Prognostic and therapeutic value of the Eph/Ephrin signaling pathway in pancreatic cancer explored based on bioinformatics.

Pancreatic cancer (PC) is one of the most common malignant tumors of the digestive tract and has a very high mortality rate worldwide. Different PC patients may respond differently to therapy and develop therapeutic resistance due to the complexity and variety of the tumor microenvironment. The Eph/ephrin signaling pathway is extensively involved in tumor-related biological functions. However, the key function of the Eph/ephrin signaling pathway in PC has not been fully elucidated. We first explored a pan-cancer overview of Eph/ephrin signaling pathway genes (EPGs). Then we grouped the PC patients into 3 subgroups based on EPG expression levels. Significantly different prognoses and tumor immune microenvironments between different subtypes further validate Eph/ephrin's important role in the pathophysiology of PC. Additionally, we estimated the IC50 values for several commonly used molecularly targeted drugs used to treat PC in the three clusters, which could help patients receive a more personalized treatment plan. Following a progressive screening of optimal genes, we established a prognostic signature and validated it in internal and external test sets. The receiver operating characteristic (ROC) curves of our model exhibited great predictive performance. Meanwhile, we further validated the results through qRT-PCR and immunohistochemistry. Overall, this research provides fresh clues on the prognosis and therapy of PC as well as the theoretical groundwork for future Eph/ephrin signaling pathway research.

The Molecular Characteristics and Therapeutic Implications of O-Glycan Synthesis in Pancreatic Cancer by Integrating Transcriptome and Single-Cell Data

BACKGROUND: Glycans constitute the primary components of proteins that regulate key carcinogenic processes in cancer progression. This study investigated the significance of O-glycan synthesis in the pathogenesis, outcome, and therapy of pancreatic cancer (PC). METHODS: Transcriptomic data and clinical prognostic information of PC were acquired via TCGA and GEO databases. CSA database was used to obtain single-cell data of PC. The O-glycan biosynthesis signaling pathway and its related genes were acquired via the MSigDB platform. The nonnegative matrix factorization (NMF) clustering was utilized to construct the O-glycan biosynthesis-associated molecular subtypes in PC. The LASSO and Cox regression were utilized to build the prognostic prediction model. We utilized real-time quantitative PCR (qRT-PCR) to verify the expressed levels of model genes. Single-cell analysis was utilized to investigate the levels of target genes and O-glycan biosynthesis signaling pathway in the PC tumour microenvironment. RESULTS: : We obtained 30 genes related to O-glycan biosynthesis, among which 15 were associated with the prognosis of PC. All PC samples were grouped into two distinct molecular subtypes associated with O-glycan biosynthesis: OGRGcluster C1 and OGRGcluster C2, and compared to OGRGcluster C1. PCs in OGRGcluster C2 had a more advanced clinical stage and pathological grade, worse prognosis, and more active O-glycan biosynthesis function. Immune analysis indicated that naïve B cell, CD8+ T cell, memory-activated CD4+ T cell, and monocytes displayed remarkably higher infiltration levels in OGRGcluster C1 while resting NK cell, macrophages M0, resting dendritic cell, activated dendritic cell, and neutrophils exhibited markedly higher infiltration levels in OGRGcluster C2. OGRGcluster C1 exhibited higher sensitivities to drugs, such as cisplatin, irinotecan, KRAS(G12C) inhibitor-12, oxaliplatin, paclitaxel, and sorafenib. Besides, we built the O-glycan biosynthesis-related prognostic model (including SPRR1B, COL17A1, and ECT2) with a good prediction performance. SPRR1B, COL17A1, and ECT2 were remarkably highly expressed in PC tissues and linked to a poor outcome. Single-cell analysis revealed that O-glycan biosynthesis was observed only in PC, and consistent with this, the target genes were significantly enriched in PC. CONCLUSION: We first constructed molecular subtypes and prognostic models related to O-glycan biosynthesis in PC. It is clear that O-glycan biosynthesis is related to the development, prognosis, immune microenvironment, and treatment of PC. This provides new strategies for stratification, diagnosis, and treatment of PC patients.

Oxidative stress and autophagy-mediated immune patterns and tumor microenvironment infiltration characterization in gastric cancer.

