Causality of genetically determined blood metabolites on inflammatory bowel disease: a two-sample Mendelian randomization study.

Inflammatory bowel disease (IBD) is a chronic and recurrent inflammatory disease of the gastrointestinal tract, including two subtypes: Crohn's disease (CD) and ulcerative colitis (UC). Metabolic disorders are important factors in the development of IBD. However, the evidence for the causal relationship between blood metabolites and IBD remains limited. A two-sample MR analysis was applied to evaluate relationships between 486 blood metabolites and IBD. The inverse variance weighted method was chosen as the primary MR analysis method. False discovery rate correction was used to control for false positives in multiple testing. Following complementary and sensitivity analyses were conducted using methods such as weight median, MR-egger, weighted mode, simple mode, Cochran Q test, and MR-PRESSO. Moreover, we performed replication, meta-analysis, Steiger test, and linkage disequilibrium score regression to enhance the robustness of the results. Additionally, we performed metabolic pathway analysis to identify potential metabolic pathways. As a result, we identified four significant causal associations between four blood metabolites and two IBD subtypes. Specifically, one metabolite was identified as being associated with the development of CD (mannose: odds ratio (OR) = 0.19, 95% confidence interval (CI) 0.08-0.43, P = 8.54 × 10-5). Three metabolites were identified as being associated with the development of UC (arachidonate (20:4n6): OR = 0.18, 95% CI 0.11-0.30, P = 2.09 × 10-11; 1, 5-anhydroglucitol: OR = 2.21, 95% CI 1.47-3.34, P = 1.50 × 10-4; 2-stearoylglycerophosphocholine: OR = 2.66, 95% CI 1.53-4.63, P = 5.30 × 10-4). The findings of our study suggested that the identified metabolites and metabolic pathways can be considered as useful circulating metabolic biomarkers for the screening and prevention of IBD in clinical practice, as well as candidate molecules for future mechanism exploration and drug target selection.

Therapeutic stapled peptides: Efficacy and molecular targets.

Peptide stapling, by employing a stable, preformed alpha-helical conformation, results in the production of peptides with improved membrane permeability and enhanced proteolytic stability, compared to the original peptides, and provides an effective solution to accelerate the rapid development of peptide drugs. Various reviews present peptide stapling chemistries, anchoring residues and one- or two-component cyclization, however, therapeutic stapled peptides have not been systematically summarized, especially focusing on various disease-related targets. This review highlights the latest advances in therapeutic peptide drug development facilitated by the application of stapling technology, including different stapling techniques, synthetic accessibility, applicability to biological targets, potential for solving biological problems, as well as the current status of development. Stapled peptides as therapeutic drug candidates have been classified and analysed mainly by receptor- and ligand-based stapled peptide design against various diseases, including cancer, infectious diseases, inflammation, and diabetes. This review is expected to provide a comprehensive reference for the rational design of stapled peptides for different diseases and targets to facilitate the development of therapeutic peptides with enhanced pharmacokinetic and biological properties.

A Fully Automated Deep-Learning Model for Predicting the Molecular Subtypes of Posterior Fossa Ependymomas Using T2-Weighted Images.

PURPOSE: We aimed to develop and validate a deep learning (DL) model to automatically segment posterior fossa ependymoma (PF-EPN) and predict its molecular subtypes [Group A (PFA) and Group B (PFB)] from preoperative MR images. EXPERIMENTAL DESIGN: We retrospectively identified 227 PF-EPNs (development and internal test sets) with available preoperative T2-weighted (T2w) MR images and molecular status to develop and test a 3D nnU-Net (referred to as T2-nnU-Net) for tumor segmentation and molecular subtype prediction. The network was externally tested using an external independent set [n = 40; subset-1 (n = 31) and subset-2 (n =9)] and prospectively enrolled cases [prospective validation set (n = 27)]. The Dice similarity coefficient was used to evaluate the segmentation performance. Receiver operating characteristic analysis for molecular subtype prediction was performed. RESULTS: For tumor segmentation, the T2-nnU-Net achieved a Dice score of 0.94 ± 0.02 in the internal test set. For molecular subtype prediction, the T2-nnU-Net achieved an AUC of 0.93 and accuracy of 0.89 in the internal test set, an AUC of 0.99 and accuracy of 0.93 in the external test set. In the prospective validation set, the model achieved an AUC of 0.93 and an accuracy of 0.89. The predictive performance of T2-nnU-Net was superior or comparable to that of demographic and multiple radiologic features (AUCs ranging from 0.87 to 0.95). CONCLUSIONS: A fully automated DL model was developed and validated to accurately segment PF-EPNs and predict molecular subtypes using only T2w MR images, which could help in clinical decision-making.

