Application of exosomes in tumor immunity: recent progresses.

Exosomes are small extracellular vesicles secreted by cells, ranging in size from 30 to 150 nm. They contain proteins, nucleic acids, lipids, and other bioactive molecules, which play a crucial role in intercellular communication and material transfer. In tumor immunity, exosomes present various functions while the following two are of great importance: regulating the immune response and serving as delivery carriers. This review starts with the introduction of the formation, compositions, functions, isolation, characterization, and applications of exosomes, and subsequently discusses the current status of exosomes in tumor immunotherapy, and the recent applications of exosome-based tumor immunity regulation and antitumor drug delivery. Finally, current challenge and future prospects are proposed and hope to demonstrate inspiration for targeted readers in the field.

High-Performance Hydrogel Sensors Enabled Multimodal and Accurate Human-Machine Interaction System for Active Rehabilitation.

Human-machine interaction (HMI) technology shows an important application prospect in rehabilitation medicine, but it is greatly limited by the unsatisfactory recognition accuracy and wearing comfort. Here, this work develops a fully flexible, conformable, and functionalized multimodal HMI interface consisting of hydrogel-based sensors and a self-designed flexible printed circuit board. Thanks to the component regulation and structural design of the hydrogel, both electromyogram (EMG) and forcemyography (FMG) signals can be collected accurately and stably, so that they are later decoded with the assistance of artificial intelligence (AI). Compared with traditional multichannel EMG signals, the multimodal human-machine interaction method based on the combination of EMG and FMG signals significantly improves the efficiency of human-machine interaction by increasing the information entropy of the interaction signals. The decoding accuracy of the interaction signals from only two channels for different gestures reaches 91.28%. The resulting AI-powered active rehabilitation system can control a pneumatic robotic glove to assist stroke patients in completing movements according to the recognized human motion intention. Moreover, this HMI interface is further generalized and applied to other remote sensing platforms, such as manipulators, intelligent cars, and drones, paving the way for the design of future intelligent robot systems.

PDATC-NCPMKL: Predicting drug's Anatomical Therapeutic Chemical (ATC) codes based on network consistency projection and multiple kernel learning.

The development and discovery of new drugs is time-consuming and needs lots of human and material resources. Therefore, discovery of novel effects of existing drugs is an important alternative way, which can accelerate the process of designing "new" drugs. The anatomical Therapeutic Chemical (ATC) classification system recommended by World Health Organization (WHO) is a basic research area in this regard. A novel ATC code of an existing drug suggests its novel effects. Some computational models have been proposed, which can predict the drug-ATC code associations. However, their performance is not very high. There still exist spaces for improvement. In this study, a new recommendation system (named PDATC-NCPMKL), which incorporated network consistency projection and multi-kernel learning, was designed to identify drug-ATC code associations. For drugs or ATC codes, several kernels were constructed, which were fused by a multiple kernel learning method and an additional kernel integration scheme. To enhance the performance, the drug-ATC code association adjacency matrix was reformulated by a variant of weighted K nearest known neighbors (WKNKN). The reformulated adjacency matrix, drug and ATC code kernels were fed into network consistency projection to generate the association score matrix. The proposed recommendation system was tested on the ATC codes at the second, third and fourth levels in drug ATC classification system using ten-fold cross-validation. The results indicated that all AUROC and AUPR values were close to or exceeded 0.96. Such performance was higher than some existing computational models. Some additional tests were conducted to prove the utility of adjacency matrix reformulation and to analyze the importance of drug and ATC code kernels.

Discriminative analysis of schizophrenia patients using an integrated model combining 3D CNN with 2D CNN: A multimodal MR image and connectomics analysis.