Recent years have seen a sharp rise in the amount of research on the connection between oxidative stress, autophagy, and cancer cells. However, the significant functions of oxidative stress and autophagy-related genes (OARGs) in gastric cancer (GC) are yet to be investigated integrally. Therefore, it will be a new and promising concept to search for novel OARG-related biomarkers to predict the prognosis and treatment response of GC. First, we assessed changes in prognosis and tumor microenvironment (TME) characteristics across the various oxidative stress and autophagy-related modification patterns based on a detailed analysis of 17 OARGs with prognostic significance of 808 GC samples. We identified three distinct OARG alteration patterns which displayed unique biological characteristics and immune cell infiltration features. Using principal component analysis methods, the OARGscore was developed to evaluate the OARG modification patterns of certain tumors. The negative connection between OARGscore and immune cells was statistically significant. Increased survival, a higher incidence of mutations, and a better response to immunotherapy were all predicted to be related to patients' high-OARGscore. In addition, the candidate chemotherapeutic drugs were predicted using the oncoPredict program. The low-OARGscore group was predicted to benefit more from Ribociclib, Alisertib, Niraparib, Epirubicin, Olaparib, and Axitinib, while patients in the high-OARGscore group were predicted to benefit more from Afatinib, Oxaliplatin, Paclitaxel, 5-Fluorouracil, Dabrafenib and Lapatinib. Our findings offer a specific method for predicting a patient's prognosis and susceptibility to immunotherapy, as well as a promising insight of oxidative stress and autophagy in GC.

Protection of H9c2 Myocardial Cells from Oxidative Stress by Crocetin via PINK1/Parkin Pathway-Mediated Mitophagy.

This study aimed to explore the oxidative stress-protective effect of crocetin on H2O2-mediated H9c2 myocardial cells through in vitro experiments, and further explore whether its mechanism is related to the impact of mitophagy. This study also aimed to demonstrate the therapeutic effect of safflower acid on oxidative stress in cardiomyocytes and explore whether its mechanism is related to the effect of mitophagy. Here, an H2O2-based oxidative stress model was constructed and assessed the degree of oxidative stress injury of cardiomyocytes by detecting the levels of lactate dehydrogenase (LDH), creatine kinase (CK), malondialdehyde (MDA), superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH Px). Reactive oxygen species (ROS)-detecting fluorescent dye DCFH-DA, JC-1 dye, and TUNEL dye were employed to assess mitochondrial damage and apoptosis. Autophagic flux was measured by transfecting Ad-mCherry-GFP-LC3B adenovirus. Mitophagy-related proteins were then detected via western blotting and immunofluorescence. However, crocetin (0.1-10 µM) could significantly improve cell viability and reduce apoptosis and oxidative stress damage caused by H2O2. In cells with excessive autophagic activation, crocetin could also reduce autophagy flow and the expression of mitophagy-related proteins PINK1 and Parkin, and reverse the transfer of Parkin to mitochondria. Crocetin could reduce H2O2-mediated oxidative stress damage and the apoptosis of H9c2 cells, and its mechanism was closely related to mitophagy.

Network pharmacology prediction and molecular docking-based strategy to discover the potential pharmacological mechanism of action of Wang Bu Liu Xing (Semen vaccariae) for colorectal cancer.

Background: Colorectal cancer (CRC) is the leading cause of cancer-related death worldwide. Wang Bu Liu Xing [Semen vaccariae (SV)] is a traditional Chinese medicine (TCM) ingredient with anti-angiogenic and anti-tumor effects. However, little research has been done on the ingredients found in SV or the putative process by which SV fights CRC, and this paper aims to reveal the components of SV that are effective in treating CRC. Methods: The open database and online platform were used in this study, Symptom Mapping (SymMap) and Traditional Chinese Medicine Systems Pharmacology (TCMSP) for SV ingredient and targets, Gene Expression Omnibus (GEO) for differentially expressed genes (DEGs) of CRC, Database for Annotation Visualization and Integrated Discovery (DAVID) for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, STRING-Cytoscape for protein-protein interaction (PPI), AutoDockTools for Molecular docking and others. were conducted to determine how SV affects CRC and what are the most important components, potential targets, and signaling pathways. Results: The findings of the network pharmacology study indicated that swerchirin and CDK2 potential target gene for SV was connected to anti-CRC actions. SV may inhibit CRC by interacting with crucial targets like BCL2L1, CDK2, and SERPINE1. Additionally, KEGG analysis revealed that the p53 signaling pathway may be a driver of the anti-CRC impact of SV. Molecular docking showed that swerchirin can bind with its target protein in a good bond by intermolecular force. Conclusions: In this study, the pharmacological effects of SV were examined, along with its potential therapeutic impact on CRC. These effects of SV appear to be mediated via a variety of substances, targets, and pathways. SV exerts pharmacological effects in CRC, p53 signaling pathway is great value. The main molecular docking is CDK2 and swerchirin. Moreover, our research offers a promising method for characterizing therapeutic pathways and identifying molecules in TCM.