Enhanced Tumor Targeting and Penetration of Proteolysis-Targeting Chimeras through iRGD Peptide Conjugation: A Strategy for Precise Protein Degradation in Breast Cancer.

Proteolysis-targeting chimeras (PROTACs) have recently emerged as a promising technology for drug development. However, poor water solubility, limited tissue selectivity, and inadequate tumor penetration pose significant challenges for PROTAC-based therapies in cancer treatment. Herein, we developed an iRGD-PROTAC conjugation strategy utilizing tumor-penetrating cyclic peptide iRGD (CRGDK/RGPD/EC) to deliver PROTACs deep into breast cancer tissues. As a conceptual validation study, iRGD peptides were conjugated with a bromodomain-containing protein 4 (BRD4) PROTAC through a GSH-responsive linker. The resulting iRGD-PROTAC conjugate iPR showed enhanced water solubility, tumor-targeting capability, and penetration within tumor tissues, resulting in increased antibreast cancer efficacy in animal models and patient-derived organoids. This study demonstrates the advantages of combining iRGD and PROTACs in improving drug delivery and highlights the importance of tissue selectivity and penetration ability in PROTAC-based therapeutics.

Automated Determination of the H3 K27-Altered Status in Spinal Cord Diffuse Midline Glioma by Radiomics Based on T2-Weighted MR Images.

BACKGROUND AND PURPOSE: Conventional MR imaging is not sufficient to discern the H3 K27-altered status of spinal cord diffuse midline glioma. This study aimed to develop a radiomics-based model based on preoperative T2WI to determine the H3 K27-altered status of spinal cord diffuse midline glioma. MATERIALS AND METHODS: Ninety-seven patients with confirmed spinal cord diffuse midline gliomas were retrospectively recruited and randomly assigned to the training (n = 67) and test (n = 30) sets. One hundred seven radiomics features were initially extracted from automatically-segmented tumors on T2WI, then 11 features selected by the Pearson correlation coefficient and the Kruskal-Wallis test were used to train and test a logistic regression model for predicting the H3 K27-altered status. Sensitivity analysis was performed using additional random splits of the training and test sets, as well as applying other classifiers for comparison. The performance of the model was evaluated through its accuracy, sensitivity, specificity, and area under the curve. Finally, a prospective set including 28 patients with spinal cord diffuse midline gliomas was used to validate the logistic regression model independently. RESULTS: The logistic regression model accurately predicted the H3 K27-altered status with accuracies of 0.833 and 0.786, sensitivities of 0.813 and 0.750, specificities of 0.857 and 0.833, and areas under the curve of 0.839 and 0.818 in the test and prospective sets, respectively. Sensitivity analysis confirmed the robustness of the model, with predictive accuracies of 0.767-0.833. CONCLUSIONS: Radiomics signatures based on preoperative T2WI could accurately predict the H3 K27-altered status of spinal cord diffuse midline glioma, providing potential benefits for clinical management.

Amide proton transfer-weighted imaging and derived radiomics in the classification of adult-type diffuse gliomas.