OBJECTIVE: Few studies have applied deep learning to the discriminative analysis of schizophrenia (SZ) patients using the fusional features of multimodal MRI data. Here, we proposed an integrated model combining a 3D convolutional neural network (CNN) with a 2D CNN to classify SZ patients. METHOD: Structural MRI (sMRI) and resting-state functional MRI (rs-fMRI) data were acquired for 140 SZ patients and 205 normal controls. We computed structural connectivity (SC) from the sMRI data as well as functional connectivity (FC), amplitude of low-frequency fluctuation (ALFF), and regional homogeneity (ReHo) from the rs-fMRI data. The 3D images of T1, ReHo, and ALFF were used as the inputs for the 3D CNN model, while the SC and FC matrices were used as the inputs for the 2D CNN model. Moreover, we added squeeze and excitation blocks (SE-blocks) to each layer of the integrated model and used a support vector machine (SVM) to replace the softmax classifier. RESULTS: The integrated model proposed in this study, using the fusional features of the T1 images, and the matrices of FC, showed the best performance. The use of the SE-blocks and SVM classifiers significantly improved the performance of the integrated model, in which the accuracy, sensitivity, specificity, area under the curve, and F1-score were 89.86%, 86.21%, 92.50%, 89.35%, and 87.72%, respectively. CONCLUSIONS: Our findings indicated that an integrated model combining 3D CNN with 2D CNN is a promising method to improve the classification performance of SZ patients and has potential for the clinical diagnosis of psychiatric diseases.

Nano-optogenetic CAR-T Cell Immunotherapy.

Chimeric antigen receptor (CAR)-T cell immunotherapy emerges as an effective cancer treatment. However, significant safety concerns remain, such as cytokine release syndrome (CRS) and "on-target, off-tumor" cytotoxicity, due to a lack of precise control over conventional CAR-T cell activity. To address this issue, a nano-optogenetic approach has been developed to enable spatiotemporal control of CAR-T cell activity. This system is comprised of synthetic light-sensitive CAR-T cells and upconversion nanoparticles acting as an in situ nanotransducer, allowing near-infrared light to wirelessly control CAR-T cell immunotherapy.

Dynamic monitoring of serum tumor markers as prognostic factors in patients with advanced non-small-cell lung cancer treated with first-line immunotherapy: a multicenter retrospective study.

Background: To date, no specific studies have reported the use of dynamic serum tumor markers (STMs) as prognostic factors in patients with advanced non-small-cell lung cancer (NSCLC) who receive first-line immunotherapy. Therefore, it is unclear whether STMs can be used as a prognostic factor for first-line immunotherapy in advanced NSCLC. Objectives: To elucidate the role of STMs in monitoring immunotherapy response in advanced NSCLC. Patients were treated with first-line programmed cell death-1/programmed cell death ligand-1 inhibitors at four Chinese centers. Design: This was a multicenter retrospective study. Methods: Blood samples were collected at baseline and after 6-8 weeks of treatment. Computed tomography scans were used to evaluate treatment efficacy according to Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. Post-treatment drops in STMs [Serum carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), cytokeratin fragment 19 (CYFRA21-1), carbohydrate antigen 19-9 (CA19-9), and carbohydrate antigen 125 (CA125)] were decreased ⩾20% (Group C) over baseline was used as cutoff level for defining a marker response. If STMs were increased by ⩾20% after treatment, the therapeutic effect was limited (Group A). Patients with STM changes between a 20% increase or decrease were enrolled in Group B. In univariate and multivariate stepwise Cox regression analyses, STMs and RECIST responses were analyzed for their impact on progression-free survival (PFS) and overall survival (OS). Results: The analysis included 716 patients. By multivariate analysis, CEA, NSE, CYFRA21-1, CA19-9, and CA125 (Group A versus Group B and Group A versus Group C) were associated with significant differences in PFS. Similar results were observed in the OS analysis. Similar results were observed in the adenocarcinoma subgroup analyses. In squamous cell carcinoma subgroup analyses, there was no statistical difference in PFS (p = 0.147) or OS (p = 0.068) between Group A and Group B for CA125. Conclusion: The increase and decrease in serum levels of STMs might be reliable prognostic factors for immunotherapy efficacy in NSCLC patients.