Controversial role of ILC3s in intestinal diseases: A novelty perspective on immunotherapy.

ILC3s have been identified as crucial immune regulators that play a role in maintaining host homeostasis and modulating the antitumor response. Emerging evidence supports the idea that LTi cells play an important role in initiating lymphoid tissue development, while other ILC3s can promote host defense and orchestrate adaptive immunity, mainly through the secretion of specific cytokines and crosstalk with other immune cells or tissues. Additionally, dysregulation of ILC3-mediated overexpression of cytokines, changes in subset abundance, and conversion toward other ILC subsets are closely linked with the occurrence of tumors and inflammatory diseases. Regulation of ILC3 cytokines, ILC conversion and LTi-induced TLSs may be a novel strategy for treating tumors and intestinal or extraintestinal inflammatory diseases. Herein, we discuss the development of ILCs, the biology of ILC3s, ILC plasticity, the correlation of ILC3s and adaptive immunity, crosstalk with the intestinal microenvironment, controversial roles of ILC3s in intestinal diseases and potential applications for treatment.

The combined signatures of the tumour microenvironment and nucleotide metabolism-related genes provide a prognostic and therapeutic biomarker for gastric cancer.

The tumour microenvironment (TME) is vital to tumour development and influences the immunotherapy response. Abnormal nucleotide metabolism (NM) not only promotes tumour cell proliferation but also inhibits immune responses in the TME. Therefore, this study aimed to determine whether the combined signatures of NM and the TME could better predict the prognosis and treatment response in gastric cancer (GC). 97 NM-related genes and 22 TME cells were evaluated in TCGA-STAD samples, and predictive NM and TME characteristics were determined. Subsequent correlation analysis and single-cell data analysis illustrated a link between NM scores and TME cells. Thereafter, NM and TME characteristics were combined to construct an NM-TME classifier. Patients in the NMlow/TMEhigh group exhibited better clinical outcomes and treatment responses, which could be attributed to the differences in immune cell infiltration, immune checkpoint genes, tumour somatic mutations, immunophenoscore, immunotherapy response rate and proteomap. Additionally, the NMhigh/TMElow group benefited more from Imatinib, Midostaurin and Linsitinib, while patients in the NMlow/TMEhigh group benefited more from Paclitaxel, Methotrexate and Camptothecin. Finally, a highly reliable nomogram was developed. In conclusion, the NM-TME classifier demonstrated a pretreatment predictive value for prognosis and therapeutic responses, which may offer novel strategies for strategizing patients with optimal therapies.

Effect of sarcopenia on survival in patients after pancreatic surgery: a systematic review and meta-analysis.

Background: Numerous studies have reported sarcopenia to be associated with unfavorable outcomes in patients who have undergone pancreatectomy. Therefore, in this meta-analysis, we examined the relationship between sarcopenia and survival after pancreatic surgery. Methods: PubMed, Embase, and Cochrane Library were searched for studies that examined the association between sarcopenia and survival after pancreatic surgery from the inception of the database until June 1, 2023. Hazard ratio (HR) for overall survival (OS) and/or progression-free survival (PFS) of sarcopenia and pancreatic surgery were extracted from the selected studies and random or fixed-effect models were used to summarize the data according to the heterogeneity. Publication bias was assessed using Egger's linear regression test and a funnel plot. Results: Sixteen studies met the inclusion criteria. For 13 aggregated univariate and 16 multivariate estimates, sarcopenia was associated with decreased OS (univariate analysis: HR 1.69, 95% CI 1.48-1.93; multivariate analysis: HR 1.69; 95% CI 1.39-2.05, I2 = 77.4%). Furthermore, sarcopenia was significantly associated with poor PFS of pancreatic resection (Change to univariate analysis: HR 1.74, 95% CI 1.47-2.05; multivariate analysis: HR 1.54; 95% CI 1.23-1.93, I2 = 63%). Conclusion: Sarcopenia may be a significant prognostic factor for a shortened survival following pancreatectomy since it is linked to an elevated risk of mortality. Further studies are required to understand how sarcopenia affects long-term results after pancreatic resection.Systematic review registrationRegistration ID: CRD42023438208 https://www.crd.york.ac.uk/PROSPERO/#recordDetails.