OBJECTIVES: To evaluate the utility of amide proton transfer-weighted (APTw) MRI imaging and its derived radiomics in classifying adult-type diffuse glioma. MATERIALS AND METHODS: In this prospective study, APTw imaging was performed on 129 patients with adult-type diffuse gliomas. The mean APTw-related metrics (chemical exchange saturation transfer ratio (CESTR), CESTR normalized with the reference value (CESTRnr), and relaxation-compensated inverse magnetization transfer ratio (MTRRex)) and radiomic features within 3D tumor masks were extracted. APTw-radiomics models were developed using a support vector machine (SVM) classifier. Sensitivity analysis with tumor area of interest, different histogram cutoff values, and other classifiers were conducted. RESULTS: CESTR, CESTRnr, and MTRRex in glioblastomas were all significantly higher (p < 0.0003) than those of oligodendrogliomas and astrocytomas, with no significant difference between oligodendrogliomas and astrocytomas. The APTw-related metrics for IDH-wildtype and high-grade gliomas were significantly higher (p < 0.001) than those for the IDH-mutant and low-grade gliomas, with area under the curve (AUCs) of 0.88 for CESTR. The CESTR-radiomics models demonstrated accuracies of 84% (AUC 0.87), 83% (AUC 0.83), 90% (AUC 0.95), and 84% (AUC 0.86) in predicting the IDH mutation status, differentiating glioblastomas from astrocytomas, distinguishing glioblastomas from oligodendrogliomas, and determining high/low grade prediction, respectively, but showed poor performance in distinguishing oligodendrogliomas from astrocytomas (accuracy 63%, AUC 0.63). The sensitivity analysis affirmed the robustness of the APTw signal and APTw-derived radiomics prediction models. CONCLUSION: APTw imaging, along with its derived radiomics, presents a promising quantitative approach for prediction IDH mutation and grading adult-type diffuse glioma. CLINICAL RELEVANCE STATEMENT: Amide proton transfer-weighted imaging, a quantitative imaging biomarker, coupled with its derived radiomics, offers a promising non-invasive approach for predicting IDH mutation status and grading adult-type diffuse gliomas, thereby informing individualized clinical diagnostics and treatment strategies. KEY POINTS: • This study evaluates the differences of different amide proton transfer-weighted metrics across three molecular subtypes and their efficacy in classifying adult-type diffuse glioma. • Chemical exchange saturation transfer ratio normalized with the reference value and relaxation-compensated inverse magnetization transfer ratio effectively predicts IDH mutation/grading, notably the first one. • Amide proton transfer-weighted imaging and its derived radiomics holds potential to be used as a diagnostic tool in routine clinical characterizing adult-type diffuse glioma.

M6ATMR: identifying N6-methyladenosine sites through RNA sequence similarity matrix reconstruction guided by Transformer.

Numerous studies have focused on the classification of N6-methyladenosine (m6A) modification sites in RNA sequences, treating it as a multi-feature extraction task. In these studies, the incorporation of physicochemical properties of nucleotides has been applied to enhance recognition efficacy. However, the introduction of excessive supplementary information may introduce noise to the RNA sequence features, and the utilization of sequence similarity information remains underexplored. In this research, we present a novel method for RNA m6A modification site recognition called M6ATMR. Our approach relies solely on sequence information, leveraging Transformer to guide the reconstruction of the sequence similarity matrix, thereby enhancing feature representation. Initially, M6ATMR encodes RNA sequences using 3-mers to generate the sequence similarity matrix. Meanwhile, Transformer is applied to extract sequence structure graphs for each RNA sequence. Subsequently, to capture low-dimensional representations of similarity matrices and structure graphs, we introduce a graph self-correlation convolution block. These representations are then fused and reconstructed through the local-global fusion block. Notably, we adopt iteratively updated sequence structure graphs to continuously optimize the similarity matrix, thereby constraining the end-to-end feature extraction process. Finally, we employ the random forest (RF) algorithm for identifying m6A modification sites based on the reconstructed features. Experimental results demonstrate that M6ATMR achieves promising performance by solely utilizing RNA sequences for m6A modification site identification. Our proposed method can be considered an effective complement to existing RNA m6A modification site recognition approaches.

Deep Learning for Noninvasive Assessment of H3 K27M Mutation Status in Diffuse Midline Gliomas Using MR Imaging.