Expanding PROTACtable genome universe of E3 ligases.

Proteolysis-targeting chimera (PROTAC) and other targeted protein degradation (TPD) molecules that induce degradation by the ubiquitin-proteasome system (UPS) offer new opportunities to engage targets that remain challenging to be inhibited by conventional small molecules. One fundamental element in the degradation process is the E3 ligase. However, less than 2% amongst hundreds of E3 ligases in the human genome have been engaged in current studies in the TPD field, calling for the recruiting of additional ones to further enhance the therapeutic potential of TPD. To accelerate the development of PROTACs utilizing under-explored E3 ligases, we systematically characterize E3 ligases from seven different aspects, including chemical ligandability, expression patterns, protein-protein interactions (PPI), structure availability, functional essentiality, cellular location, and PPI interface by analyzing 30 large-scale data sets. Our analysis uncovers several E3 ligases as promising extant PROTACs. In total, combining confidence score, ligandability, expression pattern, and PPI, we identified 76 E3 ligases as PROTAC-interacting candidates. We develop a user-friendly and flexible web portal ( https://hanlaboratory.com/E3Atlas/ ) aimed at assisting researchers to rapidly identify E3 ligases with promising TPD activities against specifically desired targets, facilitating the development of these therapies in cancer and beyond.

TET2 modulates spatial relocalization of heterochromatin in aged hematopoietic stem and progenitor cells.

DNA methylation deregulation at partially methylated domains (PMDs) represents an epigenetic signature of aging and cancer, yet the underlying molecular basis and resulting biological consequences remain unresolved. We report herein a mechanistic link between disrupted DNA methylation at PMDs and the spatial relocalization of H3K9me3-marked heterochromatin in aged hematopoietic stem and progenitor cells (HSPCs) or those with impaired DNA methylation. We uncover that TET2 modulates the spatial redistribution of H3K9me3-marked heterochromatin to mediate the upregulation of endogenous retroviruses (ERVs) and interferon-stimulated genes (ISGs), hence contributing to functional decline of aged HSPCs. TET2-deficient HSPCs retain perinuclear distribution of heterochromatin and exhibit age-related clonal expansion. Reverse transcriptase inhibitors suppress ERVs and ISGs expression, thereby restoring age-related defects in aged HSPCs. Collectively, our findings deepen the understanding of the functional interplay between DNA methylation and histone modifications, which is vital for maintaining heterochromatin function and safeguarding genome stability in stem cells.

Collagen-EGCG Combination Synergistically Prevents UVB-Induced Skin Photoaging in Nude Mice.

Ultraviolet (UV) radiation is a major cause of skin photoaging through generating excessive oxidative stress and inflammation. One of the strategies is to use photo-chemoprotectors, such as natural products with antioxidant and anti-inflammatory properties, to protect the skin from photo damage. The present study investigates the photoprotective potentials of topical administration of unhydrolyzed collagen, epigallocatechin gallate (EGCG), and their combination against ultraviolet B (UVB)-induced photoaging in nude mice. It is found that both the solo and combined pretreatments could recover UVB-induced depletion of antioxidative enzymes, including superoxide dismutase and glutathione peroxidase (GSH-Px), as well as an increase of lipid peroxide malondialdehyde and inflammatory tumor necrosis factor-α. Meanwhile, the UVB-stimulated skin collagen degradation is attenuated significantly with drug treatments, which is evidenced by expression analysis of matrix metalloproteinase-1 and hydroxyproline. Additionally, the mouse skin histology shows that the drug-pretreated groups possess decreased epidermis thickness and normal collagen fiber structure of the dermis layer. These results demonstrate that both EGCG and collagen can protect the skin against UVB-induced skin photoaging. Synergistically, the combination of them shows the maximum prevention to skin damage, showing its potential in the application of anti-photoaging formulation products.

Comparison of first-line immunotherapy efficacy between advanced lung squamous cell carcinoma and pulmonary lymphoepithelioma-like carcinoma: A propensity score matching multicenter study.