Machine learning identification of cuproptosis and necroptosis-associated molecular subtypes to aid in prognosis assessment and immunotherapy response prediction in low-grade glioma.

Both cuproptosis and necroptosis are typical cell death processes that serve essential regulatory roles in the onset and progression of malignancies, including low-grade glioma (LGG). Nonetheless, there remains a paucity of research on cuproptosis and necroptosis-related gene (CNRG) prognostic signature in patients with LGG. We acquired patient data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) and captured CNRGs from the well-recognized literature. Firstly, we comprehensively summarized the pan-cancer landscape of CNRGs from the perspective of expression traits, prognostic values, mutation profiles, and pathway regulation. Then, we devised a technique for predicting the clinical efficacy of immunotherapy for LGG patients. Non-negative matrix factorization (NMF) defined by CNRGs with prognostic values was performed to generate molecular subtypes (i.e., C1 and C2). C1 subtype is characterized by poor prognosis in terms of disease-specific survival (DSS), progression-free survival (PFS), and overall survival (OS), more patients with G3 and tumour recurrence, high abundance of immunocyte infiltration, high expression of immune checkpoints, and poor response to immunotherapy. LASSO-SVM-random Forest analysis was performed to aid in developing a novel and robust CNRG-based prognostic signature. LGG patients in the TCGA and GEO databases were categorized into the training and test cohorts, respectively. A five-gene signature, including SQSTM1, ZBP1, PLK1, CFLAR, and FADD, for predicting OS of LGG patients was constructed and its predictive reliability was confirmed in both training and test cohorts. In both the training and the test datasets (cohorts), higher risk scores were linked to a lower OS rate. The time-dependent ROC curve proved that the risk score had outstanding prediction efficiency for LGG patients in the training and test cohorts. Univariate and multivariate Cox regression analyses showed the CNRG-based prognostic signature independently functioned as a risk factor for OS in LGG patients. Furthermore, we developed a highly reliable nomogram to facilitate the clinical practice of the CNRG-based prognostic signature (AUC > 0.9). Collectively, our results gave a promising understanding of cuproptosis and necroptosis in LGG, as well as a tailored prediction tool for prognosis and immunotherapeutic responses in patients.

Impact of Yiqi Huoxue Decoction on the Relationship between Remodeling of Cardiac Nerves and Macrophages after Myocardial Infarction in Rats.

Sympathetic nerve remodeling after myocardial infarction (MI) has an indispensable role in cardiac remodeling. Numerous works have shown that sympathetic nerve remodeling can be delayed by inhibition of inflammatory response. Earlier studies have shown improvement in ventricular remodeling and inhibited chronic stage neural remodeling by Yiqi Huoxue decoction (YQHX). Therefore, the current study looked at the inhibitory effect of YQHX prescription on proinflammatory mediators and macrophages and the effect on neural remodeling at 3 and 7 days after MI. YQHX inhibited the expression of Toll-like receptor 4 (TLR4) and nuclear factor kappa B (NF-κB) proteins and macrophage infiltration within 7 days after myocardial infarction. YQHX could decrease Th-positive nerve fiber density in the area around infarction and reduce the expression of growth-associated protein 43 (GAP43), nerve growth factor (NGF), and tyrosine hydroxylase (TH) proteins, which was associated with the remodeling of sympathetic nerves. Thus, the nerve remodeling inhibition after MI due to YQHX may be through its anti-inflammatory action. These data provide direct evidence for the potential application of traditional Chinese medicine (TCM) in the remodeling of sympathetic nerves after MI.

Wintertime vertical distribution of black carbon and single scattering albedo in a semi-arid region derived from tethered balloon observations.