BACKGROUND: Determination of H3 K27M mutation in diffuse midline glioma (DMG) is key for prognostic assessment and stratifying patient subgroups for clinical trials. MRI can noninvasively depict morphological and metabolic characteristics of H3 K27M mutant DMG. PURPOSE: This study aimed to develop a deep learning (DL) approach to noninvasively predict H3 K27M mutation in DMG using T2-weighted images. STUDY TYPE: Retrospective and prospective. POPULATION: For diffuse midline brain gliomas, 341 patients from Center-1 (27 ± 19 years, 184 males), 42 patients from Center-2 (33 ± 19 years, 27 males) and 35 patients (37 ± 18 years, 24 males). For diffuse spinal cord gliomas, 133 patients from Center-1 (30 ± 15 years, 80 males). FIELD STRENGTH/SEQUENCE: 5T and 3T, T2-weighted turbo spin echo imaging. ASSESSMENT: Conventional radiological features were independently reviewed by two neuroradiologists. H3 K27M status was determined by histopathological examination. The Dice coefficient was used to evaluate segmentation performance. Classification performance was evaluated using accuracy, sensitivity, specificity, and area under the curve. STATISTICAL TESTS: Pearson's Chi-squared test, Fisher's exact test, two-sample Student's t-test and Mann-Whitney U test. A two-sided P value <0.05 was considered statistically significant. RESULTS: In the testing cohort, Dice coefficients of tumor segmentation using DL were 0.87 for diffuse midline brain and 0.81 for spinal cord gliomas. In the internal prospective testing dataset, the predictive accuracies, sensitivities, and specificities of H3 K27M mutation status were 92.1%, 98.2%, 82.9% in diffuse midline brain gliomas and 85.4%, 88.9%, 82.6% in spinal cord gliomas. Furthermore, this study showed that the performance generalizes to external institutions, with predictive accuracies of 85.7%-90.5%, sensitivities of 90.9%-96.0%, and specificities of 82.4%-83.3%. DATA CONCLUSION: In this study, an automatic DL framework was developed and validated for accurately predicting H3 K27M mutation using T2-weighted images, which could contribute to the noninvasive determination of H3 K27M status for clinical decision-making. EVIDENCE LEVEL: 2 Technical Efficacy: Stage 2.

miR-3682-3p Activated by c-Myc Aggravates the Migration and Stemness in Hepatocellular Carcinoma Cells by Regulating PTEN/PI3K/AKT/ß-Catenin Signaling.

BACKGROUND: Hepatocellular carcinoma (HCC) is a leading cancer worldwide. miRNA has been linked to cancer processes. We want to figure out what the underlying mechanism and functions of miR-3682-3p are in HCC. METHODS: Thirty pairs of tumor tissues and adjacent tissues were obtained from HCC patients. mRNA and protein expressions were detected by quantitative real-time PCR and Western blot, respectively. The migration and invasion were measured using transwell or wound-healing assays. Dual luciferase and ChIP assays were utilized to detect gene interactions. RESULTS: miR-3682-3p was highly expressed in HCC tissues and cell lines. Silencing of miR-3682-3p inhibited cell migration and invasion, increased E-cadherin expression, and decreased N-cadherin, vimentin, and snail expressions, as well as the SOX2, OCT4, and Bmi1 expression, thereby restraining EMT and stemness of HCC in vitro. miR-3682-3p was positively activated by c-Myc and could directly target PTEN to activate PI3K/AKT/ß-catenin pathway. In addition, inhibition of PTEN weakened the anti-migration and anti-stemness effects of miR-3682-3p downregulation in HCC cells. CONCLUSION: miR-3682-3p promoted HCC migration and stemness through PTEN/PI3K/AKT/ß-catenin signaling, implying that miR-3682-3p might be a promising target for HCC clinical treatment.

LncRNA SNHG16 promotes colorectal cancer cell proliferation, migration, and epithelial-mesenchymal transition through miR-124-3p/MCP-1.

