promotes their progression. It is characterized by the abnormal accumulation of extracellular matrix proteins (ECM) and impaired ECM degradation. Activated hepatic stellate cells (HSCs) are the major cellular source of ECM-producing myofibroblasts. If liver fibrosis is uncontrolled, it may lead to cirrhosis and even liver cancer, primarily hepatocellular carcinoma (HCC). Natural killer (NK) cells are a key component of innate immunity and have miscellaneous roles in liver health and disease. Accumulating evidence shows that NK cells play dual roles in the development and progression of liver fibrosis, including profibrotic and anti-fibrotic functions. Regulating NK cells can suppress the activation of HSCs and improve their cytotoxicity against activated HSCs or myofibroblasts to reverse liver fibrosis. Cells such as regulatory T cells (Tregs) and molecules such as prostaglandin E receptor 3 (EP3) can regulate the cytotoxic function of NK cells. In addition, treatments such as alcohol dehydrogenase 3 (ADH3) inhibitors, microRNAs, natural killer group 2, member D (NKG2D) activators, and natural products can enhance NK cell function to inhibit liver fibrosis. In this review, we summarized the cellular and molecular factors that affect the interaction of NK cells with HSCs, as well as the treatments that regulate NK cell function against liver fibrosis. Despite a lot of information about NK cells and their interaction with HSCs, our current knowledge is still insufficient to explain the complex crosstalk between these cells and hepatocytes, liver sinusoidal endothelial cells, Kupffer cells, B cells, and T cells, as well as thrombocytes, regarding the development and progression of liver fibrosis.

Western diet contributes to the pathogenesis of non-alcoholic steatohepatitis in male mice via remodeling gut microbiota and increasing production of 2-oleoylglycerol.

The interplay between western diet and gut microbiota drives the development of non-alcoholic fatty liver disease and its progression to non-alcoholic steatohepatitis. However, the specific microbial and metabolic mediators contributing to non-alcoholic steatohepatitis remain to be identified. Here, a choline-low high-fat and high-sugar diet, representing a typical western diet, named CL-HFS, successfully induces male mouse non-alcoholic steatohepatitis with some features of the human disease, such as hepatic inflammation, steatosis, and fibrosis. Metataxonomic and metabolomic studies identify Blautia producta and 2-oleoylglycerol as clinically relevant bacterial and metabolic mediators contributing to CL-HFS-induced non-alcoholic steatohepatitis. In vivo studies validate that both Blautia producta and 2-oleoylglycerol promote liver inflammation and hepatic fibrosis in normal diet- or CL-HFS-fed mice. Cellular and molecular studies reveal that the GPR119/TAK1/NF-κB/TGF-ß1 signaling pathway mediates 2-oleoylglycerol-induced macrophage priming and subsequent hepatic stellate cell activation. These findings advance our understanding of non-alcoholic steatohepatitis pathogenesis and provide targets for developing microbiome/metabolite-based therapeutic strategies against non-alcoholic steatohepatitis.

AIE-active Ir(III) complexes as type-I dominant photosensitizers for efficient photodynamic therapy.

The ability of a photosensitizer (PS) to generate reactive oxygen species (ROS) including type I oxygen free radicals and type II 1O2 is pivotal for photodynamic therapy. Luminescent Ir(III) complexes are effective PSs with high 1O2 generation ability owing to their high intersystem crossing ability and effective energy transfer to 3O2. However, so far, reports on type I ROS based on ˙OH generation induced by Ir(III) PS are still rare. In this work, four novel aggregation-induced emission (AIE)-active Ir(III) PSs, namely MFIriqa, MFIrqa, SFIriqa, and SFIrqa have been designed and synthesized, which show highly efficient emission in the aggregated state. Cell imaging experiment results indicate that all four Ir(III) PSs can effectively improve the signal-to-noise ratio of imaging by reducing the interference from the background due to their fascinating AIE properties. Importantly, in vitro, Ir(III) PSs MFIrqa, SFIriqa, and SFIrqa nanoparticles show obvious photodynamic activity toward cancer cells upon irradiation accompanied by type I ˙OH generation, which may be attributed to the unique excited-state characteristics of Ir(III) complexes. This work will provide guidance for the construction of a type I photosensitizer based on the AIE-active Ir(III) complex, which offers great advantages for potential clinical applications under hypoxic conditions.

Bayesian Method for Water Quality Emergency Monitoring in Environmental Pollution Accident Disposal.

Along with the country's comprehensive strength, the people's wealth is also more and more substantial, in every aspect of life has been significantly improved, people also pay more attention to environmental protection. The harm of environmental pollution should not be underestimated. Once the environmental pollution accident occurs, it must be handled promptly, or a series of consequences are very serious. Therefore, it is necessary to study the Bayesian method of water quality emergency monitoring in the disposal of environmental pollution accidents. The purpose of this article was to solve the slow progress of water quality monitoring in the disposal of environmental pollution accidents. Through the Bayesian method of environmental pollution accident disposal in water quality emergency monitoring, the target node variables, intermediate node variables, and evidence node variables are used for analysis. Construct a Bayesian network topology. This article uses the fuzzy Bayesian network risk assessment model to provide a reference for the emergency monitoring of water quality disposal in regional environmental pollution accidents and conduct risk assessment to facilitate the next work arrangement. The results show that the Bayesian method of water quality emergency monitoring in environmental pollution accident disposal can provide effective feedback. Compared with traditional methods, the risk assessment of water quality monitoring for environmental pollution accidents is 40% faster and 10% more accurate in calculating the probability of accidents caused by basic factors. The application of the Bayesian water quality emergency monitoring method in environmental pollution accident disposal is conducive to improving the efficiency of environmental pollution disposal, in-depth analysis of the existing problems in the current environmental emergency management work, and suggestions for improving the emergency mechanism of sudden environmental pollution accident. The purpose was to provide reference for the government to properly handle sudden environmental pollution accidents.