The vertical distribution of atmospheric aerosols plays an essential role in aerosol-radiation and aerosol-cloud interactions. Because of strong light absorption, the radiative effects of black carbon (BC) are highly sensitive to its vertical distribution; the lack of high-resolution observations is the reason for their poor quantification. We used a tethered balloon platform to acquire high-resolution vertical profiles of BC, particle number concentration, and meteorological parameters in the semi-arid region of Northwest China in December 2018. A total of 112 BC profiles were classified into four vertical distribution categories, which were determined by local emissions, regional transport, vertical mixing due to the ABL evolution, and topography. BC profiles with peaks near or above the atmospheric boundary layer (ABL) accounted for 57% of the profiles. Vertical single scattering albedo (SSA) profiles were subsequently calculated using the profiles of BC and particle size distribution. The vertical SSA distribution is generally modulated by BC profiles. The diurnal variations of the BC and SSA profiles were summarized using a boundary-layer normalization method. In the ABL, BC decreased and SSA increased with increasing height at 02:00, 08:00, and 20:00, while both BC and SSA exhibited a uniform distribution at 14:00. The SSA decreased above the ABL at 14:00, which might have had a profound impact on ABL development. These results provide a better understanding of the vertical BC and SSA distributions, which can also be used to reduce uncertainties in estimating the BC radiative effects.

High-Dimensional Precision Medicine From Patient-Derived Xenografts.

The complexity of human cancer often results in significant heterogeneity in response to treatment. Precision medicine offers the potential to improve patient outcomes by leveraging this heterogeneity. Individualized treatment rules (ITRs) formalize precision medicine as maps from the patient covariate space into the space of allowable treatments. The optimal ITR is that which maximizes the mean of a clinical outcome in a population of interest. Patient-derived xenograft (PDX) studies permit the evaluation of multiple treatments within a single tumor, and thus are ideally suited for estimating optimal ITRs. PDX data are characterized by correlated outcomes, a high-dimensional feature space, and a large number of treatments. Here we explore machine learning methods for estimating optimal ITRs from PDX data. We analyze data from a large PDX study to identify biomarkers that are informative for developing personalized treatment recommendations in multiple cancers. We estimate optimal ITRs using regression-based (Q-learning) and direct-search methods (outcome weighted learning). Finally, we implement a superlearner approach to combine multiple estimated ITRs and show that the resulting ITR performs better than any of the input ITRs, mitigating uncertainty regarding user choice. Our results indicate that PDX data are a valuable resource for developing individualized treatment strategies in oncology. Supplementary materials for this article are available online.

Sharp bounds on the relative treatment effect for ordinal outcomes.

For ordinal outcomes, the average treatment effect is often ill-defined and hard to interpret. Echoing Agresti and Kateri, we argue that the relative treatment effect can be a useful measure, especially for ordinal outcomes, which is defined as γ=pr{Yi(1)>Yi(0)}-pr{Yi(1)

Habitat orientation alters the outcome of interspecific competition: A microcosm study with zooplankton grazers.

Habitat orientation has recently been demonstrated to affect the foraging behavior, growth, and production of plankton grazers. Because the orientation effect may vary with species, we hypothesize that habitat orientation may alter interspecific interactions between animal species. We experimentally investigated how habitat orientation (placing cuboid chambers in three orientations with long, medium, and small side as the chamber height) affected the interaction between two common cladoceran species, Daphnia magna and Moina micrura, which competitively exploited green algae of Chlorella pyrenoidosa at two volume scales (64 and 512 ml). Results show that chamber orientation and volume additively affected the behavior and species performance of the grazers. Specifically, both grazer species generally decreased their average swimming velocity, grazing rate (on algal cells), body size, and survival and reproduction rates with increasing chamber height for both chamber volumes and with decreasing chamber volume regardless of chamber orientation. Nevertheless, the decrease magnitude was greater for M. micrura with increasing chamber height but was greater for D. magna with decreasing chamber volume. Correspondingly, when cocultured, the density ratio of D. magna to M. micrura increased with increasing chamber height but decreased with decreasing chamber volume. At the end of the experiment, none of D. magna individuals survived in the small and short (large-based) chambers, and few M. micrura individuals survived in large and tall (small-based) chambers. These results indicate that both habitat orientation and size affect the outcome of interspecific competition between grazer species. We suggest that variation in habitat orientation may improve community coexistence and species diversity in nature.