Colorectal cancer (CRC) has been the third leading cause of cancer-associated deaths. LncRNA SNHG16 is reported to be involved in metastasis of CRC cells. However, the mechanism by which SNHG16 regulates CRC progression is poorly understood. The proliferation of CRC cells was examined by MTT. Wound healing and transwell assay were used to measure migration and invasion ability. RT-qPCR and western blot were used to examine gene expression. Immunofluorescence was conducted to evaluate the EMT of CRC cells. Luciferase reporter assay were used to confirm direct interaction between miR-124-3p and SNHG16 or MCP-1. The interaction between miR-124-3p and SNHG16 was detected by RIP and RNA pull down assay. H&E staining was used to test the histomorphological changes of hepatic metastatic nodules. Finally, xenograft tumor experiment was utilized to determine tumor growth in vivo. SNHG16 and miR-124-3p were dysregulated in human colorectal tumors or cells. Knockdown of SNHG16 led to attenuate cell proliferation, migration, invasion, and EMT of CRC cells. And xenograft tumor experiment showed that SNHG16 might influence tumor growth. In contrast, miR-124-3p exerted the antitumor effects. Knockdown of miR-124-3p can reverse the effect of sh-SNHG16 on CRC cells. miR-124-3p could directly bind to SNHG16 or MCP-1. More importantly, MCP-1 acts as a critical effector mediating the role of SNHG16/ miR-124-3p in CRC cells. In summary, our data suggest that SNHG16 plays a contributory role in proliferation, migration, and EMT of CRC cells via miR-124-3p/MCP-1 axis, which offers a rationale for targeting SNHG16 and developing therapeutic drugs to treat CRC.

Association of postoperative recurrence with radiological and clinicopathological features in patients with stage IA-IIA lung adenocarcinoma.

OBJECTIVES: To retrospectively investigate whether radiological and clinicopathological characteristics were associated with the presence of stage IA-IIA lung adenocarcinoma in patients at high risk for a postoperative recurrence. MATERIALS AND METHODS: Three hundred twelve patients with biopsy-proven node-negative early-stage (IA-IIA) lung adenocarcinoma met the inclusion criteria for this study. Demographics data and histopathological findings were collected from medical records. Computed tomography (CT) performed approximately 1 month before surgery was manually scored using 23 CT descriptors. Univariate analyses were applied to demonstrate an association between clinicopathological and radiological features and 2-/5-year recurrences. Multivariate logistic regression was performed to assess the ability of radiological and clinicopathological features to discriminate low and high-risk factors for recurrence. A ROC curve was used to evaluate prediction performance. RESULTS: Univariate analysis revealed that the 2-year recurrence was associated with six radiological features and two clinicopathological features, while 5-year recurrence was associated with five radiological features and two clinicopathological features. A multivariate logistic regression model of combined clinicopathological and radiological features showed that stage IIA (OR = 2.87), solid texture (solid part > 50 %: OR = 4.81; solid part = 100 %: OR = 3.61), pleural attachment (OR = 3.97) and bronchovascular bundle thickening (OR = 2.16) were associated with the independent predictors of 2-year recurrence, and stage IIA (OR = 3.52), solid texture (solid part > 50 %: OR = 3.56; solid part = 100 %: OR = 2.44) and pleural attachment (OR = 4.57) were associated with 5-year recurrence. Combined radiological and clinicopathological features could be significant indicators of 2- and 5-year recurrences (AUC = 0.784 and AUC = 0.815, respectively). CONCLUSIONS: The combination of radiological and clinicopathological features has the potential to help predict postoperative recurrence in patients with stage IA-IIA lung adenocarcinomas and guide oncologists and patients whether to undergo additional treatment after surgery.

Angiopep-2-Modified Carboxymethyl Chitosan-Based pH/Reduction Dual-Stimuli-Responsive Nanogels for Enhanced Targeting Glioblastoma.