Background: Compared with other lung squamous cell carcinomas (LUSC), pulmonary lymphoepithelioma-like carcinoma (pLELC) is closely associated with Epstein-Barr virus (EBV) infections with a unique molecular profile and immune microenvironment. This study was thus established to compare the treatment response and effectiveness of immunotherapy between pLELC and LUSC. Material and Methods: We enrolled 31 patients with pLELC and 116 with LUSC receiving first-line immunotherapy at three centers in China and compared the treatment response and effectiveness of immunotherapy. Propensity score matching (PSM) was used to balance the differences in baseline data between the two groups. Results: Before PSM, progression-free survival and overall survival were longer in the pLELC group than in the LUSC group (progression-free survival: hazard ratio (HR), 1.67, 95% CI: 1.05-2.63, P = 0.028; overall survival: HR, 1.90, 95% CI: 1.06-3.40, P = 0.028). This remained unchanged after PSM (progression-free survival: HR, 1.79, 95% CI: 1.02-3.15, P = 0.044; overall survival: HR, 2.20; 95% CI: 1.10-4.37, P = 0.022). Conclusion: pLELC showed a clinically meaningful survival benefit compared with traditional LUSC following immunotherapy. Subsequent studies should consider the role of the EBV in the tumor immune microenvironment of pLELC.

Optogenetic engineering of STING signaling allows remote immunomodulation to enhance cancer immunotherapy.

The cGAS-STING signaling pathway has emerged as a promising target for immunotherapy development. Here, we introduce a light-sensitive optogenetic device for control of the cGAS/STING signaling to conditionally modulate innate immunity, called 'light-inducible SMOC-like repeats' (LiSmore). We demonstrate that photo-activated LiSmore boosts dendritic cell (DC) maturation and antigen presentation with high spatiotemporal precision. This non-invasive approach photo-sensitizes cytotoxic T lymphocytes to engage tumor antigens, leading to a sustained antitumor immune response. When combined with an immune checkpoint blocker (ICB), LiSmore improves antitumor efficacy in an immunosuppressive lung cancer model that is otherwise unresponsive to conventional ICB treatment. Additionally, LiSmore exhibits an abscopal effect by effectively suppressing tumor growth in a distal site in a bilateral mouse model of melanoma. Collectively, our findings establish the potential of targeted optogenetic activation of the STING signaling pathway for remote immunomodulation in mice.

Baseline serum tumor markers predict the survival of patients with advanced non-small cell lung cancer receiving first-line immunotherapy: a multicenter retrospective study.

BACKGROUND: This study aimed to investigate the association between baseline serum tumor markers (STMs) (carcinoembryonic antigen [CEA], neuron-specific enolase [NSE], cytokeratin-19 fragment [CYFRA21-1], carbohydrate antigen 19-9 [CA19-9], and carbohydrate antigen 125 [CA125]) and the efficacy of first-line immunotherapy in patients with advanced non-small cell lung cancer. METHODS: This multicenter retrospective study evaluated patients who received first-line immunotherapy between July 2017 and July 2022. The endpoints were progression-free survival (PFS) and overall survival (OS), as defined by the Response Evaluation Criteria in Solid Tumors version 1.1. We divided the patients into three groups based on STM levels: Group A ≥ threefold upper limit of normal, threefold upper limit of normal > Group B > upper limit of normal, and Group C ≤ upper limit of normal. RESULTS: In total, 716 patients were included in this study. In Cox proportional hazards analyses, the STM levels in Group C were independently associated with superior PFS and OS in patients with lung adenocarcinoma (LUAD). Except for CA19-9 level, the STM levels in Group C were independently associated with superior PFS and OS in patients with lung squamous carcinoma (LUSC). Except for CEA and CA19-9 levels, the levels in Group A were independently associated with inferior PFS and OS in patients with LUAD and LUSC. CONCLUSIONS: Serum CEA, NSE, CYFRA21-1, and CA125 levels can predict PFS and OS in patients with LUAD and LUSC, and serum CA19-9 levels can predict PFS and OS in patients with LUAD. The higher the serum NSE, CYFRA21-1, and CA125 levels, the worse the PFS and OS in patients with LUAD and LUSC. In addition, the higher the serum CA19-9 level, the worse the OS in patients with LUAD.