Neuroprotective effect of Ziziphi Spinosae Semen on rats with p-chlorophenylalanine-induced insomnia via activation of GABAA receptor.

Ziziphus jujuba var. spinosa (Bunge) Hu ex H.F.Chow [Rhamnaceae; Ziziphi Spinosae Semen (ZSS)] has attracted extensive attention as the first choice of traditional Chinese medicine in the treatment of insomnia. However, recent studies on the sleep-improving mechanism of ZSS have mainly focused on the role of single components. Thus, to further reveal the potential mechanism of ZSS, an assessment of its multiple constituents is necessary. In this study, ZSS extract (ZSSE) was obtained from ZSS via detailed modern extraction, separation, and purification technologies. The chemical constituents of ZSSE were analyzed by high-performance liquid chromatography-mass spectrometry (HPLC-MS). For in vivo experiments, a rat model of insomnia induced by p-chlorophenylalanine (PCPA) was established to investigate the potential effect and corresponding mechanism of ZSSE on improving sleep. Hematoxylin-eosin staining (HE) results revealed that the drug group showed prominent advantages over the model group in improving sleep. Moreover, the brain levels of γ-aminobutyric acid (GABA), glutamic acid (Glu), 5-hydroxytryptamine (5-HT), and dopamine (DA) were monitored via enzyme-linked immunosorbent assay (ELISA) to further study the sleep-improving mechanism of ZSSE. We found that sleep was effectively improved via upregulation of GABA and 5-HT and downregulation of Glu and DA. In addition, molecular mechanisms of ZSSE in improving sleep were studied by immunohistochemical analysis. The results showed that sleep was improved by regulating the expression levels of GABA receptor subunit alpha-1 (GABAARα1) and GABA acid receptor subunit gamma-2 (GABAARγ2) receptors in the hypothalamus and hippocampus tissue sections. Therefore, this work not only identified the active ingredients of ZSSE but also revealed the potential pharmacological mechanism of ZSSE for improving sleep, which may greatly stimulate the prospective development and application of ZSSE.

The Species of Gut Bacteria Associated with Antitumor Immunity in Cancer Therapy.

Both preclinical and clinical studies have demonstrated that the modulation of gut microbiota could be a promising strategy for enhancing antitumor immune responses and reducing resistance to immunotherapy in cancer. Various mechanisms, including activation of pattern recognition receptors, gut commensals-produced metabolites and antigen mimicry, have been revealed. Different gut microbiota modulation strategies have been raised, such as fecal microbiota transplantation, probiotics, and dietary selection. However, the identification of gut bacteria species that are either favorable or unfavorable for cancer therapy remains a major challenge. Herein, we summarized the findings related to gut microbiota species observed in the modulation of antitumor immunity. We also discussed the different mechanisms underlying different gut bacteria's functions and the potential applications of these bacteria to cancer immunotherapy in the future.

Somatic mutation variant analysis in rural, resectable non-small cell lung carcinoma patients.

Rural non-small cell lung cancer (NSCLC) patients do worse, largely related to lack of access to care. In this study, the mutational characteristics and potential for targeted therapy in rural, resectable NSCLC patients using whole exome sequencing (WES) were analyzed. WES was performed on tumor-adjacent normal pairs from rural patients undergoing resection for NSCLC. Sequencing alignment, variant-calling, annotation, and tumor mutational burden (TMB) calculations were performed using standard methods. cBioportal and OncoKB were used for comparisons of mutational frequencies and actionable targets. Thirty-four NSCLC patients underwent WES after surgical resection. The gene most frequently containing somatic variants was TP53. The median number of somatic variants was 188 (Range 11-1056), and median TMB was 3.30 (0.33-18.56) nonsynonymous mutations per Mb. Tumor stage and survival were not associated with number of variants, TMB or TP53 mutational status. Significant concordance among the most common mutations when cross-referenced to cBioportal (R = 0.78, p < 0.0001) was observed. 24% of patients had variants in actionable genes based on OncoKB annotation. In summary, we demonstrate baseline mutational frequency and establish foundations for targeted adjuvant trials in rural NSCLC patients with specific differences. Future studies must ensure to include rural patients to improve NSCLC patient outcomes.

Discovery of Cyclic Peptide Inhibitors Targeting PD-L1 for Cancer Immunotherapy.

Blockade of the interaction between programmed cell death ligand-1 (PD-L1) and its receptor PD-1 has shown great success in cancer immunotherapy. Peptides possess unique characteristics that give them significant advantages as immune checkpoint inhibitors. However, unfavorable physicochemical properties and proteolytic stability profiles limit the translation of bioactive peptides as therapeutic agents. Studies have revealed that cyclization improves the biological activity and stability of linear peptides. In this study, we report the use of macrocyclization scanning for the discovery of cyclic anti-PD-L1 peptides with improved bioactivity. The cyclic peptides demonstrated up to a 34-fold improvement in the PD-1/PD-L1 blocking activity and significant in vivo anti-tumor activity. Our results demonstrate that macrocyclization scanning is an effective way to improve the serum stability and bioactivity of the anti-PD-L1 linear peptide. This strategy can be employed in the optimization of other bioactive peptides, particularly those for protein-protein interaction modulation.