Glioblastoma (GBM) is a fatal brain tumor with poor prognosis. Blood-brain barrier (BBB) prevents the effective delivery of chemotherapeutic agents to GBM. Herein, we developed a pH/reduction-sensitive carboxymethyl chitosan nanogel (CMCSN) modified by targeting peptide angiopep-2 (ANG) and loaded with doxorubicin (DOX). The multifunctional nanogel (DOX-ANG-CMCSN) exhibited good pH and reduction sensitivity, ideal stability, and biocompatibility. Its hydrodynamic diameter was 190 nm, drug loading was 12.7%, and the cumulative release rate of 24 h was 82.3% under the simulated tumor microenvironment. More importantly, the modification of ANG significantly enhanced BBB penetration and tumor targeting ability both in vivo and in vitro. DOX-ANG-CMCSN achieved 2-3-fold higher uptake and an enhanced antitumor activity compared with nontargeted DOX-CMCSN. Therefore, the targeted nanogels with the pH/reduction dual-stimuli response may provide a promising platform for GBM-targeted chemotherapy.

Imaging Biomarkers to Predict and Evaluate the Effectiveness of Immunotherapy in Advanced Non-Small-Cell Lung Cancer.

OBJECTIVE: We aimed to identify imaging biomarkers to assess predictive capacity of radiomics nomogram regarding treatment response status (responder/non-responder) in patients with advanced NSCLC undergoing anti-PD1 immunotherapy. METHODS: 197 eligible patients with histologically confirmed NSCLC were retrospectively enrolled from nine hospitals. We carried out a radiomics characterization from target lesions (TL) approach and largest target lesion (LL) approach on baseline and first follow-up (TP1) CT imaging data. Delta-radiomics feature was calculated as the relative net change in radiomics feature between baseline and TP1. Minimum Redundancy Maximum Relevance (mRMR) and Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression were applied for feature selection and radiomics signature construction. RESULTS: Radiomics signature at baseline did not show significant predictive value regarding response status for LL approach (P = 0.10), nor in terms of TL approach (P = 0.27). A combined Delta-radiomics nomogram incorporating Delta-radiomics signature with clinical factor of distant metastasis for target lesions had satisfactory performance in distinguishing responders from non-responders with AUCs of 0.83 (95% CI: 0.75-0.91) and 0.81 (95% CI: 0.68-0.95) in the training and test sets respectively, which was comparable with that from LL approach (P = 0.92, P = 0.97). Among a subset of those patients with available pretreatment PD-L1 expression status (n = 66), models that incorporating Delta-radiomics features showed superior predictive accuracy than that of PD-L1 expression status alone (P <0.001). CONCLUSION: Early response assessment using combined Delta-radiomics nomograms have potential advantages to identify patients that were more likely to benefit from immunotherapy, and help oncologists modify treatments tailored individually to each patient under therapy.

Agarase cocktail from agar polysaccharide utilization loci converts homogenized Gelidium amansii into neoagarooligosaccharides.

Neoagarooligosaccharides (NAOs) are drawing more and more attention because of their numerous bioactivities, yet limited number of agarases impedes NAOs production from red algae. In this study, predicted agar polysaccharide utilization loci (agar-PUL) were firstly used as inventory for agarase. 6 agarases were identified from agar-PULs and two of them were successfully expressed and analyzed. Then enzyme cocktail (GH16-1:GH16-2:Aga50D = 2:1:1) was proved to have highest synergistic effect. Finally homogenization was applied to G. amansii and proved to be an efficient way to release agar from tissues. When liquid-to-solid ratio was 9 g/150 mL, homogenization time was 20 min, and enzyme cocktail loading was 150 U/150 mL, maximum NAOs production (90.2 mg per 9 g wet G. amansii) could be achieved. Enzyme supported one-step process (ESOP) proposed in study is environment-friendly, time saving, cost saving and none-destructive, therefore has a potential industrial application in red algae utilization.

A Combined-Radiomics Approach of CT Images to Predict Response to Anti-PD-1 Immunotherapy in NSCLC: A Retrospective Multicenter Study.