An evaluation of masking nuisance odors from a source by chemical and sensory analyses.

There are many products in the market advertised as masking agents used to overpower strong nuisance odors, such as in or around water resource recovery facilities, solid waste processing facilities, landfills, composting sites, and so forth. Very little is known about the chemical component of these masking agents because they are protected by trade secrets. This is a problem for the parties involved, as the process of choosing the most adequate agent for the particular odor source falls into guesswork. This paper demonstrates that it is possible to determine how effective the masking product would be before spending time and resources in trials. It proposes to show this by comparing the Weber-Fechner curves of the odor-causing compounds known to be emitted at the facility with the curves from the potential masking agents prepared in the laboratory using an olfactometer. Several sensorial examples show that when the Weber-Fechner curves of the odorants and those of candidate masking agents are compared, it is possible to define the effectiveness of the masking agent tested. This is a novel use of the Weber-Fechner curves. The results show there is direct correlation between what is observed by a panel with real life odor samples subjected to incremental dilution and the Weber-Fechner odor intensity-odor concentration curve interaction between the odorants involved. Future work characterizing additional potential masking compounds by Weber-Fechner accompanied by odor profiling with dynamic olfactometry should shed light on the definitive effectiveness of this method in predicting masking effects and discovering useful masking compounds. PRACTITIONER POINTS: Weber-Fechner curves provide relationships between odorant concentration and odor intensity. Dynamic olfactometry, in which real-life air samples are sensorially analyzed by the odor profile method after subsequent dilutions, shows that odor masking occurs. Analyzing the Weber-Fechner curves of the odorants present in the dynamic olfactometry test show the existing odorant interactions. It is possible to predict the extent of the masking of potential compounds by comparing Weber-Fechner curves of masking agents against odorants causing nuisance. This methodology could help avoid spending resources in masking field trials that may result in further exacerbating the affected public.

High glucose enhances the aggressiveness of lung adenocarcinoma via activating epidermal growth factor receptor/signal transducer and activator of transcription 3 pathways.

Epidemiological studies revealed hyperglycemia as a poor prognostic factor for lung adenocarcinoma with unclear molecular mechanisms. The present study thus aimed to investigate the effects of high glucose on the progression of lung adenocarcinoma and its underlying mechanisms. Lung adenocarcinoma cell lines, A549 and RERF-LC-KJ, were cultured in 5.6 mM glucose (normal glucose; NG) or 25 mM glucose (high glucose; HG) resembling euglycemia and hyperglycemia. Cells were examined for proliferation by the MTT assay, and migration-invasion using Transwell. The expressions of signaling proteins in epidermal growth factor receptor (EGFR) pathways and their downstream targets were investigated using Western blots. The effects of diabetes mellitus (DM) and hyperglycemia on lung adenocarcinoma growth in vivo were studied in streptozotocin-induced diabetic BALB/cAJcl-Nu/Nu mice and their nondiabetic counterparts. High glucose significantly promoted proliferation, migration, and invasion of lung adenocarcinoma cells compared with those in normal glucose (P<.05). Western blot analyses showed the increased ratio of pEGFR/EGFR in cells cultured in high glucose and subsequently activated the signal transducer and activator of transcription 3 (STAT3). Epithelial-mesenchymal (EMT) markers were also altered in lung adenocarcinoma cells in high glucose conditions, corresponding with increased migration and invasion abilities. Erlotinib, an EGFR inhibitor, significantly reversed high glucose-induced aggressive phenotypes confirming high glucose-enhancing lung adenocarcinoma progression via the activation of EGFR. DM and hyperglycemia also promoted the growth of lung adenocarcinoma xenografts in vivo in which erlotinib significantly suppressed the growth of tumors (P<.05) suggesting EGFR inhibitor as an effective therapeutic agent for lung adenocarcinoma with DM.