OBJECTIVE: Based on non-contrast-enhanced (NCE)/contrast-enhanced (CE) computed tomography (CT) images, we try to identify a combined-radiomics model and evaluate its predictive capacity regarding response to anti-PD1 immunotherapy of patients with non-small-cell lung cancer (NSCLC). METHODS: 131 patients with NSCLC undergoing anti-PD1 immunotherapy were retrospectively enrolled from 7 institutions. Using largest lesion (LL) and target lesions (TL) approaches, we performed a radiomics analysis based on pretreatment NCE-CT (NCE-radiomics) and CE-CT images (CE-radiomics), respectively. Meanwhile, a combined-radiomics model based on NCE-CT and CE-CT images was constructed. Finally, we developed their corresponding nomograms incorporating clinical factors. ROC was used to evaluate models' predictive performance in the training and testing set, and a DeLong test was employed to compare the differences between different models. RESULTS: For TL approach, both NCE-radiomics and CE-radiomics performed poorly in predicting response to immunotherapy. For LL approach, NCE-radiomics nomograms and CE-radiomics nomograms incorporating with clinical factor of distant metastasis all showed satisfactory results, reflected by the AUCs in the training (AUC=0.84, 95% CI: 0.75-0.92; AUC=0.77, 95% CI: 0.67-0.87) and test sets (AUC=0.78, 95% CI: 0.64-0.92, AUC=0.73, 95% CI: 0.57-0.88), respectively. Compared with the NCE-radiomics nomograms, the combined-radiomics nomogram showed incremental predictive capacity in the training set (AUC=0.85, 95% CI: 0.77-0.92) and test set (AUC=0.81, 95% CI: 0.67-0.94), respectively, but no statistical difference (P=0.86, P=0.79). CONCLUSION: Compared with radiomics based on single NCE or CE-CT images, the combined-radiomics model has potential advantages to identify patients with NSCLC most likely to benefit from immunotherapy, and may effectively improve more precise and individualized decision support.

Effects of Glycosylation and d-Amino Acid Substitution on the Antitumor and Antibacterial Activities of Bee Venom Peptide HYL.

Glycosylation is a promising strategy for modulating the physicochemical properties of peptides. However, the influence of glycosylation on the biological activities of peptides remains unknown. Here, we chose the bee venom peptide HYL as a model peptide and 12 different monosaccharides as model sugars to study the effects of glycosylation site, number, and monosaccharide structure on the biochemical properties, activities, and cellular selectivities of HYL derivatives. Some analogues of HYL showed improvement not only in cell selectivity and proteolytic stability but also in antitumor and antimicrobial activity. Moreover, we found that the helicity of glycopeptides can affect its antitumor activity and proteolytic stability, and the α-linked d-monosaccharides can effectively improve the antitumor activity of HYL. Therefore, it is possible to design peptides with improved properties by varying the number, structure, and position of monosaccharides. What's more, the glycopeptides HYL-31 and HYL-33 show a promising prospect for antitumor and antimicrobial drugs development, respectively. In addition, we found that the d-lysine substitution strategy can significantly improve the proteolytic stability of HYL. Our new approach provides a reference or guidance for the research of novel antitumor and antimicrobial peptide drugs.

DTPAA-Gd Functionalized Ultrasmall Au15NCs Nanohybrids for Multimodal Imaging.

INTRODUCTION: Multimodal imaging agent has the potential to overcome the shortage and incorporate the advantages of different imaging tools for extremely sensitive diagnosis. To achieve multimodal imaging, combining multiple contrast agents into a special nanostructure has become a main strategy; However, the combination of all of these functions into one nanoplatform usually requires a complicated synthetic procedure that results in heterogeneous nanostructure. METHODS: In this study, we develop ultrasmall gold nanoclusters with 15 gold atoms (Au15NCs) functionalized with diethylenetriamine-pentaacetic acid dianhydride (DTPAA-Gd) as an optimized multimodal imaging agent to enhance imaging ability. RESULTS: The Au15NCs-DTPAA-Gd nanohybrids possess the ultra-small size and are capable of enhancing the contrast in near-infrared fluorescence (NIRF), magnetic resonance (MR) and X-ray computed tomography (CT) imaging. Meanwhile, the integrated DTPAA-Gd component not only endow the nanohybrids to produce higher T1 relaxivity (r1 = 21.4 mM-1 s-1) than Omnipaque (r1 = 3.973 mM-1s-1) but also further enhance X-ray attenuation property of Au15NCs. Importantly, the fluorescence intensity of Au15NCs-DTPAA-Gd did not decrease compared with Au15NCs. Ultimately, in vivo imaging experiments have demonstrated that Au15NCs-DTPAA-Gd nanohybrids can be quickly eliminated from the body through the urinary system and has great potential for anatomical imaging. CONCLUSION: These data manifest Au15NCs-DTPAA-Gd present great potential as a multimodal contrast agent for disease diagnosis, especially for early accurate detection of tumors.

Improving Selectivity, Proteolytic Stability, and Antitumor Activity of Hymenochirin-1B: A Novel Glycosylated Staple Strategy.

As a host defense peptide, hymenochirin-1B has attracted increasing attention for its strong cytotoxic activities. However, its poor selectivity and proteolytic stability remain major obstacles for clinical application. To solve these problems, we designed and synthesized a series of peptide analogues of hymenochirin-1B based on cationic residue substitution and stapling combined with a glycosylation strategy. Some analogues showed improvement not only in selectivity and proteolytic stability but also in antitumor activity. Among them, the glycosylated stapled peptide H-58 was identified as the most potential antitumor peptide. Flow cytometry and a competitive binding assay revealed that H-58 displayed significant antitumor selectivity. Confocal microscopy and nuclear staining with Hoechst dye demonstrated that H-58 entered the nucleus and caused DNA damage. In summary, the strategy of glycosylated stapled peptides is a promising approach for improving the antitumor selectivity, proteolytic stability, and antitumor activity of hymenochirin-1B, which can be used for other bioactive peptide modifications.

Salidroside protects PC-12 cells against amyloid ß-induced apoptosis by activation of the ERK1/2 and AKT signaling pathways.

Alzheimer's disease (AD) is one of the most frequent diseases in elderly people and causes high mortality. Its incidence is increasing annually and no effective therapeutic treatment currently exists. In the present study, salidroside, a major active ingredient of Rhodiola rosea, was able to protect PC­12 cells from the toxicity and apoptosis induced by AD inducer amyloid (A)ß1­42. Salidroside significantly protected PC­12 cells by inhibiting Aß1­42­induced cytotoxicity and mitochondria­mediated endogenous caspase apoptotic pathways. Mechanistic studies demonstrated that salidroside significantly activated the extracellular signal regulated kinase (ERK)1/2 and protein kinase B (AKT) signaling pathways. This observation was further confirmed using the ERK1/2 inhibitor PD98059 and the AKT inhibitor LY294002, which demonstrated that salidroside promoted PC­12 cell survival and proliferation by activating the ERK1/2 and AKT signaling pathways. Salidroside is a therapeutic candidate for the treatment of AD and provides a basis for further drug development.

Imaging-based Biomarkers for Predicting and Evaluating Cancer Immunotherapy Response.

Proper patient selection for immunotherapy is critical, as certain tumor microenvironments are more permissible to therapy than others. Currently, the use of programmed cell death ligand-1 (PD-L1) and microsatellite instability high and/or mismatch repair deficiency are used as biomarkers for immunotherapy response. To improve tumor characterization, methodologies are being developed to combine imaging with tumor immune environment characterization. Imaging of tumors from immunotherapy responders and nonresponders with various imaging modalities has led to the development of criteria that could predict patient response to immunotherapy. Additionally, radiomics-based artificial intelligence methods are being used to characterize tumor microenvironments to predict and evaluate immunotherapy responses, as well as to predict risk of immune-related adverse events. Molecular imaging techniques are also being developed for various modalities to observe tumor expression of immunotherapy targets, such as PD-L1 and, to confirm the target is being expressed on resident tumors. In all, the advancements of imaging techniques to define tumor immunologic characteristics will help to stratify patients who are more likely to respond to immunotherapies. Keywords: Computer Aided Diagnosis (CAD), Computer Applications-Virtual Imaging, Efficacy Studies, MR-Imaging, Molecular Imaging-Cancer, Molecular Imaging-Immunotherapy, Molecular Imaging-Nanoparticles, Molecular Imaging-Probe Development, Molecular Imaging-Target Development, SPECT/CT © RSNA, 2019.