Metformin as a booster of cancer immunotherapy.

Metformin, a biguanide antidiabetic, has been studied for its repurposing effects in oncology. Although a modest effect was observed in a single-agent regimen, metformin can synergize the anti-tumor effects of other modalities. The promising combination for cancer treatment is with immunotherapy. Despite high efficacy for some cancers, immunotherapy could be limited by modulation of the tumor immune microenvironment and the immune exhaustion of cytotoxic immune cells. Combining immunotherapy with metformin, thus, exerted a rescuing effect of immunotherapy and potentiated the anti-tumor effects of each other. Although not fully understood, metformin shows promoting effects of immunotherapy by several mechanisms. Those proposed mechanisms have been partially proven and are suggested for possible therapeutic strategies for cancer treatment. In this review, a state-of-the-art of metformin's boosting effects on immunotherapy is reviewed and discussed. The future directions for metformin research in preclinical and clinical immunotherapy are also suggested.

Shedding light on ORAI1 channel with genetic code expansion.

Genetic code expansion technology has been widely applied to control protein activity and biological systems by taking advantage of an amber stop codon suppressor tRNA and orthogonal aminoacyl-tRNA synthetase pair. With this chemical biology approach, Maltan et al. incorporated photocrosslinking unnatural amino acids (UAAs) into the transmembrane domains of ORAI1 to enable UV light-inducible calcium influx across the plasma membrane, mechanistic interrogation of the calcium release-activated calcium (CRAC) channel at the single amino acid level, and remote control of downstream calcium-modulated signaling in mammalian cells.

Engineering of NEMO as calcium indicators with large dynamics and high sensitivity.

Genetically encoded calcium indicators (GECIs) are indispensable tools for real-time monitoring of intracellular calcium signals and cellular activities in living organisms. Current GECIs face the challenge of suboptimal peak signal-to-baseline ratio (SBR) with limited resolution for reporting subtle calcium transients. We report herein the development of a suite of calcium sensors, designated NEMO, with fast kinetics and wide dynamic ranges (>100-fold). NEMO indicators report Ca2+ transients with peak SBRs around 20-fold larger than the top-of-the-range GCaMP6 series. NEMO sensors further enable the quantification of absolution calcium concentration with ratiometric or photochromic imaging. Compared with GCaMP6s, NEMOs could detect single action potentials in neurons with a peak SBR two times higher and a median peak SBR four times larger in vivo, thereby outperforming most existing state-of-the-art GECIs. Given their high sensitivity and resolution to report intracellular Ca2+ signals, NEMO sensors may find broad applications in monitoring neuronal activities and other Ca2+-modulated physiological processes in both mammals and plants.

Light-activated macromolecular phase separation modulates transcription by reconfiguring chromatin interactions.

Biomolecular condensates participate in the regulation of gene transcription, yet the relationship between nuclear condensation and transcriptional activation remains elusive. Here, we devised a biotinylated CRISPR-dCas9-based optogenetic method, light-activated macromolecular phase separation (LAMPS), to enable inducible formation, affinity purification, and multiomic dissection of nuclear condensates at the targeted genomic loci. LAMPS-induced condensation at enhancers and promoters activates endogenous gene transcription by chromatin reconfiguration, causing increased chromatin accessibility and de novo formation of long-range chromosomal loops. Proteomic profiling of light-induced condensates by dCas9-mediated affinity purification uncovers multivalent interaction-dependent remodeling of macromolecular composition, resulting in the selective enrichment of transcriptional coactivators and chromatin structure proteins. Our findings support a model whereby the formation of nuclear condensates at native genomic loci reconfigures chromatin architecture and multiprotein assemblies to modulate gene transcription. Hence, LAMPS facilitates mechanistic interrogation of the relationship between nuclear condensation, genome structure, and gene transcription in living